Raven95676
600 lines
21 KiB
Python
600 lines
21 KiB
Python
from __future__ import annotations
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import json
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import textwrap
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import os
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import asyncio
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import logging
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from typing import Dict, List, Awaitable, Literal, Any
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from dataclasses import dataclass
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from typing import Optional
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from contextlib import AsyncExitStack
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from astrbot import logger
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from astrbot.core.utils.log_pipe import LogPipe
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from astrbot.core.utils.astrbot_path import get_astrbot_data_path
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try:
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import mcp
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from mcp.client.sse import sse_client
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except (ModuleNotFoundError, ImportError):
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logger.warning("警告: 缺少依赖库 'mcp'，将无法使用 MCP 服务。")
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DEFAULT_MCP_CONFIG = {"mcpServers": {}}
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SUPPORTED_TYPES = [
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"string",
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"number",
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"object",
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"array",
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"boolean",
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] # json schema 支持的数据类型
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@dataclass
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class FuncTool:
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"""
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用于描述一个函数调用工具。
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"""
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name: str
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parameters: Dict
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description: str
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handler: Awaitable = None
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"""处理函数, 当 origin 为 mcp 时，这个为空"""
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handler_module_path: str = None
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"""处理函数的模块路径，当 origin 为 mcp 时，这个为空
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必须要保留这个字段, handler 在初始化会被 functools.partial 包装，导致 handler 的 __module__ 为 functools
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"""
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active: bool = True
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"""是否激活"""
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origin: Literal["local", "mcp"] = "local"
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"""函数工具的来源, local 为本地函数工具, mcp 为 MCP 服务"""
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# MCP 相关字段
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mcp_server_name: str = None
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"""MCP 服务名称，当 origin 为 mcp 时有效"""
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mcp_client: MCPClient = None
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"""MCP 客户端，当 origin 为 mcp 时有效"""
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def __repr__(self):
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return f"FuncTool(name={self.name}, parameters={self.parameters}, description={self.description}, active={self.active}, origin={self.origin})"
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async def execute(self, **args) -> Any:
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"""执行函数调用"""
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if self.origin == "local":
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if not self.handler:
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raise Exception(f"Local function {self.name} has no handler")
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return await self.handler(**args)
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elif self.origin == "mcp":
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if not self.mcp_client or not self.mcp_client.session:
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raise Exception(f"MCP client for {self.name} is not available")
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# 使用name属性而不是额外的mcp_tool_name
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if ":" in self.name:
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# 如果名字是格式为 mcp:server:tool_name，提取实际的工具名
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actual_tool_name = self.name.split(":")[-1]
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return await self.mcp_client.session.call_tool(actual_tool_name, args)
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else:
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return await self.mcp_client.session.call_tool(self.name, args)
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else:
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raise Exception(f"Unknown function origin: {self.origin}")
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class MCPClient:
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def __init__(self):
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# Initialize session and client objects
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self.session: Optional[mcp.ClientSession] = None
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self.exit_stack = AsyncExitStack()
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self.name = None
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self.active: bool = True
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self.tools: List[mcp.Tool] = []
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self.server_errlogs: List[str] = []
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async def connect_to_server(self, mcp_server_config: dict, name: str):
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"""连接到 MCP 服务器
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如果 `url` 参数存在，则使用 SSE 的方式连接到 MCP 服务。
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Args:
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mcp_server_config (dict): Configuration for the MCP server. See https://modelcontextprotocol.io/quickstart/server
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"""
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cfg = mcp_server_config.copy()
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if "mcpServers" in cfg and len(cfg["mcpServers"]) > 0:
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key_0 = list(cfg["mcpServers"].keys())[0]
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cfg = cfg["mcpServers"][key_0]
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cfg.pop("active", None) # Remove active flag from config
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if "url" in cfg:
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# SSE transport method
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self._streams_context = sse_client(url=cfg["url"])
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streams = await self._streams_context.__aenter__()
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# Create a new client session
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# self.session = await self._session_context.__aenter__()
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self.session = await self.exit_stack.enter_async_context(
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mcp.ClientSession(*streams)
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)
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else:
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server_params = mcp.StdioServerParameters(
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**cfg,
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)
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def callback(msg: str):
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# 处理 MCP 服务的错误日志
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self.server_errlogs.append(msg)
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stdio_transport = await self.exit_stack.enter_async_context(
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mcp.stdio_client(
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server_params,
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errlog=LogPipe(
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level=logging.ERROR,
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logger=logger,
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identifier=f"MCPServer-{name}",
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callback=callback,
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),
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),
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)
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# Create a new client session
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self.session = await self.exit_stack.enter_async_context(
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mcp.ClientSession(*stdio_transport)
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)
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await self.session.initialize()
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async def list_tools_and_save(self) -> mcp.ListToolsResult:
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"""List all tools from the server and save them to self.tools"""
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response = await self.session.list_tools()
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logger.debug(f"MCP server {self.name} list tools response: {response}")
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self.tools = response.tools
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return response
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async def cleanup(self):
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"""Clean up resources"""
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await self.exit_stack.aclose()
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class FuncCall:
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def __init__(self) -> None:
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self.func_list: List[FuncTool] = []
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"""内部加载的 func tools"""
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self.mcp_client_dict: Dict[str, MCPClient] = {}
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"""MCP 服务列表"""
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self.mcp_service_queue = asyncio.Queue()
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"""用于外部控制 MCP 服务的启停"""
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self.mcp_client_event: Dict[str, asyncio.Event] = {}
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def empty(self) -> bool:
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return len(self.func_list) == 0
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def add_func(
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self,
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name: str,
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func_args: list,
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desc: str,
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handler: Awaitable,
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) -> None:
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"""添加函数调用工具
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@param name: 函数名
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@param func_args: 函数参数列表，格式为 [{"type": "string", "name": "arg_name", "description": "arg_description"}, ...]
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@param desc: 函数描述
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@param func_obj: 处理函数
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"""
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# check if the tool has been added before
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self.remove_func(name)
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params = {
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"type": "object", # hard-coded here
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"properties": {},
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}
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for param in func_args:
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params["properties"][param["name"]] = {
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"type": param["type"],
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"description": param["description"],
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}
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_func = FuncTool(
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name=name,
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parameters=params,
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description=desc,
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handler=handler,
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)
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self.func_list.append(_func)
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logger.info(f"添加函数调用工具: {name}")
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def remove_func(self, name: str) -> None:
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"""
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删除一个函数调用工具。
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"""
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for i, f in enumerate(self.func_list):
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if f.name == name:
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self.func_list.pop(i)
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break
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def get_func(self, name) -> FuncTool:
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for f in self.func_list:
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if f.name == name:
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return f
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return None
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async def _init_mcp_clients(self) -> None:
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"""从项目根目录读取 mcp_server.json 文件，初始化 MCP 服务列表。文件格式如下：
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```
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{
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"mcpServers": {
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"weather": {
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"command": "uv",
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"args": [
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"--directory",
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"/ABSOLUTE/PATH/TO/PARENT/FOLDER/weather",
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"run",
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"weather.py"
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]
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}
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}
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...
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}
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```
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"""
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data_dir = get_astrbot_data_path()
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mcp_json_file = os.path.join(data_dir, "mcp_server.json")
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if not os.path.exists(mcp_json_file):
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# 配置文件不存在错误处理
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with open(mcp_json_file, "w", encoding="utf-8") as f:
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json.dump(DEFAULT_MCP_CONFIG, f, ensure_ascii=False, indent=4)
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logger.info(f"未找到 MCP 服务配置文件，已创建默认配置文件 {mcp_json_file}")
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return
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mcp_server_json_obj: Dict[str, Dict] = json.load(
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open(mcp_json_file, "r", encoding="utf-8")
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)["mcpServers"]
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for name in mcp_server_json_obj.keys():
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cfg = mcp_server_json_obj[name]
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if cfg.get("active", True):
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event = asyncio.Event()
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asyncio.create_task(
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self._init_mcp_client_task_wrapper(name, cfg, event)
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)
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self.mcp_client_event[name] = event
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async def mcp_service_selector(self):
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"""为了避免在不同异步任务中控制 MCP 服务导致的报错，整个项目统一通过这个 Task 来控制
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使用 self.mcp_service_queue.put_nowait() 来控制 MCP 服务的启停，数据格式如下：
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{"type": "init"} 初始化所有MCP客户端
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{"type": "init", "name": "mcp_server_name", "cfg": {...}} 初始化指定的MCP客户端
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{"type": "terminate"} 终止所有MCP客户端
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{"type": "terminate", "name": "mcp_server_name"} 终止指定的MCP客户端
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"""
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while True:
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data = await self.mcp_service_queue.get()
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if data["type"] == "init":
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if "name" in data:
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event = asyncio.Event()
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asyncio.create_task(
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self._init_mcp_client_task_wrapper(
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data["name"], data["cfg"], event
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)
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)
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self.mcp_client_event[data["name"]] = event
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else:
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await self._init_mcp_clients()
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elif data["type"] == "terminate":
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if "name" in data:
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# await self._terminate_mcp_client(data["name"])
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if data["name"] in self.mcp_client_event:
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self.mcp_client_event[data["name"]].set()
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self.mcp_client_event.pop(data["name"], None)
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self.func_list = [
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f
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for f in self.func_list
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if not (
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f.origin == "mcp" and f.mcp_server_name == data["name"]
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)
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]
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else:
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for name in self.mcp_client_dict.keys():
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# await self._terminate_mcp_client(name)
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# self.mcp_client_event[name].set()
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if name in self.mcp_client_event:
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self.mcp_client_event[name].set()
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self.mcp_client_event.pop(name, None)
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self.func_list = [f for f in self.func_list if f.origin != "mcp"]
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async def _init_mcp_client_task_wrapper(
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self, name: str, cfg: dict, event: asyncio.Event
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) -> None:
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"""初始化 MCP 客户端的包装函数，用于捕获异常"""
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try:
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await self._init_mcp_client(name, cfg)
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await event.wait()
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logger.info(f"收到 MCP 客户端 {name} 终止信号")
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await self._terminate_mcp_client(name)
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except Exception as e:
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import traceback
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traceback.print_exc()
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logger.error(f"初始化 MCP 客户端 {name} 失败: {e}")
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async def _init_mcp_client(self, name: str, config: dict) -> None:
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"""初始化单个MCP客户端"""
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try:
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# 先清理之前的客户端，如果存在
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if name in self.mcp_client_dict:
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await self._terminate_mcp_client(name)
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mcp_client = MCPClient()
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mcp_client.name = name
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self.mcp_client_dict[name] = mcp_client
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await mcp_client.connect_to_server(config, name)
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tools_res = await mcp_client.list_tools_and_save()
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tool_names = [tool.name for tool in tools_res.tools]
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# 移除该MCP服务之前的工具（如有）
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self.func_list = [
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f
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for f in self.func_list
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if not (f.origin == "mcp" and f.mcp_server_name == name)
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]
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# 将 MCP 工具转换为 FuncTool 并添加到 func_list
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for tool in mcp_client.tools:
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func_tool = FuncTool(
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name=tool.name,
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parameters=tool.inputSchema,
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description=tool.description,
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origin="mcp",
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mcp_server_name=name,
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mcp_client=mcp_client,
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)
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self.func_list.append(func_tool)
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logger.info(f"已连接 MCP 服务 {name}, Tools: {tool_names}")
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return
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except Exception as e:
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import traceback
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logger.error(traceback.format_exc())
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logger.error(f"初始化 MCP 客户端 {name} 失败: {e}")
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# 发生错误时确保客户端被清理
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if name in self.mcp_client_dict:
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await self._terminate_mcp_client(name)
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return
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async def _terminate_mcp_client(self, name: str) -> None:
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"""关闭并清理MCP客户端"""
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if name in self.mcp_client_dict:
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try:
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# 关闭MCP连接
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await self.mcp_client_dict[name].cleanup()
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del self.mcp_client_dict[name]
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except Exception as e:
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logger.info(f"清空 MCP 客户端资源 {name}: {e}。")
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# 移除关联的FuncTool
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self.func_list = [
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f
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for f in self.func_list
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if not (f.origin == "mcp" and f.mcp_server_name == name)
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]
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logger.info(f"已关闭 MCP 服务 {name}")
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def get_func_desc_openai_style(self, omit_empty_parameter_field=False) -> list:
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"""
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获得 OpenAI API 风格的**已经激活**的工具描述
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"""
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_l = []
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# 处理所有工具（包括本地和MCP工具）
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for f in self.func_list:
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if not f.active:
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continue
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func_ = {
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"type": "function",
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"function": {
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"name": f.name,
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# "parameters": f.parameters,
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"description": f.description,
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},
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}
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func_["function"]["parameters"] = f.parameters
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if not f.parameters.get("properties") and omit_empty_parameter_field:
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# 如果 properties 为空，并且 omit_empty_parameter_field 为 True，则删除 parameters 字段
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del func_["function"]["parameters"]
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_l.append(func_)
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return _l
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def get_func_desc_anthropic_style(self) -> list:
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"""
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获得 Anthropic API 风格的**已经激活**的工具描述
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"""
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tools = []
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for f in self.func_list:
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if not f.active:
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continue
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# Convert internal format to Anthropic style
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tool = {
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"name": f.name,
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"description": f.description,
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"input_schema": {
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"type": "object",
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"properties": f.parameters.get("properties", {}),
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# Keep the required field from the original parameters if it exists
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"required": f.parameters.get("required", []),
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},
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}
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tools.append(tool)
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return tools
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def get_func_desc_google_genai_style(self) -> dict:
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"""
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获得 Google GenAI API 风格的**已经激活**的工具描述
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"""
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# Gemini API 支持的数据类型和格式
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supported_types = {
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"string",
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"number",
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"integer",
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"boolean",
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"array",
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"object",
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"null",
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}
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supported_formats = {
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"string": {"enum", "date-time"},
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"integer": {"int32", "int64"},
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"number": {"float", "double"},
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}
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def convert_schema(schema: dict) -> dict:
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"""转换 schema 为 Gemini API 格式"""
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# 如果 schema 包含 anyOf，则只返回 anyOf 字段
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if "anyOf" in schema:
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return {"anyOf": [convert_schema(s) for s in schema["anyOf"]]}
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result = {}
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if "type" in schema and schema["type"] in supported_types:
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result["type"] = schema["type"]
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if "format" in schema and schema["format"] in supported_formats.get(
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result["type"], set()
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):
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result["format"] = schema["format"]
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else:
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# 暂时指定默认为null
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result["type"] = "null"
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support_fields = {
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"title",
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"description",
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"enum",
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"minimum",
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"maximum",
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"maxItems",
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"minItems",
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"nullable",
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"required",
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}
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result.update({k: schema[k] for k in support_fields if k in schema})
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if "properties" in schema:
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properties = {}
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|
for key, value in schema["properties"].items():
|
|
prop_value = convert_schema(value)
|
|
if "default" in prop_value:
|
|
del prop_value["default"]
|
|
properties[key] = prop_value
|
|
|
|
if properties: # 只在有非空属性时添加
|
|
result["properties"] = properties
|
|
|
|
if "items" in schema:
|
|
result["items"] = convert_schema(schema["items"])
|
|
|
|
return result
|
|
|
|
tools = [
|
|
{
|
|
"name": f.name,
|
|
"description": f.description,
|
|
**({"parameters": convert_schema(f.parameters)}),
|
|
}
|
|
for f in self.func_list
|
|
if f.active
|
|
]
|
|
|
|
declarations = {}
|
|
if tools:
|
|
declarations["function_declarations"] = tools
|
|
return declarations
|
|
|
|
async def func_call(self, question: str, session_id: str, provider) -> tuple:
|
|
_l = []
|
|
for f in self.func_list:
|
|
if not f.active:
|
|
continue
|
|
_l.append(
|
|
{
|
|
"name": f.name,
|
|
"parameters": f.parameters,
|
|
"description": f.description,
|
|
}
|
|
)
|
|
func_definition = json.dumps(_l, ensure_ascii=False)
|
|
|
|
prompt = textwrap.dedent(f"""
|
|
ROLE:
|
|
你是一个 Function calling AI Agent, 你的任务是将用户的提问转化为函数调用。
|
|
|
|
TOOLS:
|
|
可用的函数列表:
|
|
|
|
{func_definition}
|
|
|
|
LIMIT:
|
|
1. 你返回的内容应当能够被 Python 的 json 模块解析的 Json 格式字符串。
|
|
2. 你的 Json 返回的格式如下：`[{{"name": "<func_name>", "args": <arg_dict>}}, ...]`。参数根据上面提供的函数列表中的参数来填写。
|
|
3. 允许必要时返回多个函数调用，但需保证这些函数调用的顺序正确。
|
|
4. 如果用户的提问中不需要用到给定的函数，请直接返回 `{{"res": False}}`。
|
|
|
|
EXAMPLE:
|
|
1. `用户提问`：请问一下天气怎么样？ `函数调用`：[{{"name": "get_weather", "args": {{"city": "北京"}}}}]
|
|
|
|
用户的提问是：{question}
|
|
""")
|
|
|
|
_c = 0
|
|
while _c < 3:
|
|
try:
|
|
res = await provider.text_chat(prompt, session_id)
|
|
if res.find("```") != -1:
|
|
res = res[res.find("```json") + 7 : res.rfind("```")]
|
|
res = json.loads(res)
|
|
break
|
|
except Exception as e:
|
|
_c += 1
|
|
if _c == 3:
|
|
raise e
|
|
if "The message you submitted was too long" in str(e):
|
|
raise e
|
|
|
|
if "res" in res and not res["res"]:
|
|
return "", False
|
|
|
|
tool_call_result = []
|
|
for tool in res:
|
|
# 说明有函数调用
|
|
func_name = tool["name"]
|
|
args = tool["args"]
|
|
# 调用函数
|
|
func_tool = self.get_func(func_name)
|
|
if not func_tool:
|
|
raise Exception(f"Request function {func_name} not found.")
|
|
|
|
ret = await func_tool.execute(**args)
|
|
if ret:
|
|
tool_call_result.append(str(ret))
|
|
return tool_call_result, True
|
|
|
|
def __str__(self):
|
|
return str(self.func_list)
|
|
|
|
def __repr__(self):
|
|
return str(self.func_list)
|
|
|
|
async def terminate(self):
|
|
for name in self.mcp_client_dict.keys():
|
|
await self._terminate_mcp_client(name)
|
|
logger.debug(f"清理 MCP 客户端 {name} 资源")
|