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functionality for LLM service providers","maintainers":[{"name":"qcgm1978","email":"qcgm197874@gmail.com"}],"readme":"# @qcgm1978/llm-core\n\nLLM服务提供商核心功能库，支持多种大语言模型服务的统一管理和调用。\n\n## 功能特点\n\n- 统一管理多种LLM服务提供商的API配置\n- 支持OpenAI、Google Gemini、DeepSeek、Groq、OpenRouter等多个服务\n- 提供浏览器和Node.js双环境支持\n- 简洁易用的API接口\n- TypeScript类型支持\n- 流式响应和定义生成支持\n\n## 安装\n\n### NPM/Yarn安装\n\n```bash\nnpm install @qcgm1978/llm-core\n# 或\nyarn add @qcgm1978/llm-core\n# 或\ncnpm install @qcgm1978/llm-core\n```\n\n### 浏览器直接引入\n\n使用CDN服务直接在HTML中引入：\n\n```html\n<!-- 使用unpkg CDN -->\n<script src=\"https://unpkg.com/@qcgm1978/llm-core@latest/dist/browser.js\"></script>\n\n<!-- 或使用jsdelivr CDN -->\n<script src=\"https://cdn.jsdelivr.net/npm/@qcgm1978/llm-core@latest/dist/browser.js\"></script>\n```\n\n## 使用方法\n\n### 1. Node.js环境基本使用\n\n```javascript\n// ESM导入\nimport { initServices, llmService, providerNamesConfig } from '@qcgm1978/llm-core';\n\n// 初始化特定服务\nconst apiKeys = {\n  openai: 'your-openai-api-key',\n  gemini: 'your-gemini-api-key'\n};\n\n// 初始化服务\ninitServices(apiKeys);\n\n// 或者初始化所有服务（如果有所有API密钥）\n// import { initAllServices } from '@qcgm1978/llm-core';\n// initAllServices(apiKeys);\n\n// 获取所有可用的服务提供商名称\nconsole.log(Object.keys(providerNamesConfig));\n```\n\n### 2. 使用llmService进行对话\n\n```javascript\n// 设置当前使用的提供商\nllmService.setCurrentProvider('openai');\n\n// 执行简单对话\nasync function runChat() {\n  try {\n    // 同步响应\n    const response = await llmService.chat('你好，介绍一下自己');\n    console.log('AI响应:', response);\n    \n    // 流式响应\n    const stream = await llmService.streamChat('请解释什么是人工智能');\n    let fullResponse = '';\n    \n    for await (const chunk of stream) {\n      fullResponse += chunk;\n      console.log('流式输出:', chunk);\n    }\n    \n    console.log('完整响应:', fullResponse);\n  } catch (error) {\n    console.error('对话错误:', error);\n  }\n}\n\nrunChat();\n```\n\n### 3. 定义生成功能\n\n```javascript\n// 生成定义\nasync function generateDefinition() {\n  // 定义主题、语言和上下文\n  const topic = '机器学习';\n  const language = 'zh'; // 可选，默认为'zh'\n  const context = '为初学者提供简明解释'; // 可选\n  \n  try {\n    // 生成定义\n    const definition = await llmService.generateDefinition(topic, language, context);\n    console.log('生成的定义:', definition);\n    \n    // 流式生成定义\n    const stream = await llmService.streamDefinition(topic, language, context);\n    let fullDefinition = '';\n    \n    for await (const chunk of stream) {\n      fullDefinition += chunk;\n      console.log('流式定义输出:', chunk);\n    }\n    \n    console.log('完整定义:', fullDefinition);\n  } catch (error) {\n    console.error('定义生成错误:', error);\n  }\n}\n\ngenerateDefinition();\n```\n\n### 4. 浏览器环境使用\n\n在浏览器中引入后，可通过全局变量`llmCore`访问所有功能：\n\n```javascript\n// 检查全局变量是否存在\nif (typeof llmCore !== 'undefined') {\n  // 初始化服务\n  const apiKeys = {\n    openai: document.getElementById('openai-api-key').value\n  };\n  \n  llmCore.initServices(apiKeys);\n  llmCore.llmService.setCurrentProvider('openai');\n  \n  // 绑定按钮点击事件\n  document.getElementById('chat-button').addEventListener('click', async () => {\n    const prompt = document.getElementById('prompt-input').value;\n    const responseElement = document.getElementById('response-output');\n    \n    try {\n      // 流式响应示例\n      responseElement.textContent = '';\n      const stream = await llmCore.llmService.streamChat(prompt);\n      \n      for await (const chunk of stream) {\n        responseElement.textContent += chunk;\n      }\n    } catch (error) {\n      responseElement.textContent = '错误: ' + error.message;\n    }\n  });\n}\n```\n\n### 5. 服务提供商管理\n\n```javascript\n// 使用providerManager管理服务\nimport { providerManager } from '@qcgm1978/llm-core';\n\n// 检查特定提供商是否可用\nconst isOpenAIReady = providerManager.isProviderReady('openai');\nconsole.log('OpenAI可用状态:', isOpenAIReady);\n\n// 获取当前活跃的服务提供商\nconst activeProviders = providerManager.getActiveProviders();\nconsole.log('活跃的服务提供商:', activeProviders);\n\n// 检查API密钥是否有效格式（客户端验证）\nconst isValidKey = providerManager.validateApiKey('openai', 'sk-...');\nconsole.log('API密钥格式是否有效:', isValidKey);\n```\n\n## API 文档\n\n### 核心导出\n\n- **providerNamesConfig**: 包含所有支持的服务提供商配置的对象\n- **initServices(apiKeys)**: 初始化指定的LLM服务\n  - 参数: `apiKeys`: 包含服务名称和API密钥的对象\n  - 返回值: 无\n\n- **initAllServices(apiKeys)**: 初始化所有LLM服务\n  - 参数: `apiKeys`: 包含服务名称和API密钥的对象\n  - 返回值: 无\n\n- **llmService**: LLM服务的核心类，提供以下主要方法：\n  - `setCurrentProvider(providerName)`: 设置当前使用的服务提供商\n  - `chat(prompt)`: 发送消息并获取响应\n  - `streamChat(prompt)`: 发送消息并获取流式响应\n  - `generateDefinition(topic, language = 'zh', context?)`: 生成定义\n  - `streamDefinition(topic, language = 'zh', context?)`: 流式生成定义\n\n- **providerManager**: 服务提供商管理器，提供以下主要方法：\n  - `isProviderReady(providerName)`: 检查特定提供商是否已初始化\n  - `getActiveProviders()`: 获取所有活跃的服务提供商\n  - `validateApiKey(providerName, apiKey)`: 验证API密钥格式\n\n### 获取服务提供商配置\n\n```javascript\n// 获取所有服务提供商的配置\nconst allProviders = providerNamesConfig;\n\n// 获取特定服务提供商的配置\nconst openaiConfig = providerNamesConfig.openai;\n```\n\n## 支持的服务提供商\n\n- OpenAI\n- Google Gemini\n- DeepSeek\n- Groq\n- OpenRouter\n- Moonshot\n- YouChat\n- Doubao\n- Xunfei\n- IFLOW\n\n## 版本历史\n\n- 3.6.40: 修复豆包API调用问题，更新代理配置\n- 3.6.38: 更新API文档，优化用户使用体验\n- 3.6.31: 更新webpack配置，优化UMD输出\n- 3.6.30: 修复浏览器兼容性问题\n\n## 开发说明\n\n### 构建项目\n\n```bash\n# 构建项目\nnpm run build\n\n# 这将生成以下文件：\n# - dist/index.js (Node.js环境)\n# - dist/browser.js (浏览器环境)\n# - 相关的TypeScript类型声明文件\n```\n\n### 测试浏览器环境\n\n```bash\n# 启动本地HTTP服务器\ncd llm-core\npython3 -m http.server 8000\n\n# 然后访问 http://localhost:8000/llm-core-test.html\n```\n\n## 许可证\n\nMIT License","readmeFilename":"README.md"}