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ez-php/ai

Composer 安装命令:

composer require ez-php/ai

包简介

Multi-provider AI client for ez-php — unified driver-based abstraction over OpenAI, Anthropic, Gemini, and Mistral

README 文档

README

Multi-provider AI client for ez-php. Supports chat completions, streaming, tool calling, and embeddings across OpenAI, Anthropic, Gemini, Mistral, and Grok.

Installation

composer require ez-php/ai

Requires PHP 8.5 and ez-php/http-client.

Configuration

Register AiServiceProvider in your application and add config/ai.php:

// config/ai.php
return [
    'driver' => env('AI_DRIVER', 'openai'),

    'openai' => [
        'api_key'  => env('OPENAI_API_KEY', ''),
        'model'    => env('OPENAI_MODEL', 'gpt-4o-mini'),
        'base_url' => env('OPENAI_BASE_URL', 'https://api.openai.com'),
    ],

    'anthropic' => [
        'api_key'     => env('ANTHROPIC_API_KEY', ''),
        'model'       => env('ANTHROPIC_MODEL', 'claude-sonnet-4-6'),
        'api_version' => env('ANTHROPIC_API_VERSION', '2023-06-01'),
    ],

    'gemini' => [
        'api_key' => env('GEMINI_API_KEY', ''),
        'model'   => env('GEMINI_MODEL', 'gemini-2.0-flash'),
    ],

    'mistral' => [
        'api_key'  => env('MISTRAL_API_KEY', ''),
        'model'    => env('MISTRAL_MODEL', 'mistral-small-latest'),
        'base_url' => env('MISTRAL_BASE_URL', 'https://api.mistral.ai'),
    ],

    'grok' => [
        'api_key'  => env('GROK_API_KEY', ''),
        'model'    => env('GROK_MODEL', 'grok-3-mini'),
        'base_url' => env('GROK_BASE_URL', 'https://api.x.ai'),
    ],

    'log' => [
        'inner_driver' => env('AI_LOG_INNER_DRIVER', 'openai'),
    ],
];

Driver options

AI_DRIVER value Description
openai OpenAI chat completions API
anthropic Anthropic Messages API
gemini Google Gemini generateContent API
mistral Mistral AI (OpenAI-compatible)
grok xAI Grok (OpenAI-compatible)
log Decorates another driver with error_log output
null Returns empty responses; useful in tests

Environment variables

Variable Default Description
AI_DRIVER null Active driver
OPENAI_API_KEY OpenAI API key
OPENAI_MODEL gpt-4o-mini Default OpenAI model
OPENAI_BASE_URL https://api.openai.com Base URL (Azure / proxy support)
ANTHROPIC_API_KEY Anthropic API key
ANTHROPIC_MODEL claude-sonnet-4-6 Default Anthropic model
ANTHROPIC_API_VERSION 2023-06-01 anthropic-version header value
GEMINI_API_KEY Google AI API key
GEMINI_MODEL gemini-2.0-flash Default Gemini model
MISTRAL_API_KEY Mistral API key
MISTRAL_MODEL mistral-small-latest Default Mistral model
MISTRAL_BASE_URL https://api.mistral.ai Mistral base URL
GROK_API_KEY xAI (Grok) API key
GROK_MODEL grok-3-mini Default Grok model
GROK_BASE_URL https://api.x.ai Grok base URL
AI_LOG_INNER_DRIVER openai Driver wrapped by the log driver

Basic usage

Static facade

use EzPhp\Ai\Ai;
use EzPhp\Ai\Request\AiRequest;

$response = Ai::complete(AiRequest::make('What is the capital of France?'));

echo $response->content(); // "Paris"

Direct driver injection

use EzPhp\Ai\AiClientInterface;
use EzPhp\Ai\Request\AiRequest;

class MyService
{
    public function __construct(private AiClientInterface $ai) {}

    public function ask(string $question): string
    {
        $response = $this->ai->complete(AiRequest::make($question));
        return $response->content();
    }
}

Building requests

AiRequest is immutable. All wither methods return new instances.

use EzPhp\Ai\Request\AiRequest;
use EzPhp\Ai\Message\AiMessage;

// Single user message
$request = AiRequest::make('Hello');

// Explicit message list
$request = AiRequest::withMessages(
    AiMessage::system('You are a helpful assistant.'),
    AiMessage::user('What is 2 + 2?'),
);

// Chain withers
$request = AiRequest::make('Explain async/await')
    ->withModel('gpt-4o')
    ->withTemperature(0.7)
    ->withMaxTokens(500)
    ->withSystemPrompt('You are a concise technical writer.');

// Append a message
$request = $request->addMessage(AiMessage::user('Give an example in PHP.'));

Messages

use EzPhp\Ai\Message\AiMessage;
use EzPhp\Ai\Message\ContentPart;

// Plain text
AiMessage::user('Hello');
AiMessage::assistant('Hi there!');
AiMessage::system('You are a helpful assistant.');

// Multimodal (text + image URL)
AiMessage::userWithParts([
    ContentPart::text('What is in this image?'),
    ContentPart::imageUrl('https://example.com/image.png'),
]);

Streaming

Drivers that implement StreamingAiClientInterface support streaming responses.

use EzPhp\Ai\Ai;
use EzPhp\Ai\Request\AiRequest;
use EzPhp\Ai\StreamingAiClientInterface;

$client = Ai::getClient();

if ($client instanceof StreamingAiClientInterface) {
    $stream = $client->stream(AiRequest::make('Tell me a story.'));

    foreach ($stream as $chunk) {
        echo $chunk->content();

        if ($chunk->isFinal()) {
            echo PHP_EOL;
            echo 'Finish reason: ' . $chunk->finishReason()?->value . PHP_EOL;
        }
    }
}

// Or collect the full text at once
$text = $stream->collect();

All five production drivers (OpenAI, Anthropic, Gemini, Mistral, Grok) implement StreamingAiClientInterface.

Note: Streaming uses SSE post-hoc parsing — the full response body is buffered, then parsed line-by-line. True chunked transfer is not supported.

Tool calling

Define tools, attach them to the request, and handle tool calls in a loop.

use EzPhp\Ai\Ai;
use EzPhp\Ai\Request\AiRequest;
use EzPhp\Ai\Message\AiMessage;
use EzPhp\Ai\Response\FinishReason;
use EzPhp\Ai\Tool\ToolDefinition;

$getWeather = new ToolDefinition(
    name: 'get_weather',
    description: 'Returns the current weather for a city.',
    parameters: [
        'type' => 'object',
        'properties' => [
            'city' => ['type' => 'string', 'description' => 'The city name'],
        ],
        'required' => ['city'],
    ],
);

$request = AiRequest::make('What is the weather in Berlin?')
    ->withTools($getWeather);

$response = Ai::complete($request);

// Agentic loop
while ($response->finishReason() === FinishReason::TOOL_CALL) {
    $toolMessages = [];

    foreach ($response->toolCalls() as $call) {
        $result = match ($call->name()) {
            'get_weather' => json_encode(['temp' => '18°C', 'condition' => 'Cloudy']),
            default       => 'Unknown tool',
        };

        $toolMessages[] = AiMessage::tool($result, $call->id());
    }

    $request = $request
        ->addMessage(AiMessage::assistantWithToolCalls(...$response->toolCalls()))
        ->addMessage(...$toolMessages);  // may need multiple addMessage calls

    $response = Ai::complete($request);
}

echo $response->content();

Gemini note: Gemini does not assign separate IDs to tool calls. The function name is used as the call ID. Use the function name as toolCallId in tool result messages for Gemini conversations.

Streaming + tool calling: Tool calls are only parsed in complete(). The stream() path yields text chunks only.

Embeddings

Use OpenAiEmbeddingDriver or GeminiEmbeddingDriver directly — embeddings are not wired through AiServiceProvider or the Ai facade.

use EzPhp\Ai\Driver\OpenAiConfig;
use EzPhp\Ai\Driver\OpenAiEmbeddingDriver;
use EzPhp\HttpClient\CurlTransport;
use EzPhp\HttpClient\HttpClient;

$driver = new OpenAiEmbeddingDriver(
    new HttpClient(new CurlTransport()),
    new OpenAiConfig(apiKey: $_ENV['OPENAI_API_KEY']),
);

// Returns float[]
$vector = $driver->embed('The quick brown fox');

// Override model
$vector = $driver->embed('Hello world', 'text-embedding-3-large');
use EzPhp\Ai\Driver\GeminiConfig;
use EzPhp\Ai\Driver\GeminiEmbeddingDriver;
use EzPhp\HttpClient\CurlTransport;
use EzPhp\HttpClient\HttpClient;

$driver = new GeminiEmbeddingDriver(
    new HttpClient(new CurlTransport()),
    new GeminiConfig(apiKey: $_ENV['GEMINI_API_KEY']),
);

// Default model: text-embedding-004
$vector = $driver->embed('The quick brown fox');
Driver Default model Endpoint
OpenAiEmbeddingDriver text-embedding-3-small POST /v1/embeddings
GeminiEmbeddingDriver text-embedding-004 POST /v1beta/models/{model}:embedContent

Response object

$response = Ai::complete($request);

$response->content();       // string — generated text
$response->finishReason();  // FinishReason enum: STOP, LENGTH, TOOL_CALL, CONTENT_FILTER, ERROR
$response->usage();         // TokenUsage|null
$response->toolCalls();     // list<ToolCall> — non-empty when finishReason === TOOL_CALL
$response->hasToolCalls();  // bool
$response->rawBody();       // string — raw JSON from the provider

$usage = $response->usage();
if ($usage !== null) {
    $usage->inputTokens();   // int
    $usage->outputTokens();  // int
    $usage->totalTokens();   // int
}

Logging decorator

Wrap any driver to log every request and response via error_log:

// config/ai.php
return [
    'driver' => 'log',
    'log'    => ['inner_driver' => 'openai'],
    'openai' => ['api_key' => env('OPENAI_API_KEY')],
];

Or construct LogDriver manually with a custom logger closure:

use EzPhp\Ai\Driver\LogDriver;

$driver = new LogDriver(
    $innerDriver,
    function (string $level, string $message, array $context): void {
        $this->logger->log($level, $message, $context);
    },
);

OpenAI-compatible proxies and Azure

OpenAiDriver and MistralDriver accept a base_url config key, making them compatible with Azure OpenAI and any OpenAI-compatible proxy:

// config/ai.php — Azure OpenAI
'openai' => [
    'api_key'  => env('AZURE_OPENAI_API_KEY'),
    'model'    => 'gpt-4o',
    'base_url' => env('AZURE_OPENAI_ENDPOINT'), // e.g. https://my-resource.openai.azure.com
],

Testing

In unit tests, inject NullDriver or use FakeTransport from ez-php/http-client:

use EzPhp\Ai\Driver\NullDriver;
use EzPhp\Ai\Request\AiRequest;

$driver = NullDriver::withContent('Paris');
$response = $driver->complete(AiRequest::make('What is the capital of France?'));

assertEquals('Paris', $response->content());
use EzPhp\Ai\Driver\OpenAiDriver;
use EzPhp\Ai\Driver\OpenAiConfig;
use EzPhp\Ai\Request\AiRequest;
use EzPhp\HttpClient\FakeTransport;
use EzPhp\HttpClient\HttpClient;

$fake = new FakeTransport();
$fake->queue(200, '{"choices":[{"message":{"role":"assistant","content":"Paris"},"finish_reason":"stop"}],"usage":{"prompt_tokens":10,"completion_tokens":5,"total_tokens":15}}');

$driver = new OpenAiDriver(
    new HttpClient($fake),
    new OpenAiConfig('test-key'),
);

$response = $driver->complete(AiRequest::make('Capital of France?'));
assertEquals('Paris', $response->content());

Use Ai::resetClient() in tearDown() when tests touch the static facade to prevent state leaking between test cases.

Quality suite

# Inside Docker
docker compose exec app composer full

# Individual steps
docker compose exec app composer analyse   # PHPStan level 9
docker compose exec app composer cs        # php-cs-fixer
docker compose exec app composer test      # PHPUnit

Start the development shell:

./start.sh

ez-php/ai 适用场景与选型建议

ez-php/ai 是一款 基于 PHP 开发的 Composer 扩展包,目前已累计 19 次下载、GitHub Stars 达 0, 最近一次更新时间为 2026 年 04 月 19 日, 在 PHP 生态内属于活跃度较高的组件。

它主要适用于以下技术方向: 「php」 「ai」 「Gemini」 「openai」 「gpt」 「llm」 等业务场景。在实际项目中,围绕这些方向常见需要落地的问题包括:接口对接、性能调优、并发安全、与既有框架(Laravel / ThinkPHP / Yii / Webman 等)的兼容适配,以及生产环境的日志埋点与稳定性保障。

我们在过去多个企业项目中使用过 ez-php/ai 或与其功能相近的方案,如果你在选型或落地过程中遇到问题,例如 版本兼容、二次改造、私有化封装、与内部系统对接、生产 BUG 排查,欢迎联系我们协助评估。

围绕 ez-php/ai 我们能提供哪些服务?
定制开发 / 二次开发

基于 ez-php/ai 在你已有业务上做功能扩展、字段裁剪、UI 适配、与内部账号 / 权限 / 日志系统的深度对接。

BUG 修复 & 性能优化

线上偶发问题、内存泄漏、慢查询、并发异常等排查修复;针对高流量场景做缓存、队列、索引层面的调优。

项目外包 & 长期维护

承接完整的项目从需求 → 设计 → 开发 → 上线 → 长期运维;也可按月提供技术保姆服务。

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统计信息

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GitHub 信息

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  • 开发语言: PHP

其他信息

  • 授权协议: MIT
  • 更新时间: 2026-04-19