openapi: 3.1.0
info:
title: OpenAI API
description: The OpenAI REST API. Please see https://platform.openai.com/docs/api-reference for more details.
version: 2.3.0
termsOfService: https://openai.com/policies/terms-of-use
contact:
name: OpenAI Support
url: https://help.openai.com/
license:
name: MIT
url: https://github.com/openai/openai-openapi/blob/master/LICENSE
servers:
- url: https://api.openai.com/v1
security:
- ApiKeyAuth: []
tags:
- name: Assistants
description: Build Assistants that can call models and use tools.
- name: Audio
description: Turn audio into text or text into audio.
- name: Chat
description: Given a list of messages comprising a conversation, the model will return a response.
- name: Conversations
description: Manage conversations and conversation items.
- name: Completions
description: >-
Given a prompt, the model will return one or more predicted completions, and can also return the
probabilities of alternative tokens at each position.
- name: Embeddings
description: >-
Get a vector representation of a given input that can be easily consumed by machine learning models and
algorithms.
- name: Evals
description: Manage and run evals in the OpenAI platform.
- name: Fine-tuning
description: Manage fine-tuning jobs to tailor a model to your specific training data.
- name: Graders
description: Manage and run graders in the OpenAI platform.
- name: Batch
description: Create large batches of API requests to run asynchronously.
- name: Files
description: Files are used to upload documents that can be used with features like Assistants and Fine-tuning.
- name: Uploads
description: Use Uploads to upload large files in multiple parts.
- name: Images
description: Given a prompt and/or an input image, the model will generate a new image.
- name: Models
description: List and describe the various models available in the API.
- name: Moderations
description: Given text and/or image inputs, classifies if those inputs are potentially harmful.
- name: Audit Logs
description: List user actions and configuration changes within this organization.
paths:
/assistants:
get:
operationId: listAssistants
tags:
- Assistants
summary: List assistants
parameters:
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: order
in: query
description: >
Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
descending order.
schema:
type: string
default: desc
enum:
- asc
- desc
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
schema:
type: string
- name: before
in: query
description: >
A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, starting with obj_foo, your
subsequent call can include before=obj_foo in order to fetch the previous page of the list.
schema:
type: string
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListAssistantsResponse'
x-oaiMeta:
name: List assistants
group: assistants
beta: true
returns: A list of [assistant](https://platform.openai.com/docs/api-reference/assistants/object) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "asst_abc123",
"object": "assistant",
"created_at": 1698982736,
"name": "Coding Tutor",
"description": null,
"model": "gpt-4o",
"instructions": "You are a helpful assistant designed to make me better at coding!",
"tools": [],
"tool_resources": {},
"metadata": {},
"top_p": 1.0,
"temperature": 1.0,
"response_format": "auto"
},
{
"id": "asst_abc456",
"object": "assistant",
"created_at": 1698982718,
"name": "My Assistant",
"description": null,
"model": "gpt-4o",
"instructions": "You are a helpful assistant designed to make me better at coding!",
"tools": [],
"tool_resources": {},
"metadata": {},
"top_p": 1.0,
"temperature": 1.0,
"response_format": "auto"
},
{
"id": "asst_abc789",
"object": "assistant",
"created_at": 1698982643,
"name": null,
"description": null,
"model": "gpt-4o",
"instructions": null,
"tools": [],
"tool_resources": {},
"metadata": {},
"top_p": 1.0,
"temperature": 1.0,
"response_format": "auto"
}
],
"first_id": "asst_abc123",
"last_id": "asst_abc789",
"has_more": false
}
request:
curl: |
curl "https://api.openai.com/v1/assistants?order=desc&limit=20" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.beta.assistants.list()
page = page.data[0]
print(page.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const assistant of client.beta.assistants.list()) {
console.log(assistant.id);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.Beta.Assistants.List(context.TODO(), openai.BetaAssistantListParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.assistants.AssistantListPage;
import com.openai.models.beta.assistants.AssistantListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
AssistantListPage page = client.beta().assistants().list();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.beta.assistants.list
puts(page)
description: Returns a list of assistants.
post:
operationId: createAssistant
tags:
- Assistants
summary: Create assistant
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateAssistantRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/AssistantObject'
x-oaiMeta:
name: Create assistant
group: assistants
beta: true
returns: An [assistant](https://platform.openai.com/docs/api-reference/assistants/object) object.
examples:
- title: Code Interpreter
request:
curl: |
curl "https://api.openai.com/v1/assistants" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"instructions": "You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
"name": "Math Tutor",
"tools": [{"type": "code_interpreter"}],
"model": "gpt-4o"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
assistant = client.beta.assistants.create(
model="gpt-4o",
)
print(assistant.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const assistant = await client.beta.assistants.create({ model: 'gpt-4o' });
console.log(assistant.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/shared"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
assistant, err := client.Beta.Assistants.New(context.TODO(), openai.BetaAssistantNewParams{
Model: shared.ChatModelGPT5,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", assistant.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.ChatModel;
import com.openai.models.beta.assistants.Assistant;
import com.openai.models.beta.assistants.AssistantCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
AssistantCreateParams params = AssistantCreateParams.builder()
.model(ChatModel.GPT_5)
.build();
Assistant assistant = client.beta().assistants().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
assistant = openai.beta.assistants.create(model: :"gpt-5")
puts(assistant)
response: |
{
"id": "asst_abc123",
"object": "assistant",
"created_at": 1698984975,
"name": "Math Tutor",
"description": null,
"model": "gpt-4o",
"instructions": "You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
"tools": [
{
"type": "code_interpreter"
}
],
"metadata": {},
"top_p": 1.0,
"temperature": 1.0,
"response_format": "auto"
}
- title: Files
request:
curl: |
curl https://api.openai.com/v1/assistants \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies.",
"tools": [{"type": "file_search"}],
"tool_resources": {"file_search": {"vector_store_ids": ["vs_123"]}},
"model": "gpt-4o"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
assistant = client.beta.assistants.create(
model="gpt-4o",
)
print(assistant.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const assistant = await client.beta.assistants.create({ model: 'gpt-4o' });
console.log(assistant.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/shared"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
assistant, err := client.Beta.Assistants.New(context.TODO(), openai.BetaAssistantNewParams{
Model: shared.ChatModelGPT5,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", assistant.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.ChatModel;
import com.openai.models.beta.assistants.Assistant;
import com.openai.models.beta.assistants.AssistantCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
AssistantCreateParams params = AssistantCreateParams.builder()
.model(ChatModel.GPT_5)
.build();
Assistant assistant = client.beta().assistants().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
assistant = openai.beta.assistants.create(model: :"gpt-5")
puts(assistant)
response: |
{
"id": "asst_abc123",
"object": "assistant",
"created_at": 1699009403,
"name": "HR Helper",
"description": null,
"model": "gpt-4o",
"instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies.",
"tools": [
{
"type": "file_search"
}
],
"tool_resources": {
"file_search": {
"vector_store_ids": ["vs_123"]
}
},
"metadata": {},
"top_p": 1.0,
"temperature": 1.0,
"response_format": "auto"
}
description: Create an assistant with a model and instructions.
/assistants/{assistant_id}:
get:
operationId: getAssistant
tags:
- Assistants
summary: Retrieve assistant
parameters:
- in: path
name: assistant_id
required: true
schema:
type: string
description: The ID of the assistant to retrieve.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/AssistantObject'
x-oaiMeta:
name: Retrieve assistant
group: assistants
beta: true
returns: >-
The [assistant](https://platform.openai.com/docs/api-reference/assistants/object) object matching
the specified ID.
examples:
response: |
{
"id": "asst_abc123",
"object": "assistant",
"created_at": 1699009709,
"name": "HR Helper",
"description": null,
"model": "gpt-4o",
"instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies.",
"tools": [
{
"type": "file_search"
}
],
"metadata": {},
"top_p": 1.0,
"temperature": 1.0,
"response_format": "auto"
}
request:
curl: |
curl https://api.openai.com/v1/assistants/asst_abc123 \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
assistant = client.beta.assistants.retrieve(
"assistant_id",
)
print(assistant.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const assistant = await client.beta.assistants.retrieve('assistant_id');
console.log(assistant.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
assistant, err := client.Beta.Assistants.Get(context.TODO(), "assistant_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", assistant.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.assistants.Assistant;
import com.openai.models.beta.assistants.AssistantRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Assistant assistant = client.beta().assistants().retrieve("assistant_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
assistant = openai.beta.assistants.retrieve("assistant_id")
puts(assistant)
description: Retrieves an assistant.
post:
operationId: modifyAssistant
tags:
- Assistants
summary: Modify assistant
parameters:
- in: path
name: assistant_id
required: true
schema:
type: string
description: The ID of the assistant to modify.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ModifyAssistantRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/AssistantObject'
x-oaiMeta:
name: Modify assistant
group: assistants
beta: true
returns: The modified [assistant](https://platform.openai.com/docs/api-reference/assistants/object) object.
examples:
response: |
{
"id": "asst_123",
"object": "assistant",
"created_at": 1699009709,
"name": "HR Helper",
"description": null,
"model": "gpt-4o",
"instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies. Always response with info from either of the files.",
"tools": [
{
"type": "file_search"
}
],
"tool_resources": {
"file_search": {
"vector_store_ids": []
}
},
"metadata": {},
"top_p": 1.0,
"temperature": 1.0,
"response_format": "auto"
}
request:
curl: |
curl https://api.openai.com/v1/assistants/asst_abc123 \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies. Always response with info from either of the files.",
"tools": [{"type": "file_search"}],
"model": "gpt-4o"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
assistant = client.beta.assistants.update(
assistant_id="assistant_id",
)
print(assistant.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const assistant = await client.beta.assistants.update('assistant_id');
console.log(assistant.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
assistant, err := client.Beta.Assistants.Update(
context.TODO(),
"assistant_id",
openai.BetaAssistantUpdateParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", assistant.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.assistants.Assistant;
import com.openai.models.beta.assistants.AssistantUpdateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Assistant assistant = client.beta().assistants().update("assistant_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
assistant = openai.beta.assistants.update("assistant_id")
puts(assistant)
description: Modifies an assistant.
delete:
operationId: deleteAssistant
tags:
- Assistants
summary: Delete assistant
parameters:
- in: path
name: assistant_id
required: true
schema:
type: string
description: The ID of the assistant to delete.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/DeleteAssistantResponse'
x-oaiMeta:
name: Delete assistant
group: assistants
beta: true
returns: Deletion status
examples:
response: |
{
"id": "asst_abc123",
"object": "assistant.deleted",
"deleted": true
}
request:
curl: |
curl https://api.openai.com/v1/assistants/asst_abc123 \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2" \
-X DELETE
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
assistant_deleted = client.beta.assistants.delete(
"assistant_id",
)
print(assistant_deleted.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const assistantDeleted = await client.beta.assistants.delete('assistant_id');
console.log(assistantDeleted.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
assistantDeleted, err := client.Beta.Assistants.Delete(context.TODO(), "assistant_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", assistantDeleted.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.assistants.AssistantDeleteParams;
import com.openai.models.beta.assistants.AssistantDeleted;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
AssistantDeleted assistantDeleted = client.beta().assistants().delete("assistant_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
assistant_deleted = openai.beta.assistants.delete("assistant_id")
puts(assistant_deleted)
description: Delete an assistant.
/audio/speech:
post:
operationId: createSpeech
tags:
- Audio
summary: Create speech
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateSpeechRequest'
responses:
'200':
description: OK
headers:
Transfer-Encoding:
schema:
type: string
description: chunked
content:
application/octet-stream:
schema:
type: string
format: binary
text/event-stream:
schema:
$ref: '#/components/schemas/CreateSpeechResponseStreamEvent'
x-oaiMeta:
name: Create speech
group: audio
returns: >-
The audio file content or a [stream of audio
events](https://platform.openai.com/docs/api-reference/audio/speech-audio-delta-event).
examples:
- title: Default
request:
curl: |
curl https://api.openai.com/v1/audio/speech \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4o-mini-tts",
"input": "The quick brown fox jumped over the lazy dog.",
"voice": "alloy"
}' \
--output speech.mp3
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
speech = client.audio.speech.create(
input="input",
model="string",
voice="ash",
)
print(speech)
content = speech.read()
print(content)
javascript: |
import fs from "fs";
import path from "path";
import OpenAI from "openai";
const openai = new OpenAI();
const speechFile = path.resolve("./speech.mp3");
async function main() {
const mp3 = await openai.audio.speech.create({
model: "gpt-4o-mini-tts",
voice: "alloy",
input: "Today is a wonderful day to build something people love!",
});
console.log(speechFile);
const buffer = Buffer.from(await mp3.arrayBuffer());
await fs.promises.writeFile(speechFile, buffer);
}
main();
csharp: |
using System;
using System.IO;
using OpenAI.Audio;
AudioClient client = new(
model: "gpt-4o-mini-tts",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
BinaryData speech = client.GenerateSpeech(
text: "The quick brown fox jumped over the lazy dog.",
voice: GeneratedSpeechVoice.Alloy
);
using FileStream stream = File.OpenWrite("speech.mp3");
speech.ToStream().CopyTo(stream);
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const speech = await client.audio.speech.create({ input: 'input', model: 'string', voice:
'ash' });
console.log(speech);
const content = await speech.blob();
console.log(content);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
speech, err := client.Audio.Speech.New(context.TODO(), openai.AudioSpeechNewParams{
Input: "input",
Model: openai.SpeechModelTTS1,
Voice: openai.AudioSpeechNewParamsVoiceAlloy,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", speech)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.core.http.HttpResponse;
import com.openai.models.audio.speech.SpeechCreateParams;
import com.openai.models.audio.speech.SpeechModel;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
SpeechCreateParams params = SpeechCreateParams.builder()
.input("input")
.model(SpeechModel.TTS_1)
.voice(SpeechCreateParams.Voice.ALLOY)
.build();
HttpResponse speech = client.audio().speech().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
speech = openai.audio.speech.create(input: "input", model: :"tts-1", voice: :alloy)
puts(speech)
- title: SSE Stream Format
request:
curl: |
curl https://api.openai.com/v1/audio/speech \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4o-mini-tts",
"input": "The quick brown fox jumped over the lazy dog.",
"voice": "alloy",
"stream_format": "sse"
}'
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const speech = await client.audio.speech.create({ input: 'input', model: 'string', voice:
'ash' });
console.log(speech);
const content = await speech.blob();
console.log(content);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
speech = client.audio.speech.create(
input="input",
model="string",
voice="ash",
)
print(speech)
content = speech.read()
print(content)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
speech, err := client.Audio.Speech.New(context.TODO(), openai.AudioSpeechNewParams{
Input: "input",
Model: openai.SpeechModelTTS1,
Voice: openai.AudioSpeechNewParamsVoiceAlloy,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", speech)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.core.http.HttpResponse;
import com.openai.models.audio.speech.SpeechCreateParams;
import com.openai.models.audio.speech.SpeechModel;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
SpeechCreateParams params = SpeechCreateParams.builder()
.input("input")
.model(SpeechModel.TTS_1)
.voice(SpeechCreateParams.Voice.ALLOY)
.build();
HttpResponse speech = client.audio().speech().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
speech = openai.audio.speech.create(input: "input", model: :"tts-1", voice: :alloy)
puts(speech)
description: Generates audio from the input text.
/audio/transcriptions:
post:
operationId: createTranscription
tags:
- Audio
summary: Create transcription
requestBody:
required: true
content:
multipart/form-data:
schema:
$ref: '#/components/schemas/CreateTranscriptionRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
anyOf:
- $ref: '#/components/schemas/CreateTranscriptionResponseJson'
- $ref: '#/components/schemas/CreateTranscriptionResponseVerboseJson'
x-stainless-skip:
- go
text/event-stream:
schema:
$ref: '#/components/schemas/CreateTranscriptionResponseStreamEvent'
x-oaiMeta:
name: Create transcription
group: audio
returns: >-
The [transcription object](https://platform.openai.com/docs/api-reference/audio/json-object), a
[verbose transcription
object](https://platform.openai.com/docs/api-reference/audio/verbose-json-object) or a [stream of
transcript
events](https://platform.openai.com/docs/api-reference/audio/transcript-text-delta-event).
examples:
- title: Default
request:
curl: |
curl https://api.openai.com/v1/audio/transcriptions \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: multipart/form-data" \
-F file="@/path/to/file/audio.mp3" \
-F model="gpt-4o-transcribe"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
transcription = client.audio.transcriptions.create(
file=b"raw file contents",
model="gpt-4o-transcribe",
)
print(transcription)
javascript: |
import fs from "fs";
import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const transcription = await openai.audio.transcriptions.create({
file: fs.createReadStream("audio.mp3"),
model: "gpt-4o-transcribe",
});
console.log(transcription.text);
}
main();
csharp: |
using System;
using OpenAI.Audio;
string audioFilePath = "audio.mp3";
AudioClient client = new(
model: "gpt-4o-transcribe",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
AudioTranscription transcription = client.TranscribeAudio(audioFilePath);
Console.WriteLine($"{transcription.Text}");
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const transcription = await client.audio.transcriptions.create({
file: fs.createReadStream('speech.mp3'),
model: 'gpt-4o-transcribe',
});
console.log(transcription);
go: |
package main
import (
"bytes"
"context"
"fmt"
"io"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{
File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
Model: openai.AudioModelWhisper1,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", transcription)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.audio.AudioModel;
import com.openai.models.audio.transcriptions.TranscriptionCreateParams;
import com.openai.models.audio.transcriptions.TranscriptionCreateResponse;
import java.io.ByteArrayInputStream;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
TranscriptionCreateParams params = TranscriptionCreateParams.builder()
.file(ByteArrayInputStream("some content".getBytes()))
.model(AudioModel.WHISPER_1)
.build();
TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
transcription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model:
:"whisper-1")
puts(transcription)
response: |
{
"text": "Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that.",
"usage": {
"type": "tokens",
"input_tokens": 14,
"input_token_details": {
"text_tokens": 0,
"audio_tokens": 14
},
"output_tokens": 45,
"total_tokens": 59
}
}
- title: Streaming
request:
curl: |
curl https://api.openai.com/v1/audio/transcriptions \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: multipart/form-data" \
-F file="@/path/to/file/audio.mp3" \
-F model="gpt-4o-mini-transcribe" \
-F stream=true
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
transcription = client.audio.transcriptions.create(
file=b"raw file contents",
model="gpt-4o-transcribe",
)
print(transcription)
javascript: |
import fs from "fs";
import OpenAI from "openai";
const openai = new OpenAI();
const stream = await openai.audio.transcriptions.create({
file: fs.createReadStream("audio.mp3"),
model: "gpt-4o-mini-transcribe",
stream: true,
});
for await (const event of stream) {
console.log(event);
}
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const transcription = await client.audio.transcriptions.create({
file: fs.createReadStream('speech.mp3'),
model: 'gpt-4o-transcribe',
});
console.log(transcription);
go: |
package main
import (
"bytes"
"context"
"fmt"
"io"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{
File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
Model: openai.AudioModelWhisper1,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", transcription)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.audio.AudioModel;
import com.openai.models.audio.transcriptions.TranscriptionCreateParams;
import com.openai.models.audio.transcriptions.TranscriptionCreateResponse;
import java.io.ByteArrayInputStream;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
TranscriptionCreateParams params = TranscriptionCreateParams.builder()
.file(ByteArrayInputStream("some content".getBytes()))
.model(AudioModel.WHISPER_1)
.build();
TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
transcription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model:
:"whisper-1")
puts(transcription)
response: >
data:
{"type":"transcript.text.delta","delta":"I","logprobs":[{"token":"I","logprob":-0.00007588794,"bytes":[73]}]}
data: {"type":"transcript.text.delta","delta":" see","logprobs":[{"token":"
see","logprob":-3.1281633e-7,"bytes":[32,115,101,101]}]}
data: {"type":"transcript.text.delta","delta":" skies","logprobs":[{"token":"
skies","logprob":-2.3392786e-6,"bytes":[32,115,107,105,101,115]}]}
data: {"type":"transcript.text.delta","delta":" of","logprobs":[{"token":"
of","logprob":-3.1281633e-7,"bytes":[32,111,102]}]}
data: {"type":"transcript.text.delta","delta":" blue","logprobs":[{"token":"
blue","logprob":-1.0280384e-6,"bytes":[32,98,108,117,101]}]}
data: {"type":"transcript.text.delta","delta":" and","logprobs":[{"token":"
and","logprob":-0.0005108566,"bytes":[32,97,110,100]}]}
data: {"type":"transcript.text.delta","delta":" clouds","logprobs":[{"token":"
clouds","logprob":-1.9361265e-7,"bytes":[32,99,108,111,117,100,115]}]}
data: {"type":"transcript.text.delta","delta":" of","logprobs":[{"token":"
of","logprob":-1.9361265e-7,"bytes":[32,111,102]}]}
data: {"type":"transcript.text.delta","delta":" white","logprobs":[{"token":"
white","logprob":-7.89631e-7,"bytes":[32,119,104,105,116,101]}]}
data:
{"type":"transcript.text.delta","delta":",","logprobs":[{"token":",","logprob":-0.0014890312,"bytes":[44]}]}
data: {"type":"transcript.text.delta","delta":" the","logprobs":[{"token":"
the","logprob":-0.0110956915,"bytes":[32,116,104,101]}]}
data: {"type":"transcript.text.delta","delta":" bright","logprobs":[{"token":"
bright","logprob":0.0,"bytes":[32,98,114,105,103,104,116]}]}
data: {"type":"transcript.text.delta","delta":" blessed","logprobs":[{"token":"
blessed","logprob":-0.000045848617,"bytes":[32,98,108,101,115,115,101,100]}]}
data: {"type":"transcript.text.delta","delta":" days","logprobs":[{"token":"
days","logprob":-0.000010802739,"bytes":[32,100,97,121,115]}]}
data:
{"type":"transcript.text.delta","delta":",","logprobs":[{"token":",","logprob":-0.00001700133,"bytes":[44]}]}
data: {"type":"transcript.text.delta","delta":" the","logprobs":[{"token":"
the","logprob":-0.0000118755715,"bytes":[32,116,104,101]}]}
data: {"type":"transcript.text.delta","delta":" dark","logprobs":[{"token":"
dark","logprob":-5.5122365e-7,"bytes":[32,100,97,114,107]}]}
data: {"type":"transcript.text.delta","delta":" sacred","logprobs":[{"token":"
sacred","logprob":-5.4385737e-6,"bytes":[32,115,97,99,114,101,100]}]}
data: {"type":"transcript.text.delta","delta":" nights","logprobs":[{"token":"
nights","logprob":-4.00813e-6,"bytes":[32,110,105,103,104,116,115]}]}
data:
{"type":"transcript.text.delta","delta":",","logprobs":[{"token":",","logprob":-0.0036910512,"bytes":[44]}]}
data: {"type":"transcript.text.delta","delta":" and","logprobs":[{"token":"
and","logprob":-0.0031903093,"bytes":[32,97,110,100]}]}
data: {"type":"transcript.text.delta","delta":" I","logprobs":[{"token":"
I","logprob":-1.504853e-6,"bytes":[32,73]}]}
data: {"type":"transcript.text.delta","delta":" think","logprobs":[{"token":"
think","logprob":-4.3202e-7,"bytes":[32,116,104,105,110,107]}]}
data: {"type":"transcript.text.delta","delta":" to","logprobs":[{"token":"
to","logprob":-1.9361265e-7,"bytes":[32,116,111]}]}
data: {"type":"transcript.text.delta","delta":" myself","logprobs":[{"token":"
myself","logprob":-1.7432603e-6,"bytes":[32,109,121,115,101,108,102]}]}
data:
{"type":"transcript.text.delta","delta":",","logprobs":[{"token":",","logprob":-0.29254505,"bytes":[44]}]}
data: {"type":"transcript.text.delta","delta":" what","logprobs":[{"token":"
what","logprob":-0.016815351,"bytes":[32,119,104,97,116]}]}
data: {"type":"transcript.text.delta","delta":" a","logprobs":[{"token":"
a","logprob":-3.1281633e-7,"bytes":[32,97]}]}
data: {"type":"transcript.text.delta","delta":" wonderful","logprobs":[{"token":"
wonderful","logprob":-2.1008714e-6,"bytes":[32,119,111,110,100,101,114,102,117,108]}]}
data: {"type":"transcript.text.delta","delta":" world","logprobs":[{"token":"
world","logprob":-8.180258e-6,"bytes":[32,119,111,114,108,100]}]}
data:
{"type":"transcript.text.delta","delta":".","logprobs":[{"token":".","logprob":-0.014231676,"bytes":[46]}]}
data: {"type":"transcript.text.done","text":"I see skies of blue and clouds of white, the bright
blessed days, the dark sacred nights, and I think to myself, what a wonderful
world.","logprobs":[{"token":"I","logprob":-0.00007588794,"bytes":[73]},{"token":"
see","logprob":-3.1281633e-7,"bytes":[32,115,101,101]},{"token":"
skies","logprob":-2.3392786e-6,"bytes":[32,115,107,105,101,115]},{"token":"
of","logprob":-3.1281633e-7,"bytes":[32,111,102]},{"token":"
blue","logprob":-1.0280384e-6,"bytes":[32,98,108,117,101]},{"token":"
and","logprob":-0.0005108566,"bytes":[32,97,110,100]},{"token":"
clouds","logprob":-1.9361265e-7,"bytes":[32,99,108,111,117,100,115]},{"token":"
of","logprob":-1.9361265e-7,"bytes":[32,111,102]},{"token":"
white","logprob":-7.89631e-7,"bytes":[32,119,104,105,116,101]},{"token":",","logprob":-0.0014890312,"bytes":[44]},{"token":"
the","logprob":-0.0110956915,"bytes":[32,116,104,101]},{"token":"
bright","logprob":0.0,"bytes":[32,98,114,105,103,104,116]},{"token":"
blessed","logprob":-0.000045848617,"bytes":[32,98,108,101,115,115,101,100]},{"token":"
days","logprob":-0.000010802739,"bytes":[32,100,97,121,115]},{"token":",","logprob":-0.00001700133,"bytes":[44]},{"token":"
the","logprob":-0.0000118755715,"bytes":[32,116,104,101]},{"token":"
dark","logprob":-5.5122365e-7,"bytes":[32,100,97,114,107]},{"token":"
sacred","logprob":-5.4385737e-6,"bytes":[32,115,97,99,114,101,100]},{"token":"
nights","logprob":-4.00813e-6,"bytes":[32,110,105,103,104,116,115]},{"token":",","logprob":-0.0036910512,"bytes":[44]},{"token":"
and","logprob":-0.0031903093,"bytes":[32,97,110,100]},{"token":"
I","logprob":-1.504853e-6,"bytes":[32,73]},{"token":"
think","logprob":-4.3202e-7,"bytes":[32,116,104,105,110,107]},{"token":"
to","logprob":-1.9361265e-7,"bytes":[32,116,111]},{"token":"
myself","logprob":-1.7432603e-6,"bytes":[32,109,121,115,101,108,102]},{"token":",","logprob":-0.29254505,"bytes":[44]},{"token":"
what","logprob":-0.016815351,"bytes":[32,119,104,97,116]},{"token":"
a","logprob":-3.1281633e-7,"bytes":[32,97]},{"token":"
wonderful","logprob":-2.1008714e-6,"bytes":[32,119,111,110,100,101,114,102,117,108]},{"token":"
world","logprob":-8.180258e-6,"bytes":[32,119,111,114,108,100]},{"token":".","logprob":-0.014231676,"bytes":[46]}],"usage":{"input_tokens":14,"input_token_details":{"text_tokens":0,"audio_tokens":14},"output_tokens":45,"total_tokens":59}}
- title: Logprobs
request:
curl: |
curl https://api.openai.com/v1/audio/transcriptions \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: multipart/form-data" \
-F file="@/path/to/file/audio.mp3" \
-F "include[]=logprobs" \
-F model="gpt-4o-transcribe" \
-F response_format="json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
transcription = client.audio.transcriptions.create(
file=b"raw file contents",
model="gpt-4o-transcribe",
)
print(transcription)
javascript: |
import fs from "fs";
import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const transcription = await openai.audio.transcriptions.create({
file: fs.createReadStream("audio.mp3"),
model: "gpt-4o-transcribe",
response_format: "json",
include: ["logprobs"]
});
console.log(transcription);
}
main();
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const transcription = await client.audio.transcriptions.create({
file: fs.createReadStream('speech.mp3'),
model: 'gpt-4o-transcribe',
});
console.log(transcription);
go: |
package main
import (
"bytes"
"context"
"fmt"
"io"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{
File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
Model: openai.AudioModelWhisper1,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", transcription)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.audio.AudioModel;
import com.openai.models.audio.transcriptions.TranscriptionCreateParams;
import com.openai.models.audio.transcriptions.TranscriptionCreateResponse;
import java.io.ByteArrayInputStream;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
TranscriptionCreateParams params = TranscriptionCreateParams.builder()
.file(ByteArrayInputStream("some content".getBytes()))
.model(AudioModel.WHISPER_1)
.build();
TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
transcription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model:
:"whisper-1")
puts(transcription)
response: |
{
"text": "Hey, my knee is hurting and I want to see the doctor tomorrow ideally.",
"logprobs": [
{ "token": "Hey", "logprob": -1.0415299, "bytes": [72, 101, 121] },
{ "token": ",", "logprob": -9.805982e-5, "bytes": [44] },
{ "token": " my", "logprob": -0.00229799, "bytes": [32, 109, 121] },
{
"token": " knee",
"logprob": -4.7159858e-5,
"bytes": [32, 107, 110, 101, 101]
},
{ "token": " is", "logprob": -0.043909557, "bytes": [32, 105, 115] },
{
"token": " hurting",
"logprob": -1.1041146e-5,
"bytes": [32, 104, 117, 114, 116, 105, 110, 103]
},
{ "token": " and", "logprob": -0.011076359, "bytes": [32, 97, 110, 100] },
{ "token": " I", "logprob": -5.3193703e-6, "bytes": [32, 73] },
{
"token": " want",
"logprob": -0.0017156356,
"bytes": [32, 119, 97, 110, 116]
},
{ "token": " to", "logprob": -7.89631e-7, "bytes": [32, 116, 111] },
{ "token": " see", "logprob": -5.5122365e-7, "bytes": [32, 115, 101, 101] },
{ "token": " the", "logprob": -0.0040786397, "bytes": [32, 116, 104, 101] },
{
"token": " doctor",
"logprob": -2.3392786e-6,
"bytes": [32, 100, 111, 99, 116, 111, 114]
},
{
"token": " tomorrow",
"logprob": -7.89631e-7,
"bytes": [32, 116, 111, 109, 111, 114, 114, 111, 119]
},
{
"token": " ideally",
"logprob": -0.5800861,
"bytes": [32, 105, 100, 101, 97, 108, 108, 121]
},
{ "token": ".", "logprob": -0.00011093382, "bytes": [46] }
],
"usage": {
"type": "tokens",
"input_tokens": 14,
"input_token_details": {
"text_tokens": 0,
"audio_tokens": 14
},
"output_tokens": 45,
"total_tokens": 59
}
}
- title: Word timestamps
request:
curl: |
curl https://api.openai.com/v1/audio/transcriptions \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: multipart/form-data" \
-F file="@/path/to/file/audio.mp3" \
-F "timestamp_granularities[]=word" \
-F model="whisper-1" \
-F response_format="verbose_json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
transcription = client.audio.transcriptions.create(
file=b"raw file contents",
model="gpt-4o-transcribe",
)
print(transcription)
javascript: |
import fs from "fs";
import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const transcription = await openai.audio.transcriptions.create({
file: fs.createReadStream("audio.mp3"),
model: "whisper-1",
response_format: "verbose_json",
timestamp_granularities: ["word"]
});
console.log(transcription.text);
}
main();
csharp: |
using System;
using OpenAI.Audio;
string audioFilePath = "audio.mp3";
AudioClient client = new(
model: "whisper-1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
AudioTranscriptionOptions options = new()
{
ResponseFormat = AudioTranscriptionFormat.Verbose,
TimestampGranularities = AudioTimestampGranularities.Word,
};
AudioTranscription transcription = client.TranscribeAudio(audioFilePath, options);
Console.WriteLine($"{transcription.Text}");
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const transcription = await client.audio.transcriptions.create({
file: fs.createReadStream('speech.mp3'),
model: 'gpt-4o-transcribe',
});
console.log(transcription);
go: |
package main
import (
"bytes"
"context"
"fmt"
"io"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{
File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
Model: openai.AudioModelWhisper1,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", transcription)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.audio.AudioModel;
import com.openai.models.audio.transcriptions.TranscriptionCreateParams;
import com.openai.models.audio.transcriptions.TranscriptionCreateResponse;
import java.io.ByteArrayInputStream;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
TranscriptionCreateParams params = TranscriptionCreateParams.builder()
.file(ByteArrayInputStream("some content".getBytes()))
.model(AudioModel.WHISPER_1)
.build();
TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
transcription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model:
:"whisper-1")
puts(transcription)
response: |
{
"task": "transcribe",
"language": "english",
"duration": 8.470000267028809,
"text": "The beach was a popular spot on a hot summer day. People were swimming in the ocean, building sandcastles, and playing beach volleyball.",
"words": [
{
"word": "The",
"start": 0.0,
"end": 0.23999999463558197
},
...
{
"word": "volleyball",
"start": 7.400000095367432,
"end": 7.900000095367432
}
],
"usage": {
"type": "duration",
"seconds": 9
}
}
- title: Segment timestamps
request:
curl: |
curl https://api.openai.com/v1/audio/transcriptions \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: multipart/form-data" \
-F file="@/path/to/file/audio.mp3" \
-F "timestamp_granularities[]=segment" \
-F model="whisper-1" \
-F response_format="verbose_json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
transcription = client.audio.transcriptions.create(
file=b"raw file contents",
model="gpt-4o-transcribe",
)
print(transcription)
javascript: |
import fs from "fs";
import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const transcription = await openai.audio.transcriptions.create({
file: fs.createReadStream("audio.mp3"),
model: "whisper-1",
response_format: "verbose_json",
timestamp_granularities: ["segment"]
});
console.log(transcription.text);
}
main();
csharp: |
using System;
using OpenAI.Audio;
string audioFilePath = "audio.mp3";
AudioClient client = new(
model: "whisper-1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
AudioTranscriptionOptions options = new()
{
ResponseFormat = AudioTranscriptionFormat.Verbose,
TimestampGranularities = AudioTimestampGranularities.Segment,
};
AudioTranscription transcription = client.TranscribeAudio(audioFilePath, options);
Console.WriteLine($"{transcription.Text}");
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const transcription = await client.audio.transcriptions.create({
file: fs.createReadStream('speech.mp3'),
model: 'gpt-4o-transcribe',
});
console.log(transcription);
go: |
package main
import (
"bytes"
"context"
"fmt"
"io"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{
File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
Model: openai.AudioModelWhisper1,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", transcription)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.audio.AudioModel;
import com.openai.models.audio.transcriptions.TranscriptionCreateParams;
import com.openai.models.audio.transcriptions.TranscriptionCreateResponse;
import java.io.ByteArrayInputStream;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
TranscriptionCreateParams params = TranscriptionCreateParams.builder()
.file(ByteArrayInputStream("some content".getBytes()))
.model(AudioModel.WHISPER_1)
.build();
TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
transcription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model:
:"whisper-1")
puts(transcription)
response: |
{
"task": "transcribe",
"language": "english",
"duration": 8.470000267028809,
"text": "The beach was a popular spot on a hot summer day. People were swimming in the ocean, building sandcastles, and playing beach volleyball.",
"segments": [
{
"id": 0,
"seek": 0,
"start": 0.0,
"end": 3.319999933242798,
"text": " The beach was a popular spot on a hot summer day.",
"tokens": [
50364, 440, 7534, 390, 257, 3743, 4008, 322, 257, 2368, 4266, 786, 13, 50530
],
"temperature": 0.0,
"avg_logprob": -0.2860786020755768,
"compression_ratio": 1.2363636493682861,
"no_speech_prob": 0.00985979475080967
},
...
],
"usage": {
"type": "duration",
"seconds": 9
}
}
description: Transcribes audio into the input language.
/audio/translations:
post:
operationId: createTranslation
tags:
- Audio
summary: Create translation
requestBody:
required: true
content:
multipart/form-data:
schema:
$ref: '#/components/schemas/CreateTranslationRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
anyOf:
- $ref: '#/components/schemas/CreateTranslationResponseJson'
- $ref: '#/components/schemas/CreateTranslationResponseVerboseJson'
x-stainless-skip:
- go
x-oaiMeta:
name: Create translation
group: audio
returns: The translated text.
examples:
response: |
{
"text": "Hello, my name is Wolfgang and I come from Germany. Where are you heading today?"
}
request:
curl: |
curl https://api.openai.com/v1/audio/translations \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: multipart/form-data" \
-F file="@/path/to/file/german.m4a" \
-F model="whisper-1"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
translation = client.audio.translations.create(
file=b"raw file contents",
model="whisper-1",
)
print(translation)
javascript: |
import fs from "fs";
import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const translation = await openai.audio.translations.create({
file: fs.createReadStream("speech.mp3"),
model: "whisper-1",
});
console.log(translation.text);
}
main();
csharp: |
using System;
using OpenAI.Audio;
string audioFilePath = "audio.mp3";
AudioClient client = new(
model: "whisper-1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
AudioTranscription transcription = client.TranscribeAudio(audioFilePath);
Console.WriteLine($"{transcription.Text}");
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const translation = await client.audio.translations.create({
file: fs.createReadStream('speech.mp3'),
model: 'whisper-1',
});
console.log(translation);
go: |
package main
import (
"bytes"
"context"
"fmt"
"io"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
translation, err := client.Audio.Translations.New(context.TODO(), openai.AudioTranslationNewParams{
File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
Model: openai.AudioModelWhisper1,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", translation)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.audio.AudioModel;
import com.openai.models.audio.translations.TranslationCreateParams;
import com.openai.models.audio.translations.TranslationCreateResponse;
import java.io.ByteArrayInputStream;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
TranslationCreateParams params = TranslationCreateParams.builder()
.file(ByteArrayInputStream("some content".getBytes()))
.model(AudioModel.WHISPER_1)
.build();
TranslationCreateResponse translation = client.audio().translations().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
translation = openai.audio.translations.create(file: Pathname(__FILE__), model: :"whisper-1")
puts(translation)
description: Translates audio into English.
/batches:
post:
summary: Create batch
operationId: createBatch
tags:
- Batch
requestBody:
required: true
content:
application/json:
schema:
type: object
required:
- input_file_id
- endpoint
- completion_window
properties:
input_file_id:
type: string
description: >
The ID of an uploaded file that contains requests for the new batch.
See [upload file](https://platform.openai.com/docs/api-reference/files/create) for how to
upload a file.
Your input file must be formatted as a [JSONL
file](https://platform.openai.com/docs/api-reference/batch/request-input), and must be
uploaded with the purpose `batch`. The file can contain up to 50,000 requests, and can be
up to 200 MB in size.
endpoint:
type: string
enum:
- /v1/responses
- /v1/chat/completions
- /v1/embeddings
- /v1/completions
description: >-
The endpoint to be used for all requests in the batch. Currently `/v1/responses`,
`/v1/chat/completions`, `/v1/embeddings`, and `/v1/completions` are supported. Note that
`/v1/embeddings` batches are also restricted to a maximum of 50,000 embedding inputs
across all requests in the batch.
completion_window:
type: string
enum:
- 24h
description: >-
The time frame within which the batch should be processed. Currently only `24h` is
supported.
metadata:
$ref: '#/components/schemas/Metadata'
output_expires_after:
$ref: '#/components/schemas/BatchFileExpirationAfter'
responses:
'200':
description: Batch created successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/Batch'
x-oaiMeta:
name: Create batch
group: batch
returns: The created [Batch](https://platform.openai.com/docs/api-reference/batch/object) object.
examples:
response: |
{
"id": "batch_abc123",
"object": "batch",
"endpoint": "/v1/chat/completions",
"errors": null,
"input_file_id": "file-abc123",
"completion_window": "24h",
"status": "validating",
"output_file_id": null,
"error_file_id": null,
"created_at": 1711471533,
"in_progress_at": null,
"expires_at": null,
"finalizing_at": null,
"completed_at": null,
"failed_at": null,
"expired_at": null,
"cancelling_at": null,
"cancelled_at": null,
"request_counts": {
"total": 0,
"completed": 0,
"failed": 0
},
"metadata": {
"customer_id": "user_123456789",
"batch_description": "Nightly eval job",
}
}
request:
curl: |
curl https://api.openai.com/v1/batches \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input_file_id": "file-abc123",
"endpoint": "/v1/chat/completions",
"completion_window": "24h"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
batch = client.batches.create(
completion_window="24h",
endpoint="/v1/responses",
input_file_id="input_file_id",
)
print(batch.id)
node: |
import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const batch = await openai.batches.create({
input_file_id: "file-abc123",
endpoint: "/v1/chat/completions",
completion_window: "24h"
});
console.log(batch);
}
main();
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const batch = await client.batches.create({
completion_window: '24h',
endpoint: '/v1/responses',
input_file_id: 'input_file_id',
});
console.log(batch.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
batch, err := client.Batches.New(context.TODO(), openai.BatchNewParams{
CompletionWindow: openai.BatchNewParamsCompletionWindow24h,
Endpoint: openai.BatchNewParamsEndpointV1Responses,
InputFileID: "input_file_id",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", batch.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.batches.Batch;
import com.openai.models.batches.BatchCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
BatchCreateParams params = BatchCreateParams.builder()
.completionWindow(BatchCreateParams.CompletionWindow._24H)
.endpoint(BatchCreateParams.Endpoint.V1_RESPONSES)
.inputFileId("input_file_id")
.build();
Batch batch = client.batches().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
batch = openai.batches.create(
completion_window: :"24h",
endpoint: :"/v1/responses",
input_file_id: "input_file_id"
)
puts(batch)
description: Creates and executes a batch from an uploaded file of requests
get:
operationId: listBatches
tags:
- Batch
summary: List batch
parameters:
- in: query
name: after
required: false
schema:
type: string
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
responses:
'200':
description: Batch listed successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ListBatchesResponse'
x-oaiMeta:
name: List batch
group: batch
returns: A list of paginated [Batch](https://platform.openai.com/docs/api-reference/batch/object) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "batch_abc123",
"object": "batch",
"endpoint": "/v1/chat/completions",
"errors": null,
"input_file_id": "file-abc123",
"completion_window": "24h",
"status": "completed",
"output_file_id": "file-cvaTdG",
"error_file_id": "file-HOWS94",
"created_at": 1711471533,
"in_progress_at": 1711471538,
"expires_at": 1711557933,
"finalizing_at": 1711493133,
"completed_at": 1711493163,
"failed_at": null,
"expired_at": null,
"cancelling_at": null,
"cancelled_at": null,
"request_counts": {
"total": 100,
"completed": 95,
"failed": 5
},
"metadata": {
"customer_id": "user_123456789",
"batch_description": "Nightly job",
}
},
{ ... },
],
"first_id": "batch_abc123",
"last_id": "batch_abc456",
"has_more": true
}
request:
curl: |
curl https://api.openai.com/v1/batches?limit=2 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.batches.list()
page = page.data[0]
print(page.id)
node: |
import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const list = await openai.batches.list();
for await (const batch of list) {
console.log(batch);
}
}
main();
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const batch of client.batches.list()) {
console.log(batch.id);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.Batches.List(context.TODO(), openai.BatchListParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.batches.BatchListPage;
import com.openai.models.batches.BatchListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
BatchListPage page = client.batches().list();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.batches.list
puts(page)
description: List your organization's batches.
/batches/{batch_id}:
get:
operationId: retrieveBatch
tags:
- Batch
summary: Retrieve batch
parameters:
- in: path
name: batch_id
required: true
schema:
type: string
description: The ID of the batch to retrieve.
responses:
'200':
description: Batch retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/Batch'
x-oaiMeta:
name: Retrieve batch
group: batch
returns: >-
The [Batch](https://platform.openai.com/docs/api-reference/batch/object) object matching the
specified ID.
examples:
response: |
{
"id": "batch_abc123",
"object": "batch",
"endpoint": "/v1/completions",
"errors": null,
"input_file_id": "file-abc123",
"completion_window": "24h",
"status": "completed",
"output_file_id": "file-cvaTdG",
"error_file_id": "file-HOWS94",
"created_at": 1711471533,
"in_progress_at": 1711471538,
"expires_at": 1711557933,
"finalizing_at": 1711493133,
"completed_at": 1711493163,
"failed_at": null,
"expired_at": null,
"cancelling_at": null,
"cancelled_at": null,
"request_counts": {
"total": 100,
"completed": 95,
"failed": 5
},
"metadata": {
"customer_id": "user_123456789",
"batch_description": "Nightly eval job",
}
}
request:
curl: |
curl https://api.openai.com/v1/batches/batch_abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
batch = client.batches.retrieve(
"batch_id",
)
print(batch.id)
node: |
import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const batch = await openai.batches.retrieve("batch_abc123");
console.log(batch);
}
main();
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const batch = await client.batches.retrieve('batch_id');
console.log(batch.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
batch, err := client.Batches.Get(context.TODO(), "batch_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", batch.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.batches.Batch;
import com.openai.models.batches.BatchRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Batch batch = client.batches().retrieve("batch_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
batch = openai.batches.retrieve("batch_id")
puts(batch)
description: Retrieves a batch.
/batches/{batch_id}/cancel:
post:
operationId: cancelBatch
tags:
- Batch
summary: Cancel batch
parameters:
- in: path
name: batch_id
required: true
schema:
type: string
description: The ID of the batch to cancel.
responses:
'200':
description: Batch is cancelling. Returns the cancelling batch's details.
content:
application/json:
schema:
$ref: '#/components/schemas/Batch'
x-oaiMeta:
name: Cancel batch
group: batch
returns: >-
The [Batch](https://platform.openai.com/docs/api-reference/batch/object) object matching the
specified ID.
examples:
response: |
{
"id": "batch_abc123",
"object": "batch",
"endpoint": "/v1/chat/completions",
"errors": null,
"input_file_id": "file-abc123",
"completion_window": "24h",
"status": "cancelling",
"output_file_id": null,
"error_file_id": null,
"created_at": 1711471533,
"in_progress_at": 1711471538,
"expires_at": 1711557933,
"finalizing_at": null,
"completed_at": null,
"failed_at": null,
"expired_at": null,
"cancelling_at": 1711475133,
"cancelled_at": null,
"request_counts": {
"total": 100,
"completed": 23,
"failed": 1
},
"metadata": {
"customer_id": "user_123456789",
"batch_description": "Nightly eval job",
}
}
request:
curl: |
curl https://api.openai.com/v1/batches/batch_abc123/cancel \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-X POST
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
batch = client.batches.cancel(
"batch_id",
)
print(batch.id)
node: |
import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const batch = await openai.batches.cancel("batch_abc123");
console.log(batch);
}
main();
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const batch = await client.batches.cancel('batch_id');
console.log(batch.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
batch, err := client.Batches.Cancel(context.TODO(), "batch_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", batch.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.batches.Batch;
import com.openai.models.batches.BatchCancelParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Batch batch = client.batches().cancel("batch_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
batch = openai.batches.cancel("batch_id")
puts(batch)
description: >-
Cancels an in-progress batch. The batch will be in status `cancelling` for up to 10 minutes, before
changing to `cancelled`, where it will have partial results (if any) available in the output file.
/chat/completions:
get:
operationId: listChatCompletions
tags:
- Chat
summary: List Chat Completions
parameters:
- name: model
in: query
description: The model used to generate the Chat Completions.
required: false
schema:
type: string
- name: metadata
in: query
description: |
A list of metadata keys to filter the Chat Completions by. Example:
`metadata[key1]=value1&metadata[key2]=value2`
required: false
schema:
$ref: '#/components/schemas/Metadata'
- name: after
in: query
description: Identifier for the last chat completion from the previous pagination request.
required: false
schema:
type: string
- name: limit
in: query
description: Number of Chat Completions to retrieve.
required: false
schema:
type: integer
default: 20
- name: order
in: query
description: >-
Sort order for Chat Completions by timestamp. Use `asc` for ascending order or `desc` for
descending order. Defaults to `asc`.
required: false
schema:
type: string
enum:
- asc
- desc
default: asc
responses:
'200':
description: A list of Chat Completions
content:
application/json:
schema:
$ref: '#/components/schemas/ChatCompletionList'
x-oaiMeta:
name: List Chat Completions
group: chat
returns: >-
A list of [Chat Completions](https://platform.openai.com/docs/api-reference/chat/list-object)
matching the specified filters.
path: list
examples:
response: |
{
"object": "list",
"data": [
{
"object": "chat.completion",
"id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
"model": "gpt-4.1-2025-04-14",
"created": 1738960610,
"request_id": "req_ded8ab984ec4bf840f37566c1011c417",
"tool_choice": null,
"usage": {
"total_tokens": 31,
"completion_tokens": 18,
"prompt_tokens": 13
},
"seed": 4944116822809979520,
"top_p": 1.0,
"temperature": 1.0,
"presence_penalty": 0.0,
"frequency_penalty": 0.0,
"system_fingerprint": "fp_50cad350e4",
"input_user": null,
"service_tier": "default",
"tools": null,
"metadata": {},
"choices": [
{
"index": 0,
"message": {
"content": "Mind of circuits hum, \nLearning patterns in silence— \nFuture's quiet spark.",
"role": "assistant",
"tool_calls": null,
"function_call": null
},
"finish_reason": "stop",
"logprobs": null
}
],
"response_format": null
}
],
"first_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
"last_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/chat/completions \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.chat.completions.list()
page = page.data[0]
print(page.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const chatCompletion of client.chat.completions.list()) {
console.log(chatCompletion.id);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.Chat.Completions.List(context.TODO(), openai.ChatCompletionListParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.chat.completions.ChatCompletionListPage;
import com.openai.models.chat.completions.ChatCompletionListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ChatCompletionListPage page = client.chat().completions().list();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.chat.completions.list
puts(page)
description: |
List stored Chat Completions. Only Chat Completions that have been stored
with the `store` parameter set to `true` will be returned.
post:
operationId: createChatCompletion
tags:
- Chat
summary: Create chat completion
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateChatCompletionRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/CreateChatCompletionResponse'
text/event-stream:
schema:
$ref: '#/components/schemas/CreateChatCompletionStreamResponse'
x-oaiMeta:
name: Create chat completion
group: chat
returns: >
Returns a [chat completion](https://platform.openai.com/docs/api-reference/chat/object) object, or a
streamed sequence of [chat completion
chunk](https://platform.openai.com/docs/api-reference/chat/streaming) objects if the request is
streamed.
path: create
examples:
- title: Default
request:
curl: |
curl https://api.openai.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "VAR_chat_model_id",
"messages": [
{
"role": "developer",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "Hello!"
}
]
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
chat_completion = client.chat.completions.create(
messages=[{
"content": "string",
"role": "developer",
}],
model="gpt-4o",
)
print(chat_completion)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const chatCompletion = await client.chat.completions.create({
messages: [{ content: 'string', role: 'developer' }],
model: 'gpt-4o',
});
console.log(chatCompletion);
csharp: |
using System;
using System.Collections.Generic;
using OpenAI.Chat;
ChatClient client = new(
model: "gpt-4.1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
List<ChatMessage> messages =
[
new SystemChatMessage("You are a helpful assistant."),
new UserChatMessage("Hello!")
];
ChatCompletion completion = client.CompleteChat(messages);
Console.WriteLine(completion.Content[0].Text);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/shared"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{
OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{
Content: openai.ChatCompletionDeveloperMessageParamContentUnion{
OfString: openai.String("string"),
},
},
}},
Model: shared.ChatModelGPT5,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", chatCompletion)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.ChatModel;
import com.openai.models.chat.completions.ChatCompletion;
import com.openai.models.chat.completions.ChatCompletionCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()
.addDeveloperMessage("string")
.model(ChatModel.GPT_5)
.build();
ChatCompletion chatCompletion = client.chat().completions().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
chat_completion = openai.chat.completions.create(messages: [{content: "string", role:
:developer}], model: :"gpt-5")
puts(chat_completion)
response: |
{
"id": "chatcmpl-B9MBs8CjcvOU2jLn4n570S5qMJKcT",
"object": "chat.completion",
"created": 1741569952,
"model": "gpt-4.1-2025-04-14",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello! How can I assist you today?",
"refusal": null,
"annotations": []
},
"logprobs": null,
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 19,
"completion_tokens": 10,
"total_tokens": 29,
"prompt_tokens_details": {
"cached_tokens": 0,
"audio_tokens": 0
},
"completion_tokens_details": {
"reasoning_tokens": 0,
"audio_tokens": 0,
"accepted_prediction_tokens": 0,
"rejected_prediction_tokens": 0
}
},
"service_tier": "default"
}
- title: Image input
request:
curl: |
curl https://api.openai.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "gpt-4.1",
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "What is in this image?"
},
{
"type": "image_url",
"image_url": {
"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
}
}
]
}
],
"max_tokens": 300
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
chat_completion = client.chat.completions.create(
messages=[{
"content": "string",
"role": "developer",
}],
model="gpt-4o",
)
print(chat_completion)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const chatCompletion = await client.chat.completions.create({
messages: [{ content: 'string', role: 'developer' }],
model: 'gpt-4o',
});
console.log(chatCompletion);
csharp: |
using System;
using System.Collections.Generic;
using OpenAI.Chat;
ChatClient client = new(
model: "gpt-4.1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
List<ChatMessage> messages =
[
new UserChatMessage(
[
ChatMessageContentPart.CreateTextPart("What's in this image?"),
ChatMessageContentPart.CreateImagePart(new Uri("https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"))
])
];
ChatCompletion completion = client.CompleteChat(messages);
Console.WriteLine(completion.Content[0].Text);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/shared"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{
OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{
Content: openai.ChatCompletionDeveloperMessageParamContentUnion{
OfString: openai.String("string"),
},
},
}},
Model: shared.ChatModelGPT5,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", chatCompletion)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.ChatModel;
import com.openai.models.chat.completions.ChatCompletion;
import com.openai.models.chat.completions.ChatCompletionCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()
.addDeveloperMessage("string")
.model(ChatModel.GPT_5)
.build();
ChatCompletion chatCompletion = client.chat().completions().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
chat_completion = openai.chat.completions.create(messages: [{content: "string", role:
:developer}], model: :"gpt-5")
puts(chat_completion)
response: |
{
"id": "chatcmpl-B9MHDbslfkBeAs8l4bebGdFOJ6PeG",
"object": "chat.completion",
"created": 1741570283,
"model": "gpt-4.1-2025-04-14",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "The image shows a wooden boardwalk path running through a lush green field or meadow. The sky is bright blue with some scattered clouds, giving the scene a serene and peaceful atmosphere. Trees and shrubs are visible in the background.",
"refusal": null,
"annotations": []
},
"logprobs": null,
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 1117,
"completion_tokens": 46,
"total_tokens": 1163,
"prompt_tokens_details": {
"cached_tokens": 0,
"audio_tokens": 0
},
"completion_tokens_details": {
"reasoning_tokens": 0,
"audio_tokens": 0,
"accepted_prediction_tokens": 0,
"rejected_prediction_tokens": 0
}
},
"service_tier": "default"
}
- title: Streaming
request:
curl: |
curl https://api.openai.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "VAR_chat_model_id",
"messages": [
{
"role": "developer",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "Hello!"
}
],
"stream": true
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
chat_completion = client.chat.completions.create(
messages=[{
"content": "string",
"role": "developer",
}],
model="gpt-4o",
)
print(chat_completion)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const chatCompletion = await client.chat.completions.create({
messages: [{ content: 'string', role: 'developer' }],
model: 'gpt-4o',
});
console.log(chatCompletion);
csharp: >
using System;
using System.ClientModel;
using System.Collections.Generic;
using System.Threading.Tasks;
using OpenAI.Chat;
ChatClient client = new(
model: "gpt-4.1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
List<ChatMessage> messages =
[
new SystemChatMessage("You are a helpful assistant."),
new UserChatMessage("Hello!")
];
AsyncCollectionResult<StreamingChatCompletionUpdate> completionUpdates =
client.CompleteChatStreamingAsync(messages);
await foreach (StreamingChatCompletionUpdate completionUpdate in completionUpdates)
{
if (completionUpdate.ContentUpdate.Count > 0)
{
Console.Write(completionUpdate.ContentUpdate[0].Text);
}
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/shared"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{
OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{
Content: openai.ChatCompletionDeveloperMessageParamContentUnion{
OfString: openai.String("string"),
},
},
}},
Model: shared.ChatModelGPT5,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", chatCompletion)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.ChatModel;
import com.openai.models.chat.completions.ChatCompletion;
import com.openai.models.chat.completions.ChatCompletionCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()
.addDeveloperMessage("string")
.model(ChatModel.GPT_5)
.build();
ChatCompletion chatCompletion = client.chat().completions().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
chat_completion = openai.chat.completions.create(messages: [{content: "string", role:
:developer}], model: :"gpt-5")
puts(chat_completion)
response: >
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
"system_fingerprint": "fp_44709d6fcb",
"choices":[{"index":0,"delta":{"role":"assistant","content":""},"logprobs":null,"finish_reason":null}]}
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
"system_fingerprint": "fp_44709d6fcb",
"choices":[{"index":0,"delta":{"content":"Hello"},"logprobs":null,"finish_reason":null}]}
....
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
"system_fingerprint": "fp_44709d6fcb",
"choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}]}
- title: Functions
request:
curl: |
curl https://api.openai.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "gpt-4.1",
"messages": [
{
"role": "user",
"content": "What is the weather like in Boston today?"
}
],
"tools": [
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"]
}
},
"required": ["location"]
}
}
}
],
"tool_choice": "auto"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
chat_completion = client.chat.completions.create(
messages=[{
"content": "string",
"role": "developer",
}],
model="gpt-4o",
)
print(chat_completion)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const chatCompletion = await client.chat.completions.create({
messages: [{ content: 'string', role: 'developer' }],
model: 'gpt-4o',
});
console.log(chatCompletion);
csharp: |
using System;
using System.Collections.Generic;
using OpenAI.Chat;
ChatClient client = new(
model: "gpt-4.1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
ChatTool getCurrentWeatherTool = ChatTool.CreateFunctionTool(
functionName: "get_current_weather",
functionDescription: "Get the current weather in a given location",
functionParameters: BinaryData.FromString("""
{
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
},
"unit": {
"type": "string",
"enum": [ "celsius", "fahrenheit" ]
}
},
"required": [ "location" ]
}
""")
);
List<ChatMessage> messages =
[
new UserChatMessage("What's the weather like in Boston today?"),
];
ChatCompletionOptions options = new()
{
Tools =
{
getCurrentWeatherTool
},
ToolChoice = ChatToolChoice.CreateAutoChoice(),
};
ChatCompletion completion = client.CompleteChat(messages, options);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/shared"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{
OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{
Content: openai.ChatCompletionDeveloperMessageParamContentUnion{
OfString: openai.String("string"),
},
},
}},
Model: shared.ChatModelGPT5,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", chatCompletion)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.ChatModel;
import com.openai.models.chat.completions.ChatCompletion;
import com.openai.models.chat.completions.ChatCompletionCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()
.addDeveloperMessage("string")
.model(ChatModel.GPT_5)
.build();
ChatCompletion chatCompletion = client.chat().completions().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
chat_completion = openai.chat.completions.create(messages: [{content: "string", role:
:developer}], model: :"gpt-5")
puts(chat_completion)
response: |
{
"id": "chatcmpl-abc123",
"object": "chat.completion",
"created": 1699896916,
"model": "gpt-4o-mini",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": null,
"tool_calls": [
{
"id": "call_abc123",
"type": "function",
"function": {
"name": "get_current_weather",
"arguments": "{\n\"location\": \"Boston, MA\"\n}"
}
}
]
},
"logprobs": null,
"finish_reason": "tool_calls"
}
],
"usage": {
"prompt_tokens": 82,
"completion_tokens": 17,
"total_tokens": 99,
"completion_tokens_details": {
"reasoning_tokens": 0,
"accepted_prediction_tokens": 0,
"rejected_prediction_tokens": 0
}
}
}
- title: Logprobs
request:
curl: |
curl https://api.openai.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "VAR_chat_model_id",
"messages": [
{
"role": "user",
"content": "Hello!"
}
],
"logprobs": true,
"top_logprobs": 2
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
chat_completion = client.chat.completions.create(
messages=[{
"content": "string",
"role": "developer",
}],
model="gpt-4o",
)
print(chat_completion)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const chatCompletion = await client.chat.completions.create({
messages: [{ content: 'string', role: 'developer' }],
model: 'gpt-4o',
});
console.log(chatCompletion);
csharp: |
using System;
using System.Collections.Generic;
using OpenAI.Chat;
ChatClient client = new(
model: "gpt-4.1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
List<ChatMessage> messages =
[
new UserChatMessage("Hello!")
];
ChatCompletionOptions options = new()
{
IncludeLogProbabilities = true,
TopLogProbabilityCount = 2
};
ChatCompletion completion = client.CompleteChat(messages, options);
Console.WriteLine(completion.Content[0].Text);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/shared"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{
OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{
Content: openai.ChatCompletionDeveloperMessageParamContentUnion{
OfString: openai.String("string"),
},
},
}},
Model: shared.ChatModelGPT5,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", chatCompletion)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.ChatModel;
import com.openai.models.chat.completions.ChatCompletion;
import com.openai.models.chat.completions.ChatCompletionCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()
.addDeveloperMessage("string")
.model(ChatModel.GPT_5)
.build();
ChatCompletion chatCompletion = client.chat().completions().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
chat_completion = openai.chat.completions.create(messages: [{content: "string", role:
:developer}], model: :"gpt-5")
puts(chat_completion)
response: |
{
"id": "chatcmpl-123",
"object": "chat.completion",
"created": 1702685778,
"model": "gpt-4o-mini",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello! How can I assist you today?"
},
"logprobs": {
"content": [
{
"token": "Hello",
"logprob": -0.31725305,
"bytes": [72, 101, 108, 108, 111],
"top_logprobs": [
{
"token": "Hello",
"logprob": -0.31725305,
"bytes": [72, 101, 108, 108, 111]
},
{
"token": "Hi",
"logprob": -1.3190403,
"bytes": [72, 105]
}
]
},
{
"token": "!",
"logprob": -0.02380986,
"bytes": [
33
],
"top_logprobs": [
{
"token": "!",
"logprob": -0.02380986,
"bytes": [33]
},
{
"token": " there",
"logprob": -3.787621,
"bytes": [32, 116, 104, 101, 114, 101]
}
]
},
{
"token": " How",
"logprob": -0.000054669687,
"bytes": [32, 72, 111, 119],
"top_logprobs": [
{
"token": " How",
"logprob": -0.000054669687,
"bytes": [32, 72, 111, 119]
},
{
"token": "<|end|>",
"logprob": -10.953937,
"bytes": null
}
]
},
{
"token": " can",
"logprob": -0.015801601,
"bytes": [32, 99, 97, 110],
"top_logprobs": [
{
"token": " can",
"logprob": -0.015801601,
"bytes": [32, 99, 97, 110]
},
{
"token": " may",
"logprob": -4.161023,
"bytes": [32, 109, 97, 121]
}
]
},
{
"token": " I",
"logprob": -3.7697225e-6,
"bytes": [
32,
73
],
"top_logprobs": [
{
"token": " I",
"logprob": -3.7697225e-6,
"bytes": [32, 73]
},
{
"token": " assist",
"logprob": -13.596657,
"bytes": [32, 97, 115, 115, 105, 115, 116]
}
]
},
{
"token": " assist",
"logprob": -0.04571125,
"bytes": [32, 97, 115, 115, 105, 115, 116],
"top_logprobs": [
{
"token": " assist",
"logprob": -0.04571125,
"bytes": [32, 97, 115, 115, 105, 115, 116]
},
{
"token": " help",
"logprob": -3.1089056,
"bytes": [32, 104, 101, 108, 112]
}
]
},
{
"token": " you",
"logprob": -5.4385737e-6,
"bytes": [32, 121, 111, 117],
"top_logprobs": [
{
"token": " you",
"logprob": -5.4385737e-6,
"bytes": [32, 121, 111, 117]
},
{
"token": " today",
"logprob": -12.807695,
"bytes": [32, 116, 111, 100, 97, 121]
}
]
},
{
"token": " today",
"logprob": -0.0040071653,
"bytes": [32, 116, 111, 100, 97, 121],
"top_logprobs": [
{
"token": " today",
"logprob": -0.0040071653,
"bytes": [32, 116, 111, 100, 97, 121]
},
{
"token": "?",
"logprob": -5.5247097,
"bytes": [63]
}
]
},
{
"token": "?",
"logprob": -0.0008108172,
"bytes": [63],
"top_logprobs": [
{
"token": "?",
"logprob": -0.0008108172,
"bytes": [63]
},
{
"token": "?\n",
"logprob": -7.184561,
"bytes": [63, 10]
}
]
}
]
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 9,
"completion_tokens": 9,
"total_tokens": 18,
"completion_tokens_details": {
"reasoning_tokens": 0,
"accepted_prediction_tokens": 0,
"rejected_prediction_tokens": 0
}
},
"system_fingerprint": null
}
description: >
**Starting a new project?** We recommend trying
[Responses](https://platform.openai.com/docs/api-reference/responses)
to take advantage of the latest OpenAI platform features. Compare
[Chat Completions with
Responses](https://platform.openai.com/docs/guides/responses-vs-chat-completions?api-mode=responses).
---
Creates a model response for the given chat conversation. Learn more in the
[text generation](https://platform.openai.com/docs/guides/text-generation),
[vision](https://platform.openai.com/docs/guides/vision),
and [audio](https://platform.openai.com/docs/guides/audio) guides.
Parameter support can differ depending on the model used to generate the
response, particularly for newer reasoning models. Parameters that are only
supported for reasoning models are noted below. For the current state of
unsupported parameters in reasoning models,
[refer to the reasoning guide](https://platform.openai.com/docs/guides/reasoning).
/chat/completions/{completion_id}:
get:
operationId: getChatCompletion
tags:
- Chat
summary: Get chat completion
parameters:
- in: path
name: completion_id
required: true
schema:
type: string
description: The ID of the chat completion to retrieve.
responses:
'200':
description: A chat completion
content:
application/json:
schema:
$ref: '#/components/schemas/CreateChatCompletionResponse'
x-oaiMeta:
name: Get chat completion
group: chat
returns: >-
The [ChatCompletion](https://platform.openai.com/docs/api-reference/chat/object) object matching the
specified ID.
examples:
response: |
{
"object": "chat.completion",
"id": "chatcmpl-abc123",
"model": "gpt-4o-2024-08-06",
"created": 1738960610,
"request_id": "req_ded8ab984ec4bf840f37566c1011c417",
"tool_choice": null,
"usage": {
"total_tokens": 31,
"completion_tokens": 18,
"prompt_tokens": 13
},
"seed": 4944116822809979520,
"top_p": 1.0,
"temperature": 1.0,
"presence_penalty": 0.0,
"frequency_penalty": 0.0,
"system_fingerprint": "fp_50cad350e4",
"input_user": null,
"service_tier": "default",
"tools": null,
"metadata": {},
"choices": [
{
"index": 0,
"message": {
"content": "Mind of circuits hum, \nLearning patterns in silence— \nFuture's quiet spark.",
"role": "assistant",
"tool_calls": null,
"function_call": null
},
"finish_reason": "stop",
"logprobs": null
}
],
"response_format": null
}
request:
curl: |
curl https://api.openai.com/v1/chat/completions/chatcmpl-abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
chat_completion = client.chat.completions.retrieve(
"completion_id",
)
print(chat_completion.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const chatCompletion = await client.chat.completions.retrieve('completion_id');
console.log(chatCompletion.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
chatCompletion, err := client.Chat.Completions.Get(context.TODO(), "completion_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", chatCompletion.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.chat.completions.ChatCompletion;
import com.openai.models.chat.completions.ChatCompletionRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ChatCompletion chatCompletion = client.chat().completions().retrieve("completion_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
chat_completion = openai.chat.completions.retrieve("completion_id")
puts(chat_completion)
description: |
Get a stored chat completion. Only Chat Completions that have been created
with the `store` parameter set to `true` will be returned.
post:
operationId: updateChatCompletion
tags:
- Chat
summary: Update chat completion
parameters:
- in: path
name: completion_id
required: true
schema:
type: string
description: The ID of the chat completion to update.
requestBody:
required: true
content:
application/json:
schema:
type: object
required:
- metadata
properties:
metadata:
$ref: '#/components/schemas/Metadata'
responses:
'200':
description: A chat completion
content:
application/json:
schema:
$ref: '#/components/schemas/CreateChatCompletionResponse'
x-oaiMeta:
name: Update chat completion
group: chat
returns: >-
The [ChatCompletion](https://platform.openai.com/docs/api-reference/chat/object) object matching the
specified ID.
examples:
response: |
{
"object": "chat.completion",
"id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
"model": "gpt-4o-2024-08-06",
"created": 1738960610,
"request_id": "req_ded8ab984ec4bf840f37566c1011c417",
"tool_choice": null,
"usage": {
"total_tokens": 31,
"completion_tokens": 18,
"prompt_tokens": 13
},
"seed": 4944116822809979520,
"top_p": 1.0,
"temperature": 1.0,
"presence_penalty": 0.0,
"frequency_penalty": 0.0,
"system_fingerprint": "fp_50cad350e4",
"input_user": null,
"service_tier": "default",
"tools": null,
"metadata": {
"foo": "bar"
},
"choices": [
{
"index": 0,
"message": {
"content": "Mind of circuits hum, \nLearning patterns in silence— \nFuture's quiet spark.",
"role": "assistant",
"tool_calls": null,
"function_call": null
},
"finish_reason": "stop",
"logprobs": null
}
],
"response_format": null
}
request:
curl: |
curl -X POST https://api.openai.com/v1/chat/completions/chat_abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{"metadata": {"foo": "bar"}}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
chat_completion = client.chat.completions.update(
completion_id="completion_id",
metadata={
"foo": "string"
},
)
print(chat_completion.id)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const chatCompletion = await client.chat.completions.update('completion_id', { metadata: { foo:
'string' } });
console.log(chatCompletion.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/shared"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
chatCompletion, err := client.Chat.Completions.Update(
context.TODO(),
"completion_id",
openai.ChatCompletionUpdateParams{
Metadata: shared.Metadata{
"foo": "string",
},
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", chatCompletion.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.core.JsonValue;
import com.openai.models.chat.completions.ChatCompletion;
import com.openai.models.chat.completions.ChatCompletionUpdateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ChatCompletionUpdateParams params = ChatCompletionUpdateParams.builder()
.completionId("completion_id")
.metadata(ChatCompletionUpdateParams.Metadata.builder()
.putAdditionalProperty("foo", JsonValue.from("string"))
.build())
.build();
ChatCompletion chatCompletion = client.chat().completions().update(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
chat_completion = openai.chat.completions.update("completion_id", metadata: {foo: "string"})
puts(chat_completion)
description: |
Modify a stored chat completion. Only Chat Completions that have been
created with the `store` parameter set to `true` can be modified. Currently,
the only supported modification is to update the `metadata` field.
delete:
operationId: deleteChatCompletion
tags:
- Chat
summary: Delete chat completion
parameters:
- in: path
name: completion_id
required: true
schema:
type: string
description: The ID of the chat completion to delete.
responses:
'200':
description: The chat completion was deleted successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ChatCompletionDeleted'
x-oaiMeta:
name: Delete chat completion
group: chat
returns: A deletion confirmation object.
examples:
response: |
{
"object": "chat.completion.deleted",
"id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
"deleted": true
}
request:
curl: |
curl -X DELETE https://api.openai.com/v1/chat/completions/chat_abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
chat_completion_deleted = client.chat.completions.delete(
"completion_id",
)
print(chat_completion_deleted.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const chatCompletionDeleted = await client.chat.completions.delete('completion_id');
console.log(chatCompletionDeleted.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
chatCompletionDeleted, err := client.Chat.Completions.Delete(context.TODO(), "completion_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", chatCompletionDeleted.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.chat.completions.ChatCompletionDeleteParams;
import com.openai.models.chat.completions.ChatCompletionDeleted;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ChatCompletionDeleted chatCompletionDeleted = client.chat().completions().delete("completion_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
chat_completion_deleted = openai.chat.completions.delete("completion_id")
puts(chat_completion_deleted)
description: |
Delete a stored chat completion. Only Chat Completions that have been
created with the `store` parameter set to `true` can be deleted.
/chat/completions/{completion_id}/messages:
get:
operationId: getChatCompletionMessages
tags:
- Chat
summary: Get chat messages
parameters:
- in: path
name: completion_id
required: true
schema:
type: string
description: The ID of the chat completion to retrieve messages from.
- name: after
in: query
description: Identifier for the last message from the previous pagination request.
required: false
schema:
type: string
- name: limit
in: query
description: Number of messages to retrieve.
required: false
schema:
type: integer
default: 20
- name: order
in: query
description: >-
Sort order for messages by timestamp. Use `asc` for ascending order or `desc` for descending
order. Defaults to `asc`.
required: false
schema:
type: string
enum:
- asc
- desc
default: asc
responses:
'200':
description: A list of messages
content:
application/json:
schema:
$ref: '#/components/schemas/ChatCompletionMessageList'
x-oaiMeta:
name: Get chat messages
group: chat
returns: >-
A list of [messages](https://platform.openai.com/docs/api-reference/chat/message-list) for the
specified chat completion.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
"role": "user",
"content": "write a haiku about ai",
"name": null,
"content_parts": null
}
],
"first_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
"last_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/chat/completions/chat_abc123/messages \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.chat.completions.messages.list(
completion_id="completion_id",
)
page = page.data[0]
print(page)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const chatCompletionStoreMessage of
client.chat.completions.messages.list('completion_id')) {
console.log(chatCompletionStoreMessage);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.Chat.Completions.Messages.List(
context.TODO(),
"completion_id",
openai.ChatCompletionMessageListParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.chat.completions.messages.MessageListPage;
import com.openai.models.chat.completions.messages.MessageListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
MessageListPage page = client.chat().completions().messages().list("completion_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.chat.completions.messages.list("completion_id")
puts(page)
description: |
Get the messages in a stored chat completion. Only Chat Completions that
have been created with the `store` parameter set to `true` will be
returned.
/completions:
post:
operationId: createCompletion
tags:
- Completions
summary: Create completion
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateCompletionRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/CreateCompletionResponse'
x-oaiMeta:
name: Create completion
group: completions
returns: >
Returns a [completion](https://platform.openai.com/docs/api-reference/completions/object) object, or
a sequence of completion objects if the request is streamed.
legacy: true
examples:
- title: No streaming
request:
curl: |
curl https://api.openai.com/v1/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "VAR_completion_model_id",
"prompt": "Say this is a test",
"max_tokens": 7,
"temperature": 0
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
completion = client.completions.create(
model="string",
prompt="This is a test.",
)
print(completion)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const completion = await client.completions.create({ model: 'string', prompt: 'This is a
test.' });
console.log(completion);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
completion, err := client.Completions.New(context.TODO(), openai.CompletionNewParams{
Model: openai.CompletionNewParamsModelGPT3_5TurboInstruct,
Prompt: openai.CompletionNewParamsPromptUnion{
OfString: openai.String("This is a test."),
},
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", completion)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.completions.Completion;
import com.openai.models.completions.CompletionCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
CompletionCreateParams params = CompletionCreateParams.builder()
.model(CompletionCreateParams.Model.GPT_3_5_TURBO_INSTRUCT)
.prompt("This is a test.")
.build();
Completion completion = client.completions().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
completion = openai.completions.create(model: :"gpt-3.5-turbo-instruct", prompt: "This is a
test.")
puts(completion)
response: |
{
"id": "cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7",
"object": "text_completion",
"created": 1589478378,
"model": "VAR_completion_model_id",
"system_fingerprint": "fp_44709d6fcb",
"choices": [
{
"text": "\n\nThis is indeed a test",
"index": 0,
"logprobs": null,
"finish_reason": "length"
}
],
"usage": {
"prompt_tokens": 5,
"completion_tokens": 7,
"total_tokens": 12
}
}
- title: Streaming
request:
curl: |
curl https://api.openai.com/v1/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "VAR_completion_model_id",
"prompt": "Say this is a test",
"max_tokens": 7,
"temperature": 0,
"stream": true
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
completion = client.completions.create(
model="string",
prompt="This is a test.",
)
print(completion)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const completion = await client.completions.create({ model: 'string', prompt: 'This is a
test.' });
console.log(completion);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
completion, err := client.Completions.New(context.TODO(), openai.CompletionNewParams{
Model: openai.CompletionNewParamsModelGPT3_5TurboInstruct,
Prompt: openai.CompletionNewParamsPromptUnion{
OfString: openai.String("This is a test."),
},
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", completion)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.completions.Completion;
import com.openai.models.completions.CompletionCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
CompletionCreateParams params = CompletionCreateParams.builder()
.model(CompletionCreateParams.Model.GPT_3_5_TURBO_INSTRUCT)
.prompt("This is a test.")
.build();
Completion completion = client.completions().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
completion = openai.completions.create(model: :"gpt-3.5-turbo-instruct", prompt: "This is a
test.")
puts(completion)
response: |
{
"id": "cmpl-7iA7iJjj8V2zOkCGvWF2hAkDWBQZe",
"object": "text_completion",
"created": 1690759702,
"choices": [
{
"text": "This",
"index": 0,
"logprobs": null,
"finish_reason": null
}
],
"model": "gpt-3.5-turbo-instruct"
"system_fingerprint": "fp_44709d6fcb",
}
description: Creates a completion for the provided prompt and parameters.
/containers:
get:
summary: List containers
description: List Containers
operationId: ListContainers
parameters:
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: order
in: query
description: >
Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
descending order.
schema:
type: string
default: desc
enum:
- asc
- desc
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
schema:
type: string
responses:
'200':
description: Success
content:
application/json:
schema:
$ref: '#/components/schemas/ContainerListResource'
x-oaiMeta:
name: List containers
group: containers
returns: a list of [container](https://platform.openai.com/docs/api-reference/containers/object) objects.
path: get
examples:
response: |
{
"object": "list",
"data": [
{
"id": "cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863",
"object": "container",
"created_at": 1747844794,
"status": "running",
"expires_after": {
"anchor": "last_active_at",
"minutes": 20
},
"last_active_at": 1747844794,
"name": "My Container"
}
],
"first_id": "container_123",
"last_id": "container_123",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/containers \
-H "Authorization: Bearer $OPENAI_API_KEY"
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const containerListResponse of client.containers.list()) {
console.log(containerListResponse.id);
}
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.containers.list()
page = page.data[0]
print(page.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.Containers.List(context.TODO(), openai.ContainerListParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.containers.ContainerListPage;
import com.openai.models.containers.ContainerListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ContainerListPage page = client.containers().list();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.containers.list
puts(page)
post:
summary: Create container
description: Create Container
operationId: CreateContainer
parameters: []
requestBody:
content:
application/json:
schema:
$ref: '#/components/schemas/CreateContainerBody'
responses:
'200':
description: Success
content:
application/json:
schema:
$ref: '#/components/schemas/ContainerResource'
x-oaiMeta:
name: Create container
group: containers
returns: The created [container](https://platform.openai.com/docs/api-reference/containers/object) object.
path: post
examples:
response: |
{
"id": "cntr_682e30645a488191b6363a0cbefc0f0a025ec61b66250591",
"object": "container",
"created_at": 1747857508,
"status": "running",
"expires_after": {
"anchor": "last_active_at",
"minutes": 20
},
"last_active_at": 1747857508,
"name": "My Container"
}
request:
curl: |
curl https://api.openai.com/v1/containers \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"name": "My Container"
}'
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const container = await client.containers.create({ name: 'name' });
console.log(container.id);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
container = client.containers.create(
name="name",
)
print(container.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
container, err := client.Containers.New(context.TODO(), openai.ContainerNewParams{
Name: "name",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", container.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.containers.ContainerCreateParams;
import com.openai.models.containers.ContainerCreateResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ContainerCreateParams params = ContainerCreateParams.builder()
.name("name")
.build();
ContainerCreateResponse container = client.containers().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
container = openai.containers.create(name: "name")
puts(container)
/containers/{container_id}:
get:
summary: Retrieve container
description: Retrieve Container
operationId: RetrieveContainer
parameters:
- name: container_id
in: path
required: true
schema:
type: string
responses:
'200':
description: Success
content:
application/json:
schema:
$ref: '#/components/schemas/ContainerResource'
x-oaiMeta:
name: Retrieve container
group: containers
returns: The [container](https://platform.openai.com/docs/api-reference/containers/object) object.
path: get
examples:
response: |
{
"id": "cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863",
"object": "container",
"created_at": 1747844794,
"status": "running",
"expires_after": {
"anchor": "last_active_at",
"minutes": 20
},
"last_active_at": 1747844794,
"name": "My Container"
}
request:
curl: >
curl https://api.openai.com/v1/containers/cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863
\
-H "Authorization: Bearer $OPENAI_API_KEY"
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const container = await client.containers.retrieve('container_id');
console.log(container.id);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
container = client.containers.retrieve(
"container_id",
)
print(container.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
container, err := client.Containers.Get(context.TODO(), "container_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", container.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.containers.ContainerRetrieveParams;
import com.openai.models.containers.ContainerRetrieveResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ContainerRetrieveResponse container = client.containers().retrieve("container_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
container = openai.containers.retrieve("container_id")
puts(container)
delete:
operationId: DeleteContainer
summary: Delete a container
description: Delete Container
parameters:
- name: container_id
in: path
description: The ID of the container to delete.
required: true
schema:
type: string
responses:
'200':
description: OK
x-oaiMeta:
name: Delete a container
group: containers
returns: Deletion Status
path: delete
examples:
response: |
{
"id": "cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863",
"object": "container.deleted",
"deleted": true
}
request:
curl: >
curl -X DELETE
https://api.openai.com/v1/containers/cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863 \
-H "Authorization: Bearer $OPENAI_API_KEY"
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
await client.containers.delete('container_id');
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
client.containers.delete(
"container_id",
)
go: |
package main
import (
"context"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
err := client.Containers.Delete(context.TODO(), "container_id")
if err != nil {
panic(err.Error())
}
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.containers.ContainerDeleteParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
client.containers().delete("container_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
result = openai.containers.delete("container_id")
puts(result)
/containers/{container_id}/files:
post:
summary: Create container file
description: >
Create a Container File
You can send either a multipart/form-data request with the raw file content, or a JSON request with a
file ID.
operationId: CreateContainerFile
parameters:
- name: container_id
in: path
required: true
schema:
type: string
requestBody:
required: true
content:
multipart/form-data:
schema:
$ref: '#/components/schemas/CreateContainerFileBody'
responses:
'200':
description: Success
content:
application/json:
schema:
$ref: '#/components/schemas/ContainerFileResource'
x-oaiMeta:
name: Create container file
group: containers
returns: >-
The created [container file](https://platform.openai.com/docs/api-reference/container-files/object)
object.
path: post
examples:
response: |
{
"id": "cfile_682e0e8a43c88191a7978f477a09bdf5",
"object": "container.file",
"created_at": 1747848842,
"bytes": 880,
"container_id": "cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04",
"path": "/mnt/data/88e12fa445d32636f190a0b33daed6cb-tsconfig.json",
"source": "user"
}
request:
curl: >
curl
https://api.openai.com/v1/containers/cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04/files
\
-H "Authorization: Bearer $OPENAI_API_KEY" \
-F file="@example.txt"
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const file = await client.containers.files.create('container_id');
console.log(file.id);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
file = client.containers.files.create(
container_id="container_id",
)
print(file.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
file, err := client.Containers.Files.New(
context.TODO(),
"container_id",
openai.ContainerFileNewParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", file.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.containers.files.FileCreateParams;
import com.openai.models.containers.files.FileCreateResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileCreateResponse file = client.containers().files().create("container_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
file = openai.containers.files.create("container_id")
puts(file)
get:
summary: List container files
description: List Container files
operationId: ListContainerFiles
parameters:
- name: container_id
in: path
required: true
schema:
type: string
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: order
in: query
description: >
Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
descending order.
schema:
type: string
default: desc
enum:
- asc
- desc
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
schema:
type: string
responses:
'200':
description: Success
content:
application/json:
schema:
$ref: '#/components/schemas/ContainerFileListResource'
x-oaiMeta:
name: List container files
group: containers
returns: >-
a list of [container file](https://platform.openai.com/docs/api-reference/container-files/object)
objects.
path: get
examples:
response: |
{
"object": "list",
"data": [
{
"id": "cfile_682e0e8a43c88191a7978f477a09bdf5",
"object": "container.file",
"created_at": 1747848842,
"bytes": 880,
"container_id": "cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04",
"path": "/mnt/data/88e12fa445d32636f190a0b33daed6cb-tsconfig.json",
"source": "user"
}
],
"first_id": "cfile_682e0e8a43c88191a7978f477a09bdf5",
"has_more": false,
"last_id": "cfile_682e0e8a43c88191a7978f477a09bdf5"
}
request:
curl: >
curl
https://api.openai.com/v1/containers/cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04/files
\
-H "Authorization: Bearer $OPENAI_API_KEY"
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const fileListResponse of client.containers.files.list('container_id')) {
console.log(fileListResponse.id);
}
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.containers.files.list(
container_id="container_id",
)
page = page.data[0]
print(page.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.Containers.Files.List(
context.TODO(),
"container_id",
openai.ContainerFileListParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.containers.files.FileListPage;
import com.openai.models.containers.files.FileListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileListPage page = client.containers().files().list("container_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.containers.files.list("container_id")
puts(page)
/containers/{container_id}/files/{file_id}:
get:
summary: Retrieve container file
description: Retrieve Container File
operationId: RetrieveContainerFile
parameters:
- name: container_id
in: path
required: true
schema:
type: string
- name: file_id
in: path
required: true
schema:
type: string
responses:
'200':
description: Success
content:
application/json:
schema:
$ref: '#/components/schemas/ContainerFileResource'
x-oaiMeta:
name: Retrieve container file
group: containers
returns: The [container file](https://platform.openai.com/docs/api-reference/container-files/object) object.
path: get
examples:
response: |
{
"id": "cfile_682e0e8a43c88191a7978f477a09bdf5",
"object": "container.file",
"created_at": 1747848842,
"bytes": 880,
"container_id": "cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04",
"path": "/mnt/data/88e12fa445d32636f190a0b33daed6cb-tsconfig.json",
"source": "user"
}
request:
curl: |
curl https://api.openai.com/v1/containers/container_123/files/file_456 \
-H "Authorization: Bearer $OPENAI_API_KEY"
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const file = await client.containers.files.retrieve('file_id', { container_id: 'container_id'
});
console.log(file.id);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
file = client.containers.files.retrieve(
file_id="file_id",
container_id="container_id",
)
print(file.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
file, err := client.Containers.Files.Get(
context.TODO(),
"container_id",
"file_id",
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", file.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.containers.files.FileRetrieveParams;
import com.openai.models.containers.files.FileRetrieveResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileRetrieveParams params = FileRetrieveParams.builder()
.containerId("container_id")
.fileId("file_id")
.build();
FileRetrieveResponse file = client.containers().files().retrieve(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
file = openai.containers.files.retrieve("file_id", container_id: "container_id")
puts(file)
delete:
operationId: DeleteContainerFile
summary: Delete a container file
description: Delete Container File
parameters:
- name: container_id
in: path
required: true
schema:
type: string
- name: file_id
in: path
required: true
schema:
type: string
responses:
'200':
description: OK
x-oaiMeta:
name: Delete a container file
group: containers
returns: Deletion Status
path: delete
examples:
response: |
{
"id": "cfile_682e0e8a43c88191a7978f477a09bdf5",
"object": "container.file.deleted",
"deleted": true
}
request:
curl: >
curl -X DELETE
https://api.openai.com/v1/containers/cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863/files/cfile_682e0e8a43c88191a7978f477a09bdf5
\
-H "Authorization: Bearer $OPENAI_API_KEY"
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
await client.containers.files.delete('file_id', { container_id: 'container_id' });
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
client.containers.files.delete(
file_id="file_id",
container_id="container_id",
)
go: |
package main
import (
"context"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
err := client.Containers.Files.Delete(
context.TODO(),
"container_id",
"file_id",
)
if err != nil {
panic(err.Error())
}
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.containers.files.FileDeleteParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileDeleteParams params = FileDeleteParams.builder()
.containerId("container_id")
.fileId("file_id")
.build();
client.containers().files().delete(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
result = openai.containers.files.delete("file_id", container_id: "container_id")
puts(result)
/containers/{container_id}/files/{file_id}/content:
get:
summary: Retrieve container file content
description: Retrieve Container File Content
operationId: RetrieveContainerFileContent
parameters:
- name: container_id
in: path
required: true
schema:
type: string
- name: file_id
in: path
required: true
schema:
type: string
responses:
'200':
description: Success
x-oaiMeta:
name: Retrieve container file content
group: containers
returns: The contents of the container file.
path: get
examples:
response: |
<binary content of the file>
request:
curl: |
curl https://api.openai.com/v1/containers/container_123/files/cfile_456/content \
-H "Authorization: Bearer $OPENAI_API_KEY"
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const content = await client.containers.files.content.retrieve('file_id', { container_id:
'container_id' });
console.log(content);
const data = await content.blob();
console.log(data);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
content = client.containers.files.content.retrieve(
file_id="file_id",
container_id="container_id",
)
print(content)
data = content.read()
print(data)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
content, err := client.Containers.Files.Content.Get(
context.TODO(),
"container_id",
"file_id",
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", content)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.core.http.HttpResponse;
import com.openai.models.containers.files.content.ContentRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ContentRetrieveParams params = ContentRetrieveParams.builder()
.containerId("container_id")
.fileId("file_id")
.build();
HttpResponse content = client.containers().files().content().retrieve(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
content = openai.containers.files.content.retrieve("file_id", container_id: "container_id")
puts(content)
/conversations:
post:
operationId: createConversation
tags:
- Conversations
summary: Create a conversation
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateConversationRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ConversationResource'
x-oaiMeta:
name: Create a conversation
group: conversations
returns: >
Returns a [Conversation](https://platform.openai.com/docs/api-reference/conversations/object)
object.
path: create
examples:
- title: Create a conversation
request:
curl: |
curl https://api.openai.com/v1/conversations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"metadata": {"topic": "demo"},
"items": [
{
"type": "message",
"role": "user",
"content": "Hello!"
}
]
}'
javascript: |
import OpenAI from "openai";
const client = new OpenAI();
const conversation = await client.conversations.create({
metadata: { topic: "demo" },
items: [
{ type: "message", role: "user", content: "Hello!" }
],
});
console.log(conversation);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
conversation = client.conversations.create()
print(conversation.id)
csharp: |
using System;
using System.Collections.Generic;
using OpenAI.Conversations;
OpenAIConversationClient client = new(
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
Conversation conversation = client.CreateConversation(
new CreateConversationOptions
{
Metadata = new Dictionary<string, string>
{
{ "topic", "demo" }
},
Items =
{
new ConversationMessageInput
{
Role = "user",
Content = "Hello!"
}
}
}
);
Console.WriteLine(conversation.Id);
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const conversation = await client.conversations.create();
console.log(conversation.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/conversations"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
conversation, err := client.Conversations.New(context.TODO(), conversations.ConversationNewParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", conversation.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.conversations.Conversation;
import com.openai.models.conversations.ConversationCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Conversation conversation = client.conversations().create();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
conversation = openai.conversations.create
puts(conversation)
response: |
{
"id": "conv_123",
"object": "conversation",
"created_at": 1741900000,
"metadata": {"topic": "demo"}
}
description: Create a conversation with the given ID.
/conversations/{conversation_id}:
get:
operationId: getConversation
tags:
- Conversations
summary: Retrieve a conversation
parameters:
- in: path
name: conversation_id
required: true
schema:
type: string
example: conv_123
description: The ID of the conversation to retrieve.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ConversationResource'
x-oaiMeta:
name: Retrieve a conversation
group: conversations
returns: >
Returns a [Conversation](https://platform.openai.com/docs/api-reference/conversations/object)
object.
path: retrieve
examples:
- title: Retrieve a conversation
request:
curl: |
curl https://api.openai.com/v1/conversations/conv_123 \
-H "Authorization: Bearer $OPENAI_API_KEY"
javascript: |
import OpenAI from "openai";
const client = new OpenAI();
const conversation = await client.conversations.retrieve("conv_123");
console.log(conversation);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
conversation = client.conversations.retrieve(
"conv_123",
)
print(conversation.id)
csharp: |
using System;
using OpenAI.Conversations;
OpenAIConversationClient client = new(
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
Conversation conversation = client.GetConversation("conv_123");
Console.WriteLine(conversation.Id);
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const conversation = await client.conversations.retrieve('conv_123');
console.log(conversation.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
conversation, err := client.Conversations.Get(context.TODO(), "conv_123")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", conversation.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.conversations.Conversation;
import com.openai.models.conversations.ConversationRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Conversation conversation = client.conversations().retrieve("conv_123");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
conversation = openai.conversations.retrieve("conv_123")
puts(conversation)
response: |
{
"id": "conv_123",
"object": "conversation",
"created_at": 1741900000,
"metadata": {"topic": "demo"}
}
description: Get a conversation with the given ID.
post:
operationId: updateConversation
tags:
- Conversations
summary: Update a conversation
parameters:
- in: path
name: conversation_id
required: true
schema:
type: string
example: conv_123
description: The ID of the conversation to update.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/UpdateConversationBody'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ConversationResource'
x-oaiMeta:
name: Update a conversation
group: conversations
returns: >
Returns the updated
[Conversation](https://platform.openai.com/docs/api-reference/conversations/object) object.
path: update
examples:
- title: Update conversation metadata
request:
curl: |
curl https://api.openai.com/v1/conversations/conv_123 \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"metadata": {"topic": "project-x"}
}'
javascript: |
import OpenAI from "openai";
const client = new OpenAI();
const updated = await client.conversations.update(
"conv_123",
{ metadata: { topic: "project-x" } }
);
console.log(updated);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
conversation = client.conversations.update(
conversation_id="conv_123",
metadata={
"foo": "string"
},
)
print(conversation.id)
csharp: |
using System;
using System.Collections.Generic;
using OpenAI.Conversations;
OpenAIConversationClient client = new(
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
Conversation updated = client.UpdateConversation(
conversationId: "conv_123",
new UpdateConversationOptions
{
Metadata = new Dictionary<string, string>
{
{ "topic", "project-x" }
}
}
);
Console.WriteLine(updated.Id);
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const conversation = await client.conversations.update('conv_123', { metadata: { foo: 'string'
} });
console.log(conversation.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/conversations"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
conversation, err := client.Conversations.Update(
context.TODO(),
"conv_123",
conversations.ConversationUpdateParams{
Metadata: map[string]string{
"foo": "string",
},
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", conversation.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.core.JsonValue;
import com.openai.models.conversations.Conversation;
import com.openai.models.conversations.ConversationUpdateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ConversationUpdateParams params = ConversationUpdateParams.builder()
.conversationId("conv_123")
.metadata(ConversationUpdateParams.Metadata.builder()
.putAdditionalProperty("foo", JsonValue.from("string"))
.build())
.build();
Conversation conversation = client.conversations().update(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
conversation = openai.conversations.update("conv_123", metadata: {foo: "string"})
puts(conversation)
response: |
{
"id": "conv_123",
"object": "conversation",
"created_at": 1741900000,
"metadata": {"topic": "project-x"}
}
description: Update a conversation's metadata with the given ID.
delete:
operationId: deleteConversation
tags:
- Conversations
summary: Delete a conversation
parameters:
- in: path
name: conversation_id
required: true
schema:
type: string
example: conv_123
description: The ID of the conversation to delete.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/DeletedConversationResource'
x-oaiMeta:
name: Delete a conversation
group: conversations
returns: |
A success message.
path: delete
examples:
- title: Delete a conversation
request:
curl: |
curl -X DELETE https://api.openai.com/v1/conversations/conv_123 \
-H "Authorization: Bearer $OPENAI_API_KEY"
javascript: |
import OpenAI from "openai";
const client = new OpenAI();
const deleted = await client.conversations.delete("conv_123");
console.log(deleted);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
conversation_deleted_resource = client.conversations.delete(
"conv_123",
)
print(conversation_deleted_resource.id)
csharp: |
using System;
using OpenAI.Conversations;
OpenAIConversationClient client = new(
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
DeletedConversation deleted = client.DeleteConversation("conv_123");
Console.WriteLine(deleted.Id);
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const conversationDeletedResource = await client.conversations.delete('conv_123');
console.log(conversationDeletedResource.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
conversationDeletedResource, err := client.Conversations.Delete(context.TODO(), "conv_123")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", conversationDeletedResource.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.conversations.ConversationDeleteParams;
import com.openai.models.conversations.ConversationDeletedResource;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ConversationDeletedResource conversationDeletedResource = client.conversations().delete("conv_123");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
conversation_deleted_resource = openai.conversations.delete("conv_123")
puts(conversation_deleted_resource)
response: |
{
"id": "conv_123",
"object": "conversation.deleted",
"deleted": true
}
description: Delete a conversation with the given ID.
/conversations/{conversation_id}/items:
post:
operationId: createConversationItems
tags:
- Conversations
summary: Create items
parameters:
- in: path
name: conversation_id
required: true
schema:
type: string
example: conv_123
description: The ID of the conversation to add the item to.
- name: include
in: query
required: false
schema:
type: array
items:
$ref: '#/components/schemas/Includable'
description: >
Additional fields to include in the response. See the `include`
parameter for [listing Conversation items
above](https://platform.openai.com/docs/api-reference/conversations/list-items#conversations_list_items-include)
for more information.
requestBody:
required: true
content:
application/json:
schema:
properties:
items:
type: array
description: |
The items to add to the conversation. You may add up to 20 items at a time.
items:
$ref: '#/components/schemas/InputItem'
maxItems: 20
required:
- items
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ConversationItemList'
x-oaiMeta:
name: Create items
group: conversations
returns: >
Returns the list of added
[items](https://platform.openai.com/docs/api-reference/conversations/list-items-object).
path: create-item
examples:
- title: Add a user message to a conversation
request:
curl: |
curl https://api.openai.com/v1/conversations/conv_123/items \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"items": [
{
"type": "message",
"role": "user",
"content": [
{"type": "input_text", "text": "Hello!"}
]
},
{
"type": "message",
"role": "user",
"content": [
{"type": "input_text", "text": "How are you?"}
]
}
]
}'
javascript: |
import OpenAI from "openai";
const client = new OpenAI();
const items = await client.conversations.items.create(
"conv_123",
{
items: [
{
type: "message",
role: "user",
content: [{ type: "input_text", text: "Hello!" }],
},
{
type: "message",
role: "user",
content: [{ type: "input_text", text: "How are you?" }],
},
],
}
);
console.log(items.data);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
conversation_item_list = client.conversations.items.create(
conversation_id="conv_123",
items=[{
"content": "string",
"role": "user",
}],
)
print(conversation_item_list.first_id)
csharp: |
using System;
using System.Collections.Generic;
using OpenAI.Conversations;
OpenAIConversationClient client = new(
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
ConversationItemList created = client.ConversationItems.Create(
conversationId: "conv_123",
new CreateConversationItemsOptions
{
Items = new List<ConversationItem>
{
new ConversationMessage
{
Role = "user",
Content =
{
new ConversationInputText { Text = "Hello!" }
}
},
new ConversationMessage
{
Role = "user",
Content =
{
new ConversationInputText { Text = "How are you?" }
}
}
}
}
);
Console.WriteLine(created.Data.Count);
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const conversationItemList = await client.conversations.items.create('conv_123', {
items: [{ content: 'string', role: 'user' }],
});
console.log(conversationItemList.first_id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/conversations"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/responses"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
conversationItemList, err := client.Conversations.Items.New(
context.TODO(),
"conv_123",
conversations.ItemNewParams{
Items: []responses.ResponseInputItemUnionParam{responses.ResponseInputItemUnionParam{
OfMessage: &responses.EasyInputMessageParam{
Content: responses.EasyInputMessageContentUnionParam{
OfString: openai.String("string"),
},
Role: responses.EasyInputMessageRoleUser,
},
}},
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", conversationItemList.FirstID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.conversations.items.ConversationItemList;
import com.openai.models.conversations.items.ItemCreateParams;
import com.openai.models.responses.EasyInputMessage;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ItemCreateParams params = ItemCreateParams.builder()
.conversationId("conv_123")
.addItem(EasyInputMessage.builder()
.content("string")
.role(EasyInputMessage.Role.USER)
.build())
.build();
ConversationItemList conversationItemList = client.conversations().items().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
conversation_item_list = openai.conversations.items.create("conv_123", items: [{content:
"string", role: :user}])
puts(conversation_item_list)
response: |
{
"object": "list",
"data": [
{
"type": "message",
"id": "msg_abc",
"status": "completed",
"role": "user",
"content": [
{"type": "input_text", "text": "Hello!"}
]
},
{
"type": "message",
"id": "msg_def",
"status": "completed",
"role": "user",
"content": [
{"type": "input_text", "text": "How are you?"}
]
}
],
"first_id": "msg_abc",
"last_id": "msg_def",
"has_more": false
}
description: Create items in a conversation with the given ID.
get:
operationId: listConversationItems
tags:
- Conversations
summary: List items
parameters:
- in: path
name: conversation_id
required: true
schema:
type: string
example: conv_123
description: The ID of the conversation to list items for.
- name: limit
in: query
description: |
A limit on the number of objects to be returned. Limit can range between
1 and 100, and the default is 20.
required: false
schema:
type: integer
default: 20
- in: query
name: order
schema:
type: string
enum:
- asc
- desc
description: |
The order to return the input items in. Default is `desc`.
- `asc`: Return the input items in ascending order.
- `desc`: Return the input items in descending order.
- in: query
name: after
schema:
type: string
description: |
An item ID to list items after, used in pagination.
- name: include
in: query
required: false
schema:
type: array
items:
$ref: '#/components/schemas/Includable'
description: |
Specify additional output data to include in the model response. Currently
supported values are:
- `code_interpreter_call.outputs`: Includes the outputs of python code execution
in code interpreter tool call items.
- `computer_call_output.output.image_url`: Include image urls from the computer call output.
- `file_search_call.results`: Include the search results of
the file search tool call.
- `message.input_image.image_url`: Include image urls from the input message.
- `message.output_text.logprobs`: Include logprobs with assistant messages.
- `reasoning.encrypted_content`: Includes an encrypted version of reasoning
tokens in reasoning item outputs. This enables reasoning items to be used in
multi-turn conversations when using the Responses API statelessly (like
when the `store` parameter is set to `false`, or when an organization is
enrolled in the zero data retention program).
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ConversationItemList'
x-oaiMeta:
name: List items
group: conversations
returns: >
Returns a [list
object](https://platform.openai.com/docs/api-reference/conversations/list-items-object) containing
Conversation items.
path: list-items
examples:
- title: List items in a conversation
request:
curl: |
curl "https://api.openai.com/v1/conversations/conv_123/items?limit=10" \
-H "Authorization: Bearer $OPENAI_API_KEY"
javascript: |
import OpenAI from "openai";
const client = new OpenAI();
const items = await client.conversations.items.list("conv_123", { limit: 10 });
console.log(items.data);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.conversations.items.list(
conversation_id="conv_123",
)
page = page.data[0]
print(page)
csharp: |
using System;
using OpenAI.Conversations;
OpenAIConversationClient client = new(
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
ConversationItemList items = client.ConversationItems.List(
conversationId: "conv_123",
new ListConversationItemsOptions { Limit = 10 }
);
Console.WriteLine(items.Data.Count);
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const conversationItem of client.conversations.items.list('conv_123')) {
console.log(conversationItem);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/conversations"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.Conversations.Items.List(
context.TODO(),
"conv_123",
conversations.ItemListParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.conversations.items.ItemListPage;
import com.openai.models.conversations.items.ItemListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ItemListPage page = client.conversations().items().list("conv_123");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.conversations.items.list("conv_123")
puts(page)
response: |
{
"object": "list",
"data": [
{
"type": "message",
"id": "msg_abc",
"status": "completed",
"role": "user",
"content": [
{"type": "input_text", "text": "Hello!"}
]
}
],
"first_id": "msg_abc",
"last_id": "msg_abc",
"has_more": false
}
description: List all items for a conversation with the given ID.
/conversations/{conversation_id}/items/{item_id}:
get:
operationId: getConversationItem
tags:
- Conversations
summary: Retrieve an item
parameters:
- in: path
name: conversation_id
required: true
schema:
type: string
example: conv_123
description: The ID of the conversation that contains the item.
- in: path
name: item_id
required: true
schema:
type: string
example: msg_abc
description: The ID of the item to retrieve.
- name: include
in: query
required: false
schema:
type: array
items:
$ref: '#/components/schemas/Includable'
description: >
Additional fields to include in the response. See the `include`
parameter for [listing Conversation items
above](https://platform.openai.com/docs/api-reference/conversations/list-items#conversations_list_items-include)
for more information.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ConversationItem'
x-oaiMeta:
name: Retrieve an item
group: conversations
returns: >
Returns a [Conversation
Item](https://platform.openai.com/docs/api-reference/conversations/item-object).
path: get-item
examples:
- title: Retrieve an item
request:
curl: |
curl https://api.openai.com/v1/conversations/conv_123/items/msg_abc \
-H "Authorization: Bearer $OPENAI_API_KEY"
javascript: |
import OpenAI from "openai";
const client = new OpenAI();
const item = await client.conversations.items.retrieve(
"conv_123",
"msg_abc"
);
console.log(item);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
conversation_item = client.conversations.items.retrieve(
item_id="msg_abc",
conversation_id="conv_123",
)
print(conversation_item)
csharp: |
using System;
using OpenAI.Conversations;
OpenAIConversationClient client = new(
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
ConversationItem item = client.ConversationItems.Get(
conversationId: "conv_123",
itemId: "msg_abc"
);
Console.WriteLine(item.Id);
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const conversationItem = await client.conversations.items.retrieve('msg_abc', {
conversation_id: 'conv_123',
});
console.log(conversationItem);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/conversations"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
conversationItem, err := client.Conversations.Items.Get(
context.TODO(),
"conv_123",
"msg_abc",
conversations.ItemGetParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", conversationItem)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.conversations.items.ConversationItem;
import com.openai.models.conversations.items.ItemRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ItemRetrieveParams params = ItemRetrieveParams.builder()
.conversationId("conv_123")
.itemId("msg_abc")
.build();
ConversationItem conversationItem = client.conversations().items().retrieve(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
conversation_item = openai.conversations.items.retrieve("msg_abc", conversation_id:
"conv_123")
puts(conversation_item)
response: |
{
"type": "message",
"id": "msg_abc",
"status": "completed",
"role": "user",
"content": [
{"type": "input_text", "text": "Hello!"}
]
}
description: Get a single item from a conversation with the given IDs.
delete:
operationId: deleteConversationItem
tags:
- Conversations
summary: Delete an item
parameters:
- in: path
name: conversation_id
required: true
schema:
type: string
example: conv_123
description: The ID of the conversation that contains the item.
- in: path
name: item_id
required: true
schema:
type: string
example: msg_abc
description: The ID of the item to delete.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ConversationResource'
x-oaiMeta:
name: Delete an item
group: conversations
returns: >
Returns the updated
[Conversation](https://platform.openai.com/docs/api-reference/conversations/object) object.
path: delete-item
examples:
- title: Delete an item
request:
curl: |
curl -X DELETE https://api.openai.com/v1/conversations/conv_123/items/msg_abc \
-H "Authorization: Bearer $OPENAI_API_KEY"
javascript: |
import OpenAI from "openai";
const client = new OpenAI();
const conversation = await client.conversations.items.delete(
"conv_123",
"msg_abc"
);
console.log(conversation);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
conversation = client.conversations.items.delete(
item_id="msg_abc",
conversation_id="conv_123",
)
print(conversation.id)
csharp: |
using System;
using OpenAI.Conversations;
OpenAIConversationClient client = new(
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
Conversation conversation = client.ConversationItems.Delete(
conversationId: "conv_123",
itemId: "msg_abc"
);
Console.WriteLine(conversation.Id);
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const conversation = await client.conversations.items.delete('msg_abc', { conversation_id:
'conv_123' });
console.log(conversation.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
conversation, err := client.Conversations.Items.Delete(
context.TODO(),
"conv_123",
"msg_abc",
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", conversation.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.conversations.Conversation;
import com.openai.models.conversations.items.ItemDeleteParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ItemDeleteParams params = ItemDeleteParams.builder()
.conversationId("conv_123")
.itemId("msg_abc")
.build();
Conversation conversation = client.conversations().items().delete(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
conversation = openai.conversations.items.delete("msg_abc", conversation_id: "conv_123")
puts(conversation)
response: |
{
"id": "conv_123",
"object": "conversation",
"created_at": 1741900000,
"metadata": {"topic": "demo"}
}
description: Delete an item from a conversation with the given IDs.
/embeddings:
post:
operationId: createEmbedding
tags:
- Embeddings
summary: Create embeddings
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateEmbeddingRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/CreateEmbeddingResponse'
x-oaiMeta:
name: Create embeddings
group: embeddings
returns: A list of [embedding](https://platform.openai.com/docs/api-reference/embeddings/object) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"object": "embedding",
"embedding": [
0.0023064255,
-0.009327292,
.... (1536 floats total for ada-002)
-0.0028842222,
],
"index": 0
}
],
"model": "text-embedding-ada-002",
"usage": {
"prompt_tokens": 8,
"total_tokens": 8
}
}
request:
curl: |
curl https://api.openai.com/v1/embeddings \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input": "The food was delicious and the waiter...",
"model": "text-embedding-ada-002",
"encoding_format": "float"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
create_embedding_response = client.embeddings.create(
input="The quick brown fox jumped over the lazy dog",
model="text-embedding-3-small",
)
print(create_embedding_response.data)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const createEmbeddingResponse = await client.embeddings.create({
input: 'The quick brown fox jumped over the lazy dog',
model: 'text-embedding-3-small',
});
console.log(createEmbeddingResponse.data);
csharp: >
using System;
using OpenAI.Embeddings;
EmbeddingClient client = new(
model: "text-embedding-3-small",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
OpenAIEmbedding embedding = client.GenerateEmbedding(input: "The quick brown fox jumped over the
lazy dog");
ReadOnlyMemory<float> vector = embedding.ToFloats();
for (int i = 0; i < vector.Length; i++)
{
Console.WriteLine($" [{i,4}] = {vector.Span[i]}");
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
createEmbeddingResponse, err := client.Embeddings.New(context.TODO(), openai.EmbeddingNewParams{
Input: openai.EmbeddingNewParamsInputUnion{
OfString: openai.String("The quick brown fox jumped over the lazy dog"),
},
Model: openai.EmbeddingModelTextEmbeddingAda002,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", createEmbeddingResponse.Data)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.embeddings.CreateEmbeddingResponse;
import com.openai.models.embeddings.EmbeddingCreateParams;
import com.openai.models.embeddings.EmbeddingModel;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
EmbeddingCreateParams params = EmbeddingCreateParams.builder()
.input("The quick brown fox jumped over the lazy dog")
.model(EmbeddingModel.TEXT_EMBEDDING_ADA_002)
.build();
CreateEmbeddingResponse createEmbeddingResponse = client.embeddings().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
create_embedding_response = openai.embeddings.create(
input: "The quick brown fox jumped over the lazy dog",
model: :"text-embedding-ada-002"
)
puts(create_embedding_response)
description: Creates an embedding vector representing the input text.
/evals:
get:
operationId: listEvals
tags:
- Evals
summary: List evals
parameters:
- name: after
in: query
description: Identifier for the last eval from the previous pagination request.
required: false
schema:
type: string
- name: limit
in: query
description: Number of evals to retrieve.
required: false
schema:
type: integer
default: 20
- name: order
in: query
description: Sort order for evals by timestamp. Use `asc` for ascending order or `desc` for descending order.
required: false
schema:
type: string
enum:
- asc
- desc
default: asc
- name: order_by
in: query
description: |
Evals can be ordered by creation time or last updated time. Use
`created_at` for creation time or `updated_at` for last updated time.
required: false
schema:
type: string
enum:
- created_at
- updated_at
default: created_at
responses:
'200':
description: A list of evals
content:
application/json:
schema:
$ref: '#/components/schemas/EvalList'
x-oaiMeta:
name: List evals
group: evals
returns: >-
A list of [evals](https://platform.openai.com/docs/api-reference/evals/object) matching the
specified filters.
path: list
examples:
response: |
{
"object": "list",
"data": [
{
"id": "eval_67abd54d9b0081909a86353f6fb9317a",
"object": "eval",
"data_source_config": {
"type": "stored_completions",
"metadata": {
"usecase": "push_notifications_summarizer"
},
"schema": {
"type": "object",
"properties": {
"item": {
"type": "object"
},
"sample": {
"type": "object"
}
},
"required": [
"item",
"sample"
]
}
},
"testing_criteria": [
{
"name": "Push Notification Summary Grader",
"id": "Push Notification Summary Grader-9b876f24-4762-4be9-aff4-db7a9b31c673",
"type": "label_model",
"model": "o3-mini",
"input": [
{
"type": "message",
"role": "developer",
"content": {
"type": "input_text",
"text": "\nLabel the following push notification summary as either correct or incorrect.\nThe push notification and the summary will be provided below.\nA good push notificiation summary is concise and snappy.\nIf it is good, then label it as correct, if not, then incorrect.\n"
}
},
{
"type": "message",
"role": "user",
"content": {
"type": "input_text",
"text": "\nPush notifications: {{item.input}}\nSummary: {{sample.output_text}}\n"
}
}
],
"passing_labels": [
"correct"
],
"labels": [
"correct",
"incorrect"
],
"sampling_params": null
}
],
"name": "Push Notification Summary Grader",
"created_at": 1739314509,
"metadata": {
"description": "A stored completions eval for push notification summaries"
}
}
],
"first_id": "eval_67abd54d9b0081909a86353f6fb9317a",
"last_id": "eval_67aa884cf6688190b58f657d4441c8b7",
"has_more": true
}
request:
curl: |
curl https://api.openai.com/v1/evals?limit=1 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.evals.list()
page = page.data[0]
print(page.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const evalListResponse of client.evals.list()) {
console.log(evalListResponse.id);
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.evals.EvalListPage;
import com.openai.models.evals.EvalListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
EvalListPage page = client.evals().list();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.evals.list
puts(page)
description: |
List evaluations for a project.
post:
operationId: createEval
tags:
- Evals
summary: Create eval
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateEvalRequest'
responses:
'201':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/Eval'
x-oaiMeta:
name: Create eval
group: evals
returns: The created [Eval](https://platform.openai.com/docs/api-reference/evals/object) object.
path: post
examples:
response: |
{
"object": "eval",
"id": "eval_67b7fa9a81a88190ab4aa417e397ea21",
"data_source_config": {
"type": "stored_completions",
"metadata": {
"usecase": "chatbot"
},
"schema": {
"type": "object",
"properties": {
"item": {
"type": "object"
},
"sample": {
"type": "object"
}
},
"required": [
"item",
"sample"
]
},
"testing_criteria": [
{
"name": "Example label grader",
"type": "label_model",
"model": "o3-mini",
"input": [
{
"type": "message",
"role": "developer",
"content": {
"type": "input_text",
"text": "Classify the sentiment of the following statement as one of positive, neutral, or negative"
}
},
{
"type": "message",
"role": "user",
"content": {
"type": "input_text",
"text": "Statement: {{item.input}}"
}
}
],
"passing_labels": [
"positive"
],
"labels": [
"positive",
"neutral",
"negative"
]
}
],
"name": "Sentiment",
"created_at": 1740110490,
"metadata": {
"description": "An eval for sentiment analysis"
}
}
request:
curl: |
curl https://api.openai.com/v1/evals \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"name": "Sentiment",
"data_source_config": {
"type": "stored_completions",
"metadata": {
"usecase": "chatbot"
}
},
"testing_criteria": [
{
"type": "label_model",
"model": "o3-mini",
"input": [
{
"role": "developer",
"content": "Classify the sentiment of the following statement as one of 'positive', 'neutral', or 'negative'"
},
{
"role": "user",
"content": "Statement: {{item.input}}"
}
],
"passing_labels": [
"positive"
],
"labels": [
"positive",
"neutral",
"negative"
],
"name": "Example label grader"
}
]
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
eval = client.evals.create(
data_source_config={
"item_schema": {
"foo": "bar"
},
"type": "custom",
},
testing_criteria=[{
"input": [{
"content": "content",
"role": "role",
}],
"labels": ["string"],
"model": "model",
"name": "name",
"passing_labels": ["string"],
"type": "label_model",
}],
)
print(eval.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const _eval = await client.evals.create({
data_source_config: { item_schema: { foo: 'bar' }, type: 'custom' },
testing_criteria: [
{
input: [{ content: 'content', role: 'role' }],
labels: ['string'],
model: 'model',
name: 'name',
passing_labels: ['string'],
type: 'label_model',
},
],
});
console.log(_eval.id);
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.core.JsonValue;
import com.openai.models.evals.EvalCreateParams;
import com.openai.models.evals.EvalCreateResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
EvalCreateParams params = EvalCreateParams.builder()
.customDataSourceConfig(EvalCreateParams.DataSourceConfig.Custom.ItemSchema.builder()
.putAdditionalProperty("foo", JsonValue.from("bar"))
.build())
.addTestingCriterion(EvalCreateParams.TestingCriterion.LabelModel.builder()
.addInput(EvalCreateParams.TestingCriterion.LabelModel.Input.SimpleInputMessage.builder()
.content("content")
.role("role")
.build())
.addLabel("string")
.model("model")
.name("name")
.addPassingLabel("string")
.build())
.build();
EvalCreateResponse eval = client.evals().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
eval_ = openai.evals.create(
data_source_config: {item_schema: {foo: "bar"}, type: :custom},
testing_criteria: [
{
input: [{content: "content", role: "role"}],
labels: ["string"],
model: "model",
name: "name",
passing_labels: ["string"],
type: :label_model
}
]
)
puts(eval_)
description: >
Create the structure of an evaluation that can be used to test a model's performance.
An evaluation is a set of testing criteria and the config for a data source, which dictates the schema
of the data used in the evaluation. After creating an evaluation, you can run it on different models
and model parameters. We support several types of graders and datasources.
For more information, see the [Evals guide](https://platform.openai.com/docs/guides/evals).
/evals/{eval_id}:
get:
operationId: getEval
tags:
- Evals
summary: Get an eval
parameters:
- name: eval_id
in: path
required: true
schema:
type: string
description: The ID of the evaluation to retrieve.
responses:
'200':
description: The evaluation
content:
application/json:
schema:
$ref: '#/components/schemas/Eval'
x-oaiMeta:
name: Get an eval
group: evals
returns: >-
The [Eval](https://platform.openai.com/docs/api-reference/evals/object) object matching the
specified ID.
path: get
examples:
response: |
{
"object": "eval",
"id": "eval_67abd54d9b0081909a86353f6fb9317a",
"data_source_config": {
"type": "custom",
"schema": {
"type": "object",
"properties": {
"item": {
"type": "object",
"properties": {
"input": {
"type": "string"
},
"ground_truth": {
"type": "string"
}
},
"required": [
"input",
"ground_truth"
]
}
},
"required": [
"item"
]
}
},
"testing_criteria": [
{
"name": "String check",
"id": "String check-2eaf2d8d-d649-4335-8148-9535a7ca73c2",
"type": "string_check",
"input": "{{item.input}}",
"reference": "{{item.ground_truth}}",
"operation": "eq"
}
],
"name": "External Data Eval",
"created_at": 1739314509,
"metadata": {},
}
request:
curl: |
curl https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
eval = client.evals.retrieve(
"eval_id",
)
print(eval.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const _eval = await client.evals.retrieve('eval_id');
console.log(_eval.id);
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.evals.EvalRetrieveParams;
import com.openai.models.evals.EvalRetrieveResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
EvalRetrieveResponse eval = client.evals().retrieve("eval_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
eval_ = openai.evals.retrieve("eval_id")
puts(eval_)
description: |
Get an evaluation by ID.
post:
operationId: updateEval
tags:
- Evals
summary: Update an eval
parameters:
- name: eval_id
in: path
required: true
schema:
type: string
description: The ID of the evaluation to update.
requestBody:
description: Request to update an evaluation
required: true
content:
application/json:
schema:
type: object
properties:
name:
type: string
description: Rename the evaluation.
metadata:
$ref: '#/components/schemas/Metadata'
responses:
'200':
description: The updated evaluation
content:
application/json:
schema:
$ref: '#/components/schemas/Eval'
x-oaiMeta:
name: Update an eval
group: evals
returns: >-
The [Eval](https://platform.openai.com/docs/api-reference/evals/object) object matching the updated
version.
path: update
examples:
response: |
{
"object": "eval",
"id": "eval_67abd54d9b0081909a86353f6fb9317a",
"data_source_config": {
"type": "custom",
"schema": {
"type": "object",
"properties": {
"item": {
"type": "object",
"properties": {
"input": {
"type": "string"
},
"ground_truth": {
"type": "string"
}
},
"required": [
"input",
"ground_truth"
]
}
},
"required": [
"item"
]
}
},
"testing_criteria": [
{
"name": "String check",
"id": "String check-2eaf2d8d-d649-4335-8148-9535a7ca73c2",
"type": "string_check",
"input": "{{item.input}}",
"reference": "{{item.ground_truth}}",
"operation": "eq"
}
],
"name": "Updated Eval",
"created_at": 1739314509,
"metadata": {"description": "Updated description"},
}
request:
curl: |
curl https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{"name": "Updated Eval", "metadata": {"description": "Updated description"}}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
eval = client.evals.update(
eval_id="eval_id",
)
print(eval.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const _eval = await client.evals.update('eval_id');
console.log(_eval.id);
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.evals.EvalUpdateParams;
import com.openai.models.evals.EvalUpdateResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
EvalUpdateResponse eval = client.evals().update("eval_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
eval_ = openai.evals.update("eval_id")
puts(eval_)
description: |
Update certain properties of an evaluation.
delete:
operationId: deleteEval
tags:
- Evals
summary: Delete an eval
parameters:
- name: eval_id
in: path
required: true
schema:
type: string
description: The ID of the evaluation to delete.
responses:
'200':
description: Successfully deleted the evaluation.
content:
application/json:
schema:
type: object
properties:
object:
type: string
example: eval.deleted
deleted:
type: boolean
example: true
eval_id:
type: string
example: eval_abc123
required:
- object
- deleted
- eval_id
'404':
description: Evaluation not found.
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
x-oaiMeta:
name: Delete an eval
group: evals
returns: A deletion confirmation object.
examples:
response: |
{
"object": "eval.deleted",
"deleted": true,
"eval_id": "eval_abc123"
}
request:
curl: |
curl https://api.openai.com/v1/evals/eval_abc123 \
-X DELETE \
-H "Authorization: Bearer $OPENAI_API_KEY"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
eval = client.evals.delete(
"eval_id",
)
print(eval.eval_id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const _eval = await client.evals.delete('eval_id');
console.log(_eval.eval_id);
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.evals.EvalDeleteParams;
import com.openai.models.evals.EvalDeleteResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
EvalDeleteResponse eval = client.evals().delete("eval_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
eval_ = openai.evals.delete("eval_id")
puts(eval_)
description: |
Delete an evaluation.
/evals/{eval_id}/runs:
get:
operationId: getEvalRuns
tags:
- Evals
summary: Get eval runs
parameters:
- name: eval_id
in: path
required: true
schema:
type: string
description: The ID of the evaluation to retrieve runs for.
- name: after
in: query
description: Identifier for the last run from the previous pagination request.
required: false
schema:
type: string
- name: limit
in: query
description: Number of runs to retrieve.
required: false
schema:
type: integer
default: 20
- name: order
in: query
description: >-
Sort order for runs by timestamp. Use `asc` for ascending order or `desc` for descending order.
Defaults to `asc`.
required: false
schema:
type: string
enum:
- asc
- desc
default: asc
- name: status
in: query
description: Filter runs by status. One of `queued` | `in_progress` | `failed` | `completed` | `canceled`.
required: false
schema:
type: string
enum:
- queued
- in_progress
- completed
- canceled
- failed
responses:
'200':
description: A list of runs for the evaluation
content:
application/json:
schema:
$ref: '#/components/schemas/EvalRunList'
x-oaiMeta:
name: Get eval runs
group: evals
returns: >-
A list of [EvalRun](https://platform.openai.com/docs/api-reference/evals/run-object) objects
matching the specified ID.
path: get-runs
examples:
response: |
{
"object": "list",
"data": [
{
"object": "eval.run",
"id": "evalrun_67e0c7d31560819090d60c0780591042",
"eval_id": "eval_67e0c726d560819083f19a957c4c640b",
"report_url": "https://platform.openai.com/evaluations/eval_67e0c726d560819083f19a957c4c640b",
"status": "completed",
"model": "o3-mini",
"name": "bulk_with_negative_examples_o3-mini",
"created_at": 1742784467,
"result_counts": {
"total": 1,
"errored": 0,
"failed": 0,
"passed": 1
},
"per_model_usage": [
{
"model_name": "o3-mini",
"invocation_count": 1,
"prompt_tokens": 563,
"completion_tokens": 874,
"total_tokens": 1437,
"cached_tokens": 0
}
],
"per_testing_criteria_results": [
{
"testing_criteria": "Push Notification Summary Grader-1808cd0b-eeec-4e0b-a519-337e79f4f5d1",
"passed": 1,
"failed": 0
}
],
"data_source": {
"type": "completions",
"source": {
"type": "file_content",
"content": [
{
"item": {
"notifications": "\n- New message from Sarah: \"Can you call me later?\"\n- Your package has been delivered!\n- Flash sale: 20% off electronics for the next 2 hours!\n"
}
}
]
},
"input_messages": {
"type": "template",
"template": [
{
"type": "message",
"role": "developer",
"content": {
"type": "input_text",
"text": "\n\n\n\nYou are a helpful assistant that takes in an array of push notifications and returns a collapsed summary of them.\nThe push notification will be provided as follows:\n<push_notifications>\n...notificationlist...\n</push_notifications>\n\nYou should return just the summary and nothing else.\n\n\nYou should return a summary that is concise and snappy.\n\n\nHere is an example of a good summary:\n<push_notifications>\n- Traffic alert: Accident reported on Main Street.- Package out for delivery: Expected by 5 PM.- New friend suggestion: Connect with Emma.\n</push_notifications>\n<summary>\nTraffic alert, package expected by 5pm, suggestion for new friend (Emily).\n</summary>\n\n\nHere is an example of a bad summary:\n<push_notifications>\n- Traffic alert: Accident reported on Main Street.- Package out for delivery: Expected by 5 PM.- New friend suggestion: Connect with Emma.\n</push_notifications>\n<summary>\nTraffic alert reported on main street. You have a package that will arrive by 5pm, Emily is a new friend suggested for you.\n</summary>\n"
}
},
{
"type": "message",
"role": "user",
"content": {
"type": "input_text",
"text": "<push_notifications>{{item.notifications}}</push_notifications>"
}
}
]
},
"model": "o3-mini",
"sampling_params": null
},
"error": null,
"metadata": {}
}
],
"first_id": "evalrun_67e0c7d31560819090d60c0780591042",
"last_id": "evalrun_67e0c7d31560819090d60c0780591042",
"has_more": true
}
request:
curl: |
curl https://api.openai.com/v1/evals/egroup_67abd54d9b0081909a86353f6fb9317a/runs \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.evals.runs.list(
eval_id="eval_id",
)
page = page.data[0]
print(page.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const runListResponse of client.evals.runs.list('eval_id')) {
console.log(runListResponse.id);
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.evals.runs.RunListPage;
import com.openai.models.evals.runs.RunListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunListPage page = client.evals().runs().list("eval_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.evals.runs.list("eval_id")
puts(page)
description: |
Get a list of runs for an evaluation.
post:
operationId: createEvalRun
tags:
- Evals
summary: Create eval run
parameters:
- in: path
name: eval_id
required: true
schema:
type: string
description: The ID of the evaluation to create a run for.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateEvalRunRequest'
responses:
'201':
description: Successfully created a run for the evaluation
content:
application/json:
schema:
$ref: '#/components/schemas/EvalRun'
'400':
description: Bad request (for example, missing eval object)
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
x-oaiMeta:
name: Create eval run
group: evals
returns: >-
The [EvalRun](https://platform.openai.com/docs/api-reference/evals/run-object) object matching the
specified ID.
examples:
response: |
{
"object": "eval.run",
"id": "evalrun_67e57965b480819094274e3a32235e4c",
"eval_id": "eval_67e579652b548190aaa83ada4b125f47",
"report_url": "https://platform.openai.com/evaluations/eval_67e579652b548190aaa83ada4b125f47&run_id=evalrun_67e57965b480819094274e3a32235e4c",
"status": "queued",
"model": "gpt-4o-mini",
"name": "gpt-4o-mini",
"created_at": 1743092069,
"result_counts": {
"total": 0,
"errored": 0,
"failed": 0,
"passed": 0
},
"per_model_usage": null,
"per_testing_criteria_results": null,
"data_source": {
"type": "completions",
"source": {
"type": "file_content",
"content": [
{
"item": {
"input": "Tech Company Launches Advanced Artificial Intelligence Platform",
"ground_truth": "Technology"
}
}
]
},
"input_messages": {
"type": "template",
"template": [
{
"type": "message",
"role": "developer",
"content": {
"type": "input_text",
"text": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\" \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\" \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\" \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\" \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\" \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n"
}
},
{
"type": "message",
"role": "user",
"content": {
"type": "input_text",
"text": "{{item.input}}"
}
}
]
},
"model": "gpt-4o-mini",
"sampling_params": {
"seed": 42,
"temperature": 1.0,
"top_p": 1.0,
"max_completions_tokens": 2048
}
},
"error": null,
"metadata": {}
}
request:
curl: |
curl https://api.openai.com/v1/evals/eval_67e579652b548190aaa83ada4b125f47/runs \
-X POST \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{"name":"gpt-4o-mini","data_source":{"type":"completions","input_messages":{"type":"template","template":[{"role":"developer","content":"Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\" \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\" \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\" \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\" \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\" \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n"} , {"role":"user","content":"{{item.input}}"}]} ,"sampling_params":{"temperature":1,"max_completions_tokens":2048,"top_p":1,"seed":42},"model":"gpt-4o-mini","source":{"type":"file_content","content":[{"item":{"input":"Tech Company Launches Advanced Artificial Intelligence Platform","ground_truth":"Technology"}}]}}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.evals.runs.create(
eval_id="eval_id",
data_source={
"source": {
"content": [{
"item": {
"foo": "bar"
}
}],
"type": "file_content",
},
"type": "jsonl",
},
)
print(run.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.evals.runs.create('eval_id', {
data_source: { source: { content: [{ item: { foo: 'bar' } }], type: 'file_content' }, type: 'jsonl' },
});
console.log(run.id);
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.core.JsonValue;
import com.openai.models.evals.runs.CreateEvalJsonlRunDataSource;
import com.openai.models.evals.runs.RunCreateParams;
import com.openai.models.evals.runs.RunCreateResponse;
import java.util.List;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunCreateParams params = RunCreateParams.builder()
.evalId("eval_id")
.dataSource(CreateEvalJsonlRunDataSource.builder()
.fileContentSource(List.of(CreateEvalJsonlRunDataSource.Source.FileContent.Content.builder()
.item(CreateEvalJsonlRunDataSource.Source.FileContent.Content.Item.builder()
.putAdditionalProperty("foo", JsonValue.from("bar"))
.build())
.build()))
.build())
.build();
RunCreateResponse run = client.evals().runs().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.evals.runs.create(
"eval_id",
data_source: {source: {content: [{item: {foo: "bar"}}], type: :file_content}, type: :jsonl}
)
puts(run)
description: >
Kicks off a new run for a given evaluation, specifying the data source, and what model configuration
to use to test. The datasource will be validated against the schema specified in the config of the
evaluation.
/evals/{eval_id}/runs/{run_id}:
get:
operationId: getEvalRun
tags:
- Evals
summary: Get an eval run
parameters:
- name: eval_id
in: path
required: true
schema:
type: string
description: The ID of the evaluation to retrieve runs for.
- name: run_id
in: path
required: true
schema:
type: string
description: The ID of the run to retrieve.
responses:
'200':
description: The evaluation run
content:
application/json:
schema:
$ref: '#/components/schemas/EvalRun'
x-oaiMeta:
name: Get an eval run
group: evals
returns: >-
The [EvalRun](https://platform.openai.com/docs/api-reference/evals/run-object) object matching the
specified ID.
path: get
examples:
response: |
{
"object": "eval.run",
"id": "evalrun_67abd54d60ec8190832b46859da808f7",
"eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
"report_url": "https://platform.openai.com/evaluations/eval_67abd54d9b0081909a86353f6fb9317a?run_id=evalrun_67abd54d60ec8190832b46859da808f7",
"status": "queued",
"model": "gpt-4o-mini",
"name": "gpt-4o-mini",
"created_at": 1743092069,
"result_counts": {
"total": 0,
"errored": 0,
"failed": 0,
"passed": 0
},
"per_model_usage": null,
"per_testing_criteria_results": null,
"data_source": {
"type": "completions",
"source": {
"type": "file_content",
"content": [
{
"item": {
"input": "Tech Company Launches Advanced Artificial Intelligence Platform",
"ground_truth": "Technology"
}
},
{
"item": {
"input": "Central Bank Increases Interest Rates Amid Inflation Concerns",
"ground_truth": "Markets"
}
},
{
"item": {
"input": "International Summit Addresses Climate Change Strategies",
"ground_truth": "World"
}
},
{
"item": {
"input": "Major Retailer Reports Record-Breaking Holiday Sales",
"ground_truth": "Business"
}
},
{
"item": {
"input": "National Team Qualifies for World Championship Finals",
"ground_truth": "Sports"
}
},
{
"item": {
"input": "Stock Markets Rally After Positive Economic Data Released",
"ground_truth": "Markets"
}
},
{
"item": {
"input": "Global Manufacturer Announces Merger with Competitor",
"ground_truth": "Business"
}
},
{
"item": {
"input": "Breakthrough in Renewable Energy Technology Unveiled",
"ground_truth": "Technology"
}
},
{
"item": {
"input": "World Leaders Sign Historic Climate Agreement",
"ground_truth": "World"
}
},
{
"item": {
"input": "Professional Athlete Sets New Record in Championship Event",
"ground_truth": "Sports"
}
},
{
"item": {
"input": "Financial Institutions Adapt to New Regulatory Requirements",
"ground_truth": "Business"
}
},
{
"item": {
"input": "Tech Conference Showcases Advances in Artificial Intelligence",
"ground_truth": "Technology"
}
},
{
"item": {
"input": "Global Markets Respond to Oil Price Fluctuations",
"ground_truth": "Markets"
}
},
{
"item": {
"input": "International Cooperation Strengthened Through New Treaty",
"ground_truth": "World"
}
},
{
"item": {
"input": "Sports League Announces Revised Schedule for Upcoming Season",
"ground_truth": "Sports"
}
}
]
},
"input_messages": {
"type": "template",
"template": [
{
"type": "message",
"role": "developer",
"content": {
"type": "input_text",
"text": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\" \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\" \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\" \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\" \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\" \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n"
}
},
{
"type": "message",
"role": "user",
"content": {
"type": "input_text",
"text": "{{item.input}}"
}
}
]
},
"model": "gpt-4o-mini",
"sampling_params": {
"seed": 42,
"temperature": 1.0,
"top_p": 1.0,
"max_completions_tokens": 2048
}
},
"error": null,
"metadata": {}
}
request:
curl: >
curl
https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a/runs/evalrun_67abd54d60ec8190832b46859da808f7
\
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.evals.runs.retrieve(
run_id="run_id",
eval_id="eval_id",
)
print(run.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.evals.runs.retrieve('run_id', { eval_id: 'eval_id' });
console.log(run.id);
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.evals.runs.RunRetrieveParams;
import com.openai.models.evals.runs.RunRetrieveResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunRetrieveParams params = RunRetrieveParams.builder()
.evalId("eval_id")
.runId("run_id")
.build();
RunRetrieveResponse run = client.evals().runs().retrieve(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.evals.runs.retrieve("run_id", eval_id: "eval_id")
puts(run)
description: |
Get an evaluation run by ID.
post:
operationId: cancelEvalRun
tags:
- Evals
summary: Cancel eval run
parameters:
- name: eval_id
in: path
required: true
schema:
type: string
description: The ID of the evaluation whose run you want to cancel.
- name: run_id
in: path
required: true
schema:
type: string
description: The ID of the run to cancel.
responses:
'200':
description: The canceled eval run object
content:
application/json:
schema:
$ref: '#/components/schemas/EvalRun'
x-oaiMeta:
name: Cancel eval run
group: evals
returns: >-
The updated [EvalRun](https://platform.openai.com/docs/api-reference/evals/run-object) object
reflecting that the run is canceled.
path: post
examples:
response: |
{
"object": "eval.run",
"id": "evalrun_67abd54d60ec8190832b46859da808f7",
"eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
"report_url": "https://platform.openai.com/evaluations/eval_67abd54d9b0081909a86353f6fb9317a?run_id=evalrun_67abd54d60ec8190832b46859da808f7",
"status": "canceled",
"model": "gpt-4o-mini",
"name": "gpt-4o-mini",
"created_at": 1743092069,
"result_counts": {
"total": 0,
"errored": 0,
"failed": 0,
"passed": 0
},
"per_model_usage": null,
"per_testing_criteria_results": null,
"data_source": {
"type": "completions",
"source": {
"type": "file_content",
"content": [
{
"item": {
"input": "Tech Company Launches Advanced Artificial Intelligence Platform",
"ground_truth": "Technology"
}
},
{
"item": {
"input": "Central Bank Increases Interest Rates Amid Inflation Concerns",
"ground_truth": "Markets"
}
},
{
"item": {
"input": "International Summit Addresses Climate Change Strategies",
"ground_truth": "World"
}
},
{
"item": {
"input": "Major Retailer Reports Record-Breaking Holiday Sales",
"ground_truth": "Business"
}
},
{
"item": {
"input": "National Team Qualifies for World Championship Finals",
"ground_truth": "Sports"
}
},
{
"item": {
"input": "Stock Markets Rally After Positive Economic Data Released",
"ground_truth": "Markets"
}
},
{
"item": {
"input": "Global Manufacturer Announces Merger with Competitor",
"ground_truth": "Business"
}
},
{
"item": {
"input": "Breakthrough in Renewable Energy Technology Unveiled",
"ground_truth": "Technology"
}
},
{
"item": {
"input": "World Leaders Sign Historic Climate Agreement",
"ground_truth": "World"
}
},
{
"item": {
"input": "Professional Athlete Sets New Record in Championship Event",
"ground_truth": "Sports"
}
},
{
"item": {
"input": "Financial Institutions Adapt to New Regulatory Requirements",
"ground_truth": "Business"
}
},
{
"item": {
"input": "Tech Conference Showcases Advances in Artificial Intelligence",
"ground_truth": "Technology"
}
},
{
"item": {
"input": "Global Markets Respond to Oil Price Fluctuations",
"ground_truth": "Markets"
}
},
{
"item": {
"input": "International Cooperation Strengthened Through New Treaty",
"ground_truth": "World"
}
},
{
"item": {
"input": "Sports League Announces Revised Schedule for Upcoming Season",
"ground_truth": "Sports"
}
}
]
},
"input_messages": {
"type": "template",
"template": [
{
"type": "message",
"role": "developer",
"content": {
"type": "input_text",
"text": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\" \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\" \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\" \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\" \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\" \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n"
}
},
{
"type": "message",
"role": "user",
"content": {
"type": "input_text",
"text": "{{item.input}}"
}
}
]
},
"model": "gpt-4o-mini",
"sampling_params": {
"seed": 42,
"temperature": 1.0,
"top_p": 1.0,
"max_completions_tokens": 2048
}
},
"error": null,
"metadata": {}
}
request:
curl: >
curl
https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a/runs/evalrun_67abd54d60ec8190832b46859da808f7/cancel
\
-X POST \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.evals.runs.cancel(
run_id="run_id",
eval_id="eval_id",
)
print(response.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.evals.runs.cancel('run_id', { eval_id: 'eval_id' });
console.log(response.id);
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.evals.runs.RunCancelParams;
import com.openai.models.evals.runs.RunCancelResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunCancelParams params = RunCancelParams.builder()
.evalId("eval_id")
.runId("run_id")
.build();
RunCancelResponse response = client.evals().runs().cancel(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.evals.runs.cancel("run_id", eval_id: "eval_id")
puts(response)
description: |
Cancel an ongoing evaluation run.
delete:
operationId: deleteEvalRun
tags:
- Evals
summary: Delete eval run
parameters:
- name: eval_id
in: path
required: true
schema:
type: string
description: The ID of the evaluation to delete the run from.
- name: run_id
in: path
required: true
schema:
type: string
description: The ID of the run to delete.
responses:
'200':
description: Successfully deleted the eval run
content:
application/json:
schema:
type: object
properties:
object:
type: string
example: eval.run.deleted
deleted:
type: boolean
example: true
run_id:
type: string
example: evalrun_677469f564d48190807532a852da3afb
'404':
description: Run not found
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
x-oaiMeta:
name: Delete eval run
group: evals
returns: An object containing the status of the delete operation.
path: delete
examples:
response: |
{
"object": "eval.run.deleted",
"deleted": true,
"run_id": "evalrun_abc456"
}
request:
curl: |
curl https://api.openai.com/v1/evals/eval_123abc/runs/evalrun_abc456 \
-X DELETE \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.evals.runs.delete(
run_id="run_id",
eval_id="eval_id",
)
print(run.run_id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.evals.runs.delete('run_id', { eval_id: 'eval_id' });
console.log(run.run_id);
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.evals.runs.RunDeleteParams;
import com.openai.models.evals.runs.RunDeleteResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunDeleteParams params = RunDeleteParams.builder()
.evalId("eval_id")
.runId("run_id")
.build();
RunDeleteResponse run = client.evals().runs().delete(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.evals.runs.delete("run_id", eval_id: "eval_id")
puts(run)
description: |
Delete an eval run.
/evals/{eval_id}/runs/{run_id}/output_items:
get:
operationId: getEvalRunOutputItems
tags:
- Evals
summary: Get eval run output items
parameters:
- name: eval_id
in: path
required: true
schema:
type: string
description: The ID of the evaluation to retrieve runs for.
- name: run_id
in: path
required: true
schema:
type: string
description: The ID of the run to retrieve output items for.
- name: after
in: query
description: Identifier for the last output item from the previous pagination request.
required: false
schema:
type: string
- name: limit
in: query
description: Number of output items to retrieve.
required: false
schema:
type: integer
default: 20
- name: status
in: query
description: |
Filter output items by status. Use `failed` to filter by failed output
items or `pass` to filter by passed output items.
required: false
schema:
type: string
enum:
- fail
- pass
- name: order
in: query
description: >-
Sort order for output items by timestamp. Use `asc` for ascending order or `desc` for descending
order. Defaults to `asc`.
required: false
schema:
type: string
enum:
- asc
- desc
default: asc
responses:
'200':
description: A list of output items for the evaluation run
content:
application/json:
schema:
$ref: '#/components/schemas/EvalRunOutputItemList'
x-oaiMeta:
name: Get eval run output items
group: evals
returns: >-
A list of
[EvalRunOutputItem](https://platform.openai.com/docs/api-reference/evals/run-output-item-object)
objects matching the specified ID.
path: get
examples:
response: |
{
"object": "list",
"data": [
{
"object": "eval.run.output_item",
"id": "outputitem_67e5796c28e081909917bf79f6e6214d",
"created_at": 1743092076,
"run_id": "evalrun_67abd54d60ec8190832b46859da808f7",
"eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
"status": "pass",
"datasource_item_id": 5,
"datasource_item": {
"input": "Stock Markets Rally After Positive Economic Data Released",
"ground_truth": "Markets"
},
"results": [
{
"name": "String check-a2486074-d803-4445-b431-ad2262e85d47",
"sample": null,
"passed": true,
"score": 1.0
}
],
"sample": {
"input": [
{
"role": "developer",
"content": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\" \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\" \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\" \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\" \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\" \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n",
"tool_call_id": null,
"tool_calls": null,
"function_call": null
},
{
"role": "user",
"content": "Stock Markets Rally After Positive Economic Data Released",
"tool_call_id": null,
"tool_calls": null,
"function_call": null
}
],
"output": [
{
"role": "assistant",
"content": "Markets",
"tool_call_id": null,
"tool_calls": null,
"function_call": null
}
],
"finish_reason": "stop",
"model": "gpt-4o-mini-2024-07-18",
"usage": {
"total_tokens": 325,
"completion_tokens": 2,
"prompt_tokens": 323,
"cached_tokens": 0
},
"error": null,
"temperature": 1.0,
"max_completion_tokens": 2048,
"top_p": 1.0,
"seed": 42
}
}
],
"first_id": "outputitem_67e5796c28e081909917bf79f6e6214d",
"last_id": "outputitem_67e5796c28e081909917bf79f6e6214d",
"has_more": true
}
request:
curl: >
curl
https://api.openai.com/v1/evals/egroup_67abd54d9b0081909a86353f6fb9317a/runs/erun_67abd54d60ec8190832b46859da808f7/output_items
\
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.evals.runs.output_items.list(
run_id="run_id",
eval_id="eval_id",
)
page = page.data[0]
print(page.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const outputItemListResponse of client.evals.runs.outputItems.list('run_id', {
eval_id: 'eval_id',
})) {
console.log(outputItemListResponse.id);
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.evals.runs.outputitems.OutputItemListPage;
import com.openai.models.evals.runs.outputitems.OutputItemListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
OutputItemListParams params = OutputItemListParams.builder()
.evalId("eval_id")
.runId("run_id")
.build();
OutputItemListPage page = client.evals().runs().outputItems().list(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.evals.runs.output_items.list("run_id", eval_id: "eval_id")
puts(page)
description: |
Get a list of output items for an evaluation run.
/evals/{eval_id}/runs/{run_id}/output_items/{output_item_id}:
get:
operationId: getEvalRunOutputItem
tags:
- Evals
summary: Get an output item of an eval run
parameters:
- name: eval_id
in: path
required: true
schema:
type: string
description: The ID of the evaluation to retrieve runs for.
- name: run_id
in: path
required: true
schema:
type: string
description: The ID of the run to retrieve.
- name: output_item_id
in: path
required: true
schema:
type: string
description: The ID of the output item to retrieve.
responses:
'200':
description: The evaluation run output item
content:
application/json:
schema:
$ref: '#/components/schemas/EvalRunOutputItem'
x-oaiMeta:
name: Get an output item of an eval run
group: evals
returns: >-
The [EvalRunOutputItem](https://platform.openai.com/docs/api-reference/evals/run-output-item-object)
object matching the specified ID.
path: get
examples:
response: |
{
"object": "eval.run.output_item",
"id": "outputitem_67e5796c28e081909917bf79f6e6214d",
"created_at": 1743092076,
"run_id": "evalrun_67abd54d60ec8190832b46859da808f7",
"eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
"status": "pass",
"datasource_item_id": 5,
"datasource_item": {
"input": "Stock Markets Rally After Positive Economic Data Released",
"ground_truth": "Markets"
},
"results": [
{
"name": "String check-a2486074-d803-4445-b431-ad2262e85d47",
"sample": null,
"passed": true,
"score": 1.0
}
],
"sample": {
"input": [
{
"role": "developer",
"content": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\" \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\" \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\" \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\" \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\" \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n",
"tool_call_id": null,
"tool_calls": null,
"function_call": null
},
{
"role": "user",
"content": "Stock Markets Rally After Positive Economic Data Released",
"tool_call_id": null,
"tool_calls": null,
"function_call": null
}
],
"output": [
{
"role": "assistant",
"content": "Markets",
"tool_call_id": null,
"tool_calls": null,
"function_call": null
}
],
"finish_reason": "stop",
"model": "gpt-4o-mini-2024-07-18",
"usage": {
"total_tokens": 325,
"completion_tokens": 2,
"prompt_tokens": 323,
"cached_tokens": 0
},
"error": null,
"temperature": 1.0,
"max_completion_tokens": 2048,
"top_p": 1.0,
"seed": 42
}
}
request:
curl: >
curl
https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a/runs/evalrun_67abd54d60ec8190832b46859da808f7/output_items/outputitem_67abd55eb6548190bb580745d5644a33
\
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
output_item = client.evals.runs.output_items.retrieve(
output_item_id="output_item_id",
eval_id="eval_id",
run_id="run_id",
)
print(output_item.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const outputItem = await client.evals.runs.outputItems.retrieve('output_item_id', {
eval_id: 'eval_id',
run_id: 'run_id',
});
console.log(outputItem.id);
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.evals.runs.outputitems.OutputItemRetrieveParams;
import com.openai.models.evals.runs.outputitems.OutputItemRetrieveResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
OutputItemRetrieveParams params = OutputItemRetrieveParams.builder()
.evalId("eval_id")
.runId("run_id")
.outputItemId("output_item_id")
.build();
OutputItemRetrieveResponse outputItem = client.evals().runs().outputItems().retrieve(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
output_item = openai.evals.runs.output_items.retrieve("output_item_id", eval_id: "eval_id",
run_id: "run_id")
puts(output_item)
description: |
Get an evaluation run output item by ID.
/files:
get:
operationId: listFiles
tags:
- Files
summary: List files
parameters:
- in: query
name: purpose
required: false
schema:
type: string
description: Only return files with the given purpose.
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 10,000, and the
default is 10,000.
required: false
schema:
type: integer
default: 10000
- name: order
in: query
description: >
Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
descending order.
schema:
type: string
default: desc
enum:
- asc
- desc
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
schema:
type: string
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListFilesResponse'
x-oaiMeta:
name: List files
group: files
returns: A list of [File](https://platform.openai.com/docs/api-reference/files/object) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "file-abc123",
"object": "file",
"bytes": 175,
"created_at": 1613677385,
"expires_at": 1677614202,
"filename": "salesOverview.pdf",
"purpose": "assistants",
},
{
"id": "file-abc456",
"object": "file",
"bytes": 140,
"created_at": 1613779121,
"expires_at": 1677614202,
"filename": "puppy.jsonl",
"purpose": "fine-tune",
}
],
"first_id": "file-abc123",
"last_id": "file-abc456",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/files \
-H "Authorization: Bearer $OPENAI_API_KEY"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.files.list()
page = page.data[0]
print(page)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const fileObject of client.files.list()) {
console.log(fileObject);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.Files.List(context.TODO(), openai.FileListParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.files.FileListPage;
import com.openai.models.files.FileListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileListPage page = client.files().list();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.files.list
puts(page)
description: Returns a list of files.
post:
operationId: createFile
tags:
- Files
summary: Upload file
requestBody:
required: true
content:
multipart/form-data:
schema:
$ref: '#/components/schemas/CreateFileRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/OpenAIFile'
x-oaiMeta:
name: Upload file
group: files
returns: The uploaded [File](https://platform.openai.com/docs/api-reference/files/object) object.
examples:
response: |
{
"id": "file-abc123",
"object": "file",
"bytes": 120000,
"created_at": 1677610602,
"expires_at": 1677614202,
"filename": "mydata.jsonl",
"purpose": "fine-tune",
}
request:
curl: |
curl https://api.openai.com/v1/files \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-F purpose="fine-tune" \
-F file="@mydata.jsonl"
-F expires_after[anchor]="created_at"
-F expires_after[seconds]=3600
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
file_object = client.files.create(
file=b"raw file contents",
purpose="assistants",
)
print(file_object.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const fileObject = await client.files.create({
file: fs.createReadStream('fine-tune.jsonl'),
purpose: 'assistants',
});
console.log(fileObject.id);
go: |
package main
import (
"bytes"
"context"
"fmt"
"io"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
fileObject, err := client.Files.New(context.TODO(), openai.FileNewParams{
File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
Purpose: openai.FilePurposeAssistants,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", fileObject.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.files.FileCreateParams;
import com.openai.models.files.FileObject;
import com.openai.models.files.FilePurpose;
import java.io.ByteArrayInputStream;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileCreateParams params = FileCreateParams.builder()
.file(ByteArrayInputStream("some content".getBytes()))
.purpose(FilePurpose.ASSISTANTS)
.build();
FileObject fileObject = client.files().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
file_object = openai.files.create(file: Pathname(__FILE__), purpose: :assistants)
puts(file_object)
description: >
Upload a file that can be used across various endpoints. Individual files can be up to 512 MB, and the
size of all files uploaded by one organization can be up to 1 TB.
The Assistants API supports files up to 2 million tokens and of specific file types. See the
[Assistants Tools guide](https://platform.openai.com/docs/assistants/tools) for details.
The Fine-tuning API only supports `.jsonl` files. The input also has certain required formats for
fine-tuning [chat](https://platform.openai.com/docs/api-reference/fine-tuning/chat-input) or
[completions](https://platform.openai.com/docs/api-reference/fine-tuning/completions-input) models.
The Batch API only supports `.jsonl` files up to 200 MB in size. The input also has a specific
required [format](https://platform.openai.com/docs/api-reference/batch/request-input).
Please [contact us](https://help.openai.com/) if you need to increase these storage limits.
/files/{file_id}:
delete:
operationId: deleteFile
tags:
- Files
summary: Delete file
parameters:
- in: path
name: file_id
required: true
schema:
type: string
description: The ID of the file to use for this request.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/DeleteFileResponse'
x-oaiMeta:
name: Delete file
group: files
returns: Deletion status.
examples:
response: |
{
"id": "file-abc123",
"object": "file",
"deleted": true
}
request:
curl: |
curl https://api.openai.com/v1/files/file-abc123 \
-X DELETE \
-H "Authorization: Bearer $OPENAI_API_KEY"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
file_deleted = client.files.delete(
"file_id",
)
print(file_deleted.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const fileDeleted = await client.files.delete('file_id');
console.log(fileDeleted.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
fileDeleted, err := client.Files.Delete(context.TODO(), "file_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", fileDeleted.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.files.FileDeleteParams;
import com.openai.models.files.FileDeleted;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileDeleted fileDeleted = client.files().delete("file_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
file_deleted = openai.files.delete("file_id")
puts(file_deleted)
description: Delete a file.
get:
operationId: retrieveFile
tags:
- Files
summary: Retrieve file
parameters:
- in: path
name: file_id
required: true
schema:
type: string
description: The ID of the file to use for this request.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/OpenAIFile'
x-oaiMeta:
name: Retrieve file
group: files
returns: >-
The [File](https://platform.openai.com/docs/api-reference/files/object) object matching the
specified ID.
examples:
response: |
{
"id": "file-abc123",
"object": "file",
"bytes": 120000,
"created_at": 1677610602,
"expires_at": 1677614202,
"filename": "mydata.jsonl",
"purpose": "fine-tune",
}
request:
curl: |
curl https://api.openai.com/v1/files/file-abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
file_object = client.files.retrieve(
"file_id",
)
print(file_object.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const fileObject = await client.files.retrieve('file_id');
console.log(fileObject.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
fileObject, err := client.Files.Get(context.TODO(), "file_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", fileObject.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.files.FileObject;
import com.openai.models.files.FileRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileObject fileObject = client.files().retrieve("file_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
file_object = openai.files.retrieve("file_id")
puts(file_object)
description: Returns information about a specific file.
/files/{file_id}/content:
get:
operationId: downloadFile
tags:
- Files
summary: Retrieve file content
parameters:
- in: path
name: file_id
required: true
schema:
type: string
description: The ID of the file to use for this request.
responses:
'200':
description: OK
content:
application/json:
schema:
type: string
x-oaiMeta:
name: Retrieve file content
group: files
returns: The file content.
examples:
response: ''
request:
curl: |
curl https://api.openai.com/v1/files/file-abc123/content \
-H "Authorization: Bearer $OPENAI_API_KEY" > file.jsonl
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.files.content(
"file_id",
)
print(response)
content = response.read()
print(content)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.files.content('file_id');
console.log(response);
const content = await response.blob();
console.log(content);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
response, err := client.Files.Content(context.TODO(), "file_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", response)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.core.http.HttpResponse;
import com.openai.models.files.FileContentParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
HttpResponse response = client.files().content("file_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.files.content("file_id")
puts(response)
description: Returns the contents of the specified file.
/fine_tuning/alpha/graders/run:
post:
operationId: runGrader
tags:
- Fine-tuning
summary: Run grader
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/RunGraderRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/RunGraderResponse'
x-oaiMeta:
name: Run grader
beta: true
group: graders
returns: The results from the grader run.
examples:
response: |
{
"reward": 1.0,
"metadata": {
"name": "Example score model grader",
"type": "score_model",
"errors": {
"formula_parse_error": false,
"sample_parse_error": false,
"truncated_observation_error": false,
"unresponsive_reward_error": false,
"invalid_variable_error": false,
"other_error": false,
"python_grader_server_error": false,
"python_grader_server_error_type": null,
"python_grader_runtime_error": false,
"python_grader_runtime_error_details": null,
"model_grader_server_error": false,
"model_grader_refusal_error": false,
"model_grader_parse_error": false,
"model_grader_server_error_details": null
},
"execution_time": 4.365238428115845,
"scores": {},
"token_usage": {
"prompt_tokens": 190,
"total_tokens": 324,
"completion_tokens": 134,
"cached_tokens": 0
},
"sampled_model_name": "gpt-4o-2024-08-06"
},
"sub_rewards": {},
"model_grader_token_usage_per_model": {
"gpt-4o-2024-08-06": {
"prompt_tokens": 190,
"total_tokens": 324,
"completion_tokens": 134,
"cached_tokens": 0
}
}
}
request:
curl: |
curl -X POST https://api.openai.com/v1/fine_tuning/alpha/graders/run \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"grader": {
"type": "score_model",
"name": "Example score model grader",
"input": [
{
"role": "user",
"content": "Score how close the reference answer is to the model answer. Score 1.0 if they are the same and 0.0 if they are different. Return just a floating point score\n\nReference answer: {{item.reference_answer}}\n\nModel answer: {{sample.output_text}}"
}
],
"model": "gpt-4o-2024-08-06",
"sampling_params": {
"temperature": 1,
"top_p": 1,
"seed": 42
}
},
"item": {
"reference_answer": "fuzzy wuzzy was a bear"
},
"model_sample": "fuzzy wuzzy was a bear"
}'
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.fineTuning.alpha.graders.run({
grader: { input: 'input', name: 'name', operation: 'eq', reference: 'reference', type: 'string_check' },
model_sample: 'model_sample',
});
console.log(response.metadata);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.fine_tuning.alpha.graders.run(
grader={
"input": "input",
"name": "name",
"operation": "eq",
"reference": "reference",
"type": "string_check",
},
model_sample="model_sample",
)
print(response.metadata)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
response, err := client.FineTuning.Alpha.Graders.Run(context.TODO(), openai.FineTuningAlphaGraderRunParams{
Grader: openai.FineTuningAlphaGraderRunParamsGraderUnion{
OfStringCheck: &openai.StringCheckGraderParam{
Input: "input",
Name: "name",
Operation: openai.StringCheckGraderOperationEq,
Reference: "reference",
},
},
ModelSample: "model_sample",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", response.Metadata)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.alpha.graders.GraderRunParams;
import com.openai.models.finetuning.alpha.graders.GraderRunResponse;
import com.openai.models.graders.gradermodels.StringCheckGrader;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
GraderRunParams params = GraderRunParams.builder()
.grader(StringCheckGrader.builder()
.input("input")
.name("name")
.operation(StringCheckGrader.Operation.EQ)
.reference("reference")
.build())
.modelSample("model_sample")
.build();
GraderRunResponse response = client.fineTuning().alpha().graders().run(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.fine_tuning.alpha.graders.run(
grader: {input: "input", name: "name", operation: :eq, reference: "reference", type: :string_check},
model_sample: "model_sample"
)
puts(response)
description: |
Run a grader.
/fine_tuning/alpha/graders/validate:
post:
operationId: validateGrader
tags:
- Fine-tuning
summary: Validate grader
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ValidateGraderRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ValidateGraderResponse'
x-oaiMeta:
name: Validate grader
beta: true
group: graders
returns: The validated grader object.
examples:
response: |
{
"grader": {
"type": "string_check",
"name": "Example string check grader",
"input": "{{sample.output_text}}",
"reference": "{{item.label}}",
"operation": "eq"
}
}
request:
curl: |
curl https://api.openai.com/v1/fine_tuning/alpha/graders/validate \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"grader": {
"type": "string_check",
"name": "Example string check grader",
"input": "{{sample.output_text}}",
"reference": "{{item.label}}",
"operation": "eq"
}
}'
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.fineTuning.alpha.graders.validate({
grader: { input: 'input', name: 'name', operation: 'eq', reference: 'reference', type: 'string_check' },
});
console.log(response.grader);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.fine_tuning.alpha.graders.validate(
grader={
"input": "input",
"name": "name",
"operation": "eq",
"reference": "reference",
"type": "string_check",
},
)
print(response.grader)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
response, err := client.FineTuning.Alpha.Graders.Validate(context.TODO(), openai.FineTuningAlphaGraderValidateParams{
Grader: openai.FineTuningAlphaGraderValidateParamsGraderUnion{
OfStringCheckGrader: &openai.StringCheckGraderParam{
Input: "input",
Name: "name",
Operation: openai.StringCheckGraderOperationEq,
Reference: "reference",
},
},
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", response.Grader)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.alpha.graders.GraderValidateParams;
import com.openai.models.finetuning.alpha.graders.GraderValidateResponse;
import com.openai.models.graders.gradermodels.StringCheckGrader;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
GraderValidateParams params = GraderValidateParams.builder()
.grader(StringCheckGrader.builder()
.input("input")
.name("name")
.operation(StringCheckGrader.Operation.EQ)
.reference("reference")
.build())
.build();
GraderValidateResponse response = client.fineTuning().alpha().graders().validate(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.fine_tuning.alpha.graders.validate(
grader: {input: "input", name: "name", operation: :eq, reference: "reference", type: :string_check}
)
puts(response)
description: |
Validate a grader.
/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions:
get:
operationId: listFineTuningCheckpointPermissions
tags:
- Fine-tuning
summary: List checkpoint permissions
parameters:
- in: path
name: fine_tuned_model_checkpoint
required: true
schema:
type: string
example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
description: |
The ID of the fine-tuned model checkpoint to get permissions for.
- name: project_id
in: query
description: The ID of the project to get permissions for.
required: false
schema:
type: string
- name: after
in: query
description: Identifier for the last permission ID from the previous pagination request.
required: false
schema:
type: string
- name: limit
in: query
description: Number of permissions to retrieve.
required: false
schema:
type: integer
default: 10
- name: order
in: query
description: The order in which to retrieve permissions.
required: false
schema:
type: string
enum:
- ascending
- descending
default: descending
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListFineTuningCheckpointPermissionResponse'
x-oaiMeta:
name: List checkpoint permissions
group: fine-tuning
returns: >-
A list of fine-tuned model checkpoint [permission
objects](https://platform.openai.com/docs/api-reference/fine-tuning/permission-object) for a
fine-tuned model checkpoint.
examples:
response: |
{
"object": "list",
"data": [
{
"object": "checkpoint.permission",
"id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
"created_at": 1721764867,
"project_id": "proj_abGMw1llN8IrBb6SvvY5A1iH"
},
{
"object": "checkpoint.permission",
"id": "cp_enQCFmOTGj3syEpYVhBRLTSy",
"created_at": 1721764800,
"project_id": "proj_iqGMw1llN8IrBb6SvvY5A1oF"
},
],
"first_id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
"last_id": "cp_enQCFmOTGj3syEpYVhBRLTSy",
"has_more": false
}
request:
curl: >
curl
https://api.openai.com/v1/fine_tuning/checkpoints/ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd/permissions
\
-H "Authorization: Bearer $OPENAI_API_KEY"
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const permission = await
client.fineTuning.checkpoints.permissions.retrieve('ft-AF1WoRqd3aJAHsqc9NY7iL8F');
console.log(permission.first_id);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
permission = client.fine_tuning.checkpoints.permissions.retrieve(
fine_tuned_model_checkpoint="ft-AF1WoRqd3aJAHsqc9NY7iL8F",
)
print(permission.first_id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
permission, err := client.FineTuning.Checkpoints.Permissions.Get(
context.TODO(),
"ft-AF1WoRqd3aJAHsqc9NY7iL8F",
openai.FineTuningCheckpointPermissionGetParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", permission.FirstID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.checkpoints.permissions.PermissionRetrieveParams;
import com.openai.models.finetuning.checkpoints.permissions.PermissionRetrieveResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
PermissionRetrieveResponse permission = client.fineTuning().checkpoints().permissions().retrieve("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
permission = openai.fine_tuning.checkpoints.permissions.retrieve("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
puts(permission)
description: |
**NOTE:** This endpoint requires an [admin API key](../admin-api-keys).
Organization owners can use this endpoint to view all permissions for a fine-tuned model checkpoint.
post:
operationId: createFineTuningCheckpointPermission
tags:
- Fine-tuning
summary: Create checkpoint permissions
parameters:
- in: path
name: fine_tuned_model_checkpoint
required: true
schema:
type: string
example: ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd
description: |
The ID of the fine-tuned model checkpoint to create a permission for.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateFineTuningCheckpointPermissionRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListFineTuningCheckpointPermissionResponse'
x-oaiMeta:
name: Create checkpoint permissions
group: fine-tuning
returns: >-
A list of fine-tuned model checkpoint [permission
objects](https://platform.openai.com/docs/api-reference/fine-tuning/permission-object) for a
fine-tuned model checkpoint.
examples:
response: |
{
"object": "list",
"data": [
{
"object": "checkpoint.permission",
"id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
"created_at": 1721764867,
"project_id": "proj_abGMw1llN8IrBb6SvvY5A1iH"
}
],
"first_id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
"last_id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
"has_more": false
}
request:
curl: >
curl
https://api.openai.com/v1/fine_tuning/checkpoints/ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd/permissions
\
-H "Authorization: Bearer $OPENAI_API_KEY"
-d '{"project_ids": ["proj_abGMw1llN8IrBb6SvvY5A1iH"]}'
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const permissionCreateResponse of client.fineTuning.checkpoints.permissions.create(
'ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd',
{ project_ids: ['string'] },
)) {
console.log(permissionCreateResponse.id);
}
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.fine_tuning.checkpoints.permissions.create(
fine_tuned_model_checkpoint="ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd",
project_ids=["string"],
)
page = page.data[0]
print(page.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.FineTuning.Checkpoints.Permissions.New(
context.TODO(),
"ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd",
openai.FineTuningCheckpointPermissionNewParams{
ProjectIDs: []string{"string"},
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.checkpoints.permissions.PermissionCreatePage;
import com.openai.models.finetuning.checkpoints.permissions.PermissionCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
PermissionCreateParams params = PermissionCreateParams.builder()
.fineTunedModelCheckpoint("ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd")
.addProjectId("string")
.build();
PermissionCreatePage page = client.fineTuning().checkpoints().permissions().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.fine_tuning.checkpoints.permissions.create(
"ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd",
project_ids: ["string"]
)
puts(page)
description: |
**NOTE:** Calling this endpoint requires an [admin API key](../admin-api-keys).
This enables organization owners to share fine-tuned models with other projects in their organization.
/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions/{permission_id}:
delete:
operationId: deleteFineTuningCheckpointPermission
tags:
- Fine-tuning
summary: Delete checkpoint permission
parameters:
- in: path
name: fine_tuned_model_checkpoint
required: true
schema:
type: string
example: ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd
description: |
The ID of the fine-tuned model checkpoint to delete a permission for.
- in: path
name: permission_id
required: true
schema:
type: string
example: cp_zc4Q7MP6XxulcVzj4MZdwsAB
description: |
The ID of the fine-tuned model checkpoint permission to delete.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/DeleteFineTuningCheckpointPermissionResponse'
x-oaiMeta:
name: Delete checkpoint permission
group: fine-tuning
returns: >-
The deletion status of the fine-tuned model checkpoint [permission
object](https://platform.openai.com/docs/api-reference/fine-tuning/permission-object).
examples:
response: |
{
"object": "checkpoint.permission",
"id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
"deleted": true
}
request:
curl: >
curl
https://api.openai.com/v1/fine_tuning/checkpoints/ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd/permissions/cp_zc4Q7MP6XxulcVzj4MZdwsAB
\
-H "Authorization: Bearer $OPENAI_API_KEY"
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const permission = await
client.fineTuning.checkpoints.permissions.delete('cp_zc4Q7MP6XxulcVzj4MZdwsAB', {
fine_tuned_model_checkpoint: 'ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd',
});
console.log(permission.id);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
permission = client.fine_tuning.checkpoints.permissions.delete(
permission_id="cp_zc4Q7MP6XxulcVzj4MZdwsAB",
fine_tuned_model_checkpoint="ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd",
)
print(permission.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
permission, err := client.FineTuning.Checkpoints.Permissions.Delete(
context.TODO(),
"ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd",
"cp_zc4Q7MP6XxulcVzj4MZdwsAB",
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", permission.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.checkpoints.permissions.PermissionDeleteParams;
import com.openai.models.finetuning.checkpoints.permissions.PermissionDeleteResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
PermissionDeleteParams params = PermissionDeleteParams.builder()
.fineTunedModelCheckpoint("ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd")
.permissionId("cp_zc4Q7MP6XxulcVzj4MZdwsAB")
.build();
PermissionDeleteResponse permission = client.fineTuning().checkpoints().permissions().delete(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
permission = openai.fine_tuning.checkpoints.permissions.delete(
"cp_zc4Q7MP6XxulcVzj4MZdwsAB",
fine_tuned_model_checkpoint: "ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd"
)
puts(permission)
description: |
**NOTE:** This endpoint requires an [admin API key](../admin-api-keys).
Organization owners can use this endpoint to delete a permission for a fine-tuned model checkpoint.
/fine_tuning/jobs:
post:
operationId: createFineTuningJob
tags:
- Fine-tuning
summary: Create fine-tuning job
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateFineTuningJobRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/FineTuningJob'
x-oaiMeta:
name: Create fine-tuning job
group: fine-tuning
returns: A [fine-tuning.job](https://platform.openai.com/docs/api-reference/fine-tuning/object) object.
examples:
- title: Default
request:
curl: |
curl https://api.openai.com/v1/fine_tuning/jobs \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"training_file": "file-BK7bzQj3FfZFXr7DbL6xJwfo",
"model": "gpt-4o-mini"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
fine_tuning_job = client.fine_tuning.jobs.create(
model="gpt-4o-mini",
training_file="file-abc123",
)
print(fine_tuning_job.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const fineTuningJob = await client.fineTuning.jobs.create({
model: 'gpt-4o-mini',
training_file: 'file-abc123',
});
console.log(fineTuningJob.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
Model: openai.FineTuningJobNewParamsModelBabbage002,
TrainingFile: "file-abc123",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", fineTuningJob.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.jobs.FineTuningJob;
import com.openai.models.finetuning.jobs.JobCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
JobCreateParams params = JobCreateParams.builder()
.model(JobCreateParams.Model.BABBAGE_002)
.trainingFile("file-abc123")
.build();
FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
fine_tuning_job = openai.fine_tuning.jobs.create(model: :"babbage-002", training_file:
"file-abc123")
puts(fine_tuning_job)
response: |
{
"object": "fine_tuning.job",
"id": "ftjob-abc123",
"model": "gpt-4o-mini-2024-07-18",
"created_at": 1721764800,
"fine_tuned_model": null,
"organization_id": "org-123",
"result_files": [],
"status": "queued",
"validation_file": null,
"training_file": "file-abc123",
"method": {
"type": "supervised",
"supervised": {
"hyperparameters": {
"batch_size": "auto",
"learning_rate_multiplier": "auto",
"n_epochs": "auto",
}
}
},
"metadata": null
}
- title: Epochs
request:
curl: |
curl https://api.openai.com/v1/fine_tuning/jobs \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"training_file": "file-abc123",
"model": "gpt-4o-mini",
"method": {
"type": "supervised",
"supervised": {
"hyperparameters": {
"n_epochs": 2
}
}
}
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
fine_tuning_job = client.fine_tuning.jobs.create(
model="gpt-4o-mini",
training_file="file-abc123",
)
print(fine_tuning_job.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const fineTuningJob = await client.fineTuning.jobs.create({
model: 'gpt-4o-mini',
training_file: 'file-abc123',
});
console.log(fineTuningJob.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
Model: openai.FineTuningJobNewParamsModelBabbage002,
TrainingFile: "file-abc123",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", fineTuningJob.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.jobs.FineTuningJob;
import com.openai.models.finetuning.jobs.JobCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
JobCreateParams params = JobCreateParams.builder()
.model(JobCreateParams.Model.BABBAGE_002)
.trainingFile("file-abc123")
.build();
FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
fine_tuning_job = openai.fine_tuning.jobs.create(model: :"babbage-002", training_file:
"file-abc123")
puts(fine_tuning_job)
response: |
{
"object": "fine_tuning.job",
"id": "ftjob-abc123",
"model": "gpt-4o-mini",
"created_at": 1721764800,
"fine_tuned_model": null,
"organization_id": "org-123",
"result_files": [],
"status": "queued",
"validation_file": null,
"training_file": "file-abc123",
"hyperparameters": {
"batch_size": "auto",
"learning_rate_multiplier": "auto",
"n_epochs": 2
},
"method": {
"type": "supervised",
"supervised": {
"hyperparameters": {
"batch_size": "auto",
"learning_rate_multiplier": "auto",
"n_epochs": 2
}
}
},
"metadata": null,
"error": {
"code": null,
"message": null,
"param": null
},
"finished_at": null,
"seed": 683058546,
"trained_tokens": null,
"estimated_finish": null,
"integrations": [],
"user_provided_suffix": null,
"usage_metrics": null,
"shared_with_openai": false
}
- title: DPO
request:
curl: |
curl https://api.openai.com/v1/fine_tuning/jobs \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"training_file": "file-abc123",
"validation_file": "file-abc123",
"model": "gpt-4o-mini",
"method": {
"type": "dpo",
"dpo": {
"hyperparameters": {
"beta": 0.1
}
}
}
}'
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const fineTuningJob = await client.fineTuning.jobs.create({
model: 'gpt-4o-mini',
training_file: 'file-abc123',
});
console.log(fineTuningJob.id);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
fine_tuning_job = client.fine_tuning.jobs.create(
model="gpt-4o-mini",
training_file="file-abc123",
)
print(fine_tuning_job.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
Model: openai.FineTuningJobNewParamsModelBabbage002,
TrainingFile: "file-abc123",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", fineTuningJob.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.jobs.FineTuningJob;
import com.openai.models.finetuning.jobs.JobCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
JobCreateParams params = JobCreateParams.builder()
.model(JobCreateParams.Model.BABBAGE_002)
.trainingFile("file-abc123")
.build();
FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
fine_tuning_job = openai.fine_tuning.jobs.create(model: :"babbage-002", training_file:
"file-abc123")
puts(fine_tuning_job)
python: |
from openai import OpenAI
from openai.types.fine_tuning import DpoMethod, DpoHyperparameters
client = OpenAI()
client.fine_tuning.jobs.create(
training_file="file-abc",
validation_file="file-123",
model="gpt-4o-mini",
method={
"type": "dpo",
"dpo": DpoMethod(
hyperparameters=DpoHyperparameters(beta=0.1)
)
}
)
response: |
{
"object": "fine_tuning.job",
"id": "ftjob-abc",
"model": "gpt-4o-mini",
"created_at": 1746130590,
"fine_tuned_model": null,
"organization_id": "org-abc",
"result_files": [],
"status": "queued",
"validation_file": "file-123",
"training_file": "file-abc",
"method": {
"type": "dpo",
"dpo": {
"hyperparameters": {
"beta": 0.1,
"batch_size": "auto",
"learning_rate_multiplier": "auto",
"n_epochs": "auto"
}
}
},
"metadata": null,
"error": {
"code": null,
"message": null,
"param": null
},
"finished_at": null,
"hyperparameters": null,
"seed": 1036326793,
"estimated_finish": null,
"integrations": [],
"user_provided_suffix": null,
"usage_metrics": null,
"shared_with_openai": false
}
- title: Reinforcement
request:
curl: |
curl https://api.openai.com/v1/fine_tuning/jobs \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"training_file": "file-abc",
"validation_file": "file-123",
"model": "o4-mini",
"method": {
"type": "reinforcement",
"reinforcement": {
"grader": {
"type": "string_check",
"name": "Example string check grader",
"input": "{{sample.output_text}}",
"reference": "{{item.label}}",
"operation": "eq"
},
"hyperparameters": {
"reasoning_effort": "medium"
}
}
}
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
fine_tuning_job = client.fine_tuning.jobs.create(
model="gpt-4o-mini",
training_file="file-abc123",
)
print(fine_tuning_job.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const fineTuningJob = await client.fineTuning.jobs.create({
model: 'gpt-4o-mini',
training_file: 'file-abc123',
});
console.log(fineTuningJob.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
Model: openai.FineTuningJobNewParamsModelBabbage002,
TrainingFile: "file-abc123",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", fineTuningJob.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.jobs.FineTuningJob;
import com.openai.models.finetuning.jobs.JobCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
JobCreateParams params = JobCreateParams.builder()
.model(JobCreateParams.Model.BABBAGE_002)
.trainingFile("file-abc123")
.build();
FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
fine_tuning_job = openai.fine_tuning.jobs.create(model: :"babbage-002", training_file:
"file-abc123")
puts(fine_tuning_job)
response: |
{
"object": "fine_tuning.job",
"id": "ftjob-abc123",
"model": "o4-mini",
"created_at": 1721764800,
"finished_at": null,
"fine_tuned_model": null,
"organization_id": "org-123",
"result_files": [],
"status": "validating_files",
"validation_file": "file-123",
"training_file": "file-abc",
"trained_tokens": null,
"error": {},
"user_provided_suffix": null,
"seed": 950189191,
"estimated_finish": null,
"integrations": [],
"method": {
"type": "reinforcement",
"reinforcement": {
"hyperparameters": {
"batch_size": "auto",
"learning_rate_multiplier": "auto",
"n_epochs": "auto",
"eval_interval": "auto",
"eval_samples": "auto",
"compute_multiplier": "auto",
"reasoning_effort": "medium"
},
"grader": {
"type": "string_check",
"name": "Example string check grader",
"input": "{{sample.output_text}}",
"reference": "{{item.label}}",
"operation": "eq"
},
"response_format": null
}
},
"metadata": null,
"usage_metrics": null,
"shared_with_openai": false
}
- title: Validation file
request:
curl: |
curl https://api.openai.com/v1/fine_tuning/jobs \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"training_file": "file-abc123",
"validation_file": "file-abc123",
"model": "gpt-4o-mini"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
fine_tuning_job = client.fine_tuning.jobs.create(
model="gpt-4o-mini",
training_file="file-abc123",
)
print(fine_tuning_job.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const fineTuningJob = await client.fineTuning.jobs.create({
model: 'gpt-4o-mini',
training_file: 'file-abc123',
});
console.log(fineTuningJob.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
Model: openai.FineTuningJobNewParamsModelBabbage002,
TrainingFile: "file-abc123",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", fineTuningJob.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.jobs.FineTuningJob;
import com.openai.models.finetuning.jobs.JobCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
JobCreateParams params = JobCreateParams.builder()
.model(JobCreateParams.Model.BABBAGE_002)
.trainingFile("file-abc123")
.build();
FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
fine_tuning_job = openai.fine_tuning.jobs.create(model: :"babbage-002", training_file:
"file-abc123")
puts(fine_tuning_job)
response: |
{
"object": "fine_tuning.job",
"id": "ftjob-abc123",
"model": "gpt-4o-mini-2024-07-18",
"created_at": 1721764800,
"fine_tuned_model": null,
"organization_id": "org-123",
"result_files": [],
"status": "queued",
"validation_file": "file-abc123",
"training_file": "file-abc123",
"method": {
"type": "supervised",
"supervised": {
"hyperparameters": {
"batch_size": "auto",
"learning_rate_multiplier": "auto",
"n_epochs": "auto",
}
}
},
"metadata": null
}
- title: W&B Integration
request:
curl: |
curl https://api.openai.com/v1/fine_tuning/jobs \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"training_file": "file-abc123",
"validation_file": "file-abc123",
"model": "gpt-4o-mini",
"integrations": [
{
"type": "wandb",
"wandb": {
"project": "my-wandb-project",
"name": "ft-run-display-name"
"tags": [
"first-experiment", "v2"
]
}
}
]
}'
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const fineTuningJob = await client.fineTuning.jobs.create({
model: 'gpt-4o-mini',
training_file: 'file-abc123',
});
console.log(fineTuningJob.id);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
fine_tuning_job = client.fine_tuning.jobs.create(
model="gpt-4o-mini",
training_file="file-abc123",
)
print(fine_tuning_job.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
Model: openai.FineTuningJobNewParamsModelBabbage002,
TrainingFile: "file-abc123",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", fineTuningJob.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.jobs.FineTuningJob;
import com.openai.models.finetuning.jobs.JobCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
JobCreateParams params = JobCreateParams.builder()
.model(JobCreateParams.Model.BABBAGE_002)
.trainingFile("file-abc123")
.build();
FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
fine_tuning_job = openai.fine_tuning.jobs.create(model: :"babbage-002", training_file:
"file-abc123")
puts(fine_tuning_job)
response: |
{
"object": "fine_tuning.job",
"id": "ftjob-abc123",
"model": "gpt-4o-mini-2024-07-18",
"created_at": 1721764800,
"fine_tuned_model": null,
"organization_id": "org-123",
"result_files": [],
"status": "queued",
"validation_file": "file-abc123",
"training_file": "file-abc123",
"integrations": [
{
"type": "wandb",
"wandb": {
"project": "my-wandb-project",
"entity": None,
"run_id": "ftjob-abc123"
}
}
],
"method": {
"type": "supervised",
"supervised": {
"hyperparameters": {
"batch_size": "auto",
"learning_rate_multiplier": "auto",
"n_epochs": "auto",
}
}
},
"metadata": null
}
description: >
Creates a fine-tuning job which begins the process of creating a new model from a given dataset.
Response includes details of the enqueued job including job status and the name of the fine-tuned
models once complete.
[Learn more about fine-tuning](https://platform.openai.com/docs/guides/model-optimization)
get:
operationId: listPaginatedFineTuningJobs
tags:
- Fine-tuning
summary: List fine-tuning jobs
parameters:
- name: after
in: query
description: Identifier for the last job from the previous pagination request.
required: false
schema:
type: string
- name: limit
in: query
description: Number of fine-tuning jobs to retrieve.
required: false
schema:
type: integer
default: 20
- in: query
name: metadata
required: false
schema:
type: object
nullable: true
additionalProperties:
type: string
style: deepObject
explode: true
description: >
Optional metadata filter. To filter, use the syntax `metadata[k]=v`. Alternatively, set
`metadata=null` to indicate no metadata.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListPaginatedFineTuningJobsResponse'
x-oaiMeta:
name: List fine-tuning jobs
group: fine-tuning
returns: >-
A list of paginated [fine-tuning
job](https://platform.openai.com/docs/api-reference/fine-tuning/object) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"object": "fine_tuning.job",
"id": "ftjob-abc123",
"model": "gpt-4o-mini-2024-07-18",
"created_at": 1721764800,
"fine_tuned_model": null,
"organization_id": "org-123",
"result_files": [],
"status": "queued",
"validation_file": null,
"training_file": "file-abc123",
"metadata": {
"key": "value"
}
},
{ ... },
{ ... }
], "has_more": true
}
request:
curl: |
curl https://api.openai.com/v1/fine_tuning/jobs?limit=2&metadata[key]=value \
-H "Authorization: Bearer $OPENAI_API_KEY"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.fine_tuning.jobs.list()
page = page.data[0]
print(page.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const fineTuningJob of client.fineTuning.jobs.list()) {
console.log(fineTuningJob.id);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.FineTuning.Jobs.List(context.TODO(), openai.FineTuningJobListParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.jobs.JobListPage;
import com.openai.models.finetuning.jobs.JobListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
JobListPage page = client.fineTuning().jobs().list();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.fine_tuning.jobs.list
puts(page)
description: |
List your organization's fine-tuning jobs
/fine_tuning/jobs/{fine_tuning_job_id}:
get:
operationId: retrieveFineTuningJob
tags:
- Fine-tuning
summary: Retrieve fine-tuning job
parameters:
- in: path
name: fine_tuning_job_id
required: true
schema:
type: string
example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
description: |
The ID of the fine-tuning job.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/FineTuningJob'
x-oaiMeta:
name: Retrieve fine-tuning job
group: fine-tuning
returns: >-
The [fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning/object) object with the
given ID.
examples:
response: |
{
"object": "fine_tuning.job",
"id": "ftjob-abc123",
"model": "davinci-002",
"created_at": 1692661014,
"finished_at": 1692661190,
"fine_tuned_model": "ft:davinci-002:my-org:custom_suffix:7q8mpxmy",
"organization_id": "org-123",
"result_files": [
"file-abc123"
],
"status": "succeeded",
"validation_file": null,
"training_file": "file-abc123",
"hyperparameters": {
"n_epochs": 4,
"batch_size": 1,
"learning_rate_multiplier": 1.0
},
"trained_tokens": 5768,
"integrations": [],
"seed": 0,
"estimated_finish": 0,
"method": {
"type": "supervised",
"supervised": {
"hyperparameters": {
"n_epochs": 4,
"batch_size": 1,
"learning_rate_multiplier": 1.0
}
}
}
}
request:
curl: |
curl https://api.openai.com/v1/fine_tuning/jobs/ft-AF1WoRqd3aJAHsqc9NY7iL8F \
-H "Authorization: Bearer $OPENAI_API_KEY"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
fine_tuning_job = client.fine_tuning.jobs.retrieve(
"ft-AF1WoRqd3aJAHsqc9NY7iL8F",
)
print(fine_tuning_job.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const fineTuningJob = await client.fineTuning.jobs.retrieve('ft-AF1WoRqd3aJAHsqc9NY7iL8F');
console.log(fineTuningJob.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
fineTuningJob, err := client.FineTuning.Jobs.Get(context.TODO(), "ft-AF1WoRqd3aJAHsqc9NY7iL8F")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", fineTuningJob.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.jobs.FineTuningJob;
import com.openai.models.finetuning.jobs.JobRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FineTuningJob fineTuningJob = client.fineTuning().jobs().retrieve("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
fine_tuning_job = openai.fine_tuning.jobs.retrieve("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
puts(fine_tuning_job)
description: |
Get info about a fine-tuning job.
[Learn more about fine-tuning](https://platform.openai.com/docs/guides/model-optimization)
/fine_tuning/jobs/{fine_tuning_job_id}/cancel:
post:
operationId: cancelFineTuningJob
tags:
- Fine-tuning
summary: Cancel fine-tuning
parameters:
- in: path
name: fine_tuning_job_id
required: true
schema:
type: string
example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
description: |
The ID of the fine-tuning job to cancel.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/FineTuningJob'
x-oaiMeta:
name: Cancel fine-tuning
group: fine-tuning
returns: >-
The cancelled [fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning/object)
object.
examples:
response: |
{
"object": "fine_tuning.job",
"id": "ftjob-abc123",
"model": "gpt-4o-mini-2024-07-18",
"created_at": 1721764800,
"fine_tuned_model": null,
"organization_id": "org-123",
"result_files": [],
"status": "cancelled",
"validation_file": "file-abc123",
"training_file": "file-abc123"
}
request:
curl: |
curl -X POST https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/cancel \
-H "Authorization: Bearer $OPENAI_API_KEY"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
fine_tuning_job = client.fine_tuning.jobs.cancel(
"ft-AF1WoRqd3aJAHsqc9NY7iL8F",
)
print(fine_tuning_job.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const fineTuningJob = await client.fineTuning.jobs.cancel('ft-AF1WoRqd3aJAHsqc9NY7iL8F');
console.log(fineTuningJob.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
fineTuningJob, err := client.FineTuning.Jobs.Cancel(context.TODO(), "ft-AF1WoRqd3aJAHsqc9NY7iL8F")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", fineTuningJob.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.jobs.FineTuningJob;
import com.openai.models.finetuning.jobs.JobCancelParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FineTuningJob fineTuningJob = client.fineTuning().jobs().cancel("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
fine_tuning_job = openai.fine_tuning.jobs.cancel("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
puts(fine_tuning_job)
description: |
Immediately cancel a fine-tune job.
/fine_tuning/jobs/{fine_tuning_job_id}/checkpoints:
get:
operationId: listFineTuningJobCheckpoints
tags:
- Fine-tuning
summary: List fine-tuning checkpoints
parameters:
- in: path
name: fine_tuning_job_id
required: true
schema:
type: string
example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
description: |
The ID of the fine-tuning job to get checkpoints for.
- name: after
in: query
description: Identifier for the last checkpoint ID from the previous pagination request.
required: false
schema:
type: string
- name: limit
in: query
description: Number of checkpoints to retrieve.
required: false
schema:
type: integer
default: 10
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListFineTuningJobCheckpointsResponse'
x-oaiMeta:
name: List fine-tuning checkpoints
group: fine-tuning
returns: >-
A list of fine-tuning [checkpoint
objects](https://platform.openai.com/docs/api-reference/fine-tuning/checkpoint-object) for a
fine-tuning job.
examples:
response: |
{
"object": "list",
"data": [
{
"object": "fine_tuning.job.checkpoint",
"id": "ftckpt_zc4Q7MP6XxulcVzj4MZdwsAB",
"created_at": 1721764867,
"fine_tuned_model_checkpoint": "ft:gpt-4o-mini-2024-07-18:my-org:custom-suffix:96olL566:ckpt-step-2000",
"metrics": {
"full_valid_loss": 0.134,
"full_valid_mean_token_accuracy": 0.874
},
"fine_tuning_job_id": "ftjob-abc123",
"step_number": 2000
},
{
"object": "fine_tuning.job.checkpoint",
"id": "ftckpt_enQCFmOTGj3syEpYVhBRLTSy",
"created_at": 1721764800,
"fine_tuned_model_checkpoint": "ft:gpt-4o-mini-2024-07-18:my-org:custom-suffix:7q8mpxmy:ckpt-step-1000",
"metrics": {
"full_valid_loss": 0.167,
"full_valid_mean_token_accuracy": 0.781
},
"fine_tuning_job_id": "ftjob-abc123",
"step_number": 1000
}
],
"first_id": "ftckpt_zc4Q7MP6XxulcVzj4MZdwsAB",
"last_id": "ftckpt_enQCFmOTGj3syEpYVhBRLTSy",
"has_more": true
}
request:
curl: |
curl https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/checkpoints \
-H "Authorization: Bearer $OPENAI_API_KEY"
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const fineTuningJobCheckpoint of client.fineTuning.jobs.checkpoints.list(
'ft-AF1WoRqd3aJAHsqc9NY7iL8F',
)) {
console.log(fineTuningJobCheckpoint.id);
}
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.fine_tuning.jobs.checkpoints.list(
fine_tuning_job_id="ft-AF1WoRqd3aJAHsqc9NY7iL8F",
)
page = page.data[0]
print(page.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.FineTuning.Jobs.Checkpoints.List(
context.TODO(),
"ft-AF1WoRqd3aJAHsqc9NY7iL8F",
openai.FineTuningJobCheckpointListParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.jobs.checkpoints.CheckpointListPage;
import com.openai.models.finetuning.jobs.checkpoints.CheckpointListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
CheckpointListPage page = client.fineTuning().jobs().checkpoints().list("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.fine_tuning.jobs.checkpoints.list("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
puts(page)
description: |
List checkpoints for a fine-tuning job.
/fine_tuning/jobs/{fine_tuning_job_id}/events:
get:
operationId: listFineTuningEvents
tags:
- Fine-tuning
summary: List fine-tuning events
parameters:
- in: path
name: fine_tuning_job_id
required: true
schema:
type: string
example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
description: |
The ID of the fine-tuning job to get events for.
- name: after
in: query
description: Identifier for the last event from the previous pagination request.
required: false
schema:
type: string
- name: limit
in: query
description: Number of events to retrieve.
required: false
schema:
type: integer
default: 20
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListFineTuningJobEventsResponse'
x-oaiMeta:
name: List fine-tuning events
group: fine-tuning
returns: A list of fine-tuning event objects.
examples:
response: |
{
"object": "list",
"data": [
{
"object": "fine_tuning.job.event",
"id": "ft-event-ddTJfwuMVpfLXseO0Am0Gqjm",
"created_at": 1721764800,
"level": "info",
"message": "Fine tuning job successfully completed",
"data": null,
"type": "message"
},
{
"object": "fine_tuning.job.event",
"id": "ft-event-tyiGuB72evQncpH87xe505Sv",
"created_at": 1721764800,
"level": "info",
"message": "New fine-tuned model created: ft:gpt-4o-mini:openai::7p4lURel",
"data": null,
"type": "message"
}
],
"has_more": true
}
request:
curl: |
curl https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/events \
-H "Authorization: Bearer $OPENAI_API_KEY"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.fine_tuning.jobs.list_events(
fine_tuning_job_id="ft-AF1WoRqd3aJAHsqc9NY7iL8F",
)
page = page.data[0]
print(page.id)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const fineTuningJobEvent of
client.fineTuning.jobs.listEvents('ft-AF1WoRqd3aJAHsqc9NY7iL8F')) {
console.log(fineTuningJobEvent.id);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.FineTuning.Jobs.ListEvents(
context.TODO(),
"ft-AF1WoRqd3aJAHsqc9NY7iL8F",
openai.FineTuningJobListEventsParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.jobs.JobListEventsPage;
import com.openai.models.finetuning.jobs.JobListEventsParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
JobListEventsPage page = client.fineTuning().jobs().listEvents("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.fine_tuning.jobs.list_events("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
puts(page)
description: |
Get status updates for a fine-tuning job.
/fine_tuning/jobs/{fine_tuning_job_id}/pause:
post:
operationId: pauseFineTuningJob
tags:
- Fine-tuning
summary: Pause fine-tuning
parameters:
- in: path
name: fine_tuning_job_id
required: true
schema:
type: string
example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
description: |
The ID of the fine-tuning job to pause.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/FineTuningJob'
x-oaiMeta:
name: Pause fine-tuning
group: fine-tuning
returns: The paused [fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning/object) object.
examples:
response: |
{
"object": "fine_tuning.job",
"id": "ftjob-abc123",
"model": "gpt-4o-mini-2024-07-18",
"created_at": 1721764800,
"fine_tuned_model": null,
"organization_id": "org-123",
"result_files": [],
"status": "paused",
"validation_file": "file-abc123",
"training_file": "file-abc123"
}
request:
curl: |
curl -X POST https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/pause \
-H "Authorization: Bearer $OPENAI_API_KEY"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
fine_tuning_job = client.fine_tuning.jobs.pause(
"ft-AF1WoRqd3aJAHsqc9NY7iL8F",
)
print(fine_tuning_job.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const fineTuningJob = await client.fineTuning.jobs.pause('ft-AF1WoRqd3aJAHsqc9NY7iL8F');
console.log(fineTuningJob.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
fineTuningJob, err := client.FineTuning.Jobs.Pause(context.TODO(), "ft-AF1WoRqd3aJAHsqc9NY7iL8F")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", fineTuningJob.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.jobs.FineTuningJob;
import com.openai.models.finetuning.jobs.JobPauseParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FineTuningJob fineTuningJob = client.fineTuning().jobs().pause("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
fine_tuning_job = openai.fine_tuning.jobs.pause("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
puts(fine_tuning_job)
description: |
Pause a fine-tune job.
/fine_tuning/jobs/{fine_tuning_job_id}/resume:
post:
operationId: resumeFineTuningJob
tags:
- Fine-tuning
summary: Resume fine-tuning
parameters:
- in: path
name: fine_tuning_job_id
required: true
schema:
type: string
example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
description: |
The ID of the fine-tuning job to resume.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/FineTuningJob'
x-oaiMeta:
name: Resume fine-tuning
group: fine-tuning
returns: The resumed [fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning/object) object.
examples:
response: |
{
"object": "fine_tuning.job",
"id": "ftjob-abc123",
"model": "gpt-4o-mini-2024-07-18",
"created_at": 1721764800,
"fine_tuned_model": null,
"organization_id": "org-123",
"result_files": [],
"status": "queued",
"validation_file": "file-abc123",
"training_file": "file-abc123"
}
request:
curl: |
curl -X POST https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/resume \
-H "Authorization: Bearer $OPENAI_API_KEY"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
fine_tuning_job = client.fine_tuning.jobs.resume(
"ft-AF1WoRqd3aJAHsqc9NY7iL8F",
)
print(fine_tuning_job.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const fineTuningJob = await client.fineTuning.jobs.resume('ft-AF1WoRqd3aJAHsqc9NY7iL8F');
console.log(fineTuningJob.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
fineTuningJob, err := client.FineTuning.Jobs.Resume(context.TODO(), "ft-AF1WoRqd3aJAHsqc9NY7iL8F")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", fineTuningJob.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.finetuning.jobs.FineTuningJob;
import com.openai.models.finetuning.jobs.JobResumeParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FineTuningJob fineTuningJob = client.fineTuning().jobs().resume("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
fine_tuning_job = openai.fine_tuning.jobs.resume("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
puts(fine_tuning_job)
description: |
Resume a fine-tune job.
/images/edits:
post:
operationId: createImageEdit
tags:
- Images
summary: Create image edit
requestBody:
required: true
content:
multipart/form-data:
schema:
$ref: '#/components/schemas/CreateImageEditRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ImagesResponse'
text/event-stream:
schema:
$ref: '#/components/schemas/ImageEditStreamEvent'
x-oaiMeta:
name: Create image edit
group: images
returns: Returns an [image](https://platform.openai.com/docs/api-reference/images/object) object.
examples:
- title: Edit image
request:
curl: |
curl -s -D >(grep -i x-request-id >&2) \
-o >(jq -r '.data[0].b64_json' | base64 --decode > gift-basket.png) \
-X POST "https://api.openai.com/v1/images/edits" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-F "model=gpt-image-1" \
-F "image[]=@body-lotion.png" \
-F "image[]=@bath-bomb.png" \
-F "image[]=@incense-kit.png" \
-F "image[]=@soap.png" \
-F 'prompt=Create a lovely gift basket with these four items in it'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
images_response = client.images.edit(
image=b"raw file contents",
prompt="A cute baby sea otter wearing a beret",
)
print(images_response)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const imagesResponse = await client.images.edit({
image: fs.createReadStream('path/to/file'),
prompt: 'A cute baby sea otter wearing a beret',
});
console.log(imagesResponse);
go: |
package main
import (
"bytes"
"context"
"fmt"
"io"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
imagesResponse, err := client.Images.Edit(context.TODO(), openai.ImageEditParams{
Image: openai.ImageEditParamsImageUnion{
OfFile: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
},
Prompt: "A cute baby sea otter wearing a beret",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", imagesResponse)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.images.ImageEditParams;
import com.openai.models.images.ImagesResponse;
import java.io.ByteArrayInputStream;
import java.io.InputStream;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ImageEditParams params = ImageEditParams.builder()
.image(ByteArrayInputStream("some content".getBytes()))
.prompt("A cute baby sea otter wearing a beret")
.build();
ImagesResponse imagesResponse = client.images().edit(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
images_response = openai.images.edit(image: Pathname(__FILE__), prompt: "A cute baby sea otter
wearing a beret")
puts(images_response)
- title: Streaming
request:
curl: |
curl -s -N -X POST "https://api.openai.com/v1/images/edits" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-F "model=gpt-image-1" \
-F "image[]=@body-lotion.png" \
-F "image[]=@bath-bomb.png" \
-F "image[]=@incense-kit.png" \
-F "image[]=@soap.png" \
-F 'prompt=Create a lovely gift basket with these four items in it' \
-F "stream=true"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
images_response = client.images.edit(
image=b"raw file contents",
prompt="A cute baby sea otter wearing a beret",
)
print(images_response)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const imagesResponse = await client.images.edit({
image: fs.createReadStream('path/to/file'),
prompt: 'A cute baby sea otter wearing a beret',
});
console.log(imagesResponse);
go: |
package main
import (
"bytes"
"context"
"fmt"
"io"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
imagesResponse, err := client.Images.Edit(context.TODO(), openai.ImageEditParams{
Image: openai.ImageEditParamsImageUnion{
OfFile: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
},
Prompt: "A cute baby sea otter wearing a beret",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", imagesResponse)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.images.ImageEditParams;
import com.openai.models.images.ImagesResponse;
import java.io.ByteArrayInputStream;
import java.io.InputStream;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ImageEditParams params = ImageEditParams.builder()
.image(ByteArrayInputStream("some content".getBytes()))
.prompt("A cute baby sea otter wearing a beret")
.build();
ImagesResponse imagesResponse = client.images().edit(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
images_response = openai.images.edit(image: Pathname(__FILE__), prompt: "A cute baby sea otter
wearing a beret")
puts(images_response)
response: >
event: image_edit.partial_image
data: {"type":"image_edit.partial_image","b64_json":"...","partial_image_index":0}
event: image_edit.completed
data:
{"type":"image_edit.completed","b64_json":"...","usage":{"total_tokens":100,"input_tokens":50,"output_tokens":50,"input_tokens_details":{"text_tokens":10,"image_tokens":40}}}
description: >-
Creates an edited or extended image given one or more source images and a prompt. This endpoint only
supports `gpt-image-1` and `dall-e-2`.
/images/generations:
post:
operationId: createImage
tags:
- Images
summary: Create image
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateImageRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ImagesResponse'
text/event-stream:
schema:
$ref: '#/components/schemas/ImageGenStreamEvent'
x-oaiMeta:
name: Create image
group: images
returns: Returns an [image](https://platform.openai.com/docs/api-reference/images/object) object.
examples:
- title: Generate image
request:
curl: |
curl https://api.openai.com/v1/images/generations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "gpt-image-1",
"prompt": "A cute baby sea otter",
"n": 1,
"size": "1024x1024"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
images_response = client.images.generate(
prompt="A cute baby sea otter",
)
print(images_response)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const imagesResponse = await client.images.generate({ prompt: 'A cute baby sea otter' });
console.log(imagesResponse);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
imagesResponse, err := client.Images.Generate(context.TODO(), openai.ImageGenerateParams{
Prompt: "A cute baby sea otter",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", imagesResponse)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.images.ImageGenerateParams;
import com.openai.models.images.ImagesResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ImageGenerateParams params = ImageGenerateParams.builder()
.prompt("A cute baby sea otter")
.build();
ImagesResponse imagesResponse = client.images().generate(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
images_response = openai.images.generate(prompt: "A cute baby sea otter")
puts(images_response)
response: |
{
"created": 1713833628,
"data": [
{
"b64_json": "..."
}
],
"usage": {
"total_tokens": 100,
"input_tokens": 50,
"output_tokens": 50,
"input_tokens_details": {
"text_tokens": 10,
"image_tokens": 40
}
}
}
- title: Streaming
request:
curl: |
curl https://api.openai.com/v1/images/generations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "gpt-image-1",
"prompt": "A cute baby sea otter",
"n": 1,
"size": "1024x1024",
"stream": true
}' \
--no-buffer
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
images_response = client.images.generate(
prompt="A cute baby sea otter",
)
print(images_response)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const imagesResponse = await client.images.generate({ prompt: 'A cute baby sea otter' });
console.log(imagesResponse);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
imagesResponse, err := client.Images.Generate(context.TODO(), openai.ImageGenerateParams{
Prompt: "A cute baby sea otter",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", imagesResponse)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.images.ImageGenerateParams;
import com.openai.models.images.ImagesResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ImageGenerateParams params = ImageGenerateParams.builder()
.prompt("A cute baby sea otter")
.build();
ImagesResponse imagesResponse = client.images().generate(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
images_response = openai.images.generate(prompt: "A cute baby sea otter")
puts(images_response)
response: >
event: image_generation.partial_image
data: {"type":"image_generation.partial_image","b64_json":"...","partial_image_index":0}
event: image_generation.completed
data:
{"type":"image_generation.completed","b64_json":"...","usage":{"total_tokens":100,"input_tokens":50,"output_tokens":50,"input_tokens_details":{"text_tokens":10,"image_tokens":40}}}
description: |
Creates an image given a prompt. [Learn more](https://platform.openai.com/docs/guides/images).
/images/variations:
post:
operationId: createImageVariation
tags:
- Images
summary: Create image variation
requestBody:
required: true
content:
multipart/form-data:
schema:
$ref: '#/components/schemas/CreateImageVariationRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ImagesResponse'
x-oaiMeta:
name: Create image variation
group: images
returns: Returns a list of [image](https://platform.openai.com/docs/api-reference/images/object) objects.
examples:
response: |
{
"created": 1589478378,
"data": [
{
"url": "https://..."
},
{
"url": "https://..."
}
]
}
request:
curl: |
curl https://api.openai.com/v1/images/variations \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-F image="@otter.png" \
-F n=2 \
-F size="1024x1024"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
images_response = client.images.create_variation(
image=b"raw file contents",
)
print(images_response.created)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const imagesResponse = await client.images.createVariation({ image:
fs.createReadStream('otter.png') });
console.log(imagesResponse.created);
csharp: |
using System;
using OpenAI.Images;
ImageClient client = new(
model: "dall-e-2",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
GeneratedImage image = client.GenerateImageVariation(imageFilePath: "otter.png");
Console.WriteLine(image.ImageUri);
go: |
package main
import (
"bytes"
"context"
"fmt"
"io"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
imagesResponse, err := client.Images.NewVariation(context.TODO(), openai.ImageNewVariationParams{
Image: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", imagesResponse.Created)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.images.ImageCreateVariationParams;
import com.openai.models.images.ImagesResponse;
import java.io.ByteArrayInputStream;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ImageCreateVariationParams params = ImageCreateVariationParams.builder()
.image(ByteArrayInputStream("some content".getBytes()))
.build();
ImagesResponse imagesResponse = client.images().createVariation(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
images_response = openai.images.create_variation(image: Pathname(__FILE__))
puts(images_response)
description: Creates a variation of a given image. This endpoint only supports `dall-e-2`.
/models:
get:
operationId: listModels
tags:
- Models
summary: List models
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListModelsResponse'
x-oaiMeta:
name: List models
group: models
returns: A list of [model](https://platform.openai.com/docs/api-reference/models/object) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "model-id-0",
"object": "model",
"created": 1686935002,
"owned_by": "organization-owner"
},
{
"id": "model-id-1",
"object": "model",
"created": 1686935002,
"owned_by": "organization-owner",
},
{
"id": "model-id-2",
"object": "model",
"created": 1686935002,
"owned_by": "openai"
},
],
"object": "list"
}
request:
curl: |
curl https://api.openai.com/v1/models \
-H "Authorization: Bearer $OPENAI_API_KEY"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.models.list()
page = page.data[0]
print(page.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const model of client.models.list()) {
console.log(model.id);
}
csharp: |
using System;
using OpenAI.Models;
OpenAIModelClient client = new(
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
foreach (var model in client.GetModels().Value)
{
Console.WriteLine(model.Id);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.Models.List(context.TODO())
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.models.ModelListPage;
import com.openai.models.models.ModelListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ModelListPage page = client.models().list();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.models.list
puts(page)
description: >-
Lists the currently available models, and provides basic information about each one such as the owner
and availability.
/models/{model}:
get:
operationId: retrieveModel
tags:
- Models
summary: Retrieve model
parameters:
- in: path
name: model
required: true
schema:
type: string
example: gpt-4o-mini
description: The ID of the model to use for this request
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/Model'
x-oaiMeta:
name: Retrieve model
group: models
returns: >-
The [model](https://platform.openai.com/docs/api-reference/models/object) object matching the
specified ID.
examples:
response: |
{
"id": "VAR_chat_model_id",
"object": "model",
"created": 1686935002,
"owned_by": "openai"
}
request:
curl: |
curl https://api.openai.com/v1/models/VAR_chat_model_id \
-H "Authorization: Bearer $OPENAI_API_KEY"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
model = client.models.retrieve(
"gpt-4o-mini",
)
print(model.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const model = await client.models.retrieve('gpt-4o-mini');
console.log(model.id);
csharp: |
using System;
using System.ClientModel;
using OpenAI.Models;
OpenAIModelClient client = new(
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
ClientResult<OpenAIModel> model = client.GetModel("babbage-002");
Console.WriteLine(model.Value.Id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
model, err := client.Models.Get(context.TODO(), "gpt-4o-mini")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", model.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.models.Model;
import com.openai.models.models.ModelRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Model model = client.models().retrieve("gpt-4o-mini");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
model = openai.models.retrieve("gpt-4o-mini")
puts(model)
description: >-
Retrieves a model instance, providing basic information about the model such as the owner and
permissioning.
delete:
operationId: deleteModel
tags:
- Models
summary: Delete a fine-tuned model
parameters:
- in: path
name: model
required: true
schema:
type: string
example: ft:gpt-4o-mini:acemeco:suffix:abc123
description: The model to delete
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/DeleteModelResponse'
x-oaiMeta:
name: Delete a fine-tuned model
group: models
returns: Deletion status.
examples:
response: |
{
"id": "ft:gpt-4o-mini:acemeco:suffix:abc123",
"object": "model",
"deleted": true
}
request:
curl: |
curl https://api.openai.com/v1/models/ft:gpt-4o-mini:acemeco:suffix:abc123 \
-X DELETE \
-H "Authorization: Bearer $OPENAI_API_KEY"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
model_deleted = client.models.delete(
"ft:gpt-4o-mini:acemeco:suffix:abc123",
)
print(model_deleted.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const modelDeleted = await client.models.delete('ft:gpt-4o-mini:acemeco:suffix:abc123');
console.log(modelDeleted.id);
csharp: |
using System;
using System.ClientModel;
using OpenAI.Models;
OpenAIModelClient client = new(
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
ClientResult success = client.DeleteModel("ft:gpt-4o-mini:acemeco:suffix:abc123");
Console.WriteLine(success);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
modelDeleted, err := client.Models.Delete(context.TODO(), "ft:gpt-4o-mini:acemeco:suffix:abc123")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", modelDeleted.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.models.ModelDeleteParams;
import com.openai.models.models.ModelDeleted;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ModelDeleted modelDeleted = client.models().delete("ft:gpt-4o-mini:acemeco:suffix:abc123");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
model_deleted = openai.models.delete("ft:gpt-4o-mini:acemeco:suffix:abc123")
puts(model_deleted)
description: Delete a fine-tuned model. You must have the Owner role in your organization to delete a model.
/moderations:
post:
operationId: createModeration
tags:
- Moderations
summary: Create moderation
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateModerationRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/CreateModerationResponse'
x-oaiMeta:
name: Create moderation
group: moderations
returns: A [moderation](https://platform.openai.com/docs/api-reference/moderations/object) object.
examples:
- title: Single string
request:
curl: |
curl https://api.openai.com/v1/moderations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"input": "I want to kill them."
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
moderation = client.moderations.create(
input="I want to kill them.",
)
print(moderation.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const moderation = await client.moderations.create({ input: 'I want to kill them.' });
console.log(moderation.id);
csharp: |
using System;
using System.ClientModel;
using OpenAI.Moderations;
ModerationClient client = new(
model: "omni-moderation-latest",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
ClientResult<ModerationResult> moderation = client.ClassifyText("I want to kill them.");
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
moderation, err := client.Moderations.New(context.TODO(), openai.ModerationNewParams{
Input: openai.ModerationNewParamsInputUnion{
OfString: openai.String("I want to kill them."),
},
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", moderation.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.moderations.ModerationCreateParams;
import com.openai.models.moderations.ModerationCreateResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ModerationCreateParams params = ModerationCreateParams.builder()
.input("I want to kill them.")
.build();
ModerationCreateResponse moderation = client.moderations().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
moderation = openai.moderations.create(input: "I want to kill them.")
puts(moderation)
response: |
{
"id": "modr-AB8CjOTu2jiq12hp1AQPfeqFWaORR",
"model": "text-moderation-007",
"results": [
{
"flagged": true,
"categories": {
"sexual": false,
"hate": false,
"harassment": true,
"self-harm": false,
"sexual/minors": false,
"hate/threatening": false,
"violence/graphic": false,
"self-harm/intent": false,
"self-harm/instructions": false,
"harassment/threatening": true,
"violence": true
},
"category_scores": {
"sexual": 0.000011726012417057063,
"hate": 0.22706663608551025,
"harassment": 0.5215635299682617,
"self-harm": 2.227119921371923e-6,
"sexual/minors": 7.107352217872176e-8,
"hate/threatening": 0.023547329008579254,
"violence/graphic": 0.00003391829886822961,
"self-harm/intent": 1.646940972932498e-6,
"self-harm/instructions": 1.1198755256458526e-9,
"harassment/threatening": 0.5694745779037476,
"violence": 0.9971134662628174
}
}
]
}
- title: Image and text
request:
curl: |
curl https://api.openai.com/v1/moderations \
-X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "omni-moderation-latest",
"input": [
{ "type": "text", "text": "...text to classify goes here..." },
{
"type": "image_url",
"image_url": {
"url": "https://example.com/image.png"
}
}
]
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
moderation = client.moderations.create(
input="I want to kill them.",
)
print(moderation.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const moderation = await client.moderations.create({ input: 'I want to kill them.' });
console.log(moderation.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
moderation, err := client.Moderations.New(context.TODO(), openai.ModerationNewParams{
Input: openai.ModerationNewParamsInputUnion{
OfString: openai.String("I want to kill them."),
},
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", moderation.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.moderations.ModerationCreateParams;
import com.openai.models.moderations.ModerationCreateResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ModerationCreateParams params = ModerationCreateParams.builder()
.input("I want to kill them.")
.build();
ModerationCreateResponse moderation = client.moderations().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
moderation = openai.moderations.create(input: "I want to kill them.")
puts(moderation)
response: |
{
"id": "modr-0d9740456c391e43c445bf0f010940c7",
"model": "omni-moderation-latest",
"results": [
{
"flagged": true,
"categories": {
"harassment": true,
"harassment/threatening": true,
"sexual": false,
"hate": false,
"hate/threatening": false,
"illicit": false,
"illicit/violent": false,
"self-harm/intent": false,
"self-harm/instructions": false,
"self-harm": false,
"sexual/minors": false,
"violence": true,
"violence/graphic": true
},
"category_scores": {
"harassment": 0.8189693396524255,
"harassment/threatening": 0.804985420696006,
"sexual": 1.573112165348997e-6,
"hate": 0.007562942636942845,
"hate/threatening": 0.004208854591835476,
"illicit": 0.030535955153511665,
"illicit/violent": 0.008925306722380033,
"self-harm/intent": 0.00023023930975076432,
"self-harm/instructions": 0.0002293869201073356,
"self-harm": 0.012598046106750154,
"sexual/minors": 2.212566909570261e-8,
"violence": 0.9999992735124786,
"violence/graphic": 0.843064871157054
},
"category_applied_input_types": {
"harassment": [
"text"
],
"harassment/threatening": [
"text"
],
"sexual": [
"text",
"image"
],
"hate": [
"text"
],
"hate/threatening": [
"text"
],
"illicit": [
"text"
],
"illicit/violent": [
"text"
],
"self-harm/intent": [
"text",
"image"
],
"self-harm/instructions": [
"text",
"image"
],
"self-harm": [
"text",
"image"
],
"sexual/minors": [
"text"
],
"violence": [
"text",
"image"
],
"violence/graphic": [
"text",
"image"
]
}
}
]
}
description: |
Classifies if text and/or image inputs are potentially harmful. Learn
more in the [moderation guide](https://platform.openai.com/docs/guides/moderation).
/organization/admin_api_keys:
get:
summary: List all organization and project API keys.
operationId: admin-api-keys-list
description: List organization API keys
parameters:
- in: query
name: after
required: false
schema:
type: string
nullable: true
description: Return keys with IDs that come after this ID in the pagination order.
- in: query
name: order
required: false
schema:
type: string
enum:
- asc
- desc
default: asc
description: Order results by creation time, ascending or descending.
- in: query
name: limit
required: false
schema:
type: integer
default: 20
description: Maximum number of keys to return.
responses:
'200':
description: A list of organization API keys.
content:
application/json:
schema:
$ref: '#/components/schemas/ApiKeyList'
x-oaiMeta:
name: List all organization and project API keys.
group: administration
returns: A list of admin and project API key objects.
examples:
response: |
{
"object": "list",
"data": [
{
"object": "organization.admin_api_key",
"id": "key_abc",
"name": "Main Admin Key",
"redacted_value": "sk-admin...def",
"created_at": 1711471533,
"last_used_at": 1711471534,
"owner": {
"type": "service_account",
"object": "organization.service_account",
"id": "sa_456",
"name": "My Service Account",
"created_at": 1711471533,
"role": "member"
}
}
],
"first_id": "key_abc",
"last_id": "key_abc",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/organization/admin_api_keys?after=key_abc&limit=20 \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
post:
summary: Create admin API key
operationId: admin-api-keys-create
description: Create an organization admin API key
requestBody:
required: true
content:
application/json:
schema:
type: object
required:
- name
properties:
name:
type: string
example: New Admin Key
responses:
'200':
description: The newly created admin API key.
content:
application/json:
schema:
$ref: '#/components/schemas/AdminApiKey'
x-oaiMeta:
name: Create admin API key
group: administration
returns: >-
The created [AdminApiKey](https://platform.openai.com/docs/api-reference/admin-api-keys/object)
object.
examples:
response: |
{
"object": "organization.admin_api_key",
"id": "key_xyz",
"name": "New Admin Key",
"redacted_value": "sk-admin...xyz",
"created_at": 1711471533,
"last_used_at": 1711471534,
"owner": {
"type": "user",
"object": "organization.user",
"id": "user_123",
"name": "John Doe",
"created_at": 1711471533,
"role": "owner"
},
"value": "sk-admin-1234abcd"
}
request:
curl: |
curl -X POST https://api.openai.com/v1/organization/admin_api_keys \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"name": "New Admin Key"
}'
/organization/admin_api_keys/{key_id}:
get:
summary: Retrieve admin API key
operationId: admin-api-keys-get
description: Retrieve a single organization API key
parameters:
- in: path
name: key_id
required: true
schema:
type: string
description: The ID of the API key.
responses:
'200':
description: Details of the requested API key.
content:
application/json:
schema:
$ref: '#/components/schemas/AdminApiKey'
x-oaiMeta:
name: Retrieve admin API key
group: administration
returns: >-
The requested [AdminApiKey](https://platform.openai.com/docs/api-reference/admin-api-keys/object)
object.
examples:
response: |
{
"object": "organization.admin_api_key",
"id": "key_abc",
"name": "Main Admin Key",
"redacted_value": "sk-admin...xyz",
"created_at": 1711471533,
"last_used_at": 1711471534,
"owner": {
"type": "user",
"object": "organization.user",
"id": "user_123",
"name": "John Doe",
"created_at": 1711471533,
"role": "owner"
}
}
request:
curl: |
curl https://api.openai.com/v1/organization/admin_api_keys/key_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
delete:
summary: Delete admin API key
operationId: admin-api-keys-delete
description: Delete an organization admin API key
parameters:
- in: path
name: key_id
required: true
schema:
type: string
description: The ID of the API key to be deleted.
responses:
'200':
description: Confirmation that the API key was deleted.
content:
application/json:
schema:
type: object
properties:
id:
type: string
example: key_abc
object:
type: string
example: organization.admin_api_key.deleted
deleted:
type: boolean
example: true
x-oaiMeta:
name: Delete admin API key
group: administration
returns: A confirmation object indicating the key was deleted.
examples:
response: |
{
"id": "key_abc",
"object": "organization.admin_api_key.deleted",
"deleted": true
}
request:
curl: |
curl -X DELETE https://api.openai.com/v1/organization/admin_api_keys/key_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
/organization/audit_logs:
get:
summary: List audit logs
operationId: list-audit-logs
tags:
- Audit Logs
parameters:
- name: effective_at
in: query
description: Return only events whose `effective_at` (Unix seconds) is in this range.
required: false
schema:
type: object
properties:
gt:
type: integer
description: Return only events whose `effective_at` (Unix seconds) is greater than this value.
gte:
type: integer
description: >-
Return only events whose `effective_at` (Unix seconds) is greater than or equal to this
value.
lt:
type: integer
description: Return only events whose `effective_at` (Unix seconds) is less than this value.
lte:
type: integer
description: Return only events whose `effective_at` (Unix seconds) is less than or equal to this value.
- name: project_ids[]
in: query
description: Return only events for these projects.
required: false
schema:
type: array
items:
type: string
- name: event_types[]
in: query
description: >-
Return only events with a `type` in one of these values. For example, `project.created`. For all
options, see the documentation for the [audit log
object](https://platform.openai.com/docs/api-reference/audit-logs/object).
required: false
schema:
type: array
items:
$ref: '#/components/schemas/AuditLogEventType'
- name: actor_ids[]
in: query
description: >-
Return only events performed by these actors. Can be a user ID, a service account ID, or an api
key tracking ID.
required: false
schema:
type: array
items:
type: string
- name: actor_emails[]
in: query
description: Return only events performed by users with these emails.
required: false
schema:
type: array
items:
type: string
- name: resource_ids[]
in: query
description: Return only events performed on these targets. For example, a project ID updated.
required: false
schema:
type: array
items:
type: string
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
schema:
type: string
- name: before
in: query
description: >
A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, starting with obj_foo, your
subsequent call can include before=obj_foo in order to fetch the previous page of the list.
schema:
type: string
responses:
'200':
description: Audit logs listed successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ListAuditLogsResponse'
x-oaiMeta:
name: List audit logs
group: audit-logs
returns: >-
A list of paginated [Audit Log](https://platform.openai.com/docs/api-reference/audit-logs/object)
objects.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "audit_log-xxx_yyyymmdd",
"type": "project.archived",
"effective_at": 1722461446,
"actor": {
"type": "api_key",
"api_key": {
"type": "user",
"user": {
"id": "user-xxx",
"email": "user@example.com"
}
}
},
"project.archived": {
"id": "proj_abc"
},
},
{
"id": "audit_log-yyy__20240101",
"type": "api_key.updated",
"effective_at": 1720804190,
"actor": {
"type": "session",
"session": {
"user": {
"id": "user-xxx",
"email": "user@example.com"
},
"ip_address": "127.0.0.1",
"user_agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
"ja3": "a497151ce4338a12c4418c44d375173e",
"ja4": "q13d0313h3_55b375c5d22e_c7319ce65786",
"ip_address_details": {
"country": "US",
"city": "San Francisco",
"region": "California",
"region_code": "CA",
"asn": "1234",
"latitude": "37.77490",
"longitude": "-122.41940"
}
}
},
"api_key.updated": {
"id": "key_xxxx",
"data": {
"scopes": ["resource_2.operation_2"]
}
},
}
],
"first_id": "audit_log-xxx__20240101",
"last_id": "audit_log_yyy__20240101",
"has_more": true
}
request:
curl: |
curl https://api.openai.com/v1/organization/audit_logs \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: List user actions and configuration changes within this organization.
/organization/certificates:
get:
summary: List organization certificates
operationId: listOrganizationCertificates
tags:
- Certificates
parameters:
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
required: false
schema:
type: string
- name: order
in: query
description: >
Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
descending order.
schema:
type: string
default: desc
enum:
- asc
- desc
responses:
'200':
description: Certificates listed successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ListCertificatesResponse'
x-oaiMeta:
name: List organization certificates
group: administration
returns: A list of [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) objects.
examples:
request:
curl: |
curl https://api.openai.com/v1/organization/certificates \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY"
response: |
{
"object": "list",
"data": [
{
"object": "organization.certificate",
"id": "cert_abc",
"name": "My Example Certificate",
"active": true,
"created_at": 1234567,
"certificate_details": {
"valid_at": 12345667,
"expires_at": 12345678
}
},
],
"first_id": "cert_abc",
"last_id": "cert_abc",
"has_more": false
}
description: List uploaded certificates for this organization.
post:
summary: Upload certificate
operationId: uploadCertificate
tags:
- Certificates
requestBody:
description: The certificate upload payload.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/UploadCertificateRequest'
responses:
'200':
description: Certificate uploaded successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/Certificate'
x-oaiMeta:
name: Upload certificate
group: administration
returns: A single [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) object.
examples:
request:
curl: |
curl -X POST https://api.openai.com/v1/organization/certificates \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"name": "My Example Certificate",
"certificate": "-----BEGIN CERTIFICATE-----\\nMIIDeT...\\n-----END CERTIFICATE-----"
}'
response: |
{
"object": "certificate",
"id": "cert_abc",
"name": "My Example Certificate",
"created_at": 1234567,
"certificate_details": {
"valid_at": 12345667,
"expires_at": 12345678
}
}
description: |
Upload a certificate to the organization. This does **not** automatically activate the certificate.
Organizations can upload up to 50 certificates.
/organization/certificates/activate:
post:
summary: Activate certificates for organization
operationId: activateOrganizationCertificates
tags:
- Certificates
requestBody:
description: The certificate activation payload.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ToggleCertificatesRequest'
responses:
'200':
description: Certificates activated successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ListCertificatesResponse'
x-oaiMeta:
name: Activate certificates for organization
group: administration
returns: >-
A list of [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) objects
that were activated.
examples:
request:
curl: |
curl https://api.openai.com/v1/organization/certificates/activate \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"data": ["cert_abc", "cert_def"]
}'
response: |
{
"object": "organization.certificate.activation",
"data": [
{
"object": "organization.certificate",
"id": "cert_abc",
"name": "My Example Certificate",
"active": true,
"created_at": 1234567,
"certificate_details": {
"valid_at": 12345667,
"expires_at": 12345678
}
},
{
"object": "organization.certificate",
"id": "cert_def",
"name": "My Example Certificate 2",
"active": true,
"created_at": 1234567,
"certificate_details": {
"valid_at": 12345667,
"expires_at": 12345678
}
},
],
}
description: |
Activate certificates at the organization level.
You can atomically and idempotently activate up to 10 certificates at a time.
/organization/certificates/deactivate:
post:
summary: Deactivate certificates for organization
operationId: deactivateOrganizationCertificates
tags:
- Certificates
requestBody:
description: The certificate deactivation payload.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ToggleCertificatesRequest'
responses:
'200':
description: Certificates deactivated successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ListCertificatesResponse'
x-oaiMeta:
name: Deactivate certificates for organization
group: administration
returns: >-
A list of [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) objects
that were deactivated.
examples:
request:
curl: |
curl https://api.openai.com/v1/organization/certificates/deactivate \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"data": ["cert_abc", "cert_def"]
}'
response: |
{
"object": "organization.certificate.deactivation",
"data": [
{
"object": "organization.certificate",
"id": "cert_abc",
"name": "My Example Certificate",
"active": false,
"created_at": 1234567,
"certificate_details": {
"valid_at": 12345667,
"expires_at": 12345678
}
},
{
"object": "organization.certificate",
"id": "cert_def",
"name": "My Example Certificate 2",
"active": false,
"created_at": 1234567,
"certificate_details": {
"valid_at": 12345667,
"expires_at": 12345678
}
},
],
}
description: |
Deactivate certificates at the organization level.
You can atomically and idempotently deactivate up to 10 certificates at a time.
/organization/certificates/{certificate_id}:
get:
summary: Get certificate
operationId: getCertificate
tags:
- Certificates
parameters:
- name: certificate_id
in: path
description: Unique ID of the certificate to retrieve.
required: true
schema:
type: string
- name: include
in: query
description: >-
A list of additional fields to include in the response. Currently the only supported value is
`content` to fetch the PEM content of the certificate.
required: false
schema:
type: array
items:
type: string
enum:
- content
responses:
'200':
description: Certificate retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/Certificate'
x-oaiMeta:
name: Get certificate
group: administration
returns: A single [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) object.
examples:
request:
curl: |
curl "https://api.openai.com/v1/organization/certificates/cert_abc?include[]=content" \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY"
response: |
{
"object": "certificate",
"id": "cert_abc",
"name": "My Example Certificate",
"created_at": 1234567,
"certificate_details": {
"valid_at": 1234567,
"expires_at": 12345678,
"content": "-----BEGIN CERTIFICATE-----MIIDeT...-----END CERTIFICATE-----"
}
}
description: |
Get a certificate that has been uploaded to the organization.
You can get a certificate regardless of whether it is active or not.
post:
summary: Modify certificate
operationId: modifyCertificate
tags:
- Certificates
requestBody:
description: The certificate modification payload.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ModifyCertificateRequest'
responses:
'200':
description: Certificate modified successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/Certificate'
x-oaiMeta:
name: Modify certificate
group: administration
returns: >-
The updated [Certificate](https://platform.openai.com/docs/api-reference/certificates/object)
object.
examples:
request:
curl: |
curl -X POST https://api.openai.com/v1/organization/certificates/cert_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"name": "Renamed Certificate"
}'
response: |
{
"object": "certificate",
"id": "cert_abc",
"name": "Renamed Certificate",
"created_at": 1234567,
"certificate_details": {
"valid_at": 12345667,
"expires_at": 12345678
}
}
description: |
Modify a certificate. Note that only the name can be modified.
delete:
summary: Delete certificate
operationId: deleteCertificate
tags:
- Certificates
responses:
'200':
description: Certificate deleted successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/DeleteCertificateResponse'
x-oaiMeta:
name: Delete certificate
group: administration
returns: A confirmation object indicating the certificate was deleted.
examples:
request:
curl: |
curl -X DELETE https://api.openai.com/v1/organization/certificates/cert_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY"
response: |
{
"object": "certificate.deleted",
"id": "cert_abc"
}
description: |
Delete a certificate from the organization.
The certificate must be inactive for the organization and all projects.
/organization/costs:
get:
summary: Costs
operationId: usage-costs
tags:
- Usage
parameters:
- name: start_time
in: query
description: Start time (Unix seconds) of the query time range, inclusive.
required: true
schema:
type: integer
- name: end_time
in: query
description: End time (Unix seconds) of the query time range, exclusive.
required: false
schema:
type: integer
- name: bucket_width
in: query
description: Width of each time bucket in response. Currently only `1d` is supported, default to `1d`.
required: false
schema:
type: string
enum:
- 1d
default: 1d
- name: project_ids
in: query
description: Return only costs for these projects.
required: false
schema:
type: array
items:
type: string
- name: group_by
in: query
description: >-
Group the costs by the specified fields. Support fields include `project_id`, `line_item` and any
combination of them.
required: false
schema:
type: array
items:
type: string
enum:
- project_id
- line_item
- name: limit
in: query
description: >
A limit on the number of buckets to be returned. Limit can range between 1 and 180, and the
default is 7.
required: false
schema:
type: integer
default: 7
- name: page
in: query
description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
schema:
type: string
responses:
'200':
description: Costs data retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/UsageResponse'
x-oaiMeta:
name: Costs
group: usage-costs
returns: >-
A list of paginated, time bucketed
[Costs](https://platform.openai.com/docs/api-reference/usage/costs_object) objects.
examples:
response: |
{
"object": "page",
"data": [
{
"object": "bucket",
"start_time": 1730419200,
"end_time": 1730505600,
"results": [
{
"object": "organization.costs.result",
"amount": {
"value": 0.06,
"currency": "usd"
},
"line_item": null,
"project_id": null
}
]
}
],
"has_more": false,
"next_page": null
}
request:
curl: |
curl "https://api.openai.com/v1/organization/costs?start_time=1730419200&limit=1" \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Get costs details for the organization.
/organization/invites:
get:
summary: List invites
operationId: list-invites
tags:
- Invites
parameters:
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
required: false
schema:
type: string
responses:
'200':
description: Invites listed successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/InviteListResponse'
x-oaiMeta:
name: List invites
group: administration
returns: A list of [Invite](https://platform.openai.com/docs/api-reference/invite/object) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"object": "organization.invite",
"id": "invite-abc",
"email": "user@example.com",
"role": "owner",
"status": "accepted",
"invited_at": 1711471533,
"expires_at": 1711471533,
"accepted_at": 1711471533
}
],
"first_id": "invite-abc",
"last_id": "invite-abc",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/organization/invites?after=invite-abc&limit=20 \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Returns a list of invites in the organization.
post:
summary: Create invite
operationId: inviteUser
tags:
- Invites
requestBody:
description: The invite request payload.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/InviteRequest'
responses:
'200':
description: User invited successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/Invite'
x-oaiMeta:
name: Create invite
group: administration
returns: The created [Invite](https://platform.openai.com/docs/api-reference/invite/object) object.
examples:
response: |
{
"object": "organization.invite",
"id": "invite-def",
"email": "anotheruser@example.com",
"role": "reader",
"status": "pending",
"invited_at": 1711471533,
"expires_at": 1711471533,
"accepted_at": null,
"projects": [
{
"id": "project-xyz",
"role": "member"
},
{
"id": "project-abc",
"role": "owner"
}
]
}
request:
curl: |
curl -X POST https://api.openai.com/v1/organization/invites \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"email": "anotheruser@example.com",
"role": "reader",
"projects": [
{
"id": "project-xyz",
"role": "member"
},
{
"id": "project-abc",
"role": "owner"
}
]
}'
description: >-
Create an invite for a user to the organization. The invite must be accepted by the user before they
have access to the organization.
/organization/invites/{invite_id}:
get:
summary: Retrieve invite
operationId: retrieve-invite
tags:
- Invites
parameters:
- in: path
name: invite_id
required: true
schema:
type: string
description: The ID of the invite to retrieve.
responses:
'200':
description: Invite retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/Invite'
x-oaiMeta:
name: Retrieve invite
group: administration
returns: >-
The [Invite](https://platform.openai.com/docs/api-reference/invite/object) object matching the
specified ID.
examples:
response: |
{
"object": "organization.invite",
"id": "invite-abc",
"email": "user@example.com",
"role": "owner",
"status": "accepted",
"invited_at": 1711471533,
"expires_at": 1711471533,
"accepted_at": 1711471533
}
request:
curl: |
curl https://api.openai.com/v1/organization/invites/invite-abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Retrieves an invite.
delete:
summary: Delete invite
operationId: delete-invite
tags:
- Invites
parameters:
- in: path
name: invite_id
required: true
schema:
type: string
description: The ID of the invite to delete.
responses:
'200':
description: Invite deleted successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/InviteDeleteResponse'
x-oaiMeta:
name: Delete invite
group: administration
returns: Confirmation that the invite has been deleted
examples:
response: |
{
"object": "organization.invite.deleted",
"id": "invite-abc",
"deleted": true
}
request:
curl: |
curl -X DELETE https://api.openai.com/v1/organization/invites/invite-abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Delete an invite. If the invite has already been accepted, it cannot be deleted.
/organization/projects:
get:
summary: List projects
operationId: list-projects
tags:
- Projects
parameters:
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
required: false
schema:
type: string
- name: include_archived
in: query
schema:
type: boolean
default: false
description: >-
If `true` returns all projects including those that have been `archived`. Archived projects are
not included by default.
responses:
'200':
description: Projects listed successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectListResponse'
x-oaiMeta:
name: List projects
group: administration
returns: A list of [Project](https://platform.openai.com/docs/api-reference/projects/object) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "proj_abc",
"object": "organization.project",
"name": "Project example",
"created_at": 1711471533,
"archived_at": null,
"status": "active"
}
],
"first_id": "proj-abc",
"last_id": "proj-xyz",
"has_more": false
}
request:
curl: >
curl
https://api.openai.com/v1/organization/projects?after=proj_abc&limit=20&include_archived=false \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Returns a list of projects.
post:
summary: Create project
operationId: create-project
tags:
- Projects
requestBody:
description: The project create request payload.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectCreateRequest'
responses:
'200':
description: Project created successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/Project'
x-oaiMeta:
name: Create project
group: administration
returns: The created [Project](https://platform.openai.com/docs/api-reference/projects/object) object.
examples:
response: |
{
"id": "proj_abc",
"object": "organization.project",
"name": "Project ABC",
"created_at": 1711471533,
"archived_at": null,
"status": "active"
}
request:
curl: |
curl -X POST https://api.openai.com/v1/organization/projects \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"name": "Project ABC"
}'
description: Create a new project in the organization. Projects can be created and archived, but cannot be deleted.
/organization/projects/{project_id}:
get:
summary: Retrieve project
operationId: retrieve-project
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
responses:
'200':
description: Project retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/Project'
x-oaiMeta:
name: Retrieve project
group: administration
description: Retrieve a project.
returns: >-
The [Project](https://platform.openai.com/docs/api-reference/projects/object) object matching the
specified ID.
examples:
response: |
{
"id": "proj_abc",
"object": "organization.project",
"name": "Project example",
"created_at": 1711471533,
"archived_at": null,
"status": "active"
}
request:
curl: |
curl https://api.openai.com/v1/organization/projects/proj_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Retrieves a project.
post:
summary: Modify project
operationId: modify-project
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
requestBody:
description: The project update request payload.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectUpdateRequest'
responses:
'200':
description: Project updated successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/Project'
'400':
description: Error response when updating the default project.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
x-oaiMeta:
name: Modify project
group: administration
returns: The updated [Project](https://platform.openai.com/docs/api-reference/projects/object) object.
examples:
response: ''
request:
curl: |
curl -X POST https://api.openai.com/v1/organization/projects/proj_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"name": "Project DEF"
}'
description: Modifies a project in the organization.
/organization/projects/{project_id}/api_keys:
get:
summary: List project API keys
operationId: list-project-api-keys
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
required: false
schema:
type: string
responses:
'200':
description: Project API keys listed successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectApiKeyListResponse'
x-oaiMeta:
name: List project API keys
group: administration
returns: >-
A list of [ProjectApiKey](https://platform.openai.com/docs/api-reference/project-api-keys/object)
objects.
examples:
response: |
{
"object": "list",
"data": [
{
"object": "organization.project.api_key",
"redacted_value": "sk-abc...def",
"name": "My API Key",
"created_at": 1711471533,
"last_used_at": 1711471534,
"id": "key_abc",
"owner": {
"type": "user",
"user": {
"object": "organization.project.user",
"id": "user_abc",
"name": "First Last",
"email": "user@example.com",
"role": "owner",
"added_at": 1711471533
}
}
}
],
"first_id": "key_abc",
"last_id": "key_xyz",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/organization/projects/proj_abc/api_keys?after=key_abc&limit=20 \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Returns a list of API keys in the project.
/organization/projects/{project_id}/api_keys/{key_id}:
get:
summary: Retrieve project API key
operationId: retrieve-project-api-key
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
- name: key_id
in: path
description: The ID of the API key.
required: true
schema:
type: string
responses:
'200':
description: Project API key retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectApiKey'
x-oaiMeta:
name: Retrieve project API key
group: administration
returns: >-
The [ProjectApiKey](https://platform.openai.com/docs/api-reference/project-api-keys/object) object
matching the specified ID.
examples:
response: |
{
"object": "organization.project.api_key",
"redacted_value": "sk-abc...def",
"name": "My API Key",
"created_at": 1711471533,
"last_used_at": 1711471534,
"id": "key_abc",
"owner": {
"type": "user",
"user": {
"object": "organization.project.user",
"id": "user_abc",
"name": "First Last",
"email": "user@example.com",
"role": "owner",
"added_at": 1711471533
}
}
}
request:
curl: |
curl https://api.openai.com/v1/organization/projects/proj_abc/api_keys/key_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Retrieves an API key in the project.
delete:
summary: Delete project API key
operationId: delete-project-api-key
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
- name: key_id
in: path
description: The ID of the API key.
required: true
schema:
type: string
responses:
'200':
description: Project API key deleted successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectApiKeyDeleteResponse'
'400':
description: Error response for various conditions.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
x-oaiMeta:
name: Delete project API key
group: administration
returns: Confirmation of the key's deletion or an error if the key belonged to a service account
examples:
response: |
{
"object": "organization.project.api_key.deleted",
"id": "key_abc",
"deleted": true
}
request:
curl: |
curl -X DELETE https://api.openai.com/v1/organization/projects/proj_abc/api_keys/key_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Deletes an API key from the project.
/organization/projects/{project_id}/archive:
post:
summary: Archive project
operationId: archive-project
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
responses:
'200':
description: Project archived successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/Project'
x-oaiMeta:
name: Archive project
group: administration
returns: The archived [Project](https://platform.openai.com/docs/api-reference/projects/object) object.
examples:
response: |
{
"id": "proj_abc",
"object": "organization.project",
"name": "Project DEF",
"created_at": 1711471533,
"archived_at": 1711471533,
"status": "archived"
}
request:
curl: |
curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/archive \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Archives a project in the organization. Archived projects cannot be used or updated.
/organization/projects/{project_id}/certificates:
get:
summary: List project certificates
operationId: listProjectCertificates
tags:
- Certificates
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
required: false
schema:
type: string
- name: order
in: query
description: >
Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
descending order.
schema:
type: string
default: desc
enum:
- asc
- desc
responses:
'200':
description: Certificates listed successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ListCertificatesResponse'
x-oaiMeta:
name: List project certificates
group: administration
returns: A list of [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) objects.
examples:
request:
curl: |
curl https://api.openai.com/v1/organization/projects/proj_abc/certificates \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY"
response: |
{
"object": "list",
"data": [
{
"object": "organization.project.certificate",
"id": "cert_abc",
"name": "My Example Certificate",
"active": true,
"created_at": 1234567,
"certificate_details": {
"valid_at": 12345667,
"expires_at": 12345678
}
},
],
"first_id": "cert_abc",
"last_id": "cert_abc",
"has_more": false
}
description: List certificates for this project.
/organization/projects/{project_id}/certificates/activate:
post:
summary: Activate certificates for project
operationId: activateProjectCertificates
tags:
- Certificates
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
requestBody:
description: The certificate activation payload.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ToggleCertificatesRequest'
responses:
'200':
description: Certificates activated successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ListCertificatesResponse'
x-oaiMeta:
name: Activate certificates for project
group: administration
returns: >-
A list of [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) objects
that were activated.
examples:
request:
curl: |
curl https://api.openai.com/v1/organization/projects/proj_abc/certificates/activate \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"data": ["cert_abc", "cert_def"]
}'
response: |
{
"object": "organization.project.certificate.activation",
"data": [
{
"object": "organization.project.certificate",
"id": "cert_abc",
"name": "My Example Certificate",
"active": true,
"created_at": 1234567,
"certificate_details": {
"valid_at": 12345667,
"expires_at": 12345678
}
},
{
"object": "organization.project.certificate",
"id": "cert_def",
"name": "My Example Certificate 2",
"active": true,
"created_at": 1234567,
"certificate_details": {
"valid_at": 12345667,
"expires_at": 12345678
}
},
],
}
description: |
Activate certificates at the project level.
You can atomically and idempotently activate up to 10 certificates at a time.
/organization/projects/{project_id}/certificates/deactivate:
post:
summary: Deactivate certificates for project
operationId: deactivateProjectCertificates
tags:
- Certificates
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
requestBody:
description: The certificate deactivation payload.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ToggleCertificatesRequest'
responses:
'200':
description: Certificates deactivated successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ListCertificatesResponse'
x-oaiMeta:
name: Deactivate certificates for project
group: administration
returns: >-
A list of [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) objects
that were deactivated.
examples:
request:
curl: |
curl https://api.openai.com/v1/organization/projects/proj_abc/certificates/deactivate \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"data": ["cert_abc", "cert_def"]
}'
response: |
{
"object": "organization.project.certificate.deactivation",
"data": [
{
"object": "organization.project.certificate",
"id": "cert_abc",
"name": "My Example Certificate",
"active": false,
"created_at": 1234567,
"certificate_details": {
"valid_at": 12345667,
"expires_at": 12345678
}
},
{
"object": "organization.project.certificate",
"id": "cert_def",
"name": "My Example Certificate 2",
"active": false,
"created_at": 1234567,
"certificate_details": {
"valid_at": 12345667,
"expires_at": 12345678
}
},
],
}
description: |
Deactivate certificates at the project level. You can atomically and
idempotently deactivate up to 10 certificates at a time.
/organization/projects/{project_id}/rate_limits:
get:
summary: List project rate limits
operationId: list-project-rate-limits
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
- name: limit
in: query
description: |
A limit on the number of objects to be returned. The default is 100.
required: false
schema:
type: integer
default: 100
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
required: false
schema:
type: string
- name: before
in: query
description: >
A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, beginning with obj_foo, your
subsequent call can include before=obj_foo in order to fetch the previous page of the list.
required: false
schema:
type: string
responses:
'200':
description: Project rate limits listed successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectRateLimitListResponse'
x-oaiMeta:
name: List project rate limits
group: administration
returns: >-
A list of
[ProjectRateLimit](https://platform.openai.com/docs/api-reference/project-rate-limits/object)
objects.
examples:
response: |
{
"object": "list",
"data": [
{
"object": "project.rate_limit",
"id": "rl-ada",
"model": "ada",
"max_requests_per_1_minute": 600,
"max_tokens_per_1_minute": 150000,
"max_images_per_1_minute": 10
}
],
"first_id": "rl-ada",
"last_id": "rl-ada",
"has_more": false
}
request:
curl: >
curl https://api.openai.com/v1/organization/projects/proj_abc/rate_limits?after=rl_xxx&limit=20
\
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
error_response: |
{
"code": 404,
"message": "The project {project_id} was not found"
}
description: Returns the rate limits per model for a project.
/organization/projects/{project_id}/rate_limits/{rate_limit_id}:
post:
summary: Modify project rate limit
operationId: update-project-rate-limits
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
- name: rate_limit_id
in: path
description: The ID of the rate limit.
required: true
schema:
type: string
requestBody:
description: The project rate limit update request payload.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectRateLimitUpdateRequest'
responses:
'200':
description: Project rate limit updated successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectRateLimit'
'400':
description: Error response for various conditions.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
x-oaiMeta:
name: Modify project rate limit
group: administration
returns: >-
The updated
[ProjectRateLimit](https://platform.openai.com/docs/api-reference/project-rate-limits/object)
object.
examples:
response: |
{
"object": "project.rate_limit",
"id": "rl-ada",
"model": "ada",
"max_requests_per_1_minute": 600,
"max_tokens_per_1_minute": 150000,
"max_images_per_1_minute": 10
}
request:
curl: |
curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/rate_limits/rl_xxx \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"max_requests_per_1_minute": 500
}'
error_response: |
{
"code": 404,
"message": "The project {project_id} was not found"
}
description: Updates a project rate limit.
/organization/projects/{project_id}/service_accounts:
get:
summary: List project service accounts
operationId: list-project-service-accounts
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
required: false
schema:
type: string
responses:
'200':
description: Project service accounts listed successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectServiceAccountListResponse'
'400':
description: Error response when project is archived.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
x-oaiMeta:
name: List project service accounts
group: administration
returns: >-
A list of
[ProjectServiceAccount](https://platform.openai.com/docs/api-reference/project-service-accounts/object)
objects.
examples:
response: |
{
"object": "list",
"data": [
{
"object": "organization.project.service_account",
"id": "svc_acct_abc",
"name": "Service Account",
"role": "owner",
"created_at": 1711471533
}
],
"first_id": "svc_acct_abc",
"last_id": "svc_acct_xyz",
"has_more": false
}
request:
curl: >
curl
https://api.openai.com/v1/organization/projects/proj_abc/service_accounts?after=custom_id&limit=20
\
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Returns a list of service accounts in the project.
post:
summary: Create project service account
operationId: create-project-service-account
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
requestBody:
description: The project service account create request payload.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectServiceAccountCreateRequest'
responses:
'200':
description: Project service account created successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectServiceAccountCreateResponse'
'400':
description: Error response when project is archived.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
x-oaiMeta:
name: Create project service account
group: administration
returns: >-
The created
[ProjectServiceAccount](https://platform.openai.com/docs/api-reference/project-service-accounts/object)
object.
examples:
response: |
{
"object": "organization.project.service_account",
"id": "svc_acct_abc",
"name": "Production App",
"role": "member",
"created_at": 1711471533,
"api_key": {
"object": "organization.project.service_account.api_key",
"value": "sk-abcdefghijklmnop123",
"name": "Secret Key",
"created_at": 1711471533,
"id": "key_abc"
}
}
request:
curl: |
curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/service_accounts \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"name": "Production App"
}'
description: >-
Creates a new service account in the project. This also returns an unredacted API key for the service
account.
/organization/projects/{project_id}/service_accounts/{service_account_id}:
get:
summary: Retrieve project service account
operationId: retrieve-project-service-account
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
- name: service_account_id
in: path
description: The ID of the service account.
required: true
schema:
type: string
responses:
'200':
description: Project service account retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectServiceAccount'
x-oaiMeta:
name: Retrieve project service account
group: administration
returns: >-
The
[ProjectServiceAccount](https://platform.openai.com/docs/api-reference/project-service-accounts/object)
object matching the specified ID.
examples:
response: |
{
"object": "organization.project.service_account",
"id": "svc_acct_abc",
"name": "Service Account",
"role": "owner",
"created_at": 1711471533
}
request:
curl: |
curl https://api.openai.com/v1/organization/projects/proj_abc/service_accounts/svc_acct_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Retrieves a service account in the project.
delete:
summary: Delete project service account
operationId: delete-project-service-account
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
- name: service_account_id
in: path
description: The ID of the service account.
required: true
schema:
type: string
responses:
'200':
description: Project service account deleted successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectServiceAccountDeleteResponse'
x-oaiMeta:
name: Delete project service account
group: administration
returns: >-
Confirmation of service account being deleted, or an error in case of an archived project, which has
no service accounts
examples:
response: |
{
"object": "organization.project.service_account.deleted",
"id": "svc_acct_abc",
"deleted": true
}
request:
curl: >
curl -X DELETE
https://api.openai.com/v1/organization/projects/proj_abc/service_accounts/svc_acct_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Deletes a service account from the project.
/organization/projects/{project_id}/users:
get:
summary: List project users
operationId: list-project-users
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
required: false
schema:
type: string
responses:
'200':
description: Project users listed successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectUserListResponse'
'400':
description: Error response when project is archived.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
x-oaiMeta:
name: List project users
group: administration
returns: >-
A list of [ProjectUser](https://platform.openai.com/docs/api-reference/project-users/object)
objects.
examples:
response: |
{
"object": "list",
"data": [
{
"object": "organization.project.user",
"id": "user_abc",
"name": "First Last",
"email": "user@example.com",
"role": "owner",
"added_at": 1711471533
}
],
"first_id": "user-abc",
"last_id": "user-xyz",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/organization/projects/proj_abc/users?after=user_abc&limit=20 \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Returns a list of users in the project.
post:
summary: Create project user
operationId: create-project-user
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
tags:
- Projects
requestBody:
description: The project user create request payload.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectUserCreateRequest'
responses:
'200':
description: User added to project successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectUser'
'400':
description: Error response for various conditions.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
x-oaiMeta:
name: Create project user
group: administration
returns: >-
The created [ProjectUser](https://platform.openai.com/docs/api-reference/project-users/object)
object.
examples:
response: |
{
"object": "organization.project.user",
"id": "user_abc",
"email": "user@example.com",
"role": "owner",
"added_at": 1711471533
}
request:
curl: |
curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/users \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"user_id": "user_abc",
"role": "member"
}'
description: >-
Adds a user to the project. Users must already be members of the organization to be added to a
project.
/organization/projects/{project_id}/users/{user_id}:
get:
summary: Retrieve project user
operationId: retrieve-project-user
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
- name: user_id
in: path
description: The ID of the user.
required: true
schema:
type: string
responses:
'200':
description: Project user retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectUser'
x-oaiMeta:
name: Retrieve project user
group: administration
returns: >-
The [ProjectUser](https://platform.openai.com/docs/api-reference/project-users/object) object
matching the specified ID.
examples:
response: |
{
"object": "organization.project.user",
"id": "user_abc",
"name": "First Last",
"email": "user@example.com",
"role": "owner",
"added_at": 1711471533
}
request:
curl: |
curl https://api.openai.com/v1/organization/projects/proj_abc/users/user_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Retrieves a user in the project.
post:
summary: Modify project user
operationId: modify-project-user
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
- name: user_id
in: path
description: The ID of the user.
required: true
schema:
type: string
requestBody:
description: The project user update request payload.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectUserUpdateRequest'
responses:
'200':
description: Project user's role updated successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectUser'
'400':
description: Error response for various conditions.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
x-oaiMeta:
name: Modify project user
group: administration
returns: >-
The updated [ProjectUser](https://platform.openai.com/docs/api-reference/project-users/object)
object.
examples:
response: |
{
"object": "organization.project.user",
"id": "user_abc",
"name": "First Last",
"email": "user@example.com",
"role": "owner",
"added_at": 1711471533
}
request:
curl: |
curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/users/user_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"role": "owner"
}'
description: Modifies a user's role in the project.
delete:
summary: Delete project user
operationId: delete-project-user
tags:
- Projects
parameters:
- name: project_id
in: path
description: The ID of the project.
required: true
schema:
type: string
- name: user_id
in: path
description: The ID of the user.
required: true
schema:
type: string
responses:
'200':
description: Project user deleted successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectUserDeleteResponse'
'400':
description: Error response for various conditions.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
x-oaiMeta:
name: Delete project user
group: administration
returns: >-
Confirmation that project has been deleted or an error in case of an archived project, which has no
users
examples:
response: |
{
"object": "organization.project.user.deleted",
"id": "user_abc",
"deleted": true
}
request:
curl: |
curl -X DELETE https://api.openai.com/v1/organization/projects/proj_abc/users/user_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Deletes a user from the project.
/organization/usage/audio_speeches:
get:
summary: Audio speeches
operationId: usage-audio-speeches
tags:
- Usage
parameters:
- name: start_time
in: query
description: Start time (Unix seconds) of the query time range, inclusive.
required: true
schema:
type: integer
- name: end_time
in: query
description: End time (Unix seconds) of the query time range, exclusive.
required: false
schema:
type: integer
- name: bucket_width
in: query
description: >-
Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
`1d`.
required: false
schema:
type: string
enum:
- 1m
- 1h
- 1d
default: 1d
- name: project_ids
in: query
description: Return only usage for these projects.
required: false
schema:
type: array
items:
type: string
- name: user_ids
in: query
description: Return only usage for these users.
required: false
schema:
type: array
items:
type: string
- name: api_key_ids
in: query
description: Return only usage for these API keys.
required: false
schema:
type: array
items:
type: string
- name: models
in: query
description: Return only usage for these models.
required: false
schema:
type: array
items:
type: string
- name: group_by
in: query
description: >-
Group the usage data by the specified fields. Support fields include `project_id`, `user_id`,
`api_key_id`, `model` or any combination of them.
required: false
schema:
type: array
items:
type: string
enum:
- project_id
- user_id
- api_key_id
- model
- name: limit
in: query
description: |
Specifies the number of buckets to return.
- `bucket_width=1d`: default: 7, max: 31
- `bucket_width=1h`: default: 24, max: 168
- `bucket_width=1m`: default: 60, max: 1440
required: false
schema:
type: integer
- name: page
in: query
description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
schema:
type: string
responses:
'200':
description: Usage data retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/UsageResponse'
x-oaiMeta:
name: Audio speeches
group: usage-audio-speeches
returns: >-
A list of paginated, time bucketed [Audio speeches
usage](https://platform.openai.com/docs/api-reference/usage/audio_speeches_object) objects.
examples:
response: |
{
"object": "page",
"data": [
{
"object": "bucket",
"start_time": 1730419200,
"end_time": 1730505600,
"results": [
{
"object": "organization.usage.audio_speeches.result",
"characters": 45,
"num_model_requests": 1,
"project_id": null,
"user_id": null,
"api_key_id": null,
"model": null
}
]
}
],
"has_more": false,
"next_page": null
}
request:
curl: >
curl "https://api.openai.com/v1/organization/usage/audio_speeches?start_time=1730419200&limit=1"
\
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Get audio speeches usage details for the organization.
/organization/usage/audio_transcriptions:
get:
summary: Audio transcriptions
operationId: usage-audio-transcriptions
tags:
- Usage
parameters:
- name: start_time
in: query
description: Start time (Unix seconds) of the query time range, inclusive.
required: true
schema:
type: integer
- name: end_time
in: query
description: End time (Unix seconds) of the query time range, exclusive.
required: false
schema:
type: integer
- name: bucket_width
in: query
description: >-
Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
`1d`.
required: false
schema:
type: string
enum:
- 1m
- 1h
- 1d
default: 1d
- name: project_ids
in: query
description: Return only usage for these projects.
required: false
schema:
type: array
items:
type: string
- name: user_ids
in: query
description: Return only usage for these users.
required: false
schema:
type: array
items:
type: string
- name: api_key_ids
in: query
description: Return only usage for these API keys.
required: false
schema:
type: array
items:
type: string
- name: models
in: query
description: Return only usage for these models.
required: false
schema:
type: array
items:
type: string
- name: group_by
in: query
description: >-
Group the usage data by the specified fields. Support fields include `project_id`, `user_id`,
`api_key_id`, `model` or any combination of them.
required: false
schema:
type: array
items:
type: string
enum:
- project_id
- user_id
- api_key_id
- model
- name: limit
in: query
description: |
Specifies the number of buckets to return.
- `bucket_width=1d`: default: 7, max: 31
- `bucket_width=1h`: default: 24, max: 168
- `bucket_width=1m`: default: 60, max: 1440
required: false
schema:
type: integer
- name: page
in: query
description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
schema:
type: string
responses:
'200':
description: Usage data retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/UsageResponse'
x-oaiMeta:
name: Audio transcriptions
group: usage-audio-transcriptions
returns: >-
A list of paginated, time bucketed [Audio transcriptions
usage](https://platform.openai.com/docs/api-reference/usage/audio_transcriptions_object) objects.
examples:
response: |
{
"object": "page",
"data": [
{
"object": "bucket",
"start_time": 1730419200,
"end_time": 1730505600,
"results": [
{
"object": "organization.usage.audio_transcriptions.result",
"seconds": 20,
"num_model_requests": 1,
"project_id": null,
"user_id": null,
"api_key_id": null,
"model": null
}
]
}
],
"has_more": false,
"next_page": null
}
request:
curl: >
curl
"https://api.openai.com/v1/organization/usage/audio_transcriptions?start_time=1730419200&limit=1"
\
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Get audio transcriptions usage details for the organization.
/organization/usage/code_interpreter_sessions:
get:
summary: Code interpreter sessions
operationId: usage-code-interpreter-sessions
tags:
- Usage
parameters:
- name: start_time
in: query
description: Start time (Unix seconds) of the query time range, inclusive.
required: true
schema:
type: integer
- name: end_time
in: query
description: End time (Unix seconds) of the query time range, exclusive.
required: false
schema:
type: integer
- name: bucket_width
in: query
description: >-
Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
`1d`.
required: false
schema:
type: string
enum:
- 1m
- 1h
- 1d
default: 1d
- name: project_ids
in: query
description: Return only usage for these projects.
required: false
schema:
type: array
items:
type: string
- name: group_by
in: query
description: Group the usage data by the specified fields. Support fields include `project_id`.
required: false
schema:
type: array
items:
type: string
enum:
- project_id
- name: limit
in: query
description: |
Specifies the number of buckets to return.
- `bucket_width=1d`: default: 7, max: 31
- `bucket_width=1h`: default: 24, max: 168
- `bucket_width=1m`: default: 60, max: 1440
required: false
schema:
type: integer
- name: page
in: query
description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
schema:
type: string
responses:
'200':
description: Usage data retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/UsageResponse'
x-oaiMeta:
name: Code interpreter sessions
group: usage-code-interpreter-sessions
returns: >-
A list of paginated, time bucketed [Code interpreter sessions
usage](https://platform.openai.com/docs/api-reference/usage/code_interpreter_sessions_object)
objects.
examples:
response: |
{
"object": "page",
"data": [
{
"object": "bucket",
"start_time": 1730419200,
"end_time": 1730505600,
"results": [
{
"object": "organization.usage.code_interpreter_sessions.result",
"num_sessions": 1,
"project_id": null
}
]
}
],
"has_more": false,
"next_page": null
}
request:
curl: >
curl
"https://api.openai.com/v1/organization/usage/code_interpreter_sessions?start_time=1730419200&limit=1"
\
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Get code interpreter sessions usage details for the organization.
/organization/usage/completions:
get:
summary: Completions
operationId: usage-completions
tags:
- Usage
parameters:
- name: start_time
in: query
description: Start time (Unix seconds) of the query time range, inclusive.
required: true
schema:
type: integer
- name: end_time
in: query
description: End time (Unix seconds) of the query time range, exclusive.
required: false
schema:
type: integer
- name: bucket_width
in: query
description: >-
Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
`1d`.
required: false
schema:
type: string
enum:
- 1m
- 1h
- 1d
default: 1d
- name: project_ids
in: query
description: Return only usage for these projects.
required: false
schema:
type: array
items:
type: string
- name: user_ids
in: query
description: Return only usage for these users.
required: false
schema:
type: array
items:
type: string
- name: api_key_ids
in: query
description: Return only usage for these API keys.
required: false
schema:
type: array
items:
type: string
- name: models
in: query
description: Return only usage for these models.
required: false
schema:
type: array
items:
type: string
- name: batch
in: query
description: >
If `true`, return batch jobs only. If `false`, return non-batch jobs only. By default, return
both.
required: false
schema:
type: boolean
- name: group_by
in: query
description: >-
Group the usage data by the specified fields. Support fields include `project_id`, `user_id`,
`api_key_id`, `model`, `batch` or any combination of them.
required: false
schema:
type: array
items:
type: string
enum:
- project_id
- user_id
- api_key_id
- model
- batch
- name: limit
in: query
description: |
Specifies the number of buckets to return.
- `bucket_width=1d`: default: 7, max: 31
- `bucket_width=1h`: default: 24, max: 168
- `bucket_width=1m`: default: 60, max: 1440
required: false
schema:
type: integer
- name: page
in: query
description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
schema:
type: string
responses:
'200':
description: Usage data retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/UsageResponse'
x-oaiMeta:
name: Completions
group: usage-completions
returns: >-
A list of paginated, time bucketed [Completions
usage](https://platform.openai.com/docs/api-reference/usage/completions_object) objects.
examples:
response: |
{
"object": "page",
"data": [
{
"object": "bucket",
"start_time": 1730419200,
"end_time": 1730505600,
"results": [
{
"object": "organization.usage.completions.result",
"input_tokens": 1000,
"output_tokens": 500,
"input_cached_tokens": 800,
"input_audio_tokens": 0,
"output_audio_tokens": 0,
"num_model_requests": 5,
"project_id": null,
"user_id": null,
"api_key_id": null,
"model": null,
"batch": null
}
]
}
],
"has_more": true,
"next_page": "page_AAAAAGdGxdEiJdKOAAAAAGcqsYA="
}
request:
curl: |
curl "https://api.openai.com/v1/organization/usage/completions?start_time=1730419200&limit=1" \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Get completions usage details for the organization.
/organization/usage/embeddings:
get:
summary: Embeddings
operationId: usage-embeddings
tags:
- Usage
parameters:
- name: start_time
in: query
description: Start time (Unix seconds) of the query time range, inclusive.
required: true
schema:
type: integer
- name: end_time
in: query
description: End time (Unix seconds) of the query time range, exclusive.
required: false
schema:
type: integer
- name: bucket_width
in: query
description: >-
Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
`1d`.
required: false
schema:
type: string
enum:
- 1m
- 1h
- 1d
default: 1d
- name: project_ids
in: query
description: Return only usage for these projects.
required: false
schema:
type: array
items:
type: string
- name: user_ids
in: query
description: Return only usage for these users.
required: false
schema:
type: array
items:
type: string
- name: api_key_ids
in: query
description: Return only usage for these API keys.
required: false
schema:
type: array
items:
type: string
- name: models
in: query
description: Return only usage for these models.
required: false
schema:
type: array
items:
type: string
- name: group_by
in: query
description: >-
Group the usage data by the specified fields. Support fields include `project_id`, `user_id`,
`api_key_id`, `model` or any combination of them.
required: false
schema:
type: array
items:
type: string
enum:
- project_id
- user_id
- api_key_id
- model
- name: limit
in: query
description: |
Specifies the number of buckets to return.
- `bucket_width=1d`: default: 7, max: 31
- `bucket_width=1h`: default: 24, max: 168
- `bucket_width=1m`: default: 60, max: 1440
required: false
schema:
type: integer
- name: page
in: query
description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
schema:
type: string
responses:
'200':
description: Usage data retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/UsageResponse'
x-oaiMeta:
name: Embeddings
group: usage-embeddings
returns: >-
A list of paginated, time bucketed [Embeddings
usage](https://platform.openai.com/docs/api-reference/usage/embeddings_object) objects.
examples:
response: |
{
"object": "page",
"data": [
{
"object": "bucket",
"start_time": 1730419200,
"end_time": 1730505600,
"results": [
{
"object": "organization.usage.embeddings.result",
"input_tokens": 16,
"num_model_requests": 2,
"project_id": null,
"user_id": null,
"api_key_id": null,
"model": null
}
]
}
],
"has_more": false,
"next_page": null
}
request:
curl: |
curl "https://api.openai.com/v1/organization/usage/embeddings?start_time=1730419200&limit=1" \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Get embeddings usage details for the organization.
/organization/usage/images:
get:
summary: Images
operationId: usage-images
tags:
- Usage
parameters:
- name: start_time
in: query
description: Start time (Unix seconds) of the query time range, inclusive.
required: true
schema:
type: integer
- name: end_time
in: query
description: End time (Unix seconds) of the query time range, exclusive.
required: false
schema:
type: integer
- name: bucket_width
in: query
description: >-
Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
`1d`.
required: false
schema:
type: string
enum:
- 1m
- 1h
- 1d
default: 1d
- name: sources
in: query
description: >-
Return only usages for these sources. Possible values are `image.generation`, `image.edit`,
`image.variation` or any combination of them.
required: false
schema:
type: array
items:
type: string
enum:
- image.generation
- image.edit
- image.variation
- name: sizes
in: query
description: >-
Return only usages for these image sizes. Possible values are `256x256`, `512x512`, `1024x1024`,
`1792x1792`, `1024x1792` or any combination of them.
required: false
schema:
type: array
items:
type: string
enum:
- 256x256
- 512x512
- 1024x1024
- 1792x1792
- 1024x1792
- name: project_ids
in: query
description: Return only usage for these projects.
required: false
schema:
type: array
items:
type: string
- name: user_ids
in: query
description: Return only usage for these users.
required: false
schema:
type: array
items:
type: string
- name: api_key_ids
in: query
description: Return only usage for these API keys.
required: false
schema:
type: array
items:
type: string
- name: models
in: query
description: Return only usage for these models.
required: false
schema:
type: array
items:
type: string
- name: group_by
in: query
description: >-
Group the usage data by the specified fields. Support fields include `project_id`, `user_id`,
`api_key_id`, `model`, `size`, `source` or any combination of them.
required: false
schema:
type: array
items:
type: string
enum:
- project_id
- user_id
- api_key_id
- model
- size
- source
- name: limit
in: query
description: |
Specifies the number of buckets to return.
- `bucket_width=1d`: default: 7, max: 31
- `bucket_width=1h`: default: 24, max: 168
- `bucket_width=1m`: default: 60, max: 1440
required: false
schema:
type: integer
- name: page
in: query
description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
schema:
type: string
responses:
'200':
description: Usage data retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/UsageResponse'
x-oaiMeta:
name: Images
group: usage-images
returns: >-
A list of paginated, time bucketed [Images
usage](https://platform.openai.com/docs/api-reference/usage/images_object) objects.
examples:
response: |
{
"object": "page",
"data": [
{
"object": "bucket",
"start_time": 1730419200,
"end_time": 1730505600,
"results": [
{
"object": "organization.usage.images.result",
"images": 2,
"num_model_requests": 2,
"size": null,
"source": null,
"project_id": null,
"user_id": null,
"api_key_id": null,
"model": null
}
]
}
],
"has_more": false,
"next_page": null
}
request:
curl: |
curl "https://api.openai.com/v1/organization/usage/images?start_time=1730419200&limit=1" \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Get images usage details for the organization.
/organization/usage/moderations:
get:
summary: Moderations
operationId: usage-moderations
tags:
- Usage
parameters:
- name: start_time
in: query
description: Start time (Unix seconds) of the query time range, inclusive.
required: true
schema:
type: integer
- name: end_time
in: query
description: End time (Unix seconds) of the query time range, exclusive.
required: false
schema:
type: integer
- name: bucket_width
in: query
description: >-
Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
`1d`.
required: false
schema:
type: string
enum:
- 1m
- 1h
- 1d
default: 1d
- name: project_ids
in: query
description: Return only usage for these projects.
required: false
schema:
type: array
items:
type: string
- name: user_ids
in: query
description: Return only usage for these users.
required: false
schema:
type: array
items:
type: string
- name: api_key_ids
in: query
description: Return only usage for these API keys.
required: false
schema:
type: array
items:
type: string
- name: models
in: query
description: Return only usage for these models.
required: false
schema:
type: array
items:
type: string
- name: group_by
in: query
description: >-
Group the usage data by the specified fields. Support fields include `project_id`, `user_id`,
`api_key_id`, `model` or any combination of them.
required: false
schema:
type: array
items:
type: string
enum:
- project_id
- user_id
- api_key_id
- model
- name: limit
in: query
description: |
Specifies the number of buckets to return.
- `bucket_width=1d`: default: 7, max: 31
- `bucket_width=1h`: default: 24, max: 168
- `bucket_width=1m`: default: 60, max: 1440
required: false
schema:
type: integer
- name: page
in: query
description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
schema:
type: string
responses:
'200':
description: Usage data retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/UsageResponse'
x-oaiMeta:
name: Moderations
group: usage-moderations
returns: >-
A list of paginated, time bucketed [Moderations
usage](https://platform.openai.com/docs/api-reference/usage/moderations_object) objects.
examples:
response: |
{
"object": "page",
"data": [
{
"object": "bucket",
"start_time": 1730419200,
"end_time": 1730505600,
"results": [
{
"object": "organization.usage.moderations.result",
"input_tokens": 16,
"num_model_requests": 2,
"project_id": null,
"user_id": null,
"api_key_id": null,
"model": null
}
]
}
],
"has_more": false,
"next_page": null
}
request:
curl: |
curl "https://api.openai.com/v1/organization/usage/moderations?start_time=1730419200&limit=1" \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Get moderations usage details for the organization.
/organization/usage/vector_stores:
get:
summary: Vector stores
operationId: usage-vector-stores
tags:
- Usage
parameters:
- name: start_time
in: query
description: Start time (Unix seconds) of the query time range, inclusive.
required: true
schema:
type: integer
- name: end_time
in: query
description: End time (Unix seconds) of the query time range, exclusive.
required: false
schema:
type: integer
- name: bucket_width
in: query
description: >-
Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
`1d`.
required: false
schema:
type: string
enum:
- 1m
- 1h
- 1d
default: 1d
- name: project_ids
in: query
description: Return only usage for these projects.
required: false
schema:
type: array
items:
type: string
- name: group_by
in: query
description: Group the usage data by the specified fields. Support fields include `project_id`.
required: false
schema:
type: array
items:
type: string
enum:
- project_id
- name: limit
in: query
description: |
Specifies the number of buckets to return.
- `bucket_width=1d`: default: 7, max: 31
- `bucket_width=1h`: default: 24, max: 168
- `bucket_width=1m`: default: 60, max: 1440
required: false
schema:
type: integer
- name: page
in: query
description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
schema:
type: string
responses:
'200':
description: Usage data retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/UsageResponse'
x-oaiMeta:
name: Vector stores
group: usage-vector-stores
returns: >-
A list of paginated, time bucketed [Vector stores
usage](https://platform.openai.com/docs/api-reference/usage/vector_stores_object) objects.
examples:
response: |
{
"object": "page",
"data": [
{
"object": "bucket",
"start_time": 1730419200,
"end_time": 1730505600,
"results": [
{
"object": "organization.usage.vector_stores.result",
"usage_bytes": 1024,
"project_id": null
}
]
}
],
"has_more": false,
"next_page": null
}
request:
curl: >
curl "https://api.openai.com/v1/organization/usage/vector_stores?start_time=1730419200&limit=1"
\
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Get vector stores usage details for the organization.
/organization/users:
get:
summary: List users
operationId: list-users
tags:
- Users
parameters:
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
required: false
schema:
type: string
- name: emails
in: query
description: Filter by the email address of users.
required: false
schema:
type: array
items:
type: string
responses:
'200':
description: Users listed successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/UserListResponse'
x-oaiMeta:
name: List users
group: administration
returns: A list of [User](https://platform.openai.com/docs/api-reference/users/object) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"object": "organization.user",
"id": "user_abc",
"name": "First Last",
"email": "user@example.com",
"role": "owner",
"added_at": 1711471533
}
],
"first_id": "user-abc",
"last_id": "user-xyz",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/organization/users?after=user_abc&limit=20 \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Lists all of the users in the organization.
/organization/users/{user_id}:
get:
summary: Retrieve user
operationId: retrieve-user
tags:
- Users
parameters:
- name: user_id
in: path
description: The ID of the user.
required: true
schema:
type: string
responses:
'200':
description: User retrieved successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/User'
x-oaiMeta:
name: Retrieve user
group: administration
returns: >-
The [User](https://platform.openai.com/docs/api-reference/users/object) object matching the
specified ID.
examples:
response: |
{
"object": "organization.user",
"id": "user_abc",
"name": "First Last",
"email": "user@example.com",
"role": "owner",
"added_at": 1711471533
}
request:
curl: |
curl https://api.openai.com/v1/organization/users/user_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Retrieves a user by their identifier.
post:
summary: Modify user
operationId: modify-user
tags:
- Users
parameters:
- name: user_id
in: path
description: The ID of the user.
required: true
schema:
type: string
requestBody:
description: The new user role to modify. This must be one of `owner` or `member`.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/UserRoleUpdateRequest'
responses:
'200':
description: User role updated successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/User'
x-oaiMeta:
name: Modify user
group: administration
returns: The updated [User](https://platform.openai.com/docs/api-reference/users/object) object.
examples:
response: |
{
"object": "organization.user",
"id": "user_abc",
"name": "First Last",
"email": "user@example.com",
"role": "owner",
"added_at": 1711471533
}
request:
curl: |
curl -X POST https://api.openai.com/v1/organization/users/user_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{
"role": "owner"
}'
description: Modifies a user's role in the organization.
delete:
summary: Delete user
operationId: delete-user
tags:
- Users
parameters:
- name: user_id
in: path
description: The ID of the user.
required: true
schema:
type: string
responses:
'200':
description: User deleted successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/UserDeleteResponse'
x-oaiMeta:
name: Delete user
group: administration
returns: Confirmation of the deleted user
examples:
response: |
{
"object": "organization.user.deleted",
"id": "user_abc",
"deleted": true
}
request:
curl: |
curl -X DELETE https://api.openai.com/v1/organization/users/user_abc \
-H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
-H "Content-Type: application/json"
description: Deletes a user from the organization.
/realtime/sessions:
post:
summary: Create session
operationId: create-realtime-session
tags:
- Realtime
requestBody:
description: Create an ephemeral API key with the given session configuration.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/RealtimeSessionCreateRequest'
responses:
'200':
description: Session created successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/RealtimeSessionCreateResponse'
x-oaiMeta:
name: Create session
group: realtime
returns: The created Realtime session object, plus an ephemeral key
examples:
response: |
{
"id": "sess_001",
"object": "realtime.session",
"model": "gpt-4o-realtime-preview",
"modalities": ["audio", "text"],
"instructions": "You are a friendly assistant.",
"voice": "alloy",
"input_audio_format": "pcm16",
"output_audio_format": "pcm16",
"input_audio_transcription": {
"model": "whisper-1"
},
"turn_detection": null,
"tools": [],
"tool_choice": "none",
"temperature": 0.7,
"max_response_output_tokens": 200,
"speed": 1.1,
"tracing": "auto",
"client_secret": {
"value": "ek_abc123",
"expires_at": 1234567890
}
}
request:
curl: |
curl -X POST https://api.openai.com/v1/realtime/sessions \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4o-realtime-preview",
"modalities": ["audio", "text"],
"instructions": "You are a friendly assistant."
}'
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const session = await client.beta.realtime.sessions.create();
console.log(session.client_secret);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
session = client.beta.realtime.sessions.create()
print(session.client_secret)
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.realtime.sessions.SessionCreateParams;
import com.openai.models.beta.realtime.sessions.SessionCreateResponse;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
SessionCreateResponse session = client.beta().realtime().sessions().create();
}
}
description: |
Create an ephemeral API token for use in client-side applications with the
Realtime API. Can be configured with the same session parameters as the
`session.update` client event.
It responds with a session object, plus a `client_secret` key which contains
a usable ephemeral API token that can be used to authenticate browser clients
for the Realtime API.
/realtime/transcription_sessions:
post:
summary: Create transcription session
operationId: create-realtime-transcription-session
tags:
- Realtime
requestBody:
description: Create an ephemeral API key with the given session configuration.
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/RealtimeTranscriptionSessionCreateRequest'
responses:
'200':
description: Session created successfully.
content:
application/json:
schema:
$ref: '#/components/schemas/RealtimeTranscriptionSessionCreateResponse'
x-oaiMeta:
name: Create transcription session
group: realtime
returns: >-
The created [Realtime transcription session
object](https://platform.openai.com/docs/api-reference/realtime-sessions/transcription_session_object),
plus an ephemeral key
examples:
response: |
{
"id": "sess_BBwZc7cFV3XizEyKGDCGL",
"object": "realtime.transcription_session",
"modalities": ["audio", "text"],
"turn_detection": {
"type": "server_vad",
"threshold": 0.5,
"prefix_padding_ms": 300,
"silence_duration_ms": 200
},
"input_audio_format": "pcm16",
"input_audio_transcription": {
"model": "gpt-4o-transcribe",
"language": null,
"prompt": ""
},
"client_secret": null
}
request:
curl: |
curl -X POST https://api.openai.com/v1/realtime/transcription_sessions \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{}'
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const transcriptionSession = await client.beta.realtime.transcriptionSessions.create();
console.log(transcriptionSession.client_secret);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
transcription_session = client.beta.realtime.transcription_sessions.create()
print(transcription_session.client_secret)
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.realtime.transcriptionsessions.TranscriptionSession;
import com.openai.models.beta.realtime.transcriptionsessions.TranscriptionSessionCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
TranscriptionSession transcriptionSession = client.beta().realtime().transcriptionSessions().create();
}
}
description: |
Create an ephemeral API token for use in client-side applications with the
Realtime API specifically for realtime transcriptions.
Can be configured with the same session parameters as the `transcription_session.update` client event.
It responds with a session object, plus a `client_secret` key which contains
a usable ephemeral API token that can be used to authenticate browser clients
for the Realtime API.
/responses:
post:
operationId: createResponse
tags:
- Responses
summary: Create a model response
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateResponse'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/Response'
text/event-stream:
schema:
$ref: '#/components/schemas/ResponseStreamEvent'
x-oaiMeta:
name: Create a model response
group: responses
returns: |
Returns a [Response](https://platform.openai.com/docs/api-reference/responses/object) object.
path: create
examples:
- title: Text input
request:
curl: |
curl https://api.openai.com/v1/responses \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "gpt-4.1",
"input": "Tell me a three sentence bedtime story about a unicorn."
}'
javascript: |
import OpenAI from "openai";
const openai = new OpenAI();
const response = await openai.responses.create({
model: "gpt-4.1",
input: "Tell me a three sentence bedtime story about a unicorn."
});
console.log(response);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.responses.create()
print(response.id)
csharp: >
using System;
using OpenAI.Responses;
OpenAIResponseClient client = new(
model: "gpt-4.1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
OpenAIResponse response = client.CreateResponse("Tell me a three sentence bedtime story about
a unicorn.");
Console.WriteLine(response.GetOutputText());
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.responses.create();
console.log(response.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/responses"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", response.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.responses.Response;
import com.openai.models.responses.ResponseCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Response response = client.responses().create();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.responses.create
puts(response)
response: |
{
"id": "resp_67ccd2bed1ec8190b14f964abc0542670bb6a6b452d3795b",
"object": "response",
"created_at": 1741476542,
"status": "completed",
"error": null,
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4.1-2025-04-14",
"output": [
{
"type": "message",
"id": "msg_67ccd2bf17f0819081ff3bb2cf6508e60bb6a6b452d3795b",
"status": "completed",
"role": "assistant",
"content": [
{
"type": "output_text",
"text": "In a peaceful grove beneath a silver moon, a unicorn named Lumina discovered a hidden pool that reflected the stars. As she dipped her horn into the water, the pool began to shimmer, revealing a pathway to a magical realm of endless night skies. Filled with wonder, Lumina whispered a wish for all who dream to find their own hidden magic, and as she glanced back, her hoofprints sparkled like stardust.",
"annotations": []
}
]
}
],
"parallel_tool_calls": true,
"previous_response_id": null,
"reasoning": {
"effort": null,
"summary": null
},
"store": true,
"temperature": 1.0,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [],
"top_p": 1.0,
"truncation": "disabled",
"usage": {
"input_tokens": 36,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 87,
"output_tokens_details": {
"reasoning_tokens": 0
},
"total_tokens": 123
},
"user": null,
"metadata": {}
}
- title: Image input
request:
curl: |
curl https://api.openai.com/v1/responses \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "gpt-4.1",
"input": [
{
"role": "user",
"content": [
{"type": "input_text", "text": "what is in this image?"},
{
"type": "input_image",
"image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
}
]
}
]
}'
javascript: |
import OpenAI from "openai";
const openai = new OpenAI();
const response = await openai.responses.create({
model: "gpt-4.1",
input: [
{
role: "user",
content: [
{ type: "input_text", text: "what is in this image?" },
{
type: "input_image",
image_url:
"https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
},
],
},
],
});
console.log(response);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.responses.create()
print(response.id)
csharp: |
using System;
using System.Collections.Generic;
using OpenAI.Responses;
OpenAIResponseClient client = new(
model: "gpt-4.1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
List<ResponseItem> inputItems =
[
ResponseItem.CreateUserMessageItem(
[
ResponseContentPart.CreateInputTextPart("What is in this image?"),
ResponseContentPart.CreateInputImagePart(new Uri("https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"))
]
)
];
OpenAIResponse response = client.CreateResponse(inputItems);
Console.WriteLine(response.GetOutputText());
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.responses.create();
console.log(response.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/responses"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", response.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.responses.Response;
import com.openai.models.responses.ResponseCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Response response = client.responses().create();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.responses.create
puts(response)
response: |
{
"id": "resp_67ccd3a9da748190baa7f1570fe91ac604becb25c45c1d41",
"object": "response",
"created_at": 1741476777,
"status": "completed",
"error": null,
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4.1-2025-04-14",
"output": [
{
"type": "message",
"id": "msg_67ccd3acc8d48190a77525dc6de64b4104becb25c45c1d41",
"status": "completed",
"role": "assistant",
"content": [
{
"type": "output_text",
"text": "The image depicts a scenic landscape with a wooden boardwalk or pathway leading through lush, green grass under a blue sky with some clouds. The setting suggests a peaceful natural area, possibly a park or nature reserve. There are trees and shrubs in the background.",
"annotations": []
}
]
}
],
"parallel_tool_calls": true,
"previous_response_id": null,
"reasoning": {
"effort": null,
"summary": null
},
"store": true,
"temperature": 1.0,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [],
"top_p": 1.0,
"truncation": "disabled",
"usage": {
"input_tokens": 328,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 52,
"output_tokens_details": {
"reasoning_tokens": 0
},
"total_tokens": 380
},
"user": null,
"metadata": {}
}
- title: File input
request:
curl: |
curl https://api.openai.com/v1/responses \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "gpt-4.1",
"input": [
{
"role": "user",
"content": [
{"type": "input_text", "text": "what is in this file?"},
{
"type": "input_file",
"file_url": "https://www.berkshirehathaway.com/letters/2024ltr.pdf"
}
]
}
]
}'
javascript: |
import OpenAI from "openai";
const openai = new OpenAI();
const response = await openai.responses.create({
model: "gpt-4.1",
input: [
{
role: "user",
content: [
{ type: "input_text", text: "what is in this file?" },
{
type: "input_file",
file_url: "https://www.berkshirehathaway.com/letters/2024ltr.pdf",
},
],
},
],
});
console.log(response);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.responses.create()
print(response.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.responses.create();
console.log(response.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/responses"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", response.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.responses.Response;
import com.openai.models.responses.ResponseCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Response response = client.responses().create();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.responses.create
puts(response)
response: |
{
"id": "resp_686eef60237881a2bd1180bb8b13de430e34c516d176ff86",
"object": "response",
"created_at": 1752100704,
"status": "completed",
"background": false,
"error": null,
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"max_tool_calls": null,
"model": "gpt-4.1-2025-04-14",
"output": [
{
"id": "msg_686eef60d3e081a29283bdcbc4322fd90e34c516d176ff86",
"type": "message",
"status": "completed",
"content": [
{
"type": "output_text",
"annotations": [],
"logprobs": [],
"text": "The file seems to contain excerpts from a letter to the shareholders of Berkshire Hathaway Inc., likely written by Warren Buffett. It covers several topics:\n\n1. **Communication Philosophy**: Buffett emphasizes the importance of transparency and candidness in reporting mistakes and successes to shareholders.\n\n2. **Mistakes and Learnings**: The letter acknowledges past mistakes in business assessments and management hires, highlighting the importance of correcting errors promptly.\n\n3. **CEO Succession**: Mention of Greg Abel stepping in as the new CEO and continuing the tradition of honest communication.\n\n4. **Pete Liegl Story**: A detailed account of acquiring Forest River and the relationship with its founder, highlighting trust and effective business decisions.\n\n5. **2024 Performance**: Overview of business performance, particularly in insurance and investment activities, with a focus on GEICO's improvement.\n\n6. **Tax Contributions**: Discussion of significant tax payments to the U.S. Treasury, credited to shareholders' reinvestments.\n\n7. **Investment Strategy**: A breakdown of Berkshire\u2019s investments in both controlled subsidiaries and marketable equities, along with a focus on long-term holding strategies.\n\n8. **American Capitalism**: Reflections on America\u2019s economic development and Berkshire\u2019s role within it.\n\n9. **Property-Casualty Insurance**: Insights into the P/C insurance business model and its challenges and benefits.\n\n10. **Japanese Investments**: Information about Berkshire\u2019s investments in Japanese companies and future plans.\n\n11. **Annual Meeting**: Details about the upcoming annual gathering in Omaha, including schedule changes and new book releases.\n\n12. **Personal Anecdotes**: Light-hearted stories about family and interactions, conveying Buffett's personable approach.\n\n13. **Financial Performance Data**: Tables comparing Berkshire\u2019s annual performance to the S&P 500, showing impressive long-term gains.\n\nOverall, the letter reinforces Berkshire Hathaway's commitment to transparency, investment in both its businesses and the wider economy, and emphasizes strong leadership and prudent financial management."
}
],
"role": "assistant"
}
],
"parallel_tool_calls": true,
"previous_response_id": null,
"reasoning": {
"effort": null,
"summary": null
},
"service_tier": "default",
"store": true,
"temperature": 1.0,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [],
"top_logprobs": 0,
"top_p": 1.0,
"truncation": "disabled",
"usage": {
"input_tokens": 8438,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 398,
"output_tokens_details": {
"reasoning_tokens": 0
},
"total_tokens": 8836
},
"user": null,
"metadata": {}
}
- title: Web search
request:
curl: |
curl https://api.openai.com/v1/responses \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "gpt-4.1",
"tools": [{ "type": "web_search_preview" }],
"input": "What was a positive news story from today?"
}'
javascript: |
import OpenAI from "openai";
const openai = new OpenAI();
const response = await openai.responses.create({
model: "gpt-4.1",
tools: [{ type: "web_search_preview" }],
input: "What was a positive news story from today?",
});
console.log(response);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.responses.create()
print(response.id)
csharp: |
using System;
using OpenAI.Responses;
OpenAIResponseClient client = new(
model: "gpt-4.1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
string userInputText = "What was a positive news story from today?";
ResponseCreationOptions options = new()
{
Tools =
{
ResponseTool.CreateWebSearchTool()
},
};
OpenAIResponse response = client.CreateResponse(userInputText, options);
Console.WriteLine(response.GetOutputText());
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.responses.create();
console.log(response.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/responses"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", response.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.responses.Response;
import com.openai.models.responses.ResponseCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Response response = client.responses().create();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.responses.create
puts(response)
response: |
{
"id": "resp_67ccf18ef5fc8190b16dbee19bc54e5f087bb177ab789d5c",
"object": "response",
"created_at": 1741484430,
"status": "completed",
"error": null,
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4.1-2025-04-14",
"output": [
{
"type": "web_search_call",
"id": "ws_67ccf18f64008190a39b619f4c8455ef087bb177ab789d5c",
"status": "completed"
},
{
"type": "message",
"id": "msg_67ccf190ca3881909d433c50b1f6357e087bb177ab789d5c",
"status": "completed",
"role": "assistant",
"content": [
{
"type": "output_text",
"text": "As of today, March 9, 2025, one notable positive news story...",
"annotations": [
{
"type": "url_citation",
"start_index": 442,
"end_index": 557,
"url": "https://.../?utm_source=chatgpt.com",
"title": "..."
},
{
"type": "url_citation",
"start_index": 962,
"end_index": 1077,
"url": "https://.../?utm_source=chatgpt.com",
"title": "..."
},
{
"type": "url_citation",
"start_index": 1336,
"end_index": 1451,
"url": "https://.../?utm_source=chatgpt.com",
"title": "..."
}
]
}
]
}
],
"parallel_tool_calls": true,
"previous_response_id": null,
"reasoning": {
"effort": null,
"summary": null
},
"store": true,
"temperature": 1.0,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [
{
"type": "web_search_preview",
"domains": [],
"search_context_size": "medium",
"user_location": {
"type": "approximate",
"city": null,
"country": "US",
"region": null,
"timezone": null
}
}
],
"top_p": 1.0,
"truncation": "disabled",
"usage": {
"input_tokens": 328,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 356,
"output_tokens_details": {
"reasoning_tokens": 0
},
"total_tokens": 684
},
"user": null,
"metadata": {}
}
- title: File search
request:
curl: |
curl https://api.openai.com/v1/responses \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "gpt-4.1",
"tools": [{
"type": "file_search",
"vector_store_ids": ["vs_1234567890"],
"max_num_results": 20
}],
"input": "What are the attributes of an ancient brown dragon?"
}'
javascript: |
import OpenAI from "openai";
const openai = new OpenAI();
const response = await openai.responses.create({
model: "gpt-4.1",
tools: [{
type: "file_search",
vector_store_ids: ["vs_1234567890"],
max_num_results: 20
}],
input: "What are the attributes of an ancient brown dragon?",
});
console.log(response);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.responses.create()
print(response.id)
csharp: |
using System;
using OpenAI.Responses;
OpenAIResponseClient client = new(
model: "gpt-4.1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
string userInputText = "What are the attributes of an ancient brown dragon?";
ResponseCreationOptions options = new()
{
Tools =
{
ResponseTool.CreateFileSearchTool(
vectorStoreIds: ["vs_1234567890"],
maxResultCount: 20
)
},
};
OpenAIResponse response = client.CreateResponse(userInputText, options);
Console.WriteLine(response.GetOutputText());
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.responses.create();
console.log(response.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/responses"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", response.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.responses.Response;
import com.openai.models.responses.ResponseCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Response response = client.responses().create();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.responses.create
puts(response)
response: |
{
"id": "resp_67ccf4c55fc48190b71bd0463ad3306d09504fb6872380d7",
"object": "response",
"created_at": 1741485253,
"status": "completed",
"error": null,
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4.1-2025-04-14",
"output": [
{
"type": "file_search_call",
"id": "fs_67ccf4c63cd08190887ef6464ba5681609504fb6872380d7",
"status": "completed",
"queries": [
"attributes of an ancient brown dragon"
],
"results": null
},
{
"type": "message",
"id": "msg_67ccf4c93e5c81909d595b369351a9d309504fb6872380d7",
"status": "completed",
"role": "assistant",
"content": [
{
"type": "output_text",
"text": "The attributes of an ancient brown dragon include...",
"annotations": [
{
"type": "file_citation",
"index": 320,
"file_id": "file-4wDz5b167pAf72nx1h9eiN",
"filename": "dragons.pdf"
},
{
"type": "file_citation",
"index": 576,
"file_id": "file-4wDz5b167pAf72nx1h9eiN",
"filename": "dragons.pdf"
},
{
"type": "file_citation",
"index": 815,
"file_id": "file-4wDz5b167pAf72nx1h9eiN",
"filename": "dragons.pdf"
},
{
"type": "file_citation",
"index": 815,
"file_id": "file-4wDz5b167pAf72nx1h9eiN",
"filename": "dragons.pdf"
},
{
"type": "file_citation",
"index": 1030,
"file_id": "file-4wDz5b167pAf72nx1h9eiN",
"filename": "dragons.pdf"
},
{
"type": "file_citation",
"index": 1030,
"file_id": "file-4wDz5b167pAf72nx1h9eiN",
"filename": "dragons.pdf"
},
{
"type": "file_citation",
"index": 1156,
"file_id": "file-4wDz5b167pAf72nx1h9eiN",
"filename": "dragons.pdf"
},
{
"type": "file_citation",
"index": 1225,
"file_id": "file-4wDz5b167pAf72nx1h9eiN",
"filename": "dragons.pdf"
}
]
}
]
}
],
"parallel_tool_calls": true,
"previous_response_id": null,
"reasoning": {
"effort": null,
"summary": null
},
"store": true,
"temperature": 1.0,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [
{
"type": "file_search",
"filters": null,
"max_num_results": 20,
"ranking_options": {
"ranker": "auto",
"score_threshold": 0.0
},
"vector_store_ids": [
"vs_1234567890"
]
}
],
"top_p": 1.0,
"truncation": "disabled",
"usage": {
"input_tokens": 18307,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 348,
"output_tokens_details": {
"reasoning_tokens": 0
},
"total_tokens": 18655
},
"user": null,
"metadata": {}
}
- title: Streaming
request:
curl: |
curl https://api.openai.com/v1/responses \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "gpt-4.1",
"instructions": "You are a helpful assistant.",
"input": "Hello!",
"stream": true
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.responses.create()
print(response.id)
javascript: |
import OpenAI from "openai";
const openai = new OpenAI();
const response = await openai.responses.create({
model: "gpt-4.1",
instructions: "You are a helpful assistant.",
input: "Hello!",
stream: true,
});
for await (const event of response) {
console.log(event);
}
csharp: >
using System;
using System.ClientModel;
using System.Threading.Tasks;
using OpenAI.Responses;
OpenAIResponseClient client = new(
model: "gpt-4.1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
string userInputText = "Hello!";
ResponseCreationOptions options = new()
{
Instructions = "You are a helpful assistant.",
};
AsyncCollectionResult<StreamingResponseUpdate> responseUpdates =
client.CreateResponseStreamingAsync(userInputText, options);
await foreach (StreamingResponseUpdate responseUpdate in responseUpdates)
{
if (responseUpdate is StreamingResponseOutputTextDeltaUpdate outputTextDeltaUpdate)
{
Console.Write(outputTextDeltaUpdate.Delta);
}
}
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.responses.create();
console.log(response.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/responses"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", response.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.responses.Response;
import com.openai.models.responses.ResponseCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Response response = client.responses().create();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.responses.create
puts(response)
response: >
event: response.created
data:
{"type":"response.created","response":{"id":"resp_67c9fdcecf488190bdd9a0409de3a1ec07b8b0ad4e5eb654","object":"response","created_at":1741290958,"status":"in_progress","error":null,"incomplete_details":null,"instructions":"You
are a helpful
assistant.","max_output_tokens":null,"model":"gpt-4.1-2025-04-14","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
event: response.in_progress
data:
{"type":"response.in_progress","response":{"id":"resp_67c9fdcecf488190bdd9a0409de3a1ec07b8b0ad4e5eb654","object":"response","created_at":1741290958,"status":"in_progress","error":null,"incomplete_details":null,"instructions":"You
are a helpful
assistant.","max_output_tokens":null,"model":"gpt-4.1-2025-04-14","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
event: response.output_item.added
data:
{"type":"response.output_item.added","output_index":0,"item":{"id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","type":"message","status":"in_progress","role":"assistant","content":[]}}
event: response.content_part.added
data:
{"type":"response.content_part.added","item_id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","output_index":0,"content_index":0,"part":{"type":"output_text","text":"","annotations":[]}}
event: response.output_text.delta
data:
{"type":"response.output_text.delta","item_id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","output_index":0,"content_index":0,"delta":"Hi"}
...
event: response.output_text.done
data:
{"type":"response.output_text.done","item_id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","output_index":0,"content_index":0,"text":"Hi
there! How can I assist you today?"}
event: response.content_part.done
data:
{"type":"response.content_part.done","item_id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","output_index":0,"content_index":0,"part":{"type":"output_text","text":"Hi
there! How can I assist you today?","annotations":[]}}
event: response.output_item.done
data:
{"type":"response.output_item.done","output_index":0,"item":{"id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","type":"message","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hi
there! How can I assist you today?","annotations":[]}]}}
event: response.completed
data:
{"type":"response.completed","response":{"id":"resp_67c9fdcecf488190bdd9a0409de3a1ec07b8b0ad4e5eb654","object":"response","created_at":1741290958,"status":"completed","error":null,"incomplete_details":null,"instructions":"You
are a helpful
assistant.","max_output_tokens":null,"model":"gpt-4.1-2025-04-14","output":[{"id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","type":"message","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hi
there! How can I assist you
today?","annotations":[]}]}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":37,"output_tokens":11,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":48},"user":null,"metadata":{}}}
- title: Functions
request:
curl: |
curl https://api.openai.com/v1/responses \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "gpt-4.1",
"input": "What is the weather like in Boston today?",
"tools": [
{
"type": "function",
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"]
}
},
"required": ["location", "unit"]
}
}
],
"tool_choice": "auto"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.responses.create()
print(response.id)
javascript: |
import OpenAI from "openai";
const openai = new OpenAI();
const tools = [
{
type: "function",
name: "get_current_weather",
description: "Get the current weather in a given location",
parameters: {
type: "object",
properties: {
location: {
type: "string",
description: "The city and state, e.g. San Francisco, CA",
},
unit: { type: "string", enum: ["celsius", "fahrenheit"] },
},
required: ["location", "unit"],
},
},
];
const response = await openai.responses.create({
model: "gpt-4.1",
tools: tools,
input: "What is the weather like in Boston today?",
tool_choice: "auto",
});
console.log(response);
csharp: |
using System;
using OpenAI.Responses;
OpenAIResponseClient client = new(
model: "gpt-4.1",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
ResponseTool getCurrentWeatherFunctionTool = ResponseTool.CreateFunctionTool(
functionName: "get_current_weather",
functionDescription: "Get the current weather in a given location",
functionParameters: BinaryData.FromString("""
{
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
},
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
},
"required": ["location", "unit"]
}
"""
)
);
string userInputText = "What is the weather like in Boston today?";
ResponseCreationOptions options = new()
{
Tools =
{
getCurrentWeatherFunctionTool
},
ToolChoice = ResponseToolChoice.CreateAutoChoice(),
};
OpenAIResponse response = client.CreateResponse(userInputText, options);
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.responses.create();
console.log(response.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/responses"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", response.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.responses.Response;
import com.openai.models.responses.ResponseCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Response response = client.responses().create();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.responses.create
puts(response)
response: |
{
"id": "resp_67ca09c5efe0819096d0511c92b8c890096610f474011cc0",
"object": "response",
"created_at": 1741294021,
"status": "completed",
"error": null,
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4.1-2025-04-14",
"output": [
{
"type": "function_call",
"id": "fc_67ca09c6bedc8190a7abfec07b1a1332096610f474011cc0",
"call_id": "call_unLAR8MvFNptuiZK6K6HCy5k",
"name": "get_current_weather",
"arguments": "{\"location\":\"Boston, MA\",\"unit\":\"celsius\"}",
"status": "completed"
}
],
"parallel_tool_calls": true,
"previous_response_id": null,
"reasoning": {
"effort": null,
"summary": null
},
"store": true,
"temperature": 1.0,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [
{
"type": "function",
"description": "Get the current weather in a given location",
"name": "get_current_weather",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
},
"unit": {
"type": "string",
"enum": [
"celsius",
"fahrenheit"
]
}
},
"required": [
"location",
"unit"
]
},
"strict": true
}
],
"top_p": 1.0,
"truncation": "disabled",
"usage": {
"input_tokens": 291,
"output_tokens": 23,
"output_tokens_details": {
"reasoning_tokens": 0
},
"total_tokens": 314
},
"user": null,
"metadata": {}
}
- title: Reasoning
request:
curl: |
curl https://api.openai.com/v1/responses \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "o3-mini",
"input": "How much wood would a woodchuck chuck?",
"reasoning": {
"effort": "high"
}
}'
javascript: |
import OpenAI from "openai";
const openai = new OpenAI();
const response = await openai.responses.create({
model: "o3-mini",
input: "How much wood would a woodchuck chuck?",
reasoning: {
effort: "high"
}
});
console.log(response);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.responses.create()
print(response.id)
csharp: |
using System;
using OpenAI.Responses;
OpenAIResponseClient client = new(
model: "o3-mini",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
string userInputText = "How much wood would a woodchuck chuck?";
ResponseCreationOptions options = new()
{
ReasoningOptions = new()
{
ReasoningEffortLevel = ResponseReasoningEffortLevel.High,
},
};
OpenAIResponse response = client.CreateResponse(userInputText, options);
Console.WriteLine(response.GetOutputText());
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.responses.create();
console.log(response.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/responses"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", response.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.responses.Response;
import com.openai.models.responses.ResponseCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Response response = client.responses().create();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.responses.create
puts(response)
response: |
{
"id": "resp_67ccd7eca01881908ff0b5146584e408072912b2993db808",
"object": "response",
"created_at": 1741477868,
"status": "completed",
"error": null,
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"model": "o1-2024-12-17",
"output": [
{
"type": "message",
"id": "msg_67ccd7f7b5848190a6f3e95d809f6b44072912b2993db808",
"status": "completed",
"role": "assistant",
"content": [
{
"type": "output_text",
"text": "The classic tongue twister...",
"annotations": []
}
]
}
],
"parallel_tool_calls": true,
"previous_response_id": null,
"reasoning": {
"effort": "high",
"summary": null
},
"store": true,
"temperature": 1.0,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [],
"top_p": 1.0,
"truncation": "disabled",
"usage": {
"input_tokens": 81,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 1035,
"output_tokens_details": {
"reasoning_tokens": 832
},
"total_tokens": 1116
},
"user": null,
"metadata": {}
}
description: >
Creates a model response. Provide [text](https://platform.openai.com/docs/guides/text) or
[image](https://platform.openai.com/docs/guides/images) inputs to generate
[text](https://platform.openai.com/docs/guides/text)
or [JSON](https://platform.openai.com/docs/guides/structured-outputs) outputs. Have the model call
your own [custom code](https://platform.openai.com/docs/guides/function-calling) or use built-in
[tools](https://platform.openai.com/docs/guides/tools) like [web
search](https://platform.openai.com/docs/guides/tools-web-search)
or [file search](https://platform.openai.com/docs/guides/tools-file-search) to use your own data
as input for the model's response.
/responses/{response_id}:
get:
operationId: getResponse
tags:
- Responses
summary: Get a model response
parameters:
- in: path
name: response_id
required: true
schema:
type: string
example: resp_677efb5139a88190b512bc3fef8e535d
description: The ID of the response to retrieve.
- in: query
name: include
schema:
type: array
items:
$ref: '#/components/schemas/Includable'
description: |
Additional fields to include in the response. See the `include`
parameter for Response creation above for more information.
- in: query
name: stream
schema:
type: boolean
description: >
If set to true, the model response data will be streamed to the client
as it is generated using [server-sent
events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format).
See the [Streaming section
below](https://platform.openai.com/docs/api-reference/responses-streaming)
for more information.
- in: query
name: starting_after
schema:
type: integer
description: |
The sequence number of the event after which to start streaming.
- in: query
name: include_obfuscation
schema:
type: boolean
description: |
When true, stream obfuscation will be enabled. Stream obfuscation adds
random characters to an `obfuscation` field on streaming delta events
to normalize payload sizes as a mitigation to certain side-channel
attacks. These obfuscation fields are included by default, but add a
small amount of overhead to the data stream. You can set
`include_obfuscation` to false to optimize for bandwidth if you trust
the network links between your application and the OpenAI API.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/Response'
x-oaiMeta:
name: Get a model response
group: responses
returns: |
The [Response](https://platform.openai.com/docs/api-reference/responses/object) object matching the
specified ID.
examples:
response: |
{
"id": "resp_67cb71b351908190a308f3859487620d06981a8637e6bc44",
"object": "response",
"created_at": 1741386163,
"status": "completed",
"error": null,
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4o-2024-08-06",
"output": [
{
"type": "message",
"id": "msg_67cb71b3c2b0819084d481baaaf148f206981a8637e6bc44",
"status": "completed",
"role": "assistant",
"content": [
{
"type": "output_text",
"text": "Silent circuits hum, \nThoughts emerge in data streams— \nDigital dawn breaks.",
"annotations": []
}
]
}
],
"parallel_tool_calls": true,
"previous_response_id": null,
"reasoning": {
"effort": null,
"summary": null
},
"store": true,
"temperature": 1.0,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [],
"top_p": 1.0,
"truncation": "disabled",
"usage": {
"input_tokens": 32,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 18,
"output_tokens_details": {
"reasoning_tokens": 0
},
"total_tokens": 50
},
"user": null,
"metadata": {}
}
request:
curl: |
curl https://api.openai.com/v1/responses/resp_123 \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY"
javascript: |
import OpenAI from "openai";
const client = new OpenAI();
const response = await client.responses.retrieve("resp_123");
console.log(response);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.responses.retrieve(
response_id="resp_677efb5139a88190b512bc3fef8e535d",
)
print(response.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.responses.retrieve('resp_677efb5139a88190b512bc3fef8e535d');
console.log(response.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/responses"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
response, err := client.Responses.Get(
context.TODO(),
"resp_677efb5139a88190b512bc3fef8e535d",
responses.ResponseGetParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", response.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.responses.Response;
import com.openai.models.responses.ResponseRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Response response = client.responses().retrieve("resp_677efb5139a88190b512bc3fef8e535d");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.responses.retrieve("resp_677efb5139a88190b512bc3fef8e535d")
puts(response)
description: |
Retrieves a model response with the given ID.
delete:
operationId: deleteResponse
tags:
- Responses
summary: Delete a model response
parameters:
- in: path
name: response_id
required: true
schema:
type: string
example: resp_677efb5139a88190b512bc3fef8e535d
description: The ID of the response to delete.
responses:
'200':
description: OK
'404':
description: Not Found
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
x-oaiMeta:
name: Delete a model response
group: responses
returns: |
A success message.
examples:
response: |
{
"id": "resp_6786a1bec27481909a17d673315b29f6",
"object": "response",
"deleted": true
}
request:
curl: |
curl -X DELETE https://api.openai.com/v1/responses/resp_123 \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY"
javascript: |
import OpenAI from "openai";
const client = new OpenAI();
const response = await client.responses.delete("resp_123");
console.log(response);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
client.responses.delete(
"resp_677efb5139a88190b512bc3fef8e535d",
)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
await client.responses.delete('resp_677efb5139a88190b512bc3fef8e535d');
go: |
package main
import (
"context"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
err := client.Responses.Delete(context.TODO(), "resp_677efb5139a88190b512bc3fef8e535d")
if err != nil {
panic(err.Error())
}
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.responses.ResponseDeleteParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
client.responses().delete("resp_677efb5139a88190b512bc3fef8e535d");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
result = openai.responses.delete("resp_677efb5139a88190b512bc3fef8e535d")
puts(result)
description: |
Deletes a model response with the given ID.
/responses/{response_id}/cancel:
post:
operationId: cancelResponse
tags:
- Responses
summary: Cancel a response
parameters:
- in: path
name: response_id
required: true
schema:
type: string
example: resp_677efb5139a88190b512bc3fef8e535d
description: The ID of the response to cancel.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/Response'
'404':
description: Not Found
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
x-oaiMeta:
name: Cancel a response
group: responses
returns: |
A [Response](https://platform.openai.com/docs/api-reference/responses/object) object.
examples:
response: |
{
"id": "resp_67cb71b351908190a308f3859487620d06981a8637e6bc44",
"object": "response",
"created_at": 1741386163,
"status": "completed",
"error": null,
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4o-2024-08-06",
"output": [
{
"type": "message",
"id": "msg_67cb71b3c2b0819084d481baaaf148f206981a8637e6bc44",
"status": "completed",
"role": "assistant",
"content": [
{
"type": "output_text",
"text": "Silent circuits hum, \nThoughts emerge in data streams— \nDigital dawn breaks.",
"annotations": []
}
]
}
],
"parallel_tool_calls": true,
"previous_response_id": null,
"reasoning": {
"effort": null,
"summary": null
},
"store": true,
"temperature": 1.0,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [],
"top_p": 1.0,
"truncation": "disabled",
"usage": {
"input_tokens": 32,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 18,
"output_tokens_details": {
"reasoning_tokens": 0
},
"total_tokens": 50
},
"user": null,
"metadata": {}
}
request:
curl: |
curl -X POST https://api.openai.com/v1/responses/resp_123/cancel \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY"
javascript: |
import OpenAI from "openai";
const client = new OpenAI();
const response = await client.responses.cancel("resp_123");
console.log(response);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
response = client.responses.cancel(
"resp_677efb5139a88190b512bc3fef8e535d",
)
print(response.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const response = await client.responses.cancel('resp_677efb5139a88190b512bc3fef8e535d');
console.log(response.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
response, err := client.Responses.Cancel(context.TODO(), "resp_677efb5139a88190b512bc3fef8e535d")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", response.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.responses.Response;
import com.openai.models.responses.ResponseCancelParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Response response = client.responses().cancel("resp_677efb5139a88190b512bc3fef8e535d");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
response = openai.responses.cancel("resp_677efb5139a88190b512bc3fef8e535d")
puts(response)
description: |
Cancels a model response with the given ID. Only responses created with
the `background` parameter set to `true` can be cancelled.
[Learn more](https://platform.openai.com/docs/guides/background).
/responses/{response_id}/input_items:
get:
operationId: listInputItems
tags:
- Responses
summary: List input items
parameters:
- in: path
name: response_id
required: true
schema:
type: string
description: The ID of the response to retrieve input items for.
- name: limit
in: query
description: |
A limit on the number of objects to be returned. Limit can range between
1 and 100, and the default is 20.
required: false
schema:
type: integer
default: 20
- in: query
name: order
schema:
type: string
enum:
- asc
- desc
description: |
The order to return the input items in. Default is `desc`.
- `asc`: Return the input items in ascending order.
- `desc`: Return the input items in descending order.
- in: query
name: after
schema:
type: string
description: |
An item ID to list items after, used in pagination.
- in: query
name: include
schema:
type: array
items:
$ref: '#/components/schemas/Includable'
description: |
Additional fields to include in the response. See the `include`
parameter for Response creation above for more information.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ResponseItemList'
x-oaiMeta:
name: List input items
group: responses
returns: A list of input item objects.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "msg_abc123",
"type": "message",
"role": "user",
"content": [
{
"type": "input_text",
"text": "Tell me a three sentence bedtime story about a unicorn."
}
]
}
],
"first_id": "msg_abc123",
"last_id": "msg_abc123",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/responses/resp_abc123/input_items \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY"
javascript: |
import OpenAI from "openai";
const client = new OpenAI();
const response = await client.responses.inputItems.list("resp_123");
console.log(response.data);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.responses.input_items.list(
response_id="response_id",
)
page = page.data[0]
print(page)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const responseItem of client.responses.inputItems.list('response_id')) {
console.log(responseItem);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/responses"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.Responses.InputItems.List(
context.TODO(),
"response_id",
responses.InputItemListParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.responses.inputitems.InputItemListPage;
import com.openai.models.responses.inputitems.InputItemListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
InputItemListPage page = client.responses().inputItems().list("response_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.responses.input_items.list("response_id")
puts(page)
description: Returns a list of input items for a given response.
/threads:
post:
operationId: createThread
tags:
- Assistants
summary: Create thread
requestBody:
content:
application/json:
schema:
$ref: '#/components/schemas/CreateThreadRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ThreadObject'
x-oaiMeta:
name: Create thread
group: threads
beta: true
returns: A [thread](https://platform.openai.com/docs/api-reference/threads) object.
examples:
- title: Empty
request:
curl: |
curl https://api.openai.com/v1/threads \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2" \
-d ''
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
thread = client.beta.threads.create()
print(thread.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const thread = await client.beta.threads.create();
console.log(thread.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
thread, err := client.Beta.Threads.New(context.TODO(), openai.BetaThreadNewParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", thread.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.Thread;
import com.openai.models.beta.threads.ThreadCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Thread thread = client.beta().threads().create();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
thread = openai.beta.threads.create
puts(thread)
response: |
{
"id": "thread_abc123",
"object": "thread",
"created_at": 1699012949,
"metadata": {},
"tool_resources": {}
}
- title: Messages
request:
curl: |
curl https://api.openai.com/v1/threads \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"messages": [{
"role": "user",
"content": "Hello, what is AI?"
}, {
"role": "user",
"content": "How does AI work? Explain it in simple terms."
}]
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
thread = client.beta.threads.create()
print(thread.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const thread = await client.beta.threads.create();
console.log(thread.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
thread, err := client.Beta.Threads.New(context.TODO(), openai.BetaThreadNewParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", thread.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.Thread;
import com.openai.models.beta.threads.ThreadCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Thread thread = client.beta().threads().create();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
thread = openai.beta.threads.create
puts(thread)
response: |
{
"id": "thread_abc123",
"object": "thread",
"created_at": 1699014083,
"metadata": {},
"tool_resources": {}
}
description: Create a thread.
/threads/runs:
post:
operationId: createThreadAndRun
tags:
- Assistants
summary: Create thread and run
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateThreadAndRunRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/RunObject'
x-oaiMeta:
name: Create thread and run
group: threads
beta: true
returns: A [run](https://platform.openai.com/docs/api-reference/runs/object) object.
examples:
- title: Default
request:
curl: |
curl https://api.openai.com/v1/threads/runs \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"assistant_id": "asst_abc123",
"thread": {
"messages": [
{"role": "user", "content": "Explain deep learning to a 5 year old."}
]
}
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.beta.threads.create_and_run(
assistant_id="assistant_id",
)
print(run.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.beta.threads.createAndRun({ assistant_id: 'assistant_id' });
console.log(run.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
run, err := client.Beta.Threads.NewAndRun(context.TODO(), openai.BetaThreadNewAndRunParams{
AssistantID: "assistant_id",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", run.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.ThreadCreateAndRunParams;
import com.openai.models.beta.threads.runs.Run;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ThreadCreateAndRunParams params = ThreadCreateAndRunParams.builder()
.assistantId("assistant_id")
.build();
Run run = client.beta().threads().createAndRun(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.beta.threads.create_and_run(assistant_id: "assistant_id")
puts(run)
response: |
{
"id": "run_abc123",
"object": "thread.run",
"created_at": 1699076792,
"assistant_id": "asst_abc123",
"thread_id": "thread_abc123",
"status": "queued",
"started_at": null,
"expires_at": 1699077392,
"cancelled_at": null,
"failed_at": null,
"completed_at": null,
"required_action": null,
"last_error": null,
"model": "gpt-4o",
"instructions": "You are a helpful assistant.",
"tools": [],
"tool_resources": {},
"metadata": {},
"temperature": 1.0,
"top_p": 1.0,
"max_completion_tokens": null,
"max_prompt_tokens": null,
"truncation_strategy": {
"type": "auto",
"last_messages": null
},
"incomplete_details": null,
"usage": null,
"response_format": "auto",
"tool_choice": "auto",
"parallel_tool_calls": true
}
- title: Streaming
request:
curl: |
curl https://api.openai.com/v1/threads/runs \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"assistant_id": "asst_123",
"thread": {
"messages": [
{"role": "user", "content": "Hello"}
]
},
"stream": true
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.beta.threads.create_and_run(
assistant_id="assistant_id",
)
print(run.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.beta.threads.createAndRun({ assistant_id: 'assistant_id' });
console.log(run.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
run, err := client.Beta.Threads.NewAndRun(context.TODO(), openai.BetaThreadNewAndRunParams{
AssistantID: "assistant_id",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", run.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.ThreadCreateAndRunParams;
import com.openai.models.beta.threads.runs.Run;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ThreadCreateAndRunParams params = ThreadCreateAndRunParams.builder()
.assistantId("assistant_id")
.build();
Run run = client.beta().threads().createAndRun(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.beta.threads.create_and_run(assistant_id: "assistant_id")
puts(run)
response: >
event: thread.created
data: {"id":"thread_123","object":"thread","created_at":1710348075,"metadata":{}}
event: thread.run.created
data:
{"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710348675,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"tool_resources":{},"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}
event: thread.run.queued
data:
{"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710348675,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"tool_resources":{},"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}
event: thread.run.in_progress
data:
{"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"in_progress","started_at":null,"expires_at":1710348675,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"tool_resources":{},"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}
event: thread.run.step.created
data:
{"id":"step_001","object":"thread.run.step","created_at":1710348076,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710348675,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":null}
event: thread.run.step.in_progress
data:
{"id":"step_001","object":"thread.run.step","created_at":1710348076,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710348675,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":null}
event: thread.message.created
data:
{"id":"msg_001","object":"thread.message","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],
"metadata":{}}
event: thread.message.in_progress
data:
{"id":"msg_001","object":"thread.message","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],
"metadata":{}}
event: thread.message.delta
data:
{"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"Hello","annotations":[]}}]}}
...
event: thread.message.delta
data:
{"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"
today"}}]}}
event: thread.message.delta
data:
{"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"?"}}]}}
event: thread.message.completed
data:
{"id":"msg_001","object":"thread.message","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"completed","incomplete_details":null,"incomplete_at":null,"completed_at":1710348077,"role":"assistant","content":[{"type":"text","text":{"value":"Hello!
How can I assist you today?","annotations":[]}}], "metadata":{}}
event: thread.run.step.completed
data:
{"id":"step_001","object":"thread.run.step","created_at":1710348076,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"completed","cancelled_at":null,"completed_at":1710348077,"expires_at":1710348675,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":{"prompt_tokens":20,"completion_tokens":11,"total_tokens":31}}
event: thread.run.completed
{"id":"run_123","object":"thread.run","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","status":"completed","started_at":1713226836,"expires_at":null,"cancelled_at":null,"failed_at":null,"completed_at":1713226837,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":{"prompt_tokens":345,"completion_tokens":11,"total_tokens":356},"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}
event: done
data: [DONE]
- title: Streaming with Functions
request:
curl: |
curl https://api.openai.com/v1/threads/runs \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"assistant_id": "asst_abc123",
"thread": {
"messages": [
{"role": "user", "content": "What is the weather like in San Francisco?"}
]
},
"tools": [
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"]
}
},
"required": ["location"]
}
}
}
],
"stream": true
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.beta.threads.create_and_run(
assistant_id="assistant_id",
)
print(run.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.beta.threads.createAndRun({ assistant_id: 'assistant_id' });
console.log(run.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
run, err := client.Beta.Threads.NewAndRun(context.TODO(), openai.BetaThreadNewAndRunParams{
AssistantID: "assistant_id",
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", run.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.ThreadCreateAndRunParams;
import com.openai.models.beta.threads.runs.Run;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ThreadCreateAndRunParams params = ThreadCreateAndRunParams.builder()
.assistantId("assistant_id")
.build();
Run run = client.beta().threads().createAndRun(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.beta.threads.create_and_run(assistant_id: "assistant_id")
puts(run)
response: >
event: thread.created
data: {"id":"thread_123","object":"thread","created_at":1710351818,"metadata":{}}
event: thread.run.created
data:
{"id":"run_123","object":"thread.run","created_at":1710351818,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710352418,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
the current weather in a given
location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
city and state, e.g. San Francisco,
CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: thread.run.queued
data:
{"id":"run_123","object":"thread.run","created_at":1710351818,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710352418,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
the current weather in a given
location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
city and state, e.g. San Francisco,
CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: thread.run.in_progress
data:
{"id":"run_123","object":"thread.run","created_at":1710351818,"assistant_id":"asst_123","thread_id":"thread_123","status":"in_progress","started_at":1710351818,"expires_at":1710352418,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
the current weather in a given
location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
city and state, e.g. San Francisco,
CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: thread.run.step.created
data:
{"id":"step_001","object":"thread.run.step","created_at":1710351819,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"tool_calls","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710352418,"failed_at":null,"last_error":null,"step_details":{"type":"tool_calls","tool_calls":[]},"usage":null}
event: thread.run.step.in_progress
data:
{"id":"step_001","object":"thread.run.step","created_at":1710351819,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"tool_calls","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710352418,"failed_at":null,"last_error":null,"step_details":{"type":"tool_calls","tool_calls":[]},"usage":null}
event: thread.run.step.delta
data:
{"id":"step_001","object":"thread.run.step.delta","delta":{"step_details":{"type":"tool_calls","tool_calls":[{"index":0,"id":"call_XXNp8YGaFrjrSjgqxtC8JJ1B","type":"function","function":{"name":"get_current_weather","arguments":"","output":null}}]}}}
event: thread.run.step.delta
data:
{"id":"step_001","object":"thread.run.step.delta","delta":{"step_details":{"type":"tool_calls","tool_calls":[{"index":0,"type":"function","function":{"arguments":"{\""}}]}}}
event: thread.run.step.delta
data:
{"id":"step_001","object":"thread.run.step.delta","delta":{"step_details":{"type":"tool_calls","tool_calls":[{"index":0,"type":"function","function":{"arguments":"location"}}]}}}
...
event: thread.run.step.delta
data:
{"id":"step_001","object":"thread.run.step.delta","delta":{"step_details":{"type":"tool_calls","tool_calls":[{"index":0,"type":"function","function":{"arguments":"ahrenheit"}}]}}}
event: thread.run.step.delta
data:
{"id":"step_001","object":"thread.run.step.delta","delta":{"step_details":{"type":"tool_calls","tool_calls":[{"index":0,"type":"function","function":{"arguments":"\"}"}}]}}}
event: thread.run.requires_action
data:
{"id":"run_123","object":"thread.run","created_at":1710351818,"assistant_id":"asst_123","thread_id":"thread_123","status":"requires_action","started_at":1710351818,"expires_at":1710352418,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":{"type":"submit_tool_outputs","submit_tool_outputs":{"tool_calls":[{"id":"call_XXNp8YGaFrjrSjgqxtC8JJ1B","type":"function","function":{"name":"get_current_weather","arguments":"{\"location\":\"San
Francisco,
CA\",\"unit\":\"fahrenheit\"}"}}]}},"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
the current weather in a given
location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
city and state, e.g. San Francisco,
CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":{"prompt_tokens":345,"completion_tokens":11,"total_tokens":356},"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: done
data: [DONE]
description: Create a thread and run it in one request.
/threads/{thread_id}:
get:
operationId: getThread
tags:
- Assistants
summary: Retrieve thread
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: The ID of the thread to retrieve.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ThreadObject'
x-oaiMeta:
name: Retrieve thread
group: threads
beta: true
returns: >-
The [thread](https://platform.openai.com/docs/api-reference/threads/object) object matching the
specified ID.
examples:
response: |
{
"id": "thread_abc123",
"object": "thread",
"created_at": 1699014083,
"metadata": {},
"tool_resources": {
"code_interpreter": {
"file_ids": []
}
}
}
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123 \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
thread = client.beta.threads.retrieve(
"thread_id",
)
print(thread.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const thread = await client.beta.threads.retrieve('thread_id');
console.log(thread.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
thread, err := client.Beta.Threads.Get(context.TODO(), "thread_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", thread.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.Thread;
import com.openai.models.beta.threads.ThreadRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Thread thread = client.beta().threads().retrieve("thread_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
thread = openai.beta.threads.retrieve("thread_id")
puts(thread)
description: Retrieves a thread.
post:
operationId: modifyThread
tags:
- Assistants
summary: Modify thread
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: The ID of the thread to modify. Only the `metadata` can be modified.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ModifyThreadRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ThreadObject'
x-oaiMeta:
name: Modify thread
group: threads
beta: true
returns: >-
The modified [thread](https://platform.openai.com/docs/api-reference/threads/object) object matching
the specified ID.
examples:
response: |
{
"id": "thread_abc123",
"object": "thread",
"created_at": 1699014083,
"metadata": {
"modified": "true",
"user": "abc123"
},
"tool_resources": {}
}
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123 \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"metadata": {
"modified": "true",
"user": "abc123"
}
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
thread = client.beta.threads.update(
thread_id="thread_id",
)
print(thread.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const thread = await client.beta.threads.update('thread_id');
console.log(thread.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
thread, err := client.Beta.Threads.Update(
context.TODO(),
"thread_id",
openai.BetaThreadUpdateParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", thread.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.Thread;
import com.openai.models.beta.threads.ThreadUpdateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Thread thread = client.beta().threads().update("thread_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
thread = openai.beta.threads.update("thread_id")
puts(thread)
description: Modifies a thread.
delete:
operationId: deleteThread
tags:
- Assistants
summary: Delete thread
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: The ID of the thread to delete.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/DeleteThreadResponse'
x-oaiMeta:
name: Delete thread
group: threads
beta: true
returns: Deletion status
examples:
response: |
{
"id": "thread_abc123",
"object": "thread.deleted",
"deleted": true
}
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123 \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2" \
-X DELETE
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
thread_deleted = client.beta.threads.delete(
"thread_id",
)
print(thread_deleted.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const threadDeleted = await client.beta.threads.delete('thread_id');
console.log(threadDeleted.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
threadDeleted, err := client.Beta.Threads.Delete(context.TODO(), "thread_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", threadDeleted.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.ThreadDeleteParams;
import com.openai.models.beta.threads.ThreadDeleted;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
ThreadDeleted threadDeleted = client.beta().threads().delete("thread_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
thread_deleted = openai.beta.threads.delete("thread_id")
puts(thread_deleted)
description: Delete a thread.
/threads/{thread_id}/messages:
get:
operationId: listMessages
tags:
- Assistants
summary: List messages
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: >-
The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) the messages belong
to.
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: order
in: query
description: >
Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
descending order.
schema:
type: string
default: desc
enum:
- asc
- desc
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
schema:
type: string
- name: before
in: query
description: >
A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, starting with obj_foo, your
subsequent call can include before=obj_foo in order to fetch the previous page of the list.
schema:
type: string
- name: run_id
in: query
description: |
Filter messages by the run ID that generated them.
schema:
type: string
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListMessagesResponse'
x-oaiMeta:
name: List messages
group: threads
beta: true
returns: A list of [message](https://platform.openai.com/docs/api-reference/messages) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "msg_abc123",
"object": "thread.message",
"created_at": 1699016383,
"assistant_id": null,
"thread_id": "thread_abc123",
"run_id": null,
"role": "user",
"content": [
{
"type": "text",
"text": {
"value": "How does AI work? Explain it in simple terms.",
"annotations": []
}
}
],
"attachments": [],
"metadata": {}
},
{
"id": "msg_abc456",
"object": "thread.message",
"created_at": 1699016383,
"assistant_id": null,
"thread_id": "thread_abc123",
"run_id": null,
"role": "user",
"content": [
{
"type": "text",
"text": {
"value": "Hello, what is AI?",
"annotations": []
}
}
],
"attachments": [],
"metadata": {}
}
],
"first_id": "msg_abc123",
"last_id": "msg_abc456",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123/messages \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.beta.threads.messages.list(
thread_id="thread_id",
)
page = page.data[0]
print(page.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const message of client.beta.threads.messages.list('thread_id')) {
console.log(message.id);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.Beta.Threads.Messages.List(
context.TODO(),
"thread_id",
openai.BetaThreadMessageListParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.messages.MessageListPage;
import com.openai.models.beta.threads.messages.MessageListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
MessageListPage page = client.beta().threads().messages().list("thread_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.beta.threads.messages.list("thread_id")
puts(page)
description: Returns a list of messages for a given thread.
post:
operationId: createMessage
tags:
- Assistants
summary: Create message
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: >-
The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) to create a message
for.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateMessageRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/MessageObject'
x-oaiMeta:
name: Create message
group: threads
beta: true
returns: A [message](https://platform.openai.com/docs/api-reference/messages/object) object.
examples:
response: |
{
"id": "msg_abc123",
"object": "thread.message",
"created_at": 1713226573,
"assistant_id": null,
"thread_id": "thread_abc123",
"run_id": null,
"role": "user",
"content": [
{
"type": "text",
"text": {
"value": "How does AI work? Explain it in simple terms.",
"annotations": []
}
}
],
"attachments": [],
"metadata": {}
}
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123/messages \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"role": "user",
"content": "How does AI work? Explain it in simple terms."
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
message = client.beta.threads.messages.create(
thread_id="thread_id",
content="string",
role="user",
)
print(message.id)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const message = await client.beta.threads.messages.create('thread_id', { content: 'string',
role: 'user' });
console.log(message.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
message, err := client.Beta.Threads.Messages.New(
context.TODO(),
"thread_id",
openai.BetaThreadMessageNewParams{
Content: openai.BetaThreadMessageNewParamsContentUnion{
OfString: openai.String("string"),
},
Role: openai.BetaThreadMessageNewParamsRoleUser,
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", message.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.messages.Message;
import com.openai.models.beta.threads.messages.MessageCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
MessageCreateParams params = MessageCreateParams.builder()
.threadId("thread_id")
.content("string")
.role(MessageCreateParams.Role.USER)
.build();
Message message = client.beta().threads().messages().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
message = openai.beta.threads.messages.create("thread_id", content: "string", role: :user)
puts(message)
description: Create a message.
/threads/{thread_id}/messages/{message_id}:
get:
operationId: getMessage
tags:
- Assistants
summary: Retrieve message
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: >-
The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) to which this
message belongs.
- in: path
name: message_id
required: true
schema:
type: string
description: The ID of the message to retrieve.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/MessageObject'
x-oaiMeta:
name: Retrieve message
group: threads
beta: true
returns: >-
The [message](https://platform.openai.com/docs/api-reference/messages/object) object matching the
specified ID.
examples:
response: |
{
"id": "msg_abc123",
"object": "thread.message",
"created_at": 1699017614,
"assistant_id": null,
"thread_id": "thread_abc123",
"run_id": null,
"role": "user",
"content": [
{
"type": "text",
"text": {
"value": "How does AI work? Explain it in simple terms.",
"annotations": []
}
}
],
"attachments": [],
"metadata": {}
}
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123/messages/msg_abc123 \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
message = client.beta.threads.messages.retrieve(
message_id="message_id",
thread_id="thread_id",
)
print(message.id)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const message = await client.beta.threads.messages.retrieve('message_id', { thread_id:
'thread_id' });
console.log(message.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
message, err := client.Beta.Threads.Messages.Get(
context.TODO(),
"thread_id",
"message_id",
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", message.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.messages.Message;
import com.openai.models.beta.threads.messages.MessageRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
MessageRetrieveParams params = MessageRetrieveParams.builder()
.threadId("thread_id")
.messageId("message_id")
.build();
Message message = client.beta().threads().messages().retrieve(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
message = openai.beta.threads.messages.retrieve("message_id", thread_id: "thread_id")
puts(message)
description: Retrieve a message.
post:
operationId: modifyMessage
tags:
- Assistants
summary: Modify message
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: The ID of the thread to which this message belongs.
- in: path
name: message_id
required: true
schema:
type: string
description: The ID of the message to modify.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ModifyMessageRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/MessageObject'
x-oaiMeta:
name: Modify message
group: threads
beta: true
returns: The modified [message](https://platform.openai.com/docs/api-reference/messages/object) object.
examples:
response: |
{
"id": "msg_abc123",
"object": "thread.message",
"created_at": 1699017614,
"assistant_id": null,
"thread_id": "thread_abc123",
"run_id": null,
"role": "user",
"content": [
{
"type": "text",
"text": {
"value": "How does AI work? Explain it in simple terms.",
"annotations": []
}
}
],
"file_ids": [],
"metadata": {
"modified": "true",
"user": "abc123"
}
}
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123/messages/msg_abc123 \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"metadata": {
"modified": "true",
"user": "abc123"
}
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
message = client.beta.threads.messages.update(
message_id="message_id",
thread_id="thread_id",
)
print(message.id)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const message = await client.beta.threads.messages.update('message_id', { thread_id: 'thread_id'
});
console.log(message.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
message, err := client.Beta.Threads.Messages.Update(
context.TODO(),
"thread_id",
"message_id",
openai.BetaThreadMessageUpdateParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", message.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.messages.Message;
import com.openai.models.beta.threads.messages.MessageUpdateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
MessageUpdateParams params = MessageUpdateParams.builder()
.threadId("thread_id")
.messageId("message_id")
.build();
Message message = client.beta().threads().messages().update(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
message = openai.beta.threads.messages.update("message_id", thread_id: "thread_id")
puts(message)
description: Modifies a message.
delete:
operationId: deleteMessage
tags:
- Assistants
summary: Delete message
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: The ID of the thread to which this message belongs.
- in: path
name: message_id
required: true
schema:
type: string
description: The ID of the message to delete.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/DeleteMessageResponse'
x-oaiMeta:
name: Delete message
group: threads
beta: true
returns: Deletion status
examples:
response: |
{
"id": "msg_abc123",
"object": "thread.message.deleted",
"deleted": true
}
request:
curl: |
curl -X DELETE https://api.openai.com/v1/threads/thread_abc123/messages/msg_abc123 \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
message_deleted = client.beta.threads.messages.delete(
message_id="message_id",
thread_id="thread_id",
)
print(message_deleted.id)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const messageDeleted = await client.beta.threads.messages.delete('message_id', { thread_id:
'thread_id' });
console.log(messageDeleted.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
messageDeleted, err := client.Beta.Threads.Messages.Delete(
context.TODO(),
"thread_id",
"message_id",
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", messageDeleted.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.messages.MessageDeleteParams;
import com.openai.models.beta.threads.messages.MessageDeleted;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
MessageDeleteParams params = MessageDeleteParams.builder()
.threadId("thread_id")
.messageId("message_id")
.build();
MessageDeleted messageDeleted = client.beta().threads().messages().delete(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
message_deleted = openai.beta.threads.messages.delete("message_id", thread_id: "thread_id")
puts(message_deleted)
description: Deletes a message.
/threads/{thread_id}/runs:
get:
operationId: listRuns
tags:
- Assistants
summary: List runs
parameters:
- name: thread_id
in: path
required: true
schema:
type: string
description: The ID of the thread the run belongs to.
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: order
in: query
description: >
Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
descending order.
schema:
type: string
default: desc
enum:
- asc
- desc
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
schema:
type: string
- name: before
in: query
description: >
A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, starting with obj_foo, your
subsequent call can include before=obj_foo in order to fetch the previous page of the list.
schema:
type: string
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListRunsResponse'
x-oaiMeta:
name: List runs
group: threads
beta: true
returns: A list of [run](https://platform.openai.com/docs/api-reference/runs/object) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "run_abc123",
"object": "thread.run",
"created_at": 1699075072,
"assistant_id": "asst_abc123",
"thread_id": "thread_abc123",
"status": "completed",
"started_at": 1699075072,
"expires_at": null,
"cancelled_at": null,
"failed_at": null,
"completed_at": 1699075073,
"last_error": null,
"model": "gpt-4o",
"instructions": null,
"incomplete_details": null,
"tools": [
{
"type": "code_interpreter"
}
],
"tool_resources": {
"code_interpreter": {
"file_ids": [
"file-abc123",
"file-abc456"
]
}
},
"metadata": {},
"usage": {
"prompt_tokens": 123,
"completion_tokens": 456,
"total_tokens": 579
},
"temperature": 1.0,
"top_p": 1.0,
"max_prompt_tokens": 1000,
"max_completion_tokens": 1000,
"truncation_strategy": {
"type": "auto",
"last_messages": null
},
"response_format": "auto",
"tool_choice": "auto",
"parallel_tool_calls": true
},
{
"id": "run_abc456",
"object": "thread.run",
"created_at": 1699063290,
"assistant_id": "asst_abc123",
"thread_id": "thread_abc123",
"status": "completed",
"started_at": 1699063290,
"expires_at": null,
"cancelled_at": null,
"failed_at": null,
"completed_at": 1699063291,
"last_error": null,
"model": "gpt-4o",
"instructions": null,
"incomplete_details": null,
"tools": [
{
"type": "code_interpreter"
}
],
"tool_resources": {
"code_interpreter": {
"file_ids": [
"file-abc123",
"file-abc456"
]
}
},
"metadata": {},
"usage": {
"prompt_tokens": 123,
"completion_tokens": 456,
"total_tokens": 579
},
"temperature": 1.0,
"top_p": 1.0,
"max_prompt_tokens": 1000,
"max_completion_tokens": 1000,
"truncation_strategy": {
"type": "auto",
"last_messages": null
},
"response_format": "auto",
"tool_choice": "auto",
"parallel_tool_calls": true
}
],
"first_id": "run_abc123",
"last_id": "run_abc456",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123/runs \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.beta.threads.runs.list(
thread_id="thread_id",
)
page = page.data[0]
print(page.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const run of client.beta.threads.runs.list('thread_id')) {
console.log(run.id);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.Beta.Threads.Runs.List(
context.TODO(),
"thread_id",
openai.BetaThreadRunListParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.runs.RunListPage;
import com.openai.models.beta.threads.runs.RunListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunListPage page = client.beta().threads().runs().list("thread_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.beta.threads.runs.list("thread_id")
puts(page)
description: Returns a list of runs belonging to a thread.
post:
operationId: createRun
tags:
- Assistants
summary: Create run
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: The ID of the thread to run.
- name: include[]
in: query
description: >
A list of additional fields to include in the response. Currently the only supported value is
`step_details.tool_calls[*].file_search.results[*].content` to fetch the file search result
content.
See the [file search tool
documentation](https://platform.openai.com/docs/assistants/tools/file-search#customizing-file-search-settings)
for more information.
schema:
type: array
items:
type: string
enum:
- step_details.tool_calls[*].file_search.results[*].content
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateRunRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/RunObject'
x-oaiMeta:
name: Create run
group: threads
beta: true
returns: A [run](https://platform.openai.com/docs/api-reference/runs/object) object.
examples:
- title: Default
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123/runs \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"assistant_id": "asst_abc123"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.beta.threads.runs.create(
thread_id="thread_id",
assistant_id="assistant_id",
)
print(run.id)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.beta.threads.runs.create('thread_id', { assistant_id: 'assistant_id'
});
console.log(run.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
run, err := client.Beta.Threads.Runs.New(
context.TODO(),
"thread_id",
openai.BetaThreadRunNewParams{
AssistantID: "assistant_id",
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", run.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.runs.Run;
import com.openai.models.beta.threads.runs.RunCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunCreateParams params = RunCreateParams.builder()
.threadId("thread_id")
.assistantId("assistant_id")
.build();
Run run = client.beta().threads().runs().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.beta.threads.runs.create("thread_id", assistant_id: "assistant_id")
puts(run)
response: |
{
"id": "run_abc123",
"object": "thread.run",
"created_at": 1699063290,
"assistant_id": "asst_abc123",
"thread_id": "thread_abc123",
"status": "queued",
"started_at": 1699063290,
"expires_at": null,
"cancelled_at": null,
"failed_at": null,
"completed_at": 1699063291,
"last_error": null,
"model": "gpt-4o",
"instructions": null,
"incomplete_details": null,
"tools": [
{
"type": "code_interpreter"
}
],
"metadata": {},
"usage": null,
"temperature": 1.0,
"top_p": 1.0,
"max_prompt_tokens": 1000,
"max_completion_tokens": 1000,
"truncation_strategy": {
"type": "auto",
"last_messages": null
},
"response_format": "auto",
"tool_choice": "auto",
"parallel_tool_calls": true
}
- title: Streaming
request:
curl: |
curl https://api.openai.com/v1/threads/thread_123/runs \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"assistant_id": "asst_123",
"stream": true
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.beta.threads.runs.create(
thread_id="thread_id",
assistant_id="assistant_id",
)
print(run.id)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.beta.threads.runs.create('thread_id', { assistant_id: 'assistant_id'
});
console.log(run.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
run, err := client.Beta.Threads.Runs.New(
context.TODO(),
"thread_id",
openai.BetaThreadRunNewParams{
AssistantID: "assistant_id",
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", run.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.runs.Run;
import com.openai.models.beta.threads.runs.RunCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunCreateParams params = RunCreateParams.builder()
.threadId("thread_id")
.assistantId("assistant_id")
.build();
Run run = client.beta().threads().runs().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.beta.threads.runs.create("thread_id", assistant_id: "assistant_id")
puts(run)
response: >
event: thread.run.created
data:
{"id":"run_123","object":"thread.run","created_at":1710330640,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710331240,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: thread.run.queued
data:
{"id":"run_123","object":"thread.run","created_at":1710330640,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710331240,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: thread.run.in_progress
data:
{"id":"run_123","object":"thread.run","created_at":1710330640,"assistant_id":"asst_123","thread_id":"thread_123","status":"in_progress","started_at":1710330641,"expires_at":1710331240,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: thread.run.step.created
data:
{"id":"step_001","object":"thread.run.step","created_at":1710330641,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710331240,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":null}
event: thread.run.step.in_progress
data:
{"id":"step_001","object":"thread.run.step","created_at":1710330641,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710331240,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":null}
event: thread.message.created
data:
{"id":"msg_001","object":"thread.message","created_at":1710330641,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],"metadata":{}}
event: thread.message.in_progress
data:
{"id":"msg_001","object":"thread.message","created_at":1710330641,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],"metadata":{}}
event: thread.message.delta
data:
{"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"Hello","annotations":[]}}]}}
...
event: thread.message.delta
data:
{"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"
today"}}]}}
event: thread.message.delta
data:
{"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"?"}}]}}
event: thread.message.completed
data:
{"id":"msg_001","object":"thread.message","created_at":1710330641,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"completed","incomplete_details":null,"incomplete_at":null,"completed_at":1710330642,"role":"assistant","content":[{"type":"text","text":{"value":"Hello!
How can I assist you today?","annotations":[]}}],"metadata":{}}
event: thread.run.step.completed
data:
{"id":"step_001","object":"thread.run.step","created_at":1710330641,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"completed","cancelled_at":null,"completed_at":1710330642,"expires_at":1710331240,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":{"prompt_tokens":20,"completion_tokens":11,"total_tokens":31}}
event: thread.run.completed
data:
{"id":"run_123","object":"thread.run","created_at":1710330640,"assistant_id":"asst_123","thread_id":"thread_123","status":"completed","started_at":1710330641,"expires_at":null,"cancelled_at":null,"failed_at":null,"completed_at":1710330642,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":{"prompt_tokens":20,"completion_tokens":11,"total_tokens":31},"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: done
data: [DONE]
- title: Streaming with Functions
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123/runs \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"assistant_id": "asst_abc123",
"tools": [
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"]
}
},
"required": ["location"]
}
}
}
],
"stream": true
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.beta.threads.runs.create(
thread_id="thread_id",
assistant_id="assistant_id",
)
print(run.id)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.beta.threads.runs.create('thread_id', { assistant_id: 'assistant_id'
});
console.log(run.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
run, err := client.Beta.Threads.Runs.New(
context.TODO(),
"thread_id",
openai.BetaThreadRunNewParams{
AssistantID: "assistant_id",
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", run.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.runs.Run;
import com.openai.models.beta.threads.runs.RunCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunCreateParams params = RunCreateParams.builder()
.threadId("thread_id")
.assistantId("assistant_id")
.build();
Run run = client.beta().threads().runs().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.beta.threads.runs.create("thread_id", assistant_id: "assistant_id")
puts(run)
response: >
event: thread.run.created
data:
{"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710348675,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: thread.run.queued
data:
{"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710348675,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: thread.run.in_progress
data:
{"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"in_progress","started_at":1710348075,"expires_at":1710348675,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: thread.run.step.created
data:
{"id":"step_001","object":"thread.run.step","created_at":1710348076,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710348675,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":null}
event: thread.run.step.in_progress
data:
{"id":"step_001","object":"thread.run.step","created_at":1710348076,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710348675,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":null}
event: thread.message.created
data:
{"id":"msg_001","object":"thread.message","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],"metadata":{}}
event: thread.message.in_progress
data:
{"id":"msg_001","object":"thread.message","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],"metadata":{}}
event: thread.message.delta
data:
{"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"Hello","annotations":[]}}]}}
...
event: thread.message.delta
data:
{"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"
today"}}]}}
event: thread.message.delta
data:
{"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"?"}}]}}
event: thread.message.completed
data:
{"id":"msg_001","object":"thread.message","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"completed","incomplete_details":null,"incomplete_at":null,"completed_at":1710348077,"role":"assistant","content":[{"type":"text","text":{"value":"Hello!
How can I assist you today?","annotations":[]}}],"metadata":{}}
event: thread.run.step.completed
data:
{"id":"step_001","object":"thread.run.step","created_at":1710348076,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"completed","cancelled_at":null,"completed_at":1710348077,"expires_at":1710348675,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":{"prompt_tokens":20,"completion_tokens":11,"total_tokens":31}}
event: thread.run.completed
data:
{"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"completed","started_at":1710348075,"expires_at":null,"cancelled_at":null,"failed_at":null,"completed_at":1710348077,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":{"prompt_tokens":20,"completion_tokens":11,"total_tokens":31},"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: done
data: [DONE]
description: Create a run.
/threads/{thread_id}/runs/{run_id}:
get:
operationId: getRun
tags:
- Assistants
summary: Retrieve run
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) that was run.
- in: path
name: run_id
required: true
schema:
type: string
description: The ID of the run to retrieve.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/RunObject'
x-oaiMeta:
name: Retrieve run
group: threads
beta: true
returns: >-
The [run](https://platform.openai.com/docs/api-reference/runs/object) object matching the specified
ID.
examples:
response: |
{
"id": "run_abc123",
"object": "thread.run",
"created_at": 1699075072,
"assistant_id": "asst_abc123",
"thread_id": "thread_abc123",
"status": "completed",
"started_at": 1699075072,
"expires_at": null,
"cancelled_at": null,
"failed_at": null,
"completed_at": 1699075073,
"last_error": null,
"model": "gpt-4o",
"instructions": null,
"incomplete_details": null,
"tools": [
{
"type": "code_interpreter"
}
],
"metadata": {},
"usage": {
"prompt_tokens": 123,
"completion_tokens": 456,
"total_tokens": 579
},
"temperature": 1.0,
"top_p": 1.0,
"max_prompt_tokens": 1000,
"max_completion_tokens": 1000,
"truncation_strategy": {
"type": "auto",
"last_messages": null
},
"response_format": "auto",
"tool_choice": "auto",
"parallel_tool_calls": true
}
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.beta.threads.runs.retrieve(
run_id="run_id",
thread_id="thread_id",
)
print(run.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.beta.threads.runs.retrieve('run_id', { thread_id: 'thread_id' });
console.log(run.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
run, err := client.Beta.Threads.Runs.Get(
context.TODO(),
"thread_id",
"run_id",
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", run.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.runs.Run;
import com.openai.models.beta.threads.runs.RunRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunRetrieveParams params = RunRetrieveParams.builder()
.threadId("thread_id")
.runId("run_id")
.build();
Run run = client.beta().threads().runs().retrieve(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.beta.threads.runs.retrieve("run_id", thread_id: "thread_id")
puts(run)
description: Retrieves a run.
post:
operationId: modifyRun
tags:
- Assistants
summary: Modify run
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) that was run.
- in: path
name: run_id
required: true
schema:
type: string
description: The ID of the run to modify.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ModifyRunRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/RunObject'
x-oaiMeta:
name: Modify run
group: threads
beta: true
returns: >-
The modified [run](https://platform.openai.com/docs/api-reference/runs/object) object matching the
specified ID.
examples:
response: |
{
"id": "run_abc123",
"object": "thread.run",
"created_at": 1699075072,
"assistant_id": "asst_abc123",
"thread_id": "thread_abc123",
"status": "completed",
"started_at": 1699075072,
"expires_at": null,
"cancelled_at": null,
"failed_at": null,
"completed_at": 1699075073,
"last_error": null,
"model": "gpt-4o",
"instructions": null,
"incomplete_details": null,
"tools": [
{
"type": "code_interpreter"
}
],
"tool_resources": {
"code_interpreter": {
"file_ids": [
"file-abc123",
"file-abc456"
]
}
},
"metadata": {
"user_id": "user_abc123"
},
"usage": {
"prompt_tokens": 123,
"completion_tokens": 456,
"total_tokens": 579
},
"temperature": 1.0,
"top_p": 1.0,
"max_prompt_tokens": 1000,
"max_completion_tokens": 1000,
"truncation_strategy": {
"type": "auto",
"last_messages": null
},
"response_format": "auto",
"tool_choice": "auto",
"parallel_tool_calls": true
}
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"metadata": {
"user_id": "user_abc123"
}
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.beta.threads.runs.update(
run_id="run_id",
thread_id="thread_id",
)
print(run.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.beta.threads.runs.update('run_id', { thread_id: 'thread_id' });
console.log(run.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
run, err := client.Beta.Threads.Runs.Update(
context.TODO(),
"thread_id",
"run_id",
openai.BetaThreadRunUpdateParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", run.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.runs.Run;
import com.openai.models.beta.threads.runs.RunUpdateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunUpdateParams params = RunUpdateParams.builder()
.threadId("thread_id")
.runId("run_id")
.build();
Run run = client.beta().threads().runs().update(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.beta.threads.runs.update("run_id", thread_id: "thread_id")
puts(run)
description: Modifies a run.
/threads/{thread_id}/runs/{run_id}/cancel:
post:
operationId: cancelRun
tags:
- Assistants
summary: Cancel a run
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: The ID of the thread to which this run belongs.
- in: path
name: run_id
required: true
schema:
type: string
description: The ID of the run to cancel.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/RunObject'
x-oaiMeta:
name: Cancel a run
group: threads
beta: true
returns: >-
The modified [run](https://platform.openai.com/docs/api-reference/runs/object) object matching the
specified ID.
examples:
response: |
{
"id": "run_abc123",
"object": "thread.run",
"created_at": 1699076126,
"assistant_id": "asst_abc123",
"thread_id": "thread_abc123",
"status": "cancelling",
"started_at": 1699076126,
"expires_at": 1699076726,
"cancelled_at": null,
"failed_at": null,
"completed_at": null,
"last_error": null,
"model": "gpt-4o",
"instructions": "You summarize books.",
"tools": [
{
"type": "file_search"
}
],
"tool_resources": {
"file_search": {
"vector_store_ids": ["vs_123"]
}
},
"metadata": {},
"usage": null,
"temperature": 1.0,
"top_p": 1.0,
"response_format": "auto",
"tool_choice": "auto",
"parallel_tool_calls": true
}
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123/cancel \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "OpenAI-Beta: assistants=v2" \
-X POST
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.beta.threads.runs.cancel(
run_id="run_id",
thread_id="thread_id",
)
print(run.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.beta.threads.runs.cancel('run_id', { thread_id: 'thread_id' });
console.log(run.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
run, err := client.Beta.Threads.Runs.Cancel(
context.TODO(),
"thread_id",
"run_id",
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", run.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.runs.Run;
import com.openai.models.beta.threads.runs.RunCancelParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunCancelParams params = RunCancelParams.builder()
.threadId("thread_id")
.runId("run_id")
.build();
Run run = client.beta().threads().runs().cancel(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.beta.threads.runs.cancel("run_id", thread_id: "thread_id")
puts(run)
description: Cancels a run that is `in_progress`.
/threads/{thread_id}/runs/{run_id}/steps:
get:
operationId: listRunSteps
tags:
- Assistants
summary: List run steps
parameters:
- name: thread_id
in: path
required: true
schema:
type: string
description: The ID of the thread the run and run steps belong to.
- name: run_id
in: path
required: true
schema:
type: string
description: The ID of the run the run steps belong to.
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: order
in: query
description: >
Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
descending order.
schema:
type: string
default: desc
enum:
- asc
- desc
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
schema:
type: string
- name: before
in: query
description: >
A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, starting with obj_foo, your
subsequent call can include before=obj_foo in order to fetch the previous page of the list.
schema:
type: string
- name: include[]
in: query
description: >
A list of additional fields to include in the response. Currently the only supported value is
`step_details.tool_calls[*].file_search.results[*].content` to fetch the file search result
content.
See the [file search tool
documentation](https://platform.openai.com/docs/assistants/tools/file-search#customizing-file-search-settings)
for more information.
schema:
type: array
items:
type: string
enum:
- step_details.tool_calls[*].file_search.results[*].content
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListRunStepsResponse'
x-oaiMeta:
name: List run steps
group: threads
beta: true
returns: A list of [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "step_abc123",
"object": "thread.run.step",
"created_at": 1699063291,
"run_id": "run_abc123",
"assistant_id": "asst_abc123",
"thread_id": "thread_abc123",
"type": "message_creation",
"status": "completed",
"cancelled_at": null,
"completed_at": 1699063291,
"expired_at": null,
"failed_at": null,
"last_error": null,
"step_details": {
"type": "message_creation",
"message_creation": {
"message_id": "msg_abc123"
}
},
"usage": {
"prompt_tokens": 123,
"completion_tokens": 456,
"total_tokens": 579
}
}
],
"first_id": "step_abc123",
"last_id": "step_abc456",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123/steps \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.beta.threads.runs.steps.list(
run_id="run_id",
thread_id="thread_id",
)
page = page.data[0]
print(page.id)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const runStep of client.beta.threads.runs.steps.list('run_id', { thread_id:
'thread_id' })) {
console.log(runStep.id);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.Beta.Threads.Runs.Steps.List(
context.TODO(),
"thread_id",
"run_id",
openai.BetaThreadRunStepListParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.runs.steps.StepListPage;
import com.openai.models.beta.threads.runs.steps.StepListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
StepListParams params = StepListParams.builder()
.threadId("thread_id")
.runId("run_id")
.build();
StepListPage page = client.beta().threads().runs().steps().list(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.beta.threads.runs.steps.list("run_id", thread_id: "thread_id")
puts(page)
description: Returns a list of run steps belonging to a run.
/threads/{thread_id}/runs/{run_id}/steps/{step_id}:
get:
operationId: getRunStep
tags:
- Assistants
summary: Retrieve run step
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: The ID of the thread to which the run and run step belongs.
- in: path
name: run_id
required: true
schema:
type: string
description: The ID of the run to which the run step belongs.
- in: path
name: step_id
required: true
schema:
type: string
description: The ID of the run step to retrieve.
- name: include[]
in: query
description: >
A list of additional fields to include in the response. Currently the only supported value is
`step_details.tool_calls[*].file_search.results[*].content` to fetch the file search result
content.
See the [file search tool
documentation](https://platform.openai.com/docs/assistants/tools/file-search#customizing-file-search-settings)
for more information.
schema:
type: array
items:
type: string
enum:
- step_details.tool_calls[*].file_search.results[*].content
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/RunStepObject'
x-oaiMeta:
name: Retrieve run step
group: threads
beta: true
returns: >-
The [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) object matching
the specified ID.
examples:
response: |
{
"id": "step_abc123",
"object": "thread.run.step",
"created_at": 1699063291,
"run_id": "run_abc123",
"assistant_id": "asst_abc123",
"thread_id": "thread_abc123",
"type": "message_creation",
"status": "completed",
"cancelled_at": null,
"completed_at": 1699063291,
"expired_at": null,
"failed_at": null,
"last_error": null,
"step_details": {
"type": "message_creation",
"message_creation": {
"message_id": "msg_abc123"
}
},
"usage": {
"prompt_tokens": 123,
"completion_tokens": 456,
"total_tokens": 579
}
}
request:
curl: |
curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123/steps/step_abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run_step = client.beta.threads.runs.steps.retrieve(
step_id="step_id",
thread_id="thread_id",
run_id="run_id",
)
print(run_step.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const runStep = await client.beta.threads.runs.steps.retrieve('step_id', {
thread_id: 'thread_id',
run_id: 'run_id',
});
console.log(runStep.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
runStep, err := client.Beta.Threads.Runs.Steps.Get(
context.TODO(),
"thread_id",
"run_id",
"step_id",
openai.BetaThreadRunStepGetParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", runStep.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.runs.steps.RunStep;
import com.openai.models.beta.threads.runs.steps.StepRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
StepRetrieveParams params = StepRetrieveParams.builder()
.threadId("thread_id")
.runId("run_id")
.stepId("step_id")
.build();
RunStep runStep = client.beta().threads().runs().steps().retrieve(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run_step = openai.beta.threads.runs.steps.retrieve("step_id", thread_id: "thread_id", run_id:
"run_id")
puts(run_step)
description: Retrieves a run step.
/threads/{thread_id}/runs/{run_id}/submit_tool_outputs:
post:
operationId: submitToolOuputsToRun
tags:
- Assistants
summary: Submit tool outputs to run
parameters:
- in: path
name: thread_id
required: true
schema:
type: string
description: >-
The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) to which this run
belongs.
- in: path
name: run_id
required: true
schema:
type: string
description: The ID of the run that requires the tool output submission.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/SubmitToolOutputsRunRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/RunObject'
x-oaiMeta:
name: Submit tool outputs to run
group: threads
beta: true
returns: >-
The modified [run](https://platform.openai.com/docs/api-reference/runs/object) object matching the
specified ID.
examples:
- title: Default
request:
curl: |
curl https://api.openai.com/v1/threads/thread_123/runs/run_123/submit_tool_outputs \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"tool_outputs": [
{
"tool_call_id": "call_001",
"output": "70 degrees and sunny."
}
]
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.beta.threads.runs.submit_tool_outputs(
run_id="run_id",
thread_id="thread_id",
tool_outputs=[{}],
)
print(run.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.beta.threads.runs.submitToolOutputs('run_id', {
thread_id: 'thread_id',
tool_outputs: [{}],
});
console.log(run.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
run, err := client.Beta.Threads.Runs.SubmitToolOutputs(
context.TODO(),
"thread_id",
"run_id",
openai.BetaThreadRunSubmitToolOutputsParams{
ToolOutputs: []openai.BetaThreadRunSubmitToolOutputsParamsToolOutput{openai.BetaThreadRunSubmitToolOutputsParamsToolOutput{
}},
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", run.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.runs.Run;
import com.openai.models.beta.threads.runs.RunSubmitToolOutputsParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunSubmitToolOutputsParams params = RunSubmitToolOutputsParams.builder()
.threadId("thread_id")
.runId("run_id")
.addToolOutput(RunSubmitToolOutputsParams.ToolOutput.builder().build())
.build();
Run run = client.beta().threads().runs().submitToolOutputs(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.beta.threads.runs.submit_tool_outputs("run_id", thread_id: "thread_id",
tool_outputs: [{}])
puts(run)
response: |
{
"id": "run_123",
"object": "thread.run",
"created_at": 1699075592,
"assistant_id": "asst_123",
"thread_id": "thread_123",
"status": "queued",
"started_at": 1699075592,
"expires_at": 1699076192,
"cancelled_at": null,
"failed_at": null,
"completed_at": null,
"last_error": null,
"model": "gpt-4o",
"instructions": null,
"tools": [
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"]
}
},
"required": ["location"]
}
}
}
],
"metadata": {},
"usage": null,
"temperature": 1.0,
"top_p": 1.0,
"max_prompt_tokens": 1000,
"max_completion_tokens": 1000,
"truncation_strategy": {
"type": "auto",
"last_messages": null
},
"response_format": "auto",
"tool_choice": "auto",
"parallel_tool_calls": true
}
- title: Streaming
request:
curl: |
curl https://api.openai.com/v1/threads/thread_123/runs/run_123/submit_tool_outputs \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"tool_outputs": [
{
"tool_call_id": "call_001",
"output": "70 degrees and sunny."
}
],
"stream": true
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
run = client.beta.threads.runs.submit_tool_outputs(
run_id="run_id",
thread_id="thread_id",
tool_outputs=[{}],
)
print(run.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const run = await client.beta.threads.runs.submitToolOutputs('run_id', {
thread_id: 'thread_id',
tool_outputs: [{}],
});
console.log(run.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
run, err := client.Beta.Threads.Runs.SubmitToolOutputs(
context.TODO(),
"thread_id",
"run_id",
openai.BetaThreadRunSubmitToolOutputsParams{
ToolOutputs: []openai.BetaThreadRunSubmitToolOutputsParamsToolOutput{openai.BetaThreadRunSubmitToolOutputsParamsToolOutput{
}},
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", run.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.runs.Run;
import com.openai.models.beta.threads.runs.RunSubmitToolOutputsParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
RunSubmitToolOutputsParams params = RunSubmitToolOutputsParams.builder()
.threadId("thread_id")
.runId("run_id")
.addToolOutput(RunSubmitToolOutputsParams.ToolOutput.builder().build())
.build();
Run run = client.beta().threads().runs().submitToolOutputs(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
run = openai.beta.threads.runs.submit_tool_outputs("run_id", thread_id: "thread_id",
tool_outputs: [{}])
puts(run)
response: >
event: thread.run.step.completed
data:
{"id":"step_001","object":"thread.run.step","created_at":1710352449,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"tool_calls","status":"completed","cancelled_at":null,"completed_at":1710352475,"expires_at":1710353047,"failed_at":null,"last_error":null,"step_details":{"type":"tool_calls","tool_calls":[{"id":"call_iWr0kQ2EaYMaxNdl0v3KYkx7","type":"function","function":{"name":"get_current_weather","arguments":"{\"location\":\"San
Francisco, CA\",\"unit\":\"fahrenheit\"}","output":"70 degrees and
sunny."}}]},"usage":{"prompt_tokens":291,"completion_tokens":24,"total_tokens":315}}
event: thread.run.queued
data:
{"id":"run_123","object":"thread.run","created_at":1710352447,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":1710352448,"expires_at":1710353047,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
the current weather in a given
location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
city and state, e.g. San Francisco,
CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: thread.run.in_progress
data:
{"id":"run_123","object":"thread.run","created_at":1710352447,"assistant_id":"asst_123","thread_id":"thread_123","status":"in_progress","started_at":1710352475,"expires_at":1710353047,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
the current weather in a given
location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
city and state, e.g. San Francisco,
CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: thread.run.step.created
data:
{"id":"step_002","object":"thread.run.step","created_at":1710352476,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710353047,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_002"}},"usage":null}
event: thread.run.step.in_progress
data:
{"id":"step_002","object":"thread.run.step","created_at":1710352476,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710353047,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_002"}},"usage":null}
event: thread.message.created
data:
{"id":"msg_002","object":"thread.message","created_at":1710352476,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],"metadata":{}}
event: thread.message.in_progress
data:
{"id":"msg_002","object":"thread.message","created_at":1710352476,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],"metadata":{}}
event: thread.message.delta
data:
{"id":"msg_002","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"The","annotations":[]}}]}}
event: thread.message.delta
data:
{"id":"msg_002","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"
current"}}]}}
event: thread.message.delta
data:
{"id":"msg_002","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"
weather"}}]}}
...
event: thread.message.delta
data:
{"id":"msg_002","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"
sunny"}}]}}
event: thread.message.delta
data:
{"id":"msg_002","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"."}}]}}
event: thread.message.completed
data:
{"id":"msg_002","object":"thread.message","created_at":1710352476,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"completed","incomplete_details":null,"incomplete_at":null,"completed_at":1710352477,"role":"assistant","content":[{"type":"text","text":{"value":"The
current weather in San Francisco, CA is 70 degrees Fahrenheit and
sunny.","annotations":[]}}],"metadata":{}}
event: thread.run.step.completed
data:
{"id":"step_002","object":"thread.run.step","created_at":1710352476,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"completed","cancelled_at":null,"completed_at":1710352477,"expires_at":1710353047,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_002"}},"usage":{"prompt_tokens":329,"completion_tokens":18,"total_tokens":347}}
event: thread.run.completed
data:
{"id":"run_123","object":"thread.run","created_at":1710352447,"assistant_id":"asst_123","thread_id":"thread_123","status":"completed","started_at":1710352475,"expires_at":null,"cancelled_at":null,"failed_at":null,"completed_at":1710352477,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
the current weather in a given
location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
city and state, e.g. San Francisco,
CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":{"prompt_tokens":20,"completion_tokens":11,"total_tokens":31},"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}
event: done
data: [DONE]
description: >
When a run has the `status: "requires_action"` and `required_action.type` is `submit_tool_outputs`,
this endpoint can be used to submit the outputs from the tool calls once they're all completed. All
outputs must be submitted in a single request.
/uploads:
post:
operationId: createUpload
tags:
- Uploads
summary: Create upload
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateUploadRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/Upload'
x-oaiMeta:
name: Create upload
group: uploads
returns: >-
The [Upload](https://platform.openai.com/docs/api-reference/uploads/object) object with status
`pending`.
examples:
response: |
{
"id": "upload_abc123",
"object": "upload",
"bytes": 2147483648,
"created_at": 1719184911,
"filename": "training_examples.jsonl",
"purpose": "fine-tune",
"status": "pending",
"expires_at": 1719127296
}
request:
curl: |
curl https://api.openai.com/v1/uploads \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"purpose": "fine-tune",
"filename": "training_examples.jsonl",
"bytes": 2147483648,
"mime_type": "text/jsonl",
"expires_after": {
"anchor": "created_at",
"seconds": 3600
}
}'
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const upload = await client.uploads.create({
bytes: 0,
filename: 'filename',
mime_type: 'mime_type',
purpose: 'assistants',
});
console.log(upload.id);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
upload = client.uploads.create(
bytes=0,
filename="filename",
mime_type="mime_type",
purpose="assistants",
)
print(upload.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
upload, err := client.Uploads.New(context.TODO(), openai.UploadNewParams{
Bytes: 0,
Filename: "filename",
MimeType: "mime_type",
Purpose: openai.FilePurposeAssistants,
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", upload.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.files.FilePurpose;
import com.openai.models.uploads.Upload;
import com.openai.models.uploads.UploadCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
UploadCreateParams params = UploadCreateParams.builder()
.bytes(0L)
.filename("filename")
.mimeType("mime_type")
.purpose(FilePurpose.ASSISTANTS)
.build();
Upload upload = client.uploads().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
upload = openai.uploads.create(bytes: 0, filename: "filename", mime_type: "mime_type", purpose:
:assistants)
puts(upload)
description: >
Creates an intermediate [Upload](https://platform.openai.com/docs/api-reference/uploads/object) object
that you can add [Parts](https://platform.openai.com/docs/api-reference/uploads/part-object) to.
Currently, an Upload can accept at most 8 GB in total and expires after an
hour after you create it.
Once you complete the Upload, we will create a
[File](https://platform.openai.com/docs/api-reference/files/object) object that contains all the parts
you uploaded. This File is usable in the rest of our platform as a regular
File object.
For certain `purpose` values, the correct `mime_type` must be specified.
Please refer to documentation for the
[supported MIME types for your use
case](https://platform.openai.com/docs/assistants/tools/file-search#supported-files).
For guidance on the proper filename extensions for each purpose, please
follow the documentation on [creating a
File](https://platform.openai.com/docs/api-reference/files/create).
/uploads/{upload_id}/cancel:
post:
operationId: cancelUpload
tags:
- Uploads
summary: Cancel upload
parameters:
- in: path
name: upload_id
required: true
schema:
type: string
example: upload_abc123
description: |
The ID of the Upload.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/Upload'
x-oaiMeta:
name: Cancel upload
group: uploads
returns: >-
The [Upload](https://platform.openai.com/docs/api-reference/uploads/object) object with status
`cancelled`.
examples:
response: |
{
"id": "upload_abc123",
"object": "upload",
"bytes": 2147483648,
"created_at": 1719184911,
"filename": "training_examples.jsonl",
"purpose": "fine-tune",
"status": "cancelled",
"expires_at": 1719127296
}
request:
curl: |
curl https://api.openai.com/v1/uploads/upload_abc123/cancel
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const upload = await client.uploads.cancel('upload_abc123');
console.log(upload.id);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
upload = client.uploads.cancel(
"upload_abc123",
)
print(upload.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
upload, err := client.Uploads.Cancel(context.TODO(), "upload_abc123")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", upload.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.uploads.Upload;
import com.openai.models.uploads.UploadCancelParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
Upload upload = client.uploads().cancel("upload_abc123");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
upload = openai.uploads.cancel("upload_abc123")
puts(upload)
description: |
Cancels the Upload. No Parts may be added after an Upload is cancelled.
/uploads/{upload_id}/complete:
post:
operationId: completeUpload
tags:
- Uploads
summary: Complete upload
parameters:
- in: path
name: upload_id
required: true
schema:
type: string
example: upload_abc123
description: |
The ID of the Upload.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CompleteUploadRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/Upload'
x-oaiMeta:
name: Complete upload
group: uploads
returns: >-
The [Upload](https://platform.openai.com/docs/api-reference/uploads/object) object with status
`completed` with an additional `file` property containing the created usable File object.
examples:
response: |
{
"id": "upload_abc123",
"object": "upload",
"bytes": 2147483648,
"created_at": 1719184911,
"filename": "training_examples.jsonl",
"purpose": "fine-tune",
"status": "completed",
"expires_at": 1719127296,
"file": {
"id": "file-xyz321",
"object": "file",
"bytes": 2147483648,
"created_at": 1719186911,
"expires_at": 1719127296,
"filename": "training_examples.jsonl",
"purpose": "fine-tune",
}
}
request:
curl: |
curl https://api.openai.com/v1/uploads/upload_abc123/complete
-d '{
"part_ids": ["part_def456", "part_ghi789"]
}'
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const upload = await client.uploads.complete('upload_abc123', { part_ids: ['string'] });
console.log(upload.id);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
upload = client.uploads.complete(
upload_id="upload_abc123",
part_ids=["string"],
)
print(upload.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
upload, err := client.Uploads.Complete(
context.TODO(),
"upload_abc123",
openai.UploadCompleteParams{
PartIDs: []string{"string"},
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", upload.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.uploads.Upload;
import com.openai.models.uploads.UploadCompleteParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
UploadCompleteParams params = UploadCompleteParams.builder()
.uploadId("upload_abc123")
.addPartId("string")
.build();
Upload upload = client.uploads().complete(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
upload = openai.uploads.complete("upload_abc123", part_ids: ["string"])
puts(upload)
description: >
Completes the [Upload](https://platform.openai.com/docs/api-reference/uploads/object).
Within the returned Upload object, there is a nested
[File](https://platform.openai.com/docs/api-reference/files/object) object that is ready to use in the
rest of the platform.
You can specify the order of the Parts by passing in an ordered list of the Part IDs.
The number of bytes uploaded upon completion must match the number of bytes initially specified when
creating the Upload object. No Parts may be added after an Upload is completed.
/uploads/{upload_id}/parts:
post:
operationId: addUploadPart
tags:
- Uploads
summary: Add upload part
parameters:
- in: path
name: upload_id
required: true
schema:
type: string
example: upload_abc123
description: |
The ID of the Upload.
requestBody:
required: true
content:
multipart/form-data:
schema:
$ref: '#/components/schemas/AddUploadPartRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/UploadPart'
x-oaiMeta:
name: Add upload part
group: uploads
returns: The upload [Part](https://platform.openai.com/docs/api-reference/uploads/part-object) object.
examples:
response: |
{
"id": "part_def456",
"object": "upload.part",
"created_at": 1719185911,
"upload_id": "upload_abc123"
}
request:
curl: |
curl https://api.openai.com/v1/uploads/upload_abc123/parts
-F data="aHR0cHM6Ly9hcGkub3BlbmFpLmNvbS92MS91cGxvYWRz..."
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const uploadPart = await client.uploads.parts.create('upload_abc123', {
data: fs.createReadStream('path/to/file'),
});
console.log(uploadPart.id);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
upload_part = client.uploads.parts.create(
upload_id="upload_abc123",
data=b"raw file contents",
)
print(upload_part.id)
go: |
package main
import (
"bytes"
"context"
"fmt"
"io"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
uploadPart, err := client.Uploads.Parts.New(
context.TODO(),
"upload_abc123",
openai.UploadPartNewParams{
Data: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", uploadPart.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.uploads.parts.PartCreateParams;
import com.openai.models.uploads.parts.UploadPart;
import java.io.ByteArrayInputStream;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
PartCreateParams params = PartCreateParams.builder()
.uploadId("upload_abc123")
.data(ByteArrayInputStream("some content".getBytes()))
.build();
UploadPart uploadPart = client.uploads().parts().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
upload_part = openai.uploads.parts.create("upload_abc123", data: Pathname(__FILE__))
puts(upload_part)
description: >
Adds a [Part](https://platform.openai.com/docs/api-reference/uploads/part-object) to an
[Upload](https://platform.openai.com/docs/api-reference/uploads/object) object. A Part represents a
chunk of bytes from the file you are trying to upload.
Each Part can be at most 64 MB, and you can add Parts until you hit the Upload maximum of 8 GB.
It is possible to add multiple Parts in parallel. You can decide the intended order of the Parts when
you [complete the Upload](https://platform.openai.com/docs/api-reference/uploads/complete).
/vector_stores:
get:
operationId: listVectorStores
tags:
- Vector stores
summary: List vector stores
parameters:
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: order
in: query
description: >
Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
descending order.
schema:
type: string
default: desc
enum:
- asc
- desc
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
schema:
type: string
- name: before
in: query
description: >
A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, starting with obj_foo, your
subsequent call can include before=obj_foo in order to fetch the previous page of the list.
schema:
type: string
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListVectorStoresResponse'
x-oaiMeta:
name: List vector stores
group: vector_stores
returns: >-
A list of [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object)
objects.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "vs_abc123",
"object": "vector_store",
"created_at": 1699061776,
"name": "Support FAQ",
"bytes": 139920,
"file_counts": {
"in_progress": 0,
"completed": 3,
"failed": 0,
"cancelled": 0,
"total": 3
}
},
{
"id": "vs_abc456",
"object": "vector_store",
"created_at": 1699061776,
"name": "Support FAQ v2",
"bytes": 139920,
"file_counts": {
"in_progress": 0,
"completed": 3,
"failed": 0,
"cancelled": 0,
"total": 3
}
}
],
"first_id": "vs_abc123",
"last_id": "vs_abc456",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.vector_stores.list()
page = page.data[0]
print(page.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const vectorStore of client.vectorStores.list()) {
console.log(vectorStore.id);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.VectorStores.List(context.TODO(), openai.VectorStoreListParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.VectorStoreListPage;
import com.openai.models.vectorstores.VectorStoreListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
VectorStoreListPage page = client.vectorStores().list();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.vector_stores.list
puts(page)
description: Returns a list of vector stores.
post:
operationId: createVectorStore
tags:
- Vector stores
summary: Create vector store
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateVectorStoreRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/VectorStoreObject'
x-oaiMeta:
name: Create vector store
group: vector_stores
returns: A [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) object.
examples:
response: |
{
"id": "vs_abc123",
"object": "vector_store",
"created_at": 1699061776,
"name": "Support FAQ",
"bytes": 139920,
"file_counts": {
"in_progress": 0,
"completed": 3,
"failed": 0,
"cancelled": 0,
"total": 3
}
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"name": "Support FAQ"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
vector_store = client.vector_stores.create()
print(vector_store.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const vectorStore = await client.vectorStores.create();
console.log(vectorStore.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
vectorStore, err := client.VectorStores.New(context.TODO(), openai.VectorStoreNewParams{
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", vectorStore.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.VectorStore;
import com.openai.models.vectorstores.VectorStoreCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
VectorStore vectorStore = client.vectorStores().create();
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
vector_store = openai.vector_stores.create
puts(vector_store)
description: Create a vector store.
/vector_stores/{vector_store_id}:
get:
operationId: getVectorStore
tags:
- Vector stores
summary: Retrieve vector store
parameters:
- in: path
name: vector_store_id
required: true
schema:
type: string
description: The ID of the vector store to retrieve.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/VectorStoreObject'
x-oaiMeta:
name: Retrieve vector store
group: vector_stores
returns: >-
The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) object
matching the specified ID.
examples:
response: |
{
"id": "vs_abc123",
"object": "vector_store",
"created_at": 1699061776
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores/vs_abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
vector_store = client.vector_stores.retrieve(
"vector_store_id",
)
print(vector_store.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const vectorStore = await client.vectorStores.retrieve('vector_store_id');
console.log(vectorStore.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
vectorStore, err := client.VectorStores.Get(context.TODO(), "vector_store_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", vectorStore.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.VectorStore;
import com.openai.models.vectorstores.VectorStoreRetrieveParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
VectorStore vectorStore = client.vectorStores().retrieve("vector_store_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
vector_store = openai.vector_stores.retrieve("vector_store_id")
puts(vector_store)
description: Retrieves a vector store.
post:
operationId: modifyVectorStore
tags:
- Vector stores
summary: Modify vector store
parameters:
- in: path
name: vector_store_id
required: true
schema:
type: string
description: The ID of the vector store to modify.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/UpdateVectorStoreRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/VectorStoreObject'
x-oaiMeta:
name: Modify vector store
group: vector_stores
returns: >-
The modified [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object)
object.
examples:
response: |
{
"id": "vs_abc123",
"object": "vector_store",
"created_at": 1699061776,
"name": "Support FAQ",
"bytes": 139920,
"file_counts": {
"in_progress": 0,
"completed": 3,
"failed": 0,
"cancelled": 0,
"total": 3
}
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores/vs_abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2"
-d '{
"name": "Support FAQ"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
vector_store = client.vector_stores.update(
vector_store_id="vector_store_id",
)
print(vector_store.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const vectorStore = await client.vectorStores.update('vector_store_id');
console.log(vectorStore.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
vectorStore, err := client.VectorStores.Update(
context.TODO(),
"vector_store_id",
openai.VectorStoreUpdateParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", vectorStore.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.VectorStore;
import com.openai.models.vectorstores.VectorStoreUpdateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
VectorStore vectorStore = client.vectorStores().update("vector_store_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
vector_store = openai.vector_stores.update("vector_store_id")
puts(vector_store)
description: Modifies a vector store.
delete:
operationId: deleteVectorStore
tags:
- Vector stores
summary: Delete vector store
parameters:
- in: path
name: vector_store_id
required: true
schema:
type: string
description: The ID of the vector store to delete.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/DeleteVectorStoreResponse'
x-oaiMeta:
name: Delete vector store
group: vector_stores
returns: Deletion status
examples:
response: |
{
id: "vs_abc123",
object: "vector_store.deleted",
deleted: true
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores/vs_abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-X DELETE
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
vector_store_deleted = client.vector_stores.delete(
"vector_store_id",
)
print(vector_store_deleted.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const vectorStoreDeleted = await client.vectorStores.delete('vector_store_id');
console.log(vectorStoreDeleted.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
vectorStoreDeleted, err := client.VectorStores.Delete(context.TODO(), "vector_store_id")
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", vectorStoreDeleted.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.VectorStoreDeleteParams;
import com.openai.models.vectorstores.VectorStoreDeleted;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
VectorStoreDeleted vectorStoreDeleted = client.vectorStores().delete("vector_store_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
vector_store_deleted = openai.vector_stores.delete("vector_store_id")
puts(vector_store_deleted)
description: Delete a vector store.
/vector_stores/{vector_store_id}/file_batches:
post:
operationId: createVectorStoreFileBatch
tags:
- Vector stores
summary: Create vector store file batch
parameters:
- in: path
name: vector_store_id
required: true
schema:
type: string
example: vs_abc123
description: |
The ID of the vector store for which to create a File Batch.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateVectorStoreFileBatchRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/VectorStoreFileBatchObject'
x-oaiMeta:
name: Create vector store file batch
group: vector_stores
returns: >-
A [vector store file
batch](https://platform.openai.com/docs/api-reference/vector-stores-file-batches/batch-object)
object.
examples:
response: |
{
"id": "vsfb_abc123",
"object": "vector_store.file_batch",
"created_at": 1699061776,
"vector_store_id": "vs_abc123",
"status": "in_progress",
"file_counts": {
"in_progress": 1,
"completed": 1,
"failed": 0,
"cancelled": 0,
"total": 0,
}
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores/vs_abc123/file_batches \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"file_ids": ["file-abc123", "file-abc456"]
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
vector_store_file_batch = client.vector_stores.file_batches.create(
vector_store_id="vs_abc123",
file_ids=["string"],
)
print(vector_store_file_batch.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const vectorStoreFileBatch = await client.vectorStores.fileBatches.create('vs_abc123', {
file_ids: ['string'],
});
console.log(vectorStoreFileBatch.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
vectorStoreFileBatch, err := client.VectorStores.FileBatches.New(
context.TODO(),
"vs_abc123",
openai.VectorStoreFileBatchNewParams{
FileIDs: []string{"string"},
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", vectorStoreFileBatch.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.filebatches.FileBatchCreateParams;
import com.openai.models.vectorstores.filebatches.VectorStoreFileBatch;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileBatchCreateParams params = FileBatchCreateParams.builder()
.vectorStoreId("vs_abc123")
.addFileId("string")
.build();
VectorStoreFileBatch vectorStoreFileBatch = client.vectorStores().fileBatches().create(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
vector_store_file_batch = openai.vector_stores.file_batches.create("vs_abc123", file_ids:
["string"])
puts(vector_store_file_batch)
description: Create a vector store file batch.
/vector_stores/{vector_store_id}/file_batches/{batch_id}:
get:
operationId: getVectorStoreFileBatch
tags:
- Vector stores
summary: Retrieve vector store file batch
parameters:
- in: path
name: vector_store_id
required: true
schema:
type: string
example: vs_abc123
description: The ID of the vector store that the file batch belongs to.
- in: path
name: batch_id
required: true
schema:
type: string
example: vsfb_abc123
description: The ID of the file batch being retrieved.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/VectorStoreFileBatchObject'
x-oaiMeta:
name: Retrieve vector store file batch
group: vector_stores
returns: >-
The [vector store file
batch](https://platform.openai.com/docs/api-reference/vector-stores-file-batches/batch-object)
object.
examples:
response: |
{
"id": "vsfb_abc123",
"object": "vector_store.file_batch",
"created_at": 1699061776,
"vector_store_id": "vs_abc123",
"status": "in_progress",
"file_counts": {
"in_progress": 1,
"completed": 1,
"failed": 0,
"cancelled": 0,
"total": 0,
}
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
vector_store_file_batch = client.vector_stores.file_batches.retrieve(
batch_id="vsfb_abc123",
vector_store_id="vs_abc123",
)
print(vector_store_file_batch.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const vectorStoreFileBatch = await client.vectorStores.fileBatches.retrieve('vsfb_abc123', {
vector_store_id: 'vs_abc123',
});
console.log(vectorStoreFileBatch.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
vectorStoreFileBatch, err := client.VectorStores.FileBatches.Get(
context.TODO(),
"vs_abc123",
"vsfb_abc123",
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", vectorStoreFileBatch.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.filebatches.FileBatchRetrieveParams;
import com.openai.models.vectorstores.filebatches.VectorStoreFileBatch;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileBatchRetrieveParams params = FileBatchRetrieveParams.builder()
.vectorStoreId("vs_abc123")
.batchId("vsfb_abc123")
.build();
VectorStoreFileBatch vectorStoreFileBatch = client.vectorStores().fileBatches().retrieve(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
vector_store_file_batch = openai.vector_stores.file_batches.retrieve("vsfb_abc123",
vector_store_id: "vs_abc123")
puts(vector_store_file_batch)
description: Retrieves a vector store file batch.
/vector_stores/{vector_store_id}/file_batches/{batch_id}/cancel:
post:
operationId: cancelVectorStoreFileBatch
tags:
- Vector stores
summary: Cancel vector store file batch
parameters:
- in: path
name: vector_store_id
required: true
schema:
type: string
description: The ID of the vector store that the file batch belongs to.
- in: path
name: batch_id
required: true
schema:
type: string
description: The ID of the file batch to cancel.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/VectorStoreFileBatchObject'
x-oaiMeta:
name: Cancel vector store file batch
group: vector_stores
returns: The modified vector store file batch object.
examples:
response: |
{
"id": "vsfb_abc123",
"object": "vector_store.file_batch",
"created_at": 1699061776,
"vector_store_id": "vs_abc123",
"status": "in_progress",
"file_counts": {
"in_progress": 12,
"completed": 3,
"failed": 0,
"cancelled": 0,
"total": 15,
}
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123/cancel \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-X POST
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
vector_store_file_batch = client.vector_stores.file_batches.cancel(
batch_id="batch_id",
vector_store_id="vector_store_id",
)
print(vector_store_file_batch.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const vectorStoreFileBatch = await client.vectorStores.fileBatches.cancel('batch_id', {
vector_store_id: 'vector_store_id',
});
console.log(vectorStoreFileBatch.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
vectorStoreFileBatch, err := client.VectorStores.FileBatches.Cancel(
context.TODO(),
"vector_store_id",
"batch_id",
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", vectorStoreFileBatch.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.filebatches.FileBatchCancelParams;
import com.openai.models.vectorstores.filebatches.VectorStoreFileBatch;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileBatchCancelParams params = FileBatchCancelParams.builder()
.vectorStoreId("vector_store_id")
.batchId("batch_id")
.build();
VectorStoreFileBatch vectorStoreFileBatch = client.vectorStores().fileBatches().cancel(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
vector_store_file_batch = openai.vector_stores.file_batches.cancel("batch_id", vector_store_id:
"vector_store_id")
puts(vector_store_file_batch)
description: >-
Cancel a vector store file batch. This attempts to cancel the processing of files in this batch as
soon as possible.
/vector_stores/{vector_store_id}/file_batches/{batch_id}/files:
get:
operationId: listFilesInVectorStoreBatch
tags:
- Vector stores
summary: List vector store files in a batch
parameters:
- name: vector_store_id
in: path
description: The ID of the vector store that the files belong to.
required: true
schema:
type: string
- name: batch_id
in: path
description: The ID of the file batch that the files belong to.
required: true
schema:
type: string
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: order
in: query
description: >
Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
descending order.
schema:
type: string
default: desc
enum:
- asc
- desc
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
schema:
type: string
- name: before
in: query
description: >
A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, starting with obj_foo, your
subsequent call can include before=obj_foo in order to fetch the previous page of the list.
schema:
type: string
- name: filter
in: query
description: Filter by file status. One of `in_progress`, `completed`, `failed`, `cancelled`.
schema:
type: string
enum:
- in_progress
- completed
- failed
- cancelled
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListVectorStoreFilesResponse'
x-oaiMeta:
name: List vector store files in a batch
group: vector_stores
returns: >-
A list of [vector store
file](https://platform.openai.com/docs/api-reference/vector-stores-files/file-object) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "file-abc123",
"object": "vector_store.file",
"created_at": 1699061776,
"vector_store_id": "vs_abc123"
},
{
"id": "file-abc456",
"object": "vector_store.file",
"created_at": 1699061776,
"vector_store_id": "vs_abc123"
}
],
"first_id": "file-abc123",
"last_id": "file-abc456",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123/files \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.vector_stores.file_batches.list_files(
batch_id="batch_id",
vector_store_id="vector_store_id",
)
page = page.data[0]
print(page.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const vectorStoreFile of client.vectorStores.fileBatches.listFiles('batch_id', {
vector_store_id: 'vector_store_id',
})) {
console.log(vectorStoreFile.id);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.VectorStores.FileBatches.ListFiles(
context.TODO(),
"vector_store_id",
"batch_id",
openai.VectorStoreFileBatchListFilesParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.filebatches.FileBatchListFilesPage;
import com.openai.models.vectorstores.filebatches.FileBatchListFilesParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileBatchListFilesParams params = FileBatchListFilesParams.builder()
.vectorStoreId("vector_store_id")
.batchId("batch_id")
.build();
FileBatchListFilesPage page = client.vectorStores().fileBatches().listFiles(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.vector_stores.file_batches.list_files("batch_id", vector_store_id:
"vector_store_id")
puts(page)
description: Returns a list of vector store files in a batch.
/vector_stores/{vector_store_id}/files:
get:
operationId: listVectorStoreFiles
tags:
- Vector stores
summary: List vector store files
parameters:
- name: vector_store_id
in: path
description: The ID of the vector store that the files belong to.
required: true
schema:
type: string
- name: limit
in: query
description: >
A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
default is 20.
required: false
schema:
type: integer
default: 20
- name: order
in: query
description: >
Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
descending order.
schema:
type: string
default: desc
enum:
- asc
- desc
- name: after
in: query
description: >
A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
call can include after=obj_foo in order to fetch the next page of the list.
schema:
type: string
- name: before
in: query
description: >
A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
instance, if you make a list request and receive 100 objects, starting with obj_foo, your
subsequent call can include before=obj_foo in order to fetch the previous page of the list.
schema:
type: string
- name: filter
in: query
description: Filter by file status. One of `in_progress`, `completed`, `failed`, `cancelled`.
schema:
type: string
enum:
- in_progress
- completed
- failed
- cancelled
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ListVectorStoreFilesResponse'
x-oaiMeta:
name: List vector store files
group: vector_stores
returns: >-
A list of [vector store
file](https://platform.openai.com/docs/api-reference/vector-stores-files/file-object) objects.
examples:
response: |
{
"object": "list",
"data": [
{
"id": "file-abc123",
"object": "vector_store.file",
"created_at": 1699061776,
"vector_store_id": "vs_abc123"
},
{
"id": "file-abc456",
"object": "vector_store.file",
"created_at": 1699061776,
"vector_store_id": "vs_abc123"
}
],
"first_id": "file-abc123",
"last_id": "file-abc456",
"has_more": false
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores/vs_abc123/files \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.vector_stores.files.list(
vector_store_id="vector_store_id",
)
page = page.data[0]
print(page.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const vectorStoreFile of client.vectorStores.files.list('vector_store_id')) {
console.log(vectorStoreFile.id);
}
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.VectorStores.Files.List(
context.TODO(),
"vector_store_id",
openai.VectorStoreFileListParams{
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.files.FileListPage;
import com.openai.models.vectorstores.files.FileListParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileListPage page = client.vectorStores().files().list("vector_store_id");
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.vector_stores.files.list("vector_store_id")
puts(page)
description: Returns a list of vector store files.
post:
operationId: createVectorStoreFile
tags:
- Vector stores
summary: Create vector store file
parameters:
- in: path
name: vector_store_id
required: true
schema:
type: string
example: vs_abc123
description: |
The ID of the vector store for which to create a File.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateVectorStoreFileRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/VectorStoreFileObject'
x-oaiMeta:
name: Create vector store file
group: vector_stores
returns: >-
A [vector store
file](https://platform.openai.com/docs/api-reference/vector-stores-files/file-object) object.
examples:
response: |
{
"id": "file-abc123",
"object": "vector_store.file",
"created_at": 1699061776,
"usage_bytes": 1234,
"vector_store_id": "vs_abcd",
"status": "completed",
"last_error": null
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores/vs_abc123/files \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"file_id": "file-abc123"
}'
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
vector_store_file = client.vector_stores.files.create(
vector_store_id="vs_abc123",
file_id="file_id",
)
print(vector_store_file.id)
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const vectorStoreFile = await client.vectorStores.files.create('vs_abc123', { file_id: 'file_id'
});
console.log(vectorStoreFile.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
vectorStoreFile, err := client.VectorStores.Files.New(
context.TODO(),
"vs_abc123",
openai.VectorStoreFileNewParams{
FileID: "file_id",
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", vectorStoreFile.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.files.FileCreateParams;
import com.openai.models.vectorstores.files.VectorStoreFile;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileCreateParams params = FileCreateParams.builder()
.vectorStoreId("vs_abc123")
.fileId("file_id")
.build();
VectorStoreFile vectorStoreFile = client.vectorStores().files().create(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
vector_store_file = openai.vector_stores.files.create("vs_abc123", file_id: "file_id")
puts(vector_store_file)
description: >-
Create a vector store file by attaching a [File](https://platform.openai.com/docs/api-reference/files)
to a [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object).
/vector_stores/{vector_store_id}/files/{file_id}:
get:
operationId: getVectorStoreFile
tags:
- Vector stores
summary: Retrieve vector store file
parameters:
- in: path
name: vector_store_id
required: true
schema:
type: string
example: vs_abc123
description: The ID of the vector store that the file belongs to.
- in: path
name: file_id
required: true
schema:
type: string
example: file-abc123
description: The ID of the file being retrieved.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/VectorStoreFileObject'
x-oaiMeta:
name: Retrieve vector store file
group: vector_stores
returns: >-
The [vector store
file](https://platform.openai.com/docs/api-reference/vector-stores-files/file-object) object.
examples:
response: |
{
"id": "file-abc123",
"object": "vector_store.file",
"created_at": 1699061776,
"vector_store_id": "vs_abcd",
"status": "completed",
"last_error": null
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores/vs_abc123/files/file-abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2"
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
vector_store_file = client.vector_stores.files.retrieve(
file_id="file-abc123",
vector_store_id="vs_abc123",
)
print(vector_store_file.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const vectorStoreFile = await client.vectorStores.files.retrieve('file-abc123', {
vector_store_id: 'vs_abc123',
});
console.log(vectorStoreFile.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
vectorStoreFile, err := client.VectorStores.Files.Get(
context.TODO(),
"vs_abc123",
"file-abc123",
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", vectorStoreFile.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.files.FileRetrieveParams;
import com.openai.models.vectorstores.files.VectorStoreFile;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileRetrieveParams params = FileRetrieveParams.builder()
.vectorStoreId("vs_abc123")
.fileId("file-abc123")
.build();
VectorStoreFile vectorStoreFile = client.vectorStores().files().retrieve(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
vector_store_file = openai.vector_stores.files.retrieve("file-abc123", vector_store_id:
"vs_abc123")
puts(vector_store_file)
description: Retrieves a vector store file.
delete:
operationId: deleteVectorStoreFile
tags:
- Vector stores
summary: Delete vector store file
parameters:
- in: path
name: vector_store_id
required: true
schema:
type: string
description: The ID of the vector store that the file belongs to.
- in: path
name: file_id
required: true
schema:
type: string
description: The ID of the file to delete.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/DeleteVectorStoreFileResponse'
x-oaiMeta:
name: Delete vector store file
group: vector_stores
returns: Deletion status
examples:
response: |
{
id: "file-abc123",
object: "vector_store.file.deleted",
deleted: true
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores/vs_abc123/files/file-abc123 \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-X DELETE
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
vector_store_file_deleted = client.vector_stores.files.delete(
file_id="file_id",
vector_store_id="vector_store_id",
)
print(vector_store_file_deleted.id)
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const vectorStoreFileDeleted = await client.vectorStores.files.delete('file_id', {
vector_store_id: 'vector_store_id',
});
console.log(vectorStoreFileDeleted.id);
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
vectorStoreFileDeleted, err := client.VectorStores.Files.Delete(
context.TODO(),
"vector_store_id",
"file_id",
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", vectorStoreFileDeleted.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.files.FileDeleteParams;
import com.openai.models.vectorstores.files.VectorStoreFileDeleted;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileDeleteParams params = FileDeleteParams.builder()
.vectorStoreId("vector_store_id")
.fileId("file_id")
.build();
VectorStoreFileDeleted vectorStoreFileDeleted = client.vectorStores().files().delete(params);
}
}
ruby: >-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
vector_store_file_deleted = openai.vector_stores.files.delete("file_id", vector_store_id:
"vector_store_id")
puts(vector_store_file_deleted)
description: >-
Delete a vector store file. This will remove the file from the vector store but the file itself will
not be deleted. To delete the file, use the [delete
file](https://platform.openai.com/docs/api-reference/files/delete) endpoint.
post:
operationId: updateVectorStoreFileAttributes
tags:
- Vector stores
summary: Update vector store file attributes
parameters:
- in: path
name: vector_store_id
required: true
schema:
type: string
example: vs_abc123
description: The ID of the vector store the file belongs to.
- in: path
name: file_id
required: true
schema:
type: string
example: file-abc123
description: The ID of the file to update attributes.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/UpdateVectorStoreFileAttributesRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/VectorStoreFileObject'
x-oaiMeta:
name: Update vector store file attributes
group: vector_stores
returns: >-
The updated [vector store
file](https://platform.openai.com/docs/api-reference/vector-stores-files/file-object) object.
examples:
response: |
{
"id": "file-abc123",
"object": "vector_store.file",
"usage_bytes": 1234,
"created_at": 1699061776,
"vector_store_id": "vs_abcd",
"status": "completed",
"last_error": null,
"chunking_strategy": {...},
"attributes": {"key1": "value1", "key2": 2}
}
request:
curl: |
curl https://api.openai.com/v1/vector_stores/{vector_store_id}/files/{file_id} \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{"attributes": {"key1": "value1", "key2": 2}}'
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
const vectorStoreFile = await client.vectorStores.files.update('file-abc123', {
vector_store_id: 'vs_abc123',
attributes: { foo: 'string' },
});
console.log(vectorStoreFile.id);
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
vector_store_file = client.vector_stores.files.update(
file_id="file-abc123",
vector_store_id="vs_abc123",
attributes={
"foo": "string"
},
)
print(vector_store_file.id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
vectorStoreFile, err := client.VectorStores.Files.Update(
context.TODO(),
"vs_abc123",
"file-abc123",
openai.VectorStoreFileUpdateParams{
Attributes: map[string]openai.VectorStoreFileUpdateParamsAttributeUnion{
"foo": openai.VectorStoreFileUpdateParamsAttributeUnion{
OfString: openai.String("string"),
},
},
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", vectorStoreFile.ID)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.core.JsonValue;
import com.openai.models.vectorstores.files.FileUpdateParams;
import com.openai.models.vectorstores.files.VectorStoreFile;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileUpdateParams params = FileUpdateParams.builder()
.vectorStoreId("vs_abc123")
.fileId("file-abc123")
.attributes(FileUpdateParams.Attributes.builder()
.putAdditionalProperty("foo", JsonValue.from("string"))
.build())
.build();
VectorStoreFile vectorStoreFile = client.vectorStores().files().update(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
vector_store_file = openai.vector_stores.files.update(
"file-abc123",
vector_store_id: "vs_abc123",
attributes: {foo: "string"}
)
puts(vector_store_file)
description: Update attributes on a vector store file.
/vector_stores/{vector_store_id}/files/{file_id}/content:
get:
operationId: retrieveVectorStoreFileContent
tags:
- Vector stores
summary: Retrieve vector store file content
parameters:
- in: path
name: vector_store_id
required: true
schema:
type: string
example: vs_abc123
description: The ID of the vector store.
- in: path
name: file_id
required: true
schema:
type: string
example: file-abc123
description: The ID of the file within the vector store.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/VectorStoreFileContentResponse'
x-oaiMeta:
name: Retrieve vector store file content
group: vector_stores
returns: The parsed contents of the specified vector store file.
examples:
response: |
{
"file_id": "file-abc123",
"filename": "example.txt",
"attributes": {"key": "value"},
"content": [
{"type": "text", "text": "..."},
...
]
}
request:
curl: |
curl \
https://api.openai.com/v1/vector_stores/vs_abc123/files/file-abc123/content \
-H "Authorization: Bearer $OPENAI_API_KEY"
node.js: |-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const fileContentResponse of client.vectorStores.files.content('file-abc123', {
vector_store_id: 'vs_abc123',
})) {
console.log(fileContentResponse.text);
}
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.vector_stores.files.content(
file_id="file-abc123",
vector_store_id="vs_abc123",
)
page = page.data[0]
print(page.text)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.VectorStores.Files.Content(
context.TODO(),
"vs_abc123",
"file-abc123",
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.files.FileContentPage;
import com.openai.models.vectorstores.files.FileContentParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
FileContentParams params = FileContentParams.builder()
.vectorStoreId("vs_abc123")
.fileId("file-abc123")
.build();
FileContentPage page = client.vectorStores().files().content(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.vector_stores.files.content("file-abc123", vector_store_id: "vs_abc123")
puts(page)
description: Retrieve the parsed contents of a vector store file.
/vector_stores/{vector_store_id}/search:
post:
operationId: searchVectorStore
tags:
- Vector stores
summary: Search vector store
parameters:
- in: path
name: vector_store_id
required: true
schema:
type: string
example: vs_abc123
description: The ID of the vector store to search.
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/VectorStoreSearchRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/VectorStoreSearchResultsPage'
x-oaiMeta:
name: Search vector store
group: vector_stores
returns: A page of search results from the vector store.
examples:
response: |
{
"object": "vector_store.search_results.page",
"search_query": "What is the return policy?",
"data": [
{
"file_id": "file_123",
"filename": "document.pdf",
"score": 0.95,
"attributes": {
"author": "John Doe",
"date": "2023-01-01"
},
"content": [
{
"type": "text",
"text": "Relevant chunk"
}
]
},
{
"file_id": "file_456",
"filename": "notes.txt",
"score": 0.89,
"attributes": {
"author": "Jane Smith",
"date": "2023-01-02"
},
"content": [
{
"type": "text",
"text": "Sample text content from the vector store."
}
]
}
],
"has_more": false,
"next_page": null
}
request:
curl: |
curl -X POST \
https://api.openai.com/v1/vector_stores/vs_abc123/search \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{"query": "What is the return policy?", "filters": {...}}'
node.js: >-
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'My API Key',
});
// Automatically fetches more pages as needed.
for await (const vectorStoreSearchResponse of client.vectorStores.search('vs_abc123', { query:
'string' })) {
console.log(vectorStoreSearchResponse.file_id);
}
python: |-
from openai import OpenAI
client = OpenAI(
api_key="My API Key",
)
page = client.vector_stores.search(
vector_store_id="vs_abc123",
query="string",
)
page = page.data[0]
print(page.file_id)
go: |
package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
page, err := client.VectorStores.Search(
context.TODO(),
"vs_abc123",
openai.VectorStoreSearchParams{
Query: openai.VectorStoreSearchParamsQueryUnion{
OfString: openai.String("string"),
},
},
)
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", page)
}
java: |-
package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.VectorStoreSearchPage;
import com.openai.models.vectorstores.VectorStoreSearchParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
VectorStoreSearchParams params = VectorStoreSearchParams.builder()
.vectorStoreId("vs_abc123")
.query("string")
.build();
VectorStoreSearchPage page = client.vectorStores().search(params);
}
}
ruby: |-
require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
page = openai.vector_stores.search("vs_abc123", query: "string")
puts(page)
description: Search a vector store for relevant chunks based on a query and file attributes filter.
webhooks:
batch_cancelled:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookBatchCancelled'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
batch_completed:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookBatchCompleted'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
batch_expired:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookBatchExpired'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
batch_failed:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookBatchFailed'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
eval_run_canceled:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookEvalRunCanceled'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
eval_run_failed:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookEvalRunFailed'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
eval_run_succeeded:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookEvalRunSucceeded'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
fine_tuning_job_cancelled:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookFineTuningJobCancelled'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
fine_tuning_job_failed:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookFineTuningJobFailed'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
fine_tuning_job_succeeded:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookFineTuningJobSucceeded'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
response_cancelled:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookResponseCancelled'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
response_completed:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookResponseCompleted'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
response_failed:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookResponseFailed'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
response_incomplete:
post:
requestBody:
description: The event payload sent by the API.
content:
application/json:
schema:
$ref: '#/components/schemas/WebhookResponseIncomplete'
responses:
'200':
description: |
Return a 200 status code to acknowledge receipt of the event. Non-200
status codes will be retried.
components:
schemas:
AddUploadPartRequest:
type: object
additionalProperties: false
properties:
data:
description: |
The chunk of bytes for this Part.
type: string
format: binary
required:
- data
AdminApiKey:
type: object
description: Represents an individual Admin API key in an org.
properties:
object:
type: string
example: organization.admin_api_key
description: The object type, which is always `organization.admin_api_key`
x-stainless-const: true
id:
type: string
example: key_abc
description: The identifier, which can be referenced in API endpoints
name:
type: string
example: Administration Key
description: The name of the API key
redacted_value:
type: string
example: sk-admin...def
description: The redacted value of the API key
value:
type: string
example: sk-admin-1234abcd
description: The value of the API key. Only shown on create.
created_at:
type: integer
format: int64
example: 1711471533
description: The Unix timestamp (in seconds) of when the API key was created
last_used_at:
type: integer
format: int64
nullable: true
example: 1711471534
description: The Unix timestamp (in seconds) of when the API key was last used
owner:
type: object
properties:
type:
type: string
example: user
description: Always `user`
object:
type: string
example: organization.user
description: The object type, which is always organization.user
id:
type: string
example: sa_456
description: The identifier, which can be referenced in API endpoints
name:
type: string
example: My Service Account
description: The name of the user
created_at:
type: integer
format: int64
example: 1711471533
description: The Unix timestamp (in seconds) of when the user was created
role:
type: string
example: owner
description: Always `owner`
required:
- object
- redacted_value
- name
- created_at
- last_used_at
- id
- owner
x-oaiMeta:
name: The admin API key object
example: |
{
"object": "organization.admin_api_key",
"id": "key_abc",
"name": "Main Admin Key",
"redacted_value": "sk-admin...xyz",
"created_at": 1711471533,
"last_used_at": 1711471534,
"owner": {
"type": "user",
"object": "organization.user",
"id": "user_123",
"name": "John Doe",
"created_at": 1711471533,
"role": "owner"
}
}
ApiKeyList:
type: object
properties:
object:
type: string
example: list
data:
type: array
items:
$ref: '#/components/schemas/AdminApiKey'
has_more:
type: boolean
example: false
first_id:
type: string
example: key_abc
last_id:
type: string
example: key_xyz
AssistantObject:
type: object
title: Assistant
description: Represents an `assistant` that can call the model and use tools.
properties:
id:
description: The identifier, which can be referenced in API endpoints.
type: string
object:
description: The object type, which is always `assistant`.
type: string
enum:
- assistant
x-stainless-const: true
created_at:
description: The Unix timestamp (in seconds) for when the assistant was created.
type: integer
name:
description: |
The name of the assistant. The maximum length is 256 characters.
type: string
maxLength: 256
nullable: true
description:
description: |
The description of the assistant. The maximum length is 512 characters.
type: string
maxLength: 512
nullable: true
model:
description: >
ID of the model to use. You can use the [List
models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your
available models, or see our [Model overview](https://platform.openai.com/docs/models) for
descriptions of them.
type: string
instructions:
description: |
The system instructions that the assistant uses. The maximum length is 256,000 characters.
type: string
maxLength: 256000
nullable: true
tools:
description: >
A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools
can be of types `code_interpreter`, `file_search`, or `function`.
default: []
type: array
maxItems: 128
items:
$ref: '#/components/schemas/AssistantTool'
tool_resources:
type: object
description: >
A set of resources that are used by the assistant's tools. The resources are specific to the type
of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the
`file_search` tool requires a list of vector store IDs.
properties:
code_interpreter:
type: object
properties:
file_ids:
type: array
description: >
A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available
to the `code_interpreter`` tool. There can be a maximum of 20 files associated with the
tool.
default: []
maxItems: 20
items:
type: string
file_search:
type: object
properties:
vector_store_ids:
type: array
description: >
The ID of the [vector
store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to
this assistant. There can be a maximum of 1 vector store attached to the assistant.
maxItems: 1
items:
type: string
nullable: true
metadata:
$ref: '#/components/schemas/Metadata'
temperature:
description: >
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
more random, while lower values like 0.2 will make it more focused and deterministic.
type: number
minimum: 0
maximum: 2
default: 1
example: 1
nullable: true
top_p:
type: number
minimum: 0
maximum: 1
default: 1
example: 1
nullable: true
description: >
An alternative to sampling with temperature, called nucleus sampling, where the model considers
the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
response_format:
$ref: '#/components/schemas/AssistantsApiResponseFormatOption'
nullable: true
required:
- id
- object
- created_at
- name
- description
- model
- instructions
- tools
- metadata
x-oaiMeta:
name: The assistant object
beta: true
example: |
{
"id": "asst_abc123",
"object": "assistant",
"created_at": 1698984975,
"name": "Math Tutor",
"description": null,
"model": "gpt-4o",
"instructions": "You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
"tools": [
{
"type": "code_interpreter"
}
],
"metadata": {},
"top_p": 1.0,
"temperature": 1.0,
"response_format": "auto"
}
AssistantStreamEvent:
description: >
Represents an event emitted when streaming a Run.
Each event in a server-sent events stream has an `event` and `data` property:
```
event: thread.created
data: {"id": "thread_123", "object": "thread", ...}
```
We emit events whenever a new object is created, transitions to a new state, or is being
streamed in parts (deltas). For example, we emit `thread.run.created` when a new run
is created, `thread.run.completed` when a run completes, and so on. When an Assistant chooses
to create a message during a run, we emit a `thread.message.created event`, a
`thread.message.in_progress` event, many `thread.message.delta` events, and finally a
`thread.message.completed` event.
We may add additional events over time, so we recommend handling unknown events gracefully
in your code. See the [Assistants API
quickstart](https://platform.openai.com/docs/assistants/overview) to learn how to
integrate the Assistants API with streaming.
x-oaiMeta:
name: Assistant stream events
beta: true
anyOf:
- $ref: '#/components/schemas/ThreadStreamEvent'
- $ref: '#/components/schemas/RunStreamEvent'
- $ref: '#/components/schemas/RunStepStreamEvent'
- $ref: '#/components/schemas/MessageStreamEvent'
- $ref: '#/components/schemas/ErrorEvent'
x-stainless-variantName: error_event
discriminator:
propertyName: event
AssistantSupportedModels:
type: string
enum:
- gpt-5
- gpt-5-mini
- gpt-5-nano
- gpt-5-2025-08-07
- gpt-5-mini-2025-08-07
- gpt-5-nano-2025-08-07
- gpt-4.1
- gpt-4.1-mini
- gpt-4.1-nano
- gpt-4.1-2025-04-14
- gpt-4.1-mini-2025-04-14
- gpt-4.1-nano-2025-04-14
- o3-mini
- o3-mini-2025-01-31
- o1
- o1-2024-12-17
- gpt-4o
- gpt-4o-2024-11-20
- gpt-4o-2024-08-06
- gpt-4o-2024-05-13
- gpt-4o-mini
- gpt-4o-mini-2024-07-18
- gpt-4.5-preview
- gpt-4.5-preview-2025-02-27
- gpt-4-turbo
- gpt-4-turbo-2024-04-09
- gpt-4-0125-preview
- gpt-4-turbo-preview
- gpt-4-1106-preview
- gpt-4-vision-preview
- gpt-4
- gpt-4-0314
- gpt-4-0613
- gpt-4-32k
- gpt-4-32k-0314
- gpt-4-32k-0613
- gpt-3.5-turbo
- gpt-3.5-turbo-16k
- gpt-3.5-turbo-0613
- gpt-3.5-turbo-1106
- gpt-3.5-turbo-0125
- gpt-3.5-turbo-16k-0613
AssistantToolsCode:
type: object
title: Code interpreter tool
properties:
type:
type: string
description: 'The type of tool being defined: `code_interpreter`'
enum:
- code_interpreter
x-stainless-const: true
required:
- type
AssistantToolsFileSearch:
type: object
title: FileSearch tool
properties:
type:
type: string
description: 'The type of tool being defined: `file_search`'
enum:
- file_search
x-stainless-const: true
file_search:
type: object
description: Overrides for the file search tool.
properties:
max_num_results:
type: integer
minimum: 1
maximum: 50
description: >
The maximum number of results the file search tool should output. The default is 20 for
`gpt-4*` models and 5 for `gpt-3.5-turbo`. This number should be between 1 and 50 inclusive.
Note that the file search tool may output fewer than `max_num_results` results. See the [file
search tool
documentation](https://platform.openai.com/docs/assistants/tools/file-search#customizing-file-search-settings)
for more information.
ranking_options:
$ref: '#/components/schemas/FileSearchRankingOptions'
required:
- type
AssistantToolsFileSearchTypeOnly:
type: object
title: FileSearch tool
properties:
type:
type: string
description: 'The type of tool being defined: `file_search`'
enum:
- file_search
x-stainless-const: true
required:
- type
AssistantToolsFunction:
type: object
title: Function tool
properties:
type:
type: string
description: 'The type of tool being defined: `function`'
enum:
- function
x-stainless-const: true
function:
$ref: '#/components/schemas/FunctionObject'
required:
- type
- function
AssistantsApiResponseFormatOption:
description: >
Specifies the format that the model must output. Compatible with
[GPT-4o](https://platform.openai.com/docs/models#gpt-4o), [GPT-4
Turbo](https://platform.openai.com/docs/models#gpt-4-turbo-and-gpt-4), and all GPT-3.5 Turbo models
since `gpt-3.5-turbo-1106`.
Setting to `{ "type": "json_schema", "json_schema": {...} }` enables Structured Outputs which ensures
the model will match your supplied JSON schema. Learn more in the [Structured Outputs
guide](https://platform.openai.com/docs/guides/structured-outputs).
Setting to `{ "type": "json_object" }` enables JSON mode, which ensures the message the model
generates is valid JSON.
**Important:** when using JSON mode, you **must** also instruct the model to produce JSON yourself via
a system or user message. Without this, the model may generate an unending stream of whitespace until
the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request.
Also note that the message content may be partially cut off if `finish_reason="length"`, which
indicates the generation exceeded `max_tokens` or the conversation exceeded the max context length.
anyOf:
- type: string
description: |
`auto` is the default value
enum:
- auto
x-stainless-const: true
- $ref: '#/components/schemas/ResponseFormatText'
- $ref: '#/components/schemas/ResponseFormatJsonObject'
- $ref: '#/components/schemas/ResponseFormatJsonSchema'
AssistantsApiToolChoiceOption:
description: >
Controls which (if any) tool is called by the model.
`none` means the model will not call any tools and instead generates a message.
`auto` is the default value and means the model can pick between generating a message or calling one
or more tools.
`required` means the model must call one or more tools before responding to the user.
Specifying a particular tool like `{"type": "file_search"}` or `{"type": "function", "function":
{"name": "my_function"}}` forces the model to call that tool.
anyOf:
- type: string
description: >
`none` means the model will not call any tools and instead generates a message. `auto` means the
model can pick between generating a message or calling one or more tools. `required` means the
model must call one or more tools before responding to the user.
enum:
- none
- auto
- required
title: Auto
- $ref: '#/components/schemas/AssistantsNamedToolChoice'
AssistantsNamedToolChoice:
type: object
description: Specifies a tool the model should use. Use to force the model to call a specific tool.
properties:
type:
type: string
enum:
- function
- code_interpreter
- file_search
description: The type of the tool. If type is `function`, the function name must be set
function:
type: object
properties:
name:
type: string
description: The name of the function to call.
required:
- name
required:
- type
AudioResponseFormat:
description: >
The format of the output, in one of these options: `json`, `text`, `srt`, `verbose_json`, or `vtt`.
For `gpt-4o-transcribe` and `gpt-4o-mini-transcribe`, the only supported format is `json`.
type: string
enum:
- json
- text
- srt
- verbose_json
- vtt
default: json
AuditLog:
type: object
description: A log of a user action or configuration change within this organization.
properties:
id:
type: string
description: The ID of this log.
type:
$ref: '#/components/schemas/AuditLogEventType'
effective_at:
type: integer
description: The Unix timestamp (in seconds) of the event.
project:
type: object
description: >-
The project that the action was scoped to. Absent for actions not scoped to projects. Note that
any admin actions taken via Admin API keys are associated with the default project.
properties:
id:
type: string
description: The project ID.
name:
type: string
description: The project title.
actor:
$ref: '#/components/schemas/AuditLogActor'
api_key.created:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The tracking ID of the API key.
data:
type: object
description: The payload used to create the API key.
properties:
scopes:
type: array
items:
type: string
description: A list of scopes allowed for the API key, e.g. `["api.model.request"]`
api_key.updated:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The tracking ID of the API key.
changes_requested:
type: object
description: The payload used to update the API key.
properties:
scopes:
type: array
items:
type: string
description: A list of scopes allowed for the API key, e.g. `["api.model.request"]`
api_key.deleted:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The tracking ID of the API key.
checkpoint_permission.created:
type: object
description: The project and fine-tuned model checkpoint that the checkpoint permission was created for.
properties:
id:
type: string
description: The ID of the checkpoint permission.
data:
type: object
description: The payload used to create the checkpoint permission.
properties:
project_id:
type: string
description: The ID of the project that the checkpoint permission was created for.
fine_tuned_model_checkpoint:
type: string
description: The ID of the fine-tuned model checkpoint.
checkpoint_permission.deleted:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The ID of the checkpoint permission.
invite.sent:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The ID of the invite.
data:
type: object
description: The payload used to create the invite.
properties:
email:
type: string
description: The email invited to the organization.
role:
type: string
description: The role the email was invited to be. Is either `owner` or `member`.
invite.accepted:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The ID of the invite.
invite.deleted:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The ID of the invite.
login.failed:
type: object
description: The details for events with this `type`.
properties:
error_code:
type: string
description: The error code of the failure.
error_message:
type: string
description: The error message of the failure.
logout.failed:
type: object
description: The details for events with this `type`.
properties:
error_code:
type: string
description: The error code of the failure.
error_message:
type: string
description: The error message of the failure.
organization.updated:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The organization ID.
changes_requested:
type: object
description: The payload used to update the organization settings.
properties:
title:
type: string
description: The organization title.
description:
type: string
description: The organization description.
name:
type: string
description: The organization name.
threads_ui_visibility:
type: string
description: >-
Visibility of the threads page which shows messages created with the Assistants API and
Playground. One of `ANY_ROLE`, `OWNERS`, or `NONE`.
usage_dashboard_visibility:
type: string
description: >-
Visibility of the usage dashboard which shows activity and costs for your organization.
One of `ANY_ROLE` or `OWNERS`.
api_call_logging:
type: string
description: >-
How your organization logs data from supported API calls. One of `disabled`,
`enabled_per_call`, `enabled_for_all_projects`, or `enabled_for_selected_projects`
api_call_logging_project_ids:
type: string
description: The list of project ids if api_call_logging is set to `enabled_for_selected_projects`
project.created:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The project ID.
data:
type: object
description: The payload used to create the project.
properties:
name:
type: string
description: The project name.
title:
type: string
description: The title of the project as seen on the dashboard.
project.updated:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The project ID.
changes_requested:
type: object
description: The payload used to update the project.
properties:
title:
type: string
description: The title of the project as seen on the dashboard.
project.archived:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The project ID.
rate_limit.updated:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The rate limit ID
changes_requested:
type: object
description: The payload used to update the rate limits.
properties:
max_requests_per_1_minute:
type: integer
description: The maximum requests per minute.
max_tokens_per_1_minute:
type: integer
description: The maximum tokens per minute.
max_images_per_1_minute:
type: integer
description: The maximum images per minute. Only relevant for certain models.
max_audio_megabytes_per_1_minute:
type: integer
description: The maximum audio megabytes per minute. Only relevant for certain models.
max_requests_per_1_day:
type: integer
description: The maximum requests per day. Only relevant for certain models.
batch_1_day_max_input_tokens:
type: integer
description: The maximum batch input tokens per day. Only relevant for certain models.
rate_limit.deleted:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The rate limit ID
service_account.created:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The service account ID.
data:
type: object
description: The payload used to create the service account.
properties:
role:
type: string
description: The role of the service account. Is either `owner` or `member`.
service_account.updated:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The service account ID.
changes_requested:
type: object
description: The payload used to updated the service account.
properties:
role:
type: string
description: The role of the service account. Is either `owner` or `member`.
service_account.deleted:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The service account ID.
user.added:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The user ID.
data:
type: object
description: The payload used to add the user to the project.
properties:
role:
type: string
description: The role of the user. Is either `owner` or `member`.
user.updated:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The project ID.
changes_requested:
type: object
description: The payload used to update the user.
properties:
role:
type: string
description: The role of the user. Is either `owner` or `member`.
user.deleted:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The user ID.
certificate.created:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The certificate ID.
name:
type: string
description: The name of the certificate.
certificate.updated:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The certificate ID.
name:
type: string
description: The name of the certificate.
certificate.deleted:
type: object
description: The details for events with this `type`.
properties:
id:
type: string
description: The certificate ID.
name:
type: string
description: The name of the certificate.
certificate:
type: string
description: The certificate content in PEM format.
certificates.activated:
type: object
description: The details for events with this `type`.
properties:
certificates:
type: array
items:
type: object
properties:
id:
type: string
description: The certificate ID.
name:
type: string
description: The name of the certificate.
certificates.deactivated:
type: object
description: The details for events with this `type`.
properties:
certificates:
type: array
items:
type: object
properties:
id:
type: string
description: The certificate ID.
name:
type: string
description: The name of the certificate.
required:
- id
- type
- effective_at
- actor
x-oaiMeta:
name: The audit log object
example: |
{
"id": "req_xxx_20240101",
"type": "api_key.created",
"effective_at": 1720804090,
"actor": {
"type": "session",
"session": {
"user": {
"id": "user-xxx",
"email": "user@example.com"
},
"ip_address": "127.0.0.1",
"user_agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
}
},
"api_key.created": {
"id": "key_xxxx",
"data": {
"scopes": ["resource.operation"]
}
}
}
AuditLogActor:
type: object
description: The actor who performed the audit logged action.
properties:
type:
type: string
description: The type of actor. Is either `session` or `api_key`.
enum:
- session
- api_key
session:
$ref: '#/components/schemas/AuditLogActorSession'
api_key:
$ref: '#/components/schemas/AuditLogActorApiKey'
AuditLogActorApiKey:
type: object
description: The API Key used to perform the audit logged action.
properties:
id:
type: string
description: The tracking id of the API key.
type:
type: string
description: The type of API key. Can be either `user` or `service_account`.
enum:
- user
- service_account
user:
$ref: '#/components/schemas/AuditLogActorUser'
service_account:
$ref: '#/components/schemas/AuditLogActorServiceAccount'
AuditLogActorServiceAccount:
type: object
description: The service account that performed the audit logged action.
properties:
id:
type: string
description: The service account id.
AuditLogActorSession:
type: object
description: The session in which the audit logged action was performed.
properties:
user:
$ref: '#/components/schemas/AuditLogActorUser'
ip_address:
type: string
description: The IP address from which the action was performed.
AuditLogActorUser:
type: object
description: The user who performed the audit logged action.
properties:
id:
type: string
description: The user id.
email:
type: string
description: The user email.
AuditLogEventType:
type: string
description: The event type.
enum:
- api_key.created
- api_key.updated
- api_key.deleted
- checkpoint_permission.created
- checkpoint_permission.deleted
- invite.sent
- invite.accepted
- invite.deleted
- login.succeeded
- login.failed
- logout.succeeded
- logout.failed
- organization.updated
- project.created
- project.updated
- project.archived
- service_account.created
- service_account.updated
- service_account.deleted
- rate_limit.updated
- rate_limit.deleted
- user.added
- user.updated
- user.deleted
AutoChunkingStrategyRequestParam:
type: object
title: Auto Chunking Strategy
description: >-
The default strategy. This strategy currently uses a `max_chunk_size_tokens` of `800` and
`chunk_overlap_tokens` of `400`.
additionalProperties: false
properties:
type:
type: string
description: Always `auto`.
enum:
- auto
x-stainless-const: true
required:
- type
Batch:
type: object
properties:
id:
type: string
object:
type: string
enum:
- batch
description: The object type, which is always `batch`.
x-stainless-const: true
endpoint:
type: string
description: The OpenAI API endpoint used by the batch.
errors:
type: object
properties:
object:
type: string
description: The object type, which is always `list`.
data:
type: array
items:
$ref: '#/components/schemas/BatchError'
input_file_id:
type: string
description: The ID of the input file for the batch.
completion_window:
type: string
description: The time frame within which the batch should be processed.
status:
type: string
description: The current status of the batch.
enum:
- validating
- failed
- in_progress
- finalizing
- completed
- expired
- cancelling
- cancelled
output_file_id:
type: string
description: The ID of the file containing the outputs of successfully executed requests.
error_file_id:
type: string
description: The ID of the file containing the outputs of requests with errors.
created_at:
type: integer
description: The Unix timestamp (in seconds) for when the batch was created.
in_progress_at:
type: integer
description: The Unix timestamp (in seconds) for when the batch started processing.
expires_at:
type: integer
description: The Unix timestamp (in seconds) for when the batch will expire.
finalizing_at:
type: integer
description: The Unix timestamp (in seconds) for when the batch started finalizing.
completed_at:
type: integer
description: The Unix timestamp (in seconds) for when the batch was completed.
failed_at:
type: integer
description: The Unix timestamp (in seconds) for when the batch failed.
expired_at:
type: integer
description: The Unix timestamp (in seconds) for when the batch expired.
cancelling_at:
type: integer
description: The Unix timestamp (in seconds) for when the batch started cancelling.
cancelled_at:
type: integer
description: The Unix timestamp (in seconds) for when the batch was cancelled.
request_counts:
$ref: '#/components/schemas/BatchRequestCounts'
metadata:
$ref: '#/components/schemas/Metadata'
required:
- id
- object
- endpoint
- input_file_id
- completion_window
- status
- created_at
x-oaiMeta:
name: The batch object
example: |
{
"id": "batch_abc123",
"object": "batch",
"endpoint": "/v1/completions",
"errors": null,
"input_file_id": "file-abc123",
"completion_window": "24h",
"status": "completed",
"output_file_id": "file-cvaTdG",
"error_file_id": "file-HOWS94",
"created_at": 1711471533,
"in_progress_at": 1711471538,
"expires_at": 1711557933,
"finalizing_at": 1711493133,
"completed_at": 1711493163,
"failed_at": null,
"expired_at": null,
"cancelling_at": null,
"cancelled_at": null,
"request_counts": {
"total": 100,
"completed": 95,
"failed": 5
},
"metadata": {
"customer_id": "user_123456789",
"batch_description": "Nightly eval job",
}
}
BatchFileExpirationAfter:
type: object
title: File expiration policy
description: The expiration policy for the output and/or error file that are generated for a batch.
properties:
anchor:
description: >-
Anchor timestamp after which the expiration policy applies. Supported anchors: `created_at`. Note
that the anchor is the file creation time, not the time the batch is created.
type: string
enum:
- created_at
x-stainless-const: true
seconds:
description: >-
The number of seconds after the anchor time that the file will expire. Must be between 3600 (1
hour) and 2592000 (30 days).
type: integer
minimum: 3600
maximum: 2592000
required:
- anchor
- seconds
BatchRequestInput:
type: object
description: The per-line object of the batch input file
properties:
custom_id:
type: string
description: >-
A developer-provided per-request id that will be used to match outputs to inputs. Must be unique
for each request in a batch.
method:
type: string
enum:
- POST
description: The HTTP method to be used for the request. Currently only `POST` is supported.
x-stainless-const: true
url:
type: string
description: >-
The OpenAI API relative URL to be used for the request. Currently `/v1/chat/completions`,
`/v1/embeddings`, and `/v1/completions` are supported.
x-oaiMeta:
name: The request input object
example: >
{"custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": {"model":
"gpt-4o-mini", "messages": [{"role": "system", "content": "You are a helpful assistant."}, {"role":
"user", "content": "What is 2+2?"}]}}
BatchRequestOutput:
type: object
description: The per-line object of the batch output and error files
properties:
id:
type: string
custom_id:
type: string
description: A developer-provided per-request id that will be used to match outputs to inputs.
response:
type: object
nullable: true
properties:
status_code:
type: integer
description: The HTTP status code of the response
request_id:
type: string
description: >-
An unique identifier for the OpenAI API request. Please include this request ID when
contacting support.
body:
type: object
x-oaiTypeLabel: map
description: The JSON body of the response
error:
type: object
nullable: true
description: >-
For requests that failed with a non-HTTP error, this will contain more information on the cause of
the failure.
properties:
code:
type: string
description: A machine-readable error code.
message:
type: string
description: A human-readable error message.
x-oaiMeta:
name: The request output object
example: >
{"id": "batch_req_wnaDys", "custom_id": "request-2", "response": {"status_code": 200, "request_id":
"req_c187b3", "body": {"id": "chatcmpl-9758Iw", "object": "chat.completion", "created": 1711475054,
"model": "gpt-4o-mini", "choices": [{"index": 0, "message": {"role": "assistant", "content": "2 + 2
equals 4."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 24, "completion_tokens": 15,
"total_tokens": 39}, "system_fingerprint": null}}, "error": null}
Certificate:
type: object
description: Represents an individual `certificate` uploaded to the organization.
properties:
object:
type: string
enum:
- certificate
- organization.certificate
- organization.project.certificate
description: >
The object type.
- If creating, updating, or getting a specific certificate, the object type is `certificate`.
- If listing, activating, or deactivating certificates for the organization, the object type is
`organization.certificate`.
- If listing, activating, or deactivating certificates for a project, the object type is
`organization.project.certificate`.
x-stainless-const: true
id:
type: string
description: The identifier, which can be referenced in API endpoints
name:
type: string
description: The name of the certificate.
created_at:
type: integer
description: The Unix timestamp (in seconds) of when the certificate was uploaded.
certificate_details:
type: object
properties:
valid_at:
type: integer
description: The Unix timestamp (in seconds) of when the certificate becomes valid.
expires_at:
type: integer
description: The Unix timestamp (in seconds) of when the certificate expires.
content:
type: string
description: The content of the certificate in PEM format.
active:
type: boolean
description: >-
Whether the certificate is currently active at the specified scope. Not returned when getting
details for a specific certificate.
required:
- object
- id
- name
- created_at
- certificate_details
x-oaiMeta:
name: The certificate object
example: |
{
"object": "certificate",
"id": "cert_abc",
"name": "My Certificate",
"created_at": 1234567,
"certificate_details": {
"valid_at": 1234567,
"expires_at": 12345678,
"content": "-----BEGIN CERTIFICATE----- MIIGAjCCA...6znFlOW+ -----END CERTIFICATE-----"
}
}
ChatCompletionAllowedTools:
type: object
title: Allowed tools
description: |
Constrains the tools available to the model to a pre-defined set.
properties:
mode:
type: string
enum:
- auto
- required
description: |
Constrains the tools available to the model to a pre-defined set.
`auto` allows the model to pick from among the allowed tools and generate a
message.
`required` requires the model to call one or more of the allowed tools.
tools:
type: array
description: |
A list of tool definitions that the model should be allowed to call.
For the Chat Completions API, the list of tool definitions might look like:
```json
[
{ "type": "function", "function": { "name": "get_weather" } },
{ "type": "function", "function": { "name": "get_time" } }
]
```
items:
type: object
x-oaiExpandable: false
description: |
A tool definition that the model should be allowed to call.
additionalProperties: true
required:
- mode
- tools
ChatCompletionAllowedToolsChoice:
type: object
title: Allowed tools
description: |
Constrains the tools available to the model to a pre-defined set.
properties:
type:
type: string
enum:
- allowed_tools
description: Allowed tool configuration type. Always `allowed_tools`.
x-stainless-const: true
allowed_tools:
$ref: '#/components/schemas/ChatCompletionAllowedTools'
required:
- type
- allowed_tools
ChatCompletionDeleted:
type: object
properties:
object:
type: string
description: The type of object being deleted.
enum:
- chat.completion.deleted
x-stainless-const: true
id:
type: string
description: The ID of the chat completion that was deleted.
deleted:
type: boolean
description: Whether the chat completion was deleted.
required:
- object
- id
- deleted
ChatCompletionFunctionCallOption:
type: object
description: |
Specifying a particular function via `{"name": "my_function"}` forces the model to call that function.
properties:
name:
type: string
description: The name of the function to call.
required:
- name
x-stainless-variantName: function_call_option
ChatCompletionFunctions:
type: object
deprecated: true
properties:
description:
type: string
description: >-
A description of what the function does, used by the model to choose when and how to call the
function.
name:
type: string
description: >-
The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes,
with a maximum length of 64.
parameters:
$ref: '#/components/schemas/FunctionParameters'
required:
- name
ChatCompletionList:
type: object
title: ChatCompletionList
description: |
An object representing a list of Chat Completions.
properties:
object:
type: string
enum:
- list
default: list
description: |
The type of this object. It is always set to "list".
x-stainless-const: true
data:
type: array
description: |
An array of chat completion objects.
items:
$ref: '#/components/schemas/CreateChatCompletionResponse'
first_id:
type: string
description: The identifier of the first chat completion in the data array.
last_id:
type: string
description: The identifier of the last chat completion in the data array.
has_more:
type: boolean
description: Indicates whether there are more Chat Completions available.
required:
- object
- data
- first_id
- last_id
- has_more
x-oaiMeta:
name: The chat completion list object
group: chat
example: |
{
"object": "list",
"data": [
{
"object": "chat.completion",
"id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
"model": "gpt-4o-2024-08-06",
"created": 1738960610,
"request_id": "req_ded8ab984ec4bf840f37566c1011c417",
"tool_choice": null,
"usage": {
"total_tokens": 31,
"completion_tokens": 18,
"prompt_tokens": 13
},
"seed": 4944116822809979520,
"top_p": 1.0,
"temperature": 1.0,
"presence_penalty": 0.0,
"frequency_penalty": 0.0,
"system_fingerprint": "fp_50cad350e4",
"input_user": null,
"service_tier": "default",
"tools": null,
"metadata": {},
"choices": [
{
"index": 0,
"message": {
"content": "Mind of circuits hum, \nLearning patterns in silence— \nFuture's quiet spark.",
"role": "assistant",
"tool_calls": null,
"function_call": null
},
"finish_reason": "stop",
"logprobs": null
}
],
"response_format": null
}
],
"first_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
"last_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
"has_more": false
}
ChatCompletionMessageCustomToolCall:
type: object
title: Custom tool call
description: |
A call to a custom tool created by the model.
properties:
id:
type: string
description: The ID of the tool call.
type:
type: string
enum:
- custom
description: The type of the tool. Always `custom`.
x-stainless-const: true
custom:
type: object
description: The custom tool that the model called.
properties:
name:
type: string
description: The name of the custom tool to call.
input:
type: string
description: The input for the custom tool call generated by the model.
required:
- name
- input
required:
- id
- type
- custom
ChatCompletionMessageList:
type: object
title: ChatCompletionMessageList
description: |
An object representing a list of chat completion messages.
properties:
object:
type: string
enum:
- list
default: list
description: |
The type of this object. It is always set to "list".
x-stainless-const: true
data:
type: array
description: |
An array of chat completion message objects.
items:
allOf:
- $ref: '#/components/schemas/ChatCompletionResponseMessage'
- type: object
required:
- id
properties:
id:
type: string
description: The identifier of the chat message.
content_parts:
type: array
nullable: true
description: >
If a content parts array was provided, this is an array of `text` and `image_url`
parts.
Otherwise, null.
items:
anyOf:
- $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
- $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartImage'
first_id:
type: string
description: The identifier of the first chat message in the data array.
last_id:
type: string
description: The identifier of the last chat message in the data array.
has_more:
type: boolean
description: Indicates whether there are more chat messages available.
required:
- object
- data
- first_id
- last_id
- has_more
x-oaiMeta:
name: The chat completion message list object
group: chat
example: |
{
"object": "list",
"data": [
{
"id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
"role": "user",
"content": "write a haiku about ai",
"name": null,
"content_parts": null
}
],
"first_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
"last_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
"has_more": false
}
ChatCompletionMessageToolCall:
type: object
title: Function tool call
description: |
A call to a function tool created by the model.
properties:
id:
type: string
description: The ID of the tool call.
type:
type: string
enum:
- function
description: The type of the tool. Currently, only `function` is supported.
x-stainless-const: true
function:
type: object
description: The function that the model called.
properties:
name:
type: string
description: The name of the function to call.
arguments:
type: string
description: >-
The arguments to call the function with, as generated by the model in JSON format. Note that
the model does not always generate valid JSON, and may hallucinate parameters not defined by
your function schema. Validate the arguments in your code before calling your function.
required:
- name
- arguments
required:
- id
- type
- function
ChatCompletionMessageToolCallChunk:
type: object
properties:
index:
type: integer
id:
type: string
description: The ID of the tool call.
type:
type: string
enum:
- function
description: The type of the tool. Currently, only `function` is supported.
x-stainless-const: true
function:
type: object
properties:
name:
type: string
description: The name of the function to call.
arguments:
type: string
description: >-
The arguments to call the function with, as generated by the model in JSON format. Note that
the model does not always generate valid JSON, and may hallucinate parameters not defined by
your function schema. Validate the arguments in your code before calling your function.
required:
- index
ChatCompletionMessageToolCalls:
type: array
description: The tool calls generated by the model, such as function calls.
items:
anyOf:
- $ref: '#/components/schemas/ChatCompletionMessageToolCall'
- $ref: '#/components/schemas/ChatCompletionMessageCustomToolCall'
x-stainless-naming:
python:
model_name: chat_completion_message_tool_call_union
param_model_name: chat_completion_message_tool_call_union_param
discriminator:
propertyName: type
x-stainless-go-variant-constructor: skip
ChatCompletionModalities:
type: array
nullable: true
description: >
Output types that you would like the model to generate for this request.
Most models are capable of generating text, which is the default:
`["text"]`
The `gpt-4o-audio-preview` model can also be used to [generate
audio](https://platform.openai.com/docs/guides/audio). To
request that this model generate both text and audio responses, you can
use:
`["text", "audio"]`
items:
type: string
enum:
- text
- audio
ChatCompletionNamedToolChoice:
type: object
title: Function tool choice
description: Specifies a tool the model should use. Use to force the model to call a specific function.
properties:
type:
type: string
enum:
- function
description: For function calling, the type is always `function`.
x-stainless-const: true
function:
type: object
properties:
name:
type: string
description: The name of the function to call.
required:
- name
required:
- type
- function
ChatCompletionNamedToolChoiceCustom:
type: object
title: Custom tool choice
description: Specifies a tool the model should use. Use to force the model to call a specific custom tool.
properties:
type:
type: string
enum:
- custom
description: For custom tool calling, the type is always `custom`.
x-stainless-const: true
custom:
type: object
properties:
name:
type: string
description: The name of the custom tool to call.
required:
- name
required:
- type
- custom
ChatCompletionRequestAssistantMessage:
type: object
title: Assistant message
description: |
Messages sent by the model in response to user messages.
properties:
content:
nullable: true
description: >
The contents of the assistant message. Required unless `tool_calls` or `function_call` is
specified.
anyOf:
- type: string
description: The contents of the assistant message.
title: Text content
- type: array
description: >-
An array of content parts with a defined type. Can be one or more of type `text`, or exactly
one of type `refusal`.
title: Array of content parts
items:
$ref: '#/components/schemas/ChatCompletionRequestAssistantMessageContentPart'
minItems: 1
refusal:
nullable: true
type: string
description: The refusal message by the assistant.
role:
type: string
enum:
- assistant
description: The role of the messages author, in this case `assistant`.
x-stainless-const: true
name:
type: string
description: >-
An optional name for the participant. Provides the model information to differentiate between
participants of the same role.
audio:
type: object
nullable: true
description: |
Data about a previous audio response from the model.
[Learn more](https://platform.openai.com/docs/guides/audio).
required:
- id
properties:
id:
type: string
description: |
Unique identifier for a previous audio response from the model.
tool_calls:
$ref: '#/components/schemas/ChatCompletionMessageToolCalls'
function_call:
type: object
deprecated: true
description: >-
Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be
called, as generated by the model.
nullable: true
properties:
arguments:
type: string
description: >-
The arguments to call the function with, as generated by the model in JSON format. Note that
the model does not always generate valid JSON, and may hallucinate parameters not defined by
your function schema. Validate the arguments in your code before calling your function.
name:
type: string
description: The name of the function to call.
required:
- arguments
- name
required:
- role
x-stainless-soft-required:
- content
ChatCompletionRequestAssistantMessageContentPart:
anyOf:
- $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
- $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartRefusal'
discriminator:
propertyName: type
ChatCompletionRequestDeveloperMessage:
type: object
title: Developer message
description: |
Developer-provided instructions that the model should follow, regardless of
messages sent by the user. With o1 models and newer, `developer` messages
replace the previous `system` messages.
properties:
content:
description: The contents of the developer message.
anyOf:
- type: string
description: The contents of the developer message.
title: Text content
- type: array
description: >-
An array of content parts with a defined type. For developer messages, only type `text` is
supported.
title: Array of content parts
items:
$ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
minItems: 1
role:
type: string
enum:
- developer
description: The role of the messages author, in this case `developer`.
x-stainless-const: true
name:
type: string
description: >-
An optional name for the participant. Provides the model information to differentiate between
participants of the same role.
required:
- content
- role
x-stainless-naming:
go:
variant_constructor: DeveloperMessage
ChatCompletionRequestFunctionMessage:
type: object
title: Function message
deprecated: true
properties:
role:
type: string
enum:
- function
description: The role of the messages author, in this case `function`.
x-stainless-const: true
content:
nullable: true
type: string
description: The contents of the function message.
name:
type: string
description: The name of the function to call.
required:
- role
- content
- name
ChatCompletionRequestMessage:
anyOf:
- $ref: '#/components/schemas/ChatCompletionRequestDeveloperMessage'
- $ref: '#/components/schemas/ChatCompletionRequestSystemMessage'
- $ref: '#/components/schemas/ChatCompletionRequestUserMessage'
- $ref: '#/components/schemas/ChatCompletionRequestAssistantMessage'
- $ref: '#/components/schemas/ChatCompletionRequestToolMessage'
- $ref: '#/components/schemas/ChatCompletionRequestFunctionMessage'
discriminator:
propertyName: role
ChatCompletionRequestMessageContentPartAudio:
type: object
title: Audio content part
description: |
Learn about [audio inputs](https://platform.openai.com/docs/guides/audio).
properties:
type:
type: string
enum:
- input_audio
description: The type of the content part. Always `input_audio`.
x-stainless-const: true
input_audio:
type: object
properties:
data:
type: string
description: Base64 encoded audio data.
format:
type: string
enum:
- wav
- mp3
description: |
The format of the encoded audio data. Currently supports "wav" and "mp3".
required:
- data
- format
required:
- type
- input_audio
x-stainless-naming:
go:
variant_constructor: InputAudioContentPart
ChatCompletionRequestMessageContentPartFile:
type: object
title: File content part
description: |
Learn about [file inputs](https://platform.openai.com/docs/guides/text) for text generation.
properties:
type:
type: string
enum:
- file
description: The type of the content part. Always `file`.
x-stainless-const: true
file:
type: object
properties:
filename:
type: string
description: |
The name of the file, used when passing the file to the model as a
string.
file_data:
type: string
description: |
The base64 encoded file data, used when passing the file to the model
as a string.
file_id:
type: string
description: |
The ID of an uploaded file to use as input.
x-stainless-naming:
java:
type_name: FileObject
kotlin:
type_name: FileObject
required:
- type
- file
x-stainless-naming:
go:
variant_constructor: FileContentPart
ChatCompletionRequestMessageContentPartImage:
type: object
title: Image content part
description: |
Learn about [image inputs](https://platform.openai.com/docs/guides/vision).
properties:
type:
type: string
enum:
- image_url
description: The type of the content part.
x-stainless-const: true
image_url:
type: object
properties:
url:
type: string
description: Either a URL of the image or the base64 encoded image data.
format: uri
detail:
type: string
description: >-
Specifies the detail level of the image. Learn more in the [Vision
guide](https://platform.openai.com/docs/guides/vision#low-or-high-fidelity-image-understanding).
enum:
- auto
- low
- high
default: auto
required:
- url
required:
- type
- image_url
x-stainless-naming:
go:
variant_constructor: ImageContentPart
ChatCompletionRequestMessageContentPartRefusal:
type: object
title: Refusal content part
properties:
type:
type: string
enum:
- refusal
description: The type of the content part.
x-stainless-const: true
refusal:
type: string
description: The refusal message generated by the model.
required:
- type
- refusal
ChatCompletionRequestMessageContentPartText:
type: object
title: Text content part
description: |
Learn about [text inputs](https://platform.openai.com/docs/guides/text-generation).
properties:
type:
type: string
enum:
- text
description: The type of the content part.
x-stainless-const: true
text:
type: string
description: The text content.
required:
- type
- text
x-stainless-naming:
go:
variant_constructor: TextContentPart
ChatCompletionRequestSystemMessage:
type: object
title: System message
description: |
Developer-provided instructions that the model should follow, regardless of
messages sent by the user. With o1 models and newer, use `developer` messages
for this purpose instead.
properties:
content:
description: The contents of the system message.
anyOf:
- type: string
description: The contents of the system message.
title: Text content
- type: array
description: >-
An array of content parts with a defined type. For system messages, only type `text` is
supported.
title: Array of content parts
items:
$ref: '#/components/schemas/ChatCompletionRequestSystemMessageContentPart'
minItems: 1
role:
type: string
enum:
- system
description: The role of the messages author, in this case `system`.
x-stainless-const: true
name:
type: string
description: >-
An optional name for the participant. Provides the model information to differentiate between
participants of the same role.
required:
- content
- role
x-stainless-naming:
go:
variant_constructor: SystemMessage
ChatCompletionRequestSystemMessageContentPart:
anyOf:
- $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
ChatCompletionRequestToolMessage:
type: object
title: Tool message
properties:
role:
type: string
enum:
- tool
description: The role of the messages author, in this case `tool`.
x-stainless-const: true
content:
description: The contents of the tool message.
anyOf:
- type: string
description: The contents of the tool message.
title: Text content
- type: array
description: >-
An array of content parts with a defined type. For tool messages, only type `text` is
supported.
title: Array of content parts
items:
$ref: '#/components/schemas/ChatCompletionRequestToolMessageContentPart'
minItems: 1
tool_call_id:
type: string
description: Tool call that this message is responding to.
required:
- role
- content
- tool_call_id
x-stainless-naming:
go:
variant_constructor: ToolMessage
ChatCompletionRequestToolMessageContentPart:
anyOf:
- $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
ChatCompletionRequestUserMessage:
type: object
title: User message
description: |
Messages sent by an end user, containing prompts or additional context
information.
properties:
content:
description: |
The contents of the user message.
anyOf:
- type: string
description: The text contents of the message.
title: Text content
- type: array
description: >-
An array of content parts with a defined type. Supported options differ based on the
[model](https://platform.openai.com/docs/models) being used to generate the response. Can
contain text, image, or audio inputs.
title: Array of content parts
items:
$ref: '#/components/schemas/ChatCompletionRequestUserMessageContentPart'
minItems: 1
role:
type: string
enum:
- user
description: The role of the messages author, in this case `user`.
x-stainless-const: true
name:
type: string
description: >-
An optional name for the participant. Provides the model information to differentiate between
participants of the same role.
required:
- content
- role
x-stainless-naming:
go:
variant_constructor: UserMessage
ChatCompletionRequestUserMessageContentPart:
anyOf:
- $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
- $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartImage'
- $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartAudio'
- $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartFile'
discriminator:
propertyName: type
ChatCompletionResponseMessage:
type: object
description: A chat completion message generated by the model.
properties:
content:
type: string
description: The contents of the message.
nullable: true
refusal:
type: string
description: The refusal message generated by the model.
nullable: true
tool_calls:
$ref: '#/components/schemas/ChatCompletionMessageToolCalls'
annotations:
type: array
description: |
Annotations for the message, when applicable, as when using the
[web search tool](https://platform.openai.com/docs/guides/tools-web-search?api-mode=chat).
items:
type: object
description: |
A URL citation when using web search.
required:
- type
- url_citation
properties:
type:
type: string
description: The type of the URL citation. Always `url_citation`.
enum:
- url_citation
x-stainless-const: true
url_citation:
type: object
description: A URL citation when using web search.
required:
- end_index
- start_index
- url
- title
properties:
end_index:
type: integer
description: The index of the last character of the URL citation in the message.
start_index:
type: integer
description: The index of the first character of the URL citation in the message.
url:
type: string
description: The URL of the web resource.
title:
type: string
description: The title of the web resource.
role:
type: string
enum:
- assistant
description: The role of the author of this message.
x-stainless-const: true
function_call:
type: object
deprecated: true
description: >-
Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be
called, as generated by the model.
properties:
arguments:
type: string
description: >-
The arguments to call the function with, as generated by the model in JSON format. Note that
the model does not always generate valid JSON, and may hallucinate parameters not defined by
your function schema. Validate the arguments in your code before calling your function.
name:
type: string
description: The name of the function to call.
required:
- name
- arguments
audio:
type: object
nullable: true
description: >
If the audio output modality is requested, this object contains data
about the audio response from the model. [Learn
more](https://platform.openai.com/docs/guides/audio).
required:
- id
- expires_at
- data
- transcript
properties:
id:
type: string
description: Unique identifier for this audio response.
expires_at:
type: integer
description: |
The Unix timestamp (in seconds) for when this audio response will
no longer be accessible on the server for use in multi-turn
conversations.
data:
type: string
description: |
Base64 encoded audio bytes generated by the model, in the format
specified in the request.
transcript:
type: string
description: Transcript of the audio generated by the model.
required:
- role
- content
- refusal
ChatCompletionRole:
type: string
description: The role of the author of a message
enum:
- developer
- system
- user
- assistant
- tool
- function
ChatCompletionStreamOptions:
description: |
Options for streaming response. Only set this when you set `stream: true`.
type: object
nullable: true
default: null
properties:
include_usage:
type: boolean
description: |
If set, an additional chunk will be streamed before the `data: [DONE]`
message. The `usage` field on this chunk shows the token usage statistics
for the entire request, and the `choices` field will always be an empty
array.
All other chunks will also include a `usage` field, but with a null
value. **NOTE:** If the stream is interrupted, you may not receive the
final usage chunk which contains the total token usage for the request.
include_obfuscation:
type: boolean
description: |
When true, stream obfuscation will be enabled. Stream obfuscation adds
random characters to an `obfuscation` field on streaming delta events to
normalize payload sizes as a mitigation to certain side-channel attacks.
These obfuscation fields are included by default, but add a small amount
of overhead to the data stream. You can set `include_obfuscation` to
false to optimize for bandwidth if you trust the network links between
your application and the OpenAI API.
ChatCompletionStreamResponseDelta:
type: object
description: A chat completion delta generated by streamed model responses.
properties:
content:
type: string
description: The contents of the chunk message.
nullable: true
function_call:
deprecated: true
type: object
description: >-
Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be
called, as generated by the model.
properties:
arguments:
type: string
description: >-
The arguments to call the function with, as generated by the model in JSON format. Note that
the model does not always generate valid JSON, and may hallucinate parameters not defined by
your function schema. Validate the arguments in your code before calling your function.
name:
type: string
description: The name of the function to call.
tool_calls:
type: array
items:
$ref: '#/components/schemas/ChatCompletionMessageToolCallChunk'
role:
type: string
enum:
- developer
- system
- user
- assistant
- tool
description: The role of the author of this message.
refusal:
type: string
description: The refusal message generated by the model.
nullable: true
ChatCompletionTokenLogprob:
type: object
properties:
token:
description: The token.
type: string
logprob:
description: >-
The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the
value `-9999.0` is used to signify that the token is very unlikely.
type: number
bytes:
description: >-
A list of integers representing the UTF-8 bytes representation of the token. Useful in instances
where characters are represented by multiple tokens and their byte representations must be
combined to generate the correct text representation. Can be `null` if there is no bytes
representation for the token.
type: array
items:
type: integer
nullable: true
top_logprobs:
description: >-
List of the most likely tokens and their log probability, at this token position. In rare cases,
there may be fewer than the number of requested `top_logprobs` returned.
type: array
items:
type: object
properties:
token:
description: The token.
type: string
logprob:
description: >-
The log probability of this token, if it is within the top 20 most likely tokens. Otherwise,
the value `-9999.0` is used to signify that the token is very unlikely.
type: number
bytes:
description: >-
A list of integers representing the UTF-8 bytes representation of the token. Useful in
instances where characters are represented by multiple tokens and their byte representations
must be combined to generate the correct text representation. Can be `null` if there is no
bytes representation for the token.
type: array
items:
type: integer
nullable: true
required:
- token
- logprob
- bytes
required:
- token
- logprob
- bytes
- top_logprobs
ChatCompletionTool:
type: object
title: Function tool
description: |
A function tool that can be used to generate a response.
properties:
type:
type: string
enum:
- function
description: The type of the tool. Currently, only `function` is supported.
x-stainless-const: true
function:
$ref: '#/components/schemas/FunctionObject'
required:
- type
- function
ChatCompletionToolChoiceOption:
description: >
Controls which (if any) tool is called by the model.
`none` means the model will not call any tool and instead generates a message.
`auto` means the model can pick between generating a message or calling one or more tools.
`required` means the model must call one or more tools.
Specifying a particular tool via `{"type": "function", "function": {"name": "my_function"}}` forces
the model to call that tool.
`none` is the default when no tools are present. `auto` is the default if tools are present.
anyOf:
- type: string
title: Auto
description: >
`none` means the model will not call any tool and instead generates a message. `auto` means the
model can pick between generating a message or calling one or more tools. `required` means the
model must call one or more tools.
enum:
- none
- auto
- required
- $ref: '#/components/schemas/ChatCompletionAllowedToolsChoice'
- $ref: '#/components/schemas/ChatCompletionNamedToolChoice'
- $ref: '#/components/schemas/ChatCompletionNamedToolChoiceCustom'
x-stainless-go-variant-constructor:
naming: tool_choice_option_{variant}
ChunkingStrategyRequestParam:
type: object
description: >-
The chunking strategy used to chunk the file(s). If not set, will use the `auto` strategy. Only
applicable if `file_ids` is non-empty.
anyOf:
- $ref: '#/components/schemas/AutoChunkingStrategyRequestParam'
- $ref: '#/components/schemas/StaticChunkingStrategyRequestParam'
discriminator:
propertyName: type
Click:
type: object
title: Click
description: |
A click action.
properties:
type:
type: string
enum:
- click
default: click
description: |
Specifies the event type. For a click action, this property is
always set to `click`.
x-stainless-const: true
button:
type: string
enum:
- left
- right
- wheel
- back
- forward
description: >
Indicates which mouse button was pressed during the click. One of `left`, `right`, `wheel`,
`back`, or `forward`.
x:
type: integer
description: |
The x-coordinate where the click occurred.
'y':
type: integer
description: |
The y-coordinate where the click occurred.
required:
- type
- button
- x
- 'y'
CodeInterpreterFileOutput:
type: object
title: Code interpreter file output
description: |
The output of a code interpreter tool call that is a file.
properties:
type:
type: string
enum:
- files
description: |
The type of the code interpreter file output. Always `files`.
x-stainless-const: true
files:
type: array
items:
type: object
properties:
mime_type:
type: string
description: |
The MIME type of the file.
file_id:
type: string
description: |
The ID of the file.
required:
- mime_type
- file_id
required:
- type
- files
CodeInterpreterOutputImage:
type: object
title: Code interpreter output image
description: |
The image output from the code interpreter.
properties:
type:
type: string
enum:
- image
default: image
x-stainless-const: true
description: The type of the output. Always 'image'.
url:
type: string
description: The URL of the image output from the code interpreter.
required:
- type
- url
CodeInterpreterOutputLogs:
type: object
title: Code interpreter output logs
description: |
The logs output from the code interpreter.
properties:
type:
type: string
enum:
- logs
default: logs
x-stainless-const: true
description: The type of the output. Always 'logs'.
logs:
type: string
description: The logs output from the code interpreter.
required:
- type
- logs
CodeInterpreterTextOutput:
type: object
title: Code interpreter text output
description: |
The output of a code interpreter tool call that is text.
properties:
type:
type: string
enum:
- logs
description: |
The type of the code interpreter text output. Always `logs`.
x-stainless-const: true
logs:
type: string
description: |
The logs of the code interpreter tool call.
required:
- type
- logs
CodeInterpreterTool:
type: object
title: Code interpreter
description: |
A tool that runs Python code to help generate a response to a prompt.
properties:
type:
type: string
enum:
- code_interpreter
description: |
The type of the code interpreter tool. Always `code_interpreter`.
x-stainless-const: true
container:
description: |
The code interpreter container. Can be a container ID or an object that
specifies uploaded file IDs to make available to your code.
anyOf:
- type: string
description: The container ID.
- $ref: '#/components/schemas/CodeInterpreterToolAuto'
required:
- type
- container
CodeInterpreterToolAuto:
type: object
title: CodeInterpreterContainerAuto
description: |
Configuration for a code interpreter container. Optionally specify the IDs
of the files to run the code on.
required:
- type
properties:
type:
type: string
enum:
- auto
description: Always `auto`.
x-stainless-const: true
file_ids:
type: array
items:
type: string
description: |
An optional list of uploaded files to make available to your code.
CodeInterpreterToolCall:
type: object
title: Code interpreter tool call
description: |
A tool call to run code.
properties:
type:
type: string
enum:
- code_interpreter_call
default: code_interpreter_call
x-stainless-const: true
description: |
The type of the code interpreter tool call. Always `code_interpreter_call`.
id:
type: string
description: |
The unique ID of the code interpreter tool call.
status:
type: string
enum:
- in_progress
- completed
- incomplete
- interpreting
- failed
description: >
The status of the code interpreter tool call. Valid values are `in_progress`, `completed`,
`incomplete`, `interpreting`, and `failed`.
container_id:
type: string
description: |
The ID of the container used to run the code.
code:
type: string
nullable: true
description: |
The code to run, or null if not available.
outputs:
type: array
items:
anyOf:
- $ref: '#/components/schemas/CodeInterpreterOutputLogs'
- $ref: '#/components/schemas/CodeInterpreterOutputImage'
discriminator:
propertyName: type
discriminator:
propertyName: type
nullable: true
description: |
The outputs generated by the code interpreter, such as logs or images.
Can be null if no outputs are available.
required:
- type
- id
- status
- container_id
- code
- outputs
ComparisonFilter:
type: object
additionalProperties: false
title: Comparison Filter
description: >
A filter used to compare a specified attribute key to a given value using a defined comparison
operation.
properties:
type:
type: string
default: eq
enum:
- eq
- ne
- gt
- gte
- lt
- lte
description: |
Specifies the comparison operator: `eq`, `ne`, `gt`, `gte`, `lt`, `lte`.
- `eq`: equals
- `ne`: not equal
- `gt`: greater than
- `gte`: greater than or equal
- `lt`: less than
- `lte`: less than or equal
key:
type: string
description: The key to compare against the value.
value:
description: The value to compare against the attribute key; supports string, number, or boolean types.
anyOf:
- type: string
- type: number
- type: boolean
required:
- type
- key
- value
x-oaiMeta:
name: ComparisonFilter
CompleteUploadRequest:
type: object
additionalProperties: false
properties:
part_ids:
type: array
description: |
The ordered list of Part IDs.
items:
type: string
md5:
description: >
The optional md5 checksum for the file contents to verify if the bytes uploaded matches what you
expect.
type: string
required:
- part_ids
CompletionUsage:
type: object
description: Usage statistics for the completion request.
properties:
completion_tokens:
type: integer
default: 0
description: Number of tokens in the generated completion.
prompt_tokens:
type: integer
default: 0
description: Number of tokens in the prompt.
total_tokens:
type: integer
default: 0
description: Total number of tokens used in the request (prompt + completion).
completion_tokens_details:
type: object
description: Breakdown of tokens used in a completion.
properties:
accepted_prediction_tokens:
type: integer
default: 0
description: |
When using Predicted Outputs, the number of tokens in the
prediction that appeared in the completion.
audio_tokens:
type: integer
default: 0
description: Audio input tokens generated by the model.
reasoning_tokens:
type: integer
default: 0
description: Tokens generated by the model for reasoning.
rejected_prediction_tokens:
type: integer
default: 0
description: |
When using Predicted Outputs, the number of tokens in the
prediction that did not appear in the completion. However, like
reasoning tokens, these tokens are still counted in the total
completion tokens for purposes of billing, output, and context window
limits.
prompt_tokens_details:
type: object
description: Breakdown of tokens used in the prompt.
properties:
audio_tokens:
type: integer
default: 0
description: Audio input tokens present in the prompt.
cached_tokens:
type: integer
default: 0
description: Cached tokens present in the prompt.
required:
- prompt_tokens
- completion_tokens
- total_tokens
CompoundFilter:
$recursiveAnchor: true
type: object
additionalProperties: false
title: Compound Filter
description: Combine multiple filters using `and` or `or`.
properties:
type:
type: string
description: 'Type of operation: `and` or `or`.'
enum:
- and
- or
filters:
type: array
description: Array of filters to combine. Items can be `ComparisonFilter` or `CompoundFilter`.
items:
anyOf:
- $ref: '#/components/schemas/ComparisonFilter'
- $recursiveRef: '#'
required:
- type
- filters
x-oaiMeta:
name: CompoundFilter
ComputerAction:
anyOf:
- $ref: '#/components/schemas/Click'
- $ref: '#/components/schemas/DoubleClick'
- $ref: '#/components/schemas/Drag'
- $ref: '#/components/schemas/KeyPress'
- $ref: '#/components/schemas/Move'
- $ref: '#/components/schemas/Screenshot'
- $ref: '#/components/schemas/Scroll'
- $ref: '#/components/schemas/Type'
- $ref: '#/components/schemas/Wait'
discriminator:
propertyName: type
ComputerScreenshotImage:
type: object
description: |
A computer screenshot image used with the computer use tool.
properties:
type:
type: string
enum:
- computer_screenshot
default: computer_screenshot
description: |
Specifies the event type. For a computer screenshot, this property is
always set to `computer_screenshot`.
x-stainless-const: true
image_url:
type: string
description: The URL of the screenshot image.
file_id:
type: string
description: The identifier of an uploaded file that contains the screenshot.
required:
- type
ComputerToolCall:
type: object
title: Computer tool call
description: |
A tool call to a computer use tool. See the
[computer use guide](https://platform.openai.com/docs/guides/tools-computer-use) for more information.
properties:
type:
type: string
description: The type of the computer call. Always `computer_call`.
enum:
- computer_call
default: computer_call
id:
type: string
description: The unique ID of the computer call.
call_id:
type: string
description: |
An identifier used when responding to the tool call with output.
action:
$ref: '#/components/schemas/ComputerAction'
pending_safety_checks:
type: array
items:
$ref: '#/components/schemas/ComputerToolCallSafetyCheck'
description: |
The pending safety checks for the computer call.
status:
type: string
description: |
The status of the item. One of `in_progress`, `completed`, or
`incomplete`. Populated when items are returned via API.
enum:
- in_progress
- completed
- incomplete
required:
- type
- id
- action
- call_id
- pending_safety_checks
- status
ComputerToolCallOutput:
type: object
title: Computer tool call output
description: |
The output of a computer tool call.
properties:
type:
type: string
description: |
The type of the computer tool call output. Always `computer_call_output`.
enum:
- computer_call_output
default: computer_call_output
x-stainless-const: true
id:
type: string
description: |
The ID of the computer tool call output.
call_id:
type: string
description: |
The ID of the computer tool call that produced the output.
acknowledged_safety_checks:
type: array
description: |
The safety checks reported by the API that have been acknowledged by the
developer.
items:
$ref: '#/components/schemas/ComputerToolCallSafetyCheck'
output:
$ref: '#/components/schemas/ComputerScreenshotImage'
status:
type: string
description: |
The status of the message input. One of `in_progress`, `completed`, or
`incomplete`. Populated when input items are returned via API.
enum:
- in_progress
- completed
- incomplete
required:
- type
- call_id
- output
ComputerToolCallOutputResource:
allOf:
- $ref: '#/components/schemas/ComputerToolCallOutput'
- type: object
properties:
id:
type: string
description: |
The unique ID of the computer call tool output.
required:
- id
ComputerToolCallSafetyCheck:
type: object
description: |
A pending safety check for the computer call.
properties:
id:
type: string
description: The ID of the pending safety check.
code:
type: string
description: The type of the pending safety check.
message:
type: string
description: Details about the pending safety check.
required:
- id
- code
- message
ContainerFileListResource:
type: object
properties:
object:
description: The type of object returned, must be 'list'.
const: list
data:
type: array
description: A list of container files.
items:
$ref: '#/components/schemas/ContainerFileResource'
first_id:
type: string
description: The ID of the first file in the list.
last_id:
type: string
description: The ID of the last file in the list.
has_more:
type: boolean
description: Whether there are more files available.
required:
- object
- data
- first_id
- last_id
- has_more
ContainerFileResource:
type: object
title: The container file object
properties:
id:
type: string
description: Unique identifier for the file.
object:
type: string
description: The type of this object (`container.file`).
const: container.file
container_id:
type: string
description: The container this file belongs to.
created_at:
type: integer
description: Unix timestamp (in seconds) when the file was created.
bytes:
type: integer
description: Size of the file in bytes.
path:
type: string
description: Path of the file in the container.
source:
type: string
description: Source of the file (e.g., `user`, `assistant`).
required:
- id
- object
- created_at
- bytes
- container_id
- path
- source
x-oaiMeta:
name: The container file object
example: |
{
"id": "cfile_682e0e8a43c88191a7978f477a09bdf5",
"object": "container.file",
"created_at": 1747848842,
"bytes": 880,
"container_id": "cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04",
"path": "/mnt/data/88e12fa445d32636f190a0b33daed6cb-tsconfig.json",
"source": "user"
}
ContainerListResource:
type: object
properties:
object:
description: The type of object returned, must be 'list'.
const: list
data:
type: array
description: A list of containers.
items:
$ref: '#/components/schemas/ContainerResource'
first_id:
type: string
description: The ID of the first container in the list.
last_id:
type: string
description: The ID of the last container in the list.
has_more:
type: boolean
description: Whether there are more containers available.
required:
- object
- data
- first_id
- last_id
- has_more
ContainerResource:
type: object
title: The container object
properties:
id:
type: string
description: Unique identifier for the container.
object:
type: string
description: The type of this object.
name:
type: string
description: Name of the container.
created_at:
type: integer
description: Unix timestamp (in seconds) when the container was created.
status:
type: string
description: Status of the container (e.g., active, deleted).
expires_after:
type: object
description: |
The container will expire after this time period.
The anchor is the reference point for the expiration.
The minutes is the number of minutes after the anchor before the container expires.
properties:
anchor:
type: string
description: The reference point for the expiration.
enum:
- last_active_at
minutes:
type: integer
description: The number of minutes after the anchor before the container expires.
required:
- id
- object
- name
- created_at
- status
- id
- name
- created_at
- status
x-oaiMeta:
name: The container object
example: |
{
"id": "cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863",
"object": "container",
"created_at": 1747844794,
"status": "running",
"expires_after": {
"anchor": "last_active_at",
"minutes": 20
},
"last_active_at": 1747844794,
"name": "My Container"
}
Content:
description: |
Multi-modal input and output contents.
anyOf:
- title: Input content types
$ref: '#/components/schemas/InputContent'
- title: Output content types
$ref: '#/components/schemas/OutputContent'
Conversation:
title: The conversation object
allOf:
- $ref: '#/components/schemas/ConversationResource'
x-oaiMeta:
name: The conversation object
group: conversations
ConversationItem:
title: Conversation item
description: >-
A single item within a conversation. The set of possible types are the same as the `output` type of a
[Response
object](https://platform.openai.com/docs/api-reference/responses/object#responses/object-output).
discriminator:
propertyName: type
x-oaiMeta:
name: The item object
group: conversations
anyOf:
- $ref: '#/components/schemas/Message'
- $ref: '#/components/schemas/FunctionToolCallResource'
- $ref: '#/components/schemas/FunctionToolCallOutputResource'
- $ref: '#/components/schemas/FileSearchToolCall'
- $ref: '#/components/schemas/WebSearchToolCall'
- $ref: '#/components/schemas/ImageGenToolCall'
- $ref: '#/components/schemas/ComputerToolCall'
- $ref: '#/components/schemas/ComputerToolCallOutputResource'
- $ref: '#/components/schemas/ReasoningItem'
- $ref: '#/components/schemas/CodeInterpreterToolCall'
- $ref: '#/components/schemas/LocalShellToolCall'
- $ref: '#/components/schemas/LocalShellToolCallOutput'
- $ref: '#/components/schemas/MCPListTools'
- $ref: '#/components/schemas/MCPApprovalRequest'
- $ref: '#/components/schemas/MCPApprovalResponseResource'
- $ref: '#/components/schemas/MCPToolCall'
- $ref: '#/components/schemas/CustomToolCall'
- $ref: '#/components/schemas/CustomToolCallOutput'
ConversationItemList:
type: object
title: The conversation item list
description: A list of Conversation items.
properties:
object:
description: The type of object returned, must be `list`.
x-stainless-const: true
const: list
data:
type: array
description: A list of conversation items.
items:
$ref: '#/components/schemas/ConversationItem'
has_more:
type: boolean
description: Whether there are more items available.
first_id:
type: string
description: The ID of the first item in the list.
last_id:
type: string
description: The ID of the last item in the list.
required:
- object
- data
- has_more
- first_id
- last_id
x-oaiMeta:
name: The item list
group: conversations
Coordinate:
type: object
title: Coordinate
description: |
An x/y coordinate pair, e.g. `{ x: 100, y: 200 }`.
properties:
x:
type: integer
description: |
The x-coordinate.
'y':
type: integer
description: |
The y-coordinate.
required:
- x
- 'y'
CostsResult:
type: object
description: The aggregated costs details of the specific time bucket.
properties:
object:
type: string
enum:
- organization.costs.result
x-stainless-const: true
amount:
type: object
description: The monetary value in its associated currency.
properties:
value:
type: number
description: The numeric value of the cost.
currency:
type: string
description: Lowercase ISO-4217 currency e.g. "usd"
line_item:
type: string
nullable: true
description: When `group_by=line_item`, this field provides the line item of the grouped costs result.
project_id:
type: string
nullable: true
description: When `group_by=project_id`, this field provides the project ID of the grouped costs result.
required:
- object
x-oaiMeta:
name: Costs object
example: |
{
"object": "organization.costs.result",
"amount": {
"value": 0.06,
"currency": "usd"
},
"line_item": "Image models",
"project_id": "proj_abc"
}
CreateAssistantRequest:
type: object
additionalProperties: false
properties:
model:
description: >
ID of the model to use. You can use the [List
models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your
available models, or see our [Model overview](https://platform.openai.com/docs/models) for
descriptions of them.
example: gpt-4o
anyOf:
- type: string
- $ref: '#/components/schemas/AssistantSupportedModels'
x-oaiTypeLabel: string
name:
description: |
The name of the assistant. The maximum length is 256 characters.
type: string
nullable: true
maxLength: 256
description:
description: |
The description of the assistant. The maximum length is 512 characters.
type: string
nullable: true
maxLength: 512
instructions:
description: |
The system instructions that the assistant uses. The maximum length is 256,000 characters.
type: string
nullable: true
maxLength: 256000
reasoning_effort:
$ref: '#/components/schemas/ReasoningEffort'
tools:
description: >
A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools
can be of types `code_interpreter`, `file_search`, or `function`.
default: []
type: array
maxItems: 128
items:
$ref: '#/components/schemas/AssistantTool'
tool_resources:
type: object
description: >
A set of resources that are used by the assistant's tools. The resources are specific to the type
of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the
`file_search` tool requires a list of vector store IDs.
properties:
code_interpreter:
type: object
properties:
file_ids:
type: array
description: >
A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available
to the `code_interpreter` tool. There can be a maximum of 20 files associated with the
tool.
default: []
maxItems: 20
items:
type: string
file_search:
type: object
properties:
vector_store_ids:
type: array
description: >
The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object)
attached to this assistant. There can be a maximum of 1 vector store attached to the
assistant.
maxItems: 1
items:
type: string
vector_stores:
type: array
description: >
A helper to create a [vector
store](https://platform.openai.com/docs/api-reference/vector-stores/object) with file_ids
and attach it to this assistant. There can be a maximum of 1 vector store attached to the
assistant.
maxItems: 1
items:
type: object
properties:
file_ids:
type: array
description: >
A list of [file](https://platform.openai.com/docs/api-reference/files) IDs to add to
the vector store. There can be a maximum of 10000 files in a vector store.
maxItems: 10000
items:
type: string
chunking_strategy:
type: object
description: >-
The chunking strategy used to chunk the file(s). If not set, will use the `auto`
strategy.
anyOf:
- type: object
title: Auto Chunking Strategy
description: >-
The default strategy. This strategy currently uses a `max_chunk_size_tokens` of
`800` and `chunk_overlap_tokens` of `400`.
additionalProperties: false
properties:
type:
type: string
description: Always `auto`.
enum:
- auto
x-stainless-const: true
required:
- type
- type: object
title: Static Chunking Strategy
additionalProperties: false
properties:
type:
type: string
description: Always `static`.
enum:
- static
x-stainless-const: true
static:
type: object
additionalProperties: false
properties:
max_chunk_size_tokens:
type: integer
minimum: 100
maximum: 4096
description: >-
The maximum number of tokens in each chunk. The default value is `800`.
The minimum value is `100` and the maximum value is `4096`.
chunk_overlap_tokens:
type: integer
description: >
The number of tokens that overlap between chunks. The default value is
`400`.
Note that the overlap must not exceed half of `max_chunk_size_tokens`.
required:
- max_chunk_size_tokens
- chunk_overlap_tokens
required:
- type
- static
x-stainless-naming:
java:
type_name: StaticObject
kotlin:
type_name: StaticObject
discriminator:
propertyName: type
metadata:
$ref: '#/components/schemas/Metadata'
anyOf:
- required:
- vector_store_ids
- required:
- vector_stores
nullable: true
metadata:
$ref: '#/components/schemas/Metadata'
temperature:
description: >
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
more random, while lower values like 0.2 will make it more focused and deterministic.
type: number
minimum: 0
maximum: 2
default: 1
example: 1
nullable: true
top_p:
type: number
minimum: 0
maximum: 1
default: 1
example: 1
nullable: true
description: >
An alternative to sampling with temperature, called nucleus sampling, where the model considers
the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
response_format:
$ref: '#/components/schemas/AssistantsApiResponseFormatOption'
nullable: true
required:
- model
CreateChatCompletionRequest:
allOf:
- $ref: '#/components/schemas/CreateModelResponseProperties'
- type: object
properties:
messages:
description: >
A list of messages comprising the conversation so far. Depending on the
[model](https://platform.openai.com/docs/models) you use, different message types (modalities)
are
supported, like [text](https://platform.openai.com/docs/guides/text-generation),
[images](https://platform.openai.com/docs/guides/vision), and
[audio](https://platform.openai.com/docs/guides/audio).
type: array
minItems: 1
items:
$ref: '#/components/schemas/ChatCompletionRequestMessage'
model:
description: >
Model ID used to generate the response, like `gpt-4o` or `o3`. OpenAI
offers a wide range of models with different capabilities, performance
characteristics, and price points. Refer to the [model
guide](https://platform.openai.com/docs/models)
to browse and compare available models.
$ref: '#/components/schemas/ModelIdsShared'
modalities:
$ref: '#/components/schemas/ResponseModalities'
verbosity:
$ref: '#/components/schemas/Verbosity'
reasoning_effort:
$ref: '#/components/schemas/ReasoningEffort'
max_completion_tokens:
description: >
An upper bound for the number of tokens that can be generated for a completion, including
visible output tokens and [reasoning
tokens](https://platform.openai.com/docs/guides/reasoning).
type: integer
nullable: true
frequency_penalty:
type: number
default: 0
minimum: -2
maximum: 2
nullable: true
description: |
Number between -2.0 and 2.0. Positive values penalize new tokens based on
their existing frequency in the text so far, decreasing the model's
likelihood to repeat the same line verbatim.
presence_penalty:
type: number
default: 0
minimum: -2
maximum: 2
nullable: true
description: |
Number between -2.0 and 2.0. Positive values penalize new tokens based on
whether they appear in the text so far, increasing the model's likelihood
to talk about new topics.
web_search_options:
type: object
title: Web search
description: >
This tool searches the web for relevant results to use in a response.
Learn more about the [web search
tool](https://platform.openai.com/docs/guides/tools-web-search?api-mode=chat).
properties:
user_location:
type: object
nullable: true
required:
- type
- approximate
description: |
Approximate location parameters for the search.
properties:
type:
type: string
description: |
The type of location approximation. Always `approximate`.
enum:
- approximate
x-stainless-const: true
approximate:
$ref: '#/components/schemas/WebSearchLocation'
search_context_size:
$ref: '#/components/schemas/WebSearchContextSize'
top_logprobs:
description: |
An integer between 0 and 20 specifying the number of most likely tokens to
return at each token position, each with an associated log probability.
`logprobs` must be set to `true` if this parameter is used.
type: integer
minimum: 0
maximum: 20
nullable: true
response_format:
description: |
An object specifying the format that the model must output.
Setting to `{ "type": "json_schema", "json_schema": {...} }` enables
Structured Outputs which ensures the model will match your supplied JSON
schema. Learn more in the [Structured Outputs
guide](https://platform.openai.com/docs/guides/structured-outputs).
Setting to `{ "type": "json_object" }` enables the older JSON mode, which
ensures the message the model generates is valid JSON. Using `json_schema`
is preferred for models that support it.
anyOf:
- $ref: '#/components/schemas/ResponseFormatText'
- $ref: '#/components/schemas/ResponseFormatJsonSchema'
- $ref: '#/components/schemas/ResponseFormatJsonObject'
audio:
type: object
nullable: true
description: |
Parameters for audio output. Required when audio output is requested with
`modalities: ["audio"]`. [Learn more](https://platform.openai.com/docs/guides/audio).
required:
- voice
- format
properties:
voice:
$ref: '#/components/schemas/VoiceIdsShared'
description: |
The voice the model uses to respond. Supported voices are
`alloy`, `ash`, `ballad`, `coral`, `echo`, `fable`, `nova`, `onyx`, `sage`, and `shimmer`.
format:
type: string
enum:
- wav
- aac
- mp3
- flac
- opus
- pcm16
description: |
Specifies the output audio format. Must be one of `wav`, `mp3`, `flac`,
`opus`, or `pcm16`.
store:
type: boolean
default: false
nullable: true
description: |
Whether or not to store the output of this chat completion request for
use in our [model distillation](https://platform.openai.com/docs/guides/distillation) or
[evals](https://platform.openai.com/docs/guides/evals) products.
Supports text and image inputs. Note: image inputs over 8MB will be dropped.
stream:
description: >
If set to true, the model response data will be streamed to the client
as it is generated using [server-sent
events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format).
See the [Streaming section
below](https://platform.openai.com/docs/api-reference/chat/streaming)
for more information, along with the [streaming
responses](https://platform.openai.com/docs/guides/streaming-responses)
guide for more information on how to handle the streaming events.
type: boolean
nullable: true
default: false
stop:
$ref: '#/components/schemas/StopConfiguration'
logit_bias:
type: object
x-oaiTypeLabel: map
default: null
nullable: true
additionalProperties:
type: integer
description: |
Modify the likelihood of specified tokens appearing in the completion.
Accepts a JSON object that maps tokens (specified by their token ID in the
tokenizer) to an associated bias value from -100 to 100. Mathematically,
the bias is added to the logits generated by the model prior to sampling.
The exact effect will vary per model, but values between -1 and 1 should
decrease or increase likelihood of selection; values like -100 or 100
should result in a ban or exclusive selection of the relevant token.
logprobs:
description: |
Whether to return log probabilities of the output tokens or not. If true,
returns the log probabilities of each output token returned in the
`content` of `message`.
type: boolean
default: false
nullable: true
max_tokens:
description: |
The maximum number of [tokens](/tokenizer) that can be generated in the
chat completion. This value can be used to control
[costs](https://openai.com/api/pricing/) for text generated via API.
This value is now deprecated in favor of `max_completion_tokens`, and is
not compatible with [o-series models](https://platform.openai.com/docs/guides/reasoning).
type: integer
nullable: true
deprecated: true
'n':
type: integer
minimum: 1
maximum: 128
default: 1
example: 1
nullable: true
description: >-
How many chat completion choices to generate for each input message. Note that you will be
charged based on the number of generated tokens across all of the choices. Keep `n` as `1` to
minimize costs.
prediction:
nullable: true
description: >
Configuration for a [Predicted
Output](https://platform.openai.com/docs/guides/predicted-outputs),
which can greatly improve response times when large parts of the model
response are known ahead of time. This is most common when you are
regenerating a file with only minor changes to most of the content.
anyOf:
- $ref: '#/components/schemas/PredictionContent'
discriminator:
propertyName: type
seed:
type: integer
minimum: -9223372036854776000
maximum: 9223372036854776000
nullable: true
deprecated: true
description: >
This feature is in Beta.
If specified, our system will make a best effort to sample deterministically, such that
repeated requests with the same `seed` and parameters should return the same result.
Determinism is not guaranteed, and you should refer to the `system_fingerprint` response
parameter to monitor changes in the backend.
x-oaiMeta:
beta: true
stream_options:
$ref: '#/components/schemas/ChatCompletionStreamOptions'
tools:
type: array
description: |
A list of tools the model may call. You can provide either
[custom tools](https://platform.openai.com/docs/guides/function-calling#custom-tools) or
[function tools](https://platform.openai.com/docs/guides/function-calling).
items:
anyOf:
- $ref: '#/components/schemas/ChatCompletionTool'
- $ref: '#/components/schemas/CustomToolChatCompletions'
x-stainless-naming:
python:
model_name: chat_completion_tool_union
param_model_name: chat_completion_tool_union_param
discriminator:
propertyName: type
x-stainless-go-variant-constructor:
naming: chat_completion_{variant}_tool
tool_choice:
$ref: '#/components/schemas/ChatCompletionToolChoiceOption'
parallel_tool_calls:
$ref: '#/components/schemas/ParallelToolCalls'
function_call:
deprecated: true
description: |
Deprecated in favor of `tool_choice`.
Controls which (if any) function is called by the model.
`none` means the model will not call a function and instead generates a
message.
`auto` means the model can pick between generating a message or calling a
function.
Specifying a particular function via `{"name": "my_function"}` forces the
model to call that function.
`none` is the default when no functions are present. `auto` is the default
if functions are present.
anyOf:
- type: string
description: >
`none` means the model will not call a function and instead generates a message. `auto`
means the model can pick between generating a message or calling a function.
enum:
- none
- auto
title: function call mode
- $ref: '#/components/schemas/ChatCompletionFunctionCallOption'
functions:
deprecated: true
description: |
Deprecated in favor of `tools`.
A list of functions the model may generate JSON inputs for.
type: array
minItems: 1
maxItems: 128
items:
$ref: '#/components/schemas/ChatCompletionFunctions'
required:
- model
- messages
CreateChatCompletionResponse:
type: object
description: Represents a chat completion response returned by model, based on the provided input.
properties:
id:
type: string
description: A unique identifier for the chat completion.
choices:
type: array
description: A list of chat completion choices. Can be more than one if `n` is greater than 1.
items:
type: object
required:
- finish_reason
- index
- message
- logprobs
properties:
finish_reason:
type: string
description: >
The reason the model stopped generating tokens. This will be `stop` if the model hit a
natural stop point or a provided stop sequence,
`length` if the maximum number of tokens specified in the request was reached,
`content_filter` if content was omitted due to a flag from our content filters,
`tool_calls` if the model called a tool, or `function_call` (deprecated) if the model called
a function.
enum:
- stop
- length
- tool_calls
- content_filter
- function_call
index:
type: integer
description: The index of the choice in the list of choices.
message:
$ref: '#/components/schemas/ChatCompletionResponseMessage'
logprobs:
description: Log probability information for the choice.
type: object
nullable: true
properties:
content:
description: A list of message content tokens with log probability information.
type: array
items:
$ref: '#/components/schemas/ChatCompletionTokenLogprob'
nullable: true
refusal:
description: A list of message refusal tokens with log probability information.
type: array
items:
$ref: '#/components/schemas/ChatCompletionTokenLogprob'
nullable: true
required:
- content
- refusal
created:
type: integer
description: The Unix timestamp (in seconds) of when the chat completion was created.
model:
type: string
description: The model used for the chat completion.
service_tier:
$ref: '#/components/schemas/ServiceTier'
system_fingerprint:
type: string
deprecated: true
description: >
This fingerprint represents the backend configuration that the model runs with.
Can be used in conjunction with the `seed` request parameter to understand when backend changes
have been made that might impact determinism.
object:
type: string
description: The object type, which is always `chat.completion`.
enum:
- chat.completion
x-stainless-const: true
usage:
$ref: '#/components/schemas/CompletionUsage'
required:
- choices
- created
- id
- model
- object
x-oaiMeta:
name: The chat completion object
group: chat
example: |
{
"id": "chatcmpl-B9MHDbslfkBeAs8l4bebGdFOJ6PeG",
"object": "chat.completion",
"created": 1741570283,
"model": "gpt-4o-2024-08-06",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "The image shows a wooden boardwalk path running through a lush green field or meadow. The sky is bright blue with some scattered clouds, giving the scene a serene and peaceful atmosphere. Trees and shrubs are visible in the background.",
"refusal": null,
"annotations": []
},
"logprobs": null,
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 1117,
"completion_tokens": 46,
"total_tokens": 1163,
"prompt_tokens_details": {
"cached_tokens": 0,
"audio_tokens": 0
},
"completion_tokens_details": {
"reasoning_tokens": 0,
"audio_tokens": 0,
"accepted_prediction_tokens": 0,
"rejected_prediction_tokens": 0
}
},
"service_tier": "default",
"system_fingerprint": "fp_fc9f1d7035"
}
CreateChatCompletionStreamResponse:
type: object
description: |
Represents a streamed chunk of a chat completion response returned
by the model, based on the provided input.
[Learn more](https://platform.openai.com/docs/guides/streaming-responses).
properties:
id:
type: string
description: A unique identifier for the chat completion. Each chunk has the same ID.
choices:
type: array
description: >
A list of chat completion choices. Can contain more than one elements if `n` is greater than 1.
Can also be empty for the
last chunk if you set `stream_options: {"include_usage": true}`.
items:
type: object
required:
- delta
- finish_reason
- index
properties:
delta:
$ref: '#/components/schemas/ChatCompletionStreamResponseDelta'
logprobs:
description: Log probability information for the choice.
type: object
nullable: true
properties:
content:
description: A list of message content tokens with log probability information.
type: array
items:
$ref: '#/components/schemas/ChatCompletionTokenLogprob'
nullable: true
refusal:
description: A list of message refusal tokens with log probability information.
type: array
items:
$ref: '#/components/schemas/ChatCompletionTokenLogprob'
nullable: true
required:
- content
- refusal
finish_reason:
type: string
description: >
The reason the model stopped generating tokens. This will be `stop` if the model hit a
natural stop point or a provided stop sequence,
`length` if the maximum number of tokens specified in the request was reached,
`content_filter` if content was omitted due to a flag from our content filters,
`tool_calls` if the model called a tool, or `function_call` (deprecated) if the model called
a function.
enum:
- stop
- length
- tool_calls
- content_filter
- function_call
nullable: true
index:
type: integer
description: The index of the choice in the list of choices.
created:
type: integer
description: >-
The Unix timestamp (in seconds) of when the chat completion was created. Each chunk has the same
timestamp.
model:
type: string
description: The model to generate the completion.
service_tier:
$ref: '#/components/schemas/ServiceTier'
system_fingerprint:
type: string
deprecated: true
description: >
This fingerprint represents the backend configuration that the model runs with.
Can be used in conjunction with the `seed` request parameter to understand when backend changes
have been made that might impact determinism.
object:
type: string
description: The object type, which is always `chat.completion.chunk`.
enum:
- chat.completion.chunk
x-stainless-const: true
usage:
$ref: '#/components/schemas/CompletionUsage'
nullable: true
description: |
An optional field that will only be present when you set
`stream_options: {"include_usage": true}` in your request. When present, it
contains a null value **except for the last chunk** which contains the
token usage statistics for the entire request.
**NOTE:** If the stream is interrupted or cancelled, you may not
receive the final usage chunk which contains the total token usage for
the request.
required:
- choices
- created
- id
- model
- object
x-oaiMeta:
name: The chat completion chunk object
group: chat
example: >
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
"system_fingerprint": "fp_44709d6fcb",
"choices":[{"index":0,"delta":{"role":"assistant","content":""},"logprobs":null,"finish_reason":null}]}
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
"system_fingerprint": "fp_44709d6fcb",
"choices":[{"index":0,"delta":{"content":"Hello"},"logprobs":null,"finish_reason":null}]}
....
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
"system_fingerprint": "fp_44709d6fcb",
"choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}]}
CreateCompletionRequest:
type: object
properties:
model:
description: >
ID of the model to use. You can use the [List
models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your
available models, or see our [Model overview](https://platform.openai.com/docs/models) for
descriptions of them.
anyOf:
- type: string
- type: string
enum:
- gpt-3.5-turbo-instruct
- davinci-002
- babbage-002
title: Preset
x-oaiTypeLabel: string
prompt:
description: >
The prompt(s) to generate completions for, encoded as a string, array of strings, array of tokens,
or array of token arrays.
Note that <|endoftext|> is the document separator that the model sees during training, so if a
prompt is not specified the model will generate as if from the beginning of a new document.
nullable: true
anyOf:
- type: string
default: ''
example: This is a test.
- type: array
items:
type: string
default: ''
example: This is a test.
title: Array of strings
- type: array
minItems: 1
items:
type: integer
title: Array of tokens
- type: array
minItems: 1
items:
type: array
minItems: 1
items:
type: integer
title: Array of token arrays
best_of:
type: integer
default: 1
minimum: 0
maximum: 20
nullable: true
description: >
Generates `best_of` completions server-side and returns the "best" (the one with the highest log
probability per token). Results cannot be streamed.
When used with `n`, `best_of` controls the number of candidate completions and `n` specifies how
many to return – `best_of` must be greater than `n`.
**Note:** Because this parameter generates many completions, it can quickly consume your token
quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.
echo:
type: boolean
default: false
nullable: true
description: |
Echo back the prompt in addition to the completion
frequency_penalty:
type: number
default: 0
minimum: -2
maximum: 2
nullable: true
description: >
Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency
in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
[See more information about frequency and presence
penalties.](https://platform.openai.com/docs/guides/text-generation)
logit_bias:
type: object
x-oaiTypeLabel: map
default: null
nullable: true
additionalProperties:
type: integer
description: >
Modify the likelihood of specified tokens appearing in the completion.
Accepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer) to an
associated bias value from -100 to 100. You can use this [tokenizer tool](/tokenizer?view=bpe) to
convert text to token IDs. Mathematically, the bias is added to the logits generated by the model
prior to sampling. The exact effect will vary per model, but values between -1 and 1 should
decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or
exclusive selection of the relevant token.
As an example, you can pass `{"50256": -100}` to prevent the <|endoftext|> token from being
generated.
logprobs:
type: integer
minimum: 0
maximum: 5
default: null
nullable: true
description: >
Include the log probabilities on the `logprobs` most likely output tokens, as well the chosen
tokens. For example, if `logprobs` is 5, the API will return a list of the 5 most likely tokens.
The API will always return the `logprob` of the sampled token, so there may be up to `logprobs+1`
elements in the response.
The maximum value for `logprobs` is 5.
max_tokens:
type: integer
minimum: 0
default: 16
example: 16
nullable: true
description: >
The maximum number of [tokens](/tokenizer) that can be generated in the completion.
The token count of your prompt plus `max_tokens` cannot exceed the model's context length.
[Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for
counting tokens.
'n':
type: integer
minimum: 1
maximum: 128
default: 1
example: 1
nullable: true
description: >
How many completions to generate for each prompt.
**Note:** Because this parameter generates many completions, it can quickly consume your token
quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.
presence_penalty:
type: number
default: 0
minimum: -2
maximum: 2
nullable: true
description: >
Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in
the text so far, increasing the model's likelihood to talk about new topics.
[See more information about frequency and presence
penalties.](https://platform.openai.com/docs/guides/text-generation)
seed:
type: integer
format: int64
nullable: true
description: >
If specified, our system will make a best effort to sample deterministically, such that repeated
requests with the same `seed` and parameters should return the same result.
Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter
to monitor changes in the backend.
stop:
$ref: '#/components/schemas/StopConfiguration'
stream:
description: >
Whether to stream back partial progress. If set, tokens will be sent as data-only [server-sent
events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format)
as they become available, with the stream terminated by a `data: [DONE]` message. [Example Python
code](https://cookbook.openai.com/examples/how_to_stream_completions).
type: boolean
nullable: true
default: false
stream_options:
$ref: '#/components/schemas/ChatCompletionStreamOptions'
suffix:
description: |
The suffix that comes after a completion of inserted text.
This parameter is only supported for `gpt-3.5-turbo-instruct`.
default: null
nullable: true
type: string
example: test.
temperature:
type: number
minimum: 0
maximum: 2
default: 1
example: 1
nullable: true
description: >
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
more random, while lower values like 0.2 will make it more focused and deterministic.
We generally recommend altering this or `top_p` but not both.
top_p:
type: number
minimum: 0
maximum: 1
default: 1
example: 1
nullable: true
description: >
An alternative to sampling with temperature, called nucleus sampling, where the model considers
the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
top 10% probability mass are considered.
We generally recommend altering this or `temperature` but not both.
user:
type: string
example: user-1234
description: >
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
[Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).
required:
- model
- prompt
CreateCompletionResponse:
type: object
description: >
Represents a completion response from the API. Note: both the streamed and non-streamed response
objects share the same shape (unlike the chat endpoint).
properties:
id:
type: string
description: A unique identifier for the completion.
choices:
type: array
description: The list of completion choices the model generated for the input prompt.
items:
type: object
required:
- finish_reason
- index
- logprobs
- text
properties:
finish_reason:
type: string
description: >
The reason the model stopped generating tokens. This will be `stop` if the model hit a
natural stop point or a provided stop sequence,
`length` if the maximum number of tokens specified in the request was reached,
or `content_filter` if content was omitted due to a flag from our content filters.
enum:
- stop
- length
- content_filter
index:
type: integer
logprobs:
type: object
nullable: true
properties:
text_offset:
type: array
items:
type: integer
token_logprobs:
type: array
items:
type: number
tokens:
type: array
items:
type: string
top_logprobs:
type: array
items:
type: object
additionalProperties:
type: number
text:
type: string
created:
type: integer
description: The Unix timestamp (in seconds) of when the completion was created.
model:
type: string
description: The model used for completion.
system_fingerprint:
type: string
description: >
This fingerprint represents the backend configuration that the model runs with.
Can be used in conjunction with the `seed` request parameter to understand when backend changes
have been made that might impact determinism.
object:
type: string
description: The object type, which is always "text_completion"
enum:
- text_completion
x-stainless-const: true
usage:
$ref: '#/components/schemas/CompletionUsage'
required:
- id
- object
- created
- model
- choices
x-oaiMeta:
name: The completion object
legacy: true
example: |
{
"id": "cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7",
"object": "text_completion",
"created": 1589478378,
"model": "gpt-4-turbo",
"choices": [
{
"text": "\n\nThis is indeed a test",
"index": 0,
"logprobs": null,
"finish_reason": "length"
}
],
"usage": {
"prompt_tokens": 5,
"completion_tokens": 7,
"total_tokens": 12
}
}
CreateContainerBody:
type: object
properties:
name:
type: string
description: Name of the container to create.
file_ids:
type: array
description: IDs of files to copy to the container.
items:
type: string
expires_after:
type: object
description: Container expiration time in seconds relative to the 'anchor' time.
properties:
anchor:
type: string
enum:
- last_active_at
description: Time anchor for the expiration time. Currently only 'last_active_at' is supported.
minutes:
type: integer
required:
- anchor
- minutes
required:
- name
CreateContainerFileBody:
type: object
properties:
file_id:
type: string
description: Name of the file to create.
file:
description: |
The File object (not file name) to be uploaded.
type: string
format: binary
required: []
CreateConversationRequest:
type: object
description: Create a conversation
properties:
metadata:
$ref: '#/components/schemas/Metadata'
description: |
Set of 16 key-value pairs that can be attached to an object. Useful for
storing additional information about the object in a structured format.
items:
type: array
description: |
Initial items to include in the conversation context.
You may add up to 20 items at a time.
items:
$ref: '#/components/schemas/InputItem'
nullable: true
maxItems: 20
required: []
CreateEmbeddingRequest:
type: object
additionalProperties: false
properties:
input:
description: >
Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single
request, pass an array of strings or array of token arrays. The input must not exceed the max
input tokens for the model (8192 tokens for all embedding models), cannot be an empty string, and
any array must be 2048 dimensions or less. [Example Python
code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.
In addition to the per-input token limit, all embedding models enforce a maximum of 300,000
tokens summed across all inputs in a single request.
example: The quick brown fox jumped over the lazy dog
anyOf:
- type: string
title: string
description: The string that will be turned into an embedding.
default: ''
example: This is a test.
- type: array
title: Array of strings
description: The array of strings that will be turned into an embedding.
minItems: 1
maxItems: 2048
items:
type: string
default: ''
example: '[''This is a test.'']'
- type: array
title: Array of tokens
description: The array of integers that will be turned into an embedding.
minItems: 1
maxItems: 2048
items:
type: integer
- type: array
title: Array of token arrays
description: The array of arrays containing integers that will be turned into an embedding.
minItems: 1
maxItems: 2048
items:
type: array
minItems: 1
items:
type: integer
model:
description: >
ID of the model to use. You can use the [List
models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your
available models, or see our [Model overview](https://platform.openai.com/docs/models) for
descriptions of them.
example: text-embedding-3-small
anyOf:
- type: string
- type: string
enum:
- text-embedding-ada-002
- text-embedding-3-small
- text-embedding-3-large
x-stainless-nominal: false
x-oaiTypeLabel: string
encoding_format:
description: >-
The format to return the embeddings in. Can be either `float` or
[`base64`](https://pypi.org/project/pybase64/).
example: float
default: float
type: string
enum:
- float
- base64
dimensions:
description: >
The number of dimensions the resulting output embeddings should have. Only supported in
`text-embedding-3` and later models.
type: integer
minimum: 1
user:
type: string
example: user-1234
description: >
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
[Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).
required:
- model
- input
CreateEmbeddingResponse:
type: object
properties:
data:
type: array
description: The list of embeddings generated by the model.
items:
$ref: '#/components/schemas/Embedding'
model:
type: string
description: The name of the model used to generate the embedding.
object:
type: string
description: The object type, which is always "list".
enum:
- list
x-stainless-const: true
usage:
type: object
description: The usage information for the request.
properties:
prompt_tokens:
type: integer
description: The number of tokens used by the prompt.
total_tokens:
type: integer
description: The total number of tokens used by the request.
required:
- prompt_tokens
- total_tokens
required:
- object
- model
- data
- usage
CreateEvalCompletionsRunDataSource:
type: object
title: CompletionsRunDataSource
description: |
A CompletionsRunDataSource object describing a model sampling configuration.
properties:
type:
type: string
enum:
- completions
default: completions
description: The type of run data source. Always `completions`.
input_messages:
description: >-
Used when sampling from a model. Dictates the structure of the messages passed into the model. Can
either be a reference to a prebuilt trajectory (ie, `item.input_trajectory`), or a template with
variable references to the `item` namespace.
anyOf:
- type: object
title: TemplateInputMessages
properties:
type:
type: string
enum:
- template
description: The type of input messages. Always `template`.
template:
type: array
description: >-
A list of chat messages forming the prompt or context. May include variable references to
the `item` namespace, ie {{item.name}}.
items:
anyOf:
- $ref: '#/components/schemas/EasyInputMessage'
- $ref: '#/components/schemas/EvalItem'
required:
- type
- template
- type: object
title: ItemReferenceInputMessages
properties:
type:
type: string
enum:
- item_reference
description: The type of input messages. Always `item_reference`.
item_reference:
type: string
description: A reference to a variable in the `item` namespace. Ie, "item.input_trajectory"
required:
- type
- item_reference
discriminator:
propertyName: type
sampling_params:
type: object
properties:
temperature:
type: number
description: A higher temperature increases randomness in the outputs.
default: 1
max_completion_tokens:
type: integer
description: The maximum number of tokens in the generated output.
top_p:
type: number
description: An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
default: 1
seed:
type: integer
description: A seed value to initialize the randomness, during sampling.
default: 42
response_format:
description: |
An object specifying the format that the model must output.
Setting to `{ "type": "json_schema", "json_schema": {...} }` enables
Structured Outputs which ensures the model will match your supplied JSON
schema. Learn more in the [Structured Outputs
guide](https://platform.openai.com/docs/guides/structured-outputs).
Setting to `{ "type": "json_object" }` enables the older JSON mode, which
ensures the message the model generates is valid JSON. Using `json_schema`
is preferred for models that support it.
anyOf:
- $ref: '#/components/schemas/ResponseFormatText'
- $ref: '#/components/schemas/ResponseFormatJsonSchema'
- $ref: '#/components/schemas/ResponseFormatJsonObject'
tools:
type: array
description: >
A list of tools the model may call. Currently, only functions are supported as a tool. Use
this to provide a list of functions the model may generate JSON inputs for. A max of 128
functions are supported.
items:
$ref: '#/components/schemas/ChatCompletionTool'
model:
type: string
description: The name of the model to use for generating completions (e.g. "o3-mini").
source:
description: Determines what populates the `item` namespace in this run's data source.
anyOf:
- $ref: '#/components/schemas/EvalJsonlFileContentSource'
- $ref: '#/components/schemas/EvalJsonlFileIdSource'
- $ref: '#/components/schemas/EvalStoredCompletionsSource'
discriminator:
propertyName: type
required:
- type
- source
x-oaiMeta:
name: The completions data source object used to configure an individual run
group: eval runs
example: |
{
"name": "gpt-4o-mini-2024-07-18",
"data_source": {
"type": "completions",
"input_messages": {
"type": "item_reference",
"item_reference": "item.input"
},
"model": "gpt-4o-mini-2024-07-18",
"source": {
"type": "stored_completions",
"model": "gpt-4o-mini-2024-07-18"
}
}
}
CreateEvalCustomDataSourceConfig:
type: object
title: CustomDataSourceConfig
description: >
A CustomDataSourceConfig object that defines the schema for the data source used for the evaluation
runs.
This schema is used to define the shape of the data that will be:
- Used to define your testing criteria and
- What data is required when creating a run
properties:
type:
type: string
enum:
- custom
default: custom
description: The type of data source. Always `custom`.
x-stainless-const: true
item_schema:
type: object
description: The json schema for each row in the data source.
additionalProperties: true
include_sample_schema:
type: boolean
default: false
description: >-
Whether the eval should expect you to populate the sample namespace (ie, by generating responses
off of your data source)
required:
- item_schema
- type
x-oaiMeta:
name: The eval file data source config object
group: evals
example: |
{
"type": "custom",
"item_schema": {
"type": "object",
"properties": {
"name": {"type": "string"},
"age": {"type": "integer"}
},
"required": ["name", "age"]
},
"include_sample_schema": true
}
CreateEvalItem:
title: CreateEvalItem
description: >-
A chat message that makes up the prompt or context. May include variable references to the `item`
namespace, ie {{item.name}}.
type: object
x-oaiMeta:
name: The chat message object used to configure an individual run
anyOf:
- type: object
title: SimpleInputMessage
properties:
role:
type: string
description: The role of the message (e.g. "system", "assistant", "user").
content:
type: string
description: The content of the message.
required:
- role
- content
- $ref: '#/components/schemas/EvalItem'
CreateEvalJsonlRunDataSource:
type: object
title: JsonlRunDataSource
description: |
A JsonlRunDataSource object with that specifies a JSONL file that matches the eval
properties:
type:
type: string
enum:
- jsonl
default: jsonl
description: The type of data source. Always `jsonl`.
x-stainless-const: true
source:
description: Determines what populates the `item` namespace in the data source.
anyOf:
- $ref: '#/components/schemas/EvalJsonlFileContentSource'
- $ref: '#/components/schemas/EvalJsonlFileIdSource'
discriminator:
propertyName: type
required:
- type
- source
x-oaiMeta:
name: The file data source object for the eval run configuration
group: evals
example: |
{
"type": "jsonl",
"source": {
"type": "file_id",
"id": "file-9GYS6xbkWgWhmE7VoLUWFg"
}
}
CreateEvalLabelModelGrader:
type: object
title: LabelModelGrader
description: |
A LabelModelGrader object which uses a model to assign labels to each item
in the evaluation.
properties:
type:
description: The object type, which is always `label_model`.
type: string
enum:
- label_model
x-stainless-const: true
name:
type: string
description: The name of the grader.
model:
type: string
description: The model to use for the evaluation. Must support structured outputs.
input:
type: array
description: >-
A list of chat messages forming the prompt or context. May include variable references to the
`item` namespace, ie {{item.name}}.
items:
$ref: '#/components/schemas/CreateEvalItem'
labels:
type: array
items:
type: string
description: The labels to classify to each item in the evaluation.
passing_labels:
type: array
items:
type: string
description: The labels that indicate a passing result. Must be a subset of labels.
required:
- type
- model
- input
- passing_labels
- labels
- name
x-oaiMeta:
name: The eval label model grader object
group: evals
example: |
{
"type": "label_model",
"model": "gpt-4o-2024-08-06",
"input": [
{
"role": "system",
"content": "Classify the sentiment of the following statement as one of 'positive', 'neutral', or 'negative'"
},
{
"role": "user",
"content": "Statement: {{item.response}}"
}
],
"passing_labels": ["positive"],
"labels": ["positive", "neutral", "negative"],
"name": "Sentiment label grader"
}
CreateEvalLogsDataSourceConfig:
type: object
title: LogsDataSourceConfig
description: |
A data source config which specifies the metadata property of your logs query.
This is usually metadata like `usecase=chatbot` or `prompt-version=v2`, etc.
properties:
type:
type: string
enum:
- logs
default: logs
description: The type of data source. Always `logs`.
x-stainless-const: true
metadata:
type: object
description: Metadata filters for the logs data source.
additionalProperties: true
required:
- type
x-oaiMeta:
name: The logs data source object for evals
group: evals
example: |
{
"type": "logs",
"metadata": {
"use_case": "customer_support_agent"
}
}
CreateEvalRequest:
type: object
title: CreateEvalRequest
properties:
name:
type: string
description: The name of the evaluation.
metadata:
$ref: '#/components/schemas/Metadata'
data_source_config:
type: object
description: >-
The configuration for the data source used for the evaluation runs. Dictates the schema of the
data used in the evaluation.
anyOf:
- $ref: '#/components/schemas/CreateEvalCustomDataSourceConfig'
- $ref: '#/components/schemas/CreateEvalLogsDataSourceConfig'
- $ref: '#/components/schemas/CreateEvalStoredCompletionsDataSourceConfig'
discriminator:
propertyName: type
testing_criteria:
type: array
description: >-
A list of graders for all eval runs in this group. Graders can reference variables in the data
source using double curly braces notation, like `{{item.variable_name}}`. To reference the model's
output, use the `sample` namespace (ie, `{{sample.output_text}}`).
items:
anyOf:
- $ref: '#/components/schemas/CreateEvalLabelModelGrader'
- $ref: '#/components/schemas/EvalGraderStringCheck'
- $ref: '#/components/schemas/EvalGraderTextSimilarity'
- $ref: '#/components/schemas/EvalGraderPython'
- $ref: '#/components/schemas/EvalGraderScoreModel'
discriminator:
propertyName: type
required:
- data_source_config
- testing_criteria
CreateEvalResponsesRunDataSource:
type: object
title: ResponsesRunDataSource
description: |
A ResponsesRunDataSource object describing a model sampling configuration.
properties:
type:
type: string
enum:
- responses
default: responses
description: The type of run data source. Always `responses`.
input_messages:
description: >-
Used when sampling from a model. Dictates the structure of the messages passed into the model. Can
either be a reference to a prebuilt trajectory (ie, `item.input_trajectory`), or a template with
variable references to the `item` namespace.
anyOf:
- type: object
title: InputMessagesTemplate
properties:
type:
type: string
enum:
- template
description: The type of input messages. Always `template`.
template:
type: array
description: >-
A list of chat messages forming the prompt or context. May include variable references to
the `item` namespace, ie {{item.name}}.
items:
anyOf:
- type: object
title: ChatMessage
properties:
role:
type: string
description: The role of the message (e.g. "system", "assistant", "user").
content:
type: string
description: The content of the message.
required:
- role
- content
- $ref: '#/components/schemas/EvalItem'
required:
- type
- template
- type: object
title: InputMessagesItemReference
properties:
type:
type: string
enum:
- item_reference
description: The type of input messages. Always `item_reference`.
item_reference:
type: string
description: A reference to a variable in the `item` namespace. Ie, "item.name"
required:
- type
- item_reference
discriminator:
propertyName: type
sampling_params:
type: object
properties:
temperature:
type: number
description: A higher temperature increases randomness in the outputs.
default: 1
max_completion_tokens:
type: integer
description: The maximum number of tokens in the generated output.
top_p:
type: number
description: An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
default: 1
seed:
type: integer
description: A seed value to initialize the randomness, during sampling.
default: 42
tools:
type: array
description: |
An array of tools the model may call while generating a response. You
can specify which tool to use by setting the `tool_choice` parameter.
The two categories of tools you can provide the model are:
- **Built-in tools**: Tools that are provided by OpenAI that extend the
model's capabilities, like [web search](https://platform.openai.com/docs/guides/tools-web-search)
or [file search](https://platform.openai.com/docs/guides/tools-file-search). Learn more about
[built-in tools](https://platform.openai.com/docs/guides/tools).
- **Function calls (custom tools)**: Functions that are defined by you,
enabling the model to call your own code. Learn more about
[function calling](https://platform.openai.com/docs/guides/function-calling).
items:
$ref: '#/components/schemas/Tool'
text:
type: object
description: |
Configuration options for a text response from the model. Can be plain
text or structured JSON data. Learn more:
- [Text inputs and outputs](https://platform.openai.com/docs/guides/text)
- [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs)
properties:
format:
$ref: '#/components/schemas/TextResponseFormatConfiguration'
model:
type: string
description: The name of the model to use for generating completions (e.g. "o3-mini").
source:
description: Determines what populates the `item` namespace in this run's data source.
anyOf:
- $ref: '#/components/schemas/EvalJsonlFileContentSource'
- $ref: '#/components/schemas/EvalJsonlFileIdSource'
- $ref: '#/components/schemas/EvalResponsesSource'
discriminator:
propertyName: type
required:
- type
- source
x-oaiMeta:
name: The completions data source object used to configure an individual run
group: eval runs
example: |
{
"name": "gpt-4o-mini-2024-07-18",
"data_source": {
"type": "responses",
"input_messages": {
"type": "item_reference",
"item_reference": "item.input"
},
"model": "gpt-4o-mini-2024-07-18",
"source": {
"type": "responses",
"model": "gpt-4o-mini-2024-07-18"
}
}
}
CreateEvalRunRequest:
type: object
title: CreateEvalRunRequest
properties:
name:
type: string
description: The name of the run.
metadata:
$ref: '#/components/schemas/Metadata'
data_source:
type: object
description: Details about the run's data source.
anyOf:
- $ref: '#/components/schemas/CreateEvalJsonlRunDataSource'
- $ref: '#/components/schemas/CreateEvalCompletionsRunDataSource'
- $ref: '#/components/schemas/CreateEvalResponsesRunDataSource'
required:
- data_source
CreateEvalStoredCompletionsDataSourceConfig:
type: object
title: StoredCompletionsDataSourceConfig
description: |
Deprecated in favor of LogsDataSourceConfig.
properties:
type:
type: string
enum:
- stored_completions
default: stored_completions
description: The type of data source. Always `stored_completions`.
x-stainless-const: true
metadata:
type: object
description: Metadata filters for the stored completions data source.
additionalProperties: true
required:
- type
deprecated: true
x-oaiMeta:
name: The stored completions data source object for evals
group: evals
example: |
{
"type": "stored_completions",
"metadata": {
"use_case": "customer_support_agent"
}
}
CreateFileRequest:
type: object
additionalProperties: false
properties:
file:
description: |
The File object (not file name) to be uploaded.
type: string
format: binary
x-oaiMeta:
exampleFilePath: fine-tune.jsonl
purpose:
$ref: '#/components/schemas/FilePurpose'
expires_after:
$ref: '#/components/schemas/FileExpirationAfter'
required:
- file
- purpose
CreateFineTuningCheckpointPermissionRequest:
type: object
additionalProperties: false
properties:
project_ids:
type: array
description: The project identifiers to grant access to.
items:
type: string
required:
- project_ids
CreateFineTuningJobRequest:
type: object
properties:
model:
description: >
The name of the model to fine-tune. You can select one of the
[supported
models](https://platform.openai.com/docs/guides/fine-tuning#which-models-can-be-fine-tuned).
example: gpt-4o-mini
anyOf:
- type: string
- type: string
enum:
- babbage-002
- davinci-002
- gpt-3.5-turbo
- gpt-4o-mini
title: Preset
x-oaiTypeLabel: string
training_file:
description: >
The ID of an uploaded file that contains training data.
See [upload file](https://platform.openai.com/docs/api-reference/files/create) for how to upload a
file.
Your dataset must be formatted as a JSONL file. Additionally, you must upload your file with the
purpose `fine-tune`.
The contents of the file should differ depending on if the model uses the
[chat](https://platform.openai.com/docs/api-reference/fine-tuning/chat-input),
[completions](https://platform.openai.com/docs/api-reference/fine-tuning/completions-input)
format, or if the fine-tuning method uses the
[preference](https://platform.openai.com/docs/api-reference/fine-tuning/preference-input) format.
See the [fine-tuning guide](https://platform.openai.com/docs/guides/model-optimization) for more
details.
type: string
example: file-abc123
hyperparameters:
type: object
description: >
The hyperparameters used for the fine-tuning job.
This value is now deprecated in favor of `method`, and should be passed in under the `method`
parameter.
properties:
batch_size:
description: |
Number of examples in each batch. A larger batch size means that model parameters
are updated less frequently, but with lower variance.
default: auto
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
title: Auto
- type: integer
minimum: 1
maximum: 256
learning_rate_multiplier:
description: |
Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
overfitting.
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
title: Auto
- type: number
minimum: 0
exclusiveMinimum: true
n_epochs:
description: |
The number of epochs to train the model for. An epoch refers to one full cycle
through the training dataset.
default: auto
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
title: Auto
- type: integer
minimum: 1
maximum: 50
deprecated: true
suffix:
description: >
A string of up to 64 characters that will be added to your fine-tuned model name.
For example, a `suffix` of "custom-model-name" would produce a model name like
`ft:gpt-4o-mini:openai:custom-model-name:7p4lURel`.
type: string
minLength: 1
maxLength: 64
default: null
nullable: true
validation_file:
description: >
The ID of an uploaded file that contains validation data.
If you provide this file, the data is used to generate validation
metrics periodically during fine-tuning. These metrics can be viewed in
the fine-tuning results file.
The same data should not be present in both train and validation files.
Your dataset must be formatted as a JSONL file. You must upload your file with the purpose
`fine-tune`.
See the [fine-tuning guide](https://platform.openai.com/docs/guides/model-optimization) for more
details.
type: string
nullable: true
example: file-abc123
integrations:
type: array
description: A list of integrations to enable for your fine-tuning job.
nullable: true
items:
type: object
required:
- type
- wandb
properties:
type:
description: >
The type of integration to enable. Currently, only "wandb" (Weights and Biases) is
supported.
anyOf:
- type: string
enum:
- wandb
x-stainless-const: true
wandb:
type: object
description: >
The settings for your integration with Weights and Biases. This payload specifies the
project that
metrics will be sent to. Optionally, you can set an explicit display name for your run, add
tags
to your run, and set a default entity (team, username, etc) to be associated with your run.
required:
- project
properties:
project:
description: |
The name of the project that the new run will be created under.
type: string
example: my-wandb-project
name:
description: |
A display name to set for the run. If not set, we will use the Job ID as the name.
nullable: true
type: string
entity:
description: >
The entity to use for the run. This allows you to set the team or username of the WandB
user that you would
like associated with the run. If not set, the default entity for the registered WandB
API key is used.
nullable: true
type: string
tags:
description: >
A list of tags to be attached to the newly created run. These tags are passed through
directly to WandB. Some
default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}",
"openai/{ftjob-abcdef}".
type: array
items:
type: string
example: custom-tag
seed:
description: >
The seed controls the reproducibility of the job. Passing in the same seed and job parameters
should produce the same results, but may differ in rare cases.
If a seed is not specified, one will be generated for you.
type: integer
nullable: true
minimum: 0
maximum: 2147483647
example: 42
method:
$ref: '#/components/schemas/FineTuneMethod'
metadata:
$ref: '#/components/schemas/Metadata'
required:
- model
- training_file
CreateImageEditRequest:
type: object
properties:
image:
anyOf:
- type: string
format: binary
- type: array
maxItems: 16
items:
type: string
format: binary
description: |
The image(s) to edit. Must be a supported image file or an array of images.
For `gpt-image-1`, each image should be a `png`, `webp`, or `jpg` file less
than 50MB. You can provide up to 16 images.
For `dall-e-2`, you can only provide one image, and it should be a square
`png` file less than 4MB.
x-oaiMeta:
exampleFilePath: otter.png
prompt:
description: >-
A text description of the desired image(s). The maximum length is 1000 characters for `dall-e-2`,
and 32000 characters for `gpt-image-1`.
type: string
example: A cute baby sea otter wearing a beret
mask:
description: >-
An additional image whose fully transparent areas (e.g. where alpha is zero) indicate where
`image` should be edited. If there are multiple images provided, the mask will be applied on the
first image. Must be a valid PNG file, less than 4MB, and have the same dimensions as `image`.
type: string
format: binary
x-oaiMeta:
exampleFilePath: mask.png
background:
type: string
enum:
- transparent
- opaque
- auto
default: auto
example: transparent
nullable: true
description: |
Allows to set transparency for the background of the generated image(s).
This parameter is only supported for `gpt-image-1`. Must be one of
`transparent`, `opaque` or `auto` (default value). When `auto` is used, the
model will automatically determine the best background for the image.
If `transparent`, the output format needs to support transparency, so it
should be set to either `png` (default value) or `webp`.
model:
anyOf:
- type: string
- type: string
enum:
- dall-e-2
- gpt-image-1
x-stainless-const: true
x-oaiTypeLabel: string
nullable: true
description: >-
The model to use for image generation. Only `dall-e-2` and `gpt-image-1` are supported. Defaults
to `dall-e-2` unless a parameter specific to `gpt-image-1` is used.
'n':
type: integer
minimum: 1
maximum: 10
default: 1
example: 1
nullable: true
description: The number of images to generate. Must be between 1 and 10.
size:
type: string
enum:
- 256x256
- 512x512
- 1024x1024
- 1536x1024
- 1024x1536
- auto
default: 1024x1024
example: 1024x1024
nullable: true
description: >-
The size of the generated images. Must be one of `1024x1024`, `1536x1024` (landscape), `1024x1536`
(portrait), or `auto` (default value) for `gpt-image-1`, and one of `256x256`, `512x512`, or
`1024x1024` for `dall-e-2`.
response_format:
type: string
enum:
- url
- b64_json
default: url
example: url
nullable: true
description: >-
The format in which the generated images are returned. Must be one of `url` or `b64_json`. URLs
are only valid for 60 minutes after the image has been generated. This parameter is only supported
for `dall-e-2`, as `gpt-image-1` will always return base64-encoded images.
output_format:
type: string
enum:
- png
- jpeg
- webp
default: png
example: png
nullable: true
description: |
The format in which the generated images are returned. This parameter is
only supported for `gpt-image-1`. Must be one of `png`, `jpeg`, or `webp`.
The default value is `png`.
output_compression:
type: integer
default: 100
example: 100
nullable: true
description: |
The compression level (0-100%) for the generated images. This parameter
is only supported for `gpt-image-1` with the `webp` or `jpeg` output
formats, and defaults to 100.
user:
type: string
example: user-1234
description: >
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
[Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).
input_fidelity:
$ref: '#/components/schemas/ImageInputFidelity'
stream:
type: boolean
default: false
example: false
nullable: true
description: >
Edit the image in streaming mode. Defaults to `false`. See the
[Image generation guide](https://platform.openai.com/docs/guides/image-generation) for more
information.
partial_images:
$ref: '#/components/schemas/PartialImages'
quality:
type: string
enum:
- standard
- low
- medium
- high
- auto
default: auto
example: high
nullable: true
description: >
The quality of the image that will be generated. `high`, `medium` and `low` are only supported for
`gpt-image-1`. `dall-e-2` only supports `standard` quality. Defaults to `auto`.
required:
- prompt
- image
CreateImageRequest:
type: object
properties:
prompt:
description: >-
A text description of the desired image(s). The maximum length is 32000 characters for
`gpt-image-1`, 1000 characters for `dall-e-2` and 4000 characters for `dall-e-3`.
type: string
example: A cute baby sea otter
model:
anyOf:
- type: string
- type: string
enum:
- dall-e-2
- dall-e-3
- gpt-image-1
x-stainless-nominal: false
x-oaiTypeLabel: string
nullable: true
description: >-
The model to use for image generation. One of `dall-e-2`, `dall-e-3`, or `gpt-image-1`. Defaults
to `dall-e-2` unless a parameter specific to `gpt-image-1` is used.
'n':
type: integer
minimum: 1
maximum: 10
default: 1
example: 1
nullable: true
description: >-
The number of images to generate. Must be between 1 and 10. For `dall-e-3`, only `n=1` is
supported.
quality:
type: string
enum:
- standard
- hd
- low
- medium
- high
- auto
default: auto
example: medium
nullable: true
description: |
The quality of the image that will be generated.
- `auto` (default value) will automatically select the best quality for the given model.
- `high`, `medium` and `low` are supported for `gpt-image-1`.
- `hd` and `standard` are supported for `dall-e-3`.
- `standard` is the only option for `dall-e-2`.
response_format:
type: string
enum:
- url
- b64_json
default: url
example: url
nullable: true
description: >-
The format in which generated images with `dall-e-2` and `dall-e-3` are returned. Must be one of
`url` or `b64_json`. URLs are only valid for 60 minutes after the image has been generated. This
parameter isn't supported for `gpt-image-1` which will always return base64-encoded images.
output_format:
type: string
enum:
- png
- jpeg
- webp
default: png
example: png
nullable: true
description: >-
The format in which the generated images are returned. This parameter is only supported for
`gpt-image-1`. Must be one of `png`, `jpeg`, or `webp`.
output_compression:
type: integer
default: 100
example: 100
nullable: true
description: >-
The compression level (0-100%) for the generated images. This parameter is only supported for
`gpt-image-1` with the `webp` or `jpeg` output formats, and defaults to 100.
stream:
type: boolean
default: false
example: false
nullable: true
description: >
Generate the image in streaming mode. Defaults to `false`. See the
[Image generation guide](https://platform.openai.com/docs/guides/image-generation) for more
information.
This parameter is only supported for `gpt-image-1`.
partial_images:
$ref: '#/components/schemas/PartialImages'
size:
type: string
enum:
- auto
- 1024x1024
- 1536x1024
- 1024x1536
- 256x256
- 512x512
- 1792x1024
- 1024x1792
default: auto
example: 1024x1024
nullable: true
description: >-
The size of the generated images. Must be one of `1024x1024`, `1536x1024` (landscape), `1024x1536`
(portrait), or `auto` (default value) for `gpt-image-1`, one of `256x256`, `512x512`, or
`1024x1024` for `dall-e-2`, and one of `1024x1024`, `1792x1024`, or `1024x1792` for `dall-e-3`.
moderation:
type: string
enum:
- low
- auto
default: auto
example: low
nullable: true
description: >-
Control the content-moderation level for images generated by `gpt-image-1`. Must be either `low`
for less restrictive filtering or `auto` (default value).
background:
type: string
enum:
- transparent
- opaque
- auto
default: auto
example: transparent
nullable: true
description: |
Allows to set transparency for the background of the generated image(s).
This parameter is only supported for `gpt-image-1`. Must be one of
`transparent`, `opaque` or `auto` (default value). When `auto` is used, the
model will automatically determine the best background for the image.
If `transparent`, the output format needs to support transparency, so it
should be set to either `png` (default value) or `webp`.
style:
type: string
enum:
- vivid
- natural
default: vivid
example: vivid
nullable: true
description: >-
The style of the generated images. This parameter is only supported for `dall-e-3`. Must be one of
`vivid` or `natural`. Vivid causes the model to lean towards generating hyper-real and dramatic
images. Natural causes the model to produce more natural, less hyper-real looking images.
user:
type: string
example: user-1234
description: >
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
[Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).
required:
- prompt
CreateImageVariationRequest:
type: object
properties:
image:
description: >-
The image to use as the basis for the variation(s). Must be a valid PNG file, less than 4MB, and
square.
type: string
format: binary
x-oaiMeta:
exampleFilePath: otter.png
model:
anyOf:
- type: string
- type: string
enum:
- dall-e-2
x-stainless-const: true
x-oaiTypeLabel: string
nullable: true
description: The model to use for image generation. Only `dall-e-2` is supported at this time.
'n':
type: integer
minimum: 1
maximum: 10
default: 1
example: 1
nullable: true
description: The number of images to generate. Must be between 1 and 10.
response_format:
type: string
enum:
- url
- b64_json
default: url
example: url
nullable: true
description: >-
The format in which the generated images are returned. Must be one of `url` or `b64_json`. URLs
are only valid for 60 minutes after the image has been generated.
size:
type: string
enum:
- 256x256
- 512x512
- 1024x1024
default: 1024x1024
example: 1024x1024
nullable: true
description: The size of the generated images. Must be one of `256x256`, `512x512`, or `1024x1024`.
user:
type: string
example: user-1234
description: >
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
[Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).
required:
- image
CreateMessageRequest:
type: object
additionalProperties: false
required:
- role
- content
properties:
role:
type: string
enum:
- user
- assistant
description: >
The role of the entity that is creating the message. Allowed values include:
- `user`: Indicates the message is sent by an actual user and should be used in most cases to
represent user-generated messages.
- `assistant`: Indicates the message is generated by the assistant. Use this value to insert
messages from the assistant into the conversation.
content:
anyOf:
- type: string
description: The text contents of the message.
title: Text content
- type: array
description: >-
An array of content parts with a defined type, each can be of type `text` or images can be
passed with `image_url` or `image_file`. Image types are only supported on [Vision-compatible
models](https://platform.openai.com/docs/models).
title: Array of content parts
items:
anyOf:
- $ref: '#/components/schemas/MessageContentImageFileObject'
- $ref: '#/components/schemas/MessageContentImageUrlObject'
- $ref: '#/components/schemas/MessageRequestContentTextObject'
discriminator:
propertyName: type
minItems: 1
attachments:
type: array
items:
type: object
properties:
file_id:
type: string
description: The ID of the file to attach to the message.
tools:
description: The tools to add this file to.
type: array
items:
anyOf:
- $ref: '#/components/schemas/AssistantToolsCode'
- $ref: '#/components/schemas/AssistantToolsFileSearchTypeOnly'
discriminator:
propertyName: type
description: A list of files attached to the message, and the tools they should be added to.
required:
- file_id
- tools
nullable: true
metadata:
$ref: '#/components/schemas/Metadata'
CreateModelResponseProperties:
allOf:
- $ref: '#/components/schemas/ModelResponseProperties'
- type: object
properties:
top_logprobs:
description: |
An integer between 0 and 20 specifying the number of most likely tokens to
return at each token position, each with an associated log probability.
type: integer
minimum: 0
maximum: 20
CreateModerationRequest:
type: object
properties:
input:
description: |
Input (or inputs) to classify. Can be a single string, an array of strings, or
an array of multi-modal input objects similar to other models.
anyOf:
- type: string
description: A string of text to classify for moderation.
default: ''
example: I want to kill them.
- type: array
description: An array of strings to classify for moderation.
items:
type: string
default: ''
example: I want to kill them.
- type: array
description: An array of multi-modal inputs to the moderation model.
items:
anyOf:
- $ref: '#/components/schemas/ModerationImageURLInput'
- $ref: '#/components/schemas/ModerationTextInput'
discriminator:
propertyName: type
title: Moderation Multi Modal Array
model:
description: |
The content moderation model you would like to use. Learn more in
[the moderation guide](https://platform.openai.com/docs/guides/moderation), and learn about
available models [here](https://platform.openai.com/docs/models#moderation).
nullable: false
anyOf:
- type: string
- type: string
enum:
- omni-moderation-latest
- omni-moderation-2024-09-26
- text-moderation-latest
- text-moderation-stable
x-stainless-nominal: false
x-oaiTypeLabel: string
required:
- input
CreateModerationResponse:
type: object
description: Represents if a given text input is potentially harmful.
properties:
id:
type: string
description: The unique identifier for the moderation request.
model:
type: string
description: The model used to generate the moderation results.
results:
type: array
description: A list of moderation objects.
items:
type: object
properties:
flagged:
type: boolean
description: Whether any of the below categories are flagged.
categories:
type: object
description: A list of the categories, and whether they are flagged or not.
properties:
hate:
type: boolean
description: >-
Content that expresses, incites, or promotes hate based on race, gender, ethnicity,
religion, nationality, sexual orientation, disability status, or caste. Hateful content
aimed at non-protected groups (e.g., chess players) is harassment.
hate/threatening:
type: boolean
description: >-
Hateful content that also includes violence or serious harm towards the targeted group
based on race, gender, ethnicity, religion, nationality, sexual orientation, disability
status, or caste.
harassment:
type: boolean
description: Content that expresses, incites, or promotes harassing language towards any target.
harassment/threatening:
type: boolean
description: Harassment content that also includes violence or serious harm towards any target.
illicit:
type: boolean
nullable: true
description: >-
Content that includes instructions or advice that facilitate the planning or execution
of wrongdoing, or that gives advice or instruction on how to commit illicit acts. For
example, "how to shoplift" would fit this category.
illicit/violent:
type: boolean
nullable: true
description: >-
Content that includes instructions or advice that facilitate the planning or execution
of wrongdoing that also includes violence, or that gives advice or instruction on the
procurement of any weapon.
self-harm:
type: boolean
description: >-
Content that promotes, encourages, or depicts acts of self-harm, such as suicide,
cutting, and eating disorders.
self-harm/intent:
type: boolean
description: >-
Content where the speaker expresses that they are engaging or intend to engage in acts
of self-harm, such as suicide, cutting, and eating disorders.
self-harm/instructions:
type: boolean
description: >-
Content that encourages performing acts of self-harm, such as suicide, cutting, and
eating disorders, or that gives instructions or advice on how to commit such acts.
sexual:
type: boolean
description: >-
Content meant to arouse sexual excitement, such as the description of sexual activity,
or that promotes sexual services (excluding sex education and wellness).
sexual/minors:
type: boolean
description: Sexual content that includes an individual who is under 18 years old.
violence:
type: boolean
description: Content that depicts death, violence, or physical injury.
violence/graphic:
type: boolean
description: Content that depicts death, violence, or physical injury in graphic detail.
required:
- hate
- hate/threatening
- harassment
- harassment/threatening
- illicit
- illicit/violent
- self-harm
- self-harm/intent
- self-harm/instructions
- sexual
- sexual/minors
- violence
- violence/graphic
category_scores:
type: object
description: A list of the categories along with their scores as predicted by model.
properties:
hate:
type: number
description: The score for the category 'hate'.
hate/threatening:
type: number
description: The score for the category 'hate/threatening'.
harassment:
type: number
description: The score for the category 'harassment'.
harassment/threatening:
type: number
description: The score for the category 'harassment/threatening'.
illicit:
type: number
description: The score for the category 'illicit'.
illicit/violent:
type: number
description: The score for the category 'illicit/violent'.
self-harm:
type: number
description: The score for the category 'self-harm'.
self-harm/intent:
type: number
description: The score for the category 'self-harm/intent'.
self-harm/instructions:
type: number
description: The score for the category 'self-harm/instructions'.
sexual:
type: number
description: The score for the category 'sexual'.
sexual/minors:
type: number
description: The score for the category 'sexual/minors'.
violence:
type: number
description: The score for the category 'violence'.
violence/graphic:
type: number
description: The score for the category 'violence/graphic'.
required:
- hate
- hate/threatening
- harassment
- harassment/threatening
- illicit
- illicit/violent
- self-harm
- self-harm/intent
- self-harm/instructions
- sexual
- sexual/minors
- violence
- violence/graphic
category_applied_input_types:
type: object
description: A list of the categories along with the input type(s) that the score applies to.
properties:
hate:
type: array
description: The applied input type(s) for the category 'hate'.
items:
type: string
enum:
- text
x-stainless-const: true
hate/threatening:
type: array
description: The applied input type(s) for the category 'hate/threatening'.
items:
type: string
enum:
- text
x-stainless-const: true
harassment:
type: array
description: The applied input type(s) for the category 'harassment'.
items:
type: string
enum:
- text
x-stainless-const: true
harassment/threatening:
type: array
description: The applied input type(s) for the category 'harassment/threatening'.
items:
type: string
enum:
- text
x-stainless-const: true
illicit:
type: array
description: The applied input type(s) for the category 'illicit'.
items:
type: string
enum:
- text
x-stainless-const: true
illicit/violent:
type: array
description: The applied input type(s) for the category 'illicit/violent'.
items:
type: string
enum:
- text
x-stainless-const: true
self-harm:
type: array
description: The applied input type(s) for the category 'self-harm'.
items:
type: string
enum:
- text
- image
self-harm/intent:
type: array
description: The applied input type(s) for the category 'self-harm/intent'.
items:
type: string
enum:
- text
- image
self-harm/instructions:
type: array
description: The applied input type(s) for the category 'self-harm/instructions'.
items:
type: string
enum:
- text
- image
sexual:
type: array
description: The applied input type(s) for the category 'sexual'.
items:
type: string
enum:
- text
- image
sexual/minors:
type: array
description: The applied input type(s) for the category 'sexual/minors'.
items:
type: string
enum:
- text
x-stainless-const: true
violence:
type: array
description: The applied input type(s) for the category 'violence'.
items:
type: string
enum:
- text
- image
violence/graphic:
type: array
description: The applied input type(s) for the category 'violence/graphic'.
items:
type: string
enum:
- text
- image
required:
- hate
- hate/threatening
- harassment
- harassment/threatening
- illicit
- illicit/violent
- self-harm
- self-harm/intent
- self-harm/instructions
- sexual
- sexual/minors
- violence
- violence/graphic
required:
- flagged
- categories
- category_scores
- category_applied_input_types
required:
- id
- model
- results
x-oaiMeta:
name: The moderation object
example: |
{
"id": "modr-0d9740456c391e43c445bf0f010940c7",
"model": "omni-moderation-latest",
"results": [
{
"flagged": true,
"categories": {
"harassment": true,
"harassment/threatening": true,
"sexual": false,
"hate": false,
"hate/threatening": false,
"illicit": false,
"illicit/violent": false,
"self-harm/intent": false,
"self-harm/instructions": false,
"self-harm": false,
"sexual/minors": false,
"violence": true,
"violence/graphic": true
},
"category_scores": {
"harassment": 0.8189693396524255,
"harassment/threatening": 0.804985420696006,
"sexual": 1.573112165348997e-6,
"hate": 0.007562942636942845,
"hate/threatening": 0.004208854591835476,
"illicit": 0.030535955153511665,
"illicit/violent": 0.008925306722380033,
"self-harm/intent": 0.00023023930975076432,
"self-harm/instructions": 0.0002293869201073356,
"self-harm": 0.012598046106750154,
"sexual/minors": 2.212566909570261e-8,
"violence": 0.9999992735124786,
"violence/graphic": 0.843064871157054
},
"category_applied_input_types": {
"harassment": [
"text"
],
"harassment/threatening": [
"text"
],
"sexual": [
"text",
"image"
],
"hate": [
"text"
],
"hate/threatening": [
"text"
],
"illicit": [
"text"
],
"illicit/violent": [
"text"
],
"self-harm/intent": [
"text",
"image"
],
"self-harm/instructions": [
"text",
"image"
],
"self-harm": [
"text",
"image"
],
"sexual/minors": [
"text"
],
"violence": [
"text",
"image"
],
"violence/graphic": [
"text",
"image"
]
}
}
]
}
CreateResponse:
allOf:
- $ref: '#/components/schemas/CreateModelResponseProperties'
- $ref: '#/components/schemas/ResponseProperties'
- type: object
properties:
input:
description: |
Text, image, or file inputs to the model, used to generate a response.
Learn more:
- [Text inputs and outputs](https://platform.openai.com/docs/guides/text)
- [Image inputs](https://platform.openai.com/docs/guides/images)
- [File inputs](https://platform.openai.com/docs/guides/pdf-files)
- [Conversation state](https://platform.openai.com/docs/guides/conversation-state)
- [Function calling](https://platform.openai.com/docs/guides/function-calling)
anyOf:
- type: string
title: Text input
description: |
A text input to the model, equivalent to a text input with the
`user` role.
- type: array
title: Input item list
description: |
A list of one or many input items to the model, containing
different content types.
items:
$ref: '#/components/schemas/InputItem'
include:
type: array
description: |
Specify additional output data to include in the model response. Currently
supported values are:
- `code_interpreter_call.outputs`: Includes the outputs of python code execution
in code interpreter tool call items.
- `computer_call_output.output.image_url`: Include image urls from the computer call output.
- `file_search_call.results`: Include the search results of
the file search tool call.
- `message.input_image.image_url`: Include image urls from the input message.
- `message.output_text.logprobs`: Include logprobs with assistant messages.
- `reasoning.encrypted_content`: Includes an encrypted version of reasoning
tokens in reasoning item outputs. This enables reasoning items to be used in
multi-turn conversations when using the Responses API statelessly (like
when the `store` parameter is set to `false`, or when an organization is
enrolled in the zero data retention program).
items:
$ref: '#/components/schemas/Includable'
nullable: true
parallel_tool_calls:
type: boolean
description: |
Whether to allow the model to run tool calls in parallel.
default: true
nullable: true
store:
type: boolean
description: |
Whether to store the generated model response for later retrieval via
API.
default: true
nullable: true
instructions:
type: string
nullable: true
description: |
A system (or developer) message inserted into the model's context.
When using along with `previous_response_id`, the instructions from a previous
response will not be carried over to the next response. This makes it simple
to swap out system (or developer) messages in new responses.
stream:
description: >
If set to true, the model response data will be streamed to the client
as it is generated using [server-sent
events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format).
See the [Streaming section
below](https://platform.openai.com/docs/api-reference/responses-streaming)
for more information.
type: boolean
nullable: true
default: false
stream_options:
$ref: '#/components/schemas/ResponseStreamOptions'
conversation:
description: >
The conversation that this response belongs to. Items from this conversation are prepended to
`input_items` for this response request.
Input items and output items from this response are automatically added to this conversation
after this response completes.
nullable: true
anyOf:
- type: string
title: Conversation ID
description: |
The unique ID of the conversation.
- $ref: '#/components/schemas/ConversationParam'
CreateRunRequest:
type: object
additionalProperties: false
properties:
assistant_id:
description: >-
The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) to use to
execute this run.
type: string
model:
description: >-
The ID of the [Model](https://platform.openai.com/docs/api-reference/models) to be used to execute
this run. If a value is provided here, it will override the model associated with the assistant.
If not, the model associated with the assistant will be used.
anyOf:
- type: string
- $ref: '#/components/schemas/AssistantSupportedModels'
x-oaiTypeLabel: string
nullable: true
reasoning_effort:
$ref: '#/components/schemas/ReasoningEffort'
instructions:
description: >-
Overrides the
[instructions](https://platform.openai.com/docs/api-reference/assistants/createAssistant) of the
assistant. This is useful for modifying the behavior on a per-run basis.
type: string
nullable: true
additional_instructions:
description: >-
Appends additional instructions at the end of the instructions for the run. This is useful for
modifying the behavior on a per-run basis without overriding other instructions.
type: string
nullable: true
additional_messages:
description: Adds additional messages to the thread before creating the run.
type: array
items:
$ref: '#/components/schemas/CreateMessageRequest'
nullable: true
tools:
description: >-
Override the tools the assistant can use for this run. This is useful for modifying the behavior
on a per-run basis.
nullable: true
type: array
maxItems: 20
items:
$ref: '#/components/schemas/AssistantTool'
metadata:
$ref: '#/components/schemas/Metadata'
temperature:
type: number
minimum: 0
maximum: 2
default: 1
example: 1
nullable: true
description: >
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
more random, while lower values like 0.2 will make it more focused and deterministic.
top_p:
type: number
minimum: 0
maximum: 1
default: 1
example: 1
nullable: true
description: >
An alternative to sampling with temperature, called nucleus sampling, where the model considers
the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
stream:
type: boolean
nullable: true
description: >
If `true`, returns a stream of events that happen during the Run as server-sent events,
terminating when the Run enters a terminal state with a `data: [DONE]` message.
max_prompt_tokens:
type: integer
nullable: true
description: >
The maximum number of prompt tokens that may be used over the course of the run. The run will make
a best effort to use only the number of prompt tokens specified, across multiple turns of the run.
If the run exceeds the number of prompt tokens specified, the run will end with status
`incomplete`. See `incomplete_details` for more info.
minimum: 256
max_completion_tokens:
type: integer
nullable: true
description: >
The maximum number of completion tokens that may be used over the course of the run. The run will
make a best effort to use only the number of completion tokens specified, across multiple turns of
the run. If the run exceeds the number of completion tokens specified, the run will end with
status `incomplete`. See `incomplete_details` for more info.
minimum: 256
truncation_strategy:
allOf:
- $ref: '#/components/schemas/TruncationObject'
- nullable: true
tool_choice:
allOf:
- $ref: '#/components/schemas/AssistantsApiToolChoiceOption'
- nullable: true
parallel_tool_calls:
$ref: '#/components/schemas/ParallelToolCalls'
response_format:
$ref: '#/components/schemas/AssistantsApiResponseFormatOption'
nullable: true
required: &ref_0
- assistant_id
CreateSpeechRequest:
type: object
additionalProperties: false
properties:
model:
description: >
One of the available [TTS models](https://platform.openai.com/docs/models#tts): `tts-1`,
`tts-1-hd` or `gpt-4o-mini-tts`.
anyOf:
- type: string
- type: string
enum:
- tts-1
- tts-1-hd
- gpt-4o-mini-tts
x-stainless-nominal: false
x-oaiTypeLabel: string
input:
type: string
description: The text to generate audio for. The maximum length is 4096 characters.
maxLength: 4096
instructions:
type: string
description: >-
Control the voice of your generated audio with additional instructions. Does not work with `tts-1`
or `tts-1-hd`.
maxLength: 4096
voice:
description: >-
The voice to use when generating the audio. Supported voices are `alloy`, `ash`, `ballad`,
`coral`, `echo`, `fable`, `onyx`, `nova`, `sage`, `shimmer`, and `verse`. Previews of the voices
are available in the [Text to speech
guide](https://platform.openai.com/docs/guides/text-to-speech#voice-options).
$ref: '#/components/schemas/VoiceIdsShared'
response_format:
description: The format to audio in. Supported formats are `mp3`, `opus`, `aac`, `flac`, `wav`, and `pcm`.
default: mp3
type: string
enum:
- mp3
- opus
- aac
- flac
- wav
- pcm
speed:
description: The speed of the generated audio. Select a value from `0.25` to `4.0`. `1.0` is the default.
type: number
default: 1
minimum: 0.25
maximum: 4
stream_format:
description: >-
The format to stream the audio in. Supported formats are `sse` and `audio`. `sse` is not supported
for `tts-1` or `tts-1-hd`.
type: string
default: audio
enum:
- sse
- audio
required:
- model
- input
- voice
CreateSpeechResponseStreamEvent:
anyOf:
- $ref: '#/components/schemas/SpeechAudioDeltaEvent'
- $ref: '#/components/schemas/SpeechAudioDoneEvent'
discriminator:
propertyName: type
CreateThreadAndRunRequest:
type: object
additionalProperties: false
properties:
assistant_id:
description: >-
The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) to use to
execute this run.
type: string
thread:
$ref: '#/components/schemas/CreateThreadRequest'
model:
description: >-
The ID of the [Model](https://platform.openai.com/docs/api-reference/models) to be used to execute
this run. If a value is provided here, it will override the model associated with the assistant.
If not, the model associated with the assistant will be used.
anyOf:
- type: string
- type: string
enum:
- gpt-5
- gpt-5-mini
- gpt-5-nano
- gpt-5-2025-08-07
- gpt-5-mini-2025-08-07
- gpt-5-nano-2025-08-07
- gpt-4.1
- gpt-4.1-mini
- gpt-4.1-nano
- gpt-4.1-2025-04-14
- gpt-4.1-mini-2025-04-14
- gpt-4.1-nano-2025-04-14
- gpt-4o
- gpt-4o-2024-11-20
- gpt-4o-2024-08-06
- gpt-4o-2024-05-13
- gpt-4o-mini
- gpt-4o-mini-2024-07-18
- gpt-4.5-preview
- gpt-4.5-preview-2025-02-27
- gpt-4-turbo
- gpt-4-turbo-2024-04-09
- gpt-4-0125-preview
- gpt-4-turbo-preview
- gpt-4-1106-preview
- gpt-4-vision-preview
- gpt-4
- gpt-4-0314
- gpt-4-0613
- gpt-4-32k
- gpt-4-32k-0314
- gpt-4-32k-0613
- gpt-3.5-turbo
- gpt-3.5-turbo-16k
- gpt-3.5-turbo-0613
- gpt-3.5-turbo-1106
- gpt-3.5-turbo-0125
- gpt-3.5-turbo-16k-0613
x-oaiTypeLabel: string
nullable: true
instructions:
description: >-
Override the default system message of the assistant. This is useful for modifying the behavior on
a per-run basis.
type: string
nullable: true
tools:
description: >-
Override the tools the assistant can use for this run. This is useful for modifying the behavior
on a per-run basis.
nullable: true
type: array
maxItems: 20
items:
$ref: '#/components/schemas/AssistantTool'
tool_resources:
type: object
description: >
A set of resources that are used by the assistant's tools. The resources are specific to the type
of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the
`file_search` tool requires a list of vector store IDs.
properties:
code_interpreter:
type: object
properties:
file_ids:
type: array
description: >
A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available
to the `code_interpreter` tool. There can be a maximum of 20 files associated with the
tool.
default: []
maxItems: 20
items:
type: string
file_search:
type: object
properties:
vector_store_ids:
type: array
description: >
The ID of the [vector
store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to
this assistant. There can be a maximum of 1 vector store attached to the assistant.
maxItems: 1
items:
type: string
nullable: true
metadata:
$ref: '#/components/schemas/Metadata'
temperature:
type: number
minimum: 0
maximum: 2
default: 1
example: 1
nullable: true
description: >
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
more random, while lower values like 0.2 will make it more focused and deterministic.
top_p:
type: number
minimum: 0
maximum: 1
default: 1
example: 1
nullable: true
description: >
An alternative to sampling with temperature, called nucleus sampling, where the model considers
the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
stream:
type: boolean
nullable: true
description: >
If `true`, returns a stream of events that happen during the Run as server-sent events,
terminating when the Run enters a terminal state with a `data: [DONE]` message.
max_prompt_tokens:
type: integer
nullable: true
description: >
The maximum number of prompt tokens that may be used over the course of the run. The run will make
a best effort to use only the number of prompt tokens specified, across multiple turns of the run.
If the run exceeds the number of prompt tokens specified, the run will end with status
`incomplete`. See `incomplete_details` for more info.
minimum: 256
max_completion_tokens:
type: integer
nullable: true
description: >
The maximum number of completion tokens that may be used over the course of the run. The run will
make a best effort to use only the number of completion tokens specified, across multiple turns of
the run. If the run exceeds the number of completion tokens specified, the run will end with
status `incomplete`. See `incomplete_details` for more info.
minimum: 256
truncation_strategy:
allOf:
- $ref: '#/components/schemas/TruncationObject'
- nullable: true
tool_choice:
allOf:
- $ref: '#/components/schemas/AssistantsApiToolChoiceOption'
- nullable: true
parallel_tool_calls:
$ref: '#/components/schemas/ParallelToolCalls'
response_format:
$ref: '#/components/schemas/AssistantsApiResponseFormatOption'
nullable: true
required: *ref_0
CreateThreadRequest:
type: object
description: |
Options to create a new thread. If no thread is provided when running a
request, an empty thread will be created.
additionalProperties: false
properties:
messages:
description: >-
A list of [messages](https://platform.openai.com/docs/api-reference/messages) to start the thread
with.
type: array
items:
$ref: '#/components/schemas/CreateMessageRequest'
tool_resources:
type: object
description: >
A set of resources that are made available to the assistant's tools in this thread. The resources
are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file
IDs, while the `file_search` tool requires a list of vector store IDs.
properties:
code_interpreter:
type: object
properties:
file_ids:
type: array
description: >
A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available
to the `code_interpreter` tool. There can be a maximum of 20 files associated with the
tool.
default: []
maxItems: 20
items:
type: string
file_search:
type: object
properties:
vector_store_ids:
type: array
description: >
The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object)
attached to this thread. There can be a maximum of 1 vector store attached to the thread.
maxItems: 1
items:
type: string
vector_stores:
type: array
description: >
A helper to create a [vector
store](https://platform.openai.com/docs/api-reference/vector-stores/object) with file_ids
and attach it to this thread. There can be a maximum of 1 vector store attached to the
thread.
maxItems: 1
items:
type: object
properties:
file_ids:
type: array
description: >
A list of [file](https://platform.openai.com/docs/api-reference/files) IDs to add to
the vector store. There can be a maximum of 10000 files in a vector store.
maxItems: 10000
items:
type: string
chunking_strategy:
type: object
description: >-
The chunking strategy used to chunk the file(s). If not set, will use the `auto`
strategy.
anyOf:
- type: object
title: Auto Chunking Strategy
description: >-
The default strategy. This strategy currently uses a `max_chunk_size_tokens` of
`800` and `chunk_overlap_tokens` of `400`.
additionalProperties: false
properties:
type:
type: string
description: Always `auto`.
enum:
- auto
x-stainless-const: true
required:
- type
- type: object
title: Static Chunking Strategy
additionalProperties: false
properties:
type:
type: string
description: Always `static`.
enum:
- static
x-stainless-const: true
static:
type: object
additionalProperties: false
properties:
max_chunk_size_tokens:
type: integer
minimum: 100
maximum: 4096
description: >-
The maximum number of tokens in each chunk. The default value is `800`.
The minimum value is `100` and the maximum value is `4096`.
chunk_overlap_tokens:
type: integer
description: >
The number of tokens that overlap between chunks. The default value is
`400`.
Note that the overlap must not exceed half of `max_chunk_size_tokens`.
required:
- max_chunk_size_tokens
- chunk_overlap_tokens
required:
- type
- static
x-stainless-naming:
java:
type_name: StaticObject
kotlin:
type_name: StaticObject
discriminator:
propertyName: type
metadata:
$ref: '#/components/schemas/Metadata'
anyOf:
- required:
- vector_store_ids
- required:
- vector_stores
nullable: true
metadata:
$ref: '#/components/schemas/Metadata'
CreateTranscriptionRequest:
type: object
additionalProperties: false
properties:
file:
description: >
The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4,
mpeg, mpga, m4a, ogg, wav, or webm.
type: string
x-oaiTypeLabel: file
format: binary
x-oaiMeta:
exampleFilePath: speech.mp3
model:
description: >
ID of the model to use. The options are `gpt-4o-transcribe`, `gpt-4o-mini-transcribe`, and
`whisper-1` (which is powered by our open source Whisper V2 model).
example: gpt-4o-transcribe
anyOf:
- type: string
- type: string
enum:
- whisper-1
- gpt-4o-transcribe
- gpt-4o-mini-transcribe
x-stainless-const: true
x-stainless-nominal: false
x-oaiTypeLabel: string
language:
description: >
The language of the input audio. Supplying the input language in
[ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format will improve
accuracy and latency.
type: string
prompt:
description: >
An optional text to guide the model's style or continue a previous audio segment. The
[prompt](https://platform.openai.com/docs/guides/speech-to-text#prompting) should match the audio
language.
type: string
response_format:
$ref: '#/components/schemas/AudioResponseFormat'
temperature:
description: >
The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more
random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the
model will use [log probability](https://en.wikipedia.org/wiki/Log_probability) to automatically
increase the temperature until certain thresholds are hit.
type: number
default: 0
stream:
description: >
If set to true, the model response data will be streamed to the client
as it is generated using [server-sent
events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format).
See the [Streaming section of the Speech-to-Text
guide](https://platform.openai.com/docs/guides/speech-to-text?lang=curl#streaming-transcriptions)
for more information.
Note: Streaming is not supported for the `whisper-1` model and will be ignored.
type: boolean
nullable: true
default: false
chunking_strategy:
$ref: '#/components/schemas/TranscriptionChunkingStrategy'
timestamp_granularities:
description: >
The timestamp granularities to populate for this transcription. `response_format` must be set
`verbose_json` to use timestamp granularities. Either or both of these options are supported:
`word`, or `segment`. Note: There is no additional latency for segment timestamps, but generating
word timestamps incurs additional latency.
type: array
items:
type: string
enum:
- word
- segment
default:
- segment
include:
description: |
Additional information to include in the transcription response.
`logprobs` will return the log probabilities of the tokens in the
response to understand the model's confidence in the transcription.
`logprobs` only works with response_format set to `json` and only with
the models `gpt-4o-transcribe` and `gpt-4o-mini-transcribe`.
type: array
items:
$ref: '#/components/schemas/TranscriptionInclude'
required:
- file
- model
CreateTranscriptionResponseJson:
type: object
description: Represents a transcription response returned by model, based on the provided input.
properties:
text:
type: string
description: The transcribed text.
logprobs:
type: array
optional: true
description: >
The log probabilities of the tokens in the transcription. Only returned with the models
`gpt-4o-transcribe` and `gpt-4o-mini-transcribe` if `logprobs` is added to the `include` array.
items:
type: object
properties:
token:
type: string
description: The token in the transcription.
logprob:
type: number
description: The log probability of the token.
bytes:
type: array
items:
type: number
description: The bytes of the token.
usage:
type: object
description: Token usage statistics for the request.
anyOf:
- $ref: '#/components/schemas/TranscriptTextUsageTokens'
title: Token Usage
- $ref: '#/components/schemas/TranscriptTextUsageDuration'
title: Duration Usage
discriminator:
propertyName: type
required:
- text
x-oaiMeta:
name: The transcription object (JSON)
group: audio
example: |
{
"text": "Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that.",
"usage": {
"type": "tokens",
"input_tokens": 14,
"input_token_details": {
"text_tokens": 10,
"audio_tokens": 4
},
"output_tokens": 101,
"total_tokens": 115
}
}
CreateTranscriptionResponseStreamEvent:
anyOf:
- $ref: '#/components/schemas/TranscriptTextDeltaEvent'
- $ref: '#/components/schemas/TranscriptTextDoneEvent'
discriminator:
propertyName: type
CreateTranscriptionResponseVerboseJson:
type: object
description: Represents a verbose json transcription response returned by model, based on the provided input.
properties:
language:
type: string
description: The language of the input audio.
duration:
type: number
description: The duration of the input audio.
text:
type: string
description: The transcribed text.
words:
type: array
description: Extracted words and their corresponding timestamps.
items:
$ref: '#/components/schemas/TranscriptionWord'
segments:
type: array
description: Segments of the transcribed text and their corresponding details.
items:
$ref: '#/components/schemas/TranscriptionSegment'
usage:
$ref: '#/components/schemas/TranscriptTextUsageDuration'
required:
- language
- duration
- text
x-oaiMeta:
name: The transcription object (Verbose JSON)
group: audio
example: |
{
"task": "transcribe",
"language": "english",
"duration": 8.470000267028809,
"text": "The beach was a popular spot on a hot summer day. People were swimming in the ocean, building sandcastles, and playing beach volleyball.",
"segments": [
{
"id": 0,
"seek": 0,
"start": 0.0,
"end": 3.319999933242798,
"text": " The beach was a popular spot on a hot summer day.",
"tokens": [
50364, 440, 7534, 390, 257, 3743, 4008, 322, 257, 2368, 4266, 786, 13, 50530
],
"temperature": 0.0,
"avg_logprob": -0.2860786020755768,
"compression_ratio": 1.2363636493682861,
"no_speech_prob": 0.00985979475080967
},
...
],
"usage": {
"type": "duration",
"seconds": 9
}
}
CreateTranslationRequest:
type: object
additionalProperties: false
properties:
file:
description: >
The audio file object (not file name) translate, in one of these formats: flac, mp3, mp4, mpeg,
mpga, m4a, ogg, wav, or webm.
type: string
x-oaiTypeLabel: file
format: binary
x-oaiMeta:
exampleFilePath: speech.mp3
model:
description: >
ID of the model to use. Only `whisper-1` (which is powered by our open source Whisper V2 model) is
currently available.
example: whisper-1
anyOf:
- type: string
- type: string
enum:
- whisper-1
x-stainless-const: true
x-oaiTypeLabel: string
prompt:
description: >
An optional text to guide the model's style or continue a previous audio segment. The
[prompt](https://platform.openai.com/docs/guides/speech-to-text#prompting) should be in English.
type: string
response_format:
description: >
The format of the output, in one of these options: `json`, `text`, `srt`, `verbose_json`, or
`vtt`.
type: string
enum:
- json
- text
- srt
- verbose_json
- vtt
default: json
temperature:
description: >
The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more
random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the
model will use [log probability](https://en.wikipedia.org/wiki/Log_probability) to automatically
increase the temperature until certain thresholds are hit.
type: number
default: 0
required:
- file
- model
CreateTranslationResponseJson:
type: object
properties:
text:
type: string
required:
- text
CreateTranslationResponseVerboseJson:
type: object
properties:
language:
type: string
description: The language of the output translation (always `english`).
duration:
type: number
description: The duration of the input audio.
text:
type: string
description: The translated text.
segments:
type: array
description: Segments of the translated text and their corresponding details.
items:
$ref: '#/components/schemas/TranscriptionSegment'
required:
- language
- duration
- text
CreateUploadRequest:
type: object
additionalProperties: false
properties:
filename:
description: |
The name of the file to upload.
type: string
purpose:
description: >
The intended purpose of the uploaded file.
See the [documentation on File
purposes](https://platform.openai.com/docs/api-reference/files/create#files-create-purpose).
type: string
enum:
- assistants
- batch
- fine-tune
- vision
bytes:
description: |
The number of bytes in the file you are uploading.
type: integer
mime_type:
description: >
The MIME type of the file.
This must fall within the supported MIME types for your file purpose. See the supported MIME types
for assistants and vision.
type: string
expires_after:
$ref: '#/components/schemas/FileExpirationAfter'
required:
- filename
- purpose
- bytes
- mime_type
CreateVectorStoreFileBatchRequest:
type: object
additionalProperties: false
properties:
file_ids:
description: >-
A list of [File](https://platform.openai.com/docs/api-reference/files) IDs that the vector store
should use. Useful for tools like `file_search` that can access files.
type: array
minItems: 1
maxItems: 500
items:
type: string
chunking_strategy:
$ref: '#/components/schemas/ChunkingStrategyRequestParam'
attributes:
$ref: '#/components/schemas/VectorStoreFileAttributes'
required:
- file_ids
CreateVectorStoreFileRequest:
type: object
additionalProperties: false
properties:
file_id:
description: >-
A [File](https://platform.openai.com/docs/api-reference/files) ID that the vector store should
use. Useful for tools like `file_search` that can access files.
type: string
chunking_strategy:
$ref: '#/components/schemas/ChunkingStrategyRequestParam'
attributes:
$ref: '#/components/schemas/VectorStoreFileAttributes'
required:
- file_id
CreateVectorStoreRequest:
type: object
additionalProperties: false
properties:
file_ids:
description: >-
A list of [File](https://platform.openai.com/docs/api-reference/files) IDs that the vector store
should use. Useful for tools like `file_search` that can access files.
type: array
maxItems: 500
items:
type: string
name:
description: The name of the vector store.
type: string
expires_after:
$ref: '#/components/schemas/VectorStoreExpirationAfter'
chunking_strategy:
$ref: '#/components/schemas/ChunkingStrategyRequestParam'
metadata:
$ref: '#/components/schemas/Metadata'
CustomTool:
type: object
title: Custom tool
description: |
A custom tool that processes input using a specified format. Learn more about
[custom tools](https://platform.openai.com/docs/guides/function-calling#custom-tools).
properties:
type:
type: string
enum:
- custom
description: The type of the custom tool. Always `custom`.
x-stainless-const: true
name:
type: string
description: The name of the custom tool, used to identify it in tool calls.
description:
type: string
description: |
Optional description of the custom tool, used to provide more context.
format:
description: |
The input format for the custom tool. Default is unconstrained text.
anyOf:
- type: object
title: Text format
description: Unconstrained free-form text.
properties:
type:
type: string
enum:
- text
description: Unconstrained text format. Always `text`.
x-stainless-const: true
required:
- type
additionalProperties: false
- type: object
title: Grammar format
description: A grammar defined by the user.
properties:
type:
type: string
enum:
- grammar
description: Grammar format. Always `grammar`.
x-stainless-const: true
definition:
type: string
description: The grammar definition.
syntax:
type: string
description: The syntax of the grammar definition. One of `lark` or `regex`.
enum:
- lark
- regex
required:
- type
- definition
- syntax
additionalProperties: false
discriminator:
propertyName: type
required:
- type
- name
CustomToolCall:
type: object
title: Custom tool call
description: |
A call to a custom tool created by the model.
properties:
type:
type: string
enum:
- custom_tool_call
x-stainless-const: true
description: |
The type of the custom tool call. Always `custom_tool_call`.
id:
type: string
description: |
The unique ID of the custom tool call in the OpenAI platform.
call_id:
type: string
description: |
An identifier used to map this custom tool call to a tool call output.
name:
type: string
description: |
The name of the custom tool being called.
input:
type: string
description: |
The input for the custom tool call generated by the model.
required:
- type
- call_id
- name
- input
CustomToolCallOutput:
type: object
title: Custom tool call output
description: |
The output of a custom tool call from your code, being sent back to the model.
properties:
type:
type: string
enum:
- custom_tool_call_output
x-stainless-const: true
description: |
The type of the custom tool call output. Always `custom_tool_call_output`.
id:
type: string
description: |
The unique ID of the custom tool call output in the OpenAI platform.
call_id:
type: string
description: |
The call ID, used to map this custom tool call output to a custom tool call.
output:
type: string
description: |
The output from the custom tool call generated by your code.
required:
- type
- call_id
- output
CustomToolChatCompletions:
type: object
title: Custom tool
description: |
A custom tool that processes input using a specified format.
properties:
type:
type: string
enum:
- custom
description: The type of the custom tool. Always `custom`.
x-stainless-const: true
custom:
type: object
title: Custom tool properties
description: |
Properties of the custom tool.
properties:
name:
type: string
description: The name of the custom tool, used to identify it in tool calls.
description:
type: string
description: |
Optional description of the custom tool, used to provide more context.
format:
description: |
The input format for the custom tool. Default is unconstrained text.
anyOf:
- type: object
title: Text format
description: Unconstrained free-form text.
properties:
type:
type: string
enum:
- text
description: Unconstrained text format. Always `text`.
x-stainless-const: true
required:
- type
additionalProperties: false
- type: object
title: Grammar format
description: A grammar defined by the user.
properties:
type:
type: string
enum:
- grammar
description: Grammar format. Always `grammar`.
x-stainless-const: true
grammar:
type: object
title: Grammar format
description: Your chosen grammar.
properties:
definition:
type: string
description: The grammar definition.
syntax:
type: string
description: The syntax of the grammar definition. One of `lark` or `regex`.
enum:
- lark
- regex
required:
- definition
- syntax
required:
- type
- grammar
additionalProperties: false
discriminator:
propertyName: type
required:
- name
required:
- type
- custom
DeleteAssistantResponse:
type: object
properties:
id:
type: string
deleted:
type: boolean
object:
type: string
enum:
- assistant.deleted
x-stainless-const: true
required:
- id
- object
- deleted
DeleteCertificateResponse:
type: object
properties:
object:
description: The object type, must be `certificate.deleted`.
x-stainless-const: true
const: certificate.deleted
id:
type: string
description: The ID of the certificate that was deleted.
required:
- object
- id
DeleteFileResponse:
type: object
properties:
id:
type: string
object:
type: string
enum:
- file
x-stainless-const: true
deleted:
type: boolean
required:
- id
- object
- deleted
DeleteFineTuningCheckpointPermissionResponse:
type: object
properties:
id:
type: string
description: The ID of the fine-tuned model checkpoint permission that was deleted.
object:
type: string
description: The object type, which is always "checkpoint.permission".
enum:
- checkpoint.permission
x-stainless-const: true
deleted:
type: boolean
description: Whether the fine-tuned model checkpoint permission was successfully deleted.
required:
- id
- object
- deleted
DeleteMessageResponse:
type: object
properties:
id:
type: string
deleted:
type: boolean
object:
type: string
enum:
- thread.message.deleted
x-stainless-const: true
required:
- id
- object
- deleted
DeleteModelResponse:
type: object
properties:
id:
type: string
deleted:
type: boolean
object:
type: string
required:
- id
- object
- deleted
DeleteThreadResponse:
type: object
properties:
id:
type: string
deleted:
type: boolean
object:
type: string
enum:
- thread.deleted
x-stainless-const: true
required:
- id
- object
- deleted
DeleteVectorStoreFileResponse:
type: object
properties:
id:
type: string
deleted:
type: boolean
object:
type: string
enum:
- vector_store.file.deleted
x-stainless-const: true
required:
- id
- object
- deleted
DeleteVectorStoreResponse:
type: object
properties:
id:
type: string
deleted:
type: boolean
object:
type: string
enum:
- vector_store.deleted
x-stainless-const: true
required:
- id
- object
- deleted
DeletedConversation:
title: The deleted conversation object
allOf:
- $ref: '#/components/schemas/DeletedConversationResource'
x-oaiMeta:
name: The deleted conversation object
group: conversations
DoneEvent:
type: object
properties:
event:
type: string
enum:
- done
x-stainless-const: true
data:
type: string
enum:
- '[DONE]'
x-stainless-const: true
required:
- event
- data
description: Occurs when a stream ends.
x-oaiMeta:
dataDescription: '`data` is `[DONE]`'
DoubleClick:
type: object
title: DoubleClick
description: |
A double click action.
properties:
type:
type: string
enum:
- double_click
default: double_click
description: |
Specifies the event type. For a double click action, this property is
always set to `double_click`.
x-stainless-const: true
x:
type: integer
description: |
The x-coordinate where the double click occurred.
'y':
type: integer
description: |
The y-coordinate where the double click occurred.
required:
- type
- x
- 'y'
Drag:
type: object
title: Drag
description: |
A drag action.
properties:
type:
type: string
enum:
- drag
default: drag
description: |
Specifies the event type. For a drag action, this property is
always set to `drag`.
x-stainless-const: true
path:
type: array
description: >
An array of coordinates representing the path of the drag action. Coordinates will appear as an
array
of objects, eg
```
[
{ x: 100, y: 200 },
{ x: 200, y: 300 }
]
```
items:
title: Drag path coordinates
description: |
A series of x/y coordinate pairs in the drag path.
$ref: '#/components/schemas/Coordinate'
required:
- type
- path
EasyInputMessage:
type: object
title: Input message
description: |
A message input to the model with a role indicating instruction following
hierarchy. Instructions given with the `developer` or `system` role take
precedence over instructions given with the `user` role. Messages with the
`assistant` role are presumed to have been generated by the model in previous
interactions.
properties:
role:
type: string
description: |
The role of the message input. One of `user`, `assistant`, `system`, or
`developer`.
enum:
- user
- assistant
- system
- developer
content:
description: |
Text, image, or audio input to the model, used to generate a response.
Can also contain previous assistant responses.
anyOf:
- type: string
title: Text input
description: |
A text input to the model.
- $ref: '#/components/schemas/InputMessageContentList'
type:
type: string
description: |
The type of the message input. Always `message`.
enum:
- message
x-stainless-const: true
required:
- role
- content
Embedding:
type: object
description: |
Represents an embedding vector returned by embedding endpoint.
properties:
index:
type: integer
description: The index of the embedding in the list of embeddings.
embedding:
type: array
description: >
The embedding vector, which is a list of floats. The length of vector depends on the model as
listed in the [embedding guide](https://platform.openai.com/docs/guides/embeddings).
items:
type: number
format: float
object:
type: string
description: The object type, which is always "embedding".
enum:
- embedding
x-stainless-const: true
required:
- index
- object
- embedding
x-oaiMeta:
name: The embedding object
example: |
{
"object": "embedding",
"embedding": [
0.0023064255,
-0.009327292,
.... (1536 floats total for ada-002)
-0.0028842222,
],
"index": 0
}
Error:
type: object
properties:
code:
type: string
nullable: true
message:
type: string
nullable: false
param:
type: string
nullable: true
type:
type: string
nullable: false
required:
- type
- message
- param
- code
ErrorEvent:
type: object
properties:
event:
type: string
enum:
- error
x-stainless-const: true
data:
$ref: '#/components/schemas/Error'
required:
- event
- data
description: >-
Occurs when an [error](https://platform.openai.com/docs/guides/error-codes#api-errors) occurs. This
can happen due to an internal server error or a timeout.
x-oaiMeta:
dataDescription: '`data` is an [error](/docs/guides/error-codes#api-errors)'
ErrorResponse:
type: object
properties:
error:
$ref: '#/components/schemas/Error'
required:
- error
Eval:
type: object
title: Eval
description: |
An Eval object with a data source config and testing criteria.
An Eval represents a task to be done for your LLM integration.
Like:
- Improve the quality of my chatbot
- See how well my chatbot handles customer support
- Check if o4-mini is better at my usecase than gpt-4o
properties:
object:
type: string
enum:
- eval
default: eval
description: The object type.
x-stainless-const: true
id:
type: string
description: Unique identifier for the evaluation.
name:
type: string
description: The name of the evaluation.
example: Chatbot effectiveness Evaluation
data_source_config:
type: object
description: Configuration of data sources used in runs of the evaluation.
anyOf:
- $ref: '#/components/schemas/EvalCustomDataSourceConfig'
- $ref: '#/components/schemas/EvalLogsDataSourceConfig'
- $ref: '#/components/schemas/EvalStoredCompletionsDataSourceConfig'
discriminator:
propertyName: type
testing_criteria:
description: A list of testing criteria.
type: array
items:
anyOf:
- $ref: '#/components/schemas/EvalGraderLabelModel'
- $ref: '#/components/schemas/EvalGraderStringCheck'
- $ref: '#/components/schemas/EvalGraderTextSimilarity'
- $ref: '#/components/schemas/EvalGraderPython'
- $ref: '#/components/schemas/EvalGraderScoreModel'
created_at:
type: integer
description: The Unix timestamp (in seconds) for when the eval was created.
metadata:
$ref: '#/components/schemas/Metadata'
required:
- id
- data_source_config
- object
- testing_criteria
- name
- created_at
- metadata
x-oaiMeta:
name: The eval object
group: evals
example: |
{
"object": "eval",
"id": "eval_67abd54d9b0081909a86353f6fb9317a",
"data_source_config": {
"type": "custom",
"item_schema": {
"type": "object",
"properties": {
"label": {"type": "string"},
},
"required": ["label"]
},
"include_sample_schema": true
},
"testing_criteria": [
{
"name": "My string check grader",
"type": "string_check",
"input": "{{sample.output_text}}",
"reference": "{{item.label}}",
"operation": "eq",
}
],
"name": "External Data Eval",
"created_at": 1739314509,
"metadata": {
"test": "synthetics",
}
}
EvalApiError:
type: object
title: EvalApiError
description: |
An object representing an error response from the Eval API.
properties:
code:
type: string
description: The error code.
message:
type: string
description: The error message.
required:
- code
- message
x-oaiMeta:
name: The API error object
group: evals
example: |
{
"code": "internal_error",
"message": "The eval run failed due to an internal error."
}
EvalCustomDataSourceConfig:
type: object
title: CustomDataSourceConfig
description: |
A CustomDataSourceConfig which specifies the schema of your `item` and optionally `sample` namespaces.
The response schema defines the shape of the data that will be:
- Used to define your testing criteria and
- What data is required when creating a run
properties:
type:
type: string
enum:
- custom
default: custom
description: The type of data source. Always `custom`.
x-stainless-const: true
schema:
type: object
description: |
The json schema for the run data source items.
Learn how to build JSON schemas [here](https://json-schema.org/).
additionalProperties: true
required:
- type
- schema
x-oaiMeta:
name: The eval custom data source config object
group: evals
example: |
{
"type": "custom",
"schema": {
"type": "object",
"properties": {
"item": {
"type": "object",
"properties": {
"label": {"type": "string"},
},
"required": ["label"]
}
},
"required": ["item"]
}
}
EvalGraderLabelModel:
type: object
title: LabelModelGrader
allOf:
- $ref: '#/components/schemas/GraderLabelModel'
EvalGraderPython:
type: object
title: PythonGrader
allOf:
- $ref: '#/components/schemas/GraderPython'
- type: object
properties:
pass_threshold:
type: number
description: The threshold for the score.
x-oaiMeta:
name: Eval Python Grader
group: graders
example: |
{
"type": "python",
"name": "Example python grader",
"image_tag": "2025-05-08",
"source": """
def grade(sample: dict, item: dict) -> float:
\"""
Returns 1.0 if `output_text` equals `label`, otherwise 0.0.
\"""
output = sample.get("output_text")
label = item.get("label")
return 1.0 if output == label else 0.0
""",
"pass_threshold": 0.8
}
EvalGraderScoreModel:
type: object
title: ScoreModelGrader
allOf:
- $ref: '#/components/schemas/GraderScoreModel'
- type: object
properties:
pass_threshold:
type: number
description: The threshold for the score.
EvalGraderStringCheck:
type: object
title: StringCheckGrader
allOf:
- $ref: '#/components/schemas/GraderStringCheck'
EvalGraderTextSimilarity:
type: object
title: TextSimilarityGrader
allOf:
- $ref: '#/components/schemas/GraderTextSimilarity'
- type: object
properties:
pass_threshold:
type: number
description: The threshold for the score.
required:
- pass_threshold
x-oaiMeta:
name: Text Similarity Grader
group: graders
example: |
{
"type": "text_similarity",
"name": "Example text similarity grader",
"input": "{{sample.output_text}}",
"reference": "{{item.label}}",
"pass_threshold": 0.8,
"evaluation_metric": "fuzzy_match"
}
EvalItem:
type: object
title: Eval message object
description: |
A message input to the model with a role indicating instruction following
hierarchy. Instructions given with the `developer` or `system` role take
precedence over instructions given with the `user` role. Messages with the
`assistant` role are presumed to have been generated by the model in previous
interactions.
properties:
role:
type: string
description: |
The role of the message input. One of `user`, `assistant`, `system`, or
`developer`.
enum:
- user
- assistant
- system
- developer
content:
description: |
Inputs to the model - can contain template strings.
anyOf:
- type: string
title: Text input
description: |
A text input to the model.
- $ref: '#/components/schemas/InputTextContent'
- type: object
title: Output text
description: |
A text output from the model.
properties:
type:
type: string
description: |
The type of the output text. Always `output_text`.
enum:
- output_text
x-stainless-const: true
text:
type: string
description: |
The text output from the model.
required:
- type
- text
- type: object
title: Input image
description: |
An image input to the model.
properties:
type:
type: string
description: |
The type of the image input. Always `input_image`.
enum:
- input_image
x-stainless-const: true
image_url:
type: string
description: |
The URL of the image input.
detail:
type: string
description: >
The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`.
Defaults to `auto`.
required:
- type
- image_url
- type: array
title: An array of Input text and Input image
description: |
A list of inputs, each of which may be either an input text or input image object.
type:
type: string
description: |
The type of the message input. Always `message`.
enum:
- message
x-stainless-const: true
required:
- role
- content
EvalJsonlFileContentSource:
type: object
title: EvalJsonlFileContentSource
properties:
type:
type: string
enum:
- file_content
default: file_content
description: The type of jsonl source. Always `file_content`.
x-stainless-const: true
content:
type: array
items:
type: object
properties:
item:
type: object
additionalProperties: true
sample:
type: object
additionalProperties: true
required:
- item
description: The content of the jsonl file.
required:
- type
- content
EvalJsonlFileIdSource:
type: object
title: EvalJsonlFileIdSource
properties:
type:
type: string
enum:
- file_id
default: file_id
description: The type of jsonl source. Always `file_id`.
x-stainless-const: true
id:
type: string
description: The identifier of the file.
required:
- type
- id
EvalList:
type: object
title: EvalList
description: |
An object representing a list of evals.
properties:
object:
type: string
enum:
- list
default: list
description: |
The type of this object. It is always set to "list".
x-stainless-const: true
data:
type: array
description: |
An array of eval objects.
items:
$ref: '#/components/schemas/Eval'
first_id:
type: string
description: The identifier of the first eval in the data array.
last_id:
type: string
description: The identifier of the last eval in the data array.
has_more:
type: boolean
description: Indicates whether there are more evals available.
required:
- object
- data
- first_id
- last_id
- has_more
x-oaiMeta:
name: The eval list object
group: evals
example: |
{
"object": "list",
"data": [
{
"object": "eval",
"id": "eval_67abd54d9b0081909a86353f6fb9317a",
"data_source_config": {
"type": "custom",
"schema": {
"type": "object",
"properties": {
"item": {
"type": "object",
"properties": {
"input": {
"type": "string"
},
"ground_truth": {
"type": "string"
}
},
"required": [
"input",
"ground_truth"
]
}
},
"required": [
"item"
]
}
},
"testing_criteria": [
{
"name": "String check",
"id": "String check-2eaf2d8d-d649-4335-8148-9535a7ca73c2",
"type": "string_check",
"input": "{{item.input}}",
"reference": "{{item.ground_truth}}",
"operation": "eq"
}
],
"name": "External Data Eval",
"created_at": 1739314509,
"metadata": {},
}
],
"first_id": "eval_67abd54d9b0081909a86353f6fb9317a",
"last_id": "eval_67abd54d9b0081909a86353f6fb9317a",
"has_more": true
}
EvalLogsDataSourceConfig:
type: object
title: LogsDataSourceConfig
description: >
A LogsDataSourceConfig which specifies the metadata property of your logs query.
This is usually metadata like `usecase=chatbot` or `prompt-version=v2`, etc.
The schema returned by this data source config is used to defined what variables are available in your
evals.
`item` and `sample` are both defined when using this data source config.
properties:
type:
type: string
enum:
- logs
default: logs
description: The type of data source. Always `logs`.
x-stainless-const: true
metadata:
$ref: '#/components/schemas/Metadata'
schema:
type: object
description: |
The json schema for the run data source items.
Learn how to build JSON schemas [here](https://json-schema.org/).
additionalProperties: true
required:
- type
- schema
x-oaiMeta:
name: The logs data source object for evals
group: evals
example: |
{
"type": "logs",
"metadata": {
"language": "english"
},
"schema": {
"type": "object",
"properties": {
"item": {
"type": "object"
},
"sample": {
"type": "object"
}
},
"required": [
"item",
"sample"
}
}
EvalResponsesSource:
type: object
title: EvalResponsesSource
description: |
A EvalResponsesSource object describing a run data source configuration.
properties:
type:
type: string
enum:
- responses
description: The type of run data source. Always `responses`.
metadata:
type: object
nullable: true
description: Metadata filter for the responses. This is a query parameter used to select responses.
model:
type: string
nullable: true
description: The name of the model to find responses for. This is a query parameter used to select responses.
instructions_search:
type: string
nullable: true
description: >-
Optional string to search the 'instructions' field. This is a query parameter used to select
responses.
created_after:
type: integer
minimum: 0
nullable: true
description: >-
Only include items created after this timestamp (inclusive). This is a query parameter used to
select responses.
created_before:
type: integer
minimum: 0
nullable: true
description: >-
Only include items created before this timestamp (inclusive). This is a query parameter used to
select responses.
reasoning_effort:
$ref: '#/components/schemas/ReasoningEffort'
nullable: true
description: Optional reasoning effort parameter. This is a query parameter used to select responses.
temperature:
type: number
nullable: true
description: Sampling temperature. This is a query parameter used to select responses.
top_p:
type: number
nullable: true
description: Nucleus sampling parameter. This is a query parameter used to select responses.
users:
type: array
items:
type: string
nullable: true
description: List of user identifiers. This is a query parameter used to select responses.
tools:
type: array
items:
type: string
nullable: true
description: List of tool names. This is a query parameter used to select responses.
required:
- type
x-oaiMeta:
name: The run data source object used to configure an individual run
group: eval runs
example: |
{
"type": "responses",
"model": "gpt-4o-mini-2024-07-18",
"temperature": 0.7,
"top_p": 1.0,
"users": ["user1", "user2"],
"tools": ["tool1", "tool2"],
"instructions_search": "You are a coding assistant"
}
EvalRun:
type: object
title: EvalRun
description: |
A schema representing an evaluation run.
properties:
object:
type: string
enum:
- eval.run
default: eval.run
description: The type of the object. Always "eval.run".
x-stainless-const: true
id:
type: string
description: Unique identifier for the evaluation run.
eval_id:
type: string
description: The identifier of the associated evaluation.
status:
type: string
description: The status of the evaluation run.
model:
type: string
description: The model that is evaluated, if applicable.
name:
type: string
description: The name of the evaluation run.
created_at:
type: integer
description: Unix timestamp (in seconds) when the evaluation run was created.
report_url:
type: string
description: The URL to the rendered evaluation run report on the UI dashboard.
result_counts:
type: object
description: Counters summarizing the outcomes of the evaluation run.
properties:
total:
type: integer
description: Total number of executed output items.
errored:
type: integer
description: Number of output items that resulted in an error.
failed:
type: integer
description: Number of output items that failed to pass the evaluation.
passed:
type: integer
description: Number of output items that passed the evaluation.
required:
- total
- errored
- failed
- passed
per_model_usage:
type: array
description: Usage statistics for each model during the evaluation run.
items:
type: object
properties:
model_name:
type: string
description: The name of the model.
x-stainless-naming:
python:
property_name: run_model_name
invocation_count:
type: integer
description: The number of invocations.
prompt_tokens:
type: integer
description: The number of prompt tokens used.
completion_tokens:
type: integer
description: The number of completion tokens generated.
total_tokens:
type: integer
description: The total number of tokens used.
cached_tokens:
type: integer
description: The number of tokens retrieved from cache.
required:
- model_name
- invocation_count
- prompt_tokens
- completion_tokens
- total_tokens
- cached_tokens
per_testing_criteria_results:
type: array
description: Results per testing criteria applied during the evaluation run.
items:
type: object
properties:
testing_criteria:
type: string
description: A description of the testing criteria.
passed:
type: integer
description: Number of tests passed for this criteria.
failed:
type: integer
description: Number of tests failed for this criteria.
required:
- testing_criteria
- passed
- failed
data_source:
type: object
description: Information about the run's data source.
anyOf:
- $ref: '#/components/schemas/CreateEvalJsonlRunDataSource'
- $ref: '#/components/schemas/CreateEvalCompletionsRunDataSource'
- $ref: '#/components/schemas/CreateEvalResponsesRunDataSource'
discriminator:
propertyName: type
metadata:
$ref: '#/components/schemas/Metadata'
error:
$ref: '#/components/schemas/EvalApiError'
required:
- object
- id
- eval_id
- status
- model
- name
- created_at
- report_url
- result_counts
- per_model_usage
- per_testing_criteria_results
- data_source
- metadata
- error
x-oaiMeta:
name: The eval run object
group: evals
example: |
{
"object": "eval.run",
"id": "evalrun_67e57965b480819094274e3a32235e4c",
"eval_id": "eval_67e579652b548190aaa83ada4b125f47",
"report_url": "https://platform.openai.com/evaluations/eval_67e579652b548190aaa83ada4b125f47?run_id=evalrun_67e57965b480819094274e3a32235e4c",
"status": "queued",
"model": "gpt-4o-mini",
"name": "gpt-4o-mini",
"created_at": 1743092069,
"result_counts": {
"total": 0,
"errored": 0,
"failed": 0,
"passed": 0
},
"per_model_usage": null,
"per_testing_criteria_results": null,
"data_source": {
"type": "completions",
"source": {
"type": "file_content",
"content": [
{
"item": {
"input": "Tech Company Launches Advanced Artificial Intelligence Platform",
"ground_truth": "Technology"
}
},
{
"item": {
"input": "Central Bank Increases Interest Rates Amid Inflation Concerns",
"ground_truth": "Markets"
}
},
{
"item": {
"input": "International Summit Addresses Climate Change Strategies",
"ground_truth": "World"
}
},
{
"item": {
"input": "Major Retailer Reports Record-Breaking Holiday Sales",
"ground_truth": "Business"
}
},
{
"item": {
"input": "National Team Qualifies for World Championship Finals",
"ground_truth": "Sports"
}
},
{
"item": {
"input": "Stock Markets Rally After Positive Economic Data Released",
"ground_truth": "Markets"
}
},
{
"item": {
"input": "Global Manufacturer Announces Merger with Competitor",
"ground_truth": "Business"
}
},
{
"item": {
"input": "Breakthrough in Renewable Energy Technology Unveiled",
"ground_truth": "Technology"
}
},
{
"item": {
"input": "World Leaders Sign Historic Climate Agreement",
"ground_truth": "World"
}
},
{
"item": {
"input": "Professional Athlete Sets New Record in Championship Event",
"ground_truth": "Sports"
}
},
{
"item": {
"input": "Financial Institutions Adapt to New Regulatory Requirements",
"ground_truth": "Business"
}
},
{
"item": {
"input": "Tech Conference Showcases Advances in Artificial Intelligence",
"ground_truth": "Technology"
}
},
{
"item": {
"input": "Global Markets Respond to Oil Price Fluctuations",
"ground_truth": "Markets"
}
},
{
"item": {
"input": "International Cooperation Strengthened Through New Treaty",
"ground_truth": "World"
}
},
{
"item": {
"input": "Sports League Announces Revised Schedule for Upcoming Season",
"ground_truth": "Sports"
}
}
]
},
"input_messages": {
"type": "template",
"template": [
{
"type": "message",
"role": "developer",
"content": {
"type": "input_text",
"text": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\" \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\" \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\" \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\" \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\" \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n"
}
},
{
"type": "message",
"role": "user",
"content": {
"type": "input_text",
"text": "{{item.input}}"
}
}
]
},
"model": "gpt-4o-mini",
"sampling_params": {
"seed": 42,
"temperature": 1.0,
"top_p": 1.0,
"max_completions_tokens": 2048
}
},
"error": null,
"metadata": {}
}
EvalRunList:
type: object
title: EvalRunList
description: |
An object representing a list of runs for an evaluation.
properties:
object:
type: string
enum:
- list
default: list
description: |
The type of this object. It is always set to "list".
x-stainless-const: true
data:
type: array
description: |
An array of eval run objects.
items:
$ref: '#/components/schemas/EvalRun'
first_id:
type: string
description: The identifier of the first eval run in the data array.
last_id:
type: string
description: The identifier of the last eval run in the data array.
has_more:
type: boolean
description: Indicates whether there are more evals available.
required:
- object
- data
- first_id
- last_id
- has_more
x-oaiMeta:
name: The eval run list object
group: evals
example: |
{
"object": "list",
"data": [
{
"object": "eval.run",
"id": "evalrun_67b7fbdad46c819092f6fe7a14189620",
"eval_id": "eval_67b7fa9a81a88190ab4aa417e397ea21",
"report_url": "https://platform.openai.com/evaluations/eval_67b7fa9a81a88190ab4aa417e397ea21?run_id=evalrun_67b7fbdad46c819092f6fe7a14189620",
"status": "completed",
"model": "o3-mini",
"name": "Academic Assistant",
"created_at": 1740110812,
"result_counts": {
"total": 171,
"errored": 0,
"failed": 80,
"passed": 91
},
"per_model_usage": null,
"per_testing_criteria_results": [
{
"testing_criteria": "String check grader",
"passed": 91,
"failed": 80
}
],
"run_data_source": {
"type": "completions",
"template_messages": [
{
"type": "message",
"role": "system",
"content": {
"type": "input_text",
"text": "You are a helpful assistant."
}
},
{
"type": "message",
"role": "user",
"content": {
"type": "input_text",
"text": "Hello, can you help me with my homework?"
}
}
],
"datasource_reference": null,
"model": "o3-mini",
"max_completion_tokens": null,
"seed": null,
"temperature": null,
"top_p": null
},
"error": null,
"metadata": {"test": "synthetics"}
}
],
"first_id": "evalrun_67abd54d60ec8190832b46859da808f7",
"last_id": "evalrun_67abd54d60ec8190832b46859da808f7",
"has_more": false
}
EvalRunOutputItem:
type: object
title: EvalRunOutputItem
description: |
A schema representing an evaluation run output item.
properties:
object:
type: string
enum:
- eval.run.output_item
default: eval.run.output_item
description: The type of the object. Always "eval.run.output_item".
x-stainless-const: true
id:
type: string
description: Unique identifier for the evaluation run output item.
run_id:
type: string
description: The identifier of the evaluation run associated with this output item.
eval_id:
type: string
description: The identifier of the evaluation group.
created_at:
type: integer
description: Unix timestamp (in seconds) when the evaluation run was created.
status:
type: string
description: The status of the evaluation run.
datasource_item_id:
type: integer
description: The identifier for the data source item.
datasource_item:
type: object
description: Details of the input data source item.
additionalProperties: true
results:
type: array
description: A list of results from the evaluation run.
items:
type: object
description: A result object.
additionalProperties: true
sample:
type: object
description: A sample containing the input and output of the evaluation run.
properties:
input:
type: array
description: An array of input messages.
items:
type: object
description: An input message.
properties:
role:
type: string
description: The role of the message sender (e.g., system, user, developer).
content:
type: string
description: The content of the message.
required:
- role
- content
output:
type: array
description: An array of output messages.
items:
type: object
properties:
role:
type: string
description: The role of the message (e.g. "system", "assistant", "user").
content:
type: string
description: The content of the message.
finish_reason:
type: string
description: The reason why the sample generation was finished.
model:
type: string
description: The model used for generating the sample.
usage:
type: object
description: Token usage details for the sample.
properties:
total_tokens:
type: integer
description: The total number of tokens used.
completion_tokens:
type: integer
description: The number of completion tokens generated.
prompt_tokens:
type: integer
description: The number of prompt tokens used.
cached_tokens:
type: integer
description: The number of tokens retrieved from cache.
required:
- total_tokens
- completion_tokens
- prompt_tokens
- cached_tokens
error:
$ref: '#/components/schemas/EvalApiError'
temperature:
type: number
description: The sampling temperature used.
max_completion_tokens:
type: integer
description: The maximum number of tokens allowed for completion.
top_p:
type: number
description: The top_p value used for sampling.
seed:
type: integer
description: The seed used for generating the sample.
required:
- input
- output
- finish_reason
- model
- usage
- error
- temperature
- max_completion_tokens
- top_p
- seed
required:
- object
- id
- run_id
- eval_id
- created_at
- status
- datasource_item_id
- datasource_item
- results
- sample
x-oaiMeta:
name: The eval run output item object
group: evals
example: |
{
"object": "eval.run.output_item",
"id": "outputitem_67abd55eb6548190bb580745d5644a33",
"run_id": "evalrun_67abd54d60ec8190832b46859da808f7",
"eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
"created_at": 1739314509,
"status": "pass",
"datasource_item_id": 137,
"datasource_item": {
"teacher": "To grade essays, I only check for style, content, and grammar.",
"student": "I am a student who is trying to write the best essay."
},
"results": [
{
"name": "String Check Grader",
"type": "string-check-grader",
"score": 1.0,
"passed": true,
}
],
"sample": {
"input": [
{
"role": "system",
"content": "You are an evaluator bot..."
},
{
"role": "user",
"content": "You are assessing..."
}
],
"output": [
{
"role": "assistant",
"content": "The rubric is not clear nor concise."
}
],
"finish_reason": "stop",
"model": "gpt-4o-2024-08-06",
"usage": {
"total_tokens": 521,
"completion_tokens": 2,
"prompt_tokens": 519,
"cached_tokens": 0
},
"error": null,
"temperature": 1.0,
"max_completion_tokens": 2048,
"top_p": 1.0,
"seed": 42
}
}
EvalRunOutputItemList:
type: object
title: EvalRunOutputItemList
description: |
An object representing a list of output items for an evaluation run.
properties:
object:
type: string
enum:
- list
default: list
description: |
The type of this object. It is always set to "list".
x-stainless-const: true
data:
type: array
description: |
An array of eval run output item objects.
items:
$ref: '#/components/schemas/EvalRunOutputItem'
first_id:
type: string
description: The identifier of the first eval run output item in the data array.
last_id:
type: string
description: The identifier of the last eval run output item in the data array.
has_more:
type: boolean
description: Indicates whether there are more eval run output items available.
required:
- object
- data
- first_id
- last_id
- has_more
x-oaiMeta:
name: The eval run output item list object
group: evals
example: |
{
"object": "list",
"data": [
{
"object": "eval.run.output_item",
"id": "outputitem_67abd55eb6548190bb580745d5644a33",
"run_id": "evalrun_67abd54d60ec8190832b46859da808f7",
"eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
"created_at": 1739314509,
"status": "pass",
"datasource_item_id": 137,
"datasource_item": {
"teacher": "To grade essays, I only check for style, content, and grammar.",
"student": "I am a student who is trying to write the best essay."
},
"results": [
{
"name": "String Check Grader",
"type": "string-check-grader",
"score": 1.0,
"passed": true,
}
],
"sample": {
"input": [
{
"role": "system",
"content": "You are an evaluator bot..."
},
{
"role": "user",
"content": "You are assessing..."
}
],
"output": [
{
"role": "assistant",
"content": "The rubric is not clear nor concise."
}
],
"finish_reason": "stop",
"model": "gpt-4o-2024-08-06",
"usage": {
"total_tokens": 521,
"completion_tokens": 2,
"prompt_tokens": 519,
"cached_tokens": 0
},
"error": null,
"temperature": 1.0,
"max_completion_tokens": 2048,
"top_p": 1.0,
"seed": 42
}
},
],
"first_id": "outputitem_67abd55eb6548190bb580745d5644a33",
"last_id": "outputitem_67abd55eb6548190bb580745d5644a33",
"has_more": false
}
EvalStoredCompletionsDataSourceConfig:
type: object
title: StoredCompletionsDataSourceConfig
description: |
Deprecated in favor of LogsDataSourceConfig.
properties:
type:
type: string
enum:
- stored_completions
default: stored_completions
description: The type of data source. Always `stored_completions`.
x-stainless-const: true
metadata:
$ref: '#/components/schemas/Metadata'
schema:
type: object
description: |
The json schema for the run data source items.
Learn how to build JSON schemas [here](https://json-schema.org/).
additionalProperties: true
required:
- type
- schema
deprecated: true
x-oaiMeta:
name: The stored completions data source object for evals
group: evals
example: |
{
"type": "stored_completions",
"metadata": {
"language": "english"
},
"schema": {
"type": "object",
"properties": {
"item": {
"type": "object"
},
"sample": {
"type": "object"
}
},
"required": [
"item",
"sample"
}
}
EvalStoredCompletionsSource:
type: object
title: StoredCompletionsRunDataSource
description: |
A StoredCompletionsRunDataSource configuration describing a set of filters
properties:
type:
type: string
enum:
- stored_completions
default: stored_completions
description: The type of source. Always `stored_completions`.
x-stainless-const: true
metadata:
$ref: '#/components/schemas/Metadata'
model:
type: string
nullable: true
description: An optional model to filter by (e.g., 'gpt-4o').
created_after:
type: integer
nullable: true
description: An optional Unix timestamp to filter items created after this time.
created_before:
type: integer
nullable: true
description: An optional Unix timestamp to filter items created before this time.
limit:
type: integer
nullable: true
description: An optional maximum number of items to return.
required:
- type
x-oaiMeta:
name: The stored completions data source object used to configure an individual run
group: eval runs
example: |
{
"type": "stored_completions",
"model": "gpt-4o",
"created_after": 1668124800,
"created_before": 1668124900,
"limit": 100,
"metadata": {}
}
FileExpirationAfter:
type: object
title: File expiration policy
description: >-
The expiration policy for a file. By default, files with `purpose=batch` expire after 30 days and all
other files are persisted until they are manually deleted.
properties:
anchor:
description: 'Anchor timestamp after which the expiration policy applies. Supported anchors: `created_at`.'
type: string
enum:
- created_at
x-stainless-const: true
seconds:
description: >-
The number of seconds after the anchor time that the file will expire. Must be between 3600 (1
hour) and 2592000 (30 days).
type: integer
minimum: 3600
maximum: 2592000
required:
- anchor
- seconds
FilePath:
type: object
title: File path
description: |
A path to a file.
properties:
type:
type: string
description: |
The type of the file path. Always `file_path`.
enum:
- file_path
x-stainless-const: true
file_id:
type: string
description: |
The ID of the file.
index:
type: integer
description: |
The index of the file in the list of files.
required:
- type
- file_id
- index
FileSearchRanker:
type: string
description: The ranker to use for the file search. If not specified will use the `auto` ranker.
enum:
- auto
- default_2024_08_21
FileSearchRankingOptions:
title: File search tool call ranking options
type: object
description: >
The ranking options for the file search. If not specified, the file search tool will use the `auto`
ranker and a score_threshold of 0.
See the [file search tool
documentation](https://platform.openai.com/docs/assistants/tools/file-search#customizing-file-search-settings)
for more information.
properties:
ranker:
$ref: '#/components/schemas/FileSearchRanker'
score_threshold:
type: number
description: >-
The score threshold for the file search. All values must be a floating point number between 0 and
1.
minimum: 0
maximum: 1
required:
- score_threshold
FileSearchToolCall:
type: object
title: File search tool call
description: |
The results of a file search tool call. See the
[file search guide](https://platform.openai.com/docs/guides/tools-file-search) for more information.
properties:
id:
type: string
description: |
The unique ID of the file search tool call.
type:
type: string
enum:
- file_search_call
description: |
The type of the file search tool call. Always `file_search_call`.
x-stainless-const: true
status:
type: string
description: |
The status of the file search tool call. One of `in_progress`,
`searching`, `incomplete` or `failed`,
enum:
- in_progress
- searching
- completed
- incomplete
- failed
queries:
type: array
items:
type: string
description: |
The queries used to search for files.
results:
type: array
description: |
The results of the file search tool call.
items:
type: object
properties:
file_id:
type: string
description: |
The unique ID of the file.
text:
type: string
description: |
The text that was retrieved from the file.
filename:
type: string
description: |
The name of the file.
attributes:
$ref: '#/components/schemas/VectorStoreFileAttributes'
score:
type: number
format: float
description: |
The relevance score of the file - a value between 0 and 1.
nullable: true
required:
- id
- type
- status
- queries
FineTuneChatCompletionRequestAssistantMessage:
allOf:
- type: object
title: Assistant message
deprecated: false
properties:
weight:
type: integer
enum:
- 0
- 1
description: Controls whether the assistant message is trained against (0 or 1)
- $ref: '#/components/schemas/ChatCompletionRequestAssistantMessage'
required:
- role
FineTuneChatRequestInput:
type: object
description: |
The per-line training example of a fine-tuning input file for chat models using the supervised method.
Input messages may contain text or image content only. Audio and file input messages
are not currently supported for fine-tuning.
properties:
messages:
type: array
minItems: 1
items:
anyOf:
- $ref: '#/components/schemas/ChatCompletionRequestSystemMessage'
- $ref: '#/components/schemas/ChatCompletionRequestUserMessage'
- $ref: '#/components/schemas/FineTuneChatCompletionRequestAssistantMessage'
- $ref: '#/components/schemas/ChatCompletionRequestToolMessage'
- $ref: '#/components/schemas/ChatCompletionRequestFunctionMessage'
tools:
type: array
description: A list of tools the model may generate JSON inputs for.
items:
$ref: '#/components/schemas/ChatCompletionTool'
parallel_tool_calls:
$ref: '#/components/schemas/ParallelToolCalls'
functions:
deprecated: true
description: A list of functions the model may generate JSON inputs for.
type: array
minItems: 1
maxItems: 128
items:
$ref: '#/components/schemas/ChatCompletionFunctions'
x-oaiMeta:
name: Training format for chat models using the supervised method
example: |
{
"messages": [
{ "role": "user", "content": "What is the weather in San Francisco?" },
{
"role": "assistant",
"tool_calls": [
{
"id": "call_id",
"type": "function",
"function": {
"name": "get_current_weather",
"arguments": "{\"location\": \"San Francisco, USA\", \"format\": \"celsius\"}"
}
}
]
}
],
"parallel_tool_calls": false,
"tools": [
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and country, eg. San Francisco, USA"
},
"format": { "type": "string", "enum": ["celsius", "fahrenheit"] }
},
"required": ["location", "format"]
}
}
}
]
}
FineTuneDPOHyperparameters:
type: object
description: The hyperparameters used for the DPO fine-tuning job.
properties:
beta:
description: >
The beta value for the DPO method. A higher beta value will increase the weight of the penalty
between the policy and reference model.
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
- type: number
minimum: 0
maximum: 2
exclusiveMinimum: true
batch_size:
description: >
Number of examples in each batch. A larger batch size means that model parameters are updated less
frequently, but with lower variance.
default: auto
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
- type: integer
minimum: 1
maximum: 256
learning_rate_multiplier:
description: |
Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
- type: number
minimum: 0
exclusiveMinimum: true
n_epochs:
description: >
The number of epochs to train the model for. An epoch refers to one full cycle through the
training dataset.
default: auto
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
- type: integer
minimum: 1
maximum: 50
FineTuneDPOMethod:
type: object
description: Configuration for the DPO fine-tuning method.
properties:
hyperparameters:
$ref: '#/components/schemas/FineTuneDPOHyperparameters'
FineTuneMethod:
type: object
description: The method used for fine-tuning.
properties:
type:
type: string
description: The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
enum:
- supervised
- dpo
- reinforcement
supervised:
$ref: '#/components/schemas/FineTuneSupervisedMethod'
dpo:
$ref: '#/components/schemas/FineTuneDPOMethod'
reinforcement:
$ref: '#/components/schemas/FineTuneReinforcementMethod'
required:
- type
FineTunePreferenceRequestInput:
type: object
description: |
The per-line training example of a fine-tuning input file for chat models using the dpo method.
Input messages may contain text or image content only. Audio and file input messages
are not currently supported for fine-tuning.
properties:
input:
type: object
properties:
messages:
type: array
minItems: 1
items:
anyOf:
- $ref: '#/components/schemas/ChatCompletionRequestSystemMessage'
- $ref: '#/components/schemas/ChatCompletionRequestUserMessage'
- $ref: '#/components/schemas/FineTuneChatCompletionRequestAssistantMessage'
- $ref: '#/components/schemas/ChatCompletionRequestToolMessage'
- $ref: '#/components/schemas/ChatCompletionRequestFunctionMessage'
tools:
type: array
description: A list of tools the model may generate JSON inputs for.
items:
$ref: '#/components/schemas/ChatCompletionTool'
parallel_tool_calls:
$ref: '#/components/schemas/ParallelToolCalls'
preferred_output:
type: array
description: The preferred completion message for the output.
maxItems: 1
items:
anyOf:
- $ref: '#/components/schemas/ChatCompletionRequestAssistantMessage'
non_preferred_output:
type: array
description: The non-preferred completion message for the output.
maxItems: 1
items:
anyOf:
- $ref: '#/components/schemas/ChatCompletionRequestAssistantMessage'
x-oaiMeta:
name: Training format for chat models using the preference method
example: |
{
"input": {
"messages": [
{ "role": "user", "content": "What is the weather in San Francisco?" }
]
},
"preferred_output": [
{
"role": "assistant",
"content": "The weather in San Francisco is 70 degrees Fahrenheit."
}
],
"non_preferred_output": [
{
"role": "assistant",
"content": "The weather in San Francisco is 21 degrees Celsius."
}
]
}
FineTuneReinforcementHyperparameters:
type: object
description: The hyperparameters used for the reinforcement fine-tuning job.
properties:
batch_size:
description: >
Number of examples in each batch. A larger batch size means that model parameters are updated less
frequently, but with lower variance.
default: auto
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
- type: integer
minimum: 1
maximum: 256
learning_rate_multiplier:
description: |
Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
- type: number
minimum: 0
exclusiveMinimum: true
n_epochs:
description: >
The number of epochs to train the model for. An epoch refers to one full cycle through the
training dataset.
default: auto
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
- type: integer
minimum: 1
maximum: 50
reasoning_effort:
description: |
Level of reasoning effort.
type: string
enum:
- default
- low
- medium
- high
default: default
compute_multiplier:
description: |
Multiplier on amount of compute used for exploring search space during training.
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
- type: number
minimum: 0.00001
maximum: 10
exclusiveMinimum: true
eval_interval:
description: |
The number of training steps between evaluation runs.
default: auto
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
- type: integer
minimum: 1
eval_samples:
description: |
Number of evaluation samples to generate per training step.
default: auto
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
- type: integer
minimum: 1
FineTuneReinforcementMethod:
type: object
description: Configuration for the reinforcement fine-tuning method.
properties:
grader:
type: object
description: The grader used for the fine-tuning job.
anyOf:
- $ref: '#/components/schemas/GraderStringCheck'
- $ref: '#/components/schemas/GraderTextSimilarity'
- $ref: '#/components/schemas/GraderPython'
- $ref: '#/components/schemas/GraderScoreModel'
- $ref: '#/components/schemas/GraderMulti'
hyperparameters:
$ref: '#/components/schemas/FineTuneReinforcementHyperparameters'
required:
- grader
FineTuneReinforcementRequestInput:
type: object
unevaluatedProperties: true
description: >
Per-line training example for reinforcement fine-tuning. Note that `messages` and `tools` are the only
reserved keywords.
Any other arbitrary key-value data can be included on training datapoints and will be available to
reference during grading under the `{{ item.XXX }}` template variable.
Input messages may contain text or image content only. Audio and file input messages
are not currently supported for fine-tuning.
required:
- messages
properties:
messages:
type: array
minItems: 1
items:
anyOf:
- $ref: '#/components/schemas/ChatCompletionRequestDeveloperMessage'
- $ref: '#/components/schemas/ChatCompletionRequestUserMessage'
- $ref: '#/components/schemas/FineTuneChatCompletionRequestAssistantMessage'
- $ref: '#/components/schemas/ChatCompletionRequestToolMessage'
tools:
type: array
description: A list of tools the model may generate JSON inputs for.
items:
$ref: '#/components/schemas/ChatCompletionTool'
x-oaiMeta:
name: Training format for reasoning models using the reinforcement method
example: |
{
"messages": [
{
"role": "user",
"content": "Your task is to take a chemical in SMILES format and predict the number of hydrobond bond donors and acceptors according to Lipinkski's rule. CCN(CC)CCC(=O)c1sc(N)nc1C"
},
],
# Any other JSON data can be inserted into an example and referenced during RFT grading
"reference_answer": {
"donor_bond_counts": 5,
"acceptor_bond_counts": 7
}
}
FineTuneSupervisedHyperparameters:
type: object
description: The hyperparameters used for the fine-tuning job.
properties:
batch_size:
description: >
Number of examples in each batch. A larger batch size means that model parameters are updated less
frequently, but with lower variance.
default: auto
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
- type: integer
minimum: 1
maximum: 256
learning_rate_multiplier:
description: |
Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
- type: number
minimum: 0
exclusiveMinimum: true
n_epochs:
description: >
The number of epochs to train the model for. An epoch refers to one full cycle through the
training dataset.
default: auto
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
- type: integer
minimum: 1
maximum: 50
FineTuneSupervisedMethod:
type: object
description: Configuration for the supervised fine-tuning method.
properties:
hyperparameters:
$ref: '#/components/schemas/FineTuneSupervisedHyperparameters'
FineTuningCheckpointPermission:
type: object
title: FineTuningCheckpointPermission
description: |
The `checkpoint.permission` object represents a permission for a fine-tuned model checkpoint.
properties:
id:
type: string
description: The permission identifier, which can be referenced in the API endpoints.
created_at:
type: integer
description: The Unix timestamp (in seconds) for when the permission was created.
project_id:
type: string
description: The project identifier that the permission is for.
object:
type: string
description: The object type, which is always "checkpoint.permission".
enum:
- checkpoint.permission
x-stainless-const: true
required:
- created_at
- id
- object
- project_id
x-oaiMeta:
name: The fine-tuned model checkpoint permission object
example: |
{
"object": "checkpoint.permission",
"id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
"created_at": 1712211699,
"project_id": "proj_abGMw1llN8IrBb6SvvY5A1iH"
}
FineTuningIntegration:
type: object
title: Fine-Tuning Job Integration
required:
- type
- wandb
properties:
type:
type: string
description: The type of the integration being enabled for the fine-tuning job
enum:
- wandb
x-stainless-const: true
wandb:
type: object
description: |
The settings for your integration with Weights and Biases. This payload specifies the project that
metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags
to your run, and set a default entity (team, username, etc) to be associated with your run.
required:
- project
properties:
project:
description: |
The name of the project that the new run will be created under.
type: string
example: my-wandb-project
name:
description: |
A display name to set for the run. If not set, we will use the Job ID as the name.
nullable: true
type: string
entity:
description: >
The entity to use for the run. This allows you to set the team or username of the WandB user
that you would
like associated with the run. If not set, the default entity for the registered WandB API key
is used.
nullable: true
type: string
tags:
description: >
A list of tags to be attached to the newly created run. These tags are passed through directly
to WandB. Some
default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}",
"openai/{ftjob-abcdef}".
type: array
items:
type: string
example: custom-tag
FineTuningJob:
type: object
title: FineTuningJob
description: |
The `fine_tuning.job` object represents a fine-tuning job that has been created through the API.
properties:
id:
type: string
description: The object identifier, which can be referenced in the API endpoints.
created_at:
type: integer
description: The Unix timestamp (in seconds) for when the fine-tuning job was created.
error:
type: object
nullable: true
description: >-
For fine-tuning jobs that have `failed`, this will contain more information on the cause of the
failure.
properties:
code:
type: string
description: A machine-readable error code.
message:
type: string
description: A human-readable error message.
param:
type: string
description: >-
The parameter that was invalid, usually `training_file` or `validation_file`. This field will
be null if the failure was not parameter-specific.
nullable: true
required:
- code
- message
- param
fine_tuned_model:
type: string
nullable: true
description: >-
The name of the fine-tuned model that is being created. The value will be null if the fine-tuning
job is still running.
finished_at:
type: integer
nullable: true
description: >-
The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null
if the fine-tuning job is still running.
hyperparameters:
type: object
description: >-
The hyperparameters used for the fine-tuning job. This value will only be returned when running
`supervised` jobs.
properties:
batch_size:
nullable: true
description: |
Number of examples in each batch. A larger batch size means that model parameters
are updated less frequently, but with lower variance.
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
title: Auto
- type: integer
minimum: 1
maximum: 256
title: Manual
learning_rate_multiplier:
description: |
Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
overfitting.
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
title: Auto
- type: number
minimum: 0
exclusiveMinimum: true
n_epochs:
description: |
The number of epochs to train the model for. An epoch refers to one full cycle
through the training dataset.
default: auto
anyOf:
- type: string
enum:
- auto
x-stainless-const: true
title: Auto
- type: integer
minimum: 1
maximum: 50
model:
type: string
description: The base model that is being fine-tuned.
object:
type: string
description: The object type, which is always "fine_tuning.job".
enum:
- fine_tuning.job
x-stainless-const: true
organization_id:
type: string
description: The organization that owns the fine-tuning job.
result_files:
type: array
description: >-
The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the
[Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents).
items:
type: string
example: file-abc123
status:
type: string
description: >-
The current status of the fine-tuning job, which can be either `validating_files`, `queued`,
`running`, `succeeded`, `failed`, or `cancelled`.
enum:
- validating_files
- queued
- running
- succeeded
- failed
- cancelled
trained_tokens:
type: integer
nullable: true
description: >-
The total number of billable tokens processed by this fine-tuning job. The value will be null if
the fine-tuning job is still running.
training_file:
type: string
description: >-
The file ID used for training. You can retrieve the training data with the [Files
API](https://platform.openai.com/docs/api-reference/files/retrieve-contents).
validation_file:
type: string
nullable: true
description: >-
The file ID used for validation. You can retrieve the validation results with the [Files
API](https://platform.openai.com/docs/api-reference/files/retrieve-contents).
integrations:
type: array
nullable: true
description: A list of integrations to enable for this fine-tuning job.
maxItems: 5
items:
anyOf:
- $ref: '#/components/schemas/FineTuningIntegration'
discriminator:
propertyName: type
seed:
type: integer
description: The seed used for the fine-tuning job.
estimated_finish:
type: integer
nullable: true
description: >-
The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value
will be null if the fine-tuning job is not running.
method:
$ref: '#/components/schemas/FineTuneMethod'
metadata:
$ref: '#/components/schemas/Metadata'
required:
- created_at
- error
- finished_at
- fine_tuned_model
- hyperparameters
- id
- model
- object
- organization_id
- result_files
- status
- trained_tokens
- training_file
- validation_file
- seed
x-oaiMeta:
name: The fine-tuning job object
example: |
{
"object": "fine_tuning.job",
"id": "ftjob-abc123",
"model": "davinci-002",
"created_at": 1692661014,
"finished_at": 1692661190,
"fine_tuned_model": "ft:davinci-002:my-org:custom_suffix:7q8mpxmy",
"organization_id": "org-123",
"result_files": [
"file-abc123"
],
"status": "succeeded",
"validation_file": null,
"training_file": "file-abc123",
"hyperparameters": {
"n_epochs": 4,
"batch_size": 1,
"learning_rate_multiplier": 1.0
},
"trained_tokens": 5768,
"integrations": [],
"seed": 0,
"estimated_finish": 0,
"method": {
"type": "supervised",
"supervised": {
"hyperparameters": {
"n_epochs": 4,
"batch_size": 1,
"learning_rate_multiplier": 1.0
}
}
},
"metadata": {
"key": "value"
}
}
FineTuningJobCheckpoint:
type: object
title: FineTuningJobCheckpoint
description: >
The `fine_tuning.job.checkpoint` object represents a model checkpoint for a fine-tuning job that is
ready to use.
properties:
id:
type: string
description: The checkpoint identifier, which can be referenced in the API endpoints.
created_at:
type: integer
description: The Unix timestamp (in seconds) for when the checkpoint was created.
fine_tuned_model_checkpoint:
type: string
description: The name of the fine-tuned checkpoint model that is created.
step_number:
type: integer
description: The step number that the checkpoint was created at.
metrics:
type: object
description: Metrics at the step number during the fine-tuning job.
properties:
step:
type: number
train_loss:
type: number
train_mean_token_accuracy:
type: number
valid_loss:
type: number
valid_mean_token_accuracy:
type: number
full_valid_loss:
type: number
full_valid_mean_token_accuracy:
type: number
fine_tuning_job_id:
type: string
description: The name of the fine-tuning job that this checkpoint was created from.
object:
type: string
description: The object type, which is always "fine_tuning.job.checkpoint".
enum:
- fine_tuning.job.checkpoint
x-stainless-const: true
required:
- created_at
- fine_tuning_job_id
- fine_tuned_model_checkpoint
- id
- metrics
- object
- step_number
x-oaiMeta:
name: The fine-tuning job checkpoint object
example: |
{
"object": "fine_tuning.job.checkpoint",
"id": "ftckpt_qtZ5Gyk4BLq1SfLFWp3RtO3P",
"created_at": 1712211699,
"fine_tuned_model_checkpoint": "ft:gpt-4o-mini-2024-07-18:my-org:custom_suffix:9ABel2dg:ckpt-step-88",
"fine_tuning_job_id": "ftjob-fpbNQ3H1GrMehXRf8cO97xTN",
"metrics": {
"step": 88,
"train_loss": 0.478,
"train_mean_token_accuracy": 0.924,
"valid_loss": 10.112,
"valid_mean_token_accuracy": 0.145,
"full_valid_loss": 0.567,
"full_valid_mean_token_accuracy": 0.944
},
"step_number": 88
}
FineTuningJobEvent:
type: object
description: Fine-tuning job event object
properties:
object:
type: string
description: The object type, which is always "fine_tuning.job.event".
enum:
- fine_tuning.job.event
x-stainless-const: true
id:
type: string
description: The object identifier.
created_at:
type: integer
description: The Unix timestamp (in seconds) for when the fine-tuning job was created.
level:
type: string
description: The log level of the event.
enum:
- info
- warn
- error
message:
type: string
description: The message of the event.
type:
type: string
description: The type of event.
enum:
- message
- metrics
data:
type: object
description: The data associated with the event.
required:
- id
- object
- created_at
- level
- message
x-oaiMeta:
name: The fine-tuning job event object
example: |
{
"object": "fine_tuning.job.event",
"id": "ftevent-abc123"
"created_at": 1677610602,
"level": "info",
"message": "Created fine-tuning job",
"data": {},
"type": "message"
}
FunctionObject:
type: object
properties:
description:
type: string
description: >-
A description of what the function does, used by the model to choose when and how to call the
function.
name:
type: string
description: >-
The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes,
with a maximum length of 64.
parameters:
$ref: '#/components/schemas/FunctionParameters'
strict:
type: boolean
nullable: true
default: false
description: >-
Whether to enable strict schema adherence when generating the function call. If set to true, the
model will follow the exact schema defined in the `parameters` field. Only a subset of JSON Schema
is supported when `strict` is `true`. Learn more about Structured Outputs in the [function calling
guide](https://platform.openai.com/docs/guides/function-calling).
required:
- name
FunctionParameters:
type: object
description: >-
The parameters the functions accepts, described as a JSON Schema object. See the
[guide](https://platform.openai.com/docs/guides/function-calling) for examples, and the [JSON Schema
reference](https://json-schema.org/understanding-json-schema/) for documentation about the format.
Omitting `parameters` defines a function with an empty parameter list.
additionalProperties: true
FunctionToolCall:
type: object
title: Function tool call
description: >
A tool call to run a function. See the
[function calling guide](https://platform.openai.com/docs/guides/function-calling) for more
information.
properties:
id:
type: string
description: |
The unique ID of the function tool call.
type:
type: string
enum:
- function_call
description: |
The type of the function tool call. Always `function_call`.
x-stainless-const: true
call_id:
type: string
description: |
The unique ID of the function tool call generated by the model.
name:
type: string
description: |
The name of the function to run.
arguments:
type: string
description: |
A JSON string of the arguments to pass to the function.
status:
type: string
description: |
The status of the item. One of `in_progress`, `completed`, or
`incomplete`. Populated when items are returned via API.
enum:
- in_progress
- completed
- incomplete
required:
- type
- call_id
- name
- arguments
FunctionToolCallOutput:
type: object
title: Function tool call output
description: |
The output of a function tool call.
properties:
id:
type: string
description: |
The unique ID of the function tool call output. Populated when this item
is returned via API.
type:
type: string
enum:
- function_call_output
description: |
The type of the function tool call output. Always `function_call_output`.
x-stainless-const: true
call_id:
type: string
description: |
The unique ID of the function tool call generated by the model.
output:
type: string
description: |
A JSON string of the output of the function tool call.
status:
type: string
description: |
The status of the item. One of `in_progress`, `completed`, or
`incomplete`. Populated when items are returned via API.
enum:
- in_progress
- completed
- incomplete
required:
- type
- call_id
- output
FunctionToolCallOutputResource:
allOf:
- $ref: '#/components/schemas/FunctionToolCallOutput'
- type: object
properties:
id:
type: string
description: |
The unique ID of the function call tool output.
required:
- id
FunctionToolCallResource:
allOf:
- $ref: '#/components/schemas/FunctionToolCall'
- type: object
properties:
id:
type: string
description: |
The unique ID of the function tool call.
required:
- id
GraderLabelModel:
type: object
title: LabelModelGrader
description: |
A LabelModelGrader object which uses a model to assign labels to each item
in the evaluation.
properties:
type:
description: The object type, which is always `label_model`.
type: string
enum:
- label_model
x-stainless-const: true
name:
type: string
description: The name of the grader.
model:
type: string
description: The model to use for the evaluation. Must support structured outputs.
input:
type: array
items:
$ref: '#/components/schemas/EvalItem'
labels:
type: array
items:
type: string
description: The labels to assign to each item in the evaluation.
passing_labels:
type: array
items:
type: string
description: The labels that indicate a passing result. Must be a subset of labels.
required:
- type
- model
- input
- passing_labels
- labels
- name
x-oaiMeta:
name: Label Model Grader
group: graders
example: |
{
"name": "First label grader",
"type": "label_model",
"model": "gpt-4o-2024-08-06",
"input": [
{
"type": "message",
"role": "system",
"content": {
"type": "input_text",
"text": "Classify the sentiment of the following statement as one of positive, neutral, or negative"
}
},
{
"type": "message",
"role": "user",
"content": {
"type": "input_text",
"text": "Statement: {{item.response}}"
}
}
],
"passing_labels": [
"positive"
],
"labels": [
"positive",
"neutral",
"negative"
]
}
GraderMulti:
type: object
title: MultiGrader
description: A MultiGrader object combines the output of multiple graders to produce a single score.
properties:
type:
type: string
enum:
- multi
default: multi
description: The object type, which is always `multi`.
x-stainless-const: true
name:
type: string
description: The name of the grader.
graders:
anyOf:
- $ref: '#/components/schemas/GraderStringCheck'
- $ref: '#/components/schemas/GraderTextSimilarity'
- $ref: '#/components/schemas/GraderPython'
- $ref: '#/components/schemas/GraderScoreModel'
- $ref: '#/components/schemas/GraderLabelModel'
calculate_output:
type: string
description: A formula to calculate the output based on grader results.
required:
- name
- type
- graders
- calculate_output
x-oaiMeta:
name: Multi Grader
group: graders
example: |
{
"type": "multi",
"name": "example multi grader",
"graders": [
{
"type": "text_similarity",
"name": "example text similarity grader",
"input": "The graded text",
"reference": "The reference text",
"evaluation_metric": "fuzzy_match"
},
{
"type": "string_check",
"name": "Example string check grader",
"input": "{{sample.output_text}}",
"reference": "{{item.label}}",
"operation": "eq"
}
],
"calculate_output": "0.5 * text_similarity_score + 0.5 * string_check_score)"
}
GraderPython:
type: object
title: PythonGrader
description: |
A PythonGrader object that runs a python script on the input.
properties:
type:
type: string
enum:
- python
description: The object type, which is always `python`.
x-stainless-const: true
name:
type: string
description: The name of the grader.
source:
type: string
description: The source code of the python script.
image_tag:
type: string
description: The image tag to use for the python script.
required:
- type
- name
- source
x-oaiMeta:
name: Python Grader
group: graders
example: |
{
"type": "python",
"name": "Example python grader",
"image_tag": "2025-05-08",
"source": """
def grade(sample: dict, item: dict) -> float:
\"""
Returns 1.0 if `output_text` equals `label`, otherwise 0.0.
\"""
output = sample.get("output_text")
label = item.get("label")
return 1.0 if output == label else 0.0
""",
}
GraderScoreModel:
type: object
title: ScoreModelGrader
description: |
A ScoreModelGrader object that uses a model to assign a score to the input.
properties:
type:
type: string
enum:
- score_model
description: The object type, which is always `score_model`.
x-stainless-const: true
name:
type: string
description: The name of the grader.
model:
type: string
description: The model to use for the evaluation.
sampling_params:
type: object
description: The sampling parameters for the model.
input:
type: array
items:
$ref: '#/components/schemas/EvalItem'
description: The input text. This may include template strings.
range:
type: array
items:
type: number
min_items: 2
max_items: 2
description: The range of the score. Defaults to `[0, 1]`.
required:
- type
- name
- input
- model
x-oaiMeta:
name: Score Model Grader
group: graders
example: |
{
"type": "score_model",
"name": "Example score model grader",
"input": [
{
"role": "user",
"content": (
"Score how close the reference answer is to the model answer. Score 1.0 if they are the same and 0.0 if they are different."
" Return just a floating point score\n\n"
" Reference answer: {{item.label}}\n\n"
" Model answer: {{sample.output_text}}"
),
}
],
"model": "gpt-4o-2024-08-06",
"sampling_params": {
"temperature": 1,
"top_p": 1,
"seed": 42,
},
}
GraderStringCheck:
type: object
title: StringCheckGrader
description: >
A StringCheckGrader object that performs a string comparison between input and reference using a
specified operation.
properties:
type:
type: string
enum:
- string_check
description: The object type, which is always `string_check`.
x-stainless-const: true
name:
type: string
description: The name of the grader.
input:
type: string
description: The input text. This may include template strings.
reference:
type: string
description: The reference text. This may include template strings.
operation:
type: string
enum:
- eq
- ne
- like
- ilike
description: The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
required:
- type
- name
- input
- reference
- operation
x-oaiMeta:
name: String Check Grader
group: graders
example: |
{
"type": "string_check",
"name": "Example string check grader",
"input": "{{sample.output_text}}",
"reference": "{{item.label}}",
"operation": "eq"
}
GraderTextSimilarity:
type: object
title: TextSimilarityGrader
description: |
A TextSimilarityGrader object which grades text based on similarity metrics.
properties:
type:
type: string
enum:
- text_similarity
default: text_similarity
description: The type of grader.
x-stainless-const: true
name:
type: string
description: The name of the grader.
input:
type: string
description: The text being graded.
reference:
type: string
description: The text being graded against.
evaluation_metric:
type: string
enum:
- cosine
- fuzzy_match
- bleu
- gleu
- meteor
- rouge_1
- rouge_2
- rouge_3
- rouge_4
- rouge_5
- rouge_l
description: |
The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`,
`gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`,
or `rouge_l`.
required:
- type
- name
- input
- reference
- evaluation_metric
x-oaiMeta:
name: Text Similarity Grader
group: graders
example: |
{
"type": "text_similarity",
"name": "Example text similarity grader",
"input": "{{sample.output_text}}",
"reference": "{{item.label}}",
"evaluation_metric": "fuzzy_match"
}
Image:
type: object
description: Represents the content or the URL of an image generated by the OpenAI API.
properties:
b64_json:
type: string
description: >-
The base64-encoded JSON of the generated image. Default value for `gpt-image-1`, and only present
if `response_format` is set to `b64_json` for `dall-e-2` and `dall-e-3`.
url:
type: string
description: >-
When using `dall-e-2` or `dall-e-3`, the URL of the generated image if `response_format` is set to
`url` (default value). Unsupported for `gpt-image-1`.
revised_prompt:
type: string
description: For `dall-e-3` only, the revised prompt that was used to generate the image.
ImageEditCompletedEvent:
type: object
description: |
Emitted when image editing has completed and the final image is available.
properties:
type:
type: string
description: |
The type of the event. Always `image_edit.completed`.
enum:
- image_edit.completed
x-stainless-const: true
b64_json:
type: string
description: |
Base64-encoded final edited image data, suitable for rendering as an image.
created_at:
type: integer
description: |
The Unix timestamp when the event was created.
size:
type: string
description: |
The size of the edited image.
enum:
- 1024x1024
- 1024x1536
- 1536x1024
- auto
quality:
type: string
description: |
The quality setting for the edited image.
enum:
- low
- medium
- high
- auto
background:
type: string
description: |
The background setting for the edited image.
enum:
- transparent
- opaque
- auto
output_format:
type: string
description: |
The output format for the edited image.
enum:
- png
- webp
- jpeg
usage:
$ref: '#/components/schemas/ImagesUsage'
required:
- type
- b64_json
- created_at
- size
- quality
- background
- output_format
- usage
x-oaiMeta:
name: image_edit.completed
group: images
example: |
{
"type": "image_edit.completed",
"b64_json": "...",
"created_at": 1620000000,
"size": "1024x1024",
"quality": "high",
"background": "transparent",
"output_format": "png",
"usage": {
"total_tokens": 100,
"input_tokens": 50,
"output_tokens": 50,
"input_tokens_details": {
"text_tokens": 10,
"image_tokens": 40
}
}
}
ImageEditPartialImageEvent:
type: object
description: |
Emitted when a partial image is available during image editing streaming.
properties:
type:
type: string
description: |
The type of the event. Always `image_edit.partial_image`.
enum:
- image_edit.partial_image
x-stainless-const: true
b64_json:
type: string
description: |
Base64-encoded partial image data, suitable for rendering as an image.
created_at:
type: integer
description: |
The Unix timestamp when the event was created.
size:
type: string
description: |
The size of the requested edited image.
enum:
- 1024x1024
- 1024x1536
- 1536x1024
- auto
quality:
type: string
description: |
The quality setting for the requested edited image.
enum:
- low
- medium
- high
- auto
background:
type: string
description: |
The background setting for the requested edited image.
enum:
- transparent
- opaque
- auto
output_format:
type: string
description: |
The output format for the requested edited image.
enum:
- png
- webp
- jpeg
partial_image_index:
type: integer
description: |
0-based index for the partial image (streaming).
required:
- type
- b64_json
- created_at
- size
- quality
- background
- output_format
- partial_image_index
x-oaiMeta:
name: image_edit.partial_image
group: images
example: |
{
"type": "image_edit.partial_image",
"b64_json": "...",
"created_at": 1620000000,
"size": "1024x1024",
"quality": "high",
"background": "transparent",
"output_format": "png",
"partial_image_index": 0
}
ImageEditStreamEvent:
anyOf:
- $ref: '#/components/schemas/ImageEditPartialImageEvent'
- $ref: '#/components/schemas/ImageEditCompletedEvent'
discriminator:
propertyName: type
ImageGenCompletedEvent:
type: object
description: |
Emitted when image generation has completed and the final image is available.
properties:
type:
type: string
description: |
The type of the event. Always `image_generation.completed`.
enum:
- image_generation.completed
x-stainless-const: true
b64_json:
type: string
description: |
Base64-encoded image data, suitable for rendering as an image.
created_at:
type: integer
description: |
The Unix timestamp when the event was created.
size:
type: string
description: |
The size of the generated image.
enum:
- 1024x1024
- 1024x1536
- 1536x1024
- auto
quality:
type: string
description: |
The quality setting for the generated image.
enum:
- low
- medium
- high
- auto
background:
type: string
description: |
The background setting for the generated image.
enum:
- transparent
- opaque
- auto
output_format:
type: string
description: |
The output format for the generated image.
enum:
- png
- webp
- jpeg
usage:
$ref: '#/components/schemas/ImagesUsage'
required:
- type
- b64_json
- created_at
- size
- quality
- background
- output_format
- usage
x-oaiMeta:
name: image_generation.completed
group: images
example: |
{
"type": "image_generation.completed",
"b64_json": "...",
"created_at": 1620000000,
"size": "1024x1024",
"quality": "high",
"background": "transparent",
"output_format": "png",
"usage": {
"total_tokens": 100,
"input_tokens": 50,
"output_tokens": 50,
"input_tokens_details": {
"text_tokens": 10,
"image_tokens": 40
}
}
}
ImageGenPartialImageEvent:
type: object
description: |
Emitted when a partial image is available during image generation streaming.
properties:
type:
type: string
description: |
The type of the event. Always `image_generation.partial_image`.
enum:
- image_generation.partial_image
x-stainless-const: true
b64_json:
type: string
description: |
Base64-encoded partial image data, suitable for rendering as an image.
created_at:
type: integer
description: |
The Unix timestamp when the event was created.
size:
type: string
description: |
The size of the requested image.
enum:
- 1024x1024
- 1024x1536
- 1536x1024
- auto
quality:
type: string
description: |
The quality setting for the requested image.
enum:
- low
- medium
- high
- auto
background:
type: string
description: |
The background setting for the requested image.
enum:
- transparent
- opaque
- auto
output_format:
type: string
description: |
The output format for the requested image.
enum:
- png
- webp
- jpeg
partial_image_index:
type: integer
description: |
0-based index for the partial image (streaming).
required:
- type
- b64_json
- created_at
- size
- quality
- background
- output_format
- partial_image_index
x-oaiMeta:
name: image_generation.partial_image
group: images
example: |
{
"type": "image_generation.partial_image",
"b64_json": "...",
"created_at": 1620000000,
"size": "1024x1024",
"quality": "high",
"background": "transparent",
"output_format": "png",
"partial_image_index": 0
}
ImageGenStreamEvent:
anyOf:
- $ref: '#/components/schemas/ImageGenPartialImageEvent'
- $ref: '#/components/schemas/ImageGenCompletedEvent'
discriminator:
propertyName: type
ImageGenTool:
type: object
title: Image generation tool
description: |
A tool that generates images using a model like `gpt-image-1`.
properties:
type:
type: string
enum:
- image_generation
description: |
The type of the image generation tool. Always `image_generation`.
x-stainless-const: true
model:
type: string
enum:
- gpt-image-1
description: |
The image generation model to use. Default: `gpt-image-1`.
default: gpt-image-1
quality:
type: string
enum:
- low
- medium
- high
- auto
description: |
The quality of the generated image. One of `low`, `medium`, `high`,
or `auto`. Default: `auto`.
default: auto
size:
type: string
enum:
- 1024x1024
- 1024x1536
- 1536x1024
- auto
description: |
The size of the generated image. One of `1024x1024`, `1024x1536`,
`1536x1024`, or `auto`. Default: `auto`.
default: auto
output_format:
type: string
enum:
- png
- webp
- jpeg
description: |
The output format of the generated image. One of `png`, `webp`, or
`jpeg`. Default: `png`.
default: png
output_compression:
type: integer
minimum: 0
maximum: 100
description: |
Compression level for the output image. Default: 100.
default: 100
moderation:
type: string
enum:
- auto
- low
description: |
Moderation level for the generated image. Default: `auto`.
default: auto
background:
type: string
enum:
- transparent
- opaque
- auto
description: |
Background type for the generated image. One of `transparent`,
`opaque`, or `auto`. Default: `auto`.
default: auto
input_fidelity:
$ref: '#/components/schemas/ImageInputFidelity'
input_image_mask:
type: object
description: |
Optional mask for inpainting. Contains `image_url`
(string, optional) and `file_id` (string, optional).
properties:
image_url:
type: string
description: |
Base64-encoded mask image.
file_id:
type: string
description: |
File ID for the mask image.
required: []
additionalProperties: false
partial_images:
type: integer
minimum: 0
maximum: 3
description: |
Number of partial images to generate in streaming mode, from 0 (default value) to 3.
default: 0
required:
- type
ImageGenToolCall:
type: object
title: Image generation call
description: |
An image generation request made by the model.
properties:
type:
type: string
enum:
- image_generation_call
description: |
The type of the image generation call. Always `image_generation_call`.
x-stainless-const: true
id:
type: string
description: |
The unique ID of the image generation call.
status:
type: string
enum:
- in_progress
- completed
- generating
- failed
description: |
The status of the image generation call.
result:
type: string
description: |
The generated image encoded in base64.
nullable: true
required:
- type
- id
- status
- result
ImageInputFidelity:
type: string
enum:
- high
- low
default: low
nullable: true
description: |
Control how much effort the model will exert to match the style and features,
especially facial features, of input images. This parameter is only supported
for `gpt-image-1`. Supports `high` and `low`. Defaults to `low`.
ImagesResponse:
type: object
title: Image generation response
description: The response from the image generation endpoint.
properties:
created:
type: integer
description: The Unix timestamp (in seconds) of when the image was created.
data:
type: array
description: The list of generated images.
items:
$ref: '#/components/schemas/Image'
background:
type: string
description: The background parameter used for the image generation. Either `transparent` or `opaque`.
enum:
- transparent
- opaque
output_format:
type: string
description: The output format of the image generation. Either `png`, `webp`, or `jpeg`.
enum:
- png
- webp
- jpeg
size:
type: string
description: The size of the image generated. Either `1024x1024`, `1024x1536`, or `1536x1024`.
enum:
- 1024x1024
- 1024x1536
- 1536x1024
quality:
type: string
description: The quality of the image generated. Either `low`, `medium`, or `high`.
enum:
- low
- medium
- high
usage:
$ref: '#/components/schemas/ImageGenUsage'
required:
- created
x-oaiMeta:
name: The image generation response
group: images
example: |
{
"created": 1713833628,
"data": [
{
"b64_json": "..."
}
],
"background": "transparent",
"output_format": "png",
"size": "1024x1024",
"quality": "high",
"usage": {
"total_tokens": 100,
"input_tokens": 50,
"output_tokens": 50,
"input_tokens_details": {
"text_tokens": 10,
"image_tokens": 40
}
}
}
ImagesUsage:
type: object
description: |
For `gpt-image-1` only, the token usage information for the image generation.
required:
- total_tokens
- input_tokens
- output_tokens
- input_tokens_details
properties:
total_tokens:
type: integer
description: |
The total number of tokens (images and text) used for the image generation.
input_tokens:
type: integer
description: The number of tokens (images and text) in the input prompt.
output_tokens:
type: integer
description: The number of image tokens in the output image.
input_tokens_details:
type: object
description: The input tokens detailed information for the image generation.
required:
- text_tokens
- image_tokens
properties:
text_tokens:
type: integer
description: The number of text tokens in the input prompt.
image_tokens:
type: integer
description: The number of image tokens in the input prompt.
Includable:
type: string
description: |
Specify additional output data to include in the model response. Currently
supported values are:
- `code_interpreter_call.outputs`: Includes the outputs of python code execution
in code interpreter tool call items.
- `computer_call_output.output.image_url`: Include image urls from the computer call output.
- `file_search_call.results`: Include the search results of
the file search tool call.
- `message.input_image.image_url`: Include image urls from the input message.
- `message.output_text.logprobs`: Include logprobs with assistant messages.
- `reasoning.encrypted_content`: Includes an encrypted version of reasoning
tokens in reasoning item outputs. This enables reasoning items to be used in
multi-turn conversations when using the Responses API statelessly (like
when the `store` parameter is set to `false`, or when an organization is
enrolled in the zero data retention program).
enum:
- code_interpreter_call.outputs
- computer_call_output.output.image_url
- file_search_call.results
- message.input_image.image_url
- message.output_text.logprobs
- reasoning.encrypted_content
InputAudio:
type: object
title: Audio input
description: |
An audio input to the model.
properties:
type:
type: string
description: |
The type of the input item. Always `input_audio`.
enum:
- input_audio
x-stainless-const: true
data:
type: string
description: |
Base64-encoded audio data.
format:
type: string
description: |
The format of the audio data. Currently supported formats are `mp3` and
`wav`.
enum:
- mp3
- wav
required:
- type
- data
- format
InputContent:
anyOf:
- $ref: '#/components/schemas/InputTextContent'
- $ref: '#/components/schemas/InputImageContent'
- $ref: '#/components/schemas/InputFileContent'
discriminator:
propertyName: type
InputItem:
discriminator:
propertyName: type
anyOf:
- $ref: '#/components/schemas/EasyInputMessage'
- type: object
title: Item
description: |
An item representing part of the context for the response to be
generated by the model. Can contain text, images, and audio inputs,
as well as previous assistant responses and tool call outputs.
$ref: '#/components/schemas/Item'
- $ref: '#/components/schemas/ItemReferenceParam'
InputMessage:
type: object
title: Input message
description: |
A message input to the model with a role indicating instruction following
hierarchy. Instructions given with the `developer` or `system` role take
precedence over instructions given with the `user` role.
properties:
type:
type: string
description: |
The type of the message input. Always set to `message`.
enum:
- message
x-stainless-const: true
role:
type: string
description: |
The role of the message input. One of `user`, `system`, or `developer`.
enum:
- user
- system
- developer
status:
type: string
description: |
The status of item. One of `in_progress`, `completed`, or
`incomplete`. Populated when items are returned via API.
enum:
- in_progress
- completed
- incomplete
content:
$ref: '#/components/schemas/InputMessageContentList'
required:
- role
- content
InputMessageContentList:
type: array
title: Input item content list
description: |
A list of one or many input items to the model, containing different content
types.
items:
$ref: '#/components/schemas/InputContent'
InputMessageResource:
allOf:
- $ref: '#/components/schemas/InputMessage'
- type: object
properties:
id:
type: string
description: |
The unique ID of the message input.
required:
- id
Invite:
type: object
description: Represents an individual `invite` to the organization.
properties:
object:
type: string
enum:
- organization.invite
description: The object type, which is always `organization.invite`
x-stainless-const: true
id:
type: string
description: The identifier, which can be referenced in API endpoints
email:
type: string
description: The email address of the individual to whom the invite was sent
role:
type: string
enum:
- owner
- reader
description: '`owner` or `reader`'
status:
type: string
enum:
- accepted
- expired
- pending
description: '`accepted`,`expired`, or `pending`'
invited_at:
type: integer
description: The Unix timestamp (in seconds) of when the invite was sent.
expires_at:
type: integer
description: The Unix timestamp (in seconds) of when the invite expires.
accepted_at:
type: integer
description: The Unix timestamp (in seconds) of when the invite was accepted.
projects:
type: array
description: The projects that were granted membership upon acceptance of the invite.
items:
type: object
properties:
id:
type: string
description: Project's public ID
role:
type: string
enum:
- member
- owner
description: Project membership role
required:
- object
- id
- email
- role
- status
- invited_at
- expires_at
x-oaiMeta:
name: The invite object
example: |
{
"object": "organization.invite",
"id": "invite-abc",
"email": "user@example.com",
"role": "owner",
"status": "accepted",
"invited_at": 1711471533,
"expires_at": 1711471533,
"accepted_at": 1711471533,
"projects": [
{
"id": "project-xyz",
"role": "member"
}
]
}
InviteDeleteResponse:
type: object
properties:
object:
type: string
enum:
- organization.invite.deleted
description: The object type, which is always `organization.invite.deleted`
x-stainless-const: true
id:
type: string
deleted:
type: boolean
required:
- object
- id
- deleted
InviteListResponse:
type: object
properties:
object:
type: string
enum:
- list
description: The object type, which is always `list`
x-stainless-const: true
data:
type: array
items:
$ref: '#/components/schemas/Invite'
first_id:
type: string
description: The first `invite_id` in the retrieved `list`
last_id:
type: string
description: The last `invite_id` in the retrieved `list`
has_more:
type: boolean
description: The `has_more` property is used for pagination to indicate there are additional results.
required:
- object
- data
InviteRequest:
type: object
properties:
email:
type: string
description: Send an email to this address
role:
type: string
enum:
- reader
- owner
description: '`owner` or `reader`'
projects:
type: array
description: >-
An array of projects to which membership is granted at the same time the org invite is accepted.
If omitted, the user will be invited to the default project for compatibility with legacy
behavior.
items:
type: object
properties:
id:
type: string
description: Project's public ID
role:
type: string
enum:
- member
- owner
description: Project membership role
required:
- id
- role
required:
- email
- role
Item:
type: object
description: |
Content item used to generate a response.
discriminator:
propertyName: type
anyOf:
- $ref: '#/components/schemas/InputMessage'
- $ref: '#/components/schemas/OutputMessage'
- $ref: '#/components/schemas/FileSearchToolCall'
- $ref: '#/components/schemas/ComputerToolCall'
- $ref: '#/components/schemas/ComputerCallOutputItemParam'
- $ref: '#/components/schemas/WebSearchToolCall'
- $ref: '#/components/schemas/FunctionToolCall'
- $ref: '#/components/schemas/FunctionCallOutputItemParam'
- $ref: '#/components/schemas/ReasoningItem'
- $ref: '#/components/schemas/ImageGenToolCall'
- $ref: '#/components/schemas/CodeInterpreterToolCall'
- $ref: '#/components/schemas/LocalShellToolCall'
- $ref: '#/components/schemas/LocalShellToolCallOutput'
- $ref: '#/components/schemas/MCPListTools'
- $ref: '#/components/schemas/MCPApprovalRequest'
- $ref: '#/components/schemas/MCPApprovalResponse'
- $ref: '#/components/schemas/MCPToolCall'
- $ref: '#/components/schemas/CustomToolCallOutput'
- $ref: '#/components/schemas/CustomToolCall'
ItemResource:
description: |
Content item used to generate a response.
discriminator:
propertyName: type
anyOf:
- $ref: '#/components/schemas/InputMessageResource'
- $ref: '#/components/schemas/OutputMessage'
- $ref: '#/components/schemas/FileSearchToolCall'
- $ref: '#/components/schemas/ComputerToolCall'
- $ref: '#/components/schemas/ComputerToolCallOutputResource'
- $ref: '#/components/schemas/WebSearchToolCall'
- $ref: '#/components/schemas/FunctionToolCallResource'
- $ref: '#/components/schemas/FunctionToolCallOutputResource'
- $ref: '#/components/schemas/ImageGenToolCall'
- $ref: '#/components/schemas/CodeInterpreterToolCall'
- $ref: '#/components/schemas/LocalShellToolCall'
- $ref: '#/components/schemas/LocalShellToolCallOutput'
- $ref: '#/components/schemas/MCPListTools'
- $ref: '#/components/schemas/MCPApprovalRequest'
- $ref: '#/components/schemas/MCPApprovalResponseResource'
- $ref: '#/components/schemas/MCPToolCall'
KeyPress:
type: object
title: KeyPress
description: |
A collection of keypresses the model would like to perform.
properties:
type:
type: string
enum:
- keypress
default: keypress
description: |
Specifies the event type. For a keypress action, this property is
always set to `keypress`.
x-stainless-const: true
keys:
type: array
items:
type: string
description: |
One of the keys the model is requesting to be pressed.
description: |
The combination of keys the model is requesting to be pressed. This is an
array of strings, each representing a key.
required:
- type
- keys
ListAssistantsResponse:
type: object
properties:
object:
type: string
example: list
data:
type: array
items:
$ref: '#/components/schemas/AssistantObject'
first_id:
type: string
example: asst_abc123
last_id:
type: string
example: asst_abc456
has_more:
type: boolean
example: false
required:
- object
- data
- first_id
- last_id
- has_more
x-oaiMeta:
name: List assistants response object
group: chat
example: |
{
"object": "list",
"data": [
{
"id": "asst_abc123",
"object": "assistant",
"created_at": 1698982736,
"name": "Coding Tutor",
"description": null,
"model": "gpt-4o",
"instructions": "You are a helpful assistant designed to make me better at coding!",
"tools": [],
"tool_resources": {},
"metadata": {},
"top_p": 1.0,
"temperature": 1.0,
"response_format": "auto"
},
{
"id": "asst_abc456",
"object": "assistant",
"created_at": 1698982718,
"name": "My Assistant",
"description": null,
"model": "gpt-4o",
"instructions": "You are a helpful assistant designed to make me better at coding!",
"tools": [],
"tool_resources": {},
"metadata": {},
"top_p": 1.0,
"temperature": 1.0,
"response_format": "auto"
},
{
"id": "asst_abc789",
"object": "assistant",
"created_at": 1698982643,
"name": null,
"description": null,
"model": "gpt-4o",
"instructions": null,
"tools": [],
"tool_resources": {},
"metadata": {},
"top_p": 1.0,
"temperature": 1.0,
"response_format": "auto"
}
],
"first_id": "asst_abc123",
"last_id": "asst_abc789",
"has_more": false
}
ListAuditLogsResponse:
type: object
properties:
object:
type: string
enum:
- list
x-stainless-const: true
data:
type: array
items:
$ref: '#/components/schemas/AuditLog'
first_id:
type: string
example: audit_log-defb456h8dks
last_id:
type: string
example: audit_log-hnbkd8s93s
has_more:
type: boolean
required:
- object
- data
- first_id
- last_id
- has_more
ListBatchesResponse:
type: object
properties:
data:
type: array
items:
$ref: '#/components/schemas/Batch'
first_id:
type: string
example: batch_abc123
last_id:
type: string
example: batch_abc456
has_more:
type: boolean
object:
type: string
enum:
- list
x-stainless-const: true
required:
- object
- data
- has_more
ListCertificatesResponse:
type: object
properties:
data:
type: array
items:
$ref: '#/components/schemas/Certificate'
first_id:
type: string
example: cert_abc
last_id:
type: string
example: cert_abc
has_more:
type: boolean
object:
type: string
enum:
- list
x-stainless-const: true
required:
- object
- data
- has_more
ListFilesResponse:
type: object
properties:
object:
type: string
example: list
data:
type: array
items:
$ref: '#/components/schemas/OpenAIFile'
first_id:
type: string
example: file-abc123
last_id:
type: string
example: file-abc456
has_more:
type: boolean
example: false
required:
- object
- data
- first_id
- last_id
- has_more
ListFineTuningCheckpointPermissionResponse:
type: object
properties:
data:
type: array
items:
$ref: '#/components/schemas/FineTuningCheckpointPermission'
object:
type: string
enum:
- list
x-stainless-const: true
first_id:
type: string
nullable: true
last_id:
type: string
nullable: true
has_more:
type: boolean
required:
- object
- data
- has_more
ListFineTuningJobCheckpointsResponse:
type: object
properties:
data:
type: array
items:
$ref: '#/components/schemas/FineTuningJobCheckpoint'
object:
type: string
enum:
- list
x-stainless-const: true
first_id:
type: string
nullable: true
last_id:
type: string
nullable: true
has_more:
type: boolean
required:
- object
- data
- has_more
ListFineTuningJobEventsResponse:
type: object
properties:
data:
type: array
items:
$ref: '#/components/schemas/FineTuningJobEvent'
object:
type: string
enum:
- list
x-stainless-const: true
has_more:
type: boolean
required:
- object
- data
- has_more
ListMessagesResponse:
properties:
object:
type: string
example: list
data:
type: array
items:
$ref: '#/components/schemas/MessageObject'
first_id:
type: string
example: msg_abc123
last_id:
type: string
example: msg_abc123
has_more:
type: boolean
example: false
required:
- object
- data
- first_id
- last_id
- has_more
ListModelsResponse:
type: object
properties:
object:
type: string
enum:
- list
x-stainless-const: true
data:
type: array
items:
$ref: '#/components/schemas/Model'
required:
- object
- data
ListPaginatedFineTuningJobsResponse:
type: object
properties:
data:
type: array
items:
$ref: '#/components/schemas/FineTuningJob'
has_more:
type: boolean
object:
type: string
enum:
- list
x-stainless-const: true
required:
- object
- data
- has_more
ListRunStepsResponse:
properties:
object:
type: string
example: list
data:
type: array
items:
$ref: '#/components/schemas/RunStepObject'
first_id:
type: string
example: step_abc123
last_id:
type: string
example: step_abc456
has_more:
type: boolean
example: false
required:
- object
- data
- first_id
- last_id
- has_more
ListRunsResponse:
type: object
properties:
object:
type: string
example: list
data:
type: array
items:
$ref: '#/components/schemas/RunObject'
first_id:
type: string
example: run_abc123
last_id:
type: string
example: run_abc456
has_more:
type: boolean
example: false
required:
- object
- data
- first_id
- last_id
- has_more
ListVectorStoreFilesResponse:
properties:
object:
type: string
example: list
data:
type: array
items:
$ref: '#/components/schemas/VectorStoreFileObject'
first_id:
type: string
example: file-abc123
last_id:
type: string
example: file-abc456
has_more:
type: boolean
example: false
required:
- object
- data
- first_id
- last_id
- has_more
ListVectorStoresResponse:
properties:
object:
type: string
example: list
data:
type: array
items:
$ref: '#/components/schemas/VectorStoreObject'
first_id:
type: string
example: vs_abc123
last_id:
type: string
example: vs_abc456
has_more:
type: boolean
example: false
required:
- object
- data
- first_id
- last_id
- has_more
LocalShellExecAction:
type: object
title: Local shell exec action
description: |
Execute a shell command on the server.
properties:
type:
type: string
enum:
- exec
description: |
The type of the local shell action. Always `exec`.
x-stainless-const: true
command:
type: array
items:
type: string
description: |
The command to run.
timeout_ms:
type: integer
description: |
Optional timeout in milliseconds for the command.
nullable: true
working_directory:
type: string
description: |
Optional working directory to run the command in.
nullable: true
env:
type: object
additionalProperties:
type: string
description: |
Environment variables to set for the command.
user:
type: string
description: |
Optional user to run the command as.
nullable: true
required:
- type
- command
- env
LocalShellTool:
type: object
title: Local shell tool
description: |
A tool that allows the model to execute shell commands in a local environment.
properties:
type:
type: string
enum:
- local_shell
description: The type of the local shell tool. Always `local_shell`.
x-stainless-const: true
required:
- type
LocalShellToolCall:
type: object
title: Local shell call
description: |
A tool call to run a command on the local shell.
properties:
type:
type: string
enum:
- local_shell_call
description: |
The type of the local shell call. Always `local_shell_call`.
x-stainless-const: true
id:
type: string
description: |
The unique ID of the local shell call.
call_id:
type: string
description: |
The unique ID of the local shell tool call generated by the model.
action:
$ref: '#/components/schemas/LocalShellExecAction'
status:
type: string
enum:
- in_progress
- completed
- incomplete
description: |
The status of the local shell call.
required:
- type
- id
- call_id
- action
- status
LocalShellToolCallOutput:
type: object
title: Local shell call output
description: |
The output of a local shell tool call.
properties:
type:
type: string
enum:
- local_shell_call_output
description: |
The type of the local shell tool call output. Always `local_shell_call_output`.
x-stainless-const: true
id:
type: string
description: |
The unique ID of the local shell tool call generated by the model.
output:
type: string
description: |
A JSON string of the output of the local shell tool call.
status:
type: string
enum:
- in_progress
- completed
- incomplete
description: |
The status of the item. One of `in_progress`, `completed`, or `incomplete`.
nullable: true
required:
- id
- type
- call_id
- output
LogProbProperties:
type: object
description: |
A log probability object.
properties:
token:
type: string
description: |
The token that was used to generate the log probability.
logprob:
type: number
description: |
The log probability of the token.
bytes:
type: array
items:
type: integer
description: |
The bytes that were used to generate the log probability.
required:
- token
- logprob
- bytes
MCPApprovalRequest:
type: object
title: MCP approval request
description: |
A request for human approval of a tool invocation.
properties:
type:
type: string
enum:
- mcp_approval_request
description: |
The type of the item. Always `mcp_approval_request`.
x-stainless-const: true
id:
type: string
description: |
The unique ID of the approval request.
server_label:
type: string
description: |
The label of the MCP server making the request.
name:
type: string
description: |
The name of the tool to run.
arguments:
type: string
description: |
A JSON string of arguments for the tool.
required:
- type
- id
- server_label
- name
- arguments
MCPApprovalResponse:
type: object
title: MCP approval response
description: |
A response to an MCP approval request.
properties:
type:
type: string
enum:
- mcp_approval_response
description: |
The type of the item. Always `mcp_approval_response`.
x-stainless-const: true
id:
type: string
description: |
The unique ID of the approval response
nullable: true
approval_request_id:
type: string
description: |
The ID of the approval request being answered.
approve:
type: boolean
description: |
Whether the request was approved.
reason:
type: string
description: |
Optional reason for the decision.
nullable: true
required:
- type
- request_id
- approve
- approval_request_id
MCPApprovalResponseResource:
type: object
title: MCP approval response
description: |
A response to an MCP approval request.
properties:
type:
type: string
enum:
- mcp_approval_response
description: |
The type of the item. Always `mcp_approval_response`.
x-stainless-const: true
id:
type: string
description: |
The unique ID of the approval response
approval_request_id:
type: string
description: |
The ID of the approval request being answered.
approve:
type: boolean
description: |
Whether the request was approved.
reason:
type: string
description: |
Optional reason for the decision.
nullable: true
required:
- type
- id
- request_id
- approve
- approval_request_id
MCPListTools:
type: object
title: MCP list tools
description: |
A list of tools available on an MCP server.
properties:
type:
type: string
enum:
- mcp_list_tools
description: |
The type of the item. Always `mcp_list_tools`.
x-stainless-const: true
id:
type: string
description: |
The unique ID of the list.
server_label:
type: string
description: |
The label of the MCP server.
tools:
type: array
items:
$ref: '#/components/schemas/MCPListToolsTool'
description: |
The tools available on the server.
error:
type: string
description: |
Error message if the server could not list tools.
nullable: true
required:
- type
- id
- server_label
- tools
MCPListToolsTool:
type: object
title: MCP list tools tool
description: |
A tool available on an MCP server.
properties:
name:
type: string
description: |
The name of the tool.
description:
type: string
description: |
The description of the tool.
nullable: true
input_schema:
type: object
description: |
The JSON schema describing the tool's input.
annotations:
type: object
description: |
Additional annotations about the tool.
nullable: true
required:
- name
- input_schema
MCPTool:
type: object
title: MCP tool
description: |
Give the model access to additional tools via remote Model Context Protocol
(MCP) servers. [Learn more about MCP](https://platform.openai.com/docs/guides/tools-remote-mcp).
properties:
type:
type: string
enum:
- mcp
description: The type of the MCP tool. Always `mcp`.
x-stainless-const: true
server_label:
type: string
description: |
A label for this MCP server, used to identify it in tool calls.
server_url:
type: string
description: |
The URL for the MCP server. One of `server_url` or `connector_id` must be
provided.
connector_id:
type: string
enum:
- connector_dropbox
- connector_gmail
- connector_googlecalendar
- connector_googledrive
- connector_microsoftteams
- connector_outlookcalendar
- connector_outlookemail
- connector_sharepoint
description: |
Identifier for service connectors, like those available in ChatGPT. One of
`server_url` or `connector_id` must be provided. Learn more about service
connectors [here](https://platform.openai.com/docs/guides/tools-remote-mcp#connectors).
Currently supported `connector_id` values are:
- Dropbox: `connector_dropbox`
- Gmail: `connector_gmail`
- Google Calendar: `connector_googlecalendar`
- Google Drive: `connector_googledrive`
- Microsoft Teams: `connector_microsoftteams`
- Outlook Calendar: `connector_outlookcalendar`
- Outlook Email: `connector_outlookemail`
- SharePoint: `connector_sharepoint`
authorization:
type: string
description: |
An OAuth access token that can be used with a remote MCP server, either
with a custom MCP server URL or a service connector. Your application
must handle the OAuth authorization flow and provide the token here.
server_description:
type: string
description: |
Optional description of the MCP server, used to provide more context.
headers:
type: object
additionalProperties:
type: string
nullable: true
description: |
Optional HTTP headers to send to the MCP server. Use for authentication
or other purposes.
allowed_tools:
description: |
List of allowed tool names or a filter object.
nullable: true
anyOf:
- type: array
title: MCP allowed tools
description: A string array of allowed tool names
items:
type: string
- $ref: '#/components/schemas/MCPToolFilter'
require_approval:
description: Specify which of the MCP server's tools require approval.
nullable: true
anyOf:
- type: object
title: MCP tool approval filter
description: |
Specify which of the MCP server's tools require approval. Can be
`always`, `never`, or a filter object associated with tools
that require approval.
properties:
always:
$ref: '#/components/schemas/MCPToolFilter'
never:
$ref: '#/components/schemas/MCPToolFilter'
additionalProperties: false
- type: string
title: MCP tool approval setting
description: |
Specify a single approval policy for all tools. One of `always` or
`never`. When set to `always`, all tools will require approval. When
set to `never`, all tools will not require approval.
enum:
- always
- never
required:
- type
- server_label
MCPToolCall:
type: object
title: MCP tool call
description: |
An invocation of a tool on an MCP server.
properties:
type:
type: string
enum:
- mcp_call
description: |
The type of the item. Always `mcp_call`.
x-stainless-const: true
id:
type: string
description: |
The unique ID of the tool call.
server_label:
type: string
description: |
The label of the MCP server running the tool.
name:
type: string
description: |
The name of the tool that was run.
arguments:
type: string
description: |
A JSON string of the arguments passed to the tool.
output:
type: string
description: |
The output from the tool call.
nullable: true
error:
type: string
description: |
The error from the tool call, if any.
nullable: true
required:
- type
- id
- server_label
- name
- arguments
MCPToolFilter:
type: object
title: MCP tool filter
description: |
A filter object to specify which tools are allowed.
properties:
tool_names:
type: array
title: MCP allowed tools
items:
type: string
description: List of allowed tool names.
read_only:
type: boolean
description: >
Indicates whether or not a tool modifies data or is read-only. If an
MCP server is [annotated with
`readOnlyHint`](https://modelcontextprotocol.io/specification/2025-06-18/schema#toolannotations-readonlyhint),
it will match this filter.
required: []
additionalProperties: false
MessageContentImageFileObject:
title: Image file
type: object
description: >-
References an image [File](https://platform.openai.com/docs/api-reference/files) in the content of a
message.
properties:
type:
description: Always `image_file`.
type: string
enum:
- image_file
x-stainless-const: true
image_file:
type: object
properties:
file_id:
description: >-
The [File](https://platform.openai.com/docs/api-reference/files) ID of the image in the
message content. Set `purpose="vision"` when uploading the File if you need to later display
the file content.
type: string
detail:
type: string
description: >-
Specifies the detail level of the image if specified by the user. `low` uses fewer tokens, you
can opt in to high resolution using `high`.
enum:
- auto
- low
- high
default: auto
required:
- file_id
required:
- type
- image_file
MessageContentImageUrlObject:
title: Image URL
type: object
description: References an image URL in the content of a message.
properties:
type:
type: string
enum:
- image_url
description: The type of the content part.
x-stainless-const: true
image_url:
type: object
properties:
url:
type: string
description: 'The external URL of the image, must be a supported image types: jpeg, jpg, png, gif, webp.'
format: uri
detail:
type: string
description: >-
Specifies the detail level of the image. `low` uses fewer tokens, you can opt in to high
resolution using `high`. Default value is `auto`
enum:
- auto
- low
- high
default: auto
required:
- url
required:
- type
- image_url
MessageContentRefusalObject:
title: Refusal
type: object
description: The refusal content generated by the assistant.
properties:
type:
description: Always `refusal`.
type: string
enum:
- refusal
x-stainless-const: true
refusal:
type: string
nullable: false
required:
- type
- refusal
MessageContentTextAnnotationsFileCitationObject:
title: File citation
type: object
description: >-
A citation within the message that points to a specific quote from a specific File associated with the
assistant or the message. Generated when the assistant uses the "file_search" tool to search files.
properties:
type:
description: Always `file_citation`.
type: string
enum:
- file_citation
x-stainless-const: true
text:
description: The text in the message content that needs to be replaced.
type: string
file_citation:
type: object
properties:
file_id:
description: The ID of the specific File the citation is from.
type: string
required:
- file_id
start_index:
type: integer
minimum: 0
end_index:
type: integer
minimum: 0
required:
- type
- text
- file_citation
- start_index
- end_index
MessageContentTextAnnotationsFilePathObject:
title: File path
type: object
description: >-
A URL for the file that's generated when the assistant used the `code_interpreter` tool to generate a
file.
properties:
type:
description: Always `file_path`.
type: string
enum:
- file_path
x-stainless-const: true
text:
description: The text in the message content that needs to be replaced.
type: string
file_path:
type: object
properties:
file_id:
description: The ID of the file that was generated.
type: string
required:
- file_id
start_index:
type: integer
minimum: 0
end_index:
type: integer
minimum: 0
required:
- type
- text
- file_path
- start_index
- end_index
MessageContentTextObject:
title: Text
type: object
description: The text content that is part of a message.
properties:
type:
description: Always `text`.
type: string
enum:
- text
x-stainless-const: true
text:
type: object
properties:
value:
description: The data that makes up the text.
type: string
annotations:
type: array
items:
$ref: '#/components/schemas/TextAnnotation'
required:
- value
- annotations
required:
- type
- text
MessageDeltaContentImageFileObject:
title: Image file
type: object
description: >-
References an image [File](https://platform.openai.com/docs/api-reference/files) in the content of a
message.
properties:
index:
type: integer
description: The index of the content part in the message.
type:
description: Always `image_file`.
type: string
enum:
- image_file
x-stainless-const: true
image_file:
type: object
properties:
file_id:
description: >-
The [File](https://platform.openai.com/docs/api-reference/files) ID of the image in the
message content. Set `purpose="vision"` when uploading the File if you need to later display
the file content.
type: string
detail:
type: string
description: >-
Specifies the detail level of the image if specified by the user. `low` uses fewer tokens, you
can opt in to high resolution using `high`.
enum:
- auto
- low
- high
default: auto
required:
- index
- type
MessageDeltaContentImageUrlObject:
title: Image URL
type: object
description: References an image URL in the content of a message.
properties:
index:
type: integer
description: The index of the content part in the message.
type:
description: Always `image_url`.
type: string
enum:
- image_url
x-stainless-const: true
image_url:
type: object
properties:
url:
description: 'The URL of the image, must be a supported image types: jpeg, jpg, png, gif, webp.'
type: string
detail:
type: string
description: >-
Specifies the detail level of the image. `low` uses fewer tokens, you can opt in to high
resolution using `high`.
enum:
- auto
- low
- high
default: auto
required:
- index
- type
MessageDeltaContentRefusalObject:
title: Refusal
type: object
description: The refusal content that is part of a message.
properties:
index:
type: integer
description: The index of the refusal part in the message.
type:
description: Always `refusal`.
type: string
enum:
- refusal
x-stainless-const: true
refusal:
type: string
required:
- index
- type
MessageDeltaContentTextAnnotationsFileCitationObject:
title: File citation
type: object
description: >-
A citation within the message that points to a specific quote from a specific File associated with the
assistant or the message. Generated when the assistant uses the "file_search" tool to search files.
properties:
index:
type: integer
description: The index of the annotation in the text content part.
type:
description: Always `file_citation`.
type: string
enum:
- file_citation
x-stainless-const: true
text:
description: The text in the message content that needs to be replaced.
type: string
file_citation:
type: object
properties:
file_id:
description: The ID of the specific File the citation is from.
type: string
quote:
description: The specific quote in the file.
type: string
start_index:
type: integer
minimum: 0
end_index:
type: integer
minimum: 0
required:
- index
- type
MessageDeltaContentTextAnnotationsFilePathObject:
title: File path
type: object
description: >-
A URL for the file that's generated when the assistant used the `code_interpreter` tool to generate a
file.
properties:
index:
type: integer
description: The index of the annotation in the text content part.
type:
description: Always `file_path`.
type: string
enum:
- file_path
x-stainless-const: true
text:
description: The text in the message content that needs to be replaced.
type: string
file_path:
type: object
properties:
file_id:
description: The ID of the file that was generated.
type: string
start_index:
type: integer
minimum: 0
end_index:
type: integer
minimum: 0
required:
- index
- type
MessageDeltaContentTextObject:
title: Text
type: object
description: The text content that is part of a message.
properties:
index:
type: integer
description: The index of the content part in the message.
type:
description: Always `text`.
type: string
enum:
- text
x-stainless-const: true
text:
type: object
properties:
value:
description: The data that makes up the text.
type: string
annotations:
type: array
items:
$ref: '#/components/schemas/TextAnnotationDelta'
required:
- index
- type
MessageDeltaObject:
type: object
title: Message delta object
description: |
Represents a message delta i.e. any changed fields on a message during streaming.
properties:
id:
description: The identifier of the message, which can be referenced in API endpoints.
type: string
object:
description: The object type, which is always `thread.message.delta`.
type: string
enum:
- thread.message.delta
x-stainless-const: true
delta:
description: The delta containing the fields that have changed on the Message.
type: object
properties:
role:
description: The entity that produced the message. One of `user` or `assistant`.
type: string
enum:
- user
- assistant
content:
description: The content of the message in array of text and/or images.
type: array
items:
$ref: '#/components/schemas/MessageContentDelta'
required:
- id
- object
- delta
x-oaiMeta:
name: The message delta object
beta: true
example: |
{
"id": "msg_123",
"object": "thread.message.delta",
"delta": {
"content": [
{
"index": 0,
"type": "text",
"text": { "value": "Hello", "annotations": [] }
}
]
}
}
MessageObject:
type: object
title: The message object
description: Represents a message within a [thread](https://platform.openai.com/docs/api-reference/threads).
properties:
id:
description: The identifier, which can be referenced in API endpoints.
type: string
object:
description: The object type, which is always `thread.message`.
type: string
enum:
- thread.message
x-stainless-const: true
created_at:
description: The Unix timestamp (in seconds) for when the message was created.
type: integer
thread_id:
description: >-
The [thread](https://platform.openai.com/docs/api-reference/threads) ID that this message belongs
to.
type: string
status:
description: The status of the message, which can be either `in_progress`, `incomplete`, or `completed`.
type: string
enum:
- in_progress
- incomplete
- completed
incomplete_details:
description: On an incomplete message, details about why the message is incomplete.
type: object
properties:
reason:
type: string
description: The reason the message is incomplete.
enum:
- content_filter
- max_tokens
- run_cancelled
- run_expired
- run_failed
nullable: true
required:
- reason
completed_at:
description: The Unix timestamp (in seconds) for when the message was completed.
type: integer
nullable: true
incomplete_at:
description: The Unix timestamp (in seconds) for when the message was marked as incomplete.
type: integer
nullable: true
role:
description: The entity that produced the message. One of `user` or `assistant`.
type: string
enum:
- user
- assistant
content:
description: The content of the message in array of text and/or images.
type: array
items:
$ref: '#/components/schemas/MessageContent'
assistant_id:
description: >-
If applicable, the ID of the
[assistant](https://platform.openai.com/docs/api-reference/assistants) that authored this message.
type: string
nullable: true
run_id:
description: >-
The ID of the [run](https://platform.openai.com/docs/api-reference/runs) associated with the
creation of this message. Value is `null` when messages are created manually using the create
message or create thread endpoints.
type: string
nullable: true
attachments:
type: array
items:
type: object
properties:
file_id:
type: string
description: The ID of the file to attach to the message.
tools:
description: The tools to add this file to.
type: array
items:
anyOf:
- $ref: '#/components/schemas/AssistantToolsCode'
- $ref: '#/components/schemas/AssistantToolsFileSearchTypeOnly'
description: A list of files attached to the message, and the tools they were added to.
nullable: true
metadata:
$ref: '#/components/schemas/Metadata'
required:
- id
- object
- created_at
- thread_id
- status
- incomplete_details
- completed_at
- incomplete_at
- role
- content
- assistant_id
- run_id
- attachments
- metadata
x-oaiMeta:
name: The message object
beta: true
example: |
{
"id": "msg_abc123",
"object": "thread.message",
"created_at": 1698983503,
"thread_id": "thread_abc123",
"role": "assistant",
"content": [
{
"type": "text",
"text": {
"value": "Hi! How can I help you today?",
"annotations": []
}
}
],
"assistant_id": "asst_abc123",
"run_id": "run_abc123",
"attachments": [],
"metadata": {}
}
MessageRequestContentTextObject:
title: Text
type: object
description: The text content that is part of a message.
properties:
type:
description: Always `text`.
type: string
enum:
- text
x-stainless-const: true
text:
type: string
description: Text content to be sent to the model
required:
- type
- text
MessageStreamEvent:
anyOf:
- type: object
properties:
event:
type: string
enum:
- thread.message.created
x-stainless-const: true
data:
$ref: '#/components/schemas/MessageObject'
required:
- event
- data
description: >-
Occurs when a [message](https://platform.openai.com/docs/api-reference/messages/object) is
created.
x-oaiMeta:
dataDescription: '`data` is a [message](/docs/api-reference/messages/object)'
- type: object
properties:
event:
type: string
enum:
- thread.message.in_progress
x-stainless-const: true
data:
$ref: '#/components/schemas/MessageObject'
required:
- event
- data
description: >-
Occurs when a [message](https://platform.openai.com/docs/api-reference/messages/object) moves to
an `in_progress` state.
x-oaiMeta:
dataDescription: '`data` is a [message](/docs/api-reference/messages/object)'
- type: object
properties:
event:
type: string
enum:
- thread.message.delta
x-stainless-const: true
data:
$ref: '#/components/schemas/MessageDeltaObject'
required:
- event
- data
description: >-
Occurs when parts of a [Message](https://platform.openai.com/docs/api-reference/messages/object)
are being streamed.
x-oaiMeta:
dataDescription: '`data` is a [message delta](/docs/api-reference/assistants-streaming/message-delta-object)'
- type: object
properties:
event:
type: string
enum:
- thread.message.completed
x-stainless-const: true
data:
$ref: '#/components/schemas/MessageObject'
required:
- event
- data
description: >-
Occurs when a [message](https://platform.openai.com/docs/api-reference/messages/object) is
completed.
x-oaiMeta:
dataDescription: '`data` is a [message](/docs/api-reference/messages/object)'
- type: object
properties:
event:
type: string
enum:
- thread.message.incomplete
x-stainless-const: true
data:
$ref: '#/components/schemas/MessageObject'
required:
- event
- data
description: >-
Occurs when a [message](https://platform.openai.com/docs/api-reference/messages/object) ends
before it is completed.
x-oaiMeta:
dataDescription: '`data` is a [message](/docs/api-reference/messages/object)'
discriminator:
propertyName: event
Metadata:
type: object
description: |
Set of 16 key-value pairs that can be attached to an object. This can be
useful for storing additional information about the object in a structured
format, and querying for objects via API or the dashboard.
Keys are strings with a maximum length of 64 characters. Values are strings
with a maximum length of 512 characters.
additionalProperties:
type: string
x-oaiTypeLabel: map
nullable: true
Model:
title: Model
description: Describes an OpenAI model offering that can be used with the API.
properties:
id:
type: string
description: The model identifier, which can be referenced in the API endpoints.
created:
type: integer
description: The Unix timestamp (in seconds) when the model was created.
object:
type: string
description: The object type, which is always "model".
enum:
- model
x-stainless-const: true
owned_by:
type: string
description: The organization that owns the model.
required:
- id
- object
- created
- owned_by
x-oaiMeta:
name: The model object
example: |
{
"id": "VAR_chat_model_id",
"object": "model",
"created": 1686935002,
"owned_by": "openai"
}
ModelIds:
anyOf:
- $ref: '#/components/schemas/ModelIdsShared'
- $ref: '#/components/schemas/ModelIdsResponses'
ModelIdsResponses:
example: gpt-4o
anyOf:
- $ref: '#/components/schemas/ModelIdsShared'
- type: string
title: ResponsesOnlyModel
enum:
- o1-pro
- o1-pro-2025-03-19
- o3-pro
- o3-pro-2025-06-10
- o3-deep-research
- o3-deep-research-2025-06-26
- o4-mini-deep-research
- o4-mini-deep-research-2025-06-26
- computer-use-preview
- computer-use-preview-2025-03-11
ModelIdsShared:
example: gpt-4o
anyOf:
- type: string
- $ref: '#/components/schemas/ChatModel'
ModelResponseProperties:
type: object
properties:
metadata:
$ref: '#/components/schemas/Metadata'
top_logprobs:
description: |
An integer between 0 and 20 specifying the number of most likely tokens to
return at each token position, each with an associated log probability.
type: integer
minimum: 0
maximum: 20
nullable: true
temperature:
type: number
minimum: 0
maximum: 2
default: 1
example: 1
nullable: true
description: >
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
more random, while lower values like 0.2 will make it more focused and deterministic.
We generally recommend altering this or `top_p` but not both.
top_p:
type: number
minimum: 0
maximum: 1
default: 1
example: 1
nullable: true
description: |
An alternative to sampling with temperature, called nucleus sampling,
where the model considers the results of the tokens with top_p probability
mass. So 0.1 means only the tokens comprising the top 10% probability mass
are considered.
We generally recommend altering this or `temperature` but not both.
user:
type: string
example: user-1234
deprecated: true
description: >
This field is being replaced by `safety_identifier` and `prompt_cache_key`. Use `prompt_cache_key`
instead to maintain caching optimizations.
A stable identifier for your end-users.
Used to boost cache hit rates by better bucketing similar requests and to help OpenAI detect and
prevent abuse. [Learn
more](https://platform.openai.com/docs/guides/safety-best-practices#safety-identifiers).
safety_identifier:
type: string
example: safety-identifier-1234
description: >
A stable identifier used to help detect users of your application that may be violating OpenAI's
usage policies.
The IDs should be a string that uniquely identifies each user. We recommend hashing their username
or email address, in order to avoid sending us any identifying information. [Learn
more](https://platform.openai.com/docs/guides/safety-best-practices#safety-identifiers).
prompt_cache_key:
type: string
example: prompt-cache-key-1234
description: >
Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces
the `user` field. [Learn more](https://platform.openai.com/docs/guides/prompt-caching).
service_tier:
$ref: '#/components/schemas/ServiceTier'
ModifyAssistantRequest:
type: object
additionalProperties: false
properties:
model:
description: >
ID of the model to use. You can use the [List
models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your
available models, or see our [Model overview](https://platform.openai.com/docs/models) for
descriptions of them.
anyOf:
- type: string
- $ref: '#/components/schemas/AssistantSupportedModels'
reasoning_effort:
$ref: '#/components/schemas/ReasoningEffort'
name:
description: |
The name of the assistant. The maximum length is 256 characters.
type: string
nullable: true
maxLength: 256
description:
description: |
The description of the assistant. The maximum length is 512 characters.
type: string
nullable: true
maxLength: 512
instructions:
description: |
The system instructions that the assistant uses. The maximum length is 256,000 characters.
type: string
nullable: true
maxLength: 256000
tools:
description: >
A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools
can be of types `code_interpreter`, `file_search`, or `function`.
default: []
type: array
maxItems: 128
items:
$ref: '#/components/schemas/AssistantTool'
tool_resources:
type: object
description: >
A set of resources that are used by the assistant's tools. The resources are specific to the type
of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the
`file_search` tool requires a list of vector store IDs.
properties:
code_interpreter:
type: object
properties:
file_ids:
type: array
description: >
Overrides the list of [file](https://platform.openai.com/docs/api-reference/files) IDs
made available to the `code_interpreter` tool. There can be a maximum of 20 files
associated with the tool.
default: []
maxItems: 20
items:
type: string
file_search:
type: object
properties:
vector_store_ids:
type: array
description: >
Overrides the [vector
store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to
this assistant. There can be a maximum of 1 vector store attached to the assistant.
maxItems: 1
items:
type: string
nullable: true
metadata:
$ref: '#/components/schemas/Metadata'
temperature:
description: >
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
more random, while lower values like 0.2 will make it more focused and deterministic.
type: number
minimum: 0
maximum: 2
default: 1
example: 1
nullable: true
top_p:
type: number
minimum: 0
maximum: 1
default: 1
example: 1
nullable: true
description: >
An alternative to sampling with temperature, called nucleus sampling, where the model considers
the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
response_format:
$ref: '#/components/schemas/AssistantsApiResponseFormatOption'
nullable: true
ModifyCertificateRequest:
type: object
properties:
name:
type: string
description: The updated name for the certificate
required:
- name
ModifyMessageRequest:
type: object
additionalProperties: false
properties:
metadata:
$ref: '#/components/schemas/Metadata'
ModifyRunRequest:
type: object
additionalProperties: false
properties:
metadata:
$ref: '#/components/schemas/Metadata'
ModifyThreadRequest:
type: object
additionalProperties: false
properties:
tool_resources:
type: object
description: >
A set of resources that are made available to the assistant's tools in this thread. The resources
are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file
IDs, while the `file_search` tool requires a list of vector store IDs.
properties:
code_interpreter:
type: object
properties:
file_ids:
type: array
description: >
A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available
to the `code_interpreter` tool. There can be a maximum of 20 files associated with the
tool.
default: []
maxItems: 20
items:
type: string
file_search:
type: object
properties:
vector_store_ids:
type: array
description: >
The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object)
attached to this thread. There can be a maximum of 1 vector store attached to the thread.
maxItems: 1
items:
type: string
nullable: true
metadata:
$ref: '#/components/schemas/Metadata'
Move:
type: object
title: Move
description: |
A mouse move action.
properties:
type:
type: string
enum:
- move
default: move
description: |
Specifies the event type. For a move action, this property is
always set to `move`.
x-stainless-const: true
x:
type: integer
description: |
The x-coordinate to move to.
'y':
type: integer
description: |
The y-coordinate to move to.
required:
- type
- x
- 'y'
OpenAIFile:
title: OpenAIFile
description: The `File` object represents a document that has been uploaded to OpenAI.
properties:
id:
type: string
description: The file identifier, which can be referenced in the API endpoints.
bytes:
type: integer
description: The size of the file, in bytes.
created_at:
type: integer
description: The Unix timestamp (in seconds) for when the file was created.
expires_at:
type: integer
description: The Unix timestamp (in seconds) for when the file will expire.
filename:
type: string
description: The name of the file.
object:
type: string
description: The object type, which is always `file`.
enum:
- file
x-stainless-const: true
purpose:
type: string
description: >-
The intended purpose of the file. Supported values are `assistants`, `assistants_output`, `batch`,
`batch_output`, `fine-tune`, `fine-tune-results`, `vision`, and `user_data`.
enum:
- assistants
- assistants_output
- batch
- batch_output
- fine-tune
- fine-tune-results
- vision
- user_data
status:
type: string
deprecated: true
description: >-
Deprecated. The current status of the file, which can be either `uploaded`, `processed`, or
`error`.
enum:
- uploaded
- processed
- error
status_details:
type: string
deprecated: true
description: >-
Deprecated. For details on why a fine-tuning training file failed validation, see the `error`
field on `fine_tuning.job`.
required:
- id
- object
- bytes
- created_at
- filename
- purpose
- status
x-oaiMeta:
name: The file object
example: |
{
"id": "file-abc123",
"object": "file",
"bytes": 120000,
"created_at": 1677610602,
"expires_at": 1680202602,
"filename": "salesOverview.pdf",
"purpose": "assistants",
}
OtherChunkingStrategyResponseParam:
type: object
title: Other Chunking Strategy
description: >-
This is returned when the chunking strategy is unknown. Typically, this is because the file was
indexed before the `chunking_strategy` concept was introduced in the API.
additionalProperties: false
properties:
type:
type: string
description: Always `other`.
enum:
- other
x-stainless-const: true
required:
- type
OutputAudio:
type: object
title: Output audio
description: |
An audio output from the model.
properties:
type:
type: string
description: |
The type of the output audio. Always `output_audio`.
enum:
- output_audio
x-stainless-const: true
data:
type: string
description: |
Base64-encoded audio data from the model.
transcript:
type: string
description: |
The transcript of the audio data from the model.
required:
- type
- data
- transcript
OutputContent:
anyOf:
- $ref: '#/components/schemas/OutputTextContent'
- $ref: '#/components/schemas/RefusalContent'
discriminator:
propertyName: type
OutputItem:
anyOf:
- $ref: '#/components/schemas/OutputMessage'
- $ref: '#/components/schemas/FileSearchToolCall'
- $ref: '#/components/schemas/FunctionToolCall'
- $ref: '#/components/schemas/WebSearchToolCall'
- $ref: '#/components/schemas/ComputerToolCall'
- $ref: '#/components/schemas/ReasoningItem'
- $ref: '#/components/schemas/ImageGenToolCall'
- $ref: '#/components/schemas/CodeInterpreterToolCall'
- $ref: '#/components/schemas/LocalShellToolCall'
- $ref: '#/components/schemas/MCPToolCall'
- $ref: '#/components/schemas/MCPListTools'
- $ref: '#/components/schemas/MCPApprovalRequest'
- $ref: '#/components/schemas/CustomToolCall'
discriminator:
propertyName: type
OutputMessage:
type: object
title: Output message
description: |
An output message from the model.
properties:
id:
type: string
description: |
The unique ID of the output message.
x-stainless-go-json: omitzero
type:
type: string
description: |
The type of the output message. Always `message`.
enum:
- message
x-stainless-const: true
role:
type: string
description: |
The role of the output message. Always `assistant`.
enum:
- assistant
x-stainless-const: true
content:
type: array
description: |
The content of the output message.
items:
$ref: '#/components/schemas/OutputContent'
status:
type: string
description: |
The status of the message input. One of `in_progress`, `completed`, or
`incomplete`. Populated when input items are returned via API.
enum:
- in_progress
- completed
- incomplete
required:
- id
- type
- role
- content
- status
ParallelToolCalls:
description: >-
Whether to enable [parallel function
calling](https://platform.openai.com/docs/guides/function-calling#configuring-parallel-function-calling)
during tool use.
type: boolean
default: true
PartialImages:
type: integer
maximum: 3
minimum: 0
default: 0
example: 1
nullable: true
description: |
The number of partial images to generate. This parameter is used for
streaming responses that return partial images. Value must be between 0 and 3.
When set to 0, the response will be a single image sent in one streaming event.
Note that the final image may be sent before the full number of partial images
are generated if the full image is generated more quickly.
PredictionContent:
type: object
title: Static Content
description: |
Static predicted output content, such as the content of a text file that is
being regenerated.
required:
- type
- content
properties:
type:
type: string
enum:
- content
description: |
The type of the predicted content you want to provide. This type is
currently always `content`.
x-stainless-const: true
content:
description: |
The content that should be matched when generating a model response.
If generated tokens would match this content, the entire model response
can be returned much more quickly.
anyOf:
- type: string
title: Text content
description: |
The content used for a Predicted Output. This is often the
text of a file you are regenerating with minor changes.
- type: array
description: >-
An array of content parts with a defined type. Supported options differ based on the
[model](https://platform.openai.com/docs/models) being used to generate the response. Can
contain text inputs.
title: Array of content parts
items:
$ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
minItems: 1
Project:
type: object
description: Represents an individual project.
properties:
id:
type: string
description: The identifier, which can be referenced in API endpoints
object:
type: string
enum:
- organization.project
description: The object type, which is always `organization.project`
x-stainless-const: true
name:
type: string
description: The name of the project. This appears in reporting.
created_at:
type: integer
description: The Unix timestamp (in seconds) of when the project was created.
archived_at:
type: integer
nullable: true
description: The Unix timestamp (in seconds) of when the project was archived or `null`.
status:
type: string
enum:
- active
- archived
description: '`active` or `archived`'
required:
- id
- object
- name
- created_at
- status
x-oaiMeta:
name: The project object
example: |
{
"id": "proj_abc",
"object": "organization.project",
"name": "Project example",
"created_at": 1711471533,
"archived_at": null,
"status": "active"
}
ProjectApiKey:
type: object
description: Represents an individual API key in a project.
properties:
object:
type: string
enum:
- organization.project.api_key
description: The object type, which is always `organization.project.api_key`
x-stainless-const: true
redacted_value:
type: string
description: The redacted value of the API key
name:
type: string
description: The name of the API key
created_at:
type: integer
description: The Unix timestamp (in seconds) of when the API key was created
last_used_at:
type: integer
description: The Unix timestamp (in seconds) of when the API key was last used.
id:
type: string
description: The identifier, which can be referenced in API endpoints
owner:
type: object
properties:
type:
type: string
enum:
- user
- service_account
description: '`user` or `service_account`'
user:
$ref: '#/components/schemas/ProjectUser'
service_account:
$ref: '#/components/schemas/ProjectServiceAccount'
required:
- object
- redacted_value
- name
- created_at
- last_used_at
- id
- owner
x-oaiMeta:
name: The project API key object
example: |
{
"object": "organization.project.api_key",
"redacted_value": "sk-abc...def",
"name": "My API Key",
"created_at": 1711471533,
"last_used_at": 1711471534,
"id": "key_abc",
"owner": {
"type": "user",
"user": {
"object": "organization.project.user",
"id": "user_abc",
"name": "First Last",
"email": "user@example.com",
"role": "owner",
"created_at": 1711471533
}
}
}
ProjectApiKeyDeleteResponse:
type: object
properties:
object:
type: string
enum:
- organization.project.api_key.deleted
x-stainless-const: true
id:
type: string
deleted:
type: boolean
required:
- object
- id
- deleted
ProjectApiKeyListResponse:
type: object
properties:
object:
type: string
enum:
- list
x-stainless-const: true
data:
type: array
items:
$ref: '#/components/schemas/ProjectApiKey'
first_id:
type: string
last_id:
type: string
has_more:
type: boolean
required:
- object
- data
- first_id
- last_id
- has_more
ProjectCreateRequest:
type: object
properties:
name:
type: string
description: The friendly name of the project, this name appears in reports.
required:
- name
ProjectListResponse:
type: object
properties:
object:
type: string
enum:
- list
x-stainless-const: true
data:
type: array
items:
$ref: '#/components/schemas/Project'
first_id:
type: string
last_id:
type: string
has_more:
type: boolean
required:
- object
- data
- first_id
- last_id
- has_more
ProjectRateLimit:
type: object
description: Represents a project rate limit config.
properties:
object:
type: string
enum:
- project.rate_limit
description: The object type, which is always `project.rate_limit`
x-stainless-const: true
id:
type: string
description: The identifier, which can be referenced in API endpoints.
model:
type: string
description: The model this rate limit applies to.
max_requests_per_1_minute:
type: integer
description: The maximum requests per minute.
max_tokens_per_1_minute:
type: integer
description: The maximum tokens per minute.
max_images_per_1_minute:
type: integer
description: The maximum images per minute. Only present for relevant models.
max_audio_megabytes_per_1_minute:
type: integer
description: The maximum audio megabytes per minute. Only present for relevant models.
max_requests_per_1_day:
type: integer
description: The maximum requests per day. Only present for relevant models.
batch_1_day_max_input_tokens:
type: integer
description: The maximum batch input tokens per day. Only present for relevant models.
required:
- object
- id
- model
- max_requests_per_1_minute
- max_tokens_per_1_minute
x-oaiMeta:
name: The project rate limit object
example: |
{
"object": "project.rate_limit",
"id": "rl_ada",
"model": "ada",
"max_requests_per_1_minute": 600,
"max_tokens_per_1_minute": 150000,
"max_images_per_1_minute": 10
}
ProjectRateLimitListResponse:
type: object
properties:
object:
type: string
enum:
- list
x-stainless-const: true
data:
type: array
items:
$ref: '#/components/schemas/ProjectRateLimit'
first_id:
type: string
last_id:
type: string
has_more:
type: boolean
required:
- object
- data
- first_id
- last_id
- has_more
ProjectRateLimitUpdateRequest:
type: object
properties:
max_requests_per_1_minute:
type: integer
description: The maximum requests per minute.
max_tokens_per_1_minute:
type: integer
description: The maximum tokens per minute.
max_images_per_1_minute:
type: integer
description: The maximum images per minute. Only relevant for certain models.
max_audio_megabytes_per_1_minute:
type: integer
description: The maximum audio megabytes per minute. Only relevant for certain models.
max_requests_per_1_day:
type: integer
description: The maximum requests per day. Only relevant for certain models.
batch_1_day_max_input_tokens:
type: integer
description: The maximum batch input tokens per day. Only relevant for certain models.
ProjectServiceAccount:
type: object
description: Represents an individual service account in a project.
properties:
object:
type: string
enum:
- organization.project.service_account
description: The object type, which is always `organization.project.service_account`
x-stainless-const: true
id:
type: string
description: The identifier, which can be referenced in API endpoints
name:
type: string
description: The name of the service account
role:
type: string
enum:
- owner
- member
description: '`owner` or `member`'
created_at:
type: integer
description: The Unix timestamp (in seconds) of when the service account was created
required:
- object
- id
- name
- role
- created_at
x-oaiMeta:
name: The project service account object
example: |
{
"object": "organization.project.service_account",
"id": "svc_acct_abc",
"name": "Service Account",
"role": "owner",
"created_at": 1711471533
}
ProjectServiceAccountApiKey:
type: object
properties:
object:
type: string
enum:
- organization.project.service_account.api_key
description: The object type, which is always `organization.project.service_account.api_key`
x-stainless-const: true
value:
type: string
name:
type: string
created_at:
type: integer
id:
type: string
required:
- object
- value
- name
- created_at
- id
ProjectServiceAccountCreateRequest:
type: object
properties:
name:
type: string
description: The name of the service account being created.
required:
- name
ProjectServiceAccountCreateResponse:
type: object
properties:
object:
type: string
enum:
- organization.project.service_account
x-stainless-const: true
id:
type: string
name:
type: string
role:
type: string
enum:
- member
description: Service accounts can only have one role of type `member`
x-stainless-const: true
created_at:
type: integer
api_key:
$ref: '#/components/schemas/ProjectServiceAccountApiKey'
required:
- object
- id
- name
- role
- created_at
- api_key
ProjectServiceAccountDeleteResponse:
type: object
properties:
object:
type: string
enum:
- organization.project.service_account.deleted
x-stainless-const: true
id:
type: string
deleted:
type: boolean
required:
- object
- id
- deleted
ProjectServiceAccountListResponse:
type: object
properties:
object:
type: string
enum:
- list
x-stainless-const: true
data:
type: array
items:
$ref: '#/components/schemas/ProjectServiceAccount'
first_id:
type: string
last_id:
type: string
has_more:
type: boolean
required:
- object
- data
- first_id
- last_id
- has_more
ProjectUpdateRequest:
type: object
properties:
name:
type: string
description: The updated name of the project, this name appears in reports.
required:
- name
ProjectUser:
type: object
description: Represents an individual user in a project.
properties:
object:
type: string
enum:
- organization.project.user
description: The object type, which is always `organization.project.user`
x-stainless-const: true
id:
type: string
description: The identifier, which can be referenced in API endpoints
name:
type: string
description: The name of the user
email:
type: string
description: The email address of the user
role:
type: string
enum:
- owner
- member
description: '`owner` or `member`'
added_at:
type: integer
description: The Unix timestamp (in seconds) of when the project was added.
required:
- object
- id
- name
- email
- role
- added_at
x-oaiMeta:
name: The project user object
example: |
{
"object": "organization.project.user",
"id": "user_abc",
"name": "First Last",
"email": "user@example.com",
"role": "owner",
"added_at": 1711471533
}
ProjectUserCreateRequest:
type: object
properties:
user_id:
type: string
description: The ID of the user.
role:
type: string
enum:
- owner
- member
description: '`owner` or `member`'
required:
- user_id
- role
ProjectUserDeleteResponse:
type: object
properties:
object:
type: string
enum:
- organization.project.user.deleted
x-stainless-const: true
id:
type: string
deleted:
type: boolean
required:
- object
- id
- deleted
ProjectUserListResponse:
type: object
properties:
object:
type: string
data:
type: array
items:
$ref: '#/components/schemas/ProjectUser'
first_id:
type: string
last_id:
type: string
has_more:
type: boolean
required:
- object
- data
- first_id
- last_id
- has_more
ProjectUserUpdateRequest:
type: object
properties:
role:
type: string
enum:
- owner
- member
description: '`owner` or `member`'
required:
- role
Prompt:
type: object
nullable: true
description: |
Reference to a prompt template and its variables.
[Learn more](https://platform.openai.com/docs/guides/text?api-mode=responses#reusable-prompts).
required:
- id
properties:
id:
type: string
description: The unique identifier of the prompt template to use.
version:
type: string
description: Optional version of the prompt template.
nullable: true
variables:
$ref: '#/components/schemas/ResponsePromptVariables'
RealtimeClientEvent:
discriminator:
propertyName: type
description: |
A realtime client event.
anyOf:
- $ref: '#/components/schemas/RealtimeClientEventConversationItemCreate'
- $ref: '#/components/schemas/RealtimeClientEventConversationItemDelete'
- $ref: '#/components/schemas/RealtimeClientEventConversationItemRetrieve'
- $ref: '#/components/schemas/RealtimeClientEventConversationItemTruncate'
- $ref: '#/components/schemas/RealtimeClientEventInputAudioBufferAppend'
- $ref: '#/components/schemas/RealtimeClientEventInputAudioBufferClear'
- $ref: '#/components/schemas/RealtimeClientEventOutputAudioBufferClear'
- $ref: '#/components/schemas/RealtimeClientEventInputAudioBufferCommit'
- $ref: '#/components/schemas/RealtimeClientEventResponseCancel'
- $ref: '#/components/schemas/RealtimeClientEventResponseCreate'
- $ref: '#/components/schemas/RealtimeClientEventSessionUpdate'
- $ref: '#/components/schemas/RealtimeClientEventTranscriptionSessionUpdate'
RealtimeClientEventConversationItemCreate:
type: object
description: |
Add a new Item to the Conversation's context, including messages, function
calls, and function call responses. This event can be used both to populate a
"history" of the conversation and to add new items mid-stream, but has the
current limitation that it cannot populate assistant audio messages.
If successful, the server will respond with a `conversation.item.created`
event, otherwise an `error` event will be sent.
properties:
event_id:
type: string
description: Optional client-generated ID used to identify this event.
type:
description: The event type, must be `conversation.item.create`.
x-stainless-const: true
const: conversation.item.create
previous_item_id:
type: string
description: |
The ID of the preceding item after which the new item will be inserted.
If not set, the new item will be appended to the end of the conversation.
If set to `root`, the new item will be added to the beginning of the conversation.
If set to an existing ID, it allows an item to be inserted mid-conversation. If the
ID cannot be found, an error will be returned and the item will not be added.
item:
$ref: '#/components/schemas/RealtimeConversationItem'
required:
- type
- item
x-oaiMeta:
name: conversation.item.create
group: realtime
example: |
{
"event_id": "event_345",
"type": "conversation.item.create",
"previous_item_id": null,
"item": {
"id": "msg_001",
"type": "message",
"role": "user",
"content": [
{
"type": "input_text",
"text": "Hello, how are you?"
}
]
}
}
RealtimeClientEventConversationItemDelete:
type: object
description: |
Send this event when you want to remove any item from the conversation
history. The server will respond with a `conversation.item.deleted` event,
unless the item does not exist in the conversation history, in which case the
server will respond with an error.
properties:
event_id:
type: string
description: Optional client-generated ID used to identify this event.
type:
description: The event type, must be `conversation.item.delete`.
x-stainless-const: true
const: conversation.item.delete
item_id:
type: string
description: The ID of the item to delete.
required:
- type
- item_id
x-oaiMeta:
name: conversation.item.delete
group: realtime
example: |
{
"event_id": "event_901",
"type": "conversation.item.delete",
"item_id": "msg_003"
}
RealtimeClientEventConversationItemRetrieve:
type: object
description: >
Send this event when you want to retrieve the server's representation of a specific item in the
conversation history. This is useful, for example, to inspect user audio after noise cancellation and
VAD.
The server will respond with a `conversation.item.retrieved` event,
unless the item does not exist in the conversation history, in which case the
server will respond with an error.
properties:
event_id:
type: string
description: Optional client-generated ID used to identify this event.
type:
description: The event type, must be `conversation.item.retrieve`.
x-stainless-const: true
const: conversation.item.retrieve
item_id:
type: string
description: The ID of the item to retrieve.
required:
- type
- item_id
x-oaiMeta:
name: conversation.item.retrieve
group: realtime
example: |
{
"event_id": "event_901",
"type": "conversation.item.retrieve",
"item_id": "msg_003"
}
RealtimeClientEventConversationItemTruncate:
type: object
description: |
Send this event to truncate a previous assistant message’s audio. The server
will produce audio faster than realtime, so this event is useful when the user
interrupts to truncate audio that has already been sent to the client but not
yet played. This will synchronize the server's understanding of the audio with
the client's playback.
Truncating audio will delete the server-side text transcript to ensure there
is not text in the context that hasn't been heard by the user.
If successful, the server will respond with a `conversation.item.truncated`
event.
properties:
event_id:
type: string
description: Optional client-generated ID used to identify this event.
type:
description: The event type, must be `conversation.item.truncate`.
x-stainless-const: true
const: conversation.item.truncate
item_id:
type: string
description: |
The ID of the assistant message item to truncate. Only assistant message
items can be truncated.
content_index:
type: integer
description: The index of the content part to truncate. Set this to 0.
audio_end_ms:
type: integer
description: |
Inclusive duration up to which audio is truncated, in milliseconds. If
the audio_end_ms is greater than the actual audio duration, the server
will respond with an error.
required:
- type
- item_id
- content_index
- audio_end_ms
x-oaiMeta:
name: conversation.item.truncate
group: realtime
example: |
{
"event_id": "event_678",
"type": "conversation.item.truncate",
"item_id": "msg_002",
"content_index": 0,
"audio_end_ms": 1500
}
RealtimeClientEventInputAudioBufferAppend:
type: object
description: |
Send this event to append audio bytes to the input audio buffer. The audio
buffer is temporary storage you can write to and later commit. In Server VAD
mode, the audio buffer is used to detect speech and the server will decide
when to commit. When Server VAD is disabled, you must commit the audio buffer
manually.
The client may choose how much audio to place in each event up to a maximum
of 15 MiB, for example streaming smaller chunks from the client may allow the
VAD to be more responsive. Unlike made other client events, the server will
not send a confirmation response to this event.
properties:
event_id:
type: string
description: Optional client-generated ID used to identify this event.
type:
description: The event type, must be `input_audio_buffer.append`.
x-stainless-const: true
const: input_audio_buffer.append
audio:
type: string
description: |
Base64-encoded audio bytes. This must be in the format specified by the
`input_audio_format` field in the session configuration.
required:
- type
- audio
x-oaiMeta:
name: input_audio_buffer.append
group: realtime
example: |
{
"event_id": "event_456",
"type": "input_audio_buffer.append",
"audio": "Base64EncodedAudioData"
}
RealtimeClientEventInputAudioBufferClear:
type: object
description: |
Send this event to clear the audio bytes in the buffer. The server will
respond with an `input_audio_buffer.cleared` event.
properties:
event_id:
type: string
description: Optional client-generated ID used to identify this event.
type:
description: The event type, must be `input_audio_buffer.clear`.
x-stainless-const: true
const: input_audio_buffer.clear
required:
- type
x-oaiMeta:
name: input_audio_buffer.clear
group: realtime
example: |
{
"event_id": "event_012",
"type": "input_audio_buffer.clear"
}
RealtimeClientEventInputAudioBufferCommit:
type: object
description: |
Send this event to commit the user input audio buffer, which will create a
new user message item in the conversation. This event will produce an error
if the input audio buffer is empty. When in Server VAD mode, the client does
not need to send this event, the server will commit the audio buffer
automatically.
Committing the input audio buffer will trigger input audio transcription
(if enabled in session configuration), but it will not create a response
from the model. The server will respond with an `input_audio_buffer.committed`
event.
properties:
event_id:
type: string
description: Optional client-generated ID used to identify this event.
type:
description: The event type, must be `input_audio_buffer.commit`.
x-stainless-const: true
const: input_audio_buffer.commit
required:
- type
x-oaiMeta:
name: input_audio_buffer.commit
group: realtime
example: |
{
"event_id": "event_789",
"type": "input_audio_buffer.commit"
}
RealtimeClientEventOutputAudioBufferClear:
type: object
description: >
**WebRTC Only:** Emit to cut off the current audio response. This will trigger the server to
stop generating audio and emit a `output_audio_buffer.cleared` event. This
event should be preceded by a `response.cancel` client event to stop the
generation of the current response.
[Learn
more](https://platform.openai.com/docs/guides/realtime-conversations#client-and-server-events-for-audio-in-webrtc).
properties:
event_id:
type: string
description: The unique ID of the client event used for error handling.
type:
description: The event type, must be `output_audio_buffer.clear`.
x-stainless-const: true
const: output_audio_buffer.clear
required:
- type
x-oaiMeta:
name: output_audio_buffer.clear
group: realtime
example: |
{
"event_id": "optional_client_event_id",
"type": "output_audio_buffer.clear"
}
RealtimeClientEventResponseCancel:
type: object
description: |
Send this event to cancel an in-progress response. The server will respond
with a `response.done` event with a status of `response.status=cancelled`. If
there is no response to cancel, the server will respond with an error.
properties:
event_id:
type: string
description: Optional client-generated ID used to identify this event.
type:
description: The event type, must be `response.cancel`.
x-stainless-const: true
const: response.cancel
response_id:
type: string
description: |
A specific response ID to cancel - if not provided, will cancel an
in-progress response in the default conversation.
required:
- type
x-oaiMeta:
name: response.cancel
group: realtime
example: |
{
"event_id": "event_567",
"type": "response.cancel"
}
RealtimeClientEventResponseCreate:
type: object
description: |
This event instructs the server to create a Response, which means triggering
model inference. When in Server VAD mode, the server will create Responses
automatically.
A Response will include at least one Item, and may have two, in which case
the second will be a function call. These Items will be appended to the
conversation history.
The server will respond with a `response.created` event, events for Items
and content created, and finally a `response.done` event to indicate the
Response is complete.
The `response.create` event includes inference configuration like
`instructions`, and `temperature`. These fields will override the Session's
configuration for this Response only.
properties:
event_id:
type: string
description: Optional client-generated ID used to identify this event.
type:
description: The event type, must be `response.create`.
x-stainless-const: true
const: response.create
response:
$ref: '#/components/schemas/RealtimeResponseCreateParams'
required:
- type
x-oaiMeta:
name: response.create
group: realtime
example: |
{
"event_id": "event_234",
"type": "response.create",
"response": {
"modalities": ["text", "audio"],
"instructions": "Please assist the user.",
"voice": "sage",
"output_audio_format": "pcm16",
"tools": [
{
"type": "function",
"name": "calculate_sum",
"description": "Calculates the sum of two numbers.",
"parameters": {
"type": "object",
"properties": {
"a": { "type": "number" },
"b": { "type": "number" }
},
"required": ["a", "b"]
}
}
],
"tool_choice": "auto",
"temperature": 0.8,
"max_output_tokens": 1024
}
}
RealtimeClientEventSessionUpdate:
type: object
description: |
Send this event to update the session’s default configuration.
The client may send this event at any time to update any field,
except for `voice`. However, note that once a session has been
initialized with a particular `model`, it can’t be changed to
another model using `session.update`.
When the server receives a `session.update`, it will respond
with a `session.updated` event showing the full, effective configuration.
Only the fields that are present are updated. To clear a field like
`instructions`, pass an empty string.
properties:
event_id:
type: string
description: Optional client-generated ID used to identify this event.
type:
description: The event type, must be `session.update`.
x-stainless-const: true
const: session.update
session:
$ref: '#/components/schemas/RealtimeSessionCreateRequest'
required:
- type
- session
x-oaiMeta:
name: session.update
group: realtime
example: |
{
"event_id": "event_123",
"type": "session.update",
"session": {
"modalities": ["text", "audio"],
"instructions": "You are a helpful assistant.",
"voice": "sage",
"input_audio_format": "pcm16",
"output_audio_format": "pcm16",
"input_audio_transcription": {
"model": "whisper-1"
},
"turn_detection": {
"type": "server_vad",
"threshold": 0.5,
"prefix_padding_ms": 300,
"silence_duration_ms": 500,
"create_response": true
},
"tools": [
{
"type": "function",
"name": "get_weather",
"description": "Get the current weather...",
"parameters": {
"type": "object",
"properties": {
"location": { "type": "string" }
},
"required": ["location"]
}
}
],
"tool_choice": "auto",
"temperature": 0.8,
"max_response_output_tokens": "inf",
"speed": 1.1,
"tracing": "auto"
}
}
RealtimeClientEventTranscriptionSessionUpdate:
type: object
description: |
Send this event to update a transcription session.
properties:
event_id:
type: string
description: Optional client-generated ID used to identify this event.
type:
description: The event type, must be `transcription_session.update`.
x-stainless-const: true
const: transcription_session.update
session:
$ref: '#/components/schemas/RealtimeTranscriptionSessionCreateRequest'
required:
- type
- session
x-oaiMeta:
name: transcription_session.update
group: realtime
example: |
{
"type": "transcription_session.update",
"session": {
"input_audio_format": "pcm16",
"input_audio_transcription": {
"model": "gpt-4o-transcribe",
"prompt": "",
"language": ""
},
"turn_detection": {
"type": "server_vad",
"threshold": 0.5,
"prefix_padding_ms": 300,
"silence_duration_ms": 500,
"create_response": true,
},
"input_audio_noise_reduction": {
"type": "near_field"
},
"include": [
"item.input_audio_transcription.logprobs",
]
}
}
RealtimeConversationItem:
type: object
description: The item to add to the conversation.
properties:
id:
type: string
description: |
The unique ID of the item, this can be generated by the client to help
manage server-side context, but is not required because the server will
generate one if not provided.
type:
type: string
enum:
- message
- function_call
- function_call_output
description: |
The type of the item (`message`, `function_call`, `function_call_output`).
object:
type: string
enum:
- realtime.item
description: |
Identifier for the API object being returned - always `realtime.item`.
x-stainless-const: true
status:
type: string
enum:
- completed
- incomplete
- in_progress
description: |
The status of the item (`completed`, `incomplete`, `in_progress`). These have no effect
on the conversation, but are accepted for consistency with the
`conversation.item.created` event.
role:
type: string
enum:
- user
- assistant
- system
description: |
The role of the message sender (`user`, `assistant`, `system`), only
applicable for `message` items.
content:
type: array
description: |
The content of the message, applicable for `message` items.
- Message items of role `system` support only `input_text` content
- Message items of role `user` support `input_text` and `input_audio`
content
- Message items of role `assistant` support `text` content.
items:
$ref: '#/components/schemas/RealtimeConversationItemContent'
call_id:
type: string
description: |
The ID of the function call (for `function_call` and
`function_call_output` items). If passed on a `function_call_output`
item, the server will check that a `function_call` item with the same
ID exists in the conversation history.
name:
type: string
description: |
The name of the function being called (for `function_call` items).
arguments:
type: string
description: |
The arguments of the function call (for `function_call` items).
output:
type: string
description: |
The output of the function call (for `function_call_output` items).
RealtimeConversationItemWithReference:
type: object
description: The item to add to the conversation.
properties:
id:
type: string
description: |
For an item of type (`message` | `function_call` | `function_call_output`)
this field allows the client to assign the unique ID of the item. It is
not required because the server will generate one if not provided.
For an item of type `item_reference`, this field is required and is a
reference to any item that has previously existed in the conversation.
type:
type: string
enum:
- message
- function_call
- function_call_output
- item_reference
description: |
The type of the item (`message`, `function_call`, `function_call_output`, `item_reference`).
object:
type: string
enum:
- realtime.item
description: |
Identifier for the API object being returned - always `realtime.item`.
x-stainless-const: true
status:
type: string
enum:
- completed
- incomplete
- in_progress
description: |
The status of the item (`completed`, `incomplete`, `in_progress`). These have no effect
on the conversation, but are accepted for consistency with the
`conversation.item.created` event.
role:
type: string
enum:
- user
- assistant
- system
description: |
The role of the message sender (`user`, `assistant`, `system`), only
applicable for `message` items.
content:
type: array
description: |
The content of the message, applicable for `message` items.
- Message items of role `system` support only `input_text` content
- Message items of role `user` support `input_text` and `input_audio`
content
- Message items of role `assistant` support `text` content.
items:
type: object
properties:
type:
type: string
enum:
- input_text
- input_audio
- item_reference
- text
description: |
The content type (`input_text`, `input_audio`, `item_reference`, `text`).
text:
type: string
description: |
The text content, used for `input_text` and `text` content types.
id:
type: string
description: |
ID of a previous conversation item to reference (for `item_reference`
content types in `response.create` events). These can reference both
client and server created items.
audio:
type: string
description: |
Base64-encoded audio bytes, used for `input_audio` content type.
transcript:
type: string
description: |
The transcript of the audio, used for `input_audio` content type.
call_id:
type: string
description: |
The ID of the function call (for `function_call` and
`function_call_output` items). If passed on a `function_call_output`
item, the server will check that a `function_call` item with the same
ID exists in the conversation history.
name:
type: string
description: |
The name of the function being called (for `function_call` items).
arguments:
type: string
description: |
The arguments of the function call (for `function_call` items).
output:
type: string
description: |
The output of the function call (for `function_call_output` items).
RealtimeResponse:
type: object
description: The response resource.
properties:
id:
type: string
description: The unique ID of the response.
object:
description: The object type, must be `realtime.response`.
x-stainless-const: true
const: realtime.response
status:
type: string
enum:
- completed
- cancelled
- failed
- incomplete
- in_progress
description: |
The final status of the response (`completed`, `cancelled`, `failed`, or
`incomplete`, `in_progress`).
status_details:
type: object
description: Additional details about the status.
properties:
type:
type: string
enum:
- completed
- cancelled
- incomplete
- failed
description: |
The type of error that caused the response to fail, corresponding
with the `status` field (`completed`, `cancelled`, `incomplete`,
`failed`).
reason:
type: string
enum:
- turn_detected
- client_cancelled
- max_output_tokens
- content_filter
description: |
The reason the Response did not complete. For a `cancelled` Response,
one of `turn_detected` (the server VAD detected a new start of speech)
or `client_cancelled` (the client sent a cancel event). For an
`incomplete` Response, one of `max_output_tokens` or `content_filter`
(the server-side safety filter activated and cut off the response).
error:
type: object
description: |
A description of the error that caused the response to fail,
populated when the `status` is `failed`.
properties:
type:
type: string
description: The type of error.
code:
type: string
description: Error code, if any.
output:
type: array
description: The list of output items generated by the response.
items:
$ref: '#/components/schemas/RealtimeConversationItem'
metadata:
$ref: '#/components/schemas/Metadata'
usage:
type: object
description: |
Usage statistics for the Response, this will correspond to billing. A
Realtime API session will maintain a conversation context and append new
Items to the Conversation, thus output from previous turns (text and
audio tokens) will become the input for later turns.
properties:
total_tokens:
type: integer
description: |
The total number of tokens in the Response including input and output
text and audio tokens.
input_tokens:
type: integer
description: |
The number of input tokens used in the Response, including text and
audio tokens.
output_tokens:
type: integer
description: |
The number of output tokens sent in the Response, including text and
audio tokens.
input_token_details:
type: object
description: Details about the input tokens used in the Response.
properties:
cached_tokens:
type: integer
description: The number of cached tokens used in the Response.
text_tokens:
type: integer
description: The number of text tokens used in the Response.
audio_tokens:
type: integer
description: The number of audio tokens used in the Response.
output_token_details:
type: object
description: Details about the output tokens used in the Response.
properties:
text_tokens:
type: integer
description: The number of text tokens used in the Response.
audio_tokens:
type: integer
description: The number of audio tokens used in the Response.
conversation_id:
description: |
Which conversation the response is added to, determined by the `conversation`
field in the `response.create` event. If `auto`, the response will be added to
the default conversation and the value of `conversation_id` will be an id like
`conv_1234`. If `none`, the response will not be added to any conversation and
the value of `conversation_id` will be `null`. If responses are being triggered
by server VAD, the response will be added to the default conversation, thus
the `conversation_id` will be an id like `conv_1234`.
type: string
voice:
$ref: '#/components/schemas/VoiceIdsShared'
description: |
The voice the model used to respond.
Current voice options are `alloy`, `ash`, `ballad`, `coral`, `echo`, `sage`,
`shimmer`, and `verse`.
modalities:
type: array
description: |
The set of modalities the model used to respond. If there are multiple modalities,
the model will pick one, for example if `modalities` is `["text", "audio"]`, the model
could be responding in either text or audio.
items:
type: string
enum:
- text
- audio
output_audio_format:
type: string
enum:
- pcm16
- g711_ulaw
- g711_alaw
description: |
The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
temperature:
type: number
description: |
Sampling temperature for the model, limited to [0.6, 1.2]. Defaults to 0.8.
max_output_tokens:
description: |
Maximum number of output tokens for a single assistant response,
inclusive of tool calls, that was used in this response.
anyOf:
- type: integer
- type: string
enum:
- inf
x-stainless-const: true
RealtimeResponseCreateParams:
type: object
description: Create a new Realtime response with these parameters
properties:
modalities:
type: array
description: |
The set of modalities the model can respond with. To disable audio,
set this to ["text"].
items:
type: string
enum:
- text
- audio
instructions:
type: string
description: |
The default system instructions (i.e. system message) prepended to model
calls. This field allows the client to guide the model on desired
responses. The model can be instructed on response content and format,
(e.g. "be extremely succinct", "act friendly", "here are examples of good
responses") and on audio behavior (e.g. "talk quickly", "inject emotion
into your voice", "laugh frequently"). The instructions are not guaranteed
to be followed by the model, but they provide guidance to the model on the
desired behavior.
Note that the server sets default instructions which will be used if this
field is not set and are visible in the `session.created` event at the
start of the session.
voice:
$ref: '#/components/schemas/VoiceIdsShared'
description: |
The voice the model uses to respond. Voice cannot be changed during the
session once the model has responded with audio at least once. Current
voice options are `alloy`, `ash`, `ballad`, `coral`, `echo`, `sage`,
`shimmer`, and `verse`.
output_audio_format:
type: string
enum:
- pcm16
- g711_ulaw
- g711_alaw
description: |
The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
tools:
type: array
description: Tools (functions) available to the model.
items:
type: object
properties:
type:
type: string
enum:
- function
description: The type of the tool, i.e. `function`.
x-stainless-const: true
name:
type: string
description: The name of the function.
description:
type: string
description: |
The description of the function, including guidance on when and how
to call it, and guidance about what to tell the user when calling
(if anything).
parameters:
type: object
description: Parameters of the function in JSON Schema.
tool_choice:
type: string
description: |
How the model chooses tools. Options are `auto`, `none`, `required`, or
specify a function, like `{"type": "function", "function": {"name": "my_function"}}`.
temperature:
type: number
description: |
Sampling temperature for the model, limited to [0.6, 1.2]. Defaults to 0.8.
max_response_output_tokens:
description: |
Maximum number of output tokens for a single assistant response,
inclusive of tool calls. Provide an integer between 1 and 4096 to
limit output tokens, or `inf` for the maximum available tokens for a
given model. Defaults to `inf`.
anyOf:
- type: integer
- type: string
enum:
- inf
x-stainless-const: true
conversation:
description: |
Controls which conversation the response is added to. Currently supports
`auto` and `none`, with `auto` as the default value. The `auto` value
means that the contents of the response will be added to the default
conversation. Set this to `none` to create an out-of-band response which
will not add items to default conversation.
anyOf:
- type: string
- type: string
default: auto
enum:
- auto
- none
metadata:
$ref: '#/components/schemas/Metadata'
input:
type: array
description: |
Input items to include in the prompt for the model. Using this field
creates a new context for this Response instead of using the default
conversation. An empty array `[]` will clear the context for this Response.
Note that this can include references to items from the default conversation.
items:
$ref: '#/components/schemas/RealtimeConversationItemWithReference'
RealtimeServerEvent:
discriminator:
propertyName: type
description: |
A realtime server event.
anyOf:
- $ref: '#/components/schemas/RealtimeServerEventConversationCreated'
- $ref: '#/components/schemas/RealtimeServerEventConversationItemCreated'
- $ref: '#/components/schemas/RealtimeServerEventConversationItemDeleted'
- $ref: '#/components/schemas/RealtimeServerEventConversationItemInputAudioTranscriptionCompleted'
- $ref: '#/components/schemas/RealtimeServerEventConversationItemInputAudioTranscriptionDelta'
- $ref: '#/components/schemas/RealtimeServerEventConversationItemInputAudioTranscriptionFailed'
- $ref: '#/components/schemas/RealtimeServerEventConversationItemRetrieved'
- $ref: '#/components/schemas/RealtimeServerEventConversationItemTruncated'
- $ref: '#/components/schemas/RealtimeServerEventError'
- $ref: '#/components/schemas/RealtimeServerEventInputAudioBufferCleared'
- $ref: '#/components/schemas/RealtimeServerEventInputAudioBufferCommitted'
- $ref: '#/components/schemas/RealtimeServerEventInputAudioBufferSpeechStarted'
- $ref: '#/components/schemas/RealtimeServerEventInputAudioBufferSpeechStopped'
- $ref: '#/components/schemas/RealtimeServerEventRateLimitsUpdated'
- $ref: '#/components/schemas/RealtimeServerEventResponseAudioDelta'
- $ref: '#/components/schemas/RealtimeServerEventResponseAudioDone'
- $ref: '#/components/schemas/RealtimeServerEventResponseAudioTranscriptDelta'
- $ref: '#/components/schemas/RealtimeServerEventResponseAudioTranscriptDone'
- $ref: '#/components/schemas/RealtimeServerEventResponseContentPartAdded'
- $ref: '#/components/schemas/RealtimeServerEventResponseContentPartDone'
- $ref: '#/components/schemas/RealtimeServerEventResponseCreated'
- $ref: '#/components/schemas/RealtimeServerEventResponseDone'
- $ref: '#/components/schemas/RealtimeServerEventResponseFunctionCallArgumentsDelta'
- $ref: '#/components/schemas/RealtimeServerEventResponseFunctionCallArgumentsDone'
- $ref: '#/components/schemas/RealtimeServerEventResponseOutputItemAdded'
- $ref: '#/components/schemas/RealtimeServerEventResponseOutputItemDone'
- $ref: '#/components/schemas/RealtimeServerEventResponseTextDelta'
- $ref: '#/components/schemas/RealtimeServerEventResponseTextDone'
- $ref: '#/components/schemas/RealtimeServerEventSessionCreated'
- $ref: '#/components/schemas/RealtimeServerEventSessionUpdated'
- $ref: '#/components/schemas/RealtimeServerEventTranscriptionSessionUpdated'
- $ref: '#/components/schemas/RealtimeServerEventOutputAudioBufferStarted'
- $ref: '#/components/schemas/RealtimeServerEventOutputAudioBufferStopped'
- $ref: '#/components/schemas/RealtimeServerEventOutputAudioBufferCleared'
RealtimeServerEventConversationCreated:
type: object
description: |
Returned when a conversation is created. Emitted right after session creation.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `conversation.created`.
x-stainless-const: true
const: conversation.created
conversation:
type: object
description: The conversation resource.
properties:
id:
type: string
description: The unique ID of the conversation.
object:
description: The object type, must be `realtime.conversation`.
const: realtime.conversation
required:
- event_id
- type
- conversation
x-oaiMeta:
name: conversation.created
group: realtime
example: |
{
"event_id": "event_9101",
"type": "conversation.created",
"conversation": {
"id": "conv_001",
"object": "realtime.conversation"
}
}
RealtimeServerEventConversationItemCreated:
type: object
description: |
Returned when a conversation item is created. There are several scenarios that produce this event:
- The server is generating a Response, which if successful will produce
either one or two Items, which will be of type `message`
(role `assistant`) or type `function_call`.
- The input audio buffer has been committed, either by the client or the
server (in `server_vad` mode). The server will take the content of the
input audio buffer and add it to a new user message Item.
- The client has sent a `conversation.item.create` event to add a new Item
to the Conversation.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `conversation.item.created`.
x-stainless-const: true
const: conversation.item.created
previous_item_id:
type: string
nullable: true
description: |
The ID of the preceding item in the Conversation context, allows the
client to understand the order of the conversation. Can be `null` if the
item has no predecessor.
item:
$ref: '#/components/schemas/RealtimeConversationItem'
required:
- event_id
- type
- item
x-oaiMeta:
name: conversation.item.created
group: realtime
example: |
{
"event_id": "event_1920",
"type": "conversation.item.created",
"previous_item_id": "msg_002",
"item": {
"id": "msg_003",
"object": "realtime.item",
"type": "message",
"status": "completed",
"role": "user",
"content": []
}
}
RealtimeServerEventConversationItemDeleted:
type: object
description: |
Returned when an item in the conversation is deleted by the client with a
`conversation.item.delete` event. This event is used to synchronize the
server's understanding of the conversation history with the client's view.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `conversation.item.deleted`.
x-stainless-const: true
const: conversation.item.deleted
item_id:
type: string
description: The ID of the item that was deleted.
required:
- event_id
- type
- item_id
x-oaiMeta:
name: conversation.item.deleted
group: realtime
example: |
{
"event_id": "event_2728",
"type": "conversation.item.deleted",
"item_id": "msg_005"
}
RealtimeServerEventConversationItemInputAudioTranscriptionCompleted:
type: object
description: |
This event is the output of audio transcription for user audio written to the
user audio buffer. Transcription begins when the input audio buffer is
committed by the client or server (in `server_vad` mode). Transcription runs
asynchronously with Response creation, so this event may come before or after
the Response events.
Realtime API models accept audio natively, and thus input transcription is a
separate process run on a separate ASR (Automatic Speech Recognition) model.
The transcript may diverge somewhat from the model's interpretation, and
should be treated as a rough guide.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
type: string
enum:
- conversation.item.input_audio_transcription.completed
description: |
The event type, must be
`conversation.item.input_audio_transcription.completed`.
x-stainless-const: true
item_id:
type: string
description: The ID of the user message item containing the audio.
content_index:
type: integer
description: The index of the content part containing the audio.
transcript:
type: string
description: The transcribed text.
logprobs:
type: array
description: The log probabilities of the transcription.
nullable: true
items:
$ref: '#/components/schemas/LogProbProperties'
usage:
type: object
description: Usage statistics for the transcription.
anyOf:
- $ref: '#/components/schemas/TranscriptTextUsageTokens'
title: Token Usage
- $ref: '#/components/schemas/TranscriptTextUsageDuration'
title: Duration Usage
required:
- event_id
- type
- item_id
- content_index
- transcript
- usage
x-oaiMeta:
name: conversation.item.input_audio_transcription.completed
group: realtime
example: |
{
"event_id": "event_2122",
"type": "conversation.item.input_audio_transcription.completed",
"item_id": "msg_003",
"content_index": 0,
"transcript": "Hello, how are you?",
"usage": {
"type": "tokens",
"total_tokens": 48,
"input_tokens": 38,
"input_token_details": {
"text_tokens": 10,
"audio_tokens": 28,
},
"output_tokens": 10,
}
}
RealtimeServerEventConversationItemInputAudioTranscriptionDelta:
type: object
description: |
Returned when the text value of an input audio transcription content part is updated.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `conversation.item.input_audio_transcription.delta`.
x-stainless-const: true
const: conversation.item.input_audio_transcription.delta
item_id:
type: string
description: The ID of the item.
content_index:
type: integer
description: The index of the content part in the item's content array.
delta:
type: string
description: The text delta.
logprobs:
type: array
description: The log probabilities of the transcription.
nullable: true
items:
$ref: '#/components/schemas/LogProbProperties'
required:
- event_id
- type
- item_id
x-oaiMeta:
name: conversation.item.input_audio_transcription.delta
group: realtime
example: |
{
"type": "conversation.item.input_audio_transcription.delta",
"event_id": "event_001",
"item_id": "item_001",
"content_index": 0,
"delta": "Hello"
}
RealtimeServerEventConversationItemInputAudioTranscriptionFailed:
type: object
description: |
Returned when input audio transcription is configured, and a transcription
request for a user message failed. These events are separate from other
`error` events so that the client can identify the related Item.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
type: string
enum:
- conversation.item.input_audio_transcription.failed
description: |
The event type, must be
`conversation.item.input_audio_transcription.failed`.
x-stainless-const: true
item_id:
type: string
description: The ID of the user message item.
content_index:
type: integer
description: The index of the content part containing the audio.
error:
type: object
description: Details of the transcription error.
properties:
type:
type: string
description: The type of error.
code:
type: string
description: Error code, if any.
message:
type: string
description: A human-readable error message.
param:
type: string
description: Parameter related to the error, if any.
required:
- event_id
- type
- item_id
- content_index
- error
x-oaiMeta:
name: conversation.item.input_audio_transcription.failed
group: realtime
example: |
{
"event_id": "event_2324",
"type": "conversation.item.input_audio_transcription.failed",
"item_id": "msg_003",
"content_index": 0,
"error": {
"type": "transcription_error",
"code": "audio_unintelligible",
"message": "The audio could not be transcribed.",
"param": null
}
}
RealtimeServerEventConversationItemRetrieved:
type: object
description: |
Returned when a conversation item is retrieved with `conversation.item.retrieve`.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `conversation.item.retrieved`.
x-stainless-const: true
const: conversation.item.retrieved
item:
$ref: '#/components/schemas/RealtimeConversationItem'
required:
- event_id
- type
- item
x-oaiMeta:
name: conversation.item.retrieved
group: realtime
example: |
{
"event_id": "event_1920",
"type": "conversation.item.created",
"previous_item_id": "msg_002",
"item": {
"id": "msg_003",
"object": "realtime.item",
"type": "message",
"status": "completed",
"role": "user",
"content": [
{
"type": "input_audio",
"transcript": "hello how are you",
"audio": "base64encodedaudio=="
}
]
}
}
RealtimeServerEventConversationItemTruncated:
type: object
description: |
Returned when an earlier assistant audio message item is truncated by the
client with a `conversation.item.truncate` event. This event is used to
synchronize the server's understanding of the audio with the client's playback.
This action will truncate the audio and remove the server-side text transcript
to ensure there is no text in the context that hasn't been heard by the user.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `conversation.item.truncated`.
x-stainless-const: true
const: conversation.item.truncated
item_id:
type: string
description: The ID of the assistant message item that was truncated.
content_index:
type: integer
description: The index of the content part that was truncated.
audio_end_ms:
type: integer
description: |
The duration up to which the audio was truncated, in milliseconds.
required:
- event_id
- type
- item_id
- content_index
- audio_end_ms
x-oaiMeta:
name: conversation.item.truncated
group: realtime
example: |
{
"event_id": "event_2526",
"type": "conversation.item.truncated",
"item_id": "msg_004",
"content_index": 0,
"audio_end_ms": 1500
}
RealtimeServerEventError:
type: object
description: |
Returned when an error occurs, which could be a client problem or a server
problem. Most errors are recoverable and the session will stay open, we
recommend to implementors to monitor and log error messages by default.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `error`.
x-stainless-const: true
const: error
error:
type: object
description: Details of the error.
required:
- type
- message
properties:
type:
type: string
description: |
The type of error (e.g., "invalid_request_error", "server_error").
code:
type: string
description: Error code, if any.
nullable: true
message:
type: string
description: A human-readable error message.
param:
type: string
description: Parameter related to the error, if any.
nullable: true
event_id:
type: string
description: |
The event_id of the client event that caused the error, if applicable.
nullable: true
required:
- event_id
- type
- error
x-oaiMeta:
name: error
group: realtime
example: |
{
"event_id": "event_890",
"type": "error",
"error": {
"type": "invalid_request_error",
"code": "invalid_event",
"message": "The 'type' field is missing.",
"param": null,
"event_id": "event_567"
}
}
RealtimeServerEventInputAudioBufferCleared:
type: object
description: |
Returned when the input audio buffer is cleared by the client with a
`input_audio_buffer.clear` event.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `input_audio_buffer.cleared`.
x-stainless-const: true
const: input_audio_buffer.cleared
required:
- event_id
- type
x-oaiMeta:
name: input_audio_buffer.cleared
group: realtime
example: |
{
"event_id": "event_1314",
"type": "input_audio_buffer.cleared"
}
RealtimeServerEventInputAudioBufferCommitted:
type: object
description: |
Returned when an input audio buffer is committed, either by the client or
automatically in server VAD mode. The `item_id` property is the ID of the user
message item that will be created, thus a `conversation.item.created` event
will also be sent to the client.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `input_audio_buffer.committed`.
x-stainless-const: true
const: input_audio_buffer.committed
previous_item_id:
type: string
nullable: true
description: |
The ID of the preceding item after which the new item will be inserted.
Can be `null` if the item has no predecessor.
item_id:
type: string
description: The ID of the user message item that will be created.
required:
- event_id
- type
- item_id
x-oaiMeta:
name: input_audio_buffer.committed
group: realtime
example: |
{
"event_id": "event_1121",
"type": "input_audio_buffer.committed",
"previous_item_id": "msg_001",
"item_id": "msg_002"
}
RealtimeServerEventInputAudioBufferSpeechStarted:
type: object
description: |
Sent by the server when in `server_vad` mode to indicate that speech has been
detected in the audio buffer. This can happen any time audio is added to the
buffer (unless speech is already detected). The client may want to use this
event to interrupt audio playback or provide visual feedback to the user.
The client should expect to receive a `input_audio_buffer.speech_stopped` event
when speech stops. The `item_id` property is the ID of the user message item
that will be created when speech stops and will also be included in the
`input_audio_buffer.speech_stopped` event (unless the client manually commits
the audio buffer during VAD activation).
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `input_audio_buffer.speech_started`.
x-stainless-const: true
const: input_audio_buffer.speech_started
audio_start_ms:
type: integer
description: |
Milliseconds from the start of all audio written to the buffer during the
session when speech was first detected. This will correspond to the
beginning of audio sent to the model, and thus includes the
`prefix_padding_ms` configured in the Session.
item_id:
type: string
description: |
The ID of the user message item that will be created when speech stops.
required:
- event_id
- type
- audio_start_ms
- item_id
x-oaiMeta:
name: input_audio_buffer.speech_started
group: realtime
example: |
{
"event_id": "event_1516",
"type": "input_audio_buffer.speech_started",
"audio_start_ms": 1000,
"item_id": "msg_003"
}
RealtimeServerEventInputAudioBufferSpeechStopped:
type: object
description: |
Returned in `server_vad` mode when the server detects the end of speech in
the audio buffer. The server will also send an `conversation.item.created`
event with the user message item that is created from the audio buffer.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `input_audio_buffer.speech_stopped`.
x-stainless-const: true
const: input_audio_buffer.speech_stopped
audio_end_ms:
type: integer
description: |
Milliseconds since the session started when speech stopped. This will
correspond to the end of audio sent to the model, and thus includes the
`min_silence_duration_ms` configured in the Session.
item_id:
type: string
description: The ID of the user message item that will be created.
required:
- event_id
- type
- audio_end_ms
- item_id
x-oaiMeta:
name: input_audio_buffer.speech_stopped
group: realtime
example: |
{
"event_id": "event_1718",
"type": "input_audio_buffer.speech_stopped",
"audio_end_ms": 2000,
"item_id": "msg_003"
}
RealtimeServerEventOutputAudioBufferCleared:
type: object
description: >
**WebRTC Only:** Emitted when the output audio buffer is cleared. This happens either in VAD
mode when the user has interrupted (`input_audio_buffer.speech_started`),
or when the client has emitted the `output_audio_buffer.clear` event to manually
cut off the current audio response.
[Learn
more](https://platform.openai.com/docs/guides/realtime-conversations#client-and-server-events-for-audio-in-webrtc).
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `output_audio_buffer.cleared`.
x-stainless-const: true
const: output_audio_buffer.cleared
response_id:
type: string
description: The unique ID of the response that produced the audio.
required:
- event_id
- type
- response_id
x-oaiMeta:
name: output_audio_buffer.cleared
group: realtime
example: |
{
"event_id": "event_abc123",
"type": "output_audio_buffer.cleared",
"response_id": "resp_abc123"
}
RealtimeServerEventOutputAudioBufferStarted:
type: object
description: >
**WebRTC Only:** Emitted when the server begins streaming audio to the client. This event is
emitted after an audio content part has been added (`response.content_part.added`)
to the response.
[Learn
more](https://platform.openai.com/docs/guides/realtime-conversations#client-and-server-events-for-audio-in-webrtc).
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `output_audio_buffer.started`.
x-stainless-const: true
const: output_audio_buffer.started
response_id:
type: string
description: The unique ID of the response that produced the audio.
required:
- event_id
- type
- response_id
x-oaiMeta:
name: output_audio_buffer.started
group: realtime
example: |
{
"event_id": "event_abc123",
"type": "output_audio_buffer.started",
"response_id": "resp_abc123"
}
RealtimeServerEventOutputAudioBufferStopped:
type: object
description: >
**WebRTC Only:** Emitted when the output audio buffer has been completely drained on the server,
and no more audio is forthcoming. This event is emitted after the full response
data has been sent to the client (`response.done`).
[Learn
more](https://platform.openai.com/docs/guides/realtime-conversations#client-and-server-events-for-audio-in-webrtc).
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `output_audio_buffer.stopped`.
x-stainless-const: true
const: output_audio_buffer.stopped
response_id:
type: string
description: The unique ID of the response that produced the audio.
required:
- event_id
- type
- response_id
x-oaiMeta:
name: output_audio_buffer.stopped
group: realtime
example: |
{
"event_id": "event_abc123",
"type": "output_audio_buffer.stopped",
"response_id": "resp_abc123"
}
RealtimeServerEventRateLimitsUpdated:
type: object
description: |
Emitted at the beginning of a Response to indicate the updated rate limits.
When a Response is created some tokens will be "reserved" for the output
tokens, the rate limits shown here reflect that reservation, which is then
adjusted accordingly once the Response is completed.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `rate_limits.updated`.
x-stainless-const: true
const: rate_limits.updated
rate_limits:
type: array
description: List of rate limit information.
items:
type: object
properties:
name:
type: string
enum:
- requests
- tokens
description: |
The name of the rate limit (`requests`, `tokens`).
limit:
type: integer
description: The maximum allowed value for the rate limit.
remaining:
type: integer
description: The remaining value before the limit is reached.
reset_seconds:
type: number
description: Seconds until the rate limit resets.
required:
- event_id
- type
- rate_limits
x-oaiMeta:
name: rate_limits.updated
group: realtime
example: |
{
"event_id": "event_5758",
"type": "rate_limits.updated",
"rate_limits": [
{
"name": "requests",
"limit": 1000,
"remaining": 999,
"reset_seconds": 60
},
{
"name": "tokens",
"limit": 50000,
"remaining": 49950,
"reset_seconds": 60
}
]
}
RealtimeServerEventResponseAudioDelta:
type: object
description: Returned when the model-generated audio is updated.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `response.audio.delta`.
x-stainless-const: true
const: response.audio.delta
response_id:
type: string
description: The ID of the response.
item_id:
type: string
description: The ID of the item.
output_index:
type: integer
description: The index of the output item in the response.
content_index:
type: integer
description: The index of the content part in the item's content array.
delta:
type: string
description: Base64-encoded audio data delta.
required:
- event_id
- type
- response_id
- item_id
- output_index
- content_index
- delta
x-oaiMeta:
name: response.audio.delta
group: realtime
example: |
{
"event_id": "event_4950",
"type": "response.audio.delta",
"response_id": "resp_001",
"item_id": "msg_008",
"output_index": 0,
"content_index": 0,
"delta": "Base64EncodedAudioDelta"
}
RealtimeServerEventResponseAudioDone:
type: object
description: |
Returned when the model-generated audio is done. Also emitted when a Response
is interrupted, incomplete, or cancelled.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `response.audio.done`.
x-stainless-const: true
const: response.audio.done
response_id:
type: string
description: The ID of the response.
item_id:
type: string
description: The ID of the item.
output_index:
type: integer
description: The index of the output item in the response.
content_index:
type: integer
description: The index of the content part in the item's content array.
required:
- event_id
- type
- response_id
- item_id
- output_index
- content_index
x-oaiMeta:
name: response.audio.done
group: realtime
example: |
{
"event_id": "event_5152",
"type": "response.audio.done",
"response_id": "resp_001",
"item_id": "msg_008",
"output_index": 0,
"content_index": 0
}
RealtimeServerEventResponseAudioTranscriptDelta:
type: object
description: |
Returned when the model-generated transcription of audio output is updated.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `response.audio_transcript.delta`.
x-stainless-const: true
const: response.audio_transcript.delta
response_id:
type: string
description: The ID of the response.
item_id:
type: string
description: The ID of the item.
output_index:
type: integer
description: The index of the output item in the response.
content_index:
type: integer
description: The index of the content part in the item's content array.
delta:
type: string
description: The transcript delta.
required:
- event_id
- type
- response_id
- item_id
- output_index
- content_index
- delta
x-oaiMeta:
name: response.audio_transcript.delta
group: realtime
example: |
{
"event_id": "event_4546",
"type": "response.audio_transcript.delta",
"response_id": "resp_001",
"item_id": "msg_008",
"output_index": 0,
"content_index": 0,
"delta": "Hello, how can I a"
}
RealtimeServerEventResponseAudioTranscriptDone:
type: object
description: |
Returned when the model-generated transcription of audio output is done
streaming. Also emitted when a Response is interrupted, incomplete, or
cancelled.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `response.audio_transcript.done`.
x-stainless-const: true
const: response.audio_transcript.done
response_id:
type: string
description: The ID of the response.
item_id:
type: string
description: The ID of the item.
output_index:
type: integer
description: The index of the output item in the response.
content_index:
type: integer
description: The index of the content part in the item's content array.
transcript:
type: string
description: The final transcript of the audio.
required:
- event_id
- type
- response_id
- item_id
- output_index
- content_index
- transcript
x-oaiMeta:
name: response.audio_transcript.done
group: realtime
example: |
{
"event_id": "event_4748",
"type": "response.audio_transcript.done",
"response_id": "resp_001",
"item_id": "msg_008",
"output_index": 0,
"content_index": 0,
"transcript": "Hello, how can I assist you today?"
}
RealtimeServerEventResponseContentPartAdded:
type: object
description: |
Returned when a new content part is added to an assistant message item during
response generation.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `response.content_part.added`.
x-stainless-const: true
const: response.content_part.added
response_id:
type: string
description: The ID of the response.
item_id:
type: string
description: The ID of the item to which the content part was added.
output_index:
type: integer
description: The index of the output item in the response.
content_index:
type: integer
description: The index of the content part in the item's content array.
part:
type: object
description: The content part that was added.
properties:
type:
type: string
enum:
- text
- audio
description: The content type ("text", "audio").
text:
type: string
description: The text content (if type is "text").
audio:
type: string
description: Base64-encoded audio data (if type is "audio").
transcript:
type: string
description: The transcript of the audio (if type is "audio").
required:
- event_id
- type
- response_id
- item_id
- output_index
- content_index
- part
x-oaiMeta:
name: response.content_part.added
group: realtime
example: |
{
"event_id": "event_3738",
"type": "response.content_part.added",
"response_id": "resp_001",
"item_id": "msg_007",
"output_index": 0,
"content_index": 0,
"part": {
"type": "text",
"text": ""
}
}
RealtimeServerEventResponseContentPartDone:
type: object
description: |
Returned when a content part is done streaming in an assistant message item.
Also emitted when a Response is interrupted, incomplete, or cancelled.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `response.content_part.done`.
x-stainless-const: true
const: response.content_part.done
response_id:
type: string
description: The ID of the response.
item_id:
type: string
description: The ID of the item.
output_index:
type: integer
description: The index of the output item in the response.
content_index:
type: integer
description: The index of the content part in the item's content array.
part:
type: object
description: The content part that is done.
properties:
type:
type: string
enum:
- text
- audio
description: The content type ("text", "audio").
text:
type: string
description: The text content (if type is "text").
audio:
type: string
description: Base64-encoded audio data (if type is "audio").
transcript:
type: string
description: The transcript of the audio (if type is "audio").
required:
- event_id
- type
- response_id
- item_id
- output_index
- content_index
- part
x-oaiMeta:
name: response.content_part.done
group: realtime
example: |
{
"event_id": "event_3940",
"type": "response.content_part.done",
"response_id": "resp_001",
"item_id": "msg_007",
"output_index": 0,
"content_index": 0,
"part": {
"type": "text",
"text": "Sure, I can help with that."
}
}
RealtimeServerEventResponseCreated:
type: object
description: |
Returned when a new Response is created. The first event of response creation,
where the response is in an initial state of `in_progress`.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `response.created`.
x-stainless-const: true
const: response.created
response:
$ref: '#/components/schemas/RealtimeResponse'
required:
- event_id
- type
- response
x-oaiMeta:
name: response.created
group: realtime
example: |
{
"event_id": "event_2930",
"type": "response.created",
"response": {
"id": "resp_001",
"object": "realtime.response",
"status": "in_progress",
"status_details": null,
"output": [],
"usage": null
}
}
RealtimeServerEventResponseDone:
type: object
description: |
Returned when a Response is done streaming. Always emitted, no matter the
final state. The Response object included in the `response.done` event will
include all output Items in the Response but will omit the raw audio data.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `response.done`.
x-stainless-const: true
const: response.done
response:
$ref: '#/components/schemas/RealtimeResponse'
required:
- event_id
- type
- response
x-oaiMeta:
name: response.done
group: realtime
example: |
{
"event_id": "event_3132",
"type": "response.done",
"response": {
"id": "resp_001",
"object": "realtime.response",
"status": "completed",
"status_details": null,
"output": [
{
"id": "msg_006",
"object": "realtime.item",
"type": "message",
"status": "completed",
"role": "assistant",
"content": [
{
"type": "text",
"text": "Sure, how can I assist you today?"
}
]
}
],
"usage": {
"total_tokens":275,
"input_tokens":127,
"output_tokens":148,
"input_token_details": {
"cached_tokens":384,
"text_tokens":119,
"audio_tokens":8,
"cached_tokens_details": {
"text_tokens": 128,
"audio_tokens": 256
}
},
"output_token_details": {
"text_tokens":36,
"audio_tokens":112
}
}
}
}
RealtimeServerEventResponseFunctionCallArgumentsDelta:
type: object
description: |
Returned when the model-generated function call arguments are updated.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: |
The event type, must be `response.function_call_arguments.delta`.
x-stainless-const: true
const: response.function_call_arguments.delta
response_id:
type: string
description: The ID of the response.
item_id:
type: string
description: The ID of the function call item.
output_index:
type: integer
description: The index of the output item in the response.
call_id:
type: string
description: The ID of the function call.
delta:
type: string
description: The arguments delta as a JSON string.
required:
- event_id
- type
- response_id
- item_id
- output_index
- call_id
- delta
x-oaiMeta:
name: response.function_call_arguments.delta
group: realtime
example: |
{
"event_id": "event_5354",
"type": "response.function_call_arguments.delta",
"response_id": "resp_002",
"item_id": "fc_001",
"output_index": 0,
"call_id": "call_001",
"delta": "{\"location\": \"San\""
}
RealtimeServerEventResponseFunctionCallArgumentsDone:
type: object
description: |
Returned when the model-generated function call arguments are done streaming.
Also emitted when a Response is interrupted, incomplete, or cancelled.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: |
The event type, must be `response.function_call_arguments.done`.
x-stainless-const: true
const: response.function_call_arguments.done
response_id:
type: string
description: The ID of the response.
item_id:
type: string
description: The ID of the function call item.
output_index:
type: integer
description: The index of the output item in the response.
call_id:
type: string
description: The ID of the function call.
arguments:
type: string
description: The final arguments as a JSON string.
required:
- event_id
- type
- response_id
- item_id
- output_index
- call_id
- arguments
x-oaiMeta:
name: response.function_call_arguments.done
group: realtime
example: |
{
"event_id": "event_5556",
"type": "response.function_call_arguments.done",
"response_id": "resp_002",
"item_id": "fc_001",
"output_index": 0,
"call_id": "call_001",
"arguments": "{\"location\": \"San Francisco\"}"
}
RealtimeServerEventResponseOutputItemAdded:
type: object
description: Returned when a new Item is created during Response generation.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `response.output_item.added`.
x-stainless-const: true
const: response.output_item.added
response_id:
type: string
description: The ID of the Response to which the item belongs.
output_index:
type: integer
description: The index of the output item in the Response.
item:
$ref: '#/components/schemas/RealtimeConversationItem'
required:
- event_id
- type
- response_id
- output_index
- item
x-oaiMeta:
name: response.output_item.added
group: realtime
example: |
{
"event_id": "event_3334",
"type": "response.output_item.added",
"response_id": "resp_001",
"output_index": 0,
"item": {
"id": "msg_007",
"object": "realtime.item",
"type": "message",
"status": "in_progress",
"role": "assistant",
"content": []
}
}
RealtimeServerEventResponseOutputItemDone:
type: object
description: |
Returned when an Item is done streaming. Also emitted when a Response is
interrupted, incomplete, or cancelled.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `response.output_item.done`.
x-stainless-const: true
const: response.output_item.done
response_id:
type: string
description: The ID of the Response to which the item belongs.
output_index:
type: integer
description: The index of the output item in the Response.
item:
$ref: '#/components/schemas/RealtimeConversationItem'
required:
- event_id
- type
- response_id
- output_index
- item
x-oaiMeta:
name: response.output_item.done
group: realtime
example: |
{
"event_id": "event_3536",
"type": "response.output_item.done",
"response_id": "resp_001",
"output_index": 0,
"item": {
"id": "msg_007",
"object": "realtime.item",
"type": "message",
"status": "completed",
"role": "assistant",
"content": [
{
"type": "text",
"text": "Sure, I can help with that."
}
]
}
}
RealtimeServerEventResponseTextDelta:
type: object
description: Returned when the text value of a "text" content part is updated.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `response.text.delta`.
x-stainless-const: true
const: response.text.delta
response_id:
type: string
description: The ID of the response.
item_id:
type: string
description: The ID of the item.
output_index:
type: integer
description: The index of the output item in the response.
content_index:
type: integer
description: The index of the content part in the item's content array.
delta:
type: string
description: The text delta.
required:
- event_id
- type
- response_id
- item_id
- output_index
- content_index
- delta
x-oaiMeta:
name: response.text.delta
group: realtime
example: |
{
"event_id": "event_4142",
"type": "response.text.delta",
"response_id": "resp_001",
"item_id": "msg_007",
"output_index": 0,
"content_index": 0,
"delta": "Sure, I can h"
}
RealtimeServerEventResponseTextDone:
type: object
description: |
Returned when the text value of a "text" content part is done streaming. Also
emitted when a Response is interrupted, incomplete, or cancelled.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `response.text.done`.
x-stainless-const: true
const: response.text.done
response_id:
type: string
description: The ID of the response.
item_id:
type: string
description: The ID of the item.
output_index:
type: integer
description: The index of the output item in the response.
content_index:
type: integer
description: The index of the content part in the item's content array.
text:
type: string
description: The final text content.
required:
- event_id
- type
- response_id
- item_id
- output_index
- content_index
- text
x-oaiMeta:
name: response.text.done
group: realtime
example: |
{
"event_id": "event_4344",
"type": "response.text.done",
"response_id": "resp_001",
"item_id": "msg_007",
"output_index": 0,
"content_index": 0,
"text": "Sure, I can help with that."
}
RealtimeServerEventSessionCreated:
type: object
description: |
Returned when a Session is created. Emitted automatically when a new
connection is established as the first server event. This event will contain
the default Session configuration.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `session.created`.
x-stainless-const: true
const: session.created
session:
$ref: '#/components/schemas/RealtimeSession'
required:
- event_id
- type
- session
x-oaiMeta:
name: session.created
group: realtime
example: |
{
"event_id": "event_1234",
"type": "session.created",
"session": {
"id": "sess_001",
"object": "realtime.session",
"model": "gpt-4o-realtime-preview",
"modalities": ["text", "audio"],
"instructions": "...model instructions here...",
"voice": "sage",
"input_audio_format": "pcm16",
"output_audio_format": "pcm16",
"input_audio_transcription": null,
"turn_detection": {
"type": "server_vad",
"threshold": 0.5,
"prefix_padding_ms": 300,
"silence_duration_ms": 200
},
"tools": [],
"tool_choice": "auto",
"temperature": 0.8,
"max_response_output_tokens": "inf",
"speed": 1.1,
"tracing": "auto"
}
}
RealtimeServerEventSessionUpdated:
type: object
description: |
Returned when a session is updated with a `session.update` event, unless
there is an error.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `session.updated`.
x-stainless-const: true
const: session.updated
session:
$ref: '#/components/schemas/RealtimeSession'
required:
- event_id
- type
- session
x-oaiMeta:
name: session.updated
group: realtime
example: |
{
"event_id": "event_5678",
"type": "session.updated",
"session": {
"id": "sess_001",
"object": "realtime.session",
"model": "gpt-4o-realtime-preview",
"modalities": ["text"],
"instructions": "New instructions",
"voice": "sage",
"input_audio_format": "pcm16",
"output_audio_format": "pcm16",
"input_audio_transcription": {
"model": "whisper-1"
},
"turn_detection": null,
"tools": [],
"tool_choice": "none",
"temperature": 0.7,
"max_response_output_tokens": 200,
"speed": 1.1,
"tracing": "auto"
}
}
RealtimeServerEventTranscriptionSessionUpdated:
type: object
description: |
Returned when a transcription session is updated with a `transcription_session.update` event, unless
there is an error.
properties:
event_id:
type: string
description: The unique ID of the server event.
type:
description: The event type, must be `transcription_session.updated`.
x-stainless-const: true
const: transcription_session.updated
session:
$ref: '#/components/schemas/RealtimeTranscriptionSessionCreateResponse'
required:
- event_id
- type
- session
x-oaiMeta:
name: transcription_session.updated
group: realtime
example: |
{
"event_id": "event_5678",
"type": "transcription_session.updated",
"session": {
"id": "sess_001",
"object": "realtime.transcription_session",
"input_audio_format": "pcm16",
"input_audio_transcription": {
"model": "gpt-4o-transcribe",
"prompt": "",
"language": ""
},
"turn_detection": {
"type": "server_vad",
"threshold": 0.5,
"prefix_padding_ms": 300,
"silence_duration_ms": 500,
"create_response": true,
// "interrupt_response": false -- this will NOT be returned
},
"input_audio_noise_reduction": {
"type": "near_field"
},
"include": [
"item.input_audio_transcription.avg_logprob",
],
}
}
RealtimeSession:
type: object
description: Realtime session object configuration.
properties:
id:
type: string
description: |
Unique identifier for the session that looks like `sess_1234567890abcdef`.
modalities:
description: |
The set of modalities the model can respond with. To disable audio,
set this to ["text"].
items:
type: string
enum:
- text
- audio
model:
type: string
description: |
The Realtime model used for this session.
enum:
- gpt-4o-realtime-preview
- gpt-4o-realtime-preview-2024-10-01
- gpt-4o-realtime-preview-2024-12-17
- gpt-4o-realtime-preview-2025-06-03
- gpt-4o-mini-realtime-preview
- gpt-4o-mini-realtime-preview-2024-12-17
instructions:
type: string
description: |
The default system instructions (i.e. system message) prepended to model
calls. This field allows the client to guide the model on desired
responses. The model can be instructed on response content and format,
(e.g. "be extremely succinct", "act friendly", "here are examples of good
responses") and on audio behavior (e.g. "talk quickly", "inject emotion
into your voice", "laugh frequently"). The instructions are not
guaranteed to be followed by the model, but they provide guidance to the
model on the desired behavior.
Note that the server sets default instructions which will be used if this
field is not set and are visible in the `session.created` event at the
start of the session.
voice:
$ref: '#/components/schemas/VoiceIdsShared'
description: |
The voice the model uses to respond. Voice cannot be changed during the
session once the model has responded with audio at least once. Current
voice options are `alloy`, `ash`, `ballad`, `coral`, `echo`, `sage`,
`shimmer`, and `verse`.
input_audio_format:
type: string
default: pcm16
enum:
- pcm16
- g711_ulaw
- g711_alaw
description: |
The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
For `pcm16`, input audio must be 16-bit PCM at a 24kHz sample rate,
single channel (mono), and little-endian byte order.
output_audio_format:
type: string
default: pcm16
enum:
- pcm16
- g711_ulaw
- g711_alaw
description: |
The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
For `pcm16`, output audio is sampled at a rate of 24kHz.
input_audio_transcription:
type: object
description: >
Configuration for input audio transcription, defaults to off and can be set to `null` to turn off
once on. Input audio transcription is not native to the model, since the model consumes audio
directly. Transcription runs asynchronously through [the /audio/transcriptions
endpoint](https://platform.openai.com/docs/api-reference/audio/createTranscription) and should be
treated as guidance of input audio content rather than precisely what the model heard. The client
can optionally set the language and prompt for transcription, these offer additional guidance to
the transcription service.
properties:
model:
type: string
description: >
The model to use for transcription, current options are `gpt-4o-transcribe`,
`gpt-4o-mini-transcribe`, and `whisper-1`.
language:
type: string
description: |
The language of the input audio. Supplying the input language in
[ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format
will improve accuracy and latency.
prompt:
type: string
description: >
An optional text to guide the model's style or continue a previous audio
segment.
For `whisper-1`, the [prompt is a list of
keywords](https://platform.openai.com/docs/guides/speech-to-text#prompting).
For `gpt-4o-transcribe` models, the prompt is a free text string, for example "expect words
related to technology".
turn_detection:
type: object
description: >
Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to `null` to
turn off, in which case the client must manually trigger model response.
Server VAD means that the model will detect the start and end of speech based on audio volume and
respond at the end of user speech.
Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to
semantically estimate whether the user has finished speaking, then dynamically sets a timeout
based on this probability. For example, if user audio trails off with "uhhm", the model will score
a low probability of turn end and wait longer for the user to continue speaking. This can be
useful for more natural conversations, but may have a higher latency.
properties:
type:
type: string
default: server_vad
enum:
- server_vad
- semantic_vad
description: |
Type of turn detection.
eagerness:
type: string
default: auto
enum:
- low
- medium
- high
- auto
description: >
Used only for `semantic_vad` mode. The eagerness of the model to respond. `low` will wait
longer for the user to continue speaking, `high` will respond more quickly. `auto` is the
default and is equivalent to `medium`.
threshold:
type: number
description: >
Used only for `server_vad` mode. Activation threshold for VAD (0.0 to 1.0), this defaults to
0.5. A
higher threshold will require louder audio to activate the model, and
thus might perform better in noisy environments.
prefix_padding_ms:
type: integer
description: |
Used only for `server_vad` mode. Amount of audio to include before the VAD detected speech (in
milliseconds). Defaults to 300ms.
silence_duration_ms:
type: integer
description: >
Used only for `server_vad` mode. Duration of silence to detect speech stop (in milliseconds).
Defaults
to 500ms. With shorter values the model will respond more quickly,
but may jump in on short pauses from the user.
create_response:
type: boolean
default: true
description: |
Whether or not to automatically generate a response when a VAD stop event occurs.
interrupt_response:
type: boolean
default: true
description: |
Whether or not to automatically interrupt any ongoing response with output to the default
conversation (i.e. `conversation` of `auto`) when a VAD start event occurs.
input_audio_noise_reduction:
type: object
description: >
Configuration for input audio noise reduction. This can be set to `null` to turn off.
Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the
model.
Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and
model performance by improving perception of the input audio.
properties:
type:
type: string
enum:
- near_field
- far_field
description: >
Type of noise reduction. `near_field` is for close-talking microphones such as headphones,
`far_field` is for far-field microphones such as laptop or conference room microphones.
speed:
type: number
default: 1
maximum: 1.5
minimum: 0.25
description: |
The speed of the model's spoken response. 1.0 is the default speed. 0.25 is
the minimum speed. 1.5 is the maximum speed. This value can only be changed
in between model turns, not while a response is in progress.
tracing:
title: Tracing Configuration
description: |
Configuration options for tracing. Set to null to disable tracing. Once
tracing is enabled for a session, the configuration cannot be modified.
`auto` will create a trace for the session with default values for the
workflow name, group id, and metadata.
anyOf:
- type: string
default: auto
description: |
Default tracing mode for the session.
enum:
- auto
x-stainless-const: true
- type: object
title: Tracing Configuration
description: |
Granular configuration for tracing.
properties:
workflow_name:
type: string
description: |
The name of the workflow to attach to this trace. This is used to
name the trace in the traces dashboard.
group_id:
type: string
description: |
The group id to attach to this trace to enable filtering and
grouping in the traces dashboard.
metadata:
type: object
description: |
The arbitrary metadata to attach to this trace to enable
filtering in the traces dashboard.
tools:
type: array
description: Tools (functions) available to the model.
items:
type: object
properties:
type:
type: string
enum:
- function
description: The type of the tool, i.e. `function`.
x-stainless-const: true
name:
type: string
description: The name of the function.
description:
type: string
description: |
The description of the function, including guidance on when and how
to call it, and guidance about what to tell the user when calling
(if anything).
parameters:
type: object
description: Parameters of the function in JSON Schema.
tool_choice:
type: string
default: auto
description: |
How the model chooses tools. Options are `auto`, `none`, `required`, or
specify a function.
temperature:
type: number
default: 0.8
description: >
Sampling temperature for the model, limited to [0.6, 1.2]. For audio models a temperature of 0.8
is highly recommended for best performance.
max_response_output_tokens:
description: |
Maximum number of output tokens for a single assistant response,
inclusive of tool calls. Provide an integer between 1 and 4096 to
limit output tokens, or `inf` for the maximum available tokens for a
given model. Defaults to `inf`.
anyOf:
- type: integer
- type: string
enum:
- inf
x-stainless-const: true
RealtimeSessionCreateRequest:
type: object
description: Realtime session object configuration.
properties:
modalities:
description: |
The set of modalities the model can respond with. To disable audio,
set this to ["text"].
items:
type: string
enum:
- text
- audio
model:
type: string
description: |
The Realtime model used for this session.
enum:
- gpt-4o-realtime-preview
- gpt-4o-realtime-preview-2024-10-01
- gpt-4o-realtime-preview-2024-12-17
- gpt-4o-realtime-preview-2025-06-03
- gpt-4o-mini-realtime-preview
- gpt-4o-mini-realtime-preview-2024-12-17
instructions:
type: string
description: >
The default system instructions (i.e. system message) prepended to model calls. This field allows
the client to guide the model on desired responses. The model can be instructed on response
content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good
responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh
frequently"). The instructions are not guaranteed to be followed by the model, but they provide
guidance to the model on the desired behavior.
Note that the server sets default instructions which will be used if this field is not set and are
visible in the `session.created` event at the start of the session.
voice:
$ref: '#/components/schemas/VoiceIdsShared'
description: |
The voice the model uses to respond. Voice cannot be changed during the
session once the model has responded with audio at least once. Current
voice options are `alloy`, `ash`, `ballad`, `coral`, `echo`, `sage`,
`shimmer`, and `verse`.
input_audio_format:
type: string
default: pcm16
enum:
- pcm16
- g711_ulaw
- g711_alaw
description: |
The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
For `pcm16`, input audio must be 16-bit PCM at a 24kHz sample rate,
single channel (mono), and little-endian byte order.
output_audio_format:
type: string
default: pcm16
enum:
- pcm16
- g711_ulaw
- g711_alaw
description: |
The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
For `pcm16`, output audio is sampled at a rate of 24kHz.
input_audio_transcription:
type: object
description: >
Configuration for input audio transcription, defaults to off and can be set to `null` to turn off
once on. Input audio transcription is not native to the model, since the model consumes audio
directly. Transcription runs asynchronously through [the /audio/transcriptions
endpoint](https://platform.openai.com/docs/api-reference/audio/createTranscription) and should be
treated as guidance of input audio content rather than precisely what the model heard. The client
can optionally set the language and prompt for transcription, these offer additional guidance to
the transcription service.
properties:
model:
type: string
description: >
The model to use for transcription, current options are `gpt-4o-transcribe`,
`gpt-4o-mini-transcribe`, and `whisper-1`.
language:
type: string
description: |
The language of the input audio. Supplying the input language in
[ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format
will improve accuracy and latency.
prompt:
type: string
description: >
An optional text to guide the model's style or continue a previous audio
segment.
For `whisper-1`, the [prompt is a list of
keywords](https://platform.openai.com/docs/guides/speech-to-text#prompting).
For `gpt-4o-transcribe` models, the prompt is a free text string, for example "expect words
related to technology".
turn_detection:
type: object
description: >
Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to `null` to
turn off, in which case the client must manually trigger model response.
Server VAD means that the model will detect the start and end of speech based on audio volume and
respond at the end of user speech.
Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to
semantically estimate whether the user has finished speaking, then dynamically sets a timeout
based on this probability. For example, if user audio trails off with "uhhm", the model will score
a low probability of turn end and wait longer for the user to continue speaking. This can be
useful for more natural conversations, but may have a higher latency.
properties:
type:
type: string
default: server_vad
enum:
- server_vad
- semantic_vad
description: |
Type of turn detection.
eagerness:
type: string
default: auto
enum:
- low
- medium
- high
- auto
description: >
Used only for `semantic_vad` mode. The eagerness of the model to respond. `low` will wait
longer for the user to continue speaking, `high` will respond more quickly. `auto` is the
default and is equivalent to `medium`.
threshold:
type: number
description: >
Used only for `server_vad` mode. Activation threshold for VAD (0.0 to 1.0), this defaults to
0.5. A
higher threshold will require louder audio to activate the model, and
thus might perform better in noisy environments.
prefix_padding_ms:
type: integer
description: |
Used only for `server_vad` mode. Amount of audio to include before the VAD detected speech (in
milliseconds). Defaults to 300ms.
silence_duration_ms:
type: integer
description: >
Used only for `server_vad` mode. Duration of silence to detect speech stop (in milliseconds).
Defaults
to 500ms. With shorter values the model will respond more quickly,
but may jump in on short pauses from the user.
create_response:
type: boolean
default: true
description: |
Whether or not to automatically generate a response when a VAD stop event occurs.
interrupt_response:
type: boolean
default: true
description: |
Whether or not to automatically interrupt any ongoing response with output to the default
conversation (i.e. `conversation` of `auto`) when a VAD start event occurs.
input_audio_noise_reduction:
type: object
description: >
Configuration for input audio noise reduction. This can be set to `null` to turn off.
Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the
model.
Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and
model performance by improving perception of the input audio.
properties:
type:
type: string
enum:
- near_field
- far_field
description: >
Type of noise reduction. `near_field` is for close-talking microphones such as headphones,
`far_field` is for far-field microphones such as laptop or conference room microphones.
speed:
type: number
default: 1
maximum: 1.5
minimum: 0.25
description: |
The speed of the model's spoken response. 1.0 is the default speed. 0.25 is
the minimum speed. 1.5 is the maximum speed. This value can only be changed
in between model turns, not while a response is in progress.
tracing:
title: Tracing Configuration
description: |
Configuration options for tracing. Set to null to disable tracing. Once
tracing is enabled for a session, the configuration cannot be modified.
`auto` will create a trace for the session with default values for the
workflow name, group id, and metadata.
anyOf:
- type: string
default: auto
description: |
Default tracing mode for the session.
enum:
- auto
x-stainless-const: true
- type: object
title: Tracing Configuration
description: |
Granular configuration for tracing.
properties:
workflow_name:
type: string
description: |
The name of the workflow to attach to this trace. This is used to
name the trace in the traces dashboard.
group_id:
type: string
description: |
The group id to attach to this trace to enable filtering and
grouping in the traces dashboard.
metadata:
type: object
description: |
The arbitrary metadata to attach to this trace to enable
filtering in the traces dashboard.
tools:
type: array
description: Tools (functions) available to the model.
items:
type: object
properties:
type:
type: string
enum:
- function
description: The type of the tool, i.e. `function`.
x-stainless-const: true
name:
type: string
description: The name of the function.
description:
type: string
description: |
The description of the function, including guidance on when and how
to call it, and guidance about what to tell the user when calling
(if anything).
parameters:
type: object
description: Parameters of the function in JSON Schema.
tool_choice:
type: string
default: auto
description: |
How the model chooses tools. Options are `auto`, `none`, `required`, or
specify a function.
temperature:
type: number
default: 0.8
description: >
Sampling temperature for the model, limited to [0.6, 1.2]. For audio models a temperature of 0.8
is highly recommended for best performance.
max_response_output_tokens:
description: |
Maximum number of output tokens for a single assistant response,
inclusive of tool calls. Provide an integer between 1 and 4096 to
limit output tokens, or `inf` for the maximum available tokens for a
given model. Defaults to `inf`.
anyOf:
- type: integer
- type: string
enum:
- inf
x-stainless-const: true
client_secret:
type: object
description: |
Configuration options for the generated client secret.
properties:
expires_after:
type: object
description: |
Configuration for the ephemeral token expiration.
properties:
anchor:
type: string
enum:
- created_at
description: >
The anchor point for the ephemeral token expiration. Only `created_at` is currently
supported.
seconds:
default: 600
type: integer
description: >
The number of seconds from the anchor point to the expiration. Select a value between `10`
and `7200`.
required:
- anchor
RealtimeSessionCreateResponse:
type: object
description: |
A new Realtime session configuration, with an ephemeral key. Default TTL
for keys is one minute.
properties:
client_secret:
type: object
description: Ephemeral key returned by the API.
properties:
value:
type: string
description: |
Ephemeral key usable in client environments to authenticate connections
to the Realtime API. Use this in client-side environments rather than
a standard API token, which should only be used server-side.
expires_at:
type: integer
description: |
Timestamp for when the token expires. Currently, all tokens expire
after one minute.
required:
- value
- expires_at
modalities:
description: |
The set of modalities the model can respond with. To disable audio,
set this to ["text"].
items:
type: string
enum:
- text
- audio
instructions:
type: string
description: |
The default system instructions (i.e. system message) prepended to model
calls. This field allows the client to guide the model on desired
responses. The model can be instructed on response content and format,
(e.g. "be extremely succinct", "act friendly", "here are examples of good
responses") and on audio behavior (e.g. "talk quickly", "inject emotion
into your voice", "laugh frequently"). The instructions are not guaranteed
to be followed by the model, but they provide guidance to the model on the
desired behavior.
Note that the server sets default instructions which will be used if this
field is not set and are visible in the `session.created` event at the
start of the session.
voice:
$ref: '#/components/schemas/VoiceIdsShared'
description: |
The voice the model uses to respond. Voice cannot be changed during the
session once the model has responded with audio at least once. Current
voice options are `alloy`, `ash`, `ballad`, `coral`, `echo`, `sage`,
`shimmer`, and `verse`.
input_audio_format:
type: string
description: |
The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
output_audio_format:
type: string
description: |
The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
input_audio_transcription:
type: object
description: |
Configuration for input audio transcription, defaults to off and can be
set to `null` to turn off once on. Input audio transcription is not native
to the model, since the model consumes audio directly. Transcription runs
asynchronously and should be treated as rough guidance
rather than the representation understood by the model.
properties:
model:
type: string
description: |
The model to use for transcription.
speed:
type: number
default: 1
maximum: 1.5
minimum: 0.25
description: |
The speed of the model's spoken response. 1.0 is the default speed. 0.25 is
the minimum speed. 1.5 is the maximum speed. This value can only be changed
in between model turns, not while a response is in progress.
tracing:
title: Tracing Configuration
description: |
Configuration options for tracing. Set to null to disable tracing. Once
tracing is enabled for a session, the configuration cannot be modified.
`auto` will create a trace for the session with default values for the
workflow name, group id, and metadata.
anyOf:
- type: string
default: auto
description: |
Default tracing mode for the session.
enum:
- auto
x-stainless-const: true
- type: object
title: Tracing Configuration
description: |
Granular configuration for tracing.
properties:
workflow_name:
type: string
description: |
The name of the workflow to attach to this trace. This is used to
name the trace in the traces dashboard.
group_id:
type: string
description: |
The group id to attach to this trace to enable filtering and
grouping in the traces dashboard.
metadata:
type: object
description: |
The arbitrary metadata to attach to this trace to enable
filtering in the traces dashboard.
turn_detection:
type: object
description: |
Configuration for turn detection. Can be set to `null` to turn off. Server
VAD means that the model will detect the start and end of speech based on
audio volume and respond at the end of user speech.
properties:
type:
type: string
description: |
Type of turn detection, only `server_vad` is currently supported.
threshold:
type: number
description: |
Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A
higher threshold will require louder audio to activate the model, and
thus might perform better in noisy environments.
prefix_padding_ms:
type: integer
description: |
Amount of audio to include before the VAD detected speech (in
milliseconds). Defaults to 300ms.
silence_duration_ms:
type: integer
description: |
Duration of silence to detect speech stop (in milliseconds). Defaults
to 500ms. With shorter values the model will respond more quickly,
but may jump in on short pauses from the user.
tools:
type: array
description: Tools (functions) available to the model.
items:
type: object
properties:
type:
type: string
enum:
- function
description: The type of the tool, i.e. `function`.
x-stainless-const: true
name:
type: string
description: The name of the function.
description:
type: string
description: |
The description of the function, including guidance on when and how
to call it, and guidance about what to tell the user when calling
(if anything).
parameters:
type: object
description: Parameters of the function in JSON Schema.
tool_choice:
type: string
description: |
How the model chooses tools. Options are `auto`, `none`, `required`, or
specify a function.
temperature:
type: number
description: |
Sampling temperature for the model, limited to [0.6, 1.2]. Defaults to 0.8.
max_response_output_tokens:
description: |
Maximum number of output tokens for a single assistant response,
inclusive of tool calls. Provide an integer between 1 and 4096 to
limit output tokens, or `inf` for the maximum available tokens for a
given model. Defaults to `inf`.
anyOf:
- type: integer
- type: string
enum:
- inf
x-stainless-const: true
required:
- client_secret
x-oaiMeta:
name: The session object
group: realtime
example: |
{
"id": "sess_001",
"object": "realtime.session",
"model": "gpt-4o-realtime-preview",
"modalities": ["audio", "text"],
"instructions": "You are a friendly assistant.",
"voice": "alloy",
"input_audio_format": "pcm16",
"output_audio_format": "pcm16",
"input_audio_transcription": {
"model": "whisper-1"
},
"turn_detection": null,
"tools": [],
"tool_choice": "none",
"temperature": 0.7,
"speed": 1.1,
"tracing": "auto",
"max_response_output_tokens": 200,
"client_secret": {
"value": "ek_abc123",
"expires_at": 1234567890
}
}
RealtimeTranscriptionSessionCreateRequest:
type: object
description: Realtime transcription session object configuration.
properties:
modalities:
description: |
The set of modalities the model can respond with. To disable audio,
set this to ["text"].
items:
type: string
enum:
- text
- audio
input_audio_format:
type: string
default: pcm16
enum:
- pcm16
- g711_ulaw
- g711_alaw
description: |
The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
For `pcm16`, input audio must be 16-bit PCM at a 24kHz sample rate,
single channel (mono), and little-endian byte order.
input_audio_transcription:
type: object
description: >
Configuration for input audio transcription. The client can optionally set the language and prompt
for transcription, these offer additional guidance to the transcription service.
properties:
model:
type: string
description: >
The model to use for transcription, current options are `gpt-4o-transcribe`,
`gpt-4o-mini-transcribe`, and `whisper-1`.
enum:
- gpt-4o-transcribe
- gpt-4o-mini-transcribe
- whisper-1
language:
type: string
description: |
The language of the input audio. Supplying the input language in
[ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format
will improve accuracy and latency.
prompt:
type: string
description: >
An optional text to guide the model's style or continue a previous audio
segment.
For `whisper-1`, the [prompt is a list of
keywords](https://platform.openai.com/docs/guides/speech-to-text#prompting).
For `gpt-4o-transcribe` models, the prompt is a free text string, for example "expect words
related to technology".
turn_detection:
type: object
description: >
Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to `null` to
turn off, in which case the client must manually trigger model response.
Server VAD means that the model will detect the start and end of speech based on audio volume and
respond at the end of user speech.
Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to
semantically estimate whether the user has finished speaking, then dynamically sets a timeout
based on this probability. For example, if user audio trails off with "uhhm", the model will score
a low probability of turn end and wait longer for the user to continue speaking. This can be
useful for more natural conversations, but may have a higher latency.
properties:
type:
type: string
default: server_vad
enum:
- server_vad
- semantic_vad
description: |
Type of turn detection.
eagerness:
type: string
default: auto
enum:
- low
- medium
- high
- auto
description: >
Used only for `semantic_vad` mode. The eagerness of the model to respond. `low` will wait
longer for the user to continue speaking, `high` will respond more quickly. `auto` is the
default and is equivalent to `medium`.
threshold:
type: number
description: >
Used only for `server_vad` mode. Activation threshold for VAD (0.0 to 1.0), this defaults to
0.5. A
higher threshold will require louder audio to activate the model, and
thus might perform better in noisy environments.
prefix_padding_ms:
type: integer
description: |
Used only for `server_vad` mode. Amount of audio to include before the VAD detected speech (in
milliseconds). Defaults to 300ms.
silence_duration_ms:
type: integer
description: >
Used only for `server_vad` mode. Duration of silence to detect speech stop (in milliseconds).
Defaults
to 500ms. With shorter values the model will respond more quickly,
but may jump in on short pauses from the user.
create_response:
type: boolean
default: true
description: >
Whether or not to automatically generate a response when a VAD stop event occurs. Not
available for transcription sessions.
interrupt_response:
type: boolean
default: true
description: >
Whether or not to automatically interrupt any ongoing response with output to the default
conversation (i.e. `conversation` of `auto`) when a VAD start event occurs. Not available for
transcription sessions.
input_audio_noise_reduction:
type: object
description: >
Configuration for input audio noise reduction. This can be set to `null` to turn off.
Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the
model.
Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and
model performance by improving perception of the input audio.
properties:
type:
type: string
enum:
- near_field
- far_field
description: >
Type of noise reduction. `near_field` is for close-talking microphones such as headphones,
`far_field` is for far-field microphones such as laptop or conference room microphones.
include:
type: array
items:
type: string
description: |
The set of items to include in the transcription. Current available items are:
- `item.input_audio_transcription.logprobs`
client_secret:
type: object
description: |
Configuration options for the generated client secret.
properties:
expires_at:
type: object
description: |
Configuration for the ephemeral token expiration.
properties:
anchor:
default: created_at
type: string
enum:
- created_at
description: >
The anchor point for the ephemeral token expiration. Only `created_at` is currently
supported.
seconds:
default: 600
type: integer
description: >
The number of seconds from the anchor point to the expiration. Select a value between `10`
and `7200`.
RealtimeTranscriptionSessionCreateResponse:
type: object
description: |
A new Realtime transcription session configuration.
When a session is created on the server via REST API, the session object
also contains an ephemeral key. Default TTL for keys is 10 minutes. This
property is not present when a session is updated via the WebSocket API.
properties:
client_secret:
type: object
description: |
Ephemeral key returned by the API. Only present when the session is
created on the server via REST API.
properties:
value:
type: string
description: |
Ephemeral key usable in client environments to authenticate connections
to the Realtime API. Use this in client-side environments rather than
a standard API token, which should only be used server-side.
expires_at:
type: integer
description: |
Timestamp for when the token expires. Currently, all tokens expire
after one minute.
required:
- value
- expires_at
modalities:
description: |
The set of modalities the model can respond with. To disable audio,
set this to ["text"].
items:
type: string
enum:
- text
- audio
input_audio_format:
type: string
description: |
The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
input_audio_transcription:
type: object
description: |
Configuration of the transcription model.
properties:
model:
type: string
description: >
The model to use for transcription. Can be `gpt-4o-transcribe`, `gpt-4o-mini-transcribe`, or
`whisper-1`.
enum:
- gpt-4o-transcribe
- gpt-4o-mini-transcribe
- whisper-1
language:
type: string
description: |
The language of the input audio. Supplying the input language in
[ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format
will improve accuracy and latency.
prompt:
type: string
description: >
An optional text to guide the model's style or continue a previous audio
segment. The [prompt](https://platform.openai.com/docs/guides/speech-to-text#prompting) should
match
the audio language.
turn_detection:
type: object
description: |
Configuration for turn detection. Can be set to `null` to turn off. Server
VAD means that the model will detect the start and end of speech based on
audio volume and respond at the end of user speech.
properties:
type:
type: string
description: |
Type of turn detection, only `server_vad` is currently supported.
threshold:
type: number
description: |
Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A
higher threshold will require louder audio to activate the model, and
thus might perform better in noisy environments.
prefix_padding_ms:
type: integer
description: |
Amount of audio to include before the VAD detected speech (in
milliseconds). Defaults to 300ms.
silence_duration_ms:
type: integer
description: |
Duration of silence to detect speech stop (in milliseconds). Defaults
to 500ms. With shorter values the model will respond more quickly,
but may jump in on short pauses from the user.
required:
- client_secret
x-oaiMeta:
name: The transcription session object
group: realtime
example: |
{
"id": "sess_BBwZc7cFV3XizEyKGDCGL",
"object": "realtime.transcription_session",
"expires_at": 1742188264,
"modalities": ["audio", "text"],
"turn_detection": {
"type": "server_vad",
"threshold": 0.5,
"prefix_padding_ms": 300,
"silence_duration_ms": 200
},
"input_audio_format": "pcm16",
"input_audio_transcription": {
"model": "gpt-4o-transcribe",
"language": null,
"prompt": ""
},
"client_secret": null
}
Reasoning:
type: object
description: |
**gpt-5 and o-series models only**
Configuration options for
[reasoning models](https://platform.openai.com/docs/guides/reasoning).
title: Reasoning
properties:
effort:
$ref: '#/components/schemas/ReasoningEffort'
summary:
type: string
description: |
A summary of the reasoning performed by the model. This can be
useful for debugging and understanding the model's reasoning process.
One of `auto`, `concise`, or `detailed`.
enum:
- auto
- concise
- detailed
nullable: true
generate_summary:
type: string
deprecated: true
description: |
**Deprecated:** use `summary` instead.
A summary of the reasoning performed by the model. This can be
useful for debugging and understanding the model's reasoning process.
One of `auto`, `concise`, or `detailed`.
enum:
- auto
- concise
- detailed
nullable: true
ReasoningEffort:
type: string
enum:
- minimal
- low
- medium
- high
default: medium
nullable: true
description: |
Constrains effort on reasoning for
[reasoning models](https://platform.openai.com/docs/guides/reasoning).
Currently supported values are `minimal`, `low`, `medium`, and `high`. Reducing
reasoning effort can result in faster responses and fewer tokens used
on reasoning in a response.
ReasoningItem:
type: object
description: |
A description of the chain of thought used by a reasoning model while generating
a response. Be sure to include these items in your `input` to the Responses API
for subsequent turns of a conversation if you are manually
[managing context](https://platform.openai.com/docs/guides/conversation-state).
title: Reasoning
properties:
type:
type: string
description: |
The type of the object. Always `reasoning`.
enum:
- reasoning
x-stainless-const: true
id:
type: string
description: |
The unique identifier of the reasoning content.
encrypted_content:
type: string
description: |
The encrypted content of the reasoning item - populated when a response is
generated with `reasoning.encrypted_content` in the `include` parameter.
nullable: true
summary:
type: array
description: |
Reasoning summary content.
items:
type: object
properties:
type:
type: string
description: |
The type of the object. Always `summary_text`.
enum:
- summary_text
x-stainless-const: true
text:
type: string
description: |
A summary of the reasoning output from the model so far.
required:
- type
- text
content:
type: array
description: |
Reasoning text content.
items:
type: object
properties:
type:
type: string
description: |
The type of the object. Always `reasoning_text`.
enum:
- reasoning_text
x-stainless-const: true
text:
type: string
description: |
Reasoning text output from the model.
required:
- type
- text
status:
type: string
description: |
The status of the item. One of `in_progress`, `completed`, or
`incomplete`. Populated when items are returned via API.
enum:
- in_progress
- completed
- incomplete
required:
- id
- summary
- type
Response:
title: The response object
allOf:
- $ref: '#/components/schemas/ModelResponseProperties'
- $ref: '#/components/schemas/ResponseProperties'
- type: object
properties:
id:
type: string
description: |
Unique identifier for this Response.
object:
type: string
description: |
The object type of this resource - always set to `response`.
enum:
- response
x-stainless-const: true
status:
type: string
description: |
The status of the response generation. One of `completed`, `failed`,
`in_progress`, `cancelled`, `queued`, or `incomplete`.
enum:
- completed
- failed
- in_progress
- cancelled
- queued
- incomplete
created_at:
type: number
description: |
Unix timestamp (in seconds) of when this Response was created.
error:
$ref: '#/components/schemas/ResponseError'
incomplete_details:
type: object
nullable: true
description: |
Details about why the response is incomplete.
properties:
reason:
type: string
description: The reason why the response is incomplete.
enum:
- max_output_tokens
- content_filter
output:
type: array
description: |
An array of content items generated by the model.
- The length and order of items in the `output` array is dependent
on the model's response.
- Rather than accessing the first item in the `output` array and
assuming it's an `assistant` message with the content generated by
the model, you might consider using the `output_text` property where
supported in SDKs.
items:
$ref: '#/components/schemas/OutputItem'
instructions:
nullable: true
description: |
A system (or developer) message inserted into the model's context.
When using along with `previous_response_id`, the instructions from a previous
response will not be carried over to the next response. This makes it simple
to swap out system (or developer) messages in new responses.
anyOf:
- type: string
description: |
A text input to the model, equivalent to a text input with the
`developer` role.
- type: array
title: Input item list
description: |
A list of one or many input items to the model, containing
different content types.
items:
$ref: '#/components/schemas/InputItem'
output_text:
type: string
nullable: true
description: |
SDK-only convenience property that contains the aggregated text output
from all `output_text` items in the `output` array, if any are present.
Supported in the Python and JavaScript SDKs.
x-oaiSupportedSDKs:
- python
- javascript
x-stainless-skip: true
usage:
$ref: '#/components/schemas/ResponseUsage'
parallel_tool_calls:
type: boolean
description: |
Whether to allow the model to run tool calls in parallel.
default: true
conversation:
nullable: true
$ref: '#/components/schemas/Conversation-2'
required:
- id
- object
- created_at
- error
- incomplete_details
- instructions
- model
- tools
- output
- parallel_tool_calls
- metadata
- tool_choice
- temperature
- top_p
ResponseAudioDeltaEvent:
type: object
description: Emitted when there is a partial audio response.
properties:
type:
type: string
description: |
The type of the event. Always `response.audio.delta`.
enum:
- response.audio.delta
x-stainless-const: true
sequence_number:
type: integer
description: |
A sequence number for this chunk of the stream response.
delta:
type: string
description: |
A chunk of Base64 encoded response audio bytes.
required:
- type
- delta
- sequence_number
x-oaiMeta:
name: response.audio.delta
group: responses
example: |
{
"type": "response.audio.delta",
"response_id": "resp_123",
"delta": "base64encoded...",
"sequence_number": 1
}
ResponseAudioDoneEvent:
type: object
description: Emitted when the audio response is complete.
properties:
type:
type: string
description: |
The type of the event. Always `response.audio.done`.
enum:
- response.audio.done
x-stainless-const: true
sequence_number:
type: integer
description: |
The sequence number of the delta.
required:
- type
- sequence_number
- response_id
x-oaiMeta:
name: response.audio.done
group: responses
example: |
{
"type": "response.audio.done",
"response_id": "resp-123",
"sequence_number": 1
}
ResponseAudioTranscriptDeltaEvent:
type: object
description: Emitted when there is a partial transcript of audio.
properties:
type:
type: string
description: |
The type of the event. Always `response.audio.transcript.delta`.
enum:
- response.audio.transcript.delta
x-stainless-const: true
delta:
type: string
description: |
The partial transcript of the audio response.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- response_id
- delta
- sequence_number
x-oaiMeta:
name: response.audio.transcript.delta
group: responses
example: |
{
"type": "response.audio.transcript.delta",
"response_id": "resp_123",
"delta": " ... partial transcript ... ",
"sequence_number": 1
}
ResponseAudioTranscriptDoneEvent:
type: object
description: Emitted when the full audio transcript is completed.
properties:
type:
type: string
description: |
The type of the event. Always `response.audio.transcript.done`.
enum:
- response.audio.transcript.done
x-stainless-const: true
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- response_id
- sequence_number
x-oaiMeta:
name: response.audio.transcript.done
group: responses
example: |
{
"type": "response.audio.transcript.done",
"response_id": "resp_123",
"sequence_number": 1
}
ResponseCodeInterpreterCallCodeDeltaEvent:
type: object
description: Emitted when a partial code snippet is streamed by the code interpreter.
properties:
type:
type: string
description: The type of the event. Always `response.code_interpreter_call_code.delta`.
enum:
- response.code_interpreter_call_code.delta
x-stainless-const: true
output_index:
type: integer
description: The index of the output item in the response for which the code is being streamed.
item_id:
type: string
description: The unique identifier of the code interpreter tool call item.
delta:
type: string
description: The partial code snippet being streamed by the code interpreter.
sequence_number:
type: integer
description: The sequence number of this event, used to order streaming events.
required:
- type
- output_index
- item_id
- delta
- sequence_number
x-oaiMeta:
name: response.code_interpreter_call_code.delta
group: responses
example: |
{
"type": "response.code_interpreter_call_code.delta",
"output_index": 0,
"item_id": "ci_12345",
"delta": "print('Hello, world')",
"sequence_number": 1
}
ResponseCodeInterpreterCallCodeDoneEvent:
type: object
description: Emitted when the code snippet is finalized by the code interpreter.
properties:
type:
type: string
description: The type of the event. Always `response.code_interpreter_call_code.done`.
enum:
- response.code_interpreter_call_code.done
x-stainless-const: true
output_index:
type: integer
description: The index of the output item in the response for which the code is finalized.
item_id:
type: string
description: The unique identifier of the code interpreter tool call item.
code:
type: string
description: The final code snippet output by the code interpreter.
sequence_number:
type: integer
description: The sequence number of this event, used to order streaming events.
required:
- type
- output_index
- item_id
- code
- sequence_number
x-oaiMeta:
name: response.code_interpreter_call_code.done
group: responses
example: |
{
"type": "response.code_interpreter_call_code.done",
"output_index": 3,
"item_id": "ci_12345",
"code": "print('done')",
"sequence_number": 1
}
ResponseCodeInterpreterCallCompletedEvent:
type: object
description: Emitted when the code interpreter call is completed.
properties:
type:
type: string
description: The type of the event. Always `response.code_interpreter_call.completed`.
enum:
- response.code_interpreter_call.completed
x-stainless-const: true
output_index:
type: integer
description: The index of the output item in the response for which the code interpreter call is completed.
item_id:
type: string
description: The unique identifier of the code interpreter tool call item.
sequence_number:
type: integer
description: The sequence number of this event, used to order streaming events.
required:
- type
- output_index
- item_id
- sequence_number
x-oaiMeta:
name: response.code_interpreter_call.completed
group: responses
example: |
{
"type": "response.code_interpreter_call.completed",
"output_index": 5,
"item_id": "ci_12345",
"sequence_number": 1
}
ResponseCodeInterpreterCallInProgressEvent:
type: object
description: Emitted when a code interpreter call is in progress.
properties:
type:
type: string
description: The type of the event. Always `response.code_interpreter_call.in_progress`.
enum:
- response.code_interpreter_call.in_progress
x-stainless-const: true
output_index:
type: integer
description: The index of the output item in the response for which the code interpreter call is in progress.
item_id:
type: string
description: The unique identifier of the code interpreter tool call item.
sequence_number:
type: integer
description: The sequence number of this event, used to order streaming events.
required:
- type
- output_index
- item_id
- sequence_number
x-oaiMeta:
name: response.code_interpreter_call.in_progress
group: responses
example: |
{
"type": "response.code_interpreter_call.in_progress",
"output_index": 0,
"item_id": "ci_12345",
"sequence_number": 1
}
ResponseCodeInterpreterCallInterpretingEvent:
type: object
description: Emitted when the code interpreter is actively interpreting the code snippet.
properties:
type:
type: string
description: The type of the event. Always `response.code_interpreter_call.interpreting`.
enum:
- response.code_interpreter_call.interpreting
x-stainless-const: true
output_index:
type: integer
description: The index of the output item in the response for which the code interpreter is interpreting code.
item_id:
type: string
description: The unique identifier of the code interpreter tool call item.
sequence_number:
type: integer
description: The sequence number of this event, used to order streaming events.
required:
- type
- output_index
- item_id
- sequence_number
x-oaiMeta:
name: response.code_interpreter_call.interpreting
group: responses
example: |
{
"type": "response.code_interpreter_call.interpreting",
"output_index": 4,
"item_id": "ci_12345",
"sequence_number": 1
}
ResponseCompletedEvent:
type: object
description: Emitted when the model response is complete.
properties:
type:
type: string
description: |
The type of the event. Always `response.completed`.
enum:
- response.completed
x-stainless-const: true
response:
$ref: '#/components/schemas/Response'
description: |
Properties of the completed response.
sequence_number:
type: integer
description: The sequence number for this event.
required:
- type
- response
- sequence_number
x-oaiMeta:
name: response.completed
group: responses
example: |
{
"type": "response.completed",
"response": {
"id": "resp_123",
"object": "response",
"created_at": 1740855869,
"status": "completed",
"error": null,
"incomplete_details": null,
"input": [],
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4o-mini-2024-07-18",
"output": [
{
"id": "msg_123",
"type": "message",
"role": "assistant",
"content": [
{
"type": "output_text",
"text": "In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.",
"annotations": []
}
]
}
],
"previous_response_id": null,
"reasoning_effort": null,
"store": false,
"temperature": 1,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [],
"top_p": 1,
"truncation": "disabled",
"usage": {
"input_tokens": 0,
"output_tokens": 0,
"output_tokens_details": {
"reasoning_tokens": 0
},
"total_tokens": 0
},
"user": null,
"metadata": {}
},
"sequence_number": 1
}
ResponseContentPartAddedEvent:
type: object
description: Emitted when a new content part is added.
properties:
type:
type: string
description: |
The type of the event. Always `response.content_part.added`.
enum:
- response.content_part.added
x-stainless-const: true
item_id:
type: string
description: |
The ID of the output item that the content part was added to.
output_index:
type: integer
description: |
The index of the output item that the content part was added to.
content_index:
type: integer
description: |
The index of the content part that was added.
part:
$ref: '#/components/schemas/OutputContent'
description: |
The content part that was added.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- item_id
- output_index
- content_index
- part
- sequence_number
x-oaiMeta:
name: response.content_part.added
group: responses
example: |
{
"type": "response.content_part.added",
"item_id": "msg_123",
"output_index": 0,
"content_index": 0,
"part": {
"type": "output_text",
"text": "",
"annotations": []
},
"sequence_number": 1
}
ResponseContentPartDoneEvent:
type: object
description: Emitted when a content part is done.
properties:
type:
type: string
description: |
The type of the event. Always `response.content_part.done`.
enum:
- response.content_part.done
x-stainless-const: true
item_id:
type: string
description: |
The ID of the output item that the content part was added to.
output_index:
type: integer
description: |
The index of the output item that the content part was added to.
content_index:
type: integer
description: |
The index of the content part that is done.
sequence_number:
type: integer
description: The sequence number of this event.
part:
$ref: '#/components/schemas/OutputContent'
description: |
The content part that is done.
required:
- type
- item_id
- output_index
- content_index
- part
- sequence_number
x-oaiMeta:
name: response.content_part.done
group: responses
example: |
{
"type": "response.content_part.done",
"item_id": "msg_123",
"output_index": 0,
"content_index": 0,
"sequence_number": 1,
"part": {
"type": "output_text",
"text": "In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.",
"annotations": []
}
}
ResponseCreatedEvent:
type: object
description: |
An event that is emitted when a response is created.
properties:
type:
type: string
description: |
The type of the event. Always `response.created`.
enum:
- response.created
x-stainless-const: true
response:
$ref: '#/components/schemas/Response'
description: |
The response that was created.
sequence_number:
type: integer
description: The sequence number for this event.
required:
- type
- response
- sequence_number
x-oaiMeta:
name: response.created
group: responses
example: |
{
"type": "response.created",
"response": {
"id": "resp_67ccfcdd16748190a91872c75d38539e09e4d4aac714747c",
"object": "response",
"created_at": 1741487325,
"status": "in_progress",
"error": null,
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4o-2024-08-06",
"output": [],
"parallel_tool_calls": true,
"previous_response_id": null,
"reasoning": {
"effort": null,
"summary": null
},
"store": true,
"temperature": 1,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [],
"top_p": 1,
"truncation": "disabled",
"usage": null,
"user": null,
"metadata": {}
},
"sequence_number": 1
}
ResponseCustomToolCallInputDeltaEvent:
title: ResponseCustomToolCallInputDelta
type: object
description: |
Event representing a delta (partial update) to the input of a custom tool call.
properties:
type:
type: string
enum:
- response.custom_tool_call_input.delta
description: The event type identifier.
x-stainless-const: true
sequence_number:
type: integer
description: The sequence number of this event.
output_index:
type: integer
description: The index of the output this delta applies to.
item_id:
type: string
description: Unique identifier for the API item associated with this event.
delta:
type: string
description: The incremental input data (delta) for the custom tool call.
required:
- type
- output_index
- item_id
- delta
- sequence_number
x-oaiMeta:
name: response.custom_tool_call_input.delta
group: responses
example: |
{
"type": "response.custom_tool_call_input.delta",
"output_index": 0,
"item_id": "ctc_1234567890abcdef",
"delta": "partial input text"
}
ResponseCustomToolCallInputDoneEvent:
title: ResponseCustomToolCallInputDone
type: object
description: |
Event indicating that input for a custom tool call is complete.
properties:
type:
type: string
enum:
- response.custom_tool_call_input.done
description: The event type identifier.
x-stainless-const: true
sequence_number:
type: integer
description: The sequence number of this event.
output_index:
type: integer
description: The index of the output this event applies to.
item_id:
type: string
description: Unique identifier for the API item associated with this event.
input:
type: string
description: The complete input data for the custom tool call.
required:
- type
- output_index
- item_id
- input
- sequence_number
x-oaiMeta:
name: response.custom_tool_call_input.done
group: responses
example: |
{
"type": "response.custom_tool_call_input.done",
"output_index": 0,
"item_id": "ctc_1234567890abcdef",
"input": "final complete input text"
}
ResponseError:
type: object
description: |
An error object returned when the model fails to generate a Response.
nullable: true
properties:
code:
$ref: '#/components/schemas/ResponseErrorCode'
message:
type: string
description: |
A human-readable description of the error.
required:
- code
- message
ResponseErrorCode:
type: string
description: |
The error code for the response.
enum:
- server_error
- rate_limit_exceeded
- invalid_prompt
- vector_store_timeout
- invalid_image
- invalid_image_format
- invalid_base64_image
- invalid_image_url
- image_too_large
- image_too_small
- image_parse_error
- image_content_policy_violation
- invalid_image_mode
- image_file_too_large
- unsupported_image_media_type
- empty_image_file
- failed_to_download_image
- image_file_not_found
ResponseErrorEvent:
type: object
description: Emitted when an error occurs.
properties:
type:
type: string
description: |
The type of the event. Always `error`.
enum:
- error
x-stainless-const: true
code:
type: string
description: |
The error code.
nullable: true
message:
type: string
description: |
The error message.
param:
type: string
description: |
The error parameter.
nullable: true
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- code
- message
- param
- sequence_number
x-oaiMeta:
name: error
group: responses
example: |
{
"type": "error",
"code": "ERR_SOMETHING",
"message": "Something went wrong",
"param": null,
"sequence_number": 1
}
ResponseFailedEvent:
type: object
description: |
An event that is emitted when a response fails.
properties:
type:
type: string
description: |
The type of the event. Always `response.failed`.
enum:
- response.failed
x-stainless-const: true
sequence_number:
type: integer
description: The sequence number of this event.
response:
$ref: '#/components/schemas/Response'
description: |
The response that failed.
required:
- type
- response
- sequence_number
x-oaiMeta:
name: response.failed
group: responses
example: |
{
"type": "response.failed",
"response": {
"id": "resp_123",
"object": "response",
"created_at": 1740855869,
"status": "failed",
"error": {
"code": "server_error",
"message": "The model failed to generate a response."
},
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4o-mini-2024-07-18",
"output": [],
"previous_response_id": null,
"reasoning_effort": null,
"store": false,
"temperature": 1,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [],
"top_p": 1,
"truncation": "disabled",
"usage": null,
"user": null,
"metadata": {}
}
}
ResponseFileSearchCallCompletedEvent:
type: object
description: Emitted when a file search call is completed (results found).
properties:
type:
type: string
description: |
The type of the event. Always `response.file_search_call.completed`.
enum:
- response.file_search_call.completed
x-stainless-const: true
output_index:
type: integer
description: |
The index of the output item that the file search call is initiated.
item_id:
type: string
description: |
The ID of the output item that the file search call is initiated.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- output_index
- item_id
- sequence_number
x-oaiMeta:
name: response.file_search_call.completed
group: responses
example: |
{
"type": "response.file_search_call.completed",
"output_index": 0,
"item_id": "fs_123",
"sequence_number": 1
}
ResponseFileSearchCallInProgressEvent:
type: object
description: Emitted when a file search call is initiated.
properties:
type:
type: string
description: |
The type of the event. Always `response.file_search_call.in_progress`.
enum:
- response.file_search_call.in_progress
x-stainless-const: true
output_index:
type: integer
description: |
The index of the output item that the file search call is initiated.
item_id:
type: string
description: |
The ID of the output item that the file search call is initiated.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- output_index
- item_id
- sequence_number
x-oaiMeta:
name: response.file_search_call.in_progress
group: responses
example: |
{
"type": "response.file_search_call.in_progress",
"output_index": 0,
"item_id": "fs_123",
"sequence_number": 1
}
ResponseFileSearchCallSearchingEvent:
type: object
description: Emitted when a file search is currently searching.
properties:
type:
type: string
description: |
The type of the event. Always `response.file_search_call.searching`.
enum:
- response.file_search_call.searching
x-stainless-const: true
output_index:
type: integer
description: |
The index of the output item that the file search call is searching.
item_id:
type: string
description: |
The ID of the output item that the file search call is initiated.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- output_index
- item_id
- sequence_number
x-oaiMeta:
name: response.file_search_call.searching
group: responses
example: |
{
"type": "response.file_search_call.searching",
"output_index": 0,
"item_id": "fs_123",
"sequence_number": 1
}
ResponseFormatJsonObject:
type: object
title: JSON object
description: |
JSON object response format. An older method of generating JSON responses.
Using `json_schema` is recommended for models that support it. Note that the
model will not generate JSON without a system or user message instructing it
to do so.
properties:
type:
type: string
description: The type of response format being defined. Always `json_object`.
enum:
- json_object
x-stainless-const: true
required:
- type
ResponseFormatJsonSchema:
type: object
title: JSON schema
description: |
JSON Schema response format. Used to generate structured JSON responses.
Learn more about [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs).
properties:
type:
type: string
description: The type of response format being defined. Always `json_schema`.
enum:
- json_schema
x-stainless-const: true
json_schema:
type: object
title: JSON schema
description: |
Structured Outputs configuration options, including a JSON Schema.
properties:
description:
type: string
description: |
A description of what the response format is for, used by the model to
determine how to respond in the format.
name:
type: string
description: |
The name of the response format. Must be a-z, A-Z, 0-9, or contain
underscores and dashes, with a maximum length of 64.
schema:
$ref: '#/components/schemas/ResponseFormatJsonSchemaSchema'
strict:
type: boolean
nullable: true
default: false
description: |
Whether to enable strict schema adherence when generating the output.
If set to true, the model will always follow the exact schema defined
in the `schema` field. Only a subset of JSON Schema is supported when
`strict` is `true`. To learn more, read the [Structured Outputs
guide](https://platform.openai.com/docs/guides/structured-outputs).
required:
- name
required:
- type
- json_schema
ResponseFormatJsonSchemaSchema:
type: object
title: JSON schema
description: |
The schema for the response format, described as a JSON Schema object.
Learn how to build JSON schemas [here](https://json-schema.org/).
additionalProperties: true
ResponseFormatText:
type: object
title: Text
description: |
Default response format. Used to generate text responses.
properties:
type:
type: string
description: The type of response format being defined. Always `text`.
enum:
- text
x-stainless-const: true
required:
- type
ResponseFormatTextGrammar:
type: object
title: Text grammar
description: |
A custom grammar for the model to follow when generating text.
Learn more in the [custom grammars guide](https://platform.openai.com/docs/guides/custom-grammars).
properties:
type:
type: string
description: The type of response format being defined. Always `grammar`.
enum:
- grammar
x-stainless-const: true
grammar:
type: string
description: The custom grammar for the model to follow.
required:
- type
- grammar
ResponseFormatTextPython:
type: object
title: Python grammar
description: |
Configure the model to generate valid Python code. See the
[custom grammars guide](https://platform.openai.com/docs/guides/custom-grammars) for more details.
properties:
type:
type: string
description: The type of response format being defined. Always `python`.
enum:
- python
x-stainless-const: true
required:
- type
ResponseFunctionCallArgumentsDeltaEvent:
type: object
description: Emitted when there is a partial function-call arguments delta.
properties:
type:
type: string
description: |
The type of the event. Always `response.function_call_arguments.delta`.
enum:
- response.function_call_arguments.delta
x-stainless-const: true
item_id:
type: string
description: |
The ID of the output item that the function-call arguments delta is added to.
output_index:
type: integer
description: |
The index of the output item that the function-call arguments delta is added to.
sequence_number:
type: integer
description: The sequence number of this event.
delta:
type: string
description: |
The function-call arguments delta that is added.
required:
- type
- item_id
- output_index
- delta
- sequence_number
x-oaiMeta:
name: response.function_call_arguments.delta
group: responses
example: |
{
"type": "response.function_call_arguments.delta",
"item_id": "item-abc",
"output_index": 0,
"delta": "{ \"arg\":"
"sequence_number": 1
}
ResponseFunctionCallArgumentsDoneEvent:
type: object
description: Emitted when function-call arguments are finalized.
properties:
type:
type: string
enum:
- response.function_call_arguments.done
x-stainless-const: true
item_id:
type: string
description: The ID of the item.
output_index:
type: integer
description: The index of the output item.
sequence_number:
type: integer
description: The sequence number of this event.
arguments:
type: string
description: The function-call arguments.
required:
- type
- item_id
- output_index
- arguments
- sequence_number
x-oaiMeta:
name: response.function_call_arguments.done
group: responses
example: |
{
"type": "response.function_call_arguments.done",
"item_id": "item-abc",
"output_index": 1,
"arguments": "{ \"arg\": 123 }",
"sequence_number": 1
}
ResponseImageGenCallCompletedEvent:
type: object
title: ResponseImageGenCallCompletedEvent
description: |
Emitted when an image generation tool call has completed and the final image is available.
properties:
type:
type: string
enum:
- response.image_generation_call.completed
description: The type of the event. Always 'response.image_generation_call.completed'.
x-stainless-const: true
output_index:
type: integer
description: The index of the output item in the response's output array.
sequence_number:
type: integer
description: The sequence number of this event.
item_id:
type: string
description: The unique identifier of the image generation item being processed.
required:
- type
- output_index
- item_id
- sequence_number
x-oaiMeta:
name: response.image_generation_call.completed
group: responses
example: |
{
"type": "response.image_generation_call.completed",
"output_index": 0,
"item_id": "item-123",
"sequence_number": 1
}
ResponseImageGenCallGeneratingEvent:
type: object
title: ResponseImageGenCallGeneratingEvent
description: |
Emitted when an image generation tool call is actively generating an image (intermediate state).
properties:
type:
type: string
enum:
- response.image_generation_call.generating
description: The type of the event. Always 'response.image_generation_call.generating'.
x-stainless-const: true
output_index:
type: integer
description: The index of the output item in the response's output array.
item_id:
type: string
description: The unique identifier of the image generation item being processed.
sequence_number:
type: integer
description: The sequence number of the image generation item being processed.
required:
- type
- output_index
- item_id
- sequence_number
x-oaiMeta:
name: response.image_generation_call.generating
group: responses
example: |
{
"type": "response.image_generation_call.generating",
"output_index": 0,
"item_id": "item-123",
"sequence_number": 0
}
ResponseImageGenCallInProgressEvent:
type: object
title: ResponseImageGenCallInProgressEvent
description: |
Emitted when an image generation tool call is in progress.
properties:
type:
type: string
enum:
- response.image_generation_call.in_progress
description: The type of the event. Always 'response.image_generation_call.in_progress'.
x-stainless-const: true
output_index:
type: integer
description: The index of the output item in the response's output array.
item_id:
type: string
description: The unique identifier of the image generation item being processed.
sequence_number:
type: integer
description: The sequence number of the image generation item being processed.
required:
- type
- output_index
- item_id
- sequence_number
x-oaiMeta:
name: response.image_generation_call.in_progress
group: responses
example: |
{
"type": "response.image_generation_call.in_progress",
"output_index": 0,
"item_id": "item-123",
"sequence_number": 0
}
ResponseImageGenCallPartialImageEvent:
type: object
title: ResponseImageGenCallPartialImageEvent
description: |
Emitted when a partial image is available during image generation streaming.
properties:
type:
type: string
enum:
- response.image_generation_call.partial_image
description: The type of the event. Always 'response.image_generation_call.partial_image'.
x-stainless-const: true
output_index:
type: integer
description: The index of the output item in the response's output array.
item_id:
type: string
description: The unique identifier of the image generation item being processed.
sequence_number:
type: integer
description: The sequence number of the image generation item being processed.
partial_image_index:
type: integer
description: 0-based index for the partial image (backend is 1-based, but this is 0-based for the user).
partial_image_b64:
type: string
description: Base64-encoded partial image data, suitable for rendering as an image.
required:
- type
- output_index
- item_id
- sequence_number
- partial_image_index
- partial_image_b64
x-oaiMeta:
name: response.image_generation_call.partial_image
group: responses
example: |
{
"type": "response.image_generation_call.partial_image",
"output_index": 0,
"item_id": "item-123",
"sequence_number": 0,
"partial_image_index": 0,
"partial_image_b64": "..."
}
ResponseInProgressEvent:
type: object
description: Emitted when the response is in progress.
properties:
type:
type: string
description: |
The type of the event. Always `response.in_progress`.
enum:
- response.in_progress
x-stainless-const: true
response:
$ref: '#/components/schemas/Response'
description: |
The response that is in progress.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- response
- sequence_number
x-oaiMeta:
name: response.in_progress
group: responses
example: |
{
"type": "response.in_progress",
"response": {
"id": "resp_67ccfcdd16748190a91872c75d38539e09e4d4aac714747c",
"object": "response",
"created_at": 1741487325,
"status": "in_progress",
"error": null,
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4o-2024-08-06",
"output": [],
"parallel_tool_calls": true,
"previous_response_id": null,
"reasoning": {
"effort": null,
"summary": null
},
"store": true,
"temperature": 1,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [],
"top_p": 1,
"truncation": "disabled",
"usage": null,
"user": null,
"metadata": {}
},
"sequence_number": 1
}
ResponseIncompleteEvent:
type: object
description: |
An event that is emitted when a response finishes as incomplete.
properties:
type:
type: string
description: |
The type of the event. Always `response.incomplete`.
enum:
- response.incomplete
x-stainless-const: true
response:
$ref: '#/components/schemas/Response'
description: |
The response that was incomplete.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- response
- sequence_number
x-oaiMeta:
name: response.incomplete
group: responses
example: |
{
"type": "response.incomplete",
"response": {
"id": "resp_123",
"object": "response",
"created_at": 1740855869,
"status": "incomplete",
"error": null,
"incomplete_details": {
"reason": "max_tokens"
},
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4o-mini-2024-07-18",
"output": [],
"previous_response_id": null,
"reasoning_effort": null,
"store": false,
"temperature": 1,
"text": {
"format": {
"type": "text"
}
},
"tool_choice": "auto",
"tools": [],
"top_p": 1,
"truncation": "disabled",
"usage": null,
"user": null,
"metadata": {}
},
"sequence_number": 1
}
ResponseItemList:
type: object
description: A list of Response items.
properties:
object:
description: The type of object returned, must be `list`.
x-stainless-const: true
const: list
data:
type: array
description: A list of items used to generate this response.
items:
$ref: '#/components/schemas/ItemResource'
has_more:
type: boolean
description: Whether there are more items available.
first_id:
type: string
description: The ID of the first item in the list.
last_id:
type: string
description: The ID of the last item in the list.
required:
- object
- data
- has_more
- first_id
- last_id
x-oaiMeta:
name: The input item list
group: responses
example: |
{
"object": "list",
"data": [
{
"id": "msg_abc123",
"type": "message",
"role": "user",
"content": [
{
"type": "input_text",
"text": "Tell me a three sentence bedtime story about a unicorn."
}
]
}
],
"first_id": "msg_abc123",
"last_id": "msg_abc123",
"has_more": false
}
ResponseLogProb:
type: object
description: |
A logprob is the logarithmic probability that the model assigns to producing
a particular token at a given position in the sequence. Less-negative (higher)
logprob values indicate greater model confidence in that token choice.
properties:
token:
description: A possible text token.
type: string
logprob:
description: |
The log probability of this token.
type: number
top_logprobs:
description: |
The log probability of the top 20 most likely tokens.
type: array
items:
type: object
properties:
token:
description: A possible text token.
type: string
logprob:
description: The log probability of this token.
type: number
required:
- token
- logprob
ResponseMCPCallArgumentsDeltaEvent:
type: object
title: ResponseMCPCallArgumentsDeltaEvent
description: |
Emitted when there is a delta (partial update) to the arguments of an MCP tool call.
properties:
type:
type: string
enum:
- response.mcp_call_arguments.delta
description: The type of the event. Always 'response.mcp_call_arguments.delta'.
x-stainless-const: true
output_index:
type: integer
description: The index of the output item in the response's output array.
item_id:
type: string
description: The unique identifier of the MCP tool call item being processed.
delta:
type: string
description: |
A JSON string containing the partial update to the arguments for the MCP tool call.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- output_index
- item_id
- delta
- sequence_number
x-oaiMeta:
name: response.mcp_call_arguments.delta
group: responses
example: |
{
"type": "response.mcp_call_arguments.delta",
"output_index": 0,
"item_id": "item-abc",
"delta": "{",
"sequence_number": 1
}
ResponseMCPCallArgumentsDoneEvent:
type: object
title: ResponseMCPCallArgumentsDoneEvent
description: |
Emitted when the arguments for an MCP tool call are finalized.
properties:
type:
type: string
enum:
- response.mcp_call_arguments.done
description: The type of the event. Always 'response.mcp_call_arguments.done'.
x-stainless-const: true
output_index:
type: integer
description: The index of the output item in the response's output array.
item_id:
type: string
description: The unique identifier of the MCP tool call item being processed.
arguments:
type: string
description: |
A JSON string containing the finalized arguments for the MCP tool call.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- output_index
- item_id
- arguments
- sequence_number
x-oaiMeta:
name: response.mcp_call_arguments.done
group: responses
example: |
{
"type": "response.mcp_call_arguments.done",
"output_index": 0,
"item_id": "item-abc",
"arguments": "{\"arg1\": \"value1\", \"arg2\": \"value2\"}",
"sequence_number": 1
}
ResponseMCPCallCompletedEvent:
type: object
title: ResponseMCPCallCompletedEvent
description: |
Emitted when an MCP tool call has completed successfully.
properties:
type:
type: string
enum:
- response.mcp_call.completed
description: The type of the event. Always 'response.mcp_call.completed'.
x-stainless-const: true
item_id:
type: string
description: The ID of the MCP tool call item that completed.
output_index:
type: integer
description: The index of the output item that completed.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- item_id
- output_index
- sequence_number
x-oaiMeta:
name: response.mcp_call.completed
group: responses
example: |
{
"type": "response.mcp_call.completed",
"sequence_number": 1,
"item_id": "mcp_682d437d90a88191bf88cd03aae0c3e503937d5f622d7a90",
"output_index": 0
}
ResponseMCPCallFailedEvent:
type: object
title: ResponseMCPCallFailedEvent
description: |
Emitted when an MCP tool call has failed.
properties:
type:
type: string
enum:
- response.mcp_call.failed
description: The type of the event. Always 'response.mcp_call.failed'.
x-stainless-const: true
item_id:
type: string
description: The ID of the MCP tool call item that failed.
output_index:
type: integer
description: The index of the output item that failed.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- item_id
- output_index
- sequence_number
x-oaiMeta:
name: response.mcp_call.failed
group: responses
example: |
{
"type": "response.mcp_call.failed",
"sequence_number": 1,
"item_id": "mcp_682d437d90a88191bf88cd03aae0c3e503937d5f622d7a90",
"output_index": 0
}
ResponseMCPCallInProgressEvent:
type: object
title: ResponseMCPCallInProgressEvent
description: |
Emitted when an MCP tool call is in progress.
properties:
type:
type: string
enum:
- response.mcp_call.in_progress
description: The type of the event. Always 'response.mcp_call.in_progress'.
x-stainless-const: true
sequence_number:
type: integer
description: The sequence number of this event.
output_index:
type: integer
description: The index of the output item in the response's output array.
item_id:
type: string
description: The unique identifier of the MCP tool call item being processed.
required:
- type
- output_index
- item_id
- sequence_number
x-oaiMeta:
name: response.mcp_call.in_progress
group: responses
example: |
{
"type": "response.mcp_call.in_progress",
"sequence_number": 1,
"output_index": 0,
"item_id": "mcp_682d437d90a88191bf88cd03aae0c3e503937d5f622d7a90"
}
ResponseMCPListToolsCompletedEvent:
type: object
title: ResponseMCPListToolsCompletedEvent
description: |
Emitted when the list of available MCP tools has been successfully retrieved.
properties:
type:
type: string
enum:
- response.mcp_list_tools.completed
description: The type of the event. Always 'response.mcp_list_tools.completed'.
x-stainless-const: true
item_id:
type: string
description: The ID of the MCP tool call item that produced this output.
output_index:
type: integer
description: The index of the output item that was processed.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- item_id
- output_index
- sequence_number
x-oaiMeta:
name: response.mcp_list_tools.completed
group: responses
example: |
{
"type": "response.mcp_list_tools.completed",
"sequence_number": 1,
"output_index": 0,
"item_id": "mcpl_682d4379df088191886b70f4ec39f90403937d5f622d7a90"
}
ResponseMCPListToolsFailedEvent:
type: object
title: ResponseMCPListToolsFailedEvent
description: |
Emitted when the attempt to list available MCP tools has failed.
properties:
type:
type: string
enum:
- response.mcp_list_tools.failed
description: The type of the event. Always 'response.mcp_list_tools.failed'.
x-stainless-const: true
item_id:
type: string
description: The ID of the MCP tool call item that failed.
output_index:
type: integer
description: The index of the output item that failed.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- item_id
- output_index
- sequence_number
x-oaiMeta:
name: response.mcp_list_tools.failed
group: responses
example: |
{
"type": "response.mcp_list_tools.failed",
"sequence_number": 1,
"output_index": 0,
"item_id": "mcpl_682d4379df088191886b70f4ec39f90403937d5f622d7a90"
}
ResponseMCPListToolsInProgressEvent:
type: object
title: ResponseMCPListToolsInProgressEvent
description: |
Emitted when the system is in the process of retrieving the list of available MCP tools.
properties:
type:
type: string
enum:
- response.mcp_list_tools.in_progress
description: The type of the event. Always 'response.mcp_list_tools.in_progress'.
x-stainless-const: true
item_id:
type: string
description: The ID of the MCP tool call item that is being processed.
output_index:
type: integer
description: The index of the output item that is being processed.
sequence_number:
type: integer
description: The sequence number of this event.
required:
- type
- item_id
- output_index
- sequence_number
x-oaiMeta:
name: response.mcp_list_tools.in_progress
group: responses
example: |
{
"type": "response.mcp_list_tools.in_progress",
"sequence_number": 1,
"output_index": 0,
"item_id": "mcpl_682d4379df088191886b70f4ec39f90403937d5f622d7a90"
}
ResponseModalities:
type: array
nullable: true
description: |
Output types that you would like the model to generate.
Most models are capable of generating text, which is the default:
`["text"]`
The `gpt-4o-audio-preview` model can also be used to
[generate audio](https://platform.openai.com/docs/guides/audio). To request that this model generate
both text and audio responses, you can use:
`["text", "audio"]`
items:
type: string
enum:
- text
- audio
ResponseOutputItemAddedEvent:
type: object
description: Emitted when a new output item is added.
properties:
type:
type: string
description: |
The type of the event. Always `response.output_item.added`.
enum:
- response.output_item.added
x-stainless-const: true
output_index:
type: integer
description: |
The index of the output item that was added.
sequence_number:
type: integer
description: |
The sequence number of this event.
item:
$ref: '#/components/schemas/OutputItem'
description: |
The output item that was added.
required:
- type
- output_index
- item
- sequence_number
x-oaiMeta:
name: response.output_item.added
group: responses
example: |
{
"type": "response.output_item.added",
"output_index": 0,
"item": {
"id": "msg_123",
"status": "in_progress",
"type": "message",
"role": "assistant",
"content": []
},
"sequence_number": 1
}
ResponseOutputItemDoneEvent:
type: object
description: Emitted when an output item is marked done.
properties:
type:
type: string
description: |
The type of the event. Always `response.output_item.done`.
enum:
- response.output_item.done
x-stainless-const: true
output_index:
type: integer
description: |
The index of the output item that was marked done.
sequence_number:
type: integer
description: |
The sequence number of this event.
item:
$ref: '#/components/schemas/OutputItem'
description: |
The output item that was marked done.
required:
- type
- output_index
- item
- sequence_number
x-oaiMeta:
name: response.output_item.done
group: responses
example: |
{
"type": "response.output_item.done",
"output_index": 0,
"item": {
"id": "msg_123",
"status": "completed",
"type": "message",
"role": "assistant",
"content": [
{
"type": "output_text",
"text": "In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.",
"annotations": []
}
]
},
"sequence_number": 1
}
ResponseOutputTextAnnotationAddedEvent:
type: object
title: ResponseOutputTextAnnotationAddedEvent
description: |
Emitted when an annotation is added to output text content.
properties:
type:
type: string
enum:
- response.output_text.annotation.added
description: The type of the event. Always 'response.output_text.annotation.added'.
x-stainless-const: true
item_id:
type: string
description: The unique identifier of the item to which the annotation is being added.
output_index:
type: integer
description: The index of the output item in the response's output array.
content_index:
type: integer
description: The index of the content part within the output item.
annotation_index:
type: integer
description: The index of the annotation within the content part.
sequence_number:
type: integer
description: The sequence number of this event.
annotation:
type: object
description: The annotation object being added. (See annotation schema for details.)
required:
- type
- item_id
- output_index
- content_index
- annotation_index
- annotation
- sequence_number
x-oaiMeta:
name: response.output_text.annotation.added
group: responses
example: |
{
"type": "response.output_text.annotation.added",
"item_id": "item-abc",
"output_index": 0,
"content_index": 0,
"annotation_index": 0,
"annotation": {
"type": "text_annotation",
"text": "This is a test annotation",
"start": 0,
"end": 10
},
"sequence_number": 1
}
ResponsePromptVariables:
type: object
title: Prompt Variables
description: |
Optional map of values to substitute in for variables in your
prompt. The substitution values can either be strings, or other
Response input types like images or files.
x-oaiExpandable: true
x-oaiTypeLabel: map
nullable: true
additionalProperties:
x-oaiExpandable: true
x-oaiTypeLabel: map
anyOf:
- type: string
- $ref: '#/components/schemas/InputTextContent'
- $ref: '#/components/schemas/InputImageContent'
- $ref: '#/components/schemas/InputFileContent'
ResponseProperties:
type: object
properties:
previous_response_id:
type: string
description: >
The unique ID of the previous response to the model. Use this to
create multi-turn conversations. Learn more about
[conversation state](https://platform.openai.com/docs/guides/conversation-state). Cannot be used
in conjunction with `conversation`.
nullable: true
model:
description: >
Model ID used to generate the response, like `gpt-4o` or `o3`. OpenAI
offers a wide range of models with different capabilities, performance
characteristics, and price points. Refer to the [model
guide](https://platform.openai.com/docs/models)
to browse and compare available models.
$ref: '#/components/schemas/ModelIdsResponses'
reasoning:
$ref: '#/components/schemas/Reasoning'
nullable: true
background:
type: boolean
description: |
Whether to run the model response in the background.
[Learn more](https://platform.openai.com/docs/guides/background).
default: false
nullable: true
max_output_tokens:
description: >
An upper bound for the number of tokens that can be generated for a response, including visible
output tokens and [reasoning tokens](https://platform.openai.com/docs/guides/reasoning).
type: integer
nullable: true
max_tool_calls:
description: >
The maximum number of total calls to built-in tools that can be processed in a response. This
maximum number applies across all built-in tool calls, not per individual tool. Any further
attempts to call a tool by the model will be ignored.
type: integer
nullable: true
text:
type: object
description: |
Configuration options for a text response from the model. Can be plain
text or structured JSON data. Learn more:
- [Text inputs and outputs](https://platform.openai.com/docs/guides/text)
- [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs)
properties:
format:
$ref: '#/components/schemas/TextResponseFormatConfiguration'
verbosity:
$ref: '#/components/schemas/Verbosity'
tools:
type: array
description: |
An array of tools the model may call while generating a response. You
can specify which tool to use by setting the `tool_choice` parameter.
The two categories of tools you can provide the model are:
- **Built-in tools**: Tools that are provided by OpenAI that extend the
model's capabilities, like [web search](https://platform.openai.com/docs/guides/tools-web-search)
or [file search](https://platform.openai.com/docs/guides/tools-file-search). Learn more about
[built-in tools](https://platform.openai.com/docs/guides/tools).
- **Function calls (custom tools)**: Functions that are defined by you,
enabling the model to call your own code with strongly typed arguments
and outputs. Learn more about
[function calling](https://platform.openai.com/docs/guides/function-calling). You can also use
custom tools to call your own code.
items:
$ref: '#/components/schemas/Tool'
tool_choice:
description: |
How the model should select which tool (or tools) to use when generating
a response. See the `tools` parameter to see how to specify which tools
the model can call.
anyOf:
- $ref: '#/components/schemas/ToolChoiceOptions'
- $ref: '#/components/schemas/ToolChoiceAllowed'
- $ref: '#/components/schemas/ToolChoiceTypes'
- $ref: '#/components/schemas/ToolChoiceFunction'
- $ref: '#/components/schemas/ToolChoiceMCP'
- $ref: '#/components/schemas/ToolChoiceCustom'
prompt:
$ref: '#/components/schemas/Prompt'
truncation:
type: string
description: |
The truncation strategy to use for the model response.
- `auto`: If the context of this response and previous ones exceeds
the model's context window size, the model will truncate the
response to fit the context window by dropping input items in the
middle of the conversation.
- `disabled` (default): If a model response will exceed the context window
size for a model, the request will fail with a 400 error.
enum:
- auto
- disabled
nullable: true
default: disabled
ResponseQueuedEvent:
type: object
title: ResponseQueuedEvent
description: |
Emitted when a response is queued and waiting to be processed.
properties:
type:
type: string
enum:
- response.queued
description: The type of the event. Always 'response.queued'.
x-stainless-const: true
response:
$ref: '#/components/schemas/Response'
description: The full response object that is queued.
sequence_number:
type: integer
description: The sequence number for this event.
required:
- type
- response
- sequence_number
x-oaiMeta:
name: response.queued
group: responses
example: |
{
"type": "response.queued",
"response": {
"id": "res_123",
"status": "queued",
"created_at": "2021-01-01T00:00:00Z",
"updated_at": "2021-01-01T00:00:00Z"
},
"sequence_number": 1
}
ResponseReasoningSummaryPartAddedEvent:
type: object
description: Emitted when a new reasoning summary part is added.
properties:
type:
type: string
description: |
The type of the event. Always `response.reasoning_summary_part.added`.
enum:
- response.reasoning_summary_part.added
x-stainless-const: true
item_id:
type: string
description: |
The ID of the item this summary part is associated with.
output_index:
type: integer
description: |
The index of the output item this summary part is associated with.
summary_index:
type: integer
description: |
The index of the summary part within the reasoning summary.
sequence_number:
type: integer
description: |
The sequence number of this event.
part:
type: object
description: |
The summary part that was added.
properties:
type:
type: string
description: The type of the summary part. Always `summary_text`.
enum:
- summary_text
x-stainless-const: true
text:
type: string
description: The text of the summary part.
required:
- type
- text
required:
- type
- item_id
- output_index
- summary_index
- part
- sequence_number
x-oaiMeta:
name: response.reasoning_summary_part.added
group: responses
example: |
{
"type": "response.reasoning_summary_part.added",
"item_id": "rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476",
"output_index": 0,
"summary_index": 0,
"part": {
"type": "summary_text",
"text": ""
},
"sequence_number": 1
}
ResponseReasoningSummaryPartDoneEvent:
type: object
description: Emitted when a reasoning summary part is completed.
properties:
type:
type: string
description: |
The type of the event. Always `response.reasoning_summary_part.done`.
enum:
- response.reasoning_summary_part.done
x-stainless-const: true
item_id:
type: string
description: |
The ID of the item this summary part is associated with.
output_index:
type: integer
description: |
The index of the output item this summary part is associated with.
summary_index:
type: integer
description: |
The index of the summary part within the reasoning summary.
sequence_number:
type: integer
description: |
The sequence number of this event.
part:
type: object
description: |
The completed summary part.
properties:
type:
type: string
description: The type of the summary part. Always `summary_text`.
enum:
- summary_text
x-stainless-const: true
text:
type: string
description: The text of the summary part.
required:
- type
- text
required:
- type
- item_id
- output_index
- summary_index
- part
- sequence_number
x-oaiMeta:
name: response.reasoning_summary_part.done
group: responses
example: |
{
"type": "response.reasoning_summary_part.done",
"item_id": "rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476",
"output_index": 0,
"summary_index": 0,
"part": {
"type": "summary_text",
"text": "**Responding to a greeting**\n\nThe user just said, \"Hello!\" So, it seems I need to engage. I'll greet them back and offer help since they're looking to chat. I could say something like, \"Hello! How can I assist you today?\" That feels friendly and open. They didn't ask a specific question, so this approach will work well for starting a conversation. Let's see where it goes from there!"
},
"sequence_number": 1
}
ResponseReasoningSummaryTextDeltaEvent:
type: object
description: Emitted when a delta is added to a reasoning summary text.
properties:
type:
type: string
description: |
The type of the event. Always `response.reasoning_summary_text.delta`.
enum:
- response.reasoning_summary_text.delta
x-stainless-const: true
item_id:
type: string
description: |
The ID of the item this summary text delta is associated with.
output_index:
type: integer
description: |
The index of the output item this summary text delta is associated with.
summary_index:
type: integer
description: |
The index of the summary part within the reasoning summary.
delta:
type: string
description: |
The text delta that was added to the summary.
sequence_number:
type: integer
description: |
The sequence number of this event.
required:
- type
- item_id
- output_index
- summary_index
- delta
- sequence_number
x-oaiMeta:
name: response.reasoning_summary_text.delta
group: responses
example: |
{
"type": "response.reasoning_summary_text.delta",
"item_id": "rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476",
"output_index": 0,
"summary_index": 0,
"delta": "**Responding to a greeting**\n\nThe user just said, \"Hello!\" So, it seems I need to engage. I'll greet them back and offer help since they're looking to chat. I could say something like, \"Hello! How can I assist you today?\" That feels friendly and open. They didn't ask a specific question, so this approach will work well for starting a conversation. Let's see where it goes from there!",
"sequence_number": 1
}
ResponseReasoningSummaryTextDoneEvent:
type: object
description: Emitted when a reasoning summary text is completed.
properties:
type:
type: string
description: |
The type of the event. Always `response.reasoning_summary_text.done`.
enum:
- response.reasoning_summary_text.done
x-stainless-const: true
item_id:
type: string
description: |
The ID of the item this summary text is associated with.
output_index:
type: integer
description: |
The index of the output item this summary text is associated with.
summary_index:
type: integer
description: |
The index of the summary part within the reasoning summary.
text:
type: string
description: |
The full text of the completed reasoning summary.
sequence_number:
type: integer
description: |
The sequence number of this event.
required:
- type
- item_id
- output_index
- summary_index
- text
- sequence_number
x-oaiMeta:
name: response.reasoning_summary_text.done
group: responses
example: |
{
"type": "response.reasoning_summary_text.done",
"item_id": "rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476",
"output_index": 0,
"summary_index": 0,
"text": "**Responding to a greeting**\n\nThe user just said, \"Hello!\" So, it seems I need to engage. I'll greet them back and offer help since they're looking to chat. I could say something like, \"Hello! How can I assist you today?\" That feels friendly and open. They didn't ask a specific question, so this approach will work well for starting a conversation. Let's see where it goes from there!",
"sequence_number": 1
}
ResponseReasoningTextDeltaEvent:
type: object
description: Emitted when a delta is added to a reasoning text.
properties:
type:
type: string
description: |
The type of the event. Always `response.reasoning_text.delta`.
enum:
- response.reasoning_text.delta
x-stainless-const: true
item_id:
type: string
description: |
The ID of the item this reasoning text delta is associated with.
output_index:
type: integer
description: |
The index of the output item this reasoning text delta is associated with.
content_index:
type: integer
description: |
The index of the reasoning content part this delta is associated with.
delta:
type: string
description: |
The text delta that was added to the reasoning content.
sequence_number:
type: integer
description: |
The sequence number of this event.
required:
- type
- item_id
- output_index
- content_index
- delta
- sequence_number
x-oaiMeta:
name: response.reasoning_text.delta
group: responses
example: |
{
"type": "response.reasoning_text.delta",
"item_id": "rs_123",
"output_index": 0,
"content_index": 0,
"delta": "The",
"sequence_number": 1
}
ResponseReasoningTextDoneEvent:
type: object
description: Emitted when a reasoning text is completed.
properties:
type:
type: string
description: |
The type of the event. Always `response.reasoning_text.done`.
enum:
- response.reasoning_text.done
x-stainless-const: true
item_id:
type: string
description: |
The ID of the item this reasoning text is associated with.
output_index:
type: integer
description: |
The index of the output item this reasoning text is associated with.
content_index:
type: integer
description: |
The index of the reasoning content part.
text:
type: string
description: |
The full text of the completed reasoning content.
sequence_number:
type: integer
description: |
The sequence number of this event.
required:
- type
- item_id
- output_index
- content_index
- text
- sequence_number
x-oaiMeta:
name: response.reasoning_text.done
group: responses
example: |
{
"type": "response.reasoning_text.done",
"item_id": "rs_123",
"output_index": 0,
"content_index": 0,
"text": "The user is asking...",
"sequence_number": 4
}
ResponseRefusalDeltaEvent:
type: object
description: Emitted when there is a partial refusal text.
properties:
type:
type: string
description: |
The type of the event. Always `response.refusal.delta`.
enum:
- response.refusal.delta
x-stainless-const: true
item_id:
type: string
description: |
The ID of the output item that the refusal text is added to.
output_index:
type: integer
description: |
The index of the output item that the refusal text is added to.
content_index:
type: integer
description: |
The index of the content part that the refusal text is added to.
delta:
type: string
description: |
The refusal text that is added.
sequence_number:
type: integer
description: |
The sequence number of this event.
required:
- type
- item_id
- output_index
- content_index
- delta
- sequence_number
x-oaiMeta:
name: response.refusal.delta
group: responses
example: |
{
"type": "response.refusal.delta",
"item_id": "msg_123",
"output_index": 0,
"content_index": 0,
"delta": "refusal text so far",
"sequence_number": 1
}
ResponseRefusalDoneEvent:
type: object
description: Emitted when refusal text is finalized.
properties:
type:
type: string
description: |
The type of the event. Always `response.refusal.done`.
enum:
- response.refusal.done
x-stainless-const: true
item_id:
type: string
description: |
The ID of the output item that the refusal text is finalized.
output_index:
type: integer
description: |
The index of the output item that the refusal text is finalized.
content_index:
type: integer
description: |
The index of the content part that the refusal text is finalized.
refusal:
type: string
description: |
The refusal text that is finalized.
sequence_number:
type: integer
description: |
The sequence number of this event.
required:
- type
- item_id
- output_index
- content_index
- refusal
- sequence_number
x-oaiMeta:
name: response.refusal.done
group: responses
example: |
{
"type": "response.refusal.done",
"item_id": "item-abc",
"output_index": 1,
"content_index": 2,
"refusal": "final refusal text",
"sequence_number": 1
}
ResponseStreamEvent:
anyOf:
- $ref: '#/components/schemas/ResponseAudioDeltaEvent'
- $ref: '#/components/schemas/ResponseAudioDoneEvent'
- $ref: '#/components/schemas/ResponseAudioTranscriptDeltaEvent'
- $ref: '#/components/schemas/ResponseAudioTranscriptDoneEvent'
- $ref: '#/components/schemas/ResponseCodeInterpreterCallCodeDeltaEvent'
- $ref: '#/components/schemas/ResponseCodeInterpreterCallCodeDoneEvent'
- $ref: '#/components/schemas/ResponseCodeInterpreterCallCompletedEvent'
- $ref: '#/components/schemas/ResponseCodeInterpreterCallInProgressEvent'
- $ref: '#/components/schemas/ResponseCodeInterpreterCallInterpretingEvent'
- $ref: '#/components/schemas/ResponseCompletedEvent'
- $ref: '#/components/schemas/ResponseContentPartAddedEvent'
- $ref: '#/components/schemas/ResponseContentPartDoneEvent'
- $ref: '#/components/schemas/ResponseCreatedEvent'
- $ref: '#/components/schemas/ResponseErrorEvent'
- $ref: '#/components/schemas/ResponseFileSearchCallCompletedEvent'
- $ref: '#/components/schemas/ResponseFileSearchCallInProgressEvent'
- $ref: '#/components/schemas/ResponseFileSearchCallSearchingEvent'
- $ref: '#/components/schemas/ResponseFunctionCallArgumentsDeltaEvent'
- $ref: '#/components/schemas/ResponseFunctionCallArgumentsDoneEvent'
- $ref: '#/components/schemas/ResponseInProgressEvent'
- $ref: '#/components/schemas/ResponseFailedEvent'
- $ref: '#/components/schemas/ResponseIncompleteEvent'
- $ref: '#/components/schemas/ResponseOutputItemAddedEvent'
- $ref: '#/components/schemas/ResponseOutputItemDoneEvent'
- $ref: '#/components/schemas/ResponseReasoningSummaryPartAddedEvent'
- $ref: '#/components/schemas/ResponseReasoningSummaryPartDoneEvent'
- $ref: '#/components/schemas/ResponseReasoningSummaryTextDeltaEvent'
- $ref: '#/components/schemas/ResponseReasoningSummaryTextDoneEvent'
- $ref: '#/components/schemas/ResponseReasoningTextDeltaEvent'
- $ref: '#/components/schemas/ResponseReasoningTextDoneEvent'
- $ref: '#/components/schemas/ResponseRefusalDeltaEvent'
- $ref: '#/components/schemas/ResponseRefusalDoneEvent'
- $ref: '#/components/schemas/ResponseTextDeltaEvent'
- $ref: '#/components/schemas/ResponseTextDoneEvent'
- $ref: '#/components/schemas/ResponseWebSearchCallCompletedEvent'
- $ref: '#/components/schemas/ResponseWebSearchCallInProgressEvent'
- $ref: '#/components/schemas/ResponseWebSearchCallSearchingEvent'
- $ref: '#/components/schemas/ResponseImageGenCallCompletedEvent'
- $ref: '#/components/schemas/ResponseImageGenCallGeneratingEvent'
- $ref: '#/components/schemas/ResponseImageGenCallInProgressEvent'
- $ref: '#/components/schemas/ResponseImageGenCallPartialImageEvent'
- $ref: '#/components/schemas/ResponseMCPCallArgumentsDeltaEvent'
- $ref: '#/components/schemas/ResponseMCPCallArgumentsDoneEvent'
- $ref: '#/components/schemas/ResponseMCPCallCompletedEvent'
- $ref: '#/components/schemas/ResponseMCPCallFailedEvent'
- $ref: '#/components/schemas/ResponseMCPCallInProgressEvent'
- $ref: '#/components/schemas/ResponseMCPListToolsCompletedEvent'
- $ref: '#/components/schemas/ResponseMCPListToolsFailedEvent'
- $ref: '#/components/schemas/ResponseMCPListToolsInProgressEvent'
- $ref: '#/components/schemas/ResponseOutputTextAnnotationAddedEvent'
- $ref: '#/components/schemas/ResponseQueuedEvent'
- $ref: '#/components/schemas/ResponseCustomToolCallInputDeltaEvent'
- $ref: '#/components/schemas/ResponseCustomToolCallInputDoneEvent'
discriminator:
propertyName: type
ResponseStreamOptions:
description: |
Options for streaming responses. Only set this when you set `stream: true`.
type: object
nullable: true
default: null
properties:
include_obfuscation:
type: boolean
description: |
When true, stream obfuscation will be enabled. Stream obfuscation adds
random characters to an `obfuscation` field on streaming delta events to
normalize payload sizes as a mitigation to certain side-channel attacks.
These obfuscation fields are included by default, but add a small amount
of overhead to the data stream. You can set `include_obfuscation` to
false to optimize for bandwidth if you trust the network links between
your application and the OpenAI API.
ResponseTextDeltaEvent:
type: object
description: Emitted when there is an additional text delta.
properties:
type:
type: string
description: |
The type of the event. Always `response.output_text.delta`.
enum:
- response.output_text.delta
x-stainless-const: true
item_id:
type: string
description: |
The ID of the output item that the text delta was added to.
output_index:
type: integer
description: |
The index of the output item that the text delta was added to.
content_index:
type: integer
description: |
The index of the content part that the text delta was added to.
delta:
type: string
description: |
The text delta that was added.
sequence_number:
type: integer
description: The sequence number for this event.
logprobs:
type: array
description: |
The log probabilities of the tokens in the delta.
items:
$ref: '#/components/schemas/ResponseLogProb'
required:
- type
- item_id
- output_index
- content_index
- delta
- sequence_number
- logprobs
x-oaiMeta:
name: response.output_text.delta
group: responses
example: |
{
"type": "response.output_text.delta",
"item_id": "msg_123",
"output_index": 0,
"content_index": 0,
"delta": "In",
"sequence_number": 1
}
ResponseTextDoneEvent:
type: object
description: Emitted when text content is finalized.
properties:
type:
type: string
description: |
The type of the event. Always `response.output_text.done`.
enum:
- response.output_text.done
x-stainless-const: true
item_id:
type: string
description: |
The ID of the output item that the text content is finalized.
output_index:
type: integer
description: |
The index of the output item that the text content is finalized.
content_index:
type: integer
description: |
The index of the content part that the text content is finalized.
text:
type: string
description: |
The text content that is finalized.
sequence_number:
type: integer
description: The sequence number for this event.
logprobs:
type: array
description: |
The log probabilities of the tokens in the delta.
items:
$ref: '#/components/schemas/ResponseLogProb'
required:
- type
- item_id
- output_index
- content_index
- text
- sequence_number
- logprobs
x-oaiMeta:
name: response.output_text.done
group: responses
example: |
{
"type": "response.output_text.done",
"item_id": "msg_123",
"output_index": 0,
"content_index": 0,
"text": "In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.",
"sequence_number": 1
}
ResponseUsage:
type: object
description: |
Represents token usage details including input tokens, output tokens,
a breakdown of output tokens, and the total tokens used.
properties:
input_tokens:
type: integer
description: The number of input tokens.
input_tokens_details:
type: object
description: A detailed breakdown of the input tokens.
properties:
cached_tokens:
type: integer
description: |
The number of tokens that were retrieved from the cache.
[More on prompt caching](https://platform.openai.com/docs/guides/prompt-caching).
required:
- cached_tokens
output_tokens:
type: integer
description: The number of output tokens.
output_tokens_details:
type: object
description: A detailed breakdown of the output tokens.
properties:
reasoning_tokens:
type: integer
description: The number of reasoning tokens.
required:
- reasoning_tokens
total_tokens:
type: integer
description: The total number of tokens used.
required:
- input_tokens
- input_tokens_details
- output_tokens
- output_tokens_details
- total_tokens
ResponseWebSearchCallCompletedEvent:
type: object
description: Emitted when a web search call is completed.
properties:
type:
type: string
description: |
The type of the event. Always `response.web_search_call.completed`.
enum:
- response.web_search_call.completed
x-stainless-const: true
output_index:
type: integer
description: |
The index of the output item that the web search call is associated with.
item_id:
type: string
description: |
Unique ID for the output item associated with the web search call.
sequence_number:
type: integer
description: The sequence number of the web search call being processed.
required:
- type
- output_index
- item_id
- sequence_number
x-oaiMeta:
name: response.web_search_call.completed
group: responses
example: |
{
"type": "response.web_search_call.completed",
"output_index": 0,
"item_id": "ws_123",
"sequence_number": 0
}
ResponseWebSearchCallInProgressEvent:
type: object
description: Emitted when a web search call is initiated.
properties:
type:
type: string
description: |
The type of the event. Always `response.web_search_call.in_progress`.
enum:
- response.web_search_call.in_progress
x-stainless-const: true
output_index:
type: integer
description: |
The index of the output item that the web search call is associated with.
item_id:
type: string
description: |
Unique ID for the output item associated with the web search call.
sequence_number:
type: integer
description: The sequence number of the web search call being processed.
required:
- type
- output_index
- item_id
- sequence_number
x-oaiMeta:
name: response.web_search_call.in_progress
group: responses
example: |
{
"type": "response.web_search_call.in_progress",
"output_index": 0,
"item_id": "ws_123",
"sequence_number": 0
}
ResponseWebSearchCallSearchingEvent:
type: object
description: Emitted when a web search call is executing.
properties:
type:
type: string
description: |
The type of the event. Always `response.web_search_call.searching`.
enum:
- response.web_search_call.searching
x-stainless-const: true
output_index:
type: integer
description: |
The index of the output item that the web search call is associated with.
item_id:
type: string
description: |
Unique ID for the output item associated with the web search call.
sequence_number:
type: integer
description: The sequence number of the web search call being processed.
required:
- type
- output_index
- item_id
- sequence_number
x-oaiMeta:
name: response.web_search_call.searching
group: responses
example: |
{
"type": "response.web_search_call.searching",
"output_index": 0,
"item_id": "ws_123",
"sequence_number": 0
}
RunCompletionUsage:
type: object
description: >-
Usage statistics related to the run. This value will be `null` if the run is not in a terminal state
(i.e. `in_progress`, `queued`, etc.).
properties:
completion_tokens:
type: integer
description: Number of completion tokens used over the course of the run.
prompt_tokens:
type: integer
description: Number of prompt tokens used over the course of the run.
total_tokens:
type: integer
description: Total number of tokens used (prompt + completion).
required:
- prompt_tokens
- completion_tokens
- total_tokens
nullable: true
RunGraderRequest:
type: object
title: RunGraderRequest
properties:
grader:
type: object
description: The grader used for the fine-tuning job.
anyOf:
- $ref: '#/components/schemas/GraderStringCheck'
- $ref: '#/components/schemas/GraderTextSimilarity'
- $ref: '#/components/schemas/GraderPython'
- $ref: '#/components/schemas/GraderScoreModel'
- $ref: '#/components/schemas/GraderMulti'
discriminator:
propertyName: type
item:
type: object
description: >
The dataset item provided to the grader. This will be used to populate
the `item` namespace. See [the guide](https://platform.openai.com/docs/guides/graders) for more
details.
model_sample:
type: string
description: >
The model sample to be evaluated. This value will be used to populate
the `sample` namespace. See [the guide](https://platform.openai.com/docs/guides/graders) for more
details.
The `output_json` variable will be populated if the model sample is a
valid JSON string.
required:
- grader
- model_sample
RunGraderResponse:
type: object
properties:
reward:
type: number
metadata:
type: object
properties:
name:
type: string
type:
type: string
errors:
type: object
properties:
formula_parse_error:
type: boolean
sample_parse_error:
type: boolean
truncated_observation_error:
type: boolean
unresponsive_reward_error:
type: boolean
invalid_variable_error:
type: boolean
other_error:
type: boolean
python_grader_server_error:
type: boolean
python_grader_server_error_type:
type: string
nullable: true
python_grader_runtime_error:
type: boolean
python_grader_runtime_error_details:
type: string
nullable: true
model_grader_server_error:
type: boolean
model_grader_refusal_error:
type: boolean
model_grader_parse_error:
type: boolean
model_grader_server_error_details:
type: string
nullable: true
required:
- formula_parse_error
- sample_parse_error
- truncated_observation_error
- unresponsive_reward_error
- invalid_variable_error
- other_error
- python_grader_server_error
- python_grader_server_error_type
- python_grader_runtime_error
- python_grader_runtime_error_details
- model_grader_server_error
- model_grader_refusal_error
- model_grader_parse_error
- model_grader_server_error_details
execution_time:
type: number
scores:
type: object
additionalProperties: {}
token_usage:
type: integer
nullable: true
sampled_model_name:
type: string
nullable: true
required:
- name
- type
- errors
- execution_time
- scores
- token_usage
- sampled_model_name
sub_rewards:
type: object
additionalProperties: {}
model_grader_token_usage_per_model:
type: object
additionalProperties: {}
required:
- reward
- metadata
- sub_rewards
- model_grader_token_usage_per_model
RunObject:
type: object
title: A run on a thread
description: Represents an execution run on a [thread](https://platform.openai.com/docs/api-reference/threads).
properties:
id:
description: The identifier, which can be referenced in API endpoints.
type: string
object:
description: The object type, which is always `thread.run`.
type: string
enum:
- thread.run
x-stainless-const: true
created_at:
description: The Unix timestamp (in seconds) for when the run was created.
type: integer
thread_id:
description: >-
The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) that was executed
on as a part of this run.
type: string
assistant_id:
description: >-
The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) used for
execution of this run.
type: string
status:
$ref: '#/components/schemas/RunStatus'
required_action:
type: object
description: Details on the action required to continue the run. Will be `null` if no action is required.
nullable: true
properties:
type:
description: For now, this is always `submit_tool_outputs`.
type: string
enum:
- submit_tool_outputs
x-stainless-const: true
submit_tool_outputs:
type: object
description: Details on the tool outputs needed for this run to continue.
properties:
tool_calls:
type: array
description: A list of the relevant tool calls.
items:
$ref: '#/components/schemas/RunToolCallObject'
required:
- tool_calls
required:
- type
- submit_tool_outputs
last_error:
type: object
description: The last error associated with this run. Will be `null` if there are no errors.
nullable: true
properties:
code:
type: string
description: One of `server_error`, `rate_limit_exceeded`, or `invalid_prompt`.
enum:
- server_error
- rate_limit_exceeded
- invalid_prompt
message:
type: string
description: A human-readable description of the error.
required:
- code
- message
expires_at:
description: The Unix timestamp (in seconds) for when the run will expire.
type: integer
nullable: true
started_at:
description: The Unix timestamp (in seconds) for when the run was started.
type: integer
nullable: true
cancelled_at:
description: The Unix timestamp (in seconds) for when the run was cancelled.
type: integer
nullable: true
failed_at:
description: The Unix timestamp (in seconds) for when the run failed.
type: integer
nullable: true
completed_at:
description: The Unix timestamp (in seconds) for when the run was completed.
type: integer
nullable: true
incomplete_details:
description: Details on why the run is incomplete. Will be `null` if the run is not incomplete.
type: object
nullable: true
properties:
reason:
description: >-
The reason why the run is incomplete. This will point to which specific token limit was
reached over the course of the run.
type: string
enum:
- max_completion_tokens
- max_prompt_tokens
model:
description: >-
The model that the [assistant](https://platform.openai.com/docs/api-reference/assistants) used for
this run.
type: string
instructions:
description: >-
The instructions that the [assistant](https://platform.openai.com/docs/api-reference/assistants)
used for this run.
type: string
tools:
description: >-
The list of tools that the [assistant](https://platform.openai.com/docs/api-reference/assistants)
used for this run.
default: []
type: array
maxItems: 20
items:
$ref: '#/components/schemas/AssistantTool'
metadata:
$ref: '#/components/schemas/Metadata'
usage:
$ref: '#/components/schemas/RunCompletionUsage'
temperature:
description: The sampling temperature used for this run. If not set, defaults to 1.
type: number
nullable: true
top_p:
description: The nucleus sampling value used for this run. If not set, defaults to 1.
type: number
nullable: true
max_prompt_tokens:
type: integer
nullable: true
description: |
The maximum number of prompt tokens specified to have been used over the course of the run.
minimum: 256
max_completion_tokens:
type: integer
nullable: true
description: |
The maximum number of completion tokens specified to have been used over the course of the run.
minimum: 256
truncation_strategy:
allOf:
- $ref: '#/components/schemas/TruncationObject'
- nullable: true
tool_choice:
allOf:
- $ref: '#/components/schemas/AssistantsApiToolChoiceOption'
- nullable: true
parallel_tool_calls:
$ref: '#/components/schemas/ParallelToolCalls'
response_format:
$ref: '#/components/schemas/AssistantsApiResponseFormatOption'
nullable: true
required:
- id
- object
- created_at
- thread_id
- assistant_id
- status
- required_action
- last_error
- expires_at
- started_at
- cancelled_at
- failed_at
- completed_at
- model
- instructions
- tools
- metadata
- usage
- incomplete_details
- max_prompt_tokens
- max_completion_tokens
- truncation_strategy
- tool_choice
- parallel_tool_calls
- response_format
x-oaiMeta:
name: The run object
beta: true
example: |
{
"id": "run_abc123",
"object": "thread.run",
"created_at": 1698107661,
"assistant_id": "asst_abc123",
"thread_id": "thread_abc123",
"status": "completed",
"started_at": 1699073476,
"expires_at": null,
"cancelled_at": null,
"failed_at": null,
"completed_at": 1699073498,
"last_error": null,
"model": "gpt-4o",
"instructions": null,
"tools": [{"type": "file_search"}, {"type": "code_interpreter"}],
"metadata": {},
"incomplete_details": null,
"usage": {
"prompt_tokens": 123,
"completion_tokens": 456,
"total_tokens": 579
},
"temperature": 1.0,
"top_p": 1.0,
"max_prompt_tokens": 1000,
"max_completion_tokens": 1000,
"truncation_strategy": {
"type": "auto",
"last_messages": null
},
"response_format": "auto",
"tool_choice": "auto",
"parallel_tool_calls": true
}
RunStepCompletionUsage:
type: object
description: >-
Usage statistics related to the run step. This value will be `null` while the run step's status is
`in_progress`.
properties:
completion_tokens:
type: integer
description: Number of completion tokens used over the course of the run step.
prompt_tokens:
type: integer
description: Number of prompt tokens used over the course of the run step.
total_tokens:
type: integer
description: Total number of tokens used (prompt + completion).
required:
- prompt_tokens
- completion_tokens
- total_tokens
nullable: true
RunStepDeltaObject:
type: object
title: Run step delta object
description: |
Represents a run step delta i.e. any changed fields on a run step during streaming.
properties:
id:
description: The identifier of the run step, which can be referenced in API endpoints.
type: string
object:
description: The object type, which is always `thread.run.step.delta`.
type: string
enum:
- thread.run.step.delta
x-stainless-const: true
delta:
$ref: '#/components/schemas/RunStepDeltaObjectDelta'
required:
- id
- object
- delta
x-oaiMeta:
name: The run step delta object
beta: true
example: |
{
"id": "step_123",
"object": "thread.run.step.delta",
"delta": {
"step_details": {
"type": "tool_calls",
"tool_calls": [
{
"index": 0,
"id": "call_123",
"type": "code_interpreter",
"code_interpreter": { "input": "", "outputs": [] }
}
]
}
}
}
RunStepDeltaStepDetailsMessageCreationObject:
title: Message creation
type: object
description: Details of the message creation by the run step.
properties:
type:
description: Always `message_creation`.
type: string
enum:
- message_creation
x-stainless-const: true
message_creation:
type: object
properties:
message_id:
type: string
description: The ID of the message that was created by this run step.
required:
- type
RunStepDeltaStepDetailsToolCallsCodeObject:
title: Code interpreter tool call
type: object
description: Details of the Code Interpreter tool call the run step was involved in.
properties:
index:
type: integer
description: The index of the tool call in the tool calls array.
id:
type: string
description: The ID of the tool call.
type:
type: string
description: The type of tool call. This is always going to be `code_interpreter` for this type of tool call.
enum:
- code_interpreter
x-stainless-const: true
code_interpreter:
type: object
description: The Code Interpreter tool call definition.
properties:
input:
type: string
description: The input to the Code Interpreter tool call.
outputs:
type: array
description: >-
The outputs from the Code Interpreter tool call. Code Interpreter can output one or more
items, including text (`logs`) or images (`image`). Each of these are represented by a
different object type.
items:
type: object
anyOf:
- $ref: '#/components/schemas/RunStepDeltaStepDetailsToolCallsCodeOutputLogsObject'
- $ref: '#/components/schemas/RunStepDeltaStepDetailsToolCallsCodeOutputImageObject'
discriminator:
propertyName: type
required:
- index
- type
RunStepDeltaStepDetailsToolCallsCodeOutputImageObject:
title: Code interpreter image output
type: object
properties:
index:
type: integer
description: The index of the output in the outputs array.
type:
description: Always `image`.
type: string
enum:
- image
x-stainless-const: true
image:
type: object
properties:
file_id:
description: The [file](https://platform.openai.com/docs/api-reference/files) ID of the image.
type: string
required:
- index
- type
RunStepDeltaStepDetailsToolCallsCodeOutputLogsObject:
title: Code interpreter log output
type: object
description: Text output from the Code Interpreter tool call as part of a run step.
properties:
index:
type: integer
description: The index of the output in the outputs array.
type:
description: Always `logs`.
type: string
enum:
- logs
x-stainless-const: true
logs:
type: string
description: The text output from the Code Interpreter tool call.
required:
- index
- type
RunStepDeltaStepDetailsToolCallsFileSearchObject:
title: File search tool call
type: object
properties:
index:
type: integer
description: The index of the tool call in the tool calls array.
id:
type: string
description: The ID of the tool call object.
type:
type: string
description: The type of tool call. This is always going to be `file_search` for this type of tool call.
enum:
- file_search
x-stainless-const: true
file_search:
type: object
description: For now, this is always going to be an empty object.
x-oaiTypeLabel: map
required:
- index
- type
- file_search
RunStepDeltaStepDetailsToolCallsFunctionObject:
type: object
title: Function tool call
properties:
index:
type: integer
description: The index of the tool call in the tool calls array.
id:
type: string
description: The ID of the tool call object.
type:
type: string
description: The type of tool call. This is always going to be `function` for this type of tool call.
enum:
- function
x-stainless-const: true
function:
type: object
description: The definition of the function that was called.
properties:
name:
type: string
description: The name of the function.
arguments:
type: string
description: The arguments passed to the function.
output:
type: string
description: >-
The output of the function. This will be `null` if the outputs have not been
[submitted](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs) yet.
nullable: true
required:
- index
- type
RunStepDeltaStepDetailsToolCallsObject:
title: Tool calls
type: object
description: Details of the tool call.
properties:
type:
description: Always `tool_calls`.
type: string
enum:
- tool_calls
x-stainless-const: true
tool_calls:
type: array
description: >
An array of tool calls the run step was involved in. These can be associated with one of three
types of tools: `code_interpreter`, `file_search`, or `function`.
items:
$ref: '#/components/schemas/RunStepDeltaStepDetailsToolCall'
required:
- type
RunStepDetailsMessageCreationObject:
title: Message creation
type: object
description: Details of the message creation by the run step.
properties:
type:
description: Always `message_creation`.
type: string
enum:
- message_creation
x-stainless-const: true
message_creation:
type: object
properties:
message_id:
type: string
description: The ID of the message that was created by this run step.
required:
- message_id
required:
- type
- message_creation
RunStepDetailsToolCallsCodeObject:
title: Code Interpreter tool call
type: object
description: Details of the Code Interpreter tool call the run step was involved in.
properties:
id:
type: string
description: The ID of the tool call.
type:
type: string
description: The type of tool call. This is always going to be `code_interpreter` for this type of tool call.
enum:
- code_interpreter
x-stainless-const: true
code_interpreter:
type: object
description: The Code Interpreter tool call definition.
required:
- input
- outputs
properties:
input:
type: string
description: The input to the Code Interpreter tool call.
outputs:
type: array
description: >-
The outputs from the Code Interpreter tool call. Code Interpreter can output one or more
items, including text (`logs`) or images (`image`). Each of these are represented by a
different object type.
items:
type: object
anyOf:
- $ref: '#/components/schemas/RunStepDetailsToolCallsCodeOutputLogsObject'
- $ref: '#/components/schemas/RunStepDetailsToolCallsCodeOutputImageObject'
discriminator:
propertyName: type
required:
- id
- type
- code_interpreter
RunStepDetailsToolCallsCodeOutputImageObject:
title: Code Interpreter image output
type: object
properties:
type:
description: Always `image`.
type: string
enum:
- image
x-stainless-const: true
image:
type: object
properties:
file_id:
description: The [file](https://platform.openai.com/docs/api-reference/files) ID of the image.
type: string
required:
- file_id
required:
- type
- image
x-stainless-naming:
java:
type_name: ImageOutput
kotlin:
type_name: ImageOutput
RunStepDetailsToolCallsCodeOutputLogsObject:
title: Code Interpreter log output
type: object
description: Text output from the Code Interpreter tool call as part of a run step.
properties:
type:
description: Always `logs`.
type: string
enum:
- logs
x-stainless-const: true
logs:
type: string
description: The text output from the Code Interpreter tool call.
required:
- type
- logs
x-stainless-naming:
java:
type_name: LogsOutput
kotlin:
type_name: LogsOutput
RunStepDetailsToolCallsFileSearchObject:
title: File search tool call
type: object
properties:
id:
type: string
description: The ID of the tool call object.
type:
type: string
description: The type of tool call. This is always going to be `file_search` for this type of tool call.
enum:
- file_search
x-stainless-const: true
file_search:
type: object
description: For now, this is always going to be an empty object.
x-oaiTypeLabel: map
properties:
ranking_options:
$ref: '#/components/schemas/RunStepDetailsToolCallsFileSearchRankingOptionsObject'
results:
type: array
description: The results of the file search.
items:
$ref: '#/components/schemas/RunStepDetailsToolCallsFileSearchResultObject'
required:
- id
- type
- file_search
RunStepDetailsToolCallsFileSearchRankingOptionsObject:
title: File search tool call ranking options
type: object
description: The ranking options for the file search.
properties:
ranker:
$ref: '#/components/schemas/FileSearchRanker'
score_threshold:
type: number
description: >-
The score threshold for the file search. All values must be a floating point number between 0 and
1.
minimum: 0
maximum: 1
required:
- ranker
- score_threshold
RunStepDetailsToolCallsFileSearchResultObject:
title: File search tool call result
type: object
description: A result instance of the file search.
x-oaiTypeLabel: map
properties:
file_id:
type: string
description: The ID of the file that result was found in.
file_name:
type: string
description: The name of the file that result was found in.
score:
type: number
description: The score of the result. All values must be a floating point number between 0 and 1.
minimum: 0
maximum: 1
content:
type: array
description: >-
The content of the result that was found. The content is only included if requested via the
include query parameter.
items:
type: object
properties:
type:
type: string
description: The type of the content.
enum:
- text
x-stainless-const: true
text:
type: string
description: The text content of the file.
required:
- file_id
- file_name
- score
RunStepDetailsToolCallsFunctionObject:
type: object
title: Function tool call
properties:
id:
type: string
description: The ID of the tool call object.
type:
type: string
description: The type of tool call. This is always going to be `function` for this type of tool call.
enum:
- function
x-stainless-const: true
function:
type: object
description: The definition of the function that was called.
properties:
name:
type: string
description: The name of the function.
arguments:
type: string
description: The arguments passed to the function.
output:
type: string
description: >-
The output of the function. This will be `null` if the outputs have not been
[submitted](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs) yet.
nullable: true
required:
- name
- arguments
- output
required:
- id
- type
- function
RunStepDetailsToolCallsObject:
title: Tool calls
type: object
description: Details of the tool call.
properties:
type:
description: Always `tool_calls`.
type: string
enum:
- tool_calls
x-stainless-const: true
tool_calls:
type: array
description: >
An array of tool calls the run step was involved in. These can be associated with one of three
types of tools: `code_interpreter`, `file_search`, or `function`.
items:
$ref: '#/components/schemas/RunStepDetailsToolCall'
required:
- type
- tool_calls
RunStepObject:
type: object
title: Run steps
description: |
Represents a step in execution of a run.
properties:
id:
description: The identifier of the run step, which can be referenced in API endpoints.
type: string
object:
description: The object type, which is always `thread.run.step`.
type: string
enum:
- thread.run.step
x-stainless-const: true
created_at:
description: The Unix timestamp (in seconds) for when the run step was created.
type: integer
assistant_id:
description: >-
The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) associated
with the run step.
type: string
thread_id:
description: The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) that was run.
type: string
run_id:
description: >-
The ID of the [run](https://platform.openai.com/docs/api-reference/runs) that this run step is a
part of.
type: string
type:
description: The type of run step, which can be either `message_creation` or `tool_calls`.
type: string
enum:
- message_creation
- tool_calls
status:
description: >-
The status of the run step, which can be either `in_progress`, `cancelled`, `failed`, `completed`,
or `expired`.
type: string
enum:
- in_progress
- cancelled
- failed
- completed
- expired
step_details:
type: object
description: The details of the run step.
anyOf:
- $ref: '#/components/schemas/RunStepDetailsMessageCreationObject'
- $ref: '#/components/schemas/RunStepDetailsToolCallsObject'
discriminator:
propertyName: type
last_error:
type: object
description: The last error associated with this run step. Will be `null` if there are no errors.
nullable: true
properties:
code:
type: string
description: One of `server_error` or `rate_limit_exceeded`.
enum:
- server_error
- rate_limit_exceeded
message:
type: string
description: A human-readable description of the error.
required:
- code
- message
expired_at:
description: >-
The Unix timestamp (in seconds) for when the run step expired. A step is considered expired if the
parent run is expired.
type: integer
nullable: true
cancelled_at:
description: The Unix timestamp (in seconds) for when the run step was cancelled.
type: integer
nullable: true
failed_at:
description: The Unix timestamp (in seconds) for when the run step failed.
type: integer
nullable: true
completed_at:
description: The Unix timestamp (in seconds) for when the run step completed.
type: integer
nullable: true
metadata:
$ref: '#/components/schemas/Metadata'
usage:
$ref: '#/components/schemas/RunStepCompletionUsage'
required:
- id
- object
- created_at
- assistant_id
- thread_id
- run_id
- type
- status
- step_details
- last_error
- expired_at
- cancelled_at
- failed_at
- completed_at
- metadata
- usage
x-oaiMeta:
name: The run step object
beta: true
example: |
{
"id": "step_abc123",
"object": "thread.run.step",
"created_at": 1699063291,
"run_id": "run_abc123",
"assistant_id": "asst_abc123",
"thread_id": "thread_abc123",
"type": "message_creation",
"status": "completed",
"cancelled_at": null,
"completed_at": 1699063291,
"expired_at": null,
"failed_at": null,
"last_error": null,
"step_details": {
"type": "message_creation",
"message_creation": {
"message_id": "msg_abc123"
}
},
"usage": {
"prompt_tokens": 123,
"completion_tokens": 456,
"total_tokens": 579
}
}
RunStepStreamEvent:
anyOf:
- type: object
properties:
event:
type: string
enum:
- thread.run.step.created
x-stainless-const: true
data:
$ref: '#/components/schemas/RunStepObject'
required:
- event
- data
description: >-
Occurs when a [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) is
created.
x-oaiMeta:
dataDescription: '`data` is a [run step](/docs/api-reference/run-steps/step-object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.step.in_progress
x-stainless-const: true
data:
$ref: '#/components/schemas/RunStepObject'
required:
- event
- data
description: >-
Occurs when a [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object)
moves to an `in_progress` state.
x-oaiMeta:
dataDescription: '`data` is a [run step](/docs/api-reference/run-steps/step-object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.step.delta
x-stainless-const: true
data:
$ref: '#/components/schemas/RunStepDeltaObject'
required:
- event
- data
description: >-
Occurs when parts of a [run
step](https://platform.openai.com/docs/api-reference/run-steps/step-object) are being streamed.
x-oaiMeta:
dataDescription: '`data` is a [run step delta](/docs/api-reference/assistants-streaming/run-step-delta-object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.step.completed
x-stainless-const: true
data:
$ref: '#/components/schemas/RunStepObject'
required:
- event
- data
description: >-
Occurs when a [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) is
completed.
x-oaiMeta:
dataDescription: '`data` is a [run step](/docs/api-reference/run-steps/step-object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.step.failed
x-stainless-const: true
data:
$ref: '#/components/schemas/RunStepObject'
required:
- event
- data
description: >-
Occurs when a [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object)
fails.
x-oaiMeta:
dataDescription: '`data` is a [run step](/docs/api-reference/run-steps/step-object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.step.cancelled
x-stainless-const: true
data:
$ref: '#/components/schemas/RunStepObject'
required:
- event
- data
description: >-
Occurs when a [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) is
cancelled.
x-oaiMeta:
dataDescription: '`data` is a [run step](/docs/api-reference/run-steps/step-object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.step.expired
x-stainless-const: true
data:
$ref: '#/components/schemas/RunStepObject'
required:
- event
- data
description: >-
Occurs when a [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object)
expires.
x-oaiMeta:
dataDescription: '`data` is a [run step](/docs/api-reference/run-steps/step-object)'
discriminator:
propertyName: event
RunStreamEvent:
anyOf:
- type: object
properties:
event:
type: string
enum:
- thread.run.created
x-stainless-const: true
data:
$ref: '#/components/schemas/RunObject'
required:
- event
- data
description: Occurs when a new [run](https://platform.openai.com/docs/api-reference/runs/object) is created.
x-oaiMeta:
dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.queued
x-stainless-const: true
data:
$ref: '#/components/schemas/RunObject'
required:
- event
- data
description: >-
Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) moves to a
`queued` status.
x-oaiMeta:
dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.in_progress
x-stainless-const: true
data:
$ref: '#/components/schemas/RunObject'
required:
- event
- data
description: >-
Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) moves to an
`in_progress` status.
x-oaiMeta:
dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.requires_action
x-stainless-const: true
data:
$ref: '#/components/schemas/RunObject'
required:
- event
- data
description: >-
Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) moves to a
`requires_action` status.
x-oaiMeta:
dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.completed
x-stainless-const: true
data:
$ref: '#/components/schemas/RunObject'
required:
- event
- data
description: Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) is completed.
x-oaiMeta:
dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.incomplete
x-stainless-const: true
data:
$ref: '#/components/schemas/RunObject'
required:
- event
- data
description: >-
Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) ends with status
`incomplete`.
x-oaiMeta:
dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.failed
x-stainless-const: true
data:
$ref: '#/components/schemas/RunObject'
required:
- event
- data
description: Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) fails.
x-oaiMeta:
dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.cancelling
x-stainless-const: true
data:
$ref: '#/components/schemas/RunObject'
required:
- event
- data
description: >-
Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) moves to a
`cancelling` status.
x-oaiMeta:
dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.cancelled
x-stainless-const: true
data:
$ref: '#/components/schemas/RunObject'
required:
- event
- data
description: Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) is cancelled.
x-oaiMeta:
dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
- type: object
properties:
event:
type: string
enum:
- thread.run.expired
x-stainless-const: true
data:
$ref: '#/components/schemas/RunObject'
required:
- event
- data
description: Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) expires.
x-oaiMeta:
dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
discriminator:
propertyName: event
RunToolCallObject:
type: object
description: Tool call objects
properties:
id:
type: string
description: >-
The ID of the tool call. This ID must be referenced when you submit the tool outputs in using the
[Submit tool outputs to
run](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs) endpoint.
type:
type: string
description: The type of tool call the output is required for. For now, this is always `function`.
enum:
- function
x-stainless-const: true
function:
type: object
description: The function definition.
properties:
name:
type: string
description: The name of the function.
arguments:
type: string
description: The arguments that the model expects you to pass to the function.
required:
- name
- arguments
required:
- id
- type
- function
Screenshot:
type: object
title: Screenshot
description: |
A screenshot action.
properties:
type:
type: string
enum:
- screenshot
default: screenshot
description: |
Specifies the event type. For a screenshot action, this property is
always set to `screenshot`.
x-stainless-const: true
required:
- type
Scroll:
type: object
title: Scroll
description: |
A scroll action.
properties:
type:
type: string
enum:
- scroll
default: scroll
description: |
Specifies the event type. For a scroll action, this property is
always set to `scroll`.
x-stainless-const: true
x:
type: integer
description: |
The x-coordinate where the scroll occurred.
'y':
type: integer
description: |
The y-coordinate where the scroll occurred.
scroll_x:
type: integer
description: |
The horizontal scroll distance.
scroll_y:
type: integer
description: |
The vertical scroll distance.
required:
- type
- x
- 'y'
- scroll_x
- scroll_y
ServiceTier:
type: string
description: |
Specifies the processing type used for serving the request.
- If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'.
- If set to 'default', then the request will be processed with the standard pricing and performance for the selected model.
- If set to '[flex](https://platform.openai.com/docs/guides/flex-processing)' or '[priority](https://openai.com/api-priority-processing/)', then the request will be processed with the corresponding service tier.
- When not set, the default behavior is 'auto'.
When the `service_tier` parameter is set, the response body will include the `service_tier` value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter.
enum:
- auto
- default
- flex
- scale
- priority
nullable: true
default: auto
SpeechAudioDeltaEvent:
type: object
description: Emitted for each chunk of audio data generated during speech synthesis.
properties:
type:
type: string
description: |
The type of the event. Always `speech.audio.delta`.
enum:
- speech.audio.delta
x-stainless-const: true
audio:
type: string
description: |
A chunk of Base64-encoded audio data.
required:
- type
- audio
x-oaiMeta:
name: Stream Event (speech.audio.delta)
group: speech
example: |
{
"type": "speech.audio.delta",
"audio": "base64-encoded-audio-data"
}
SpeechAudioDoneEvent:
type: object
description: Emitted when the speech synthesis is complete and all audio has been streamed.
properties:
type:
type: string
description: |
The type of the event. Always `speech.audio.done`.
enum:
- speech.audio.done
x-stainless-const: true
usage:
type: object
description: |
Token usage statistics for the request.
properties:
input_tokens:
type: integer
description: Number of input tokens in the prompt.
output_tokens:
type: integer
description: Number of output tokens generated.
total_tokens:
type: integer
description: Total number of tokens used (input + output).
required:
- input_tokens
- output_tokens
- total_tokens
required:
- type
- usage
x-oaiMeta:
name: Stream Event (speech.audio.done)
group: speech
example: |
{
"type": "speech.audio.done",
"usage": {
"input_tokens": 14,
"output_tokens": 101,
"total_tokens": 115
}
}
StaticChunkingStrategy:
type: object
additionalProperties: false
properties:
max_chunk_size_tokens:
type: integer
minimum: 100
maximum: 4096
description: >-
The maximum number of tokens in each chunk. The default value is `800`. The minimum value is `100`
and the maximum value is `4096`.
chunk_overlap_tokens:
type: integer
description: |
The number of tokens that overlap between chunks. The default value is `400`.
Note that the overlap must not exceed half of `max_chunk_size_tokens`.
required:
- max_chunk_size_tokens
- chunk_overlap_tokens
StaticChunkingStrategyRequestParam:
type: object
title: Static Chunking Strategy
description: Customize your own chunking strategy by setting chunk size and chunk overlap.
additionalProperties: false
properties:
type:
type: string
description: Always `static`.
enum:
- static
x-stainless-const: true
static:
$ref: '#/components/schemas/StaticChunkingStrategy'
required:
- type
- static
StaticChunkingStrategyResponseParam:
type: object
title: Static Chunking Strategy
additionalProperties: false
properties:
type:
type: string
description: Always `static`.
enum:
- static
x-stainless-const: true
static:
$ref: '#/components/schemas/StaticChunkingStrategy'
required:
- type
- static
StopConfiguration:
description: |
Not supported with latest reasoning models `o3` and `o4-mini`.
Up to 4 sequences where the API will stop generating further tokens. The
returned text will not contain the stop sequence.
nullable: true
anyOf:
- type: string
default: <|endoftext|>
example: |+
nullable: true
- type: array
minItems: 1
maxItems: 4
items:
type: string
example: '["\n"]'
SubmitToolOutputsRunRequest:
type: object
additionalProperties: false
properties:
tool_outputs:
description: A list of tools for which the outputs are being submitted.
type: array
items:
type: object
properties:
tool_call_id:
type: string
description: >-
The ID of the tool call in the `required_action` object within the run object the output is
being submitted for.
output:
type: string
description: The output of the tool call to be submitted to continue the run.
stream:
type: boolean
nullable: true
description: >
If `true`, returns a stream of events that happen during the Run as server-sent events,
terminating when the Run enters a terminal state with a `data: [DONE]` message.
required:
- tool_outputs
TextResponseFormatConfiguration:
description: |
An object specifying the format that the model must output.
Configuring `{ "type": "json_schema" }` enables Structured Outputs,
which ensures the model will match your supplied JSON schema. Learn more in the
[Structured Outputs guide](https://platform.openai.com/docs/guides/structured-outputs).
The default format is `{ "type": "text" }` with no additional options.
**Not recommended for gpt-4o and newer models:**
Setting to `{ "type": "json_object" }` enables the older JSON mode, which
ensures the message the model generates is valid JSON. Using `json_schema`
is preferred for models that support it.
anyOf:
- $ref: '#/components/schemas/ResponseFormatText'
- $ref: '#/components/schemas/TextResponseFormatJsonSchema'
- $ref: '#/components/schemas/ResponseFormatJsonObject'
discriminator:
propertyName: type
TextResponseFormatJsonSchema:
type: object
title: JSON schema
description: |
JSON Schema response format. Used to generate structured JSON responses.
Learn more about [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs).
properties:
type:
type: string
description: The type of response format being defined. Always `json_schema`.
enum:
- json_schema
x-stainless-const: true
description:
type: string
description: |
A description of what the response format is for, used by the model to
determine how to respond in the format.
name:
type: string
description: |
The name of the response format. Must be a-z, A-Z, 0-9, or contain
underscores and dashes, with a maximum length of 64.
schema:
$ref: '#/components/schemas/ResponseFormatJsonSchemaSchema'
strict:
type: boolean
nullable: true
default: false
description: |
Whether to enable strict schema adherence when generating the output.
If set to true, the model will always follow the exact schema defined
in the `schema` field. Only a subset of JSON Schema is supported when
`strict` is `true`. To learn more, read the [Structured Outputs
guide](https://platform.openai.com/docs/guides/structured-outputs).
required:
- type
- schema
- name
ThreadObject:
type: object
title: Thread
description: Represents a thread that contains [messages](https://platform.openai.com/docs/api-reference/messages).
properties:
id:
description: The identifier, which can be referenced in API endpoints.
type: string
object:
description: The object type, which is always `thread`.
type: string
enum:
- thread
x-stainless-const: true
created_at:
description: The Unix timestamp (in seconds) for when the thread was created.
type: integer
tool_resources:
type: object
description: >
A set of resources that are made available to the assistant's tools in this thread. The resources
are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file
IDs, while the `file_search` tool requires a list of vector store IDs.
properties:
code_interpreter:
type: object
properties:
file_ids:
type: array
description: >
A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available
to the `code_interpreter` tool. There can be a maximum of 20 files associated with the
tool.
default: []
maxItems: 20
items:
type: string
file_search:
type: object
properties:
vector_store_ids:
type: array
description: >
The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object)
attached to this thread. There can be a maximum of 1 vector store attached to the thread.
maxItems: 1
items:
type: string
nullable: true
metadata:
$ref: '#/components/schemas/Metadata'
required:
- id
- object
- created_at
- tool_resources
- metadata
x-oaiMeta:
name: The thread object
beta: true
example: |
{
"id": "thread_abc123",
"object": "thread",
"created_at": 1698107661,
"metadata": {}
}
ThreadStreamEvent:
anyOf:
- type: object
properties:
enabled:
type: boolean
description: Whether to enable input audio transcription.
event:
type: string
enum:
- thread.created
x-stainless-const: true
data:
$ref: '#/components/schemas/ThreadObject'
required:
- event
- data
description: >-
Occurs when a new [thread](https://platform.openai.com/docs/api-reference/threads/object) is
created.
x-oaiMeta:
dataDescription: '`data` is a [thread](/docs/api-reference/threads/object)'
discriminator:
propertyName: event
ToggleCertificatesRequest:
type: object
properties:
certificate_ids:
type: array
items:
type: string
example: cert_abc
minItems: 1
maxItems: 10
required:
- certificate_ids
Tool:
description: |
A tool that can be used to generate a response.
discriminator:
propertyName: type
anyOf:
- $ref: '#/components/schemas/FunctionTool'
- $ref: '#/components/schemas/FileSearchTool'
- $ref: '#/components/schemas/WebSearchPreviewTool'
- $ref: '#/components/schemas/ComputerUsePreviewTool'
- $ref: '#/components/schemas/MCPTool'
- $ref: '#/components/schemas/CodeInterpreterTool'
- $ref: '#/components/schemas/ImageGenTool'
- $ref: '#/components/schemas/LocalShellTool'
- $ref: '#/components/schemas/CustomTool'
ToolChoiceAllowed:
type: object
title: Allowed tools
description: |
Constrains the tools available to the model to a pre-defined set.
properties:
type:
type: string
enum:
- allowed_tools
description: Allowed tool configuration type. Always `allowed_tools`.
x-stainless-const: true
mode:
type: string
enum:
- auto
- required
description: |
Constrains the tools available to the model to a pre-defined set.
`auto` allows the model to pick from among the allowed tools and generate a
message.
`required` requires the model to call one or more of the allowed tools.
tools:
type: array
description: |
A list of tool definitions that the model should be allowed to call.
For the Responses API, the list of tool definitions might look like:
```json
[
{ "type": "function", "name": "get_weather" },
{ "type": "mcp", "server_label": "deepwiki" },
{ "type": "image_generation" }
]
```
items:
type: object
description: |
A tool definition that the model should be allowed to call.
additionalProperties: true
x-oaiExpandable: false
required:
- type
- mode
- tools
ToolChoiceCustom:
type: object
title: Custom tool
description: |
Use this option to force the model to call a specific custom tool.
properties:
type:
type: string
enum:
- custom
description: For custom tool calling, the type is always `custom`.
x-stainless-const: true
name:
type: string
description: The name of the custom tool to call.
required:
- type
- name
ToolChoiceFunction:
type: object
title: Function tool
description: |
Use this option to force the model to call a specific function.
properties:
type:
type: string
enum:
- function
description: For function calling, the type is always `function`.
x-stainless-const: true
name:
type: string
description: The name of the function to call.
required:
- type
- name
ToolChoiceMCP:
type: object
title: MCP tool
description: |
Use this option to force the model to call a specific tool on a remote MCP server.
properties:
type:
type: string
enum:
- mcp
description: For MCP tools, the type is always `mcp`.
x-stainless-const: true
server_label:
type: string
description: |
The label of the MCP server to use.
name:
type: string
description: |
The name of the tool to call on the server.
nullable: true
required:
- type
- server_label
ToolChoiceOptions:
type: string
title: Tool choice mode
description: |
Controls which (if any) tool is called by the model.
`none` means the model will not call any tool and instead generates a message.
`auto` means the model can pick between generating a message or calling one or
more tools.
`required` means the model must call one or more tools.
enum:
- none
- auto
- required
ToolChoiceTypes:
type: object
title: Hosted tool
description: |
Indicates that the model should use a built-in tool to generate a response.
[Learn more about built-in tools](https://platform.openai.com/docs/guides/tools).
properties:
type:
type: string
description: |
The type of hosted tool the model should to use. Learn more about
[built-in tools](https://platform.openai.com/docs/guides/tools).
Allowed values are:
- `file_search`
- `web_search_preview`
- `computer_use_preview`
- `code_interpreter`
- `image_generation`
enum:
- file_search
- web_search_preview
- computer_use_preview
- web_search_preview_2025_03_11
- image_generation
- code_interpreter
required:
- type
TranscriptTextDeltaEvent:
type: object
description: >-
Emitted when there is an additional text delta. This is also the first event emitted when the
transcription starts. Only emitted when you [create a
transcription](https://platform.openai.com/docs/api-reference/audio/create-transcription) with the
`Stream` parameter set to `true`.
properties:
type:
type: string
description: |
The type of the event. Always `transcript.text.delta`.
enum:
- transcript.text.delta
x-stainless-const: true
delta:
type: string
description: |
The text delta that was additionally transcribed.
logprobs:
type: array
description: >
The log probabilities of the delta. Only included if you [create a
transcription](https://platform.openai.com/docs/api-reference/audio/create-transcription) with the
`include[]` parameter set to `logprobs`.
items:
type: object
properties:
token:
type: string
description: |
The token that was used to generate the log probability.
logprob:
type: number
description: |
The log probability of the token.
bytes:
type: array
items:
type: integer
description: |
The bytes that were used to generate the log probability.
required:
- type
- delta
x-oaiMeta:
name: Stream Event (transcript.text.delta)
group: transcript
example: |
{
"type": "transcript.text.delta",
"delta": " wonderful"
}
TranscriptTextDoneEvent:
type: object
description: >-
Emitted when the transcription is complete. Contains the complete transcription text. Only emitted
when you [create a
transcription](https://platform.openai.com/docs/api-reference/audio/create-transcription) with the
`Stream` parameter set to `true`.
properties:
type:
type: string
description: |
The type of the event. Always `transcript.text.done`.
enum:
- transcript.text.done
x-stainless-const: true
text:
type: string
description: |
The text that was transcribed.
logprobs:
type: array
description: >
The log probabilities of the individual tokens in the transcription. Only included if you [create
a transcription](https://platform.openai.com/docs/api-reference/audio/create-transcription) with
the `include[]` parameter set to `logprobs`.
items:
type: object
properties:
token:
type: string
description: |
The token that was used to generate the log probability.
logprob:
type: number
description: |
The log probability of the token.
bytes:
type: array
items:
type: integer
description: |
The bytes that were used to generate the log probability.
usage:
$ref: '#/components/schemas/TranscriptTextUsageTokens'
required:
- type
- text
x-oaiMeta:
name: Stream Event (transcript.text.done)
group: transcript
example: |
{
"type": "transcript.text.done",
"text": "I see skies of blue and clouds of white, the bright blessed days, the dark sacred nights, and I think to myself, what a wonderful world.",
"usage": {
"type": "tokens",
"input_tokens": 14,
"input_token_details": {
"text_tokens": 10,
"audio_tokens": 4
},
"output_tokens": 31,
"total_tokens": 45
}
}
TranscriptTextUsageDuration:
type: object
title: Duration Usage
description: Usage statistics for models billed by audio input duration.
properties:
type:
type: string
enum:
- duration
description: The type of the usage object. Always `duration` for this variant.
x-stainless-const: true
seconds:
type: number
description: Duration of the input audio in seconds.
required:
- type
- seconds
TranscriptTextUsageTokens:
type: object
title: Token Usage
description: Usage statistics for models billed by token usage.
properties:
type:
type: string
enum:
- tokens
description: The type of the usage object. Always `tokens` for this variant.
x-stainless-const: true
input_tokens:
type: integer
description: Number of input tokens billed for this request.
input_token_details:
type: object
description: Details about the input tokens billed for this request.
properties:
text_tokens:
type: integer
description: Number of text tokens billed for this request.
audio_tokens:
type: integer
description: Number of audio tokens billed for this request.
output_tokens:
type: integer
description: Number of output tokens generated.
total_tokens:
type: integer
description: Total number of tokens used (input + output).
required:
- type
- input_tokens
- output_tokens
- total_tokens
TranscriptionChunkingStrategy:
description: >-
Controls how the audio is cut into chunks. When set to `"auto"`, the server first normalizes loudness
and then uses voice activity detection (VAD) to choose boundaries. `server_vad` object can be provided
to tweak VAD detection parameters manually. If unset, the audio is transcribed as a single block.
anyOf:
- type: string
enum:
- auto
description: |
Automatically set chunking parameters based on the audio. Must be set to `"auto"`.
x-stainless-const: true
- $ref: '#/components/schemas/VadConfig'
nullable: true
x-oaiTypeLabel: string
TranscriptionInclude:
type: string
enum:
- logprobs
TranscriptionSegment:
type: object
properties:
id:
type: integer
description: Unique identifier of the segment.
seek:
type: integer
description: Seek offset of the segment.
start:
type: number
format: float
description: Start time of the segment in seconds.
end:
type: number
format: float
description: End time of the segment in seconds.
text:
type: string
description: Text content of the segment.
tokens:
type: array
items:
type: integer
description: Array of token IDs for the text content.
temperature:
type: number
format: float
description: Temperature parameter used for generating the segment.
avg_logprob:
type: number
format: float
description: Average logprob of the segment. If the value is lower than -1, consider the logprobs failed.
compression_ratio:
type: number
format: float
description: >-
Compression ratio of the segment. If the value is greater than 2.4, consider the compression
failed.
no_speech_prob:
type: number
format: float
description: >-
Probability of no speech in the segment. If the value is higher than 1.0 and the `avg_logprob` is
below -1, consider this segment silent.
required:
- id
- seek
- start
- end
- text
- tokens
- temperature
- avg_logprob
- compression_ratio
- no_speech_prob
TranscriptionWord:
type: object
properties:
word:
type: string
description: The text content of the word.
start:
type: number
format: float
description: Start time of the word in seconds.
end:
type: number
format: float
description: End time of the word in seconds.
required:
- word
- start
- end
TruncationObject:
type: object
title: Thread Truncation Controls
description: >-
Controls for how a thread will be truncated prior to the run. Use this to control the initial context
window of the run.
properties:
type:
type: string
description: >-
The truncation strategy to use for the thread. The default is `auto`. If set to `last_messages`,
the thread will be truncated to the n most recent messages in the thread. When set to `auto`,
messages in the middle of the thread will be dropped to fit the context length of the model,
`max_prompt_tokens`.
enum:
- auto
- last_messages
last_messages:
type: integer
description: The number of most recent messages from the thread when constructing the context for the run.
minimum: 1
nullable: true
required:
- type
Type:
type: object
title: Type
description: |
An action to type in text.
properties:
type:
type: string
enum:
- type
default: type
description: |
Specifies the event type. For a type action, this property is
always set to `type`.
x-stainless-const: true
text:
type: string
description: |
The text to type.
required:
- type
- text
UpdateVectorStoreFileAttributesRequest:
type: object
additionalProperties: false
properties:
attributes:
$ref: '#/components/schemas/VectorStoreFileAttributes'
required:
- attributes
x-oaiMeta:
name: Update vector store file attributes request
UpdateVectorStoreRequest:
type: object
additionalProperties: false
properties:
name:
description: The name of the vector store.
type: string
nullable: true
expires_after:
allOf:
- $ref: '#/components/schemas/VectorStoreExpirationAfter'
- nullable: true
metadata:
$ref: '#/components/schemas/Metadata'
Upload:
type: object
title: Upload
description: |
The Upload object can accept byte chunks in the form of Parts.
properties:
id:
type: string
description: The Upload unique identifier, which can be referenced in API endpoints.
created_at:
type: integer
description: The Unix timestamp (in seconds) for when the Upload was created.
filename:
type: string
description: The name of the file to be uploaded.
bytes:
type: integer
description: The intended number of bytes to be uploaded.
purpose:
type: string
description: >-
The intended purpose of the file. [Please refer
here](https://platform.openai.com/docs/api-reference/files/object#files/object-purpose) for
acceptable values.
status:
type: string
description: The status of the Upload.
enum:
- pending
- completed
- cancelled
- expired
expires_at:
type: integer
description: The Unix timestamp (in seconds) for when the Upload will expire.
object:
type: string
description: The object type, which is always "upload".
enum:
- upload
x-stainless-const: true
file:
allOf:
- $ref: '#/components/schemas/OpenAIFile'
- nullable: true
description: The ready File object after the Upload is completed.
required:
- bytes
- created_at
- expires_at
- filename
- id
- purpose
- status
- object
x-oaiMeta:
name: The upload object
example: |
{
"id": "upload_abc123",
"object": "upload",
"bytes": 2147483648,
"created_at": 1719184911,
"filename": "training_examples.jsonl",
"purpose": "fine-tune",
"status": "completed",
"expires_at": 1719127296,
"file": {
"id": "file-xyz321",
"object": "file",
"bytes": 2147483648,
"created_at": 1719186911,
"filename": "training_examples.jsonl",
"purpose": "fine-tune",
}
}
UploadCertificateRequest:
type: object
properties:
name:
type: string
description: An optional name for the certificate
content:
type: string
description: The certificate content in PEM format
required:
- content
UploadPart:
type: object
title: UploadPart
description: |
The upload Part represents a chunk of bytes we can add to an Upload object.
properties:
id:
type: string
description: The upload Part unique identifier, which can be referenced in API endpoints.
created_at:
type: integer
description: The Unix timestamp (in seconds) for when the Part was created.
upload_id:
type: string
description: The ID of the Upload object that this Part was added to.
object:
type: string
description: The object type, which is always `upload.part`.
enum:
- upload.part
x-stainless-const: true
required:
- created_at
- id
- object
- upload_id
x-oaiMeta:
name: The upload part object
example: |
{
"id": "part_def456",
"object": "upload.part",
"created_at": 1719186911,
"upload_id": "upload_abc123"
}
UsageAudioSpeechesResult:
type: object
description: The aggregated audio speeches usage details of the specific time bucket.
properties:
object:
type: string
enum:
- organization.usage.audio_speeches.result
x-stainless-const: true
characters:
type: integer
description: The number of characters processed.
num_model_requests:
type: integer
description: The count of requests made to the model.
project_id:
type: string
nullable: true
description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
user_id:
type: string
nullable: true
description: When `group_by=user_id`, this field provides the user ID of the grouped usage result.
api_key_id:
type: string
nullable: true
description: When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result.
model:
type: string
nullable: true
description: When `group_by=model`, this field provides the model name of the grouped usage result.
required:
- object
- characters
- num_model_requests
x-oaiMeta:
name: Audio speeches usage object
example: |
{
"object": "organization.usage.audio_speeches.result",
"characters": 45,
"num_model_requests": 1,
"project_id": "proj_abc",
"user_id": "user-abc",
"api_key_id": "key_abc",
"model": "tts-1"
}
UsageAudioTranscriptionsResult:
type: object
description: The aggregated audio transcriptions usage details of the specific time bucket.
properties:
object:
type: string
enum:
- organization.usage.audio_transcriptions.result
x-stainless-const: true
seconds:
type: integer
description: The number of seconds processed.
num_model_requests:
type: integer
description: The count of requests made to the model.
project_id:
type: string
nullable: true
description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
user_id:
type: string
nullable: true
description: When `group_by=user_id`, this field provides the user ID of the grouped usage result.
api_key_id:
type: string
nullable: true
description: When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result.
model:
type: string
nullable: true
description: When `group_by=model`, this field provides the model name of the grouped usage result.
required:
- object
- seconds
- num_model_requests
x-oaiMeta:
name: Audio transcriptions usage object
example: |
{
"object": "organization.usage.audio_transcriptions.result",
"seconds": 10,
"num_model_requests": 1,
"project_id": "proj_abc",
"user_id": "user-abc",
"api_key_id": "key_abc",
"model": "tts-1"
}
UsageCodeInterpreterSessionsResult:
type: object
description: The aggregated code interpreter sessions usage details of the specific time bucket.
properties:
object:
type: string
enum:
- organization.usage.code_interpreter_sessions.result
x-stainless-const: true
num_sessions:
type: integer
description: The number of code interpreter sessions.
project_id:
type: string
nullable: true
description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
required:
- object
- sessions
x-oaiMeta:
name: Code interpreter sessions usage object
example: |
{
"object": "organization.usage.code_interpreter_sessions.result",
"num_sessions": 1,
"project_id": "proj_abc"
}
UsageCompletionsResult:
type: object
description: The aggregated completions usage details of the specific time bucket.
properties:
object:
type: string
enum:
- organization.usage.completions.result
x-stainless-const: true
input_tokens:
type: integer
description: >-
The aggregated number of text input tokens used, including cached tokens. For customers subscribe
to scale tier, this includes scale tier tokens.
input_cached_tokens:
type: integer
description: >-
The aggregated number of text input tokens that has been cached from previous requests. For
customers subscribe to scale tier, this includes scale tier tokens.
output_tokens:
type: integer
description: >-
The aggregated number of text output tokens used. For customers subscribe to scale tier, this
includes scale tier tokens.
input_audio_tokens:
type: integer
description: The aggregated number of audio input tokens used, including cached tokens.
output_audio_tokens:
type: integer
description: The aggregated number of audio output tokens used.
num_model_requests:
type: integer
description: The count of requests made to the model.
project_id:
type: string
nullable: true
description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
user_id:
type: string
nullable: true
description: When `group_by=user_id`, this field provides the user ID of the grouped usage result.
api_key_id:
type: string
nullable: true
description: When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result.
model:
type: string
nullable: true
description: When `group_by=model`, this field provides the model name of the grouped usage result.
batch:
type: boolean
nullable: true
description: When `group_by=batch`, this field tells whether the grouped usage result is batch or not.
required:
- object
- input_tokens
- output_tokens
- num_model_requests
x-oaiMeta:
name: Completions usage object
example: |
{
"object": "organization.usage.completions.result",
"input_tokens": 5000,
"output_tokens": 1000,
"input_cached_tokens": 4000,
"input_audio_tokens": 300,
"output_audio_tokens": 200,
"num_model_requests": 5,
"project_id": "proj_abc",
"user_id": "user-abc",
"api_key_id": "key_abc",
"model": "gpt-4o-mini-2024-07-18",
"batch": false
}
UsageEmbeddingsResult:
type: object
description: The aggregated embeddings usage details of the specific time bucket.
properties:
object:
type: string
enum:
- organization.usage.embeddings.result
x-stainless-const: true
input_tokens:
type: integer
description: The aggregated number of input tokens used.
num_model_requests:
type: integer
description: The count of requests made to the model.
project_id:
type: string
nullable: true
description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
user_id:
type: string
nullable: true
description: When `group_by=user_id`, this field provides the user ID of the grouped usage result.
api_key_id:
type: string
nullable: true
description: When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result.
model:
type: string
nullable: true
description: When `group_by=model`, this field provides the model name of the grouped usage result.
required:
- object
- input_tokens
- num_model_requests
x-oaiMeta:
name: Embeddings usage object
example: |
{
"object": "organization.usage.embeddings.result",
"input_tokens": 20,
"num_model_requests": 2,
"project_id": "proj_abc",
"user_id": "user-abc",
"api_key_id": "key_abc",
"model": "text-embedding-ada-002-v2"
}
UsageImagesResult:
type: object
description: The aggregated images usage details of the specific time bucket.
properties:
object:
type: string
enum:
- organization.usage.images.result
x-stainless-const: true
images:
type: integer
description: The number of images processed.
num_model_requests:
type: integer
description: The count of requests made to the model.
source:
type: string
nullable: true
description: >-
When `group_by=source`, this field provides the source of the grouped usage result, possible
values are `image.generation`, `image.edit`, `image.variation`.
size:
type: string
nullable: true
description: When `group_by=size`, this field provides the image size of the grouped usage result.
project_id:
type: string
nullable: true
description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
user_id:
type: string
nullable: true
description: When `group_by=user_id`, this field provides the user ID of the grouped usage result.
api_key_id:
type: string
nullable: true
description: When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result.
model:
type: string
nullable: true
description: When `group_by=model`, this field provides the model name of the grouped usage result.
required:
- object
- images
- num_model_requests
x-oaiMeta:
name: Images usage object
example: |
{
"object": "organization.usage.images.result",
"images": 2,
"num_model_requests": 2,
"size": "1024x1024",
"source": "image.generation",
"project_id": "proj_abc",
"user_id": "user-abc",
"api_key_id": "key_abc",
"model": "dall-e-3"
}
UsageModerationsResult:
type: object
description: The aggregated moderations usage details of the specific time bucket.
properties:
object:
type: string
enum:
- organization.usage.moderations.result
x-stainless-const: true
input_tokens:
type: integer
description: The aggregated number of input tokens used.
num_model_requests:
type: integer
description: The count of requests made to the model.
project_id:
type: string
nullable: true
description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
user_id:
type: string
nullable: true
description: When `group_by=user_id`, this field provides the user ID of the grouped usage result.
api_key_id:
type: string
nullable: true
description: When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result.
model:
type: string
nullable: true
description: When `group_by=model`, this field provides the model name of the grouped usage result.
required:
- object
- input_tokens
- num_model_requests
x-oaiMeta:
name: Moderations usage object
example: |
{
"object": "organization.usage.moderations.result",
"input_tokens": 20,
"num_model_requests": 2,
"project_id": "proj_abc",
"user_id": "user-abc",
"api_key_id": "key_abc",
"model": "text-moderation"
}
UsageResponse:
type: object
properties:
object:
type: string
enum:
- page
x-stainless-const: true
data:
type: array
items:
$ref: '#/components/schemas/UsageTimeBucket'
has_more:
type: boolean
next_page:
type: string
required:
- object
- data
- has_more
- next_page
UsageTimeBucket:
type: object
properties:
object:
type: string
enum:
- bucket
x-stainless-const: true
start_time:
type: integer
end_time:
type: integer
result:
type: array
items:
anyOf:
- $ref: '#/components/schemas/UsageCompletionsResult'
- $ref: '#/components/schemas/UsageEmbeddingsResult'
- $ref: '#/components/schemas/UsageModerationsResult'
- $ref: '#/components/schemas/UsageImagesResult'
- $ref: '#/components/schemas/UsageAudioSpeechesResult'
- $ref: '#/components/schemas/UsageAudioTranscriptionsResult'
- $ref: '#/components/schemas/UsageVectorStoresResult'
- $ref: '#/components/schemas/UsageCodeInterpreterSessionsResult'
- $ref: '#/components/schemas/CostsResult'
discriminator:
propertyName: object
required:
- object
- start_time
- end_time
- result
UsageVectorStoresResult:
type: object
description: The aggregated vector stores usage details of the specific time bucket.
properties:
object:
type: string
enum:
- organization.usage.vector_stores.result
x-stainless-const: true
usage_bytes:
type: integer
description: The vector stores usage in bytes.
project_id:
type: string
nullable: true
description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
required:
- object
- usage_bytes
x-oaiMeta:
name: Vector stores usage object
example: |
{
"object": "organization.usage.vector_stores.result",
"usage_bytes": 1024,
"project_id": "proj_abc"
}
User:
type: object
description: Represents an individual `user` within an organization.
properties:
object:
type: string
enum:
- organization.user
description: The object type, which is always `organization.user`
x-stainless-const: true
id:
type: string
description: The identifier, which can be referenced in API endpoints
name:
type: string
description: The name of the user
email:
type: string
description: The email address of the user
role:
type: string
enum:
- owner
- reader
description: '`owner` or `reader`'
added_at:
type: integer
description: The Unix timestamp (in seconds) of when the user was added.
required:
- object
- id
- name
- email
- role
- added_at
x-oaiMeta:
name: The user object
example: |
{
"object": "organization.user",
"id": "user_abc",
"name": "First Last",
"email": "user@example.com",
"role": "owner",
"added_at": 1711471533
}
UserDeleteResponse:
type: object
properties:
object:
type: string
enum:
- organization.user.deleted
x-stainless-const: true
id:
type: string
deleted:
type: boolean
required:
- object
- id
- deleted
UserListResponse:
type: object
properties:
object:
type: string
enum:
- list
x-stainless-const: true
data:
type: array
items:
$ref: '#/components/schemas/User'
first_id:
type: string
last_id:
type: string
has_more:
type: boolean
required:
- object
- data
- first_id
- last_id
- has_more
UserRoleUpdateRequest:
type: object
properties:
role:
type: string
enum:
- owner
- reader
description: '`owner` or `reader`'
required:
- role
VadConfig:
type: object
additionalProperties: false
required:
- type
properties:
type:
type: string
enum:
- server_vad
description: Must be set to `server_vad` to enable manual chunking using server side VAD.
prefix_padding_ms:
type: integer
default: 300
description: |
Amount of audio to include before the VAD detected speech (in
milliseconds).
silence_duration_ms:
type: integer
default: 200
description: |
Duration of silence to detect speech stop (in milliseconds).
With shorter values the model will respond more quickly,
but may jump in on short pauses from the user.
threshold:
type: number
default: 0.5
description: |
Sensitivity threshold (0.0 to 1.0) for voice activity detection. A
higher threshold will require louder audio to activate the model, and
thus might perform better in noisy environments.
ValidateGraderRequest:
type: object
title: ValidateGraderRequest
properties:
grader:
type: object
description: The grader used for the fine-tuning job.
anyOf:
- $ref: '#/components/schemas/GraderStringCheck'
- $ref: '#/components/schemas/GraderTextSimilarity'
- $ref: '#/components/schemas/GraderPython'
- $ref: '#/components/schemas/GraderScoreModel'
- $ref: '#/components/schemas/GraderMulti'
required:
- grader
ValidateGraderResponse:
type: object
title: ValidateGraderResponse
properties:
grader:
type: object
description: The grader used for the fine-tuning job.
anyOf:
- $ref: '#/components/schemas/GraderStringCheck'
- $ref: '#/components/schemas/GraderTextSimilarity'
- $ref: '#/components/schemas/GraderPython'
- $ref: '#/components/schemas/GraderScoreModel'
- $ref: '#/components/schemas/GraderMulti'
VectorStoreExpirationAfter:
type: object
title: Vector store expiration policy
description: The expiration policy for a vector store.
properties:
anchor:
description: 'Anchor timestamp after which the expiration policy applies. Supported anchors: `last_active_at`.'
type: string
enum:
- last_active_at
x-stainless-const: true
days:
description: The number of days after the anchor time that the vector store will expire.
type: integer
minimum: 1
maximum: 365
required:
- anchor
- days
VectorStoreFileAttributes:
type: object
description: |
Set of 16 key-value pairs that can be attached to an object. This can be
useful for storing additional information about the object in a structured
format, and querying for objects via API or the dashboard. Keys are strings
with a maximum length of 64 characters. Values are strings with a maximum
length of 512 characters, booleans, or numbers.
maxProperties: 16
propertyNames:
type: string
maxLength: 64
additionalProperties:
anyOf:
- type: string
maxLength: 512
- type: number
- type: boolean
x-oaiTypeLabel: map
nullable: true
VectorStoreFileBatchObject:
type: object
title: Vector store file batch
description: A batch of files attached to a vector store.
properties:
id:
description: The identifier, which can be referenced in API endpoints.
type: string
object:
description: The object type, which is always `vector_store.file_batch`.
type: string
enum:
- vector_store.files_batch
x-stainless-const: true
created_at:
description: The Unix timestamp (in seconds) for when the vector store files batch was created.
type: integer
vector_store_id:
description: >-
The ID of the [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object)
that the [File](https://platform.openai.com/docs/api-reference/files) is attached to.
type: string
status:
description: >-
The status of the vector store files batch, which can be either `in_progress`, `completed`,
`cancelled` or `failed`.
type: string
enum:
- in_progress
- completed
- cancelled
- failed
file_counts:
type: object
properties:
in_progress:
description: The number of files that are currently being processed.
type: integer
completed:
description: The number of files that have been processed.
type: integer
failed:
description: The number of files that have failed to process.
type: integer
cancelled:
description: The number of files that where cancelled.
type: integer
total:
description: The total number of files.
type: integer
required:
- in_progress
- completed
- cancelled
- failed
- total
required:
- id
- object
- created_at
- vector_store_id
- status
- file_counts
x-oaiMeta:
name: The vector store files batch object
beta: true
example: |
{
"id": "vsfb_123",
"object": "vector_store.files_batch",
"created_at": 1698107661,
"vector_store_id": "vs_abc123",
"status": "completed",
"file_counts": {
"in_progress": 0,
"completed": 100,
"failed": 0,
"cancelled": 0,
"total": 100
}
}
VectorStoreFileContentResponse:
type: object
description: Represents the parsed content of a vector store file.
properties:
object:
type: string
enum:
- vector_store.file_content.page
description: The object type, which is always `vector_store.file_content.page`
x-stainless-const: true
data:
type: array
description: Parsed content of the file.
items:
type: object
properties:
type:
type: string
description: The content type (currently only `"text"`)
text:
type: string
description: The text content
has_more:
type: boolean
description: Indicates if there are more content pages to fetch.
next_page:
type: string
description: The token for the next page, if any.
nullable: true
required:
- object
- data
- has_more
- next_page
VectorStoreFileObject:
type: object
title: Vector store files
description: A list of files attached to a vector store.
properties:
id:
description: The identifier, which can be referenced in API endpoints.
type: string
object:
description: The object type, which is always `vector_store.file`.
type: string
enum:
- vector_store.file
x-stainless-const: true
usage_bytes:
description: >-
The total vector store usage in bytes. Note that this may be different from the original file
size.
type: integer
created_at:
description: The Unix timestamp (in seconds) for when the vector store file was created.
type: integer
vector_store_id:
description: >-
The ID of the [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object)
that the [File](https://platform.openai.com/docs/api-reference/files) is attached to.
type: string
status:
description: >-
The status of the vector store file, which can be either `in_progress`, `completed`, `cancelled`,
or `failed`. The status `completed` indicates that the vector store file is ready for use.
type: string
enum:
- in_progress
- completed
- cancelled
- failed
last_error:
type: object
description: The last error associated with this vector store file. Will be `null` if there are no errors.
nullable: true
properties:
code:
type: string
description: One of `server_error` or `rate_limit_exceeded`.
enum:
- server_error
- unsupported_file
- invalid_file
message:
type: string
description: A human-readable description of the error.
required:
- code
- message
chunking_strategy:
$ref: '#/components/schemas/ChunkingStrategyResponse'
attributes:
$ref: '#/components/schemas/VectorStoreFileAttributes'
required:
- id
- object
- usage_bytes
- created_at
- vector_store_id
- status
- last_error
x-oaiMeta:
name: The vector store file object
beta: true
example: |
{
"id": "file-abc123",
"object": "vector_store.file",
"usage_bytes": 1234,
"created_at": 1698107661,
"vector_store_id": "vs_abc123",
"status": "completed",
"last_error": null,
"chunking_strategy": {
"type": "static",
"static": {
"max_chunk_size_tokens": 800,
"chunk_overlap_tokens": 400
}
}
}
VectorStoreObject:
type: object
title: Vector store
description: A vector store is a collection of processed files can be used by the `file_search` tool.
properties:
id:
description: The identifier, which can be referenced in API endpoints.
type: string
object:
description: The object type, which is always `vector_store`.
type: string
enum:
- vector_store
x-stainless-const: true
created_at:
description: The Unix timestamp (in seconds) for when the vector store was created.
type: integer
name:
description: The name of the vector store.
type: string
usage_bytes:
description: The total number of bytes used by the files in the vector store.
type: integer
file_counts:
type: object
properties:
in_progress:
description: The number of files that are currently being processed.
type: integer
completed:
description: The number of files that have been successfully processed.
type: integer
failed:
description: The number of files that have failed to process.
type: integer
cancelled:
description: The number of files that were cancelled.
type: integer
total:
description: The total number of files.
type: integer
required:
- in_progress
- completed
- failed
- cancelled
- total
status:
description: >-
The status of the vector store, which can be either `expired`, `in_progress`, or `completed`. A
status of `completed` indicates that the vector store is ready for use.
type: string
enum:
- expired
- in_progress
- completed
expires_after:
$ref: '#/components/schemas/VectorStoreExpirationAfter'
expires_at:
description: The Unix timestamp (in seconds) for when the vector store will expire.
type: integer
nullable: true
last_active_at:
description: The Unix timestamp (in seconds) for when the vector store was last active.
type: integer
nullable: true
metadata:
$ref: '#/components/schemas/Metadata'
required:
- id
- object
- usage_bytes
- created_at
- status
- last_active_at
- name
- file_counts
- metadata
x-oaiMeta:
name: The vector store object
example: |
{
"id": "vs_123",
"object": "vector_store",
"created_at": 1698107661,
"usage_bytes": 123456,
"last_active_at": 1698107661,
"name": "my_vector_store",
"status": "completed",
"file_counts": {
"in_progress": 0,
"completed": 100,
"cancelled": 0,
"failed": 0,
"total": 100
},
"last_used_at": 1698107661
}
VectorStoreSearchRequest:
type: object
additionalProperties: false
properties:
query:
description: A query string for a search
anyOf:
- type: string
- type: array
items:
type: string
description: A list of queries to search for.
minItems: 1
rewrite_query:
description: Whether to rewrite the natural language query for vector search.
type: boolean
default: false
max_num_results:
description: The maximum number of results to return. This number should be between 1 and 50 inclusive.
type: integer
default: 10
minimum: 1
maximum: 50
filters:
description: A filter to apply based on file attributes.
anyOf:
- $ref: '#/components/schemas/ComparisonFilter'
- $ref: '#/components/schemas/CompoundFilter'
ranking_options:
description: Ranking options for search.
type: object
additionalProperties: false
properties:
ranker:
description: Enable re-ranking; set to `none` to disable, which can help reduce latency.
type: string
enum:
- none
- auto
- default-2024-11-15
default: auto
score_threshold:
type: number
minimum: 0
maximum: 1
default: 0
required:
- query
x-oaiMeta:
name: Vector store search request
VectorStoreSearchResultContentObject:
type: object
additionalProperties: false
properties:
type:
description: The type of content.
type: string
enum:
- text
text:
description: The text content returned from search.
type: string
required:
- type
- text
x-oaiMeta:
name: Vector store search result content object
VectorStoreSearchResultItem:
type: object
additionalProperties: false
properties:
file_id:
type: string
description: The ID of the vector store file.
filename:
type: string
description: The name of the vector store file.
score:
type: number
description: The similarity score for the result.
minimum: 0
maximum: 1
attributes:
$ref: '#/components/schemas/VectorStoreFileAttributes'
content:
type: array
description: Content chunks from the file.
items:
$ref: '#/components/schemas/VectorStoreSearchResultContentObject'
required:
- file_id
- filename
- score
- attributes
- content
x-oaiMeta:
name: Vector store search result item
VectorStoreSearchResultsPage:
type: object
additionalProperties: false
properties:
object:
type: string
enum:
- vector_store.search_results.page
description: The object type, which is always `vector_store.search_results.page`
x-stainless-const: true
search_query:
type: array
items:
type: string
description: The query used for this search.
minItems: 1
data:
type: array
description: The list of search result items.
items:
$ref: '#/components/schemas/VectorStoreSearchResultItem'
has_more:
type: boolean
description: Indicates if there are more results to fetch.
next_page:
type: string
description: The token for the next page, if any.
nullable: true
required:
- object
- search_query
- data
- has_more
- next_page
x-oaiMeta:
name: Vector store search results page
Verbosity:
type: string
enum:
- low
- medium
- high
default: medium
nullable: true
description: |
Constrains the verbosity of the model's response. Lower values will result in
more concise responses, while higher values will result in more verbose responses.
Currently supported values are `low`, `medium`, and `high`.
VoiceIdsShared:
example: ash
anyOf:
- type: string
- type: string
enum:
- alloy
- ash
- ballad
- coral
- echo
- sage
- shimmer
- verse
Wait:
type: object
title: Wait
description: |
A wait action.
properties:
type:
type: string
enum:
- wait
default: wait
description: |
Specifies the event type. For a wait action, this property is
always set to `wait`.
x-stainless-const: true
required:
- type
WebSearchActionFind:
type: object
title: Find action
description: |
Action type "find": Searches for a pattern within a loaded page.
properties:
type:
type: string
enum:
- find
description: |
The action type.
x-stainless-const: true
url:
type: string
format: uri
description: |
The URL of the page searched for the pattern.
pattern:
type: string
description: |
The pattern or text to search for within the page.
required:
- type
- url
- pattern
WebSearchActionOpenPage:
type: object
title: Open page action
description: |
Action type "open_page" - Opens a specific URL from search results.
properties:
type:
type: string
enum:
- open_page
description: |
The action type.
x-stainless-const: true
url:
type: string
format: uri
description: |
The URL opened by the model.
required:
- type
- url
WebSearchActionSearch:
type: object
title: Search action
description: |
Action type "search" - Performs a web search query.
properties:
type:
type: string
enum:
- search
description: |
The action type.
x-stainless-const: true
query:
type: string
description: |
The search query.
required:
- type
- query
WebSearchContextSize:
type: string
description: |
High level guidance for the amount of context window space to use for the
search. One of `low`, `medium`, or `high`. `medium` is the default.
enum:
- low
- medium
- high
default: medium
WebSearchLocation:
type: object
title: Web search location
description: Approximate location parameters for the search.
properties:
country:
type: string
description: |
The two-letter
[ISO country code](https://en.wikipedia.org/wiki/ISO_3166-1) of the user,
e.g. `US`.
region:
type: string
description: |
Free text input for the region of the user, e.g. `California`.
city:
type: string
description: |
Free text input for the city of the user, e.g. `San Francisco`.
timezone:
type: string
description: |
The [IANA timezone](https://timeapi.io/documentation/iana-timezones)
of the user, e.g. `America/Los_Angeles`.
WebSearchToolCall:
type: object
title: Web search tool call
description: |
The results of a web search tool call. See the
[web search guide](https://platform.openai.com/docs/guides/tools-web-search) for more information.
properties:
id:
type: string
description: |
The unique ID of the web search tool call.
type:
type: string
enum:
- web_search_call
description: |
The type of the web search tool call. Always `web_search_call`.
x-stainless-const: true
status:
type: string
description: |
The status of the web search tool call.
enum:
- in_progress
- searching
- completed
- failed
action:
type: object
description: |
An object describing the specific action taken in this web search call.
Includes details on how the model used the web (search, open_page, find).
anyOf:
- $ref: '#/components/schemas/WebSearchActionSearch'
- $ref: '#/components/schemas/WebSearchActionOpenPage'
- $ref: '#/components/schemas/WebSearchActionFind'
discriminator:
propertyName: type
required:
- id
- type
- status
- action
WebhookBatchCancelled:
type: object
title: batch.cancelled
description: |
Sent when a batch API request has been cancelled.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the batch API request was cancelled.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the batch API request.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `batch.cancelled`.
enum:
- batch.cancelled
x-stainless-const: true
x-oaiMeta:
name: batch.cancelled
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "batch.cancelled",
"created_at": 1719168000,
"data": {
"id": "batch_abc123"
}
}
WebhookBatchCompleted:
type: object
title: batch.completed
description: |
Sent when a batch API request has been completed.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the batch API request was completed.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the batch API request.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `batch.completed`.
enum:
- batch.completed
x-stainless-const: true
x-oaiMeta:
name: batch.completed
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "batch.completed",
"created_at": 1719168000,
"data": {
"id": "batch_abc123"
}
}
WebhookBatchExpired:
type: object
title: batch.expired
description: |
Sent when a batch API request has expired.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the batch API request expired.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the batch API request.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `batch.expired`.
enum:
- batch.expired
x-stainless-const: true
x-oaiMeta:
name: batch.expired
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "batch.expired",
"created_at": 1719168000,
"data": {
"id": "batch_abc123"
}
}
WebhookBatchFailed:
type: object
title: batch.failed
description: |
Sent when a batch API request has failed.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the batch API request failed.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the batch API request.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `batch.failed`.
enum:
- batch.failed
x-stainless-const: true
x-oaiMeta:
name: batch.failed
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "batch.failed",
"created_at": 1719168000,
"data": {
"id": "batch_abc123"
}
}
WebhookEvalRunCanceled:
type: object
title: eval.run.canceled
description: |
Sent when an eval run has been canceled.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the eval run was canceled.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the eval run.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `eval.run.canceled`.
enum:
- eval.run.canceled
x-stainless-const: true
x-oaiMeta:
name: eval.run.canceled
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "eval.run.canceled",
"created_at": 1719168000,
"data": {
"id": "evalrun_abc123"
}
}
WebhookEvalRunFailed:
type: object
title: eval.run.failed
description: |
Sent when an eval run has failed.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the eval run failed.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the eval run.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `eval.run.failed`.
enum:
- eval.run.failed
x-stainless-const: true
x-oaiMeta:
name: eval.run.failed
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "eval.run.failed",
"created_at": 1719168000,
"data": {
"id": "evalrun_abc123"
}
}
WebhookEvalRunSucceeded:
type: object
title: eval.run.succeeded
description: |
Sent when an eval run has succeeded.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the eval run succeeded.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the eval run.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `eval.run.succeeded`.
enum:
- eval.run.succeeded
x-stainless-const: true
x-oaiMeta:
name: eval.run.succeeded
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "eval.run.succeeded",
"created_at": 1719168000,
"data": {
"id": "evalrun_abc123"
}
}
WebhookFineTuningJobCancelled:
type: object
title: fine_tuning.job.cancelled
description: |
Sent when a fine-tuning job has been cancelled.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the fine-tuning job was cancelled.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the fine-tuning job.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `fine_tuning.job.cancelled`.
enum:
- fine_tuning.job.cancelled
x-stainless-const: true
x-oaiMeta:
name: fine_tuning.job.cancelled
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "fine_tuning.job.cancelled",
"created_at": 1719168000,
"data": {
"id": "ftjob_abc123"
}
}
WebhookFineTuningJobFailed:
type: object
title: fine_tuning.job.failed
description: |
Sent when a fine-tuning job has failed.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the fine-tuning job failed.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the fine-tuning job.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `fine_tuning.job.failed`.
enum:
- fine_tuning.job.failed
x-stainless-const: true
x-oaiMeta:
name: fine_tuning.job.failed
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "fine_tuning.job.failed",
"created_at": 1719168000,
"data": {
"id": "ftjob_abc123"
}
}
WebhookFineTuningJobSucceeded:
type: object
title: fine_tuning.job.succeeded
description: |
Sent when a fine-tuning job has succeeded.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the fine-tuning job succeeded.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the fine-tuning job.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `fine_tuning.job.succeeded`.
enum:
- fine_tuning.job.succeeded
x-stainless-const: true
x-oaiMeta:
name: fine_tuning.job.succeeded
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "fine_tuning.job.succeeded",
"created_at": 1719168000,
"data": {
"id": "ftjob_abc123"
}
}
WebhookResponseCancelled:
type: object
title: response.cancelled
description: |
Sent when a background response has been cancelled.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the model response was cancelled.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the model response.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `response.cancelled`.
enum:
- response.cancelled
x-stainless-const: true
x-oaiMeta:
name: response.cancelled
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "response.cancelled",
"created_at": 1719168000,
"data": {
"id": "resp_abc123"
}
}
WebhookResponseCompleted:
type: object
title: response.completed
description: |
Sent when a background response has been completed.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the model response was completed.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the model response.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `response.completed`.
enum:
- response.completed
x-stainless-const: true
x-oaiMeta:
name: response.completed
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "response.completed",
"created_at": 1719168000,
"data": {
"id": "resp_abc123"
}
}
WebhookResponseFailed:
type: object
title: response.failed
description: |
Sent when a background response has failed.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the model response failed.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the model response.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `response.failed`.
enum:
- response.failed
x-stainless-const: true
x-oaiMeta:
name: response.failed
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "response.failed",
"created_at": 1719168000,
"data": {
"id": "resp_abc123"
}
}
WebhookResponseIncomplete:
type: object
title: response.incomplete
description: |
Sent when a background response has been interrupted.
required:
- created_at
- id
- data
- type
properties:
created_at:
type: integer
description: |
The Unix timestamp (in seconds) of when the model response was interrupted.
id:
type: string
description: |
The unique ID of the event.
data:
type: object
description: |
Event data payload.
required:
- id
properties:
id:
type: string
description: |
The unique ID of the model response.
object:
type: string
description: |
The object of the event. Always `event`.
enum:
- event
x-stainless-const: true
type:
type: string
description: |
The type of the event. Always `response.incomplete`.
enum:
- response.incomplete
x-stainless-const: true
x-oaiMeta:
name: response.incomplete
group: webhook-events
example: |
{
"id": "evt_abc123",
"type": "response.incomplete",
"created_at": 1719168000,
"data": {
"id": "resp_abc123"
}
}
InputTextContent:
properties:
type:
type: string
enum:
- input_text
description: The type of the input item. Always `input_text`.
default: input_text
x-stainless-const: true
text:
type: string
description: The text input to the model.
type: object
required:
- type
- text
title: Input text
description: A text input to the model.
InputImageContent:
properties:
type:
type: string
enum:
- input_image
description: The type of the input item. Always `input_image`.
default: input_image
x-stainless-const: true
image_url:
anyOf:
- type: string
description: >-
The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in
a data URL.
- type: 'null'
file_id:
anyOf:
- type: string
description: The ID of the file to be sent to the model.
- type: 'null'
detail:
type: string
enum:
- low
- high
- auto
description: >-
The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults
to `auto`.
type: object
required:
- type
- detail
title: Input image
description: >-
An image input to the model. Learn about [image
inputs](https://platform.openai.com/docs/guides/vision).
InputFileContent:
properties:
type:
type: string
enum:
- input_file
description: The type of the input item. Always `input_file`.
default: input_file
x-stainless-const: true
file_id:
anyOf:
- type: string
description: The ID of the file to be sent to the model.
- type: 'null'
filename:
type: string
description: The name of the file to be sent to the model.
file_url:
type: string
description: The URL of the file to be sent to the model.
file_data:
type: string
description: |
The content of the file to be sent to the model.
type: object
required:
- type
title: Input file
description: A file input to the model.
FileCitationBody:
properties:
type:
type: string
enum:
- file_citation
description: The type of the file citation. Always `file_citation`.
default: file_citation
x-stainless-const: true
file_id:
type: string
description: The ID of the file.
index:
type: integer
description: The index of the file in the list of files.
filename:
type: string
description: The filename of the file cited.
type: object
required:
- type
- file_id
- index
- filename
title: File citation
description: A citation to a file.
UrlCitationBody:
properties:
type:
type: string
enum:
- url_citation
description: The type of the URL citation. Always `url_citation`.
default: url_citation
x-stainless-const: true
url:
type: string
description: The URL of the web resource.
start_index:
type: integer
description: The index of the first character of the URL citation in the message.
end_index:
type: integer
description: The index of the last character of the URL citation in the message.
title:
type: string
description: The title of the web resource.
type: object
required:
- type
- url
- start_index
- end_index
- title
title: URL citation
description: A citation for a web resource used to generate a model response.
ContainerFileCitationBody:
properties:
type:
type: string
enum:
- container_file_citation
description: The type of the container file citation. Always `container_file_citation`.
default: container_file_citation
x-stainless-const: true
container_id:
type: string
description: The ID of the container file.
file_id:
type: string
description: The ID of the file.
start_index:
type: integer
description: The index of the first character of the container file citation in the message.
end_index:
type: integer
description: The index of the last character of the container file citation in the message.
filename:
type: string
description: The filename of the container file cited.
type: object
required:
- type
- container_id
- file_id
- start_index
- end_index
- filename
title: Container file citation
description: A citation for a container file used to generate a model response.
Annotation:
discriminator:
propertyName: type
anyOf:
- $ref: '#/components/schemas/FileCitationBody'
- $ref: '#/components/schemas/UrlCitationBody'
- $ref: '#/components/schemas/ContainerFileCitationBody'
- $ref: '#/components/schemas/FilePath'
TopLogProb:
properties:
token:
type: string
logprob:
type: number
bytes:
items:
type: integer
type: array
type: object
required:
- token
- logprob
- bytes
title: Top log probability
description: The top log probability of a token.
LogProb:
properties:
token:
type: string
logprob:
type: number
bytes:
items:
type: integer
type: array
top_logprobs:
items:
$ref: '#/components/schemas/TopLogProb'
type: array
type: object
required:
- token
- logprob
- bytes
- top_logprobs
title: Log probability
description: The log probability of a token.
OutputTextContent:
properties:
type:
type: string
enum:
- output_text
description: The type of the output text. Always `output_text`.
default: output_text
x-stainless-const: true
text:
type: string
description: The text output from the model.
annotations:
items:
$ref: '#/components/schemas/Annotation'
type: array
description: The annotations of the text output.
logprobs:
items:
$ref: '#/components/schemas/LogProb'
type: array
type: object
required:
- type
- text
- annotations
title: Output text
description: A text output from the model.
RefusalContent:
properties:
type:
type: string
enum:
- refusal
description: The type of the refusal. Always `refusal`.
default: refusal
x-stainless-const: true
refusal:
type: string
description: The refusal explanation from the model.
type: object
required:
- type
- refusal
title: Refusal
description: A refusal from the model.
ComputerCallSafetyCheckParam:
properties:
id:
type: string
description: The ID of the pending safety check.
code:
anyOf:
- type: string
description: The type of the pending safety check.
- type: 'null'
message:
anyOf:
- type: string
description: Details about the pending safety check.
- type: 'null'
type: object
required:
- id
description: A pending safety check for the computer call.
ComputerCallOutputItemParam:
properties:
id:
anyOf:
- type: string
description: The ID of the computer tool call output.
- type: 'null'
call_id:
type: string
maxLength: 64
minLength: 1
description: The ID of the computer tool call that produced the output.
type:
type: string
enum:
- computer_call_output
description: The type of the computer tool call output. Always `computer_call_output`.
default: computer_call_output
x-stainless-const: true
output:
$ref: '#/components/schemas/ComputerScreenshotImage'
acknowledged_safety_checks:
anyOf:
- items:
$ref: '#/components/schemas/ComputerCallSafetyCheckParam'
type: array
description: The safety checks reported by the API that have been acknowledged by the developer.
- type: 'null'
status:
anyOf:
- type: string
enum:
- in_progress
- completed
- incomplete
description: >-
The status of the message input. One of `in_progress`, `completed`, or `incomplete`. Populated
when input items are returned via API.
- type: 'null'
type: object
required:
- call_id
- type
- output
title: Computer tool call output
description: The output of a computer tool call.
FunctionCallOutputItemParam:
properties:
id:
anyOf:
- type: string
description: The unique ID of the function tool call output. Populated when this item is returned via API.
- type: 'null'
call_id:
type: string
maxLength: 64
minLength: 1
description: The unique ID of the function tool call generated by the model.
type:
type: string
enum:
- function_call_output
description: The type of the function tool call output. Always `function_call_output`.
default: function_call_output
x-stainless-const: true
output:
type: string
maxLength: 10485760
description: A JSON string of the output of the function tool call.
status:
anyOf:
- type: string
enum:
- in_progress
- completed
- incomplete
description: >-
The status of the item. One of `in_progress`, `completed`, or `incomplete`. Populated when
items are returned via API.
- type: 'null'
type: object
required:
- call_id
- type
- output
title: Function tool call output
description: The output of a function tool call.
ItemReferenceParam:
properties:
type:
anyOf:
- type: string
enum:
- item_reference
description: The type of item to reference. Always `item_reference`.
default: item_reference
x-stainless-const: true
- type: 'null'
id:
type: string
description: The ID of the item to reference.
type: object
required:
- id
title: Item reference
description: An internal identifier for an item to reference.
ConversationResource:
properties:
id:
type: string
description: The unique ID of the conversation.
object:
type: string
enum:
- conversation
description: The object type, which is always `conversation`.
default: conversation
x-stainless-const: true
metadata:
description: >-
Set of 16 key-value pairs that can be attached to an object. This can be useful for
storing additional information about the object in a structured format, and querying for
objects via API or the dashboard.
Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.
created_at:
type: integer
description: The time at which the conversation was created, measured in seconds since the Unix epoch.
type: object
required:
- id
- object
- metadata
- created_at
MetadataParam:
additionalProperties:
type: string
maxLength: 512
type: object
maxProperties: 16
UpdateConversationBody:
properties:
metadata:
$ref: '#/components/schemas/MetadataParam'
description: >-
Set of 16 key-value pairs that can be attached to an object. This can be useful for
storing additional information about the object in a structured format, and querying for
objects via API or the dashboard.
Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.
type: object
required:
- metadata
DeletedConversationResource:
properties:
object:
type: string
enum:
- conversation.deleted
default: conversation.deleted
x-stainless-const: true
deleted:
type: boolean
id:
type: string
type: object
required:
- object
- deleted
- id
InputTextContent-2:
properties:
type:
type: string
enum:
- input_text
description: The type of the input item. Always `input_text`.
default: input_text
x-stainless-const: true
text:
type: string
description: The text input to the model.
type: object
required:
- type
- text
title: Input text
FileCitationBody-2:
properties:
type:
type: string
enum:
- file_citation
description: The type of the file citation. Always `file_citation`.
default: file_citation
x-stainless-const: true
file_id:
type: string
description: The ID of the file.
index:
type: integer
description: The index of the file in the list of files.
filename:
type: string
description: The filename of the file cited.
type: object
required:
- type
- file_id
- index
- filename
title: File citation
UrlCitationBody-2:
properties:
type:
type: string
enum:
- url_citation
description: The type of the URL citation. Always `url_citation`.
default: url_citation
x-stainless-const: true
url:
type: string
description: The URL of the web resource.
start_index:
type: integer
description: The index of the first character of the URL citation in the message.
end_index:
type: integer
description: The index of the last character of the URL citation in the message.
title:
type: string
description: The title of the web resource.
type: object
required:
- type
- url
- start_index
- end_index
- title
title: URL citation
ContainerFileCitationBody-2:
properties:
type:
type: string
enum:
- container_file_citation
description: The type of the container file citation. Always `container_file_citation`.
default: container_file_citation
x-stainless-const: true
container_id:
type: string
description: The ID of the container file.
file_id:
type: string
description: The ID of the file.
start_index:
type: integer
description: The index of the first character of the container file citation in the message.
end_index:
type: integer
description: The index of the last character of the container file citation in the message.
filename:
type: string
description: The filename of the container file cited.
type: object
required:
- type
- container_id
- file_id
- start_index
- end_index
- filename
title: Container file citation
Annotation-2:
discriminator:
propertyName: type
anyOf:
- $ref: '#/components/schemas/FileCitationBody-2'
- $ref: '#/components/schemas/UrlCitationBody-2'
- $ref: '#/components/schemas/ContainerFileCitationBody-2'
TopLogProb-2:
properties:
token:
type: string
logprob:
type: number
bytes:
items:
type: integer
type: array
type: object
required:
- token
- logprob
- bytes
title: Top log probability
LogProb-2:
properties:
token:
type: string
logprob:
type: number
bytes:
items:
type: integer
type: array
top_logprobs:
items:
$ref: '#/components/schemas/TopLogProb-2'
type: array
type: object
required:
- token
- logprob
- bytes
- top_logprobs
title: Log probability
OutputTextContent-2:
properties:
type:
type: string
enum:
- output_text
description: The type of the output text. Always `output_text`.
default: output_text
x-stainless-const: true
text:
type: string
description: The text output from the model.
annotations:
items:
$ref: '#/components/schemas/Annotation-2'
type: array
description: The annotations of the text output.
logprobs:
items:
$ref: '#/components/schemas/LogProb-2'
type: array
type: object
required:
- type
- text
- annotations
title: Output text
TextContent:
properties:
type:
type: string
enum:
- text
default: text
x-stainless-const: true
text:
type: string
type: object
required:
- type
- text
title: Text Content
SummaryTextContent:
properties:
type:
type: string
enum:
- summary_text
default: summary_text
x-stainless-const: true
text:
type: string
type: object
required:
- type
- text
title: Summary text
RefusalContent-2:
properties:
type:
type: string
enum:
- refusal
description: The type of the refusal. Always `refusal`.
default: refusal
x-stainless-const: true
refusal:
type: string
description: The refusal explanation from the model.
type: object
required:
- type
- refusal
title: Refusal
InputImageContent-2:
properties:
type:
type: string
enum:
- input_image
description: The type of the input item. Always `input_image`.
default: input_image
x-stainless-const: true
image_url:
anyOf:
- type: string
description: >-
The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in
a data URL.
- type: 'null'
file_id:
anyOf:
- type: string
description: The ID of the file to be sent to the model.
- type: 'null'
detail:
type: string
enum:
- low
- high
- auto
description: >-
The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults
to `auto`.
type: object
required:
- type
- image_url
- file_id
- detail
title: Input image
ComputerScreenshotContent:
properties:
type:
type: string
enum:
- computer_screenshot
description: >-
Specifies the event type. For a computer screenshot, this property is always set to
`computer_screenshot`.
default: computer_screenshot
x-stainless-const: true
image_url:
anyOf:
- type: string
description: The URL of the screenshot image.
- type: 'null'
file_id:
anyOf:
- type: string
description: The identifier of an uploaded file that contains the screenshot.
- type: 'null'
type: object
required:
- type
- image_url
- file_id
title: Computer screenshot
InputFileContent-2:
properties:
type:
type: string
enum:
- input_file
description: The type of the input item. Always `input_file`.
default: input_file
x-stainless-const: true
file_id:
anyOf:
- type: string
description: The ID of the file to be sent to the model.
- type: 'null'
filename:
type: string
description: The name of the file to be sent to the model.
file_url:
type: string
description: The URL of the file to be sent to the model.
type: object
required:
- type
- file_id
title: Input file
Message:
properties:
type:
type: string
enum:
- message
description: The type of the message. Always set to `message`.
default: message
x-stainless-const: true
id:
type: string
description: The unique ID of the message.
status:
type: string
enum:
- in_progress
- completed
- incomplete
description: >-
The status of item. One of `in_progress`, `completed`, or `incomplete`. Populated when items are
returned via API.
role:
type: string
enum:
- unknown
- user
- assistant
- system
- critic
- discriminator
- developer
- tool
description: >-
The role of the message. One of `unknown`, `user`, `assistant`, `system`, `critic`,
`discriminator`, `developer`, or `tool`.
content:
items:
discriminator:
propertyName: type
anyOf:
- $ref: '#/components/schemas/InputTextContent-2'
- $ref: '#/components/schemas/OutputTextContent-2'
- $ref: '#/components/schemas/TextContent'
- $ref: '#/components/schemas/SummaryTextContent'
- $ref: '#/components/schemas/RefusalContent-2'
- $ref: '#/components/schemas/InputImageContent-2'
- $ref: '#/components/schemas/ComputerScreenshotContent'
- $ref: '#/components/schemas/InputFileContent-2'
type: array
description: The content of the message
type: object
required:
- type
- id
- status
- role
- content
title: Message
FunctionTool:
properties:
type:
type: string
enum:
- function
description: The type of the function tool. Always `function`.
default: function
x-stainless-const: true
name:
type: string
description: The name of the function to call.
description:
anyOf:
- type: string
description: >-
A description of the function. Used by the model to determine whether or not to call the
function.
- type: 'null'
parameters:
anyOf:
- additionalProperties: {}
type: object
description: A JSON schema object describing the parameters of the function.
- type: 'null'
strict:
anyOf:
- type: boolean
description: Whether to enforce strict parameter validation. Default `true`.
- type: 'null'
type: object
required:
- type
- name
- strict
- parameters
title: Function
description: >-
Defines a function in your own code the model can choose to call. Learn more about [function
calling](https://platform.openai.com/docs/guides/function-calling).
RankingOptions:
properties:
ranker:
type: string
enum:
- auto
- default-2024-11-15
description: The ranker to use for the file search.
score_threshold:
type: number
description: >-
The score threshold for the file search, a number between 0 and 1. Numbers closer to 1 will
attempt to return only the most relevant results, but may return fewer results.
type: object
required: []
Filters:
anyOf:
- $ref: '#/components/schemas/ComparisonFilter'
- $ref: '#/components/schemas/CompoundFilter'
FileSearchTool:
properties:
type:
type: string
enum:
- file_search
description: The type of the file search tool. Always `file_search`.
default: file_search
x-stainless-const: true
vector_store_ids:
items:
type: string
type: array
description: The IDs of the vector stores to search.
max_num_results:
type: integer
description: The maximum number of results to return. This number should be between 1 and 50 inclusive.
ranking_options:
$ref: '#/components/schemas/RankingOptions'
description: Ranking options for search.
filters:
anyOf:
- $ref: '#/components/schemas/Filters'
description: A filter to apply.
- type: 'null'
type: object
required:
- type
- vector_store_ids
title: File search
description: >-
A tool that searches for relevant content from uploaded files. Learn more about the [file search
tool](https://platform.openai.com/docs/guides/tools-file-search).
ApproximateLocation:
properties:
type:
type: string
enum:
- approximate
description: The type of location approximation. Always `approximate`.
default: approximate
x-stainless-const: true
country:
anyOf:
- type: string
description: >-
The two-letter [ISO country code](https://en.wikipedia.org/wiki/ISO_3166-1) of the user, e.g.
`US`.
- type: 'null'
region:
anyOf:
- type: string
description: Free text input for the region of the user, e.g. `California`.
- type: 'null'
city:
anyOf:
- type: string
description: Free text input for the city of the user, e.g. `San Francisco`.
- type: 'null'
timezone:
anyOf:
- type: string
description: >-
The [IANA timezone](https://timeapi.io/documentation/iana-timezones) of the user, e.g.
`America/Los_Angeles`.
- type: 'null'
type: object
required:
- type
WebSearchPreviewTool:
properties:
type:
type: string
enum:
- web_search_preview
- web_search_preview_2025_03_11
description: The type of the web search tool. One of `web_search_preview` or `web_search_preview_2025_03_11`.
default: web_search_preview
x-stainless-const: true
user_location:
anyOf:
- $ref: '#/components/schemas/ApproximateLocation'
description: The user's location.
- type: 'null'
search_context_size:
type: string
enum:
- low
- medium
- high
description: >-
High level guidance for the amount of context window space to use for the search. One of `low`,
`medium`, or `high`. `medium` is the default.
type: object
required:
- type
title: Web search preview
description: >-
This tool searches the web for relevant results to use in a response. Learn more about the [web search
tool](https://platform.openai.com/docs/guides/tools-web-search).
ComputerUsePreviewTool:
properties:
type:
type: string
enum:
- computer_use_preview
description: The type of the computer use tool. Always `computer_use_preview`.
default: computer_use_preview
x-stainless-const: true
environment:
type: string
enum:
- windows
- mac
- linux
- ubuntu
- browser
description: The type of computer environment to control.
display_width:
type: integer
description: The width of the computer display.
display_height:
type: integer
description: The height of the computer display.
type: object
required:
- type
- environment
- display_width
- display_height
title: Computer use preview
description: >-
A tool that controls a virtual computer. Learn more about the [computer
tool](https://platform.openai.com/docs/guides/tools-computer-use).
ImageGenInputUsageDetails:
properties:
text_tokens:
type: integer
description: The number of text tokens in the input prompt.
image_tokens:
type: integer
description: The number of image tokens in the input prompt.
type: object
required:
- text_tokens
- image_tokens
title: Input usage details
description: The input tokens detailed information for the image generation.
ImageGenUsage:
properties:
input_tokens:
type: integer
description: The number of tokens (images and text) in the input prompt.
total_tokens:
type: integer
description: The total number of tokens (images and text) used for the image generation.
output_tokens:
type: integer
description: The number of output tokens generated by the model.
input_tokens_details:
$ref: '#/components/schemas/ImageGenInputUsageDetails'
type: object
required:
- input_tokens
- total_tokens
- output_tokens
- input_tokens_details
title: Image generation usage
description: For `gpt-image-1` only, the token usage information for the image generation.
ConversationParam:
properties:
id:
type: string
description: The unique ID of the conversation.
type: object
required:
- id
title: Conversation object
description: The conversation that this response belongs to.
Conversation-2:
properties:
id:
type: string
description: The unique ID of the conversation.
type: object
required:
- id
title: Conversation
description: >-
The conversation that this response belongs to. Input items and output items from this response are
automatically added to this conversation.
RealtimeConversationItemContent:
type: object
properties:
type:
type: string
enum:
- input_text
- input_audio
- item_reference
- text
- audio
description: |
The content type (`input_text`, `input_audio`, `item_reference`, `text`, `audio`).
text:
type: string
description: |
The text content, used for `input_text` and `text` content types.
id:
type: string
description: |
ID of a previous conversation item to reference (for `item_reference`
content types in `response.create` events). These can reference both
client and server created items.
audio:
type: string
description: |
Base64-encoded audio bytes, used for `input_audio` content type.
transcript:
type: string
description: |
The transcript of the audio, used for `input_audio` and `audio`
content types.
RealtimeConnectParams:
type: object
properties:
model:
type: string
required:
- model
ModerationImageURLInput:
type: object
description: An object describing an image to classify.
properties:
type:
description: Always `image_url`.
type: string
enum:
- image_url
x-stainless-const: true
image_url:
type: object
description: Contains either an image URL or a data URL for a base64 encoded image.
properties:
url:
type: string
description: Either a URL of the image or the base64 encoded image data.
format: uri
example: https://example.com/image.jpg
required:
- url
required:
- type
- image_url
ModerationTextInput:
type: object
description: An object describing text to classify.
properties:
type:
description: Always `text`.
type: string
enum:
- text
x-stainless-const: true
text:
description: A string of text to classify.
type: string
example: I want to kill them
required:
- type
- text
ChunkingStrategyResponse:
type: object
description: The strategy used to chunk the file.
anyOf:
- $ref: '#/components/schemas/StaticChunkingStrategyResponseParam'
- $ref: '#/components/schemas/OtherChunkingStrategyResponseParam'
discriminator:
propertyName: type
FilePurpose:
description: >
The intended purpose of the uploaded file. One of: - `assistants`: Used in the Assistants API -
`batch`: Used in the Batch API - `fine-tune`: Used for fine-tuning - `vision`: Images used for vision
fine-tuning - `user_data`: Flexible file type for any purpose - `evals`: Used for eval data sets
type: string
enum:
- assistants
- batch
- fine-tune
- vision
- user_data
- evals
BatchError:
type: object
properties:
code:
type: string
description: An error code identifying the error type.
message:
type: string
description: A human-readable message providing more details about the error.
param:
type: string
description: The name of the parameter that caused the error, if applicable.
nullable: true
line:
type: integer
description: The line number of the input file where the error occurred, if applicable.
nullable: true
BatchRequestCounts:
type: object
properties:
total:
type: integer
description: Total number of requests in the batch.
completed:
type: integer
description: Number of requests that have been completed successfully.
failed:
type: integer
description: Number of requests that have failed.
required:
- total
- completed
- failed
description: The request counts for different statuses within the batch.
AssistantTool:
anyOf:
- $ref: '#/components/schemas/AssistantToolsCode'
- $ref: '#/components/schemas/AssistantToolsFileSearch'
- $ref: '#/components/schemas/AssistantToolsFunction'
discriminator:
propertyName: type
TextAnnotationDelta:
anyOf:
- $ref: '#/components/schemas/MessageDeltaContentTextAnnotationsFileCitationObject'
- $ref: '#/components/schemas/MessageDeltaContentTextAnnotationsFilePathObject'
discriminator:
propertyName: type
TextAnnotation:
anyOf:
- $ref: '#/components/schemas/MessageContentTextAnnotationsFileCitationObject'
- $ref: '#/components/schemas/MessageContentTextAnnotationsFilePathObject'
discriminator:
propertyName: type
RunStepDetailsToolCall:
anyOf:
- $ref: '#/components/schemas/RunStepDetailsToolCallsCodeObject'
- $ref: '#/components/schemas/RunStepDetailsToolCallsFileSearchObject'
- $ref: '#/components/schemas/RunStepDetailsToolCallsFunctionObject'
discriminator:
propertyName: type
RunStepDeltaStepDetailsToolCall:
anyOf:
- $ref: '#/components/schemas/RunStepDeltaStepDetailsToolCallsCodeObject'
- $ref: '#/components/schemas/RunStepDeltaStepDetailsToolCallsFileSearchObject'
- $ref: '#/components/schemas/RunStepDeltaStepDetailsToolCallsFunctionObject'
discriminator:
propertyName: type
MessageContent:
anyOf:
- $ref: '#/components/schemas/MessageContentImageFileObject'
- $ref: '#/components/schemas/MessageContentImageUrlObject'
- $ref: '#/components/schemas/MessageContentTextObject'
- $ref: '#/components/schemas/MessageContentRefusalObject'
discriminator:
propertyName: type
MessageContentDelta:
anyOf:
- $ref: '#/components/schemas/MessageDeltaContentImageFileObject'
- $ref: '#/components/schemas/MessageDeltaContentTextObject'
- $ref: '#/components/schemas/MessageDeltaContentRefusalObject'
- $ref: '#/components/schemas/MessageDeltaContentImageUrlObject'
discriminator:
propertyName: type
ChatModel:
type: string
enum:
- gpt-5
- gpt-5-mini
- gpt-5-nano
- gpt-5-2025-08-07
- gpt-5-mini-2025-08-07
- gpt-5-nano-2025-08-07
- gpt-5-chat-latest
- gpt-4.1
- gpt-4.1-mini
- gpt-4.1-nano
- gpt-4.1-2025-04-14
- gpt-4.1-mini-2025-04-14
- gpt-4.1-nano-2025-04-14
- o4-mini
- o4-mini-2025-04-16
- o3
- o3-2025-04-16
- o3-mini
- o3-mini-2025-01-31
- o1
- o1-2024-12-17
- o1-preview
- o1-preview-2024-09-12
- o1-mini
- o1-mini-2024-09-12
- gpt-4o
- gpt-4o-2024-11-20
- gpt-4o-2024-08-06
- gpt-4o-2024-05-13
- gpt-4o-audio-preview
- gpt-4o-audio-preview-2024-10-01
- gpt-4o-audio-preview-2024-12-17
- gpt-4o-audio-preview-2025-06-03
- gpt-4o-mini-audio-preview
- gpt-4o-mini-audio-preview-2024-12-17
- gpt-4o-search-preview
- gpt-4o-mini-search-preview
- gpt-4o-search-preview-2025-03-11
- gpt-4o-mini-search-preview-2025-03-11
- chatgpt-4o-latest
- codex-mini-latest
- gpt-4o-mini
- gpt-4o-mini-2024-07-18
- gpt-4-turbo
- gpt-4-turbo-2024-04-09
- gpt-4-0125-preview
- gpt-4-turbo-preview
- gpt-4-1106-preview
- gpt-4-vision-preview
- gpt-4
- gpt-4-0314
- gpt-4-0613
- gpt-4-32k
- gpt-4-32k-0314
- gpt-4-32k-0613
- gpt-3.5-turbo
- gpt-3.5-turbo-16k
- gpt-3.5-turbo-0301
- gpt-3.5-turbo-0613
- gpt-3.5-turbo-1106
- gpt-3.5-turbo-0125
- gpt-3.5-turbo-16k-0613
x-stainless-nominal: false
CreateThreadAndRunRequestWithoutStream:
type: object
additionalProperties: false
properties:
assistant_id:
description: >-
The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) to use to
execute this run.
type: string
thread:
$ref: '#/components/schemas/CreateThreadRequest'
model:
description: >-
The ID of the [Model](https://platform.openai.com/docs/api-reference/models) to be used to execute
this run. If a value is provided here, it will override the model associated with the assistant.
If not, the model associated with the assistant will be used.
anyOf:
- type: string
- type: string
enum:
- gpt-5
- gpt-5-mini
- gpt-5-nano
- gpt-5-2025-08-07
- gpt-5-mini-2025-08-07
- gpt-5-nano-2025-08-07
- gpt-4.1
- gpt-4.1-mini
- gpt-4.1-nano
- gpt-4.1-2025-04-14
- gpt-4.1-mini-2025-04-14
- gpt-4.1-nano-2025-04-14
- gpt-4o
- gpt-4o-2024-11-20
- gpt-4o-2024-08-06
- gpt-4o-2024-05-13
- gpt-4o-mini
- gpt-4o-mini-2024-07-18
- gpt-4.5-preview
- gpt-4.5-preview-2025-02-27
- gpt-4-turbo
- gpt-4-turbo-2024-04-09
- gpt-4-0125-preview
- gpt-4-turbo-preview
- gpt-4-1106-preview
- gpt-4-vision-preview
- gpt-4
- gpt-4-0314
- gpt-4-0613
- gpt-4-32k
- gpt-4-32k-0314
- gpt-4-32k-0613
- gpt-3.5-turbo
- gpt-3.5-turbo-16k
- gpt-3.5-turbo-0613
- gpt-3.5-turbo-1106
- gpt-3.5-turbo-0125
- gpt-3.5-turbo-16k-0613
x-oaiTypeLabel: string
nullable: true
instructions:
description: >-
Override the default system message of the assistant. This is useful for modifying the behavior on
a per-run basis.
type: string
nullable: true
tools:
description: >-
Override the tools the assistant can use for this run. This is useful for modifying the behavior
on a per-run basis.
nullable: true
type: array
maxItems: 20
items:
$ref: '#/components/schemas/AssistantTool'
tool_resources:
type: object
description: >
A set of resources that are used by the assistant's tools. The resources are specific to the type
of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the
`file_search` tool requires a list of vector store IDs.
properties:
code_interpreter:
type: object
properties:
file_ids:
type: array
description: >
A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available
to the `code_interpreter` tool. There can be a maximum of 20 files associated with the
tool.
default: []
maxItems: 20
items:
type: string
file_search:
type: object
properties:
vector_store_ids:
type: array
description: >
The ID of the [vector
store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to
this assistant. There can be a maximum of 1 vector store attached to the assistant.
maxItems: 1
items:
type: string
nullable: true
metadata:
$ref: '#/components/schemas/Metadata'
temperature:
type: number
minimum: 0
maximum: 2
default: 1
example: 1
nullable: true
description: >
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
more random, while lower values like 0.2 will make it more focused and deterministic.
top_p:
type: number
minimum: 0
maximum: 1
default: 1
example: 1
nullable: true
description: >
An alternative to sampling with temperature, called nucleus sampling, where the model considers
the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
max_prompt_tokens:
type: integer
nullable: true
description: >
The maximum number of prompt tokens that may be used over the course of the run. The run will make
a best effort to use only the number of prompt tokens specified, across multiple turns of the run.
If the run exceeds the number of prompt tokens specified, the run will end with status
`incomplete`. See `incomplete_details` for more info.
minimum: 256
max_completion_tokens:
type: integer
nullable: true
description: >
The maximum number of completion tokens that may be used over the course of the run. The run will
make a best effort to use only the number of completion tokens specified, across multiple turns of
the run. If the run exceeds the number of completion tokens specified, the run will end with
status `incomplete`. See `incomplete_details` for more info.
minimum: 256
truncation_strategy:
allOf:
- $ref: '#/components/schemas/TruncationObject'
- nullable: true
tool_choice:
allOf:
- $ref: '#/components/schemas/AssistantsApiToolChoiceOption'
- nullable: true
parallel_tool_calls:
$ref: '#/components/schemas/ParallelToolCalls'
response_format:
$ref: '#/components/schemas/AssistantsApiResponseFormatOption'
nullable: true
required: *ref_0
CreateRunRequestWithoutStream:
type: object
additionalProperties: false
properties:
assistant_id:
description: >-
The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) to use to
execute this run.
type: string
model:
description: >-
The ID of the [Model](https://platform.openai.com/docs/api-reference/models) to be used to execute
this run. If a value is provided here, it will override the model associated with the assistant.
If not, the model associated with the assistant will be used.
anyOf:
- type: string
- $ref: '#/components/schemas/AssistantSupportedModels'
x-oaiTypeLabel: string
nullable: true
reasoning_effort:
$ref: '#/components/schemas/ReasoningEffort'
instructions:
description: >-
Overrides the
[instructions](https://platform.openai.com/docs/api-reference/assistants/createAssistant) of the
assistant. This is useful for modifying the behavior on a per-run basis.
type: string
nullable: true
additional_instructions:
description: >-
Appends additional instructions at the end of the instructions for the run. This is useful for
modifying the behavior on a per-run basis without overriding other instructions.
type: string
nullable: true
additional_messages:
description: Adds additional messages to the thread before creating the run.
type: array
items:
$ref: '#/components/schemas/CreateMessageRequest'
nullable: true
tools:
description: >-
Override the tools the assistant can use for this run. This is useful for modifying the behavior
on a per-run basis.
nullable: true
type: array
maxItems: 20
items:
$ref: '#/components/schemas/AssistantTool'
metadata:
$ref: '#/components/schemas/Metadata'
temperature:
type: number
minimum: 0
maximum: 2
default: 1
example: 1
nullable: true
description: >
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
more random, while lower values like 0.2 will make it more focused and deterministic.
top_p:
type: number
minimum: 0
maximum: 1
default: 1
example: 1
nullable: true
description: >
An alternative to sampling with temperature, called nucleus sampling, where the model considers
the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
max_prompt_tokens:
type: integer
nullable: true
description: >
The maximum number of prompt tokens that may be used over the course of the run. The run will make
a best effort to use only the number of prompt tokens specified, across multiple turns of the run.
If the run exceeds the number of prompt tokens specified, the run will end with status
`incomplete`. See `incomplete_details` for more info.
minimum: 256
max_completion_tokens:
type: integer
nullable: true
description: >
The maximum number of completion tokens that may be used over the course of the run. The run will
make a best effort to use only the number of completion tokens specified, across multiple turns of
the run. If the run exceeds the number of completion tokens specified, the run will end with
status `incomplete`. See `incomplete_details` for more info.
minimum: 256
truncation_strategy:
allOf:
- $ref: '#/components/schemas/TruncationObject'
- nullable: true
tool_choice:
allOf:
- $ref: '#/components/schemas/AssistantsApiToolChoiceOption'
- nullable: true
parallel_tool_calls:
$ref: '#/components/schemas/ParallelToolCalls'
response_format:
$ref: '#/components/schemas/AssistantsApiResponseFormatOption'
nullable: true
required: *ref_0
SubmitToolOutputsRunRequestWithoutStream:
type: object
additionalProperties: false
properties:
tool_outputs:
description: A list of tools for which the outputs are being submitted.
type: array
items:
type: object
properties:
tool_call_id:
type: string
description: >-
The ID of the tool call in the `required_action` object within the run object the output is
being submitted for.
output:
type: string
description: The output of the tool call to be submitted to continue the run.
required:
- tool_outputs
RunStatus:
description: >-
The status of the run, which can be either `queued`, `in_progress`, `requires_action`, `cancelling`,
`cancelled`, `failed`, `completed`, `incomplete`, or `expired`.
type: string
enum:
- queued
- in_progress
- requires_action
- cancelling
- cancelled
- failed
- completed
- incomplete
- expired
RunStepDeltaObjectDelta:
description: The delta containing the fields that have changed on the run step.
type: object
properties:
step_details:
type: object
description: The details of the run step.
anyOf:
- $ref: '#/components/schemas/RunStepDeltaStepDetailsMessageCreationObject'
- $ref: '#/components/schemas/RunStepDeltaStepDetailsToolCallsObject'
discriminator:
propertyName: type
securitySchemes:
ApiKeyAuth:
type: http
scheme: bearer
x-oaiMeta:
navigationGroups:
- id: responses
title: Responses API
- id: webhooks
title: Webhooks
- id: endpoints
title: Platform APIs
- id: vector_stores
title: Vector stores
- id: containers
title: Containers
- id: realtime
title: Realtime
beta: true
- id: chat
title: Chat Completions
- id: assistants
title: Assistants
beta: true
- id: administration
title: Administration
- id: legacy
title: Legacy
groups:
- id: responses
title: Responses
description: |
OpenAI's most advanced interface for generating model responses. Supports
text and image inputs, and text outputs. Create stateful interactions
with the model, using the output of previous responses as input. Extend
the model's capabilities with built-in tools for file search, web search,
computer use, and more. Allow the model access to external systems and data
using function calling.
Related guides:
- [Quickstart](https://platform.openai.com/docs/quickstart?api-mode=responses)
- [Text inputs and outputs](https://platform.openai.com/docs/guides/text?api-mode=responses)
- [Image inputs](https://platform.openai.com/docs/guides/images?api-mode=responses)
- [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs?api-mode=responses)
- [Function calling](https://platform.openai.com/docs/guides/function-calling?api-mode=responses)
- [Conversation state](https://platform.openai.com/docs/guides/conversation-state?api-mode=responses)
- [Extend the models with tools](https://platform.openai.com/docs/guides/tools?api-mode=responses)
navigationGroup: responses
sections:
- type: endpoint
key: createResponse
path: create
- type: endpoint
key: getResponse
path: get
- type: endpoint
key: deleteResponse
path: delete
- type: endpoint
key: cancelResponse
path: cancel
- type: endpoint
key: listInputItems
path: input-items
- type: object
key: Response
path: object
- type: object
key: ResponseItemList
path: list
- id: conversations
title: Conversations
description: |
Create and manage conversations to store and retrieve conversation state across Response API calls.
navigationGroup: responses
sections:
- type: endpoint
key: createConversation
path: create
- type: endpoint
key: getConversation
path: retrieve
- type: endpoint
key: updateConversation
path: update
- type: endpoint
key: deleteConversation
path: delete
- type: endpoint
key: listConversationItems
path: list-items
- type: endpoint
key: createConversationItems
path: create-items
- type: endpoint
key: getConversationItem
path: get-item
- type: endpoint
key: deleteConversationItem
path: delete-item
- type: object
key: Conversation
path: object
- type: object
key: ConversationItemList
path: list-items-object
- id: responses-streaming
title: Streaming events
description: >
When you [create a Response](https://platform.openai.com/docs/api-reference/responses/create) with
`stream` set to `true`, the server will emit server-sent events to the
client as the Response is generated. This section contains the events that
are emitted by the server.
[Learn more about streaming
responses](https://platform.openai.com/docs/guides/streaming-responses?api-mode=responses).
navigationGroup: responses
sections:
- type: object
key: ResponseCreatedEvent
path: <auto>
- type: object
key: ResponseInProgressEvent
path: <auto>
- type: object
key: ResponseCompletedEvent
path: <auto>
- type: object
key: ResponseFailedEvent
path: <auto>
- type: object
key: ResponseIncompleteEvent
path: <auto>
- type: object
key: ResponseOutputItemAddedEvent
path: <auto>
- type: object
key: ResponseOutputItemDoneEvent
path: <auto>
- type: object
key: ResponseContentPartAddedEvent
path: <auto>
- type: object
key: ResponseContentPartDoneEvent
path: <auto>
- type: object
key: ResponseTextDeltaEvent
path: response/output_text/delta
- type: object
key: ResponseTextDoneEvent
path: response/output_text/done
- type: object
key: ResponseRefusalDeltaEvent
path: <auto>
- type: object
key: ResponseRefusalDoneEvent
path: <auto>
- type: object
key: ResponseFunctionCallArgumentsDeltaEvent
path: <auto>
- type: object
key: ResponseFunctionCallArgumentsDoneEvent
path: <auto>
- type: object
key: ResponseFileSearchCallInProgressEvent
path: <auto>
- type: object
key: ResponseFileSearchCallSearchingEvent
path: <auto>
- type: object
key: ResponseFileSearchCallCompletedEvent
path: <auto>
- type: object
key: ResponseWebSearchCallInProgressEvent
path: <auto>
- type: object
key: ResponseWebSearchCallSearchingEvent
path: <auto>
- type: object
key: ResponseWebSearchCallCompletedEvent
path: <auto>
- type: object
key: ResponseReasoningSummaryPartAddedEvent
path: <auto>
- type: object
key: ResponseReasoningSummaryPartDoneEvent
path: <auto>
- type: object
key: ResponseReasoningSummaryTextDeltaEvent
path: <auto>
- type: object
key: ResponseReasoningSummaryTextDoneEvent
path: <auto>
- type: object
key: ResponseReasoningTextDeltaEvent
path: <auto>
- type: object
key: ResponseReasoningTextDoneEvent
path: <auto>
- type: object
key: ResponseImageGenCallCompletedEvent
path: <auto>
- type: object
key: ResponseImageGenCallGeneratingEvent
path: <auto>
- type: object
key: ResponseImageGenCallInProgressEvent
path: <auto>
- type: object
key: ResponseImageGenCallPartialImageEvent
path: <auto>
- type: object
key: ResponseMCPCallArgumentsDeltaEvent
path: <auto>
- type: object
key: ResponseMCPCallArgumentsDoneEvent
path: <auto>
- type: object
key: ResponseMCPCallCompletedEvent
path: <auto>
- type: object
key: ResponseMCPCallFailedEvent
path: <auto>
- type: object
key: ResponseMCPCallInProgressEvent
path: <auto>
- type: object
key: ResponseMCPListToolsCompletedEvent
path: <auto>
- type: object
key: ResponseMCPListToolsFailedEvent
path: <auto>
- type: object
key: ResponseMCPListToolsInProgressEvent
path: <auto>
- type: object
key: ResponseCodeInterpreterCallInProgressEvent
path: <auto>
- type: object
key: ResponseCodeInterpreterCallInterpretingEvent
path: <auto>
- type: object
key: ResponseCodeInterpreterCallCompletedEvent
path: <auto>
- type: object
key: ResponseCodeInterpreterCallCodeDeltaEvent
path: <auto>
- type: object
key: ResponseCodeInterpreterCallCodeDoneEvent
path: <auto>
- type: object
key: ResponseOutputTextAnnotationAddedEvent
path: <auto>
- type: object
key: ResponseQueuedEvent
path: <auto>
- type: object
key: ResponseCustomToolCallInputDeltaEvent
path: <auto>
- type: object
key: ResponseCustomToolCallInputDoneEvent
path: <auto>
- type: object
key: ResponseErrorEvent
path: <auto>
- id: webhook-events
title: Webhook Events
description: |
Webhooks are HTTP requests sent by OpenAI to a URL you specify when certain
events happen during the course of API usage.
[Learn more about webhooks](https://platform.openai.com/docs/guides/webhooks).
navigationGroup: webhooks
sections:
- type: object
key: WebhookResponseCompleted
path: <auto>
- type: object
key: WebhookResponseCancelled
path: <auto>
- type: object
key: WebhookResponseFailed
path: <auto>
- type: object
key: WebhookResponseIncomplete
path: <auto>
- type: object
key: WebhookBatchCompleted
path: <auto>
- type: object
key: WebhookBatchCancelled
path: <auto>
- type: object
key: WebhookBatchExpired
path: <auto>
- type: object
key: WebhookBatchFailed
path: <auto>
- type: object
key: WebhookFineTuningJobSucceeded
path: <auto>
- type: object
key: WebhookFineTuningJobFailed
path: <auto>
- type: object
key: WebhookFineTuningJobCancelled
path: <auto>
- type: object
key: WebhookEvalRunSucceeded
path: <auto>
- type: object
key: WebhookEvalRunFailed
path: <auto>
- type: object
key: WebhookEvalRunCanceled
path: <auto>
- id: audio
title: Audio
description: |
Learn how to turn audio into text or text into audio.
Related guide: [Speech to text](https://platform.openai.com/docs/guides/speech-to-text)
navigationGroup: endpoints
sections:
- type: endpoint
key: createSpeech
path: createSpeech
- type: endpoint
key: createTranscription
path: createTranscription
- type: endpoint
key: createTranslation
path: createTranslation
- type: object
key: CreateTranscriptionResponseJson
path: json-object
- type: object
key: CreateTranscriptionResponseVerboseJson
path: verbose-json-object
- type: object
key: SpeechAudioDeltaEvent
path: speech-audio-delta-event
- type: object
key: SpeechAudioDoneEvent
path: speech-audio-done-event
- type: object
key: TranscriptTextDeltaEvent
path: transcript-text-delta-event
- type: object
key: TranscriptTextDoneEvent
path: transcript-text-done-event
- id: images
title: Images
description: |
Given a prompt and/or an input image, the model will generate a new image.
Related guide: [Image generation](https://platform.openai.com/docs/guides/images)
navigationGroup: endpoints
sections:
- type: endpoint
key: createImage
path: create
- type: endpoint
key: createImageEdit
path: createEdit
- type: endpoint
key: createImageVariation
path: createVariation
- type: object
key: ImagesResponse
path: object
- id: images-streaming
title: Image Streaming
description: |
Stream image generation and editing in real time with server-sent events.
[Learn more about image streaming](https://platform.openai.com/docs/guides/image-generation).
navigationGroup: endpoints
sections:
- type: object
key: ImageGenPartialImageEvent
path: <auto>
- type: object
key: ImageGenCompletedEvent
path: <auto>
- type: object
key: ImageEditPartialImageEvent
path: <auto>
- type: object
key: ImageEditCompletedEvent
path: <auto>
- id: embeddings
title: Embeddings
description: >
Get a vector representation of a given input that can be easily consumed by machine learning models
and algorithms.
Related guide: [Embeddings](https://platform.openai.com/docs/guides/embeddings)
navigationGroup: endpoints
sections:
- type: endpoint
key: createEmbedding
path: create
- type: object
key: Embedding
path: object
- id: evals
title: Evals
description: |
Create, manage, and run evals in the OpenAI platform.
Related guide: [Evals](https://platform.openai.com/docs/guides/evals)
navigationGroup: endpoints
sections:
- type: endpoint
key: createEval
path: create
- type: endpoint
key: getEval
path: get
- type: endpoint
key: updateEval
path: update
- type: endpoint
key: deleteEval
path: delete
- type: endpoint
key: listEvals
path: list
- type: endpoint
key: getEvalRuns
path: getRuns
- type: endpoint
key: getEvalRun
path: getRun
- type: endpoint
key: createEvalRun
path: createRun
- type: endpoint
key: cancelEvalRun
path: cancelRun
- type: endpoint
key: deleteEvalRun
path: deleteRun
- type: endpoint
key: getEvalRunOutputItem
path: getRunOutputItem
- type: endpoint
key: getEvalRunOutputItems
path: getRunOutputItems
- type: object
key: Eval
path: object
- type: object
key: EvalRun
path: run-object
- type: object
key: EvalRunOutputItem
path: run-output-item-object
- id: fine-tuning
title: Fine-tuning
description: |
Manage fine-tuning jobs to tailor a model to your specific training data.
Related guide: [Fine-tune models](https://platform.openai.com/docs/guides/fine-tuning)
navigationGroup: endpoints
sections:
- type: endpoint
key: createFineTuningJob
path: create
- type: endpoint
key: listPaginatedFineTuningJobs
path: list
- type: endpoint
key: listFineTuningEvents
path: list-events
- type: endpoint
key: listFineTuningJobCheckpoints
path: list-checkpoints
- type: endpoint
key: listFineTuningCheckpointPermissions
path: list-permissions
- type: endpoint
key: createFineTuningCheckpointPermission
path: create-permission
- type: endpoint
key: deleteFineTuningCheckpointPermission
path: delete-permission
- type: endpoint
key: retrieveFineTuningJob
path: retrieve
- type: endpoint
key: cancelFineTuningJob
path: cancel
- type: endpoint
key: resumeFineTuningJob
path: resume
- type: endpoint
key: pauseFineTuningJob
path: pause
- type: object
key: FineTuneChatRequestInput
path: chat-input
- type: object
key: FineTunePreferenceRequestInput
path: preference-input
- type: object
key: FineTuneReinforcementRequestInput
path: reinforcement-input
- type: object
key: FineTuningJob
path: object
- type: object
key: FineTuningJobEvent
path: event-object
- type: object
key: FineTuningJobCheckpoint
path: checkpoint-object
- type: object
key: FineTuningCheckpointPermission
path: permission-object
- id: graders
title: Graders
description: |
Manage and run graders in the OpenAI platform.
Related guide: [Graders](https://platform.openai.com/docs/guides/graders)
navigationGroup: endpoints
sections:
- type: object
key: GraderStringCheck
path: string-check
- type: object
key: GraderTextSimilarity
path: text-similarity
- type: object
key: GraderScoreModel
path: score-model
- type: object
key: GraderLabelModel
path: label-model
- type: object
key: GraderPython
path: python
- type: object
key: GraderMulti
path: multi
- type: endpoint
key: runGrader
path: run
- type: endpoint
key: validateGrader
path: validate
beta: true
- id: batch
title: Batch
description: >
Create large batches of API requests for asynchronous processing. The Batch API returns completions
within 24 hours for a 50% discount.
Related guide: [Batch](https://platform.openai.com/docs/guides/batch)
navigationGroup: endpoints
sections:
- type: endpoint
key: createBatch
path: create
- type: endpoint
key: retrieveBatch
path: retrieve
- type: endpoint
key: cancelBatch
path: cancel
- type: endpoint
key: listBatches
path: list
- type: object
key: Batch
path: object
- type: object
key: BatchRequestInput
path: request-input
- type: object
key: BatchRequestOutput
path: request-output
- id: files
title: Files
description: >
Files are used to upload documents that can be used with features like
[Assistants](https://platform.openai.com/docs/api-reference/assistants),
[Fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning), and [Batch
API](https://platform.openai.com/docs/guides/batch).
navigationGroup: endpoints
sections:
- type: endpoint
key: createFile
path: create
- type: endpoint
key: listFiles
path: list
- type: endpoint
key: retrieveFile
path: retrieve
- type: endpoint
key: deleteFile
path: delete
- type: endpoint
key: downloadFile
path: retrieve-contents
- type: object
key: OpenAIFile
path: object
- id: uploads
title: Uploads
description: |
Allows you to upload large files in multiple parts.
navigationGroup: endpoints
sections:
- type: endpoint
key: createUpload
path: create
- type: endpoint
key: addUploadPart
path: add-part
- type: endpoint
key: completeUpload
path: complete
- type: endpoint
key: cancelUpload
path: cancel
- type: object
key: Upload
path: object
- type: object
key: UploadPart
path: part-object
- id: models
title: Models
description: >
List and describe the various models available in the API. You can refer to the
[Models](https://platform.openai.com/docs/models) documentation to understand what models are
available and the differences between them.
navigationGroup: endpoints
sections:
- type: endpoint
key: listModels
path: list
- type: endpoint
key: retrieveModel
path: retrieve
- type: endpoint
key: deleteModel
path: delete
- type: object
key: Model
path: object
- id: moderations
title: Moderations
description: >
Given text and/or image inputs, classifies if those inputs are potentially harmful across several
categories.
Related guide: [Moderations](https://platform.openai.com/docs/guides/moderation)
navigationGroup: endpoints
sections:
- type: endpoint
key: createModeration
path: create
- type: object
key: CreateModerationResponse
path: object
- id: vector-stores
title: Vector stores
description: >
Vector stores power semantic search for the Retrieval API and the `file_search` tool in the Responses
and Assistants APIs.
Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search)
navigationGroup: vector_stores
sections:
- type: endpoint
key: createVectorStore
path: create
- type: endpoint
key: listVectorStores
path: list
- type: endpoint
key: getVectorStore
path: retrieve
- type: endpoint
key: modifyVectorStore
path: modify
- type: endpoint
key: deleteVectorStore
path: delete
- type: endpoint
key: searchVectorStore
path: search
- type: object
key: VectorStoreObject
path: object
- id: vector-stores-files
title: Vector store files
description: |
Vector store files represent files inside a vector store.
Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search)
navigationGroup: vector_stores
sections:
- type: endpoint
key: createVectorStoreFile
path: createFile
- type: endpoint
key: listVectorStoreFiles
path: listFiles
- type: endpoint
key: getVectorStoreFile
path: getFile
- type: endpoint
key: retrieveVectorStoreFileContent
path: getContent
- type: endpoint
key: updateVectorStoreFileAttributes
path: updateAttributes
- type: endpoint
key: deleteVectorStoreFile
path: deleteFile
- type: object
key: VectorStoreFileObject
path: file-object
- id: vector-stores-file-batches
title: Vector store file batches
description: |
Vector store file batches represent operations to add multiple files to a vector store.
Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search)
navigationGroup: vector_stores
sections:
- type: endpoint
key: createVectorStoreFileBatch
path: createBatch
- type: endpoint
key: getVectorStoreFileBatch
path: getBatch
- type: endpoint
key: cancelVectorStoreFileBatch
path: cancelBatch
- type: endpoint
key: listFilesInVectorStoreBatch
path: listBatchFiles
- type: object
key: VectorStoreFileBatchObject
path: batch-object
- id: containers
title: Containers
description: |
Create and manage containers for use with the Code Interpreter tool.
navigationGroup: containers
sections:
- type: endpoint
key: CreateContainer
path: createContainers
- type: endpoint
key: ListContainers
path: listContainers
- type: endpoint
key: RetrieveContainer
path: retrieveContainer
- type: endpoint
key: DeleteContainer
path: deleteContainer
- type: object
key: ContainerResource
path: object
- id: container-files
title: Container Files
description: |
Create and manage container files for use with the Code Interpreter tool.
navigationGroup: containers
sections:
- type: endpoint
key: CreateContainerFile
path: createContainerFile
- type: endpoint
key: ListContainerFiles
path: listContainerFiles
- type: endpoint
key: RetrieveContainerFile
path: retrieveContainerFile
- type: endpoint
key: RetrieveContainerFileContent
path: retrieveContainerFileContent
- type: endpoint
key: DeleteContainerFile
path: deleteContainerFile
- type: object
key: ContainerFileResource
path: object
- id: realtime
title: Realtime
beta: true
description: |
Communicate with a GPT-4o class model in real time using WebRTC or
WebSockets. Supports text and audio inputs and ouputs, along with audio
transcriptions.
[Learn more about the Realtime API](https://platform.openai.com/docs/guides/realtime).
navigationGroup: realtime
- id: realtime-sessions
title: Session tokens
description: |
REST API endpoint to generate ephemeral session tokens for use in client-side
applications.
navigationGroup: realtime
sections:
- type: endpoint
key: create-realtime-session
path: create
- type: endpoint
key: create-realtime-transcription-session
path: create-transcription
- type: object
key: RealtimeSessionCreateResponse
path: session_object
- type: object
key: RealtimeTranscriptionSessionCreateResponse
path: transcription_session_object
- id: realtime-client-events
title: Client events
description: |
These are events that the OpenAI Realtime WebSocket server will accept from the client.
navigationGroup: realtime
sections:
- type: object
key: RealtimeClientEventSessionUpdate
path: <auto>
- type: object
key: RealtimeClientEventInputAudioBufferAppend
path: <auto>
- type: object
key: RealtimeClientEventInputAudioBufferCommit
path: <auto>
- type: object
key: RealtimeClientEventInputAudioBufferClear
path: <auto>
- type: object
key: RealtimeClientEventConversationItemCreate
path: <auto>
- type: object
key: RealtimeClientEventConversationItemRetrieve
path: <auto>
- type: object
key: RealtimeClientEventConversationItemTruncate
path: <auto>
- type: object
key: RealtimeClientEventConversationItemDelete
path: <auto>
- type: object
key: RealtimeClientEventResponseCreate
path: <auto>
- type: object
key: RealtimeClientEventResponseCancel
path: <auto>
- type: object
key: RealtimeClientEventTranscriptionSessionUpdate
path: <auto>
- type: object
key: RealtimeClientEventOutputAudioBufferClear
path: <auto>
- id: realtime-server-events
title: Server events
description: |
These are events emitted from the OpenAI Realtime WebSocket server to the client.
navigationGroup: realtime
sections:
- type: object
key: RealtimeServerEventError
path: <auto>
- type: object
key: RealtimeServerEventSessionCreated
path: <auto>
- type: object
key: RealtimeServerEventSessionUpdated
path: <auto>
- type: object
key: RealtimeServerEventConversationCreated
path: <auto>
- type: object
key: RealtimeServerEventConversationItemCreated
path: <auto>
- type: object
key: RealtimeServerEventConversationItemRetrieved
path: <auto>
- type: object
key: RealtimeServerEventConversationItemInputAudioTranscriptionCompleted
path: <auto>
- type: object
key: RealtimeServerEventConversationItemInputAudioTranscriptionDelta
path: <auto>
- type: object
key: RealtimeServerEventConversationItemInputAudioTranscriptionFailed
path: <auto>
- type: object
key: RealtimeServerEventConversationItemTruncated
path: <auto>
- type: object
key: RealtimeServerEventConversationItemDeleted
path: <auto>
- type: object
key: RealtimeServerEventInputAudioBufferCommitted
path: <auto>
- type: object
key: RealtimeServerEventInputAudioBufferCleared
path: <auto>
- type: object
key: RealtimeServerEventInputAudioBufferSpeechStarted
path: <auto>
- type: object
key: RealtimeServerEventInputAudioBufferSpeechStopped
path: <auto>
- type: object
key: RealtimeServerEventResponseCreated
path: <auto>
- type: object
key: RealtimeServerEventResponseDone
path: <auto>
- type: object
key: RealtimeServerEventResponseOutputItemAdded
path: <auto>
- type: object
key: RealtimeServerEventResponseOutputItemDone
path: <auto>
- type: object
key: RealtimeServerEventResponseContentPartAdded
path: <auto>
- type: object
key: RealtimeServerEventResponseContentPartDone
path: <auto>
- type: object
key: RealtimeServerEventResponseTextDelta
path: <auto>
- type: object
key: RealtimeServerEventResponseTextDone
path: <auto>
- type: object
key: RealtimeServerEventResponseAudioTranscriptDelta
path: <auto>
- type: object
key: RealtimeServerEventResponseAudioTranscriptDone
path: <auto>
- type: object
key: RealtimeServerEventResponseAudioDelta
path: <auto>
- type: object
key: RealtimeServerEventResponseAudioDone
path: <auto>
- type: object
key: RealtimeServerEventResponseFunctionCallArgumentsDelta
path: <auto>
- type: object
key: RealtimeServerEventResponseFunctionCallArgumentsDone
path: <auto>
- type: object
key: RealtimeServerEventTranscriptionSessionUpdated
path: <auto>
- type: object
key: RealtimeServerEventRateLimitsUpdated
path: <auto>
- type: object
key: RealtimeServerEventOutputAudioBufferStarted
path: <auto>
- type: object
key: RealtimeServerEventOutputAudioBufferStopped
path: <auto>
- type: object
key: RealtimeServerEventOutputAudioBufferCleared
path: <auto>
- id: chat
title: Chat Completions
description: >
The Chat Completions API endpoint will generate a model response from a
list of messages comprising a conversation.
Related guides:
- [Quickstart](https://platform.openai.com/docs/quickstart?api-mode=chat)
- [Text inputs and outputs](https://platform.openai.com/docs/guides/text?api-mode=chat)
- [Image inputs](https://platform.openai.com/docs/guides/images?api-mode=chat)
- [Audio inputs and outputs](https://platform.openai.com/docs/guides/audio?api-mode=chat)
- [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs?api-mode=chat)
- [Function calling](https://platform.openai.com/docs/guides/function-calling?api-mode=chat)
- [Conversation state](https://platform.openai.com/docs/guides/conversation-state?api-mode=chat)
**Starting a new project?** We recommend trying
[Responses](https://platform.openai.com/docs/api-reference/responses)
to take advantage of the latest OpenAI platform features. Compare
[Chat Completions with
Responses](https://platform.openai.com/docs/guides/responses-vs-chat-completions?api-mode=responses).
navigationGroup: chat
sections:
- type: endpoint
key: createChatCompletion
path: create
- type: endpoint
key: getChatCompletion
path: get
- type: endpoint
key: getChatCompletionMessages
path: getMessages
- type: endpoint
key: listChatCompletions
path: list
- type: endpoint
key: updateChatCompletion
path: update
- type: endpoint
key: deleteChatCompletion
path: delete
- type: object
key: CreateChatCompletionResponse
path: object
- type: object
key: ChatCompletionList
path: list-object
- type: object
key: ChatCompletionMessageList
path: message-list
- id: chat-streaming
title: Streaming
description: |
Stream Chat Completions in real time. Receive chunks of completions
returned from the model using server-sent events.
[Learn more](https://platform.openai.com/docs/guides/streaming-responses?api-mode=chat).
navigationGroup: chat
sections:
- type: object
key: CreateChatCompletionStreamResponse
path: streaming
- id: assistants
title: Assistants
beta: true
description: |
Build assistants that can call models and use tools to perform tasks.
[Get started with the Assistants API](https://platform.openai.com/docs/assistants)
navigationGroup: assistants
sections:
- type: endpoint
key: createAssistant
path: createAssistant
- type: endpoint
key: listAssistants
path: listAssistants
- type: endpoint
key: getAssistant
path: getAssistant
- type: endpoint
key: modifyAssistant
path: modifyAssistant
- type: endpoint
key: deleteAssistant
path: deleteAssistant
- type: object
key: AssistantObject
path: object
- id: threads
title: Threads
beta: true
description: |
Create threads that assistants can interact with.
Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview)
navigationGroup: assistants
sections:
- type: endpoint
key: createThread
path: createThread
- type: endpoint
key: getThread
path: getThread
- type: endpoint
key: modifyThread
path: modifyThread
- type: endpoint
key: deleteThread
path: deleteThread
- type: object
key: ThreadObject
path: object
- id: messages
title: Messages
beta: true
description: |
Create messages within threads
Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview)
navigationGroup: assistants
sections:
- type: endpoint
key: createMessage
path: createMessage
- type: endpoint
key: listMessages
path: listMessages
- type: endpoint
key: getMessage
path: getMessage
- type: endpoint
key: modifyMessage
path: modifyMessage
- type: endpoint
key: deleteMessage
path: deleteMessage
- type: object
key: MessageObject
path: object
- id: runs
title: Runs
beta: true
description: |
Represents an execution run on a thread.
Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview)
navigationGroup: assistants
sections:
- type: endpoint
key: createRun
path: createRun
- type: endpoint
key: createThreadAndRun
path: createThreadAndRun
- type: endpoint
key: listRuns
path: listRuns
- type: endpoint
key: getRun
path: getRun
- type: endpoint
key: modifyRun
path: modifyRun
- type: endpoint
key: submitToolOuputsToRun
path: submitToolOutputs
- type: endpoint
key: cancelRun
path: cancelRun
- type: object
key: RunObject
path: object
- id: run-steps
title: Run steps
beta: true
description: |
Represents the steps (model and tool calls) taken during the run.
Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview)
navigationGroup: assistants
sections:
- type: endpoint
key: listRunSteps
path: listRunSteps
- type: endpoint
key: getRunStep
path: getRunStep
- type: object
key: RunStepObject
path: step-object
- id: assistants-streaming
title: Streaming
beta: true
description: >
Stream the result of executing a Run or resuming a Run after submitting tool outputs.
You can stream events from the [Create Thread and
Run](https://platform.openai.com/docs/api-reference/runs/createThreadAndRun),
[Create Run](https://platform.openai.com/docs/api-reference/runs/createRun), and [Submit Tool
Outputs](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs)
endpoints by passing `"stream": true`. The response will be a [Server-Sent
events](https://html.spec.whatwg.org/multipage/server-sent-events.html#server-sent-events) stream.
Our Node and Python SDKs provide helpful utilities to make streaming easy. Reference the
[Assistants API quickstart](https://platform.openai.com/docs/assistants/overview) to learn more.
navigationGroup: assistants
sections:
- type: object
key: MessageDeltaObject
path: message-delta-object
- type: object
key: RunStepDeltaObject
path: run-step-delta-object
- type: object
key: AssistantStreamEvent
path: events
- id: administration
title: Administration
description: >
Programmatically manage your organization.
The Audit Logs endpoint provides a log of all actions taken in the organization for security and
monitoring purposes.
To access these endpoints please generate an Admin API Key through the [API Platform Organization
overview](/organization/admin-keys). Admin API keys cannot be used for non-administration endpoints.
For best practices on setting up your organization, please refer to this
[guide](https://platform.openai.com/docs/guides/production-best-practices#setting-up-your-organization)
navigationGroup: administration
- id: admin-api-keys
title: Admin API Keys
description: >
Admin API keys enable Organization Owners to programmatically manage various aspects of their
organization, including users, projects, and API keys. These keys provide administrative capabilities,
such as creating, updating, and deleting users; managing projects; and overseeing API key lifecycles.
Key Features of Admin API Keys:
- User Management: Invite new users, update roles, and remove users from the organization.
- Project Management: Create, update, archive projects, and manage user assignments within projects.
- API Key Oversight: List, retrieve, and delete API keys associated with projects.
Only Organization Owners have the authority to create and utilize Admin API keys. To manage these
keys, Organization Owners can navigate to the Admin Keys section of their API Platform dashboard.
For direct access to the Admin Keys management page, Organization Owners can use the following link:
[https://platform.openai.com/settings/organization/admin-keys](https://platform.openai.com/settings/organization/admin-keys)
It's crucial to handle Admin API keys with care due to their elevated permissions. Adhering to best
practices, such as regular key rotation and assigning appropriate permissions, enhances security and
ensures proper governance within the organization.
navigationGroup: administration
sections:
- type: endpoint
key: admin-api-keys-list
path: list
- type: endpoint
key: admin-api-keys-create
path: create
- type: endpoint
key: admin-api-keys-get
path: listget
- type: endpoint
key: admin-api-keys-delete
path: delete
- type: object
key: AdminApiKey
path: object
- id: invite
title: Invites
description: Invite and manage invitations for an organization.
navigationGroup: administration
sections:
- type: endpoint
key: list-invites
path: list
- type: endpoint
key: inviteUser
path: create
- type: endpoint
key: retrieve-invite
path: retrieve
- type: endpoint
key: delete-invite
path: delete
- type: object
key: Invite
path: object
- id: users
title: Users
description: |
Manage users and their role in an organization.
navigationGroup: administration
sections:
- type: endpoint
key: list-users
path: list
- type: endpoint
key: modify-user
path: modify
- type: endpoint
key: retrieve-user
path: retrieve
- type: endpoint
key: delete-user
path: delete
- type: object
key: User
path: object
- id: projects
title: Projects
description: |
Manage the projects within an orgnanization includes creation, updating, and archiving or projects.
The Default project cannot be archived.
navigationGroup: administration
sections:
- type: endpoint
key: list-projects
path: list
- type: endpoint
key: create-project
path: create
- type: endpoint
key: retrieve-project
path: retrieve
- type: endpoint
key: modify-project
path: modify
- type: endpoint
key: archive-project
path: archive
- type: object
key: Project
path: object
- id: project-users
title: Project users
description: |
Manage users within a project, including adding, updating roles, and removing users.
navigationGroup: administration
sections:
- type: endpoint
key: list-project-users
path: list
- type: endpoint
key: create-project-user
path: create
- type: endpoint
key: retrieve-project-user
path: retrieve
- type: endpoint
key: modify-project-user
path: modify
- type: endpoint
key: delete-project-user
path: delete
- type: object
key: ProjectUser
path: object
- id: project-service-accounts
title: Project service accounts
description: >
Manage service accounts within a project. A service account is a bot user that is not associated with
a user.
If a user leaves an organization, their keys and membership in projects will no longer work. Service
accounts
do not have this limitation. However, service accounts can also be deleted from a project.
navigationGroup: administration
sections:
- type: endpoint
key: list-project-service-accounts
path: list
- type: endpoint
key: create-project-service-account
path: create
- type: endpoint
key: retrieve-project-service-account
path: retrieve
- type: endpoint
key: delete-project-service-account
path: delete
- type: object
key: ProjectServiceAccount
path: object
- id: project-api-keys
title: Project API keys
description: >
Manage API keys for a given project. Supports listing and deleting keys for users.
This API does not allow issuing keys for users, as users need to authorize themselves to generate
keys.
navigationGroup: administration
sections:
- type: endpoint
key: list-project-api-keys
path: list
- type: endpoint
key: retrieve-project-api-key
path: retrieve
- type: endpoint
key: delete-project-api-key
path: delete
- type: object
key: ProjectApiKey
path: object
- id: project-rate-limits
title: Project rate limits
description: >
Manage rate limits per model for projects. Rate limits may be configured to be equal to or lower than
the organization's rate limits.
navigationGroup: administration
sections:
- type: endpoint
key: list-project-rate-limits
path: list
- type: endpoint
key: update-project-rate-limits
path: update
- type: object
key: ProjectRateLimit
path: object
- id: audit-logs
title: Audit logs
description: >
Logs of user actions and configuration changes within this organization.
To log events, an Organization Owner must activate logging in the [Data Controls
Settings](/settings/organization/data-controls/data-retention).
Once activated, for security reasons, logging cannot be deactivated.
navigationGroup: administration
sections:
- type: endpoint
key: list-audit-logs
path: list
- type: object
key: AuditLog
path: object
- id: usage
title: Usage
description: >
The **Usage API** provides detailed insights into your activity across the OpenAI API. It also
includes a separate [Costs endpoint](https://platform.openai.com/docs/api-reference/usage/costs),
which offers visibility into your spend, breaking down consumption by invoice line items and project
IDs.
While the Usage API delivers granular usage data, it may not always reconcile perfectly with the Costs
due to minor differences in how usage and spend are recorded. For financial purposes, we recommend
using the [Costs endpoint](https://platform.openai.com/docs/api-reference/usage/costs) or the [Costs
tab](/settings/organization/usage) in the Usage Dashboard, which will reconcile back to your billing
invoice.
navigationGroup: administration
sections:
- type: endpoint
key: usage-completions
path: completions
- type: object
key: UsageCompletionsResult
path: completions_object
- type: endpoint
key: usage-embeddings
path: embeddings
- type: object
key: UsageEmbeddingsResult
path: embeddings_object
- type: endpoint
key: usage-moderations
path: moderations
- type: object
key: UsageModerationsResult
path: moderations_object
- type: endpoint
key: usage-images
path: images
- type: object
key: UsageImagesResult
path: images_object
- type: endpoint
key: usage-audio-speeches
path: audio_speeches
- type: object
key: UsageAudioSpeechesResult
path: audio_speeches_object
- type: endpoint
key: usage-audio-transcriptions
path: audio_transcriptions
- type: object
key: UsageAudioTranscriptionsResult
path: audio_transcriptions_object
- type: endpoint
key: usage-vector-stores
path: vector_stores
- type: object
key: UsageVectorStoresResult
path: vector_stores_object
- type: endpoint
key: usage-code-interpreter-sessions
path: code_interpreter_sessions
- type: object
key: UsageCodeInterpreterSessionsResult
path: code_interpreter_sessions_object
- type: endpoint
key: usage-costs
path: costs
- type: object
key: CostsResult
path: costs_object
- id: certificates
beta: true
title: Certificates
description: >
Manage Mutual TLS certificates across your organization and projects.
[Learn more about Mutual
TLS.](https://help.openai.com/en/articles/10876024-openai-mutual-tls-beta-program)
navigationGroup: administration
sections:
- type: endpoint
key: uploadCertificate
path: uploadCertificate
- type: endpoint
key: getCertificate
path: getCertificate
- type: endpoint
key: modifyCertificate
path: modifyCertificate
- type: endpoint
key: deleteCertificate
path: deleteCertificate
- type: endpoint
key: listOrganizationCertificates
path: listOrganizationCertificates
- type: endpoint
key: listProjectCertificates
path: listProjectCertificates
- type: endpoint
key: activateOrganizationCertificates
path: activateOrganizationCertificates
- type: endpoint
key: deactivateOrganizationCertificates
path: deactivateOrganizationCertificates
- type: endpoint
key: activateProjectCertificates
path: activateProjectCertificates
- type: endpoint
key: deactivateProjectCertificates
path: deactivateProjectCertificates
- type: object
key: Certificate
path: object
- id: completions
title: Completions
legacy: true
navigationGroup: legacy
description: >
Given a prompt, the model will return one or more predicted completions along with the probabilities
of alternative tokens at each position. Most developer should use our [Chat Completions
API](https://platform.openai.com/docs/guides/text-generation#text-generation-models) to leverage our
best and newest models.
sections:
- type: endpoint
key: createCompletion
path: create
- type: object
key: CreateCompletionResponse
path: object