feat: 项目完成

2026-03-20 22:56:24 +08:00
parent 0b087df55e
commit c2a515ec2c
33 changed files with 1234 additions and 2 deletions
--- a/_demo/mcp/streamable_agent.py
+++ b/_demo/mcp/streamable_agent.py
@@ -0,0 +1,84 @@
+import json
+import logging
+import asyncio
+from langchain_openai import ChatOpenAI
+from mcp import ClientSession
+from mcp.client.streamable_http import streamablehttp_client
+from langchain_mcp_adapters.tools import load_mcp_tools
+from langchain.agents import create_tool_calling_agent, AgentExecutor
+from langchain_core.prompts import ChatPromptTemplate
+from conf import settings
+
+# 创建模型
+llm = ChatOpenAI(
+    base_url=settings.base_url,
+    api_key=settings.api_key,
+    model=settings.model_name,
+    temperature=0.1
+)
+
+# MCP 服务器的 Streamable-HTTP 连接地址
+server_url = "http://127.0.0.1:8002/mcp"
+
+# 配置日志
+logging.basicConfig(
+    level=logging.DEBUG,  # 提高日志级别以捕获更多信息
+    format='[客户端] %(asctime)s - %(levelname)s - %(message)s'
+)
+
+# 定义mcp客户端
+mcp_client = None
+
+async def run_agent():
+    global mcp_client
+    logging.info(f"准备连接到 Streamable-HTTP 服务器: {server_url}")
+    # 启动 MCP server，通过streamable建立连接
+    async with streamablehttp_client(server_url) as (read, write, _):
+        logging.info("连接已成功建立！")
+        # 使用读写通道创建 MCP 会话
+        async with ClientSession(read, write) as session:
+            try:
+                await session.initialize()
+                logging.info("会话初始化成功，可以开始加载工具。")
+                # 动态创建一个临时类 MCPClientHolder，把 session 放进去。这样就可以在函数外部通过 mcp_client.session 调用 MCP 工具
+                mcp_client = type("MCPClientHolder", (), {"session": session})()
+
+                # 从 session 自动获取 MCP server 提供的工具列表。
+                tools = await load_mcp_tools(session)
+                # print(f"tools-->{tools}")
+
+                # 创建 agent 的提示模板
+                prompt = ChatPromptTemplate.from_messages([
+                    ("system", "你是一个乐于助人的助手，能够调用工具回答用户问题。"),
+                    ("human", "{input}"),
+                    ("placeholder", "{agent_scratchpad}"),
+                ])
+
+                # 构建工具调用代理
+                agent = create_tool_calling_agent(llm, tools, prompt)
+
+                # 创建代理执行器
+                agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
+
+                # 代理调用
+                print("MCP客户端启动，输入'quit'退出")
+                while True:
+                    query = input("\nQuery: ").strip()
+                    if query.lower() == "quit":
+                        break
+                    # 发送用户查询到 agent 并打印格式化响应
+                    logging.info(f"处理用户查询: {query}")
+                    try:
+                        response = await agent_executor.ainvoke({"input": query})
+                        print(f"response-->{response}")
+                    except Exception:
+                        print("解析有问题")
+            except Exception as e:
+                logging.error(f"会话初始化或工具调用时发生错误: {e}", exc_info=True)
+                raise
+
+if __name__ == "__main__":
+    try:
+        asyncio.run(run_agent())
+    except Exception as e:
+        logging.error(f"客户端运行失败: {e}", exc_info=True)