NAME

WebService::Ollama - ollama client

VERSION

Version 0.07

SYNOPSIS


            
              
              my $ollama = WebService::Ollama->new(
        base_url => 'http://localhost:11434',
        model => 'llama3.2'
);
$ollama->load_completion_model;
my $string = "";
my $why = $ollama->completion(
        prompt => 'Why is the sky blue?',
        stream => 1,
        stream_cb => sub {
                my ($res) = @_;
                $string .= $res->response;
        }
); # returns all chunked responses as an array
$ollama->unload_completion_model;

SUBROUTINES/METHODS

version

Retrieve the Ollama version


            
              
              $ollama->version;

create_model

Create a model from: another model, a safetensors directory or a GGUF file.

Parameters

model: name of the model to create
from: (optional) name of an existing model to create the new model from
files: (optional) a dictionary of file names to SHA256 digests of blobs to create the model from
adapters: (optional) a dictionary of file names to SHA256 digests of blobs for LORA adapters
template: (optional) the prompt template for the model
license: (optional) a string or list of strings containing the license or licenses for the model
system: (optional) a string containing the system prompt for the model
parameters: (optional) a dictionary of parameters for the model (see Modelfile for a list of parameters)
messages: (optional) a list of message objects used to create a conversation
stream: (optional) if false the response will be returned as a single response object, rather than a stream of objects
stream_cb: (optional) cb to handle stream data
quantize: (optional) quantize a non-quantized (e.g. float16) model


            
              
              $ollama->create_model(
        model => 'mario',
        from => 'llama3.2',
        system => 'You are Mario from Super Mario Bros.'
);
my $mario_story = $ollama->chat(
        model => 'mario',
        messages => [
                {
                        role => 'user',
                        content => 'Hello, Tell me a story.',
                }
        ],
);

copy_model

Copy a model. Creates a model with another name from an existing model.

Parameters

source: source of model to be copied from.
destination: destination of model to be copied to.


            
              
              $ollama->copy_model(
        source => 'llama3.2',
        destination => 'llama3-backup'
);

delete_model

Delete a model and its data.

Parameters

model: model name to delete


            
              
              $ollama->delete_model(
        model => 'mario'
);

available_models

List models that are available locally.


            
              
              $ollama->available_models;

running_models

List models that are currently loaded into memory.


            
              
              $ollama->running_models;

load_completion_model

Load a model into memory


            
              
              $ollama->load_completion_model;
$ollama->load_completion_model(model => 'llava');

unload_completion_model

Unload a model from memory


            
              
              $ollama->unload_completion_model;
$ollama->unload_completion_model(model => 'llava');

completion

Generate a response for a given prompt with a provided model. This is a streaming endpoint, so there will be a series of responses. The final response object will include statistics and additional data from the request.

Parameters

model: (required) the model name
prompt: the prompt to generate a response for
suffix: the text after the model response
images: (optional) a list of base64-encoded images (for multimodal models such as llava)
image_files: (optional) a list of image files

Advanced parameters (optional):

format

the format to return a response in. Format can be json or a JSON schema

options

additional model parameters listed in the documentation for the Modelfile such as temperature

system

system message to (overrides what is defined in the Modelfile)

template

the prompt template to use (overrides what is defined in the Modelfile)

stream

if false the response will be returned as a single response object, rather than a stream of objects

stream_cb

(optional) cb to handle stream data

raw


            
              
              if true no formatting will be applied to the prompt. You may choose to use the raw parameter if you are specifying a full templated prompt in your request to the API

keep_alive

controls how long the model will stay loaded into memory following the request (default: 5m)

context (deprecated)

the context parameter returned from a previous request to /generate, this can be used to keep a short conversational memory


            
              
              my $image = $ollama->completion(
        model => 'llava',
        prompt => 'What is in this image?',
        image_files => [
                "t/pingu.png"
        ]
); 
my $json = $ollama->completion(
        prompt => "What color is the sky at different times of the day? Respond using JSON",
        format => "json",
)->json_response;
my $json2 = $ollama->completion(
        prompt => "Ollama is 22 years old and is busy saving the world. Respond using JSON",
        format => {
                type => "object",
                properties => {
                        age => {
                                "type" => "integer"
                        },
                        available => {
                                "type" => "boolean"
                        }
                },
                required => [
                        "age",
                        "available"
                ]
        }
)->json_response;

load_chat_model

Load a model into memory


            
              
              $ollama->load_chat_model;
$ollama->load_chat_model(model => 'llava');

unload_chat_model

Unload a model from memory


            
              
              $ollama->unload_chat_model;
$ollama->unload_chat_model(model => 'llava');

chat

Generate the next message in a chat with a provided model.

Parameters

model

(required) the model name

messages

the messages of the chat, this can be used to keep a chat memory

The message object has the following fields:

role: the role of the message, either system, user, assistant, or tool
content: the content of the message
images: (optional) a list of images to include in the message (for multimodal models such as llava)
tool_calls: (optional): a list of tools in JSON that the model wants to use

tools

list of tools in JSON for the model to use if supported

format

the format to return a response in. Format can be json or a JSON schema.

options

additional model parameters listed in the documentation for the Modelfile such as temperature

stream

if false the response will be returned as a single response object, rather than a stream of objects

keep_alive

controls how long the model will stay loaded into memory following the request (default: 5m)


            
              
              my $completion = $ollama->chat(
        messages => [
                {
                        role => 'user',
                        content => 'Why is the sky blue?',
                }
        ],
);
my $image = $ollama->chat(
        model => 'llava',
        messages => [
                {
                        role => 'user',
                        content => 'What is in this image?',
                        image_files => [
                                "t/pingu.png"
                        ]
                }
        ]
);
my $json = $ollama->chat(
        messages => [
                {
                        role => "user",
                        "content" => "Ollama is 22 years old and is busy saving the world. Respond using JSON",
                }
        ],
        format => {
                type => "object",
                properties => {
                        age => {
                                "type" => "integer"
                        },
                        available => {
                                "type" => "boolean"
                        }
                },
                required => [
                        "age",
                        "available"
                ]
        }
)->json_response;

embed

Generate embeddings from a model

Parameters

model: name of model to generate embeddings from
input: text or list of text to generate embeddings for
truncate: (optional) truncates the end of each input to fit within context length. Returns error if false and context length is exceeded. Defaults to true
options: (optional) additional model parameters listed in the documentation for the Modelfile such as temperature
keep_alive: (optional) controls how long the model will stay loaded into memory following the request (default: 5m)


            
              
              my $embeddings = $ollama->embed(
        model => "nomic-embed-text",
        input => "Why is the sky blue?"
);

AUTHOR

LNATION, <email at lnation.org>

BUGS

Please report any bugs or feature requests to bug-webservice-ollama at rt.cpan.org, or through the web interface at https://rt.cpan.org/NoAuth/ReportBug.html?Queue=WebService-Ollama. I will be notified, and then you'll automatically be notified of progress on your bug as I make changes.

SUPPORT

You can find documentation for this module with the perldoc command.


            
              
              perldoc WebService::Ollama

You can also look for information at:

RT: CPAN's request tracker (report bugs here)

https://rt.cpan.org/NoAuth/Bugs.html?Dist=WebService-Ollama
CPAN Ratings

https://cpanratings.perl.org/d/WebService-Ollama
Search CPAN

https://metacpan.org/release/WebService-Ollama

ACKNOWLEDGEMENTS

LICENSE AND COPYRIGHT

This is free software, licensed under:


            
              
              The Artistic License 2.0 (GPL Compatible)

To install WebService::Ollama, copy and paste the appropriate command in to your terminal.

cpanm

cpanm WebService::Ollama

CPAN shell

perl -MCPAN -e shell
install WebService::Ollama

For more information on module installation, please visit the detailed CPAN module installation guide.

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NAME

VERSION

SYNOPSIS

SUBROUTINES/METHODS

version

create_model

Parameters

copy_model

Parameters

delete_model

Parameters

available_models

running_models

load_completion_model

unload_completion_model

completion

Parameters

Advanced parameters (optional):

load_chat_model

unload_chat_model

chat

Parameters

embed

Parameters

AUTHOR

BUGS

SUPPORT

ACKNOWLEDGEMENTS

LICENSE AND COPYRIGHT

Module Install Instructions