/ 
SignalWire-ML-1.22
River stage zero No dependents
/ SignalWire::ML

NAME

SignalWire::ML - Light and fast SWML generator

METHODS

new($class, $args)

Constructor method. Creates a new SignalWire::ML object with default values.

Example

Here's an example of how to use SignalWire::ML:


            

              
              
use SignalWire::ML;
# Create a new SignalWire::ML object
my $ml = SignalWire::ML->new({
    version => '1.0.0'
});
# Set AI prompt
$ml->set_aiprompt({
    text => "What's the weather like today?",
    temperature => 0.7,
    top_p => 0.9
});
# Set AI parameters
$ml->set_aiparams({
    max_tokens => 150
});
# Add an AI application to a section
$ml->add_aiapplication('main');
# Render the result
my $json_output = $ml->render_json();
print $json_output;

This example demonstrates creating a SignalWire::ML object, setting various parameters and contexts, adding applications, and then rendering the result as JSON.

add_aiapplication($self, $section)

Adds an AI application to the specified section.

set_context_steps($self, $context_name, $steps)

Sets the steps for a specific context in the prompt.

add_context_steps($self, $context_name, $steps)

Adds steps to an existing context in the prompt.

set_prompt_contexts($self, $contexts)

Sets the contexts for the prompt.

add_application($self, $section, $app, $args)

Adds an application to the specified section with given arguments.

This method is used to add an application to a specific section in the SignalWire::ML object.

Example usage:


            

              
              
my $swml = SignalWire::ML->new({version => '1.0.0'});
$swml->add_application("main", "answer");
$swml->add_application("main", "play",
    { urls => [ "https://github.com/freeswitch/freeswitch-sounds/raw/master/en/us/callie/ivr/48000/ivr-welcome_to_freeswitch.wav" ] });
$swml->add_application("main", "hangup");
$swml->add_aiapplication('main');
print $swml->render_json;

This example demonstrates creating a SignalWire::ML object, adding various applications including an answer, play, and hangup application, then adding an AI application to the 'main' section, and finally rendering the result as JSON.

set_aipost_prompt_url($self, $postprompt)

Sets the AI post-prompt URL and related parameters.

set_global_data($self, $data)

Sets the global data for the ML object.

set_aiparams($self, $params)

Sets the AI parameters.

add_aiparams($self, $params)

Adds additional AI parameters.

set_aipost_prompt($self, $postprompt)

Sets the AI post-prompt parameters.

set_aiprompt($self, $prompt)

Sets the AI prompt parameters.

swaig_response($self, $response)

Processes and returns the SWAIG response.

swaig_response_json($self, $response)

Processes the SWAIG response and returns it as JSON.

render($self)

Renders the content of the ML object.

render_json($self)

Renders the content of the ML object as JSON.

render_yaml($self)

Renders the content of the ML object as YAML.

SYNOPSIS

TODO