Ovid · July 6, 2024 13:24
diff --git a/Chat.pm b/Chat.pm
 # See also: https://curtispoe.org/articles/an-openai-chatbot-in-perl.html
 use v5.40.0;
 use experimental qw( class );

 class OpenAI::Chat;

 use OpenAPI::Client::OpenAI;
 use Data::Printer;
 use Carp qw( croak );
 use utf8::all;

 # these parameters are optional
 field $model          :param = 'gpt-3.5-turbo-0125';
 field $temperature    :param = .1;
 field $context_size   :param = 16384; # roughly

 # For this example, you must pass a system message. However,
 # for production code, you probably want a default one.
 field $system_message :param :reader; # no default for this one

 # we use $history to track the full history of the conversation, including
 # token usage. The LLM is stateless. I cannot remember your conversation,
 # so we send the full conversation to the LLM each time.
 field $history = [];
 field $openai  = OpenAPI::Client::OpenAI->new;

 method _get_messages ($message) {
    my @messages = map { $_->{messages}->@* } $history->@*;
    if ($system_message) {
        # we always add the system message to the front so that the LLM can
        # understand how it's supposed to behave.
        unshift @messages, { role => 'system', content => $system_message };
    }
    push @messages, $self->_format_user_message($message);
    return \@messages;
 }

 method _format_user_message ($message) {
    return { role => 'user', content => $message };
 }

 method _total_tokens () {
    my $total_tokens = 0;
    for my $entry ( $history->@* ) {
        $total_tokens += $entry->{usage}{total_tokens};
    }
    return $total_tokens;
 }

 method _trim_messages_to_context_size () {
    while ( $self->_total_tokens > $context_size ) {
        # remove the oldest messages first
        shift $history->@*;
    }
 }

 method prompt ($prompt) {
    my $response = $openai->createChatCompletion(
        {
            body => {
                model       => $model,
                messages    => $self->_get_messages($prompt),
                temperature => $temperature,
            }
        }
    );
    if ( $response->res->is_success ) {
        my $result;
        try {
            my $message = $response->res->json->{choices}[0]{message};
            my $usage   = $response->res->json->{usage};
            push $history->@* => {
                # track the messages *and* the token usage so we can
                # keep track of our context size
                messages => [
                    $self->_format_user_message($prompt),    # prompt
                    $message,                                # response
                ],
                usage => $usage,
            };
            $result = $message->{content};
            $self ->_trim_messages_to_context_size;
        }
        catch ($e) {
            croak("Error decoding JSON: $e");
        }
        return $result;
    }
    else {
        my $error = $response->res;
        croak( $error->to_string );
    }
 }

 method _data_printer {
    my $details = {
        model          => $model,
        system_message => $system_message,
        temperature    => $temperature,
        context_size   => $context_size,
        history        => $history,
    };
    return np $details;
 }
	# See also: https://curtispoe.org/articles/an-openai-chatbot-in-perl.html
	use v5.40.0;
	use experimental qw( class );

	class OpenAI::Chat;

	use OpenAPI::Client::OpenAI;
	use Data::Printer;
	use Carp qw( croak );
	use utf8::all;

	# these parameters are optional
	field $model :param = 'gpt-3.5-turbo-0125';
	field $temperature :param = .1;
	field $context_size :param = 16384; # roughly

	# For this example, you must pass a system message. However,
	# for production code, you probably want a default one.
	field $system_message :param :reader; # no default for this one

	# we use $history to track the full history of the conversation, including
	# token usage. The LLM is stateless. I cannot remember your conversation,
	# so we send the full conversation to the LLM each time.
	field $history = [];
	field $openai = OpenAPI::Client::OpenAI->new;

	method _get_messages ($message) {
	my @messages = map { $_->{messages}->@* } $history->@*;
	if ($system_message) {
	# we always add the system message to the front so that the LLM can
	# understand how it's supposed to behave.
	unshift @messages, { role => 'system', content => $system_message };
	}
	push @messages, $self->_format_user_message($message);
	return \@messages;
	}

	method _format_user_message ($message) {
	return { role => 'user', content => $message };
	}

	method _total_tokens () {
	my $total_tokens = 0;
	for my $entry ( $history->@* ) {
	$total_tokens += $entry->{usage}{total_tokens};
	}
	return $total_tokens;
	}

	method _trim_messages_to_context_size () {
	while ( $self->_total_tokens > $context_size ) {
	# remove the oldest messages first
	shift $history->@*;
	}
	}

	method prompt ($prompt) {
	my $response = $openai->createChatCompletion(
	{
	body => {
	model => $model,
	messages => $self->_get_messages($prompt),
	temperature => $temperature,
	}
	}
	);
	if ( $response->res->is_success ) {
	my $result;
	try {
	my $message = $response->res->json->{choices}[0]{message};
	my $usage = $response->res->json->{usage};
	push $history->@* => {
	# track the messages and the token usage so we can
	# keep track of our context size
	messages => [
	$self->_format_user_message($prompt), # prompt
	$message, # response
	],
	usage => $usage,
	};
	$result = $message->{content};
	$self ->_trim_messages_to_context_size;
	}
	catch ($e) {
	croak("Error decoding JSON: $e");
	}
	return $result;
	}
	else {
	my $error = $response->res;
	croak( $error->to_string );
	}
	}

	method _data_printer {
	my $details = {
	model => $model,
	system_message => $system_message,
	temperature => $temperature,
	context_size => $context_size,
	history => $history,
	};
	return np $details;
	}