Rand Stats



WWW::OpenAI Raku package

In brief

This Raku package provides access to the machine learning service OpenAI, [OAI1]. For more details of the OpenAI's API usage see the documentation, [OAI2].

Remark: To use the OpenAI API one has to register and obtain authorization key.

Remark: This Raku package is much "less ambitious" than the official Python package, [OAIp1], developed by OpenAI's team. Gradually, over time, I expect to add features to the Raku package that correspond to features of [OAIp1].

The design and implementation of "WWW::OpenAI" are very similar to those of "Lingua::Translation::DeepL", [AAp1].


Package installations from both sources use zef installer (which should be bundled with the "standard" Rakudo installation file.)

To install the package from Zef ecosystem use the shell command:

zef install WWW::OpenAI

To install the package from the GitHub repository use the shell command:

zef install https://github.com/antononcube/Raku-WWW-OpenAI.git

Usage examples

Remark: When the authorization key, auth-key, is specified to be Whatever then the functions openai-* attempt to use the env variable OPENAI_API_KEY.

Universal "front-end"

The package has an universal "front-end" function openai-playground for the different functionalities provided by OpenAI.

Here is a simple call for a "chat completion":

use WWW::OpenAI;
openai-playground('Where is Roger Rabbit?', max-tokens => 64);
# [{finish_reason => stop, index => 0, message => {content => 
# As an AI language model, I do not have the capability to determine the current whereabouts of fictional characters. However, Roger Rabbit is a character created for the 1988 film "Who Framed Roger Rabbit" and is still popular among fans of the movie., role => assistant}}]

Another one using Bulgarian:

openai-playground('Колко групи могат да се намерят в този облак от точки.', max-tokens => 64);
# [{finish_reason => length, index => 0, message => {content => 
# Като AI модел, не мога да видя облак от точки, който споменавате. Моля, посочете повече информация или предоставете изображение, за да мога да отгов, role => assistant}}]

Remark: The function openai-completion can be used instead in the examples above. See the section "Create chat completion" of [OAI2] for more details.

Image generation

Remark: See the files "Image-generation*" for more details.

Images can be generated with the function openai-create-image -- see the section "Images" of [OAI2].

Here is an example:

my $imgB64 = openai-create-image(
        "racoon with a sliced onion in the style of Raphael",
        response-format => 'b64_json',
        n => 1,
        size => 'small',
        format => 'values',
        method => 'cro');

Here are the options descriptions:

Here we generate an image, get its URL, and place (embed) a link to it via the output of the code cell:

my @imgRes = |openai-create-image(
        "racoon and onion in the style of Roy Lichtenstein",
        response-format => 'url',
        n => 1,
        size => 'small',
        method => 'cro');

'![](' ~ @imgRes.head<url> ~ ')';


Here is an example of using OpenAI's moderation:

my @modRes = |openai-moderation(
"I want to kill them!",
format => "values",
method => 'curl');

for @modRes -> $m { .say for $m.pairs.sort(*.value).reverse; }
# violence => 0.9640626311302185
# hate => 0.27332669496536255
# hate/threatening => 0.00637523178011179
# sexual => 8.585161026530841e-07
# violence/graphic => 2.8522084249971158e-08
# self-harm => 1.678687522321809e-09
# sexual/minors => 1.3898265871503668e-09

Command Line Interface

The package provides a Command Line Interface (CLI) script:

openai-playground --help
# Usage:
#   openai-playground <text> [--path=<Str>] [-n[=UInt]] [--max-tokens[=UInt]] [-m|--model=<Str>] [-r|--role=<Str>] [-t|--temperature[=Real]] [--response-format=<Str>] [-a|--auth-key=<Str>] [--timeout[=UInt]] [--format=<Str>] [--method=<Str>] -- Text processing using the OpenAI API.
#   openai-playground [<words> ...] [-m|--model=<Str>] [--path=<Str>] [-n[=UInt]] [--max-tokens[=UInt]] [-r|--role=<Str>] [-t|--temperature[=Real]] [--response-format=<Str>] [-a|--auth-key=<Str>] [--timeout[=UInt]] [--format=<Str>] [--method=<Str>] -- Command given as a sequence of words.
#     <text>                     Text to be processed.
#     --path=<Str>               Path, one of 'images/generations' or 'chat/completions'. [default: 'chat/completions']
#     -n[=UInt]                  Number of completions or generations. [default: 1]
#     --max-tokens[=UInt]        The maximum number of tokens to generate in the completion. [default: 16]
#     -m|--model=<Str>           Model. [default: 'Whatever']
#     -r|--role=<Str>            Role. [default: 'user']
#     -t|--temperature[=Real]    Temperature. [default: 0.7]
#     --response-format=<Str>    The format in which the generated images are returned; one of 'url' or 'b64_json'. [default: 'url']
#     -a|--auth-key=<Str>        Authorization key (to use OpenAI API.) [default: 'Whatever']
#     --timeout[=UInt]           Timeout. [default: 10]
#     --format=<Str>             Format of the result; one of "json" or "hash". [default: 'json']
#     --method=<Str>             Method for the HTTP POST query; one of "cro" or "curl". [default: 'cro']

Remark: When the authorization key argument "auth-key" is specified set to "Whatever" then openai-playground attempts to use the env variable OPENAI_API_KEY.

Mermaid diagram

The following flowchart corresponds to the steps in the package function openai-playground:

graph TD
	UI[/Some natural language text/]
	TO[/"OpenAI<br/>Processed output"/]
	WR[[Web request]]
	PJ[Parse JSON]
	MSTC[Compose query]
	MURL[[Make URL]]
	QAK{Auth key<br>supplied?}
	EAK[["Try to find<br>OPENAI_API_KEY<br>in %*ENV"]]
	QEAF{Auth key<br>found?}
	NAK[/Cannot find auth key/]
	UI --> QAK
	QAK --> |yes|MSTC
	QAK --> |no|EAK
	QEAF --> |no|NAK
	QEAF --> |yes|TTC
	TTC -.-> MURL -.-> WR -.-> TTC
	WR -.-> |URL|OpenAI 
	OpenAI -.-> |JSON|WR
	TTC --> Q 
	Q --> |yes|PJ
	Q --> |no|TO
	PJ --> TO

Potential problems

Remark: Currently this package is tested on macOS only.

SSL certificate problems



[AA1] Anton Antonov, "Connecting Mathematica and Raku", (2021), RakuForPrediction at WordPress.


[AAp1] Anton Antonov, Lingua::Translation::DeepL Raku package, (2022), GitHub/antononcube.

[AAp2] Anton Antonov, Text::CodeProcessing, (2021), GitHub/antononcube.

[OAI1] OpenAI Platform, OpenAI platform.

[OAI2] OpenAI Platform, OpenAI documentation.

[OAIp1] OpenAI, OpenAI Python Library, (2020), GitHub/openai.