OpenAI GPT-3 Api Client in PHP

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To get started with this package, you'll first want to be familiar with the OpenAI API documentation and examples.

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Installation

You can install the package via composer:

composer require orhanerday/open-ai

Quick Start

Before you get starting, you should set OPENAI_API_KEY as ENV key, and set OpenAI key as env value with the following commands;

Powershell

$Env:OPENAI_API_KEY = "sk-gjtv....."

Cmd

set OPENAI_API_KEY=sk-gjtv.....

Linux or macOS

export OPENAI_API_KEY=sk-gjtv.....

Getting issues while setting up env? Please read https://help.openai.com/en/articles/5112595-best-practices-for-api-key-safety article.

Create your index.php file and paste the following code part into the file.

<?php

require __DIR__ . '/vendor/autoload.php'; // remove this line if you use a PHP Framework.

use Orhanerday\OpenAi\OpenAi;

$open_ai_key = getenv('OPENAI_API_KEY');
$open_ai = new OpenAi($open_ai_key);

$complete = $open_ai->complete([
    'engine' => 'davinci',
    'prompt' => 'Hello',
    'temperature' => 0.9,
    'max_tokens' => 150,
    'frequency_penalty' => 0,
    'presence_penalty' => 0.6,
]);

var_dump($complete);

Run the server with the following command

php -S localhost:8000 -t .

Usage

Load your key from an environment variable.

According to the following code $open_ai is the base variable for all open-ai operations.

use Orhanerday\OpenAi\OpenAi;

$open_ai = new OpenAi(env('OPEN_AI_API_KEY'));

Completions

Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position.

$complete = $open_ai->completion([
   'model' => 'text-davinci-002',
   'prompt' => 'Hello',
   'temperature' => 0.9,
   'max_tokens' => 150,
   'frequency_penalty' => 0,
   'presence_penalty' => 0.6,
]);

Edits

Creates a new edit for the provided input, instruction, and parameters

   $result = $open_ai->createEdit([
       "model" => "text-davinci-edit-001",
       "input" => "What day of the wek is it?",
       "instruction" => "Fix the spelling mistakes",
   ]);

Images (DALL·E)

All DALL·E Examples available in this repo.

Given a prompt, the model will return one or more generated images as urls or base64 encoded.

Create image

Creates an image given a prompt.

$complete = $open_ai->image([
   "prompt" => "A cat drinking milk",
   "n" => 1,
   "size" => "256x256",
   "response_format" => "url",
]);

Create image edit

Creates an edited or extended image given an original image and a prompt.

You need HTML upload for image edit or variation? Please check DALL·E Examples

$otter = curl_file_create(__DIR__ . './files/otter.png');
$mask = curl_file_create(__DIR__ . './files/mask.jpg');

$result = $open_ai->imageEdit([
    "image" => $otter,
    "mask" => $mask,
    "prompt" => "A cute baby sea otter wearing a beret",
    "n" => 2,
    "size" => "1024x1024",
]);

Create image variation

Creates a variation of a given image.

$otter = curl_file_create(__DIR__ . './files/otter.png');

$result = $open_ai->createImageVariation([
    "image" => $otter,
    "n" => 2,
    "size" => "256x256",
]);

Searches

(Deprecated)

This endpoint is deprecated and will be removed on December 3rd, 2022 OpenAI developed new methods with better performance. Learn more.

Given a query and a set of documents or labels, the model ranks each document based on its semantic similarity to the provided query.

$search = $open_ai->search([
    'engine' => 'ada',
    'documents' => ['White House', 'hospital', 'school'],
    'query' => 'the president',
]);

Embeddings

Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.

Related guide: Embeddings

Create embeddings

$result = $open_ai->embeddings([
    "model" => "text-similarity-babbage-001",
    "input" => "The food was delicious and the waiter..."
]);

Answers

(Deprecated)

This endpoint is deprecated and will be removed on December 3rd, 2022 We’ve developed new methods with better performance. Learn more.

Given a question, a set of documents, and some examples, the API generates an answer to the question based on the information in the set of documents. This is useful for question-answering applications on sources of truth, like company documentation or a knowledge base.

$answer = $open_ai->answer([
  'documents' => ['Puppy A is happy.', 'Puppy B is sad.'],
  'question' => 'which puppy is happy?',
  'search_model' => 'ada',
  'model' => 'curie',
  'examples_context' => 'In 2017, U.S. life expectancy was 78.6 years.',
  'examples' => [['What is human life expectancy in the United States?', '78 years.']],
  'max_tokens' => 5,
  'stop' => ["\n", '<|endoftext|>'],
]);

Classifications

(Deprecated)

This endpoint is deprecated and will be removed on December 3rd, 2022 OpenAI developed new methods with better performance. Learn more.

Given a query and a set of labeled examples, the model will predict the most likely label for the query. Useful as a drop-in replacement for any ML classification or text-to-label task.

$classification = $open_ai->classification([
   'examples' => [
       ['A happy moment', 'Positive'],
       ['I am sad.', 'Negative'],
       ['I am feeling awesome', 'Positive'],
   ],
   'labels' => ['Positive', 'Negative', 'Neutral'],
   'query' => 'It is a raining day =>(',
   'search_model' => 'ada',
   'model' => 'curie',
]);

Content Moderations

Given a input text, outputs if the model classifies it as violating OpenAI's content policy.

$flags = $open_ai->moderation([
    'input' => 'I want to kill them.'
]);

Know more about Content Moderations here: OpenAI Moderations

List engines

(Deprecated)

The Engines endpoints are deprecated. Please use their replacement, Models, instead. Learn more.

Lists the currently available engines, and provides basic information about each one such as the owner and availability.

$engines = $open_ai->engines();

Files

Files are used to upload documents that can be used across features like Answers, Search, and Classifications

List files

Returns a list of files that belong to the user's organization.

$files = $open_ai->listFiles();

Upload file

Upload a file that contains document(s) to be used across various endpoints/features. Currently, the size of all the files uploaded by one organization can be up to 1 GB. Please contact OpenAI if you need to increase the storage limit.

$c_file = curl_file_create(__DIR__ . 'files/sample_file_1.jsonl');
$result = $open_ai->uploadFile([
            "purpose" => "answers",
            "file" => $c_file,
]);

Upload file with HTML Form

<form action="index.php" method="post" enctype="multipart/form-data">
    Select file to upload:
    <input type="file" name="fileToUpload" id="fileToUpload">
    <input type="submit" value="Upload File" name="submit">
</form>
<?php
require __DIR__ . '/vendor/autoload.php';

use Orhanerday\OpenAi\OpenAi;

if ($_SERVER['REQUEST_METHOD'] == 'POST') {
    ob_clean();
    $open_ai = new OpenAi('YOUR_API_KEY');
    $tmp_file = $_FILES['fileToUpload']['tmp_name'];
    $file_name = basename($_FILES['fileToUpload']['name']);
    $c_file = curl_file_create($tmp_file, $_FILES['fileToUpload']['type'], $file_name);

    echo "[";
    echo $open_ai->uploadFile(
        [
            "purpose" => "answers",
            "file" => $c_file,
        ]
    );
    echo ",";
    echo $open_ai->listFiles();
    echo "]";

}

Delete file

$result = $open_ai->deleteFile('file-xxxxxxxx');

Retrieve file

$file = $open_ai->retrieveFile('file-xxxxxxxx');

Retrieve file content

$file = $open_ai->retrieveFileContent('file-xxxxxxxx');

Fine-tunes

Manage fine-tuning jobs to tailor a model to your specific training data.

Create fine-tune

$result = $open_ai->createFineTune([
       "training_file" => "file-U3KoAAtGsjUKSPXwEUDdtw86",
]);

List fine-tune

$fine_tunes = $open_ai->listFineTunes();

Retrieve fine-tune

$fine_tune = $open_ai->retrieveFineTune('ft-AF1WoRqd3aJAHsqc9NY7iL8F');

Cancel fine-tune

$result = $open_ai->cancelFineTune('ft-AF1WoRqd3aJAHsqc9NY7iL8F');

List fine-tune events

$fine_tune_events = $open_ai->listFineTuneEvents('ft-AF1WoRqd3aJAHsqc9NY7iL8F');

Delete fine-tune model

$result = $open_ai->deleteFineTune('curie:ft-acmeco-2021-03-03-21-44-20');

Retrieve engine

(Deprecated)

Retrieves an engine instance, providing basic information about the engine such as the owner and availability.

$engine = $open_ai->engine('davinci');

Models

List and describe the various models available in the API.

List models

Lists the currently available models, and provides basic information about each one such as the owner and availability.

$result = $open_ai->listModels();

Retrieve model

Retrieves a model instance, providing basic information about the model such as the owner and permissioning.

$result = $open_ai->retrieveModel("text-ada-001");

Printing results i.e. $search

echo $search;

Testing

To run all tests:

composer test

To run only those tests that work for most user (exclude those that require a missing folder or that hit deprecated endpoints no longer available to most users):

./vendor/bin/pest --group=working

Changelog

Please see CHANGELOG for more information on what has changed recently.

Contributing

Please see CONTRIBUTING for details.

Security Vulnerabilities

Please report security vulnerabilities to orhanerday@gmail.com

Credits

• Orhan Erday
• All Contributors

License

The MIT License (MIT). Please see License File for more information.

Donation