teariot/php-yandex-gpt 问题修复 & 功能扩展

解决BUG、新增功能、兼容多环境部署,快速响应你的开发需求

邮箱:yvsm@zunyunkeji.com | QQ:316430983 | 微信:yvsm316

teariot/php-yandex-gpt

Composer 安装命令:

composer require teariot/php-yandex-gpt

包简介

A PHP library for seamless interaction with Yandex GPT (Generative Pre-trained Transformer) API, providing text generation, tokenization, and embedding functionalities.

README 文档

README

This PHP library provides a convenient interface to interact with Yandex GPT (Generative Pre-trained Transformer) API for text generation, tokenization, and obtaining embeddings.

Installation

To install the library via Composer, use the following command:

composer require teariot/php-yandex-gpt

Usage

Ensure you have obtained the necessary OAuth token and folder ID from Yandex GPT.

Text Completion

To generate text completions, use the complete method:

<?php

const OAuthToken = 'YOUR_OAUTH_TOKEN';
const folder_id = 'YOUR_FOLDER_ID';

public static function complete(string $message): array
{
    $cloud = new Cloud(self::OAuthToken, self::folder_id);
    $completion = new Completion();
    
    $completion->setModelUri(self::folder_id, 'yandexgpt-lite/latest')
            ->addText([
                [
                    'role' => $completion::USER,
                    'text' => $message,
                ]
            ]);

    $result = $cloud->request($completion);
    return json_decode($result, true);
}
?>

Or you can use asynchronous text generation.

<?php

const OAuthToken = 'YOUR_OAUTH_TOKEN';
const folder_id = 'YOUR_FOLDER_ID';

public static function complete(string $message): array
{
    $cloud = new Cloud(self::OAuthToken, self::folder_id);
    $completion = new Completion();
    
    $completion->setModelUri(self::folder_id, 'yandexgpt-lite/latest')
            ->addText([
                [
                    'role' => $completion::USER,
                    'text' => $message,
                ]
            ])
            ->isAsync();
            
    $taskData = $cloud->request($completion);
    $taskData = json_decode($taskData, true);
    
    $operation = new Operation();
    if (!empty($taskData) && isset($taskData['id'])) {
        $operation = $operation->waitAndGet($result['id'])
            ->setTimeOut(240);  // Optional: Sets the timeout for the operation. Default timeout is 120 seconds.
            
        $result = $cloud->request($operation);
        $result = json_decode($result, true);
        return json_decode($result, true);
    }
    return [];
}
?>

Enhanced Usage of complete Method

This variation showcases an extended use case of the complete method by incorporating system messages along with user messages.

<?php

const OAuthToken = 'YOUR_OAUTH_TOKEN';
const folder_id = 'YOUR_FOLDER_ID';

public static function complete(string $systemMessage, string $userMessage): array
{
    $cloud = new Cloud(self::OAuthToken, self::folder_id);
    $completion = new Completion();
    
    $completion->setModelUri(self::folder_id, 'yandexgpt-lite/latest')
            ->addText([
                [
                    'role' => $completion::SYSTEM,
                    'text' => $systemMessage,
                ],
                [
                    'role' => $completion::USER,
                    'text' => $message,
                ],
            ]);

    $result = $cloud->request($completion);
    return json_decode($result, true);
}
?>

Tokenization

For tokenizing text, utilize the tokenize method:

<?php

const OAuthToken = 'YOUR_OAUTH_TOKEN';
const folder_id = 'YOUR_FOLDER_ID';

public static function tokenize(string $message): array
{
    $cloud = new Cloud(self::OAuthToken, self::folder_id);
    $tokenize = new Tokenize($message);
    $tokenize->setModelUri(self::folder_id, 'yandexgpt/latest');
    
    $result = $cloud->request($tokenize);
    return json_decode($result, true);
}
?>

Obtaining Embeddings

To obtain embeddings from text data, use the embedding method:

<?php

const OAuthToken = 'YOUR_OAUTH_TOKEN';
const folder_id = 'YOUR_FOLDER_ID';

public static function embedding(string $message): array
{
    $cloud = new Cloud(self::OAuthToken, self::folder_id);
    $embedding = new Embedding($message);
    $embedding->setModelUri(self::folder_id, 'text-search-query/latest');
    
    $result = $cloud->request($embedding);
    return json_decode($result, true);
}
?>

Remember to replace 'YOUR_OAUTH_TOKEN' and 'YOUR_FOLDER_ID' with your actual credentials obtained from Yandex GPT.

For detailed information on available parameters and configurations, please refer to the library documentation or Yandex GPT API documentation.

License

This library is licensed under the MIT License - see the LICENSE file for details.

teariot/php-yandex-gpt 适用场景与选型建议

teariot/php-yandex-gpt 是一款 基于 PHP 开发的 Composer 扩展包,目前已累计 3.63k 次下载、GitHub Stars 达 4, 最近一次更新时间为 2024 年 01 月 09 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: 「yandex」 「Yandex GPT」 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 teariot/php-yandex-gpt 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 teariot/php-yandex-gpt 我们能提供哪些服务?
定制开发 / 二次开发

基于 teariot/php-yandex-gpt 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。

yvsm@zunyunkeji.com QQ:316430983 微信:yvsm316 西安尊云信息科技 · 专注 PHP / Go / 分布式系统研发

统计信息

  • 总下载量: 3.63k
  • 月度下载量: 0
  • 日度下载量: 0
  • 收藏数: 4
  • 点击次数: 31
  • 依赖项目数: 0
  • 推荐数: 0

GitHub 信息

  • Stars: 4
  • Watchers: 1
  • Forks: 3
  • 开发语言: PHP

其他信息

  • 授权协议: MIT
  • 更新时间: 2024-01-09