From feb1a0b280f87837ba3aaccf32e17ab3e578e944 Mon Sep 17 00:00:00 2001 From: sun <805460182@qq.com> Date: Wed, 25 Feb 2026 18:04:48 +0800 Subject: [PATCH] =?UTF-8?q?feat(agent):=20=E6=96=B0=E5=A2=9EMCP=20Agent?= =?UTF-8?q?=E5=AE=A2=E6=88=B7=E7=AB=AF=E5=92=8C=E5=B7=A5=E5=85=B7=E7=B3=BB?= =?UTF-8?q?=E7=BB=9F?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - 实现了基于LangChain的MCP Agent，支持连接MCP服务器调用工具 - 添加了环境配置文件(.env)，包含LLM模型和API配置信息 - 创建了完整的工具系统，包括BaseTool基类和Bash、Terminate、Add等工具 - 集成了天气查询工具，支持通过中国气象局API获取天气预报信息 - 实现了交互式对话功能，支持多轮工具调用和结果处理 - 添加了详细的CLAUDE.md开发指导文档 --- .env | 5 + .idea/ai_toolkit.xml | 6 + .idea/copilot.data.migration.agent.xml | 6 + .idea/misc.xml | 3 + CLAUDE.md | 106 ++ app/__init__.py | 0 app/agent.py | 403 ++++++ app/exceptions.py | 13 + app/mcp_server/__init__.py | 0 app/mcp_server/server.py | 194 +++ app/tool_call_agent.py | 96 ++ app/tools/__init__.py | 15 + app/tools/add.py | 30 + app/tools/agent_tools.py | 190 +++ app/tools/base.py | 153 ++ app/tools/bash.py | 158 ++ app/tools/execute_sql.py | 56 + app/tools/terminate.py | 25 + app/tools/weather.py | 158 ++ app/utils/__init__.py | 0 app/utils/logger.py | 89 ++ client.py | 4 +- pyproject.toml | 7 + uv.lock | 1819 +++++++++++++++++++++++- 24 files changed, 3531 insertions(+), 5 deletions(-) create mode 100644 .env create mode 100644 .idea/ai_toolkit.xml create mode 100644 .idea/copilot.data.migration.agent.xml create mode 100644 CLAUDE.md create mode 100644 app/__init__.py create mode 100644 app/agent.py create mode 100644 app/exceptions.py create mode 100644 app/mcp_server/__init__.py create mode 100644 app/mcp_server/server.py create mode 100644 app/tool_call_agent.py create mode 100644 app/tools/__init__.py create mode 100644 app/tools/add.py create mode 100644 app/tools/agent_tools.py create mode 100644 app/tools/base.py create mode 100644 app/tools/bash.py create mode 100644 app/tools/execute_sql.py create mode 100644 app/tools/terminate.py create mode 100644 app/tools/weather.py create mode 100644 app/utils/__init__.py create mode 100644 app/utils/logger.py diff --git a/.env b/.env new file mode 100644 index 0000000..57afe9e --- /dev/null +++ b/.env @@ -0,0 +1,5 @@ +LLM_MODEL=qwen3-30b-a3b-instruct-2507 +LLM_API_KEY=sk-2c4834c388724189903e8011420d6c47 +LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1 +APIHZ_ID=10007673 +APIHZ_KEY=be63d2fb5354f76abb18f62583edffae diff --git a/.idea/ai_toolkit.xml b/.idea/ai_toolkit.xml new file mode 100644 index 0000000..d5de184 --- /dev/null +++ b/.idea/ai_toolkit.xml @@ -0,0 +1,6 @@ + + + + + \ No newline at end of file diff --git a/.idea/copilot.data.migration.agent.xml b/.idea/copilot.data.migration.agent.xml new file mode 100644 index 0000000..4ea72a9 --- /dev/null +++ b/.idea/copilot.data.migration.agent.xml @@ -0,0 +1,6 @@ + + + + + \ No newline at end of file diff --git a/.idea/misc.xml b/.idea/misc.xml index ce4d17b..bf1f148 100644 --- a/.idea/misc.xml +++ b/.idea/misc.xml @@ -1,4 +1,7 @@ + + \ No newline at end of file diff --git a/CLAUDE.md b/CLAUDE.md new file mode 100644 index 0000000..bff47c9 --- /dev/null +++ b/CLAUDE.md @@ -0,0 +1,106 @@ +# CLAUDE.md + +此文件为 Claude Code（claude.ai/code）在处理此存储库中的代码时提供指导。 + +# 交互规则（优先级最高） +1. 所有与本仓库相关的沟通、文档编辑、代码注释、解释说明均使用**中文** +2. 技术术语以及命令保留英文原词（如 Langchain、Deepagents），但解释说明必须用中文 +3. 代码本身的语法/关键字保持英文（符合编程规范），但注释、文档、交互回复全部使用中文 +4. 当前项目为技术验证项目，目前使用Langchain、Deepagents等框架，遇到框架相关问题需要首先参考官方技术文档，链接： +```text +[Langchain](https://docs.langchain.com/oss/python/langchain/overview)、[Deepagents](https://docs.langchain.com/oss/python/deepagents/overview) +``` + +## 项目概述 + +TestMCP 是一个 MCP (Model Context Protocol) 服务器实现，带有 OpenAI 兼容的客户端，用于构建 AI Agent 系统。该项目是 "OpenManus" 的简化/修改版本 - 一个支持工具调用的 AI Agent 框架。 + +## 命令 + +### 运行 Demo MCP 服务器 (FastMCP 带天气工具) +```bash +python main.py +``` +运行 SSE 服务器，默认端口，包含 `add()` 和 `get_weather_by_location()` 工具。 + +### 运行 OpenManus 风格的 MCP 服务器 +```bash +python -m app.mcp_server.server --transport stdio +``` + +### 运行客户端 +```bash +python client.py +``` +通过 SSE 连接到 `http://127.0.0.1:8000/sse` 的 MCP 服务器。 + +### 启动Agent调用本地工具 +```bash +python tool_call_agent.py +``` + +### 包管理 +项目使用 `uv` 作为包管理器： +```bash +uv sync # 安装依赖 +uv add # 添加新依赖 +``` + +## 架构 + +### 核心组件 + +``` +app/ +├── mcp_server/ +│ └── server.py # MCPServer 类，包含 FastMCP 和工具注册系统 +├── tools/ +│ ├── base.py # BaseTool (抽象类), ToolResult, CLIResult +│ ├── bash.py # Bash 命令执行工具 +│ └── terminate.py # 终止工具 +├── utils/ +│ └── logger.py # 基于 Loguru 的日志系统，支持文件轮转 +└── exceptions.py # ToolError, OpenManusError, TokenLimitExceeded +``` + +### 入口点 + +1. **`client.py`** - 主客户端入口 + - `AutoToolChatSession`: 通过 SSE 连接 MCP 服务器，调用 LLM，执行工具 + - 支持 OpenAI 兼容模型 (DashScope, Ollama 等) + +2. **`main.py`** - 使用 FastMCP 的 Demo 服务器 + - 工具：`add()`, `get_weather_by_location()` + - 资源：`greeting://{name}` + - 提示词：`greet_user()` + +3. **`app/mcp_server/server.py`** - OpenManus 风格的 MCP 服务器 + - `MCPServer` 类，支持动态工具注册 + - 内置工具：bash, terminate + +### 工具系统 + +所有工具继承自 `BaseTool` (位于 `app/tools/base.py`): +- 必须实现 `async execute(self, **kwargs) -> ToolResult` +- 工具参数通过 `parameters` 字典定义 (JSON Schema 格式) +- 结果通过 `ToolResult` 返回，包含 `output`, `error`, `base64_image` 字段 + +### 环境变量配置 + +通过 `.env` 文件配置必需的环境变量： +```bash +LLM_API_KEY= +APIHZ_ID= # 用于天气 API +APIHZ_KEY= # 用于天气 API +``` + +客户端配置 (位于 `client.py`): +- `LLM_MODEL`: 模型名称 (默认：deepseek-v3) +- `LLM_BASE_URL`: OpenAI 兼容的 API 端点 + +### 关键设计模式 + +- **MCP Protocol**: 使用 Model Context Protocol 暴露工具 +- **SSE Transport**: 客户端通过 Server-Sent Events 连接 +- **Async Design**: 使用 `asyncio` 进行并发工具执行 +- **Pydantic Models**: 用于数据验证 (`ToolResult`, `BaseTool`) diff --git a/app/__init__.py b/app/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/agent.py b/app/agent.py new file mode 100644 index 0000000..aad9556 --- /dev/null +++ b/app/agent.py @@ -0,0 +1,403 @@ +""" +使用 LangChain create_agent 创建 MCP Agent 客户端 + +本模块通过 LangChain 的 create_agent 函数创建智能体， +并连接 MCP 服务器调用其注册的工具（bash, terminate, add, weather 等）。 +""" +import asyncio +import os +import json +import logging +from typing import Any, Dict, List, Optional + +from dotenv import load_dotenv, find_dotenv + +from langchain.agents import create_agent +from langchain_core.tools import BaseTool, ToolException +from langchain_openai import ChatOpenAI + +from mcp import ClientSession +from mcp.client.sse import sse_client +from mcp.types import TextContent +from pydantic.v1 import BaseModel, Field + +# 配置日志 +logging.basicConfig( + level=logging.INFO, + format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", + datefmt="%Y-%m-%d %H:%M:%S" +) +logger = logging.getLogger(__name__) + +_ = load_dotenv(find_dotenv()) + + + +from typing import Type + +class MCPTool(BaseTool): + """将 MCP 工具转换为 LangChain 工具的适配器类""" + + name: str = "" + description: str = "" + session: Optional[ClientSession] = None + args_schema: Optional[Type[BaseModel]] = None + + def __init__( + self, + name: str, + description: str, + session: ClientSession, + args_schema: Optional[Type[BaseModel]] = None, + **kwargs: Any + ): + super().__init__( + name=name, + description=description, + session=session, + args_schema=args_schema, + **kwargs + ) + + def _run(self, **kwargs: Any) -> Any: + """同步执行工具（通过 asyncio 运行）""" + return asyncio.run(self._async_run(**kwargs)) + + async def _arun(self, **kwargs: Any) -> Any: + """异步执行工具""" + return await self._async_run(**kwargs) + + async def _async_run(self, **kwargs: Any) -> Any: + """执行 MCP 工具调用""" + if self.session is None: + raise ToolException(f"MCP session is not initialized for tool: {self.name}") + + try: + logger.info(f"Calling MCP tool: {self.name} with args: {kwargs}") + response = await self.session.call_tool(self.name, kwargs) + + # 提取结果 + if response.structuredContent is not None: + result = json.dumps(response.structuredContent, ensure_ascii=False) + elif response.content: + result = "\n".join( + c.text for c in response.content if isinstance(c, TextContent) + ) + else: + result = "工具执行成功，无返回内容" + + # 限制日志长度 + log_result = result[:500] if len(result) > 500 else result + logger.info(f"MCP tool {self.name} returned: {log_result}") + return result + + except Exception as e: + error_msg = f"工具 {self.name} 执行失败：{str(e)}" + logger.error(error_msg) + raise ToolException(error_msg) + + +class MCPLangChainAgent: + """基于 LangChain 的 MCP Agent 封装类""" + + def __init__( + self, + sse_server_url: str = "http://127.0.0.1:8000/sse", + llm: Optional[Any] = None, + ): + """ + 初始化 MCP Agent + + Args: + sse_server_url: MCP 服务器的 SSE 地址 + llm: LangChain 兼容的 LLM 实例 + """ + self.sse_server_url = sse_server_url + self.llm = llm + self.session: Optional[ClientSession] = None + self.tools: List[BaseTool] = [] + self.agent = None + self._read_stream = None + self._write_stream = None + + def _generate_args_schema(self, tool_name: str, input_schema: dict) -> Optional[Type[BaseModel]]: + """为 MCP 工具生成 LangChain 兼容的参数 schema""" + if not input_schema or not input_schema.get("properties"): + return None + + properties = input_schema.get("properties", {}) + required_fields = input_schema.get("required", []) + + # 动态创建字段定义 + fields = {} + for prop_name, prop_details in properties.items(): + field_type = self._map_json_type_to_python(prop_details.get("type", "string")) + field_description = prop_details.get("description", "") + + # 根据字段是否必需来设置默认值 + if prop_name in required_fields: + fields[prop_name] = (field_type, Field(..., description=field_description)) + else: + fields[prop_name] = (field_type, Field(None, description=field_description)) + + # 动态创建 Pydantic 模型类 + schema_class = type( + f"{tool_name.title()}Schema", + (BaseModel,), + {"__annotations__": {k: v[0] for k, v in fields.items()}, **{k: v[1] for k, v in fields.items()}} + ) + return schema_class + + def _map_json_type_to_python(self, json_type: str): + """将 JSON Schema 类型映射到 Python 类型""" + type_mapping = { + "string": str, + "integer": int, + "number": float, + "boolean": bool, + "array": list, + "object": dict + } + return type_mapping.get(json_type, str) + + async def connect(self) -> None: + """连接到 MCP 服务器并加载工具""" + logger.info(f"Connecting to MCP server: {self.sse_server_url}") + + # 创建 SSE 连接 - 使用同步方式进入上下文 + self._sse_cm = sse_client(self.sse_server_url) + self._read_stream, self._write_stream = await self._sse_cm.__aenter__() + + # 创建并初始化会话 + self._session_cm = ClientSession(self._read_stream, self._write_stream) + self.session = await self._session_cm.__aenter__() + await self.session.initialize() + + # 获取工具列表 + tools_response = await self.session.list_tools() + logger.info(f"Retrieved {len(tools_response.tools)} tools from MCP server") + + # 转换 MCP 工具为 LangChain 工具 + self.tools = [] + for tool in tools_response.tools: + # 生成参数 schema 类 + args_schema_class = self._generate_args_schema(tool.name, tool.inputSchema) + + mcp_tool = MCPTool( + name=tool.name, + description=tool.description or "No description provided", + session=self.session, + args_schema=args_schema_class + ) + self.tools.append(mcp_tool) + logger.info(f"Loaded tool: {tool.name} - {tool.description[:50]}...") + + logger.info(f"Successfully connected and loaded {len(self.tools)} tools") + + async def disconnect(self) -> None: + """断开 MCP 服务器连接""" + try: + if self.session: + await self._session_cm.__aexit__(None, None, None) + self.session = None + if hasattr(self, '_sse_cm') and self._sse_cm: + await self._sse_cm.__aexit__(None, None, None) + self._read_stream = None + self._write_stream = None + logger.info("Disconnected from MCP server") + except Exception as e: + logger.warning(f"Error during disconnect: {e}") + + def create_agent(self, system_message: Optional[str] = None) -> Any: + """ + 创建 LangChain Agent + + Args: + system_message: 系统提示词 + + Returns: + Agent 实例 + """ + if self.llm is None: + raise ValueError( + "LLM is not set. Please provide a LangChain compatible LLM instance." + ) + + if not self.tools: + raise ValueError("No tools available. Please call connect() first.") + + # 系统提示词 + system_prompt = system_message or ( + "你是一个智能助手，可以使用提供的工具来帮助用户解决问题。" + "请根据用户的问题，合理选择并使用工具。" + "如果不需要使用工具，直接回答用户的问题。" + ) + + # 使用 LangChain 1.2+ 的 create_agent API + self.agent = create_agent( + model=self.llm, + tools=self.tools, + system_prompt=system_prompt, + ) + + logger.info("Agent created successfully") + return self.agent + + async def invoke(self, input_text: str) -> Dict[str, Any]: + """ + 执行 Agent + + Args: + input_text: 用户输入 + + Returns: + Agent 执行结果 + """ + if self.agent is None: + raise ValueError("Agent is not created. Please call create_agent() first.") + + logger.info(f"Invoking agent with input: {input_text}") + result = await self.agent.ainvoke({"input": input_text}) + logger.info(f"Agent execution completed.") + logger.info(f"Raw agent result type: {type(result)}, value: {result}") + return result + + async def __aenter__(self): + """异步上下文管理器入口""" + await self.connect() + return self + + async def __aexit__(self, exc_type, exc_val, exc_tb): + """异步上下文管理器出口""" + await self.disconnect() + return False # 不抑制异常 + + +def create_langchain_llm( + model_name: Optional[str] = None, + api_key: Optional[str] = None, + base_url: Optional[str] = None, + temperature: float = 0.7, + **kwargs: Any +) -> ChatOpenAI: + """ + 创建 LangChain 兼容的 ChatOpenAI 实例 + + Args: + model_name: 模型名称 + api_key: API 密钥 + base_url: API 基础 URL + temperature: 温度参数 + **kwargs: 其他参数 + + Returns: + LangChain ChatOpenAI 实例 + """ + llm_config = { + "model": model_name or os.getenv("LLM_MODEL", "deepseek-v3"), + "api_key": api_key or os.getenv("LLM_API_KEY", "your-api-key"), + "base_url": base_url or os.getenv("LLM_BASE_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1"), + "temperature": temperature, + "timeout": 300, + } + + # 合并额外参数 + llm_config.update(kwargs) + + logger.info(f"Creating LLM with model: {llm_config['model']}, base_url: {llm_config['base_url']}") + return ChatOpenAI(**llm_config) + + +async def start_interactive_chat(): + """启动交互式对话""" + print("\n" + "=" * 60) + print("MCP LangChain Agent - 交互式对话") + print("=" * 60) + print("可用工具：add, bash, terminate, get_weather_by_location") + print("输入 'quit' 或 'exit' 退出") + print("=" * 60 + "\n") + + # 创建 LLM 实例 + llm = create_langchain_llm() + + # 创建并运行 Agent + async with MCPLangChainAgent( + sse_server_url="http://127.0.0.1:8000/sse", + llm=llm + ) as agent_wrapper: + + # 创建 Agent + agent = agent_wrapper.create_agent( + system_message=( + "你是一个智能助手，可以使用以下工具：\n" + "- add(a, b): 计算两个整数的和\n" + "- bash(command): 执行 bash 命令\n" + "- terminate(status): 终止交互（status: 'success' 或 'failure'）\n" + "- get_weather_by_location(user_id, user_key, province, place): 获取天气预报\n" + "请根据用户需求合理选择工具。" + ) + ) + + while True: + try: + user_input = input("你：").strip() + + if user_input.lower() in ["quit", "exit"]: + logger.info("用户退出") + break + + if not user_input: + continue + + print("\n助手：思考中...", end="\r") + + # 执行 Agent + result = await agent_wrapper.invoke(user_input) + + # 提取最终输出 + logger.info(f"Processing result: {result} (type: {type(result)})") + + # 检查结果结构并相应地提取输出 + if isinstance(result, dict): + # 如果结果包含 messages 键（LangChain agent 的典型返回格式） + if "messages" in result and isinstance(result["messages"], list): + # 从 messages 列表中提取最后一个消息的内容 + messages = result["messages"] + if messages: + # 获取最后一个消息对象 + last_message = messages[-1] + # 检查是否是 AIMessage 对象并尝试提取 content + if hasattr(last_message, 'content'): + output = str(last_message.content) if last_message.content is not None else "无响应内容" + else: + output = str(last_message) if last_message is not None else "无响应内容" + else: + output = "无响应内容" + else: + # 尝试多种可能的键 + output = (result.get("output") or + result.get("result") or + result.get("response") or + result.get("content") or + result.get("answer") or + "无响应内容") + else: + # 如果结果不是字典，直接转换为字符串 + output = str(result) if result is not None else "无响应内容" + + # 显示结果 + print(f"助手：{output}\n") + + except KeyboardInterrupt: + logger.info("\n用户强制中断") + break + except Exception as e: + logger.error(f"执行错误：{str(e)}", exc_info=True) + print(f"错误：{str(e)}\n") + + +if __name__ == "__main__": + try: + asyncio.run(start_interactive_chat()) + except KeyboardInterrupt: + print("\n再见！") diff --git a/app/exceptions.py b/app/exceptions.py new file mode 100644 index 0000000..6db0e38 --- /dev/null +++ b/app/exceptions.py @@ -0,0 +1,13 @@ +class ToolError(Exception): + """当工具遇到错误时引发。""" + + def __init__(self, message): + self.message = message + + +class OpenManusError(Exception): + """所有 OpenManus 错误的基础异常""" + + +class TokenLimitExceeded(OpenManusError): + """当超过 token 限制时引发的异常""" diff --git a/app/mcp_server/__init__.py b/app/mcp_server/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/mcp_server/server.py b/app/mcp_server/server.py new file mode 100644 index 0000000..15a7550 --- /dev/null +++ b/app/mcp_server/server.py @@ -0,0 +1,194 @@ +import logging +import sys + + +logging.basicConfig(level=logging.INFO, handlers=[logging.StreamHandler(sys.stderr)]) + +import argparse +import asyncio +import atexit +import json +from inspect import Parameter, Signature +from typing import Any, Dict, Optional + +from mcp.server.fastmcp import FastMCP + +from app.utils.logger import logger +from app.tools.base import BaseTool +from app.tools.bash import Bash +# from app.tools.browser_use_tool import BrowserUseTool +# from app.tools.str_replace_editor import StrReplaceEditor +from app.tools.terminate import Terminate +from app.tools.add import Add +from app.tools.weather import GetWeatherByLocation + + +class MCPServer: + """具有工具注册和管理功能的 MCP 服务器实现。""" + + def __init__(self, name: str = "openmanus"): + self.server = FastMCP(name) + self.tools: Dict[str, BaseTool] = {} + + # 初始化标准工具 + self.tools["bash"] = Bash() + # self.tools["browser"] = BrowserUseTool() + # self.tools["editor"] = StrReplaceEditor() + self.tools["terminate"] = Terminate() + self.tools["add"] = Add() + self.tools["weather"] = GetWeatherByLocation() + + def register_tool(self, tool: BaseTool, method_name: Optional[str] = None) -> None: + """注册一个工具，包含参数验证和文档。""" + tool_name = method_name or tool.name + tool_param = tool.to_param() + tool_function = tool_param["function"] + + # 定义要注册的异步函数 + async def tool_method(**kwargs): + logger.info(f"Executing {tool_name}: {kwargs}") + result = await tool.execute(**kwargs) + + logger.info(f"Result of {tool_name}: {result}") + + # 处理不同类型的结果（匹配原始逻辑） + if hasattr(result, "model_dump"): + return json.dumps(result.model_dump()) + elif isinstance(result, dict): + return json.dumps(result) + return result + + # 设置方法元数据 + tool_method.__name__ = tool_name + tool_method.__doc__ = self._build_docstring(tool_function) + tool_method.__signature__ = self._build_signature(tool_function) + + # 存储参数模式（对于以编程方式访问它的工具很重要） + param_props = tool_function.get("parameters", {}).get("properties", {}) + required_params = tool_function.get("parameters", {}).get("required", []) + tool_method._parameter_schema = { + param_name: { + "description": param_details.get("description", ""), + "type": param_details.get("type", "any"), + "required": param_name in required_params, + } + for param_name, param_details in param_props.items() + } + + # 注册到服务器 + self.server.tool()(tool_method) + logger.info(f"Registered tool: {tool_name}") + + def _build_docstring(self, tool_function: dict) -> str: + """从工具函数元数据构建格式化的文档字符串。""" + description = tool_function.get("description", "") + param_props = tool_function.get("parameters", {}).get("properties", {}) + required_params = tool_function.get("parameters", {}).get("required", []) + + # 构建文档字符串（匹配原始格式） + docstring = description + if param_props: + docstring += "\n\nParameters:\n" + for param_name, param_details in param_props.items(): + required_str = ( + "(required)" if param_name in required_params else "(optional)" + ) + param_type = param_details.get("type", "any") + param_desc = param_details.get("description", "") + docstring += ( + f" {param_name} ({param_type}) {required_str}: {param_desc}\n" + ) + + return docstring + + def _build_signature(self, tool_function: dict) -> Signature: + """从工具函数元数据构建函数签名。""" + param_props = tool_function.get("parameters", {}).get("properties", {}) + required_params = tool_function.get("parameters", {}).get("required", []) + + parameters = [] + + # 遵循原始类型映射 + for param_name, param_details in param_props.items(): + param_type = param_details.get("type", "") + default = Parameter.empty if param_name in required_params else None + + # 将 JSON Schema 类型映射到 Python 类型（与原始相同） + annotation = Any + if param_type == "string": + annotation = str + elif param_type == "integer": + annotation = int + elif param_type == "number": + annotation = float + elif param_type == "boolean": + annotation = bool + elif param_type == "object": + annotation = dict + elif param_type == "array": + annotation = list + + # 创建与原始结构相同的参数 + param = Parameter( + name=param_name, + kind=Parameter.KEYWORD_ONLY, + default=default, + annotation=annotation, + ) + parameters.append(param) + + return Signature(parameters=parameters) + + async def cleanup(self) -> None: + """清理服务器资源。""" + logger.info("Cleaning up resources") + # 遵循原始清理逻辑 - 仅清理浏览器工具 + if "browser" in self.tools and hasattr(self.tools["browser"], "cleanup"): + await self.tools["browser"].cleanup() + + def register_all_tools(self) -> None: + """向服务器注册所有工具。""" + for tool in self.tools.values(): + self.register_tool(tool) + + def run(self, transport: str = "stdio") -> None: + """运行 MCP 服务器。""" + # 注册所有工具 + self.register_all_tools() + + # 注册清理函数（匹配原始行为） + atexit.register(lambda: asyncio.run(self.cleanup())) + + # 启动服务器（使用与原始相同的日志记录） + logger.info(f"Starting OpenManus server ({transport} mode)") + self.server.run(transport=transport) + + +def parse_args() -> argparse.Namespace: + """解析命令行参数。""" + parser = argparse.ArgumentParser(description="OpenManus MCP Server") + parser.add_argument( + "--transport", + choices=["stdio", "sse"], + default="stdio", + help="通信方法：stdio 或 sse (默认：stdio)", + ) + return parser.parse_args() + + +if __name__ == "__main__": + args = parse_args() + + # 创建服务器 + server = MCPServer() + server.register_all_tools() + + if args.transport == "sse": + # SSE 模式：直接运行 FastMCP 服务器（默认端口 8000） + logger.info(f"Starting MCP server with SSE transport") + server.server.run(transport="sse") + else: + # stdio 模式 + atexit.register(lambda: asyncio.run(server.cleanup())) + logger.info(f"Starting MCP server with stdio transport") + server.server.run(transport="stdio") diff --git a/app/tool_call_agent.py b/app/tool_call_agent.py new file mode 100644 index 0000000..f9044cf --- /dev/null +++ b/app/tool_call_agent.py @@ -0,0 +1,96 @@ +import os +import uuid +from deepagents import create_deep_agent +from dotenv import load_dotenv, find_dotenv +from langchain.agents import create_agent +from langgraph.checkpoint.memory import InMemorySaver +from app.tools.agent_tools import add, get_weather_by_location +from langchain_openai import ChatOpenAI +from app.tools.execute_sql import execute_query + +_ = load_dotenv(find_dotenv()) + +checkpointer = InMemorySaver() + +# model = ChatTongyi( +# model="qwen3-30b-a3b-thinking-2507", +# dashscope_api_key=os.getenv('LLM_API_KEY'), +# base_url="https://dashscope.aliyuncs.com/compatible-mode/v1" +# ) + +model = ChatOpenAI( + model="qwen3-30b-a3b-thinking-2507", + api_key=os.getenv('LLM_API_KEY'), + base_url="https://dashscope.aliyuncs.com/compatible-mode/v1" +) + +# agent = create_agent( +# model=model, +# tools=[add, get_weather_by_location], +# system_prompt="你是一个有帮助的助手。请简洁准确。" +# ) + +agent = create_deep_agent( + model=model, + tools=[add, get_weather_by_location, execute_query], + checkpointer=checkpointer, + system_prompt="你是一个有帮助的助手。请简洁准确，用中文进行回答。" +) + +thread_id = str(uuid.uuid4()) +config = { + "configurable": { + "thread_id": thread_id + } +} + + +if __name__ == "__main__": + # 启用流式输出 + print("=== 开始流式输出 ===") + stream_result = agent.stream( + {"messages": [{"role": "user", "content": "查询车上咖啡机数据，不要修改原来的sql，除非运行报错。" + "sql: select counts(*) from coffee_train"}]}, + config=config + ) + + # 逐块处理流式输出 + full_response = "" + for chunk in stream_result: + # 打印每一块内容（调试用途） + print("接收到数据块:", chunk) + + # 解析消息内容 + if 'messages' in chunk: + messages = chunk['messages'] + for msg in messages: + # 打印消息类型和所有属性 + print(f"--- 消息类型: {type(msg).__name__} ---") + if hasattr(msg, 'content') and msg.content: + print(f"消息内容: {msg.content}") + + # 处理 AIMessage（带工具调用） + if hasattr(msg, 'tool_calls') and msg.tool_calls: + print("正在调用工具...") + for tool_call in msg.tool_calls: + print(f" 工具名: {tool_call.get('name', 'N/A')}") + print(f" 参数: {tool_call.get('args', {})}") + print(f" 调用ID: {tool_call.get('id', 'N/A')}") + + # 处理 ToolMessage（工具响应） + elif hasattr(msg, 'name') and msg.name: + print(f"工具名称: {msg.name}") + print(f"工具调用ID: {msg.tool_call_id}") + print(f"工具响应: {msg.content}") + + # 处理普通消息内容 + elif hasattr(msg, 'content'): + content = msg.content + full_response += content + + print("\n=== 流式输出结束 ===") + + # 打印最终完整响应 + print("\n=== 最终完整响应 ===") + print(full_response) + diff --git a/app/tools/__init__.py b/app/tools/__init__.py new file mode 100644 index 0000000..a723830 --- /dev/null +++ b/app/tools/__init__.py @@ -0,0 +1,15 @@ +from app.tools.base import BaseTool, ToolResult, CLIResult +from app.tools.bash import Bash +from app.tools.terminate import Terminate +from app.tools.add import Add +from app.tools.weather import GetWeatherByLocation + +__all__ = [ + "BaseTool", + "ToolResult", + "CLIResult", + "Bash", + "Terminate", + "Add", + "GetWeatherByLocation", +] diff --git a/app/tools/add.py b/app/tools/add.py new file mode 100644 index 0000000..2df3dbf --- /dev/null +++ b/app/tools/add.py @@ -0,0 +1,30 @@ +from app.tools.base import BaseTool, ToolResult + + +_ADD_DESCRIPTION = """计算两个整数的和。""" + + +class Add(BaseTool): + """加法计算工具""" + + name: str = "add" + description: str = _ADD_DESCRIPTION + parameters: dict = { + "type": "object", + "properties": { + "a": { + "type": "integer", + "description": "第一个加数", + }, + "b": { + "type": "integer", + "description": "第二个加数", + }, + }, + "required": ["a", "b"], + } + + async def execute(self, a: int, b: int) -> ToolResult: + """执行加法计算""" + result = a + b + return self.success_response({"result": result}) diff --git a/app/tools/agent_tools.py b/app/tools/agent_tools.py new file mode 100644 index 0000000..ca724f5 --- /dev/null +++ b/app/tools/agent_tools.py @@ -0,0 +1,190 @@ +from langchain.agents.middleware import wrap_tool_call +from langchain.tools import tool +from typing import Dict, Optional, Union +import requests +import os +from dotenv import load_dotenv, find_dotenv +from langchain_core.messages import ToolMessage + +_ = load_dotenv(find_dotenv()) +@tool +def add(a: int, b: int) -> int: + """Add two numbers""" + return a + b + +@tool +def get_weather_by_location(province: str, place: str) -> Dict[ + str, Union[str, float, int] +]: + """ + 调用中国气象局天气预报API，获取指定省份和地点的完整当日天气信息（含基础预报、实时数据、气象预警） + + ### 参数说明 + - province: str - 查询省份/直辖市，建议去除"省""市"后缀（例："四川"而非"四川省"，"北京"而非"北京市"） + - place: str - 查询城市/区/县，建议去除"市""区""县"后缀（例："绵阳"而非"绵阳市"，"大兴"而非"大兴区"） + + ### 返回说明（成功，code=200） + 基础预报信息： + - code: int - 状态码，成功固定为200 + - guo: str - 国家名称（例："中国"） + - sheng: str - 标准化省份/直辖市名称（例："四川"） + - shi: str - 标准化城市/地区名称（例："绵阳"） + - name: str - 与shi一致，冗余字段（例："绵阳"） + - weather1: str - 当日主要天气（例："阵雨"） + - weather2: str - 当日次要天气（例："阵雨"） + - wd1: str - 当日最高温度（单位：℃，例："25"） + - wd2: str - 当日最低温度（单位：℃，例："18"） + - winddirection1: str - 当日主要风向（例："无持续风向"） + - winddirection2: str - 当日次要风向（例："无持续风向"） + - windleve1: str - 当日主要风力等级（例："微风"） + - windleve2: str - 当日次要风力等级（例："微风"） + - weather1img: str - 主要天气图标URL（例："https://rescdn.apihz.cn/resimg/tianqi/zhenyu.png"） + - weather2img: str - 次要天气图标URL（例："https://rescdn.apihz.cn/resimg/tianqi/zhenyu.png"） + - lon: str - 地区经度（保留3位小数，例："104.730"） + - lat: str - 地区纬度（保留3位小数，例："31.440"） + - uptime: str - 预报数据更新时间（格式：YYYY-MM-DD HH:MM:SS，例："2025-08-29 12:00:00"） + + 实时天气数据（顶层字段）： + - now_precipitation: float - 当前降水量（单位：mm，例：0.0） + - now_temperature: float - 当前温度（单位：℃，例：19.3） + - now_pressure: int - 当前气压（单位：hPa，例：956） + - now_humidity: int - 当前湿度（单位：%，例：85） + - now_windDirection: str - 当前风向（例："东北风"） + - now_windDirectionDegree: int - 当前风向角度（0°=北风，例：28） + - now_windSpeed: float - 当前风速（单位：m/s，例：3.2） + - now_windScale: str - 当前风力等级（例："微风"） + - now_feelst: float - 当前体感温度（单位：℃，例：19.7） + - now_uptime: str - 实时数据更新时间（格式：YYYY/MM/DD HH:MM，例："2025/08/29 10:05"） + + 气象预警（顶层字段，无预警时为空字符串）： + - alarm_id: str - 预警唯一ID（例："51070041600000_20250828215515"） + - alarm_title: str - 预警标题（例："绵阳市气象台更新大风蓝色预警信号[IV级/一般]"） + - alarm_signaltype: str - 预警类型（例："大风"） + - alarm_signallevel: str - 预警等级（例："蓝色"） + - alarm_effective: str - 预警生效时间（例："2025/08/28 21:55"） + - alarm_eventType: str - 预警事件编码（例："11B06"） + - alarm_severity: str - 预警等级英文编码（例："BLUE"） + - alarm_type: str - 预警类型编码（例："p0007004"） + + ### 返回说明（失败，code=400） + - code: int - 错误状态码，固定为400 + - msg: str - 错误详情（例："通讯秘钥错误。"、"API响应解析失败"） + """ + api_url = "https://cn.apihz.cn/api/tianqi/tqyb.php" + clean_province = province.replace("省", "").replace("市", "").strip() + clean_place = place.replace("市", "").replace("区", "").replace("县", "").strip() + final_user_id = os.getenv("APIHZ_ID") + final_user_key = os.getenv("APIHZ_KEY") + params = { + "id": final_user_id, + "key": final_user_key, + "sheng": clean_province, + "place": clean_place + } + + try: + # 1. 发送请求（增加超时重试，避免偶发网络波动） + response = requests.get(api_url, params=params, timeout=10) + response.raise_for_status() # 捕获4xx/5xx HTTP错误 + + # 2. 解析响应：先判断响应内容是否为空，再转JSON + response_text = response.text.strip() + if not response_text: + return {"code": 400, "msg": "API响应为空，无法解析天气数据"} + + # 3. 转JSON并防御None（确保weather_data是字典） + weather_data = response.json() + if not isinstance(weather_data, dict): + return {"code": 400, "msg": f"API响应格式错误，不是有效字典（实际类型：{type(weather_data).__name__}）"} + + # 4. 处理API返回的错误状态（code=400） + if weather_data.get("code") == 400: + return { + "code": 400, + "msg": weather_data.get("msg", "API返回错误，原因未知") + } + # 5. 确保API返回成功状态（code=200） + elif weather_data.get("code") != 200: + return { + "code": 400, + "msg": f"API返回非成功状态码：{weather_data.get('code', '未知')}" + } + + # 6. 提取嵌套数据（确保now_info/alarm_info是字典，避免None） + now_info = weather_data.get("nowinfo", {}) + if not isinstance(now_info, dict): + now_info = {} # 若now_info不是字典，强制设为空字典 + + alarm_info = weather_data.get("alarm", {}) + if not isinstance(alarm_info, dict): + alarm_info = {} # 若alarm不是字典，强制设为空字典 + + # 7. 构造最终返回结果（全部顶层字段，无嵌套） + return { + # 基础预报字段 + "code": 200, + "guo": weather_data.get("guo", ""), + "sheng": weather_data.get("sheng", ""), + "shi": weather_data.get("shi", ""), + "name": weather_data.get("name", ""), + "weather1": weather_data.get("weather1", ""), + "weather2": weather_data.get("weather2", ""), + "wd1": weather_data.get("wd1", ""), + "wd2": weather_data.get("wd2", ""), + "winddirection1": weather_data.get("winddirection1", ""), + "winddirection2": weather_data.get("winddirection2", ""), + "windleve1": weather_data.get("windleve1", ""), + "windleve2": weather_data.get("windleve2", ""), + "weather1img": weather_data.get("weather1img", ""), + "weather2img": weather_data.get("weather2img", ""), + "lon": weather_data.get("lon", ""), + "lat": weather_data.get("lat", ""), + "uptime": weather_data.get("uptime", ""), + # 实时天气字段 + "now_precipitation": float(now_info.get("precipitation", 0.0)), + "now_temperature": float(now_info.get("temperature", 0.0)), + "now_pressure": int(now_info.get("pressure", 0)), + "now_humidity": int(now_info.get("humidity", 0)), + "now_windDirection": now_info.get("windDirection", ""), + "now_windDirectionDegree": int(now_info.get("windDirectionDegree", 0)), + "now_windSpeed": float(now_info.get("windSpeed", 0.0)), + "now_windScale": now_info.get("windScale", ""), + "now_feelst": float(now_info.get("feelst", 0.0)), + "now_uptime": now_info.get("uptime", ""), + # 预警字段 + "alarm_id": alarm_info.get("id", ""), + "alarm_title": alarm_info.get("title", ""), + "alarm_signaltype": alarm_info.get("signaltype", ""), + "alarm_signallevel": alarm_info.get("signallevel", ""), + "alarm_effective": alarm_info.get("effective", ""), + "alarm_eventType": alarm_info.get("eventType", ""), + "alarm_severity": alarm_info.get("severity", ""), + "alarm_type": alarm_info.get("type", "") + } + + # 8. 捕获各类异常（明确错误原因） + except requests.exceptions.HTTPError as e: + status_code = response.status_code if "response" in locals() else "未知" + return {"code": 400, "msg": f"HTTP请求错误（状态码：{status_code}）：{str(e)}"} + except requests.exceptions.ConnectionError: + return {"code": 400, "msg": "网络连接错误：无法连接到天气API服务器"} + except requests.exceptions.Timeout: + return {"code": 400, "msg": "请求超时：API服务器10秒内未响应"} + except ValueError as e: + # 捕获JSON解析错误（如响应不是合法JSON） + return {"code": 400, "msg": f"API响应解析失败（JSON格式错误）：{str(e)}"} + except Exception as e: + # 捕获其他未知错误（附带具体错误信息，便于调试） + return {"code": 400, "msg": f"未知错误：{str(e)}（错误类型：{type(e).__name__}）"} + +@wrap_tool_call +def handle_tool_errors(request, handler): + """使用自定义消息处理工具执行错误。""" + try: + return handler(request) + except Exception as e: + # 向模型返回自定义错误消息 + return ToolMessage( + content=f"工具错误：请检查您的输入并重试。({str(e)})", + tool_call_id=request.tool_call["id"] + ) \ No newline at end of file diff --git a/app/tools/base.py b/app/tools/base.py new file mode 100644 index 0000000..abc52c3 --- /dev/null +++ b/app/tools/base.py @@ -0,0 +1,153 @@ +import json +from abc import ABC, abstractmethod +from typing import Any, Dict, Optional, Union + +from pydantic import BaseModel, Field + +from app.utils.logger import logger + + +class ToolResult(BaseModel): + """表示工具执行的结果。""" + + output: Any = Field(default=None) + error: Optional[str] = Field(default=None) + base64_image: Optional[str] = Field(default=None) + system: Optional[str] = Field(default=None) + + class Config: + arbitrary_types_allowed = True + + def __bool__(self): + return any(getattr(self, field) for field in self.__fields__) + + def __add__(self, other: "ToolResult"): + def combine_fields( + field: Optional[str], other_field: Optional[str], concatenate: bool = True + ): + if field and other_field: + if concatenate: + return field + other_field + raise ValueError("Cannot combine tool results") + return field or other_field + + return ToolResult( + output=combine_fields(self.output, other.output), + error=combine_fields(self.error, other.error), + base64_image=combine_fields(self.base64_image, other.base64_image, False), + system=combine_fields(self.system, other.system), + ) + + def __str__(self): + return f"Error: {self.error}" if self.error else self.output + + def replace(self, **kwargs): + """返回一个替换了给定字段的新 ToolResult。""" + # return self.copy(update=kwargs) + return type(self)(**{**self.dict(), **kwargs}) + + +class BaseTool(ABC, BaseModel): + """所有工具的整合基类，结合了 BaseModel 和 Tool 功能。 + + 提供： + - Pydantic 模型验证 + - 模式注册 + - 标准化结果处理 + - 抽象执行接口 + + 属性: + name (str): 工具名称 + description (str): 工具描述 + parameters (dict): 工具参数模式 + _schemas (Dict[str, List[ToolSchema]]): 已注册的方法模式 + """ + + name: str + description: str + parameters: Optional[dict] = None + # _schemas: Dict[str, List[ToolSchema]] = {} + + class Config: + arbitrary_types_allowed = True + underscore_attrs_are_private = False + + # def __init__(self, **data): + # """Initialize tool with model validation and schema registration.""" + # super().__init__(**data) + # logger.debug(f"Initializing tool class: {self.__class__.__name__}") + # self._register_schemas() + + # def _register_schemas(self): + # """Register schemas from all decorated methods.""" + # for name, method in inspect.getmembers(self, predicate=inspect.ismethod): + # if hasattr(method, 'tool_schemas'): + # self._schemas[name] = method.tool_schemas + # logger.debug(f"Registered schemas for method '{name}' in {self.__class__.__name__}") + + async def __call__(self, **kwargs) -> Any: + """使用给定参数执行工具。""" + return await self.execute(**kwargs) + + @abstractmethod + async def execute(self, **kwargs) -> Any: + """使用给定参数执行工具。""" + + def to_param(self) -> Dict: + """将工具转换为函数调用格式。 + + Returns: + 包含 OpenAI 函数调用格式的工具元数据的字典 + """ + return { + "type": "function", + "function": { + "name": self.name, + "description": self.description, + "parameters": self.parameters, + }, + } + + # def get_schemas(self) -> Dict[str, List[ToolSchema]]: + # """Get all registered tool schemas. + + # Returns: + # Dict mapping method names to their schema definitions + # """ + # return self._schemas + + def success_response(self, data: Union[Dict[str, Any], str]) -> ToolResult: + """创建成功的工具结果。 + + Args: + data: 结果数据（字典或字符串） + + Returns: + 带有 success=True 和格式化输出的 ToolResult + """ + if isinstance(data, str): + text = data + else: + text = json.dumps(data, indent=2) + logger.debug(f"Created success response for {self.__class__.__name__}") + return ToolResult(output=text) + + def fail_response(self, msg: str) -> ToolResult: + """创建失败的工具结果。 + + Args: + msg: 描述失败的错误消息 + + Returns: + 带有 success=False 和错误消息的 ToolResult + """ + logger.debug(f"Tool {self.__class__.__name__} returned failed result: {msg}") + return ToolResult(error=msg) + + +class CLIResult(ToolResult): + """可以渲染为 CLI 输出的 ToolResult。""" + + +class ToolFailure(ToolResult): + """表示失败的 ToolResult。""" diff --git a/app/tools/bash.py b/app/tools/bash.py new file mode 100644 index 0000000..73da13b --- /dev/null +++ b/app/tools/bash.py @@ -0,0 +1,158 @@ +import asyncio +import os +from typing import Optional + +from app.exceptions import ToolError +from app.tools.base import BaseTool, CLIResult + + +_BASH_DESCRIPTION = """在终端中执行 bash 命令。 +* 长时间运行的命令：对于可能无限期运行的命令，应该在后台运行并将输出重定向到文件，例如 command = `python3 app.py > server.log 2>&1 &`。 +* 交互式：如果 bash 命令返回退出代码 `-1`，这意味着进程尚未完成。助手必须向终端发送第二次调用，使用空的 `command`（这将检索任何额外的日志），或者它可以向正在运行的进程的 STDIN 发送附加文本（将 `command` 设置为文本），或者它可以发送 command=`ctrl+c` 来中断进程。 +* 超时：如果命令执行结果说 "Command timed out. Sending SIGINT to the process"，助手应该重试在后台运行该命令。 +""" + + +class _BashSession: + """bash shell 的会话。""" + + _started: bool + _process: asyncio.subprocess.Process + + command: str = "/bin/bash" + _output_delay: float = 0.2 # 秒 + _timeout: float = 120.0 # 秒 + _sentinel: str = "<>" + + def __init__(self): + self._started = False + self._timed_out = False + + async def start(self): + if self._started: + return + + self._process = await asyncio.create_subprocess_shell( + self.command, + preexec_fn=os.setsid, + shell=True, + bufsize=0, + stdin=asyncio.subprocess.PIPE, + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + ) + + self._started = True + + def stop(self): + """终止 bash shell。""" + if not self._started: + raise ToolError("Session has not started.") + if self._process.returncode is not None: + return + self._process.terminate() + + async def run(self, command: str): + """在 bash shell 中执行命令。""" + if not self._started: + raise ToolError("Session has not started.") + if self._process.returncode is not None: + return CLIResult( + system="tool must be restarted", + error=f"bash has exited with returncode {self._process.returncode}", + ) + if self._timed_out: + raise ToolError( + f"timed out: bash has not returned in {self._timeout} seconds and must be restarted", + ) + + # 我们知道这些不是 None，因为我们使用 PIPEs 创建了进程 + assert self._process.stdin + assert self._process.stdout + assert self._process.stderr + + # 向进程发送命令 + self._process.stdin.write( + command.encode() + f"; echo '{self._sentinel}'\n".encode() + ) + await self._process.stdin.drain() + + # 从进程读取输出，直到找到标记 + try: + async with asyncio.timeout(self._timeout): + while True: + await asyncio.sleep(self._output_delay) + # 如果我们直接从 stdout/stderr 读取，它将永远等待 EOF。 + # 改为直接使用 StreamReader 缓冲区。 + output = ( + self._process.stdout._buffer.decode() + ) # pyright: ignore[reportAttributeAccessIssue] + if self._sentinel in output: + # 去除标记并中断 + output = output[: output.index(self._sentinel)] + break + except asyncio.TimeoutError: + self._timed_out = True + raise ToolError( + f"timed out: bash has not returned in {self._timeout} seconds and must be restarted", + ) from None + + if output.endswith("\n"): + output = output[:-1] + + error = ( + self._process.stderr._buffer.decode() + ) # pyright: ignore[reportAttributeAccessIssue] + if error.endswith("\n"): + error = error[:-1] + + # 清除缓冲区，以便可以正确读取下一个输出 + self._process.stdout._buffer.clear() # pyright: ignore[reportAttributeAccessIssue] + self._process.stderr._buffer.clear() # pyright: ignore[reportAttributeAccessIssue] + + return CLIResult(output=output, error=error) + + +class Bash(BaseTool): + """用于执行 bash 命令的工具""" + + name: str = "bash" + description: str = _BASH_DESCRIPTION + parameters: dict = { + "type": "object", + "properties": { + "command": { + "type": "string", + "description": "要执行的 bash 命令。当先前的退出代码为 `-1` 时可以为空以查看其他日志。可以是 `ctrl+c` 来中断当前正在运行的进程。", + }, + }, + "required": ["command"], + } + + _session: Optional[_BashSession] = None + + async def execute( + self, command: str | None = None, restart: bool = False, **kwargs + ) -> CLIResult: + if restart: + if self._session: + self._session.stop() + self._session = _BashSession() + await self._session.start() + + return CLIResult(system="tool has been restarted.") + + if self._session is None: + self._session = _BashSession() + await self._session.start() + + if command is not None: + return await self._session.run(command) + + raise ToolError("no command provided.") + + +if __name__ == "__main__": + bash = Bash() + rst = asyncio.run(bash.execute("ls -l")) + print(rst) diff --git a/app/tools/execute_sql.py b/app/tools/execute_sql.py new file mode 100644 index 0000000..ef68de7 --- /dev/null +++ b/app/tools/execute_sql.py @@ -0,0 +1,56 @@ +from datetime import datetime, date +from decimal import Decimal +from typing import Dict, Any, List +import pymysql +from langchain_core.tools import tool +from app.agent import logger + +@tool +def execute_query(sql: str) -> List[Dict[str, Any]]: + """ + 执行SQL查询并返回结果。 + + 注意事项： + - 确保SQL语法正确，常见错误包括：counts() 应为 count()，表名拼写错误等 + - 如果收到错误响应，请根据错误信息修正SQL后重试 + - 返回格式：成功时返回查询结果列表，失败时返回包含error和message的字典 + + 参数： + sql: 要执行的SQL查询语句 + + 返回： + 查询结果列表（成功）或错误信息字典（失败） + """ + dbconfig = { + "host": "192.168.10.91", + "port": 33062, + "user": "root", + "password": "123456", + "db": "text2sql", + "charset": "utf8mb4", + } + connection = None + result = [] + try: + connection = pymysql.connect(**dbconfig) + with connection.cursor(pymysql.cursors.DictCursor) as cursor: + cursor.execute(sql) + result = cursor.fetchall() + + # 类型转换 + for row in result: + for key, value in row.items(): + if isinstance(value, (datetime, date)): + row[key] = value.strftime("%Y-%m-%d %H:%M:%S") if isinstance(value, datetime) else value.strftime("%Y-%m-%d") + elif isinstance(value, Decimal): + row[key] = float(value) + return result + except Exception as e: + error_msg = f"SQL执行失败: {str(e)}\n请检查SQL语法是否正确，并根据错误信息修正SQL。" + logger.error(error_msg) + # 返回包含错误信息的结果，而不是抛出异常 + # 使用字典格式以便模型理解错误 + return [{"error": True, "message": error_msg}] + finally: + if connection: + connection.close() \ No newline at end of file diff --git a/app/tools/terminate.py b/app/tools/terminate.py new file mode 100644 index 0000000..445e9f3 --- /dev/null +++ b/app/tools/terminate.py @@ -0,0 +1,25 @@ +from app.tools.base import BaseTool + + +_TERMINATE_DESCRIPTION = """当请求已满足或助手无法继续执行任务时终止交互。 +当你完成所有任务后，调用此工具来结束工作。""" + + +class Terminate(BaseTool): + name: str = "terminate" + description: str = _TERMINATE_DESCRIPTION + parameters: dict = { + "type": "object", + "properties": { + "status": { + "type": "string", + "description": "交互的完成状态。", + "enum": ["success", "failure"], + } + }, + "required": ["status"], + } + + async def execute(self, status: str) -> str: + """完成当前执行""" + return f"The interaction has been completed with status: {status}" diff --git a/app/tools/weather.py b/app/tools/weather.py new file mode 100644 index 0000000..e9e89ab --- /dev/null +++ b/app/tools/weather.py @@ -0,0 +1,158 @@ +import os +import requests +from typing import Dict, Union + +from app.tools.base import BaseTool, ToolResult + + +_WEATHER_DESCRIPTION = """ +调用中国气象局天气预报 API，获取指定省份和地点的完整当日天气信息（含基础预报、实时数据、气象预警）。 + +### 参数说明 +- user_id: str - 接口调用身份标识，需从 http://www.apihz.cn 注册获取，不可为空 +- user_key: str - 接口通讯秘钥，与 user_id 对应，注册后获取，不可为空 +- province: str - 查询省份/直辖市，建议去除"省""市"后缀 +- place: str - 查询城市/区/县，建议去除"市""区""县"后缀 + +### 返回说明 +成功时返回包含基础预报、实时天气和气象预警的完整信息；失败时返回错误码和错误消息。 +""" + + +class GetWeatherByLocation(BaseTool): + """天气预报查询工具""" + + name: str = "get_weather_by_location" + description: str = _WEATHER_DESCRIPTION + parameters: dict = { + "type": "object", + "properties": { + "user_id": { + "type": "string", + "description": "接口调用身份标识，需从 http://www.apihz.cn 注册获取", + }, + "user_key": { + "type": "string", + "description": "接口通讯秘钥，与 user_id 对应", + }, + "province": { + "type": "string", + "description": "查询省份/直辖市，建议去除'省''市'后缀", + }, + "place": { + "type": "string", + "description": "查询城市/区/县，建议去除'市''区''县'后缀", + }, + }, + "required": ["user_id", "user_key", "province", "place"], + } + + async def execute( + self, user_id: str, user_key: str, province: str, place: str + ) -> ToolResult: + """执行天气查询""" + api_url = "https://cn.apihz.cn/api/tianqi/tqyb.php" + clean_province = province.replace("省", "").replace("市", "").strip() + clean_place = place.replace("市", "").replace("区", "").replace("县", "").strip() + final_user_id = os.getenv("APIHZ_ID", user_id) + final_user_key = os.getenv("APIHZ_KEY", user_key) + params = { + "id": final_user_id, + "key": final_user_key, + "sheng": clean_province, + "place": clean_place, + } + + try: + # 发送请求 + response = requests.get(api_url, params=params, timeout=10) + response.raise_for_status() + + # 解析响应 + response_text = response.text.strip() + if not response_text: + return self.fail_response("API 响应为空，无法解析天气数据") + + weather_data = response.json() + if not isinstance(weather_data, dict): + return self.fail_response( + f"API 响应格式错误，不是有效字典（实际类型：{type(weather_data).__name__}）" + ) + + # 处理 API 返回的错误状态 + if weather_data.get("code") == 400: + return self.fail_response( + weather_data.get("msg", "API 返回错误，原因未知") + ) + elif weather_data.get("code") != 200: + return self.fail_response( + f"API 返回非成功状态码：{weather_data.get('code', '未知')}" + ) + + # 提取嵌套数据 + now_info = weather_data.get("nowinfo", {}) + if not isinstance(now_info, dict): + now_info = {} + + alarm_info = weather_data.get("alarm", {}) + if not isinstance(alarm_info, dict): + alarm_info = {} + + # 构造最终返回结果 + result = { + # 基础预报字段 + "code": 200, + "guo": weather_data.get("guo", ""), + "sheng": weather_data.get("sheng", ""), + "shi": weather_data.get("shi", ""), + "name": weather_data.get("name", ""), + "weather1": weather_data.get("weather1", ""), + "weather2": weather_data.get("weather2", ""), + "wd1": weather_data.get("wd1", ""), + "wd2": weather_data.get("wd2", ""), + "winddirection1": weather_data.get("winddirection1", ""), + "winddirection2": weather_data.get("winddirection2", ""), + "windleve1": weather_data.get("windleve1", ""), + "windleve2": weather_data.get("windleve2", ""), + "weather1img": weather_data.get("weather1img", ""), + "weather2img": weather_data.get("weather2img", ""), + "lon": weather_data.get("lon", ""), + "lat": weather_data.get("lat", ""), + "uptime": weather_data.get("uptime", ""), + # 实时天气字段 + "now_precipitation": float(now_info.get("precipitation", 0.0)), + "now_temperature": float(now_info.get("temperature", 0.0)), + "now_pressure": int(now_info.get("pressure", 0)), + "now_humidity": int(now_info.get("humidity", 0)), + "now_windDirection": now_info.get("windDirection", ""), + "now_windDirectionDegree": int(now_info.get("windDirectionDegree", 0)), + "now_windSpeed": float(now_info.get("windSpeed", 0.0)), + "now_windScale": now_info.get("windScale", ""), + "now_feelst": float(now_info.get("feelst", 0.0)), + "now_uptime": now_info.get("uptime", ""), + # 预警字段 + "alarm_id": alarm_info.get("id", ""), + "alarm_title": alarm_info.get("title", ""), + "alarm_signaltype": alarm_info.get("signaltype", ""), + "alarm_signallevel": alarm_info.get("signallevel", ""), + "alarm_effective": alarm_info.get("effective", ""), + "alarm_eventType": alarm_info.get("eventType", ""), + "alarm_severity": alarm_info.get("severity", ""), + "alarm_type": alarm_info.get("type", ""), + } + + return self.success_response(result) + + except requests.exceptions.HTTPError as e: + status_code = ( + response.status_code if "response" in locals() else "未知" + ) + return self.fail_response(f"HTTP 请求错误（状态码：{status_code}）：{str(e)}") + except requests.exceptions.ConnectionError: + return self.fail_response("网络连接错误：无法连接到天气 API 服务器") + except requests.exceptions.Timeout: + return self.fail_response("请求超时：API 服务器 10 秒内未响应") + except ValueError as e: + return self.fail_response(f"API 响应解析失败（JSON 格式错误）：{str(e)}") + except Exception as e: + return self.fail_response(f"未知错误：{str(e)}（错误类型：{type(e).__name__}）") diff --git a/app/utils/__init__.py b/app/utils/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/utils/logger.py b/app/utils/logger.py new file mode 100644 index 0000000..11dbb72 --- /dev/null +++ b/app/utils/logger.py @@ -0,0 +1,89 @@ +import logging +import sys +from loguru import logger + + +class InterceptHandler(logging.Handler): + def emit(self, record): + # 获取对应的 Loguru 级别 + try: + level = logger.level(record.levelname).name + except ValueError: + level = record.levelno + + # 从 logging 记录中找到调用位置 + frame, depth = logging.currentframe(), 2 + while frame.f_code.co_filename == logging.__file__: + frame = frame.f_back + depth += 1 + + logger.opt(depth=depth, exception=record.exc_info).log( + level, record.getMessage() + ) + + +def setup_logger(): + """ + 配置 Loguru 日志记录器 + - 移除默认的 handler + - 添加一个用于 INFO 级别日志的文件 sink + - 添加一个用于 ERROR 级别日志的文件 sink + - 保持控制台输出（级别为 DEBUG） + """ + # 检查是否已经初始化，防止重复初始化 + if hasattr(setup_logger, '_initialized') and setup_logger._initialized: + return + + # 1. 移除默认的控制台 handler + logger.remove() + + # 2. 添加一个新的控制台 handler，设置级别为 DEBUG + logger.add( + sys.stderr, + level="INFO", + format="{time:YYYY-MM-DD HH:mm:ss.SSS} | " + "{level: <8} | " + "{name}:{function}:{line} - {message}", + colorize=True, # 开启颜色 + ) + + # 3. 添加 INFO 日志文件 sink + # - level="INFO": 只记录 INFO 及以上级别的日志 + # - filter: 确保 ERROR 级别的日志不会写入这个文件 + # - rotation: 每天午夜创建一个新文件 + # - retention: 只保留最近 14 天的日志 + # - enqueue=True: 异步写入，提升性能 + # - encoding="utf-8": 确保中文不会乱码 + logger.add( + "logs/app.info.log", + level="INFO", + filter=lambda record: record["level"].name in ["INFO", "WARNING"], + rotation="00:00", # 每天午夜轮转 + retention="14 days", # 保留 14 天 + enqueue=True, # 异步写入 + backtrace=True, # 记录堆栈信息 + diagnose=True, # 诊断信息 + encoding="utf-8", + ) + + # 4. 添加 ERROR 日志文件 sink + # - level="ERROR": 只记录 ERROR 及以上级别的日志 (ERROR, CRITICAL) + # - rotation: 文件大小超过 10 MB 时轮转 + # - retention: 只保留最近 30 天的日志 + logger.add( + "logs/app.error.log", + level="ERROR", + rotation="10 MB", # 按文件大小轮转 + retention="30 days", # 保留 30 天 + enqueue=True, # 异步写入 + backtrace=True, + diagnose=True, + encoding="utf-8", + ) + + # 拦截 logging，以便将所有日志都转发到 Loguru + logging.basicConfig(handlers=[InterceptHandler()], level=0, force=True) + + # 设置已初始化标志 + setup_logger._initialized = True + logger.info("日志系统配置完成。") diff --git a/client.py b/client.py index 28b17f3..1448407 100644 --- a/client.py +++ b/client.py @@ -2,7 +2,7 @@ import asyncio import logging import json import os -from typing import List, Dict, Any, Generator +from typing import List, Dict, Any from mcp import ClientSession from mcp.client.sse import sse_client @@ -215,7 +215,7 @@ class AutoToolChatSession: if __name__ == "__main__": config = { "sse_server_url": "http://127.0.0.1:8000/sse", - "llm_model": os.getenv("LLM_MODEL", "qwen3-30b-a3b"), + "llm_model": os.getenv("LLM_MODEL", "deepseek-v3"), "llm_api_key": os.getenv("LLM_API_KEY", "your-api-key"), 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