add mcp use method

langgraph_qwen/mcp.py

@@ -0,0 +1,176 @@
+# langgraph_qwen/mcp.py
+from __future__ import annotations
+
+import os
+import json
+import asyncio
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+
+from langgraph.prebuilt import create_react_agent
+from .chat_model import ChatQwenOpenAICompat
+
+__all__ = [
+    "load_mcp_tools",
+    "create_qwen_agent_with_mcp_async",
+    "create_qwen_agent_with_mcp",
+    "resolve_servers_config",
+]
+
+def _env(name: str, default: str = "") -> str:
+    return os.getenv(name) or default
+
+# ---------- 配置加载 & 合并 ----------
+
+def _read_config_file(path: str) -> Dict[str, Dict[str, Any]]:
+    p = Path(path)
+    if not p.exists():
+        raise FileNotFoundError(f"MCP config file not found: {path}")
+
+    ext = p.suffix.lower()
+    if ext in {".json", ""}:
+        data = json.loads(p.read_text(encoding="utf-8"))
+    elif ext in {".yml", ".yaml"}:
+        try:
+            import yaml  # type: ignore
+        except Exception as e:
+            raise RuntimeError("需要解析 YAML：请安装 `pip install pyyaml`") from e
+        data = yaml.safe_load(p.read_text(encoding="utf-8"))
+    else:
+        raise ValueError(f"Unsupported config extension: {ext}")
+
+    # 支持两种结构：
+    # 1) {"servers": { ... }}
+    # 2) { ... }  直接就是 servers 映射
+    if isinstance(data, dict) and "servers" in data and isinstance(data["servers"], dict):
+        return data["servers"]
+    if isinstance(data, dict):
+        return data
+    raise ValueError("Invalid config structure: expect a dict (optionally under key 'servers').")
+
+def _servers_from_env_json() -> Optional[Dict[str, Dict[str, Any]]]:
+    raw = os.getenv("MCP_SERVERS_JSON")
+    if not raw:
+        return None
+    try:
+        data = json.loads(raw)
+        if isinstance(data, dict) and data:
+            return data  # 直接就是 servers 映射
+    except Exception:
+        pass
+    return None
+
+def _fallback_servers() -> Dict[str, Dict[str, Any]]:
+    # 最后兜底：单一 HTTP 测试服务（本地 FastAPI/fastmcp-http）
+    return {
+        "weather": {
+            "url": _env("WEATHER_MCP_URL", "http://127.0.0.1:8000/mcp/"),
+            "transport": _env("WEATHER_TRANSPORT", "streamable_http"),
+        }
+    }
+
+def resolve_servers_config(
+    servers: Optional[Dict[str, Dict[str, Any]]] = None,
+    config_path: Optional[str] = None,
+) -> Dict[str, Dict[str, Any]]:
+    """
+    统一解析 servers 配置的入口，优先级（后者覆盖前者）：
+      1) 文件（config_path 或 MCP_CONFIG_PATH）
+      2) 环境变量 MCP_SERVERS_JSON
+      3) 代码传入的 servers（作为最终覆盖）
+      4) 兜底本地 weather HTTP 服务器
+    """
+    merged: Dict[str, Dict[str, Any]] = {}
+
+    # 1) 文件
+    path = config_path or os.getenv("MCP_CONFIG_PATH")
+    if path:
+        try:
+            merged.update(_read_config_file(path))
+        except Exception as e:
+            raise RuntimeError(f"读取 MCP 配置文件失败：{e}")
+
+    # 2) 环境变量（JSON 字符串）
+    env_servers = _servers_from_env_json()
+    if env_servers:
+        merged.update(env_servers)
+
+    # 3) 代码传入（最后覆盖）
+    if servers:
+        merged.update(servers)
+
+    # 4) 兜底
+    if not merged:
+        merged = _fallback_servers()
+    return merged
+
+# ---------- MCP 工具加载 ----------
+
+async def load_mcp_tools(
+    servers: Optional[Dict[str, Dict[str, Any]]] = None,
+    config_path: Optional[str] = None,
+) -> List[Any]:
+    """
+    异步加载 MCP 工具（支持 HTTP streamable 与 本地 stdio/npx）。
+    依赖：langchain-mcp-adapters
+    """
+    try:
+        from langchain_mcp_adapters.client import MultiServerMCPClient  # type: ignore
+    except Exception as e:
+        raise RuntimeError("请安装：`uv pip install -e '.[mcp-adapters]'` 或 `pip install langchain-mcp_adapters`") from e
+
+    resolved_servers = resolve_servers_config(servers=servers, config_path=config_path)
+    client = MultiServerMCPClient(resolved_servers)
+
+    tools = await client.get_tools()
+
+    # 关闭会话（兼容不同版本）
+    try:
+        if hasattr(client, "close") and callable(getattr(client, "close")):
+            await client.close()  # type: ignore
+        elif hasattr(client, "close_all_sessions") and callable(getattr(client, "close_all_sessions")):
+            await client.close_all_sessions()  # type: ignore
+    except Exception:
+        pass
+    return tools
+
+# ---------- Agent 工厂 ----------
+
+async def create_qwen_agent_with_mcp_async(
+    *,
+    servers: Optional[Dict[str, Dict[str, Any]]] = None,
+    config_path: Optional[str] = None,
+    tool_choice: str = "auto",
+    model: Optional[ChatQwenOpenAICompat] = None,
+):
+    """
+    异步工厂：加载 MCP 工具 -> 绑定到 Qwen 模型 -> 创建 LangGraph ReAct agent
+    """
+    tools = await load_mcp_tools(servers=servers, config_path=config_path)
+    model = (model or ChatQwenOpenAICompat(temperature=0)).bind_tools(tools).bind(tool_choice=tool_choice)
+    return create_react_agent(model, tools)
+
+def _run_coro_sync(coro):
+    try:
+        asyncio.get_running_loop()
+    except RuntimeError:
+        return asyncio.run(coro)
+    raise RuntimeError("检测到事件循环，改用：`await create_qwen_agent_with_mcp_async(...)`")
+
+def create_qwen_agent_with_mcp(
+    *,
+    model: Optional[ChatQwenOpenAICompat] = None,
+    servers: Optional[Dict[str, Dict[str, Any]]] = None,
+    config_path: Optional[str] = None,
+    tool_choice: str = "auto",
+):
+    """
+    同步工厂：内部临时事件循环拉工具，再创建 ReAct agent。
+    用于 quickstart/脚本场景；在异步框架里请用 create_qwen_agent_with_mcp_async。
+    """
+    model = model or ChatQwenOpenAICompat(temperature=0)
+    return _run_coro_sync(
+        create_qwen_agent_with_mcp_async(
+            servers=servers, config_path=config_path, tool_choice=tool_choice, model=model
+        )
+    )