floridaman963/openai

Just for a test,the origin is from Openai-php/client

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github.com/floridaman963/openai

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dev-master 2023-04-27 08:20 UTC

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MIT 51b311f71f34ed67465fa7d3a236ddae3bb09478

phpopenai

This package is not auto-updated.

Last update: 2024-12-20 10:46:33 UTC

README

NOTICE Just for a test,the origin is from Openai-php/client

Table of Contents

Get Started

Requires PHP 8.1+

First, install OpenAI via the Composer package manager:

composer require floridaman963/openai

Ensure that the php-http/discovery composer plugin is allowed to run or install a client manually if your project does not already have a PSR-18 client integrated.

composer require guzzlehttp/guzzle

Then, interact with OpenAI's API:

$yourApiKey = getenv('YOUR_API_KEY');
$client = OpenAI::client($yourApiKey);

$result = $client->completions()->create([
    'model' => 'text-davinci-003',
    'prompt' => 'PHP is',
]);

echo $result['choices'][0]['text']; // an open-source, widely-used, server-side scripting language.

If necessary, it is possible to configure and create a separate client.

$yourApiKey = getenv('YOUR_API_KEY');

$client = OpenAI::factory()
    ->withApiKey($yourApiKey)
    ->withOrganization('your-organization') // default: null
    ->withBaseUri('openai.example.com/v1') // default: api.openai.com/v1
    ->withHttpClient($client = new \GuzzleHttp\Client([])) // default: HTTP client found using PSR-18 HTTP Client Discovery
    ->withHttpHeader('X-My-Header', 'foo')
    ->withQueryParam('my-param', 'bar')
    ->withStreamHandler(fn (RequestInterface $request): ResponseInterface => $client->send($request, [
        'stream' => true // Allows to provide a custom stream handler for the http client.
    ]))
    ->make();

Usage

Models Resource

list

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

$response = $client->models()->list();

$response->object; // 'list'

foreach ($response->data as $result) {
    $result->id; // 'text-davinci-003'
    $result->object; // 'model'
    // ...
}

$response->toArray(); // ['object' => 'list', 'data' => [...]]

retrieve

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

$response = $client->models()->retrieve('text-davinci-003');

$response->id; // 'text-davinci-003'
$response->object; // 'model'
$response->created; // 1642018370
$response->ownedBy; // 'openai'
$response->root; // 'text-davinci-003'
$response->parent; // null

foreach ($response->permission as $result) {
    $result->id; // 'modelperm-7E53j9OtnMZggjqlwMxW4QG7' 
    $result->object; // 'model_permission' 
    $result->created; // 1664307523 
    $result->allowCreateEngine; // false 
    $result->allowSampling; // true 
    $result->allowLogprobs; // true 
    $result->allowSearchIndices; // false 
    $result->allowView; // true 
    $result->allowFineTuning; // false 
    $result->organization; // '*' 
    $result->group; // null 
    $result->isBlocking; // false 
}

$response->toArray(); // ['id' => 'text-davinci-003', ...]

delete

Delete a fine-tuned model.

$response = $client->models()->delete('curie:ft-acmeco-2021-03-03-21-44-20');

$response->id; // 'curie:ft-acmeco-2021-03-03-21-44-20'
$response->object; // 'model'
$response->deleted; // true

$response->toArray(); // ['id' => 'curie:ft-acmeco-2021-03-03-21-44-20', ...]

Completions Resource

create

Creates a completion for the provided prompt and parameters.

$response = $client->completions()->create([
    'model' => 'text-davinci-003',
    'prompt' => 'Say this is a test',
    'max_tokens' => 6,
    'temperature' => 0
]);

$response->id; // 'cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7'
$response->object; // 'text_completion'
$response->created; // 1589478378
$response->model; // 'text-davinci-003'

foreach ($response->choices as $result) {
    $result->text; // '\n\nThis is a test'
    $result->index; // 0
    $result->logprobs; // null
    $result->finishReason; // 'length' or null
}

$response->usage->promptTokens; // 5,
$response->usage->completionTokens; // 6,
$response->usage->totalTokens; // 11

$response->toArray(); // ['id' => 'cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7', ...]

create streamed

Creates a streamed completion for the provided prompt and parameters.

$stream = $client->completions()->createStreamed([
        'model' => 'text-davinci-003',
        'prompt' => 'Hi',
        'max_tokens' => 10,
    ]);

foreach($stream as $response){
    $response->choices[0]->text;
}
// 1. iteration => 'I'
// 2. iteration => ' am'
// 3. iteration => ' very'
// 4. iteration => ' excited'
// ...

Chat Resource

create

Creates a completion for the chat message.

$response = $client->chat()->create([
    'model' => 'gpt-3.5-turbo',
    'messages' => [
        ['role' => 'user', 'content' => 'Hello!'],
    ],
]);

$response->id; // 'chatcmpl-6pMyfj1HF4QXnfvjtfzvufZSQq6Eq'
$response->object; // 'chat.completion'
$response->created; // 1677701073
$response->model; // 'gpt-3.5-turbo-0301'

foreach ($response->choices as $result) {
    $result->index; // 0
    $result->message->role; // 'assistant'
    $result->message->content; // '\n\nHello there! How can I assist you today?'
    $result->finishReason; // 'stop'
}

$response->usage->promptTokens; // 9,
$response->usage->completionTokens; // 12,
$response->usage->totalTokens; // 21

$response->toArray(); // ['id' => 'chatcmpl-6pMyfj1HF4QXnfvjtfzvufZSQq6Eq', ...]

created streamed

Creates a streamed completion for the chat message.

$stream = $client->chat()->createStreamed([
    'model' => 'gpt-4',
    'messages' => [
        ['role' => 'user', 'content' => 'Hello!'],
    ],
]);

foreach($stream as $response){
    $response->choices[0]->toArray();
}
// 1. iteration => ['index' => 0, 'delta' => ['role' => 'assistant'], 'finish_reason' => null]
// 2. iteration => ['index' => 0, 'delta' => ['content' => 'Hello'], 'finish_reason' => null]
// 3. iteration => ['index' => 0, 'delta' => ['content' => '!'], 'finish_reason' => null]
// ...

Audio Resource

transcribe

Transcribes audio into the input language.

$response = $client->audio()->transcribe([
    'model' => 'whisper-1',
    'file' => fopen('audio.mp3', 'r'),
    'response_format' => 'verbose_json',
]);

$response->task; // 'transcribe'
$response->language; // 'english'
$response->duration; // 2.95
$response->text; // 'Hello, how are you?'

foreach ($response->segments as $segment) {
    $segment->index; // 0
    $segment->seek; // 0
    $segment->start; // 0.0
    $segment->end; // 4.0
    $segment->text; // 'Hello, how are you?'
    $segment->tokens; // [50364, 2425, 11, 577, 366, 291, 30, 50564]
    $segment->temperature; // 0.0
    $segment->avgLogprob; // -0.45045216878255206
    $segment->compressionRatio; // 0.7037037037037037
    $segment->noSpeechProb; // 0.1076972484588623
    $segment->transient; // false
}

$response->toArray(); // ['task' => 'transcribe', ...]

translate

Translates audio into English.

$response = $client->audio()->translate([
    'model' => 'whisper-1',
    'file' => fopen('german.mp3', 'r'),
    'response_format' => 'verbose_json',
]);

$response->task; // 'translate'
$response->language; // 'english'
$response->duration; // 2.95
$response->text; // 'Hello, how are you?'

foreach ($response->segments as $segment) {
    $segment->index; // 0
    $segment->seek; // 0
    $segment->start; // 0.0
    $segment->end; // 4.0
    $segment->text; // 'Hello, how are you?'
    $segment->tokens; // [50364, 2425, 11, 577, 366, 291, 30, 50564]
    $segment->temperature; // 0.0
    $segment->avgLogprob; // -0.45045216878255206
    $segment->compressionRatio; // 0.7037037037037037
    $segment->noSpeechProb; // 0.1076972484588623
    $segment->transient; // false
}

$response->toArray(); // ['task' => 'translate', ...]

Edits Resource

create

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

$response = $client->edits()->create([
    'model' => 'text-davinci-edit-001',
    'input' => 'What day of the wek is it?',
    'instruction' => 'Fix the spelling mistakes',
]);

$response->object; // 'edit'
$response->created; // 1589478378

foreach ($response->choices as $result) {
    $result->text; // 'What day of the week is it?'
    $result->index; // 0
}

$response->usage->promptTokens; // 25,
$response->usage->completionTokens; // 32,
$response->usage->totalTokens; // 57

$response->toArray(); // ['object' => 'edit', ...]

Embeddings Resource

create

Creates an embedding vector representing the input text.

$response = $client->embeddings()->create([
    'model' => 'text-similarity-babbage-001',
    'input' => 'The food was delicious and the waiter...',
]);

$response->object; // 'list'

foreach ($response->embeddings as $embedding) {
    $embedding->object; // 'embedding'
    $embedding->embedding; // [0.018990106880664825, -0.0073809814639389515, ...]
    $embedding->index; // 0
}

$response->usage->promptTokens; // 8,
$response->usage->totalTokens; // 8

$response->toArray(); // ['data' => [...], ...]

Files Resource

list

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

$response = $client->files()->list();

$response->object; // 'list'

foreach ($response->data as $result) {
    $result->id; // 'file-XjGxS3KTG0uNmNOK362iJua3'
    $result->object; // 'file'
    // ...
}

$response->toArray(); // ['object' => 'list', 'data' => [...]]

delete

Delete a file.

$response = $client->files()->delete($file);

$response->id; // 'file-XjGxS3KTG0uNmNOK362iJua3'
$response->object; // 'file'
$response->deleted; // true

$response->toArray(); // ['id' => 'file-XjGxS3KTG0uNmNOK362iJua3', ...]

retrieve

Returns information about a specific file.

$response = $client->files()->retrieve('file-XjGxS3KTG0uNmNOK362iJua3');

$response->id; // 'file-XjGxS3KTG0uNmNOK362iJua3'
$response->object; // 'file'
$response->bytes; // 140
$response->createdAt; // 1613779657
$response->filename; // 'mydata.jsonl'
$response->purpose; // 'fine-tune'
$response->status; // 'succeeded'
$response->status_details; // null

$response->toArray(); // ['id' => 'file-XjGxS3KTG0uNmNOK362iJua3', ...]

upload

Upload a file that contains document(s) to be used across various endpoints/features.

$response = $client->files()->upload([
        'purpose' => 'fine-tune',
        'file' => fopen('my-file.jsonl', 'r'),
    ]);

$response->id; // 'file-XjGxS3KTG0uNmNOK362iJua3'
$response->object; // 'file'
$response->bytes; // 140
$response->createdAt; // 1613779657
$response->filename; // 'mydata.jsonl'
$response->purpose; // 'fine-tune'
$response->status; // 'succeeded'
$response->status_details; // null

$response->toArray(); // ['id' => 'file-XjGxS3KTG0uNmNOK362iJua3', ...]

download

Returns the contents of the specified file.

$client->files()->download($file); // '{"prompt": "<prompt text>", ...'

FineTunes Resource

create

Creates a job that fine-tunes a specified model from a given dataset.

$response = $client->fineTunes()->create([
    'training_file' => 'file-ajSREls59WBbvgSzJSVWxMCB',
    'validation_file' => 'file-XjSREls59WBbvgSzJSVWxMCa',
    'model' => 'curie',
    'n_epochs' => 4,
    'batch_size' => null,
    'learning_rate_multiplier' => null,
    'prompt_loss_weight' => 0.01,
    'compute_classification_metrics' => false,
    'classification_n_classes' => null,
    'classification_positive_class' => null,
    'classification_betas' => [],
    'suffix' => null,
]);

$response->id; // 'ft-AF1WoRqd3aJAHsqc9NY7iL8F'
$response->object; // 'fine-tune'
// ...

$response->toArray(); // ['id' => 'ft-AF1WoRqd3aJAHsqc9NY7iL8F', ...]

list

List your organization's fine-tuning jobs.

$response = $client->fineTunes()->list();

$response->object; // 'list'

foreach ($response->data as $result) {
    $result->id; // 'ft-AF1WoRqd3aJAHsqc9NY7iL8F'
    $result->object; // 'fine-tune'
    // ...
}

$response->toArray(); // ['object' => 'list', 'data' => [...]]

retrieve

Gets info about the fine-tune job.

$response = $client->fineTunes()->retrieve('ft-AF1WoRqd3aJAHsqc9NY7iL8F');

$response->id; // 'ft-AF1WoRqd3aJAHsqc9NY7iL8F'
$response->object; // 'fine-tune'
$response->model; // 'curie'
$response->createdAt; // 1614807352
$response->fineTunedModel; // 'curie => ft-acmeco-2021-03-03-21-44-20'
$response->organizationId; // 'org-jwe45798ASN82s'
$response->resultFiles; // [
$response->status; // 'succeeded'
$response->validationFiles; // [
$response->trainingFiles; // [
$response->updatedAt; // 1614807865

foreach ($response->events as $result) {
    $result->object; // 'fine-tune-event' 
    $result->createdAt; // 1614807352
    $result->level; // 'info'
    $result->message; // 'Job enqueued. Waiting for jobs ahead to complete. Queue number =>  0.'
}

$response->hyperparams->batchSize; // 4 
$response->hyperparams->learningRateMultiplier; // 0.1 
$response->hyperparams->nEpochs; // 4 
$response->hyperparams->promptLossWeight; // 0.1

foreach ($response->resultFiles as $result) {
    $result->id; // 'file-XjGxS3KTG0uNmNOK362iJua3'
    $result->object; // 'file'
    $result->bytes; // 140
    $result->createdAt; // 1613779657
    $result->filename; // 'mydata.jsonl'
    $result->purpose; // 'fine-tune'
    $result->status; // 'succeeded'
    $result->status_details; // null
}

foreach ($response->validationFiles as $result) {
    $result->id; // 'file-XjGxS3KTG0uNmNOK362iJua3'
    // ...
}

foreach ($response->trainingFiles as $result) {
    $result->id; // 'file-XjGxS3KTG0uNmNOK362iJua3'
    // ...
}

$response->toArray(); // ['id' => 'ft-AF1WoRqd3aJAHsqc9NY7iL8F', ...]

cancel

Immediately cancel a fine-tune job.

$response = $client->fineTunes()->cancel('ft-AF1WoRqd3aJAHsqc9NY7iL8F');

$response->id; // 'ft-AF1WoRqd3aJAHsqc9NY7iL8F'
$response->object; // 'fine-tune'
// ...
$response->status; // 'cancelled'
// ...

$response->toArray(); // ['id' => 'ft-AF1WoRqd3aJAHsqc9NY7iL8F', ...]

list events

Get fine-grained status updates for a fine-tune job.

$response = $client->fineTunes()->listEvents('ft-AF1WoRqd3aJAHsqc9NY7iL8F');

$response->object; // 'list'

foreach ($response->data as $result) {
    $result->object; // 'fine-tune-event' 
    $result->createdAt; // 1614807352
    // ...
}

$response->toArray(); // ['object' => 'list', 'data' => [...]]

list events streamed

Get streamed fine-grained status updates for a fine-tune job.

$stream = $client->fineTunes()->listEventsStreamed('ft-y3OpNlc8B5qBVGCCVsLZsDST');

foreach($stream as $response){
    $response->message;
}
// 1. iteration => 'Created fine-tune: ft-y3OpNlc8B5qBVGCCVsLZsDST'
// 2. iteration => 'Fine-tune costs $0.00'
// ...
// xx. iteration => 'Uploaded result file: file-ajLKUCMsFPrT633zqwr0eI4l'
// xx. iteration => 'Fine-tune succeeded'

Moderations Resource

create

Classifies if text violates OpenAI's Content Policy.

$response = $client->moderations()->create([
    'model' => 'text-moderation-latest',
    'input' => 'I want to k*** them.',
]);

$response->id; // modr-5xOyuS
$response->model; // text-moderation-003

foreach ($response->results as $result) {
    $result->flagged; // true

    foreach ($result->categories as $category) {
        $category->category->value; // 'violence'
        $category->violated; // true
        $category->score; // 0.97431367635727
    }
}

$response->toArray(); // ['id' => 'modr-5xOyuS', ...]

Images Resource

create

Creates an image given a prompt.

$response = $client->images()->create([
    'prompt' => 'A cute baby sea otter',
    'n' => 1,
    'size' => '256x256',
    'response_format' => 'url',
]);

$response->created; // 1589478378

foreach ($response->data as $data) {
    $data->url; // 'https://oaidalleapiprodscus.blob.core.windows.net/private/...'
    $data->b64_json; // null
}

$response->toArray(); // ['created' => 1589478378, data => ['url' => 'https://oaidalleapiprodscus...', ...]]

edit

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

$response = $client->images()->edit([
    'image' => fopen('image_edit_original.png', 'r'),
    'mask' => fopen('image_edit_mask.png', 'r'),
    'prompt' => 'A sunlit indoor lounge area with a pool containing a flamingo',
    'n' => 1,
    'size' => '256x256',
    'response_format' => 'url',
]);

$response->created; // 1589478378

foreach ($response->data as $data) {
    $data->url; // 'https://oaidalleapiprodscus.blob.core.windows.net/private/...'
    $data->b64_json; // null
}

$response->toArray(); // ['created' => 1589478378, data => ['url' => 'https://oaidalleapiprodscus...', ...]]

variation

Creates a variation of a given image.

$response = $client->images()->variation([
    'image' => fopen('image_edit_original.png', 'r'),
    'n' => 1,
    'size' => '256x256',
    'response_format' => 'url',
]);

$response->created; // 1589478378

foreach ($response->data as $data) {
    $data->url; // 'https://oaidalleapiprodscus.blob.core.windows.net/private/...'
    $data->b64_json; // null
}

$response->toArray(); // ['created' => 1589478378, data => ['url' => 'https://oaidalleapiprodscus...', ...]]

Testing

The package provides a fake implementation of the OpenAI\Client class that allows you to fake the API responses.

To test your code ensure you swap the OpenAI\Client class with the OpenAI\Testing\ClientFake class in your test case.

The fake responses are returned in the order they are provided while creating the fake client.

All responses are having a fake() method that allows you to easily create a response object by only providing the parameters relevant for your test case.

use OpenAI\Testing\ClientFake;
use OpenAI\Responses\Completions\CreateResponse;

$client = new ClientFake([
    CreateResponse::fake([
        'choices' => [
            [
                'text' => 'awesome!',
            ],
        ],
    ]),
]);

$completion = $client->completions()->create([
    'model' => 'text-davinci-003',
    'prompt' => 'PHP is ',
]);

expect($completion['choices'][0]['text'])->toBe('awesome!');

In case of a streamed response you can optionally provide a resource holding the fake response data.

use OpenAI\Testing\ClientFake;
use OpenAI\Responses\Chat\CreateStreamedResponse;

$client = new ClientFake([
    CreateStreamedResponse::fake(fopen('file.txt', 'r'););
]);

$completion = $client->chat()->createStreamed([
        'model' => 'gpt-3.5-turbo',
        'messages' => [
            ['role' => 'user', 'content' => 'Hello!'],
        ],
]);

expect($response->getIterator()->current())
        ->id->toBe('chatcmpl-6yo21W6LVo8Tw2yBf7aGf2g17IeIl');

After the requests have been sent there are various methods to ensure that the expected requests were sent:

// assert completion create request was sent
$client->assertSent(Completions::class, function (string $method, array $parameters): bool {
    return $method === 'create' &&
        $parameters['model'] === 'text-davinci-003' &&
        $parameters['prompt'] === 'PHP is ';
});
// or
$client->completions()->assertSent(function (string $method, array $parameters): bool {
    // ...
});

// assert 2 completion create requests were sent
$client->assertSent(Completions::class, 2);

// assert no completion create requests were sent
$client->assertNotSent(Completions::class);
// or
$client->completions()->assertNotSent();

// assert no requests were sent
$client->assertNothingSent();

To write tests expecting the API request to fail you can provide a Throwable object as the response.

$client = new ClientFake([
    new \OpenAI\Exceptions\ErrorException([
        'message' => 'The model `gpt-1` does not exist',
        'type' => 'invalid_request_error',
        'code' => null,
    ])
]);

// the `ErrorException` will be thrown
$completion = $client->completions()->create([
    'model' => 'text-davinci-003',
    'prompt' => 'PHP is ',
]);

Services

Azure

In order to use the Azure OpenAI Service, it is necessary to construct the client manually using the factory.

$client = OpenAI::factory()
    ->withBaseUri('{your-resource-name}.openai.azure.com/openai/deployments/{deployment-id}')
    ->withHttpHeader('api-key', '{your-api-key}')
    ->withQueryParam('api-version', '{version}')
    ->make();

To use Azure, you must deploy a model, identified by the {deployment-id}, which is already incorporated into the API calls. As a result, you do not have to provide the model during the calls since it is included in the BaseUri.

Therefore, a basic sample completion call would be:

$result = $client->completions()->create([
    'prompt' => 'PHP is'
]);

OpenAI PHP is an open-sourced software licensed under the MIT license.