@astack-tech/integrations/dist/index.cjs.map

Integrations for the Astack AI Framework.

{"version":3,"sources":["../src/index.ts","../src/model-provider/index.ts","../src/model-provider/deepseek/index.ts"],"sourcesContent":["/**\n * Astack 集成包\n *\n * 提供与各种外部服务和平台的集成组件\n */\n\n// 导出模型提供者组件\nexport * as ModelProvider from './model-provider';\n","export {\n  default as Deepseek,\n  type Message as DeepseekMessage,\n  type ToolCall as DeepseekToolCall,\n  type DeepseekConfig,\n  type MessageRole as DeepseekMessageRole,\n} from './deepseek';\n","import { Component } from '@astack-tech/core';\nimport OpenAI from 'openai';\n\n/**\n * Deepseek 模型提供者配置\n */\nexport interface DeepseekConfig {\n  /**\n   * API 密钥\n   */\n  apiKey: string;\n\n  /**\n   * 使用的模型名称\n   * 默认为 'deepseek-chat'\n   */\n  model?: string;\n\n  /**\n   * 自定义 API 基础 URL\n   * 默认为 Deepseek 官方 API 地址\n   */\n  baseURL?: string;\n\n  /**\n   * 温度参数，控制输出的随机性\n   */\n  temperature?: number;\n\n  /**\n   * 最大生成的 token 数\n   */\n  maxTokens?: number;\n\n  /**\n   * 采样概率\n   */\n  topP?: number;\n\n  /**\n   * 系统提示消息\n   */\n  systemPrompt?: string;\n\n  /**\n   * 工具实例数组，直接传递工具实例\n   * 每个工具应具有 name、description 和 parameters 属性\n   */\n  rawTools?: Array<{\n    name: string;\n    description: string;\n    parameters?: Record<string, unknown>;\n  }>;\n\n  /**\n   * API 格式的工具定义数组，与 rawTools 二选一\n   * 使用 OpenAI 兼容的工具定义格式\n   */\n  tools?: unknown[];\n\n  /**\n   * dangerouslyAllowBrowser\n   * 是否允许在浏览器等非安全环境内运行\n   */\n  dangerouslyAllowBrowser?: boolean;\n}\n\n/**\n * 消息角色类型\n */\nexport type MessageRole = 'system' | 'user' | 'assistant' | 'tool';\n\n/**\n * 工具调用\n */\nexport interface ToolCall {\n  /**\n   * 工具调用 ID\n   */\n  id?: string;\n\n  /**\n   * 工具名称\n   */\n  tool_name: string;\n\n  /**\n   * 工具调用参数\n   */\n  arguments: Record<string, unknown>;\n}\n\n/**\n * Token 使用统计\n */\nexport interface TokenUsage {\n  /**\n   * 完成部分的 token 数量\n   */\n  completion_tokens: number;\n\n  /**\n   * 提示部分的 token 数量\n   */\n  prompt_tokens: number;\n\n  /**\n   * 提示缓存命中的 token 数量（可选）\n   */\n  prompt_cache_hit_tokens?: number;\n\n  /**\n   * 提示缓存未命中的 token 数量（可选）\n   */\n  prompt_cache_miss_tokens?: number;\n\n  /**\n   * 总 token 数量\n   */\n  total_tokens: number;\n}\n\n/**\n * 对话消息类型\n */\nexport interface Message {\n  /**\n   * 消息角色\n   */\n  role: MessageRole;\n\n  /**\n   * 消息内容\n   */\n  content?: string;\n\n  /**\n   * 工具调用\n   */\n  tool_calls?: ToolCall[];\n\n  /**\n   * 工具调用 ID，用于工具响应消息\n   */\n  tool_call_id?: string;\n\n  /**\n   * Token 使用统计（可选）\n   */\n  usage?: TokenUsage;\n}\n\n/**\n * Deepseek 组件\n *\n * 使用 OpenAI 兼容接口调用 Deepseek 模型\n *\n * 输入:\n *   - prompt: 文本提示\n *   - messages: 对话消息数组\n *\n * 输出:\n *   - completion: 生成的文本完成\n *   - message: 生成的响应消息\n */\nclass Deepseek extends Component {\n  // OpenAI 客户端实例\n  private client: OpenAI;\n\n  // 配置选项\n  private model: string;\n  private temperature: number;\n  private maxTokens?: number;\n  private topP?: number;\n  private systemPrompt?: string;\n  private tools?: unknown[];\n\n  constructor(config: DeepseekConfig) {\n    super({});\n\n    // 配置客户端\n    this.client = new OpenAI({\n      apiKey: config.apiKey,\n      baseURL: config.baseURL || 'https://api.deepseek.com/v1',\n      dangerouslyAllowBrowser: config.dangerouslyAllowBrowser ?? false,\n    });\n\n    // 保存基本配置\n    this.model = config.model || 'deepseek-chat';\n    this.temperature = config.temperature ?? 0.7;\n    this.maxTokens = config.maxTokens;\n    this.topP = config.topP;\n    this.systemPrompt = config.systemPrompt;\n\n    // 处理工具配置，优先使用 rawTools\n    if (config.rawTools && config.rawTools.length > 0) {\n      // 将工具实例转换为 API 格式\n      this.tools = config.rawTools.map(tool => ({\n        type: 'function',\n        function: {\n          name: tool.name,\n          description: tool.description,\n          parameters: tool.parameters || {},\n        },\n      }));\n    } else {\n      // 使用直接提供的 API 格式工具\n      this.tools = config.tools;\n    }\n\n    // 重命名端口\n    Component.Port.I('prompt').attach(this);\n    Component.Port.I('messages').attach(this);\n    Component.Port.O('completion').attach(this);\n    Component.Port.O('message').attach(this);\n  }\n\n  /**\n   * 生成文本完成\n   * @param prompt 提示文本\n   * @returns 生成的文本\n   */\n  async generateCompletion(prompt: string): Promise<string> {\n    const messages: Array<OpenAI.Chat.ChatCompletionMessageParam> = [];\n\n    // 添加系统提示\n    if (this.systemPrompt) {\n      messages.push({\n        role: 'system',\n        content: this.systemPrompt,\n      });\n    }\n\n    // 添加用户提示\n    messages.push({\n      role: 'user',\n      content: prompt,\n    });\n\n    // 创建请求参数\n    // eslint-disable-next-line @typescript-eslint/no-explicit-any\n    const requestParams: any = {\n      model: this.model,\n      messages,\n      temperature: this.temperature,\n      max_tokens: this.maxTokens,\n      top_p: this.topP,\n    };\n\n    // 如果有工具定义，添加到请求中\n    if (this.tools && this.tools.length > 0) {\n      requestParams.tools = this.tools;\n    }\n\n    // 调用 API\n    const response = await this.client.chat.completions.create(requestParams);\n\n    // 处理工具调用结果\n    if (\n      response.choices[0].message.tool_calls &&\n      response.choices[0].message.tool_calls.length > 0\n    ) {\n      return JSON.stringify(response.choices[0].message);\n    }\n\n    return response.choices[0].message.content || '';\n  }\n\n  /**\n   * 流式处理对话消息\n   * @param messages 对话消息数组\n   * @param options 可选的调用选项，包含临时工具列表\n   * @returns 生成的流式响应消息异步生成器\n   */\n  async *streamChatCompletion(\n    messages: Message[],\n    options?: { temporaryTools?: unknown[] }\n  ): AsyncGenerator<Partial<Message>> {\n    // 转换消息格式 (复用现有逻辑)\n    const formattedMessages: Array<OpenAI.Chat.ChatCompletionMessageParam> = [];\n\n    // 添加系统提示\n    if (this.systemPrompt) {\n      formattedMessages.push({\n        role: 'system',\n        content: this.systemPrompt,\n      });\n    }\n\n    // 添加用户提供的消息\n    formattedMessages.push(\n      ...messages.map(msg => {\n        // eslint-disable-next-line @typescript-eslint/no-explicit-any\n        const formattedMsg: any = {\n          role: msg.role,\n          content: msg.content,\n        };\n\n        if (msg.role === 'tool' && msg.tool_call_id) {\n          formattedMsg.tool_call_id = msg.tool_call_id;\n        }\n\n        return formattedMsg;\n      })\n    );\n\n    // 创建请求参数\n    // eslint-disable-next-line @typescript-eslint/no-explicit-any\n    const requestParams: any = {\n      model: this.model,\n      messages: formattedMessages,\n      temperature: this.temperature,\n      max_tokens: this.maxTokens,\n      top_p: this.topP,\n      stream: true, // 开启流式模式\n    };\n\n    // 决定使用哪些工具\n    const toolsToUse = options?.temporaryTools || this.tools;\n\n    // 如果有工具定义，添加到请求中\n    if (toolsToUse && toolsToUse.length > 0) {\n      const formattedTools = toolsToUse.map(tool => {\n        type ToolType = {\n          type?: string;\n          name?: string;\n          description?: string;\n          parameters?: Record<string, unknown>;\n        };\n\n        const typedTool = tool as ToolType;\n\n        if (typedTool.type === 'function') {\n          return tool;\n        }\n\n        return {\n          type: 'function',\n          function: {\n            name: typedTool.name,\n            description: typedTool.description,\n            parameters: typedTool.parameters || {},\n          },\n        };\n      });\n\n      requestParams.tools = formattedTools;\n    }\n\n    // 调用流式 API\n    // eslint-disable-next-line @typescript-eslint/no-explicit-any\n    const stream = (await this.client.chat.completions.create(requestParams)) as any;\n\n    // 处理流式响应\n    for await (const chunk of stream) {\n      const delta = chunk.choices[0]?.delta;\n\n      if (delta?.content) {\n        // 流式文本内容\n        yield {\n          role: 'assistant',\n          content: delta.content,\n        };\n      }\n\n      if (delta?.tool_calls) {\n        // 流式工具调用（如果需要）\n        yield {\n          role: 'assistant',\n          content: '',\n          // eslint-disable-next-line @typescript-eslint/no-explicit-any\n          tool_calls: delta.tool_calls.map((toolCall: any) => ({\n            id: toolCall.id || '',\n            function: {\n              name: toolCall.function?.name || '',\n              arguments: toolCall.function?.arguments || '',\n            },\n            type: 'function',\n            tool_name: toolCall.function?.name || '',\n            arguments: toolCall.function?.arguments || '',\n          })),\n        };\n      }\n\n      // 提取并返回 token 使用统计信息\n      if (chunk.usage) {\n        yield {\n          role: 'assistant',\n          content: '',\n          usage: {\n            completion_tokens: chunk.usage.completion_tokens || 0,\n            prompt_tokens: chunk.usage.prompt_tokens || 0,\n            prompt_cache_hit_tokens: chunk.usage.prompt_cache_hit_tokens,\n            prompt_cache_miss_tokens: chunk.usage.prompt_cache_miss_tokens,\n            total_tokens: chunk.usage.total_tokens || 0,\n          },\n        };\n      }\n    }\n  }\n\n  /**\n   * 处理对话消息\n   * @param messages 对话消息数组\n   * @param options 可选的调用选项，包含临时工具列表\n   * @returns 生成的响应消息\n   */\n  async chatCompletion(\n    messages: Message[],\n    options?: { temporaryTools?: unknown[] }\n  ): Promise<Message> {\n    // 转换消息格式\n    const formattedMessages: Array<OpenAI.Chat.ChatCompletionMessageParam> = [];\n\n    // 添加系统提示\n    if (this.systemPrompt) {\n      formattedMessages.push({\n        role: 'system',\n        content: this.systemPrompt,\n      });\n    }\n\n    // 添加用户提供的消息\n    formattedMessages.push(\n      ...messages.map(msg => {\n        // 基本消息结构\n        // eslint-disable-next-line @typescript-eslint/no-explicit-any\n        const formattedMsg: any = {\n          role: msg.role,\n          content: msg.content,\n        };\n\n        // 如果有工具调用 ID，添加到消息中\n        if (msg.role === 'tool' && msg.tool_call_id) {\n          formattedMsg.tool_call_id = msg.tool_call_id;\n        }\n\n        return formattedMsg;\n      })\n    );\n\n    // 创建请求参数\n    // eslint-disable-next-line @typescript-eslint/no-explicit-any\n    const requestParams: any = {\n      model: this.model,\n      messages: formattedMessages,\n      temperature: this.temperature,\n      max_tokens: this.maxTokens,\n      top_p: this.topP,\n    };\n\n    // 决定使用哪些工具\n    // 如果提供了临时工具，优先使用临时工具\n    const toolsToUse = options?.temporaryTools || this.tools;\n\n    // 如果有工具定义，添加到请求中\n    if (toolsToUse && toolsToUse.length > 0) {\n      // 检查工具格式并转换，确保符合 Deepseek API 要求\n      const formattedTools = toolsToUse.map(tool => {\n        // 使用类型断言来处理 unknown 类型\n        type ToolType = {\n          type?: string;\n          name?: string;\n          description?: string;\n          parameters?: Record<string, unknown>;\n        };\n\n        const typedTool = tool as ToolType;\n\n        // 如果工具已经是 API 格式，直接返回\n        if (typedTool.type === 'function') {\n          return tool;\n        }\n\n        // 如果是简单工具实例，转换为 API 格式\n        return {\n          type: 'function',\n          function: {\n            name: typedTool.name,\n            description: typedTool.description,\n            parameters: typedTool.parameters || {},\n          },\n        };\n      });\n\n      requestParams.tools = formattedTools;\n    }\n\n    // 调用 API\n    const response = await this.client.chat.completions.create(requestParams);\n\n    // 解析响应\n    const responseMessage = response.choices[0].message;\n\n    // 转换为内部消息格式\n    const result: Message = {\n      role: 'assistant',\n      content: responseMessage.content || '',\n    };\n\n    // 提取并添加 token 使用统计信息\n    if (response.usage) {\n      const usage = response.usage as typeof response.usage & {\n        prompt_cache_hit_tokens?: number;\n        prompt_cache_miss_tokens?: number;\n      };\n      result.usage = {\n        completion_tokens: usage.completion_tokens || 0,\n        prompt_tokens: usage.prompt_tokens || 0,\n        prompt_cache_hit_tokens: usage.prompt_cache_hit_tokens,\n        prompt_cache_miss_tokens: usage.prompt_cache_miss_tokens,\n        total_tokens: usage.total_tokens || 0,\n      };\n    }\n\n    // 如果有工具调用，添加到结果中\n    if (responseMessage.tool_calls && responseMessage.tool_calls.length > 0) {\n      // 为了兼容 Agent 组件期望的格式，保留 function 和 type 字段\n      // 同时为了满足内部 ToolCall 接口，也添加 tool_name 和 arguments 字段\n      result.tool_calls = responseMessage.tool_calls.map(toolCall => {\n        // 解析参数，确保是对象形式\n        let args: Record<string, unknown>;\n\n        const rawArgs = toolCall.function.arguments;\n\n        if (typeof rawArgs === 'string') {\n          const raw = rawArgs;\n          try {\n            args = raw && raw.trim().length > 0 ? (JSON.parse(raw) as Record<string, unknown>) : {};\n          } catch {\n            args = {};\n          }\n        } else if (rawArgs && typeof rawArgs === 'object') {\n          args = rawArgs as Record<string, unknown>;\n        } else {\n          args = {};\n        }\n\n        return {\n          id: toolCall.id,\n          // 满足 Agent 组件期望的格式\n          function: {\n            name: toolCall.function.name,\n            arguments: toolCall.function.arguments || '{}',\n          },\n          type: 'function',\n          // 满足内部 ToolCall 接口\n          tool_name: toolCall.function.name,\n          arguments: args,\n        };\n      });\n    }\n\n    return result;\n  }\n\n  /**\n   * 在独立模式下运行组件\n   * @param input 输入参数，可以是提示文本或对话消息数组\n   * @returns 生成的文本或响应消息\n   */\n  async run(input: string | Message[]): Promise<string | Message> {\n    if (typeof input === 'string') {\n      return this.generateCompletion(input);\n    } else {\n      return this.chatCompletion(input);\n    }\n  }\n\n  /**\n   * 在流水线中运行组件\n   * @param $i 输入端口\n   * @param $o 输出端口\n   */\n  // eslint-disable-next-line @typescript-eslint/no-explicit-any\n  _transform($i: any, $o: any) {\n    // 处理文本提示输入\n    $i('prompt').receive(async (prompt: string) => {\n      try {\n        const completion = await this.generateCompletion(prompt);\n        $o('completion').send(completion);\n      } catch (error) {\n        console.error('Deepseek API 调用错误:', error);\n        $o('completion').send('API 调用错误');\n      }\n    });\n\n    // 处理对话消息输入\n    $i('messages').receive(async (messages: Message[]) => {\n      try {\n        const responseMessage = await this.chatCompletion(messages);\n        $o('message').send(responseMessage);\n      } catch (error) {\n        console.error('Deepseek API 调用错误:', error);\n        $o('message').send({\n          role: 'assistant',\n          content: 'API 调用错误',\n        });\n      }\n    });\n  }\n}\n\n// 默认导出组件\nexport default 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