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| import asyncio
from typing import Optional
from contextlib import AsyncExitStack
import os
import json
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
from openai import OpenAI
from dotenv import load_dotenv
load_dotenv()
api_key = os.environ["DS_API_KEY"]
base_url = os.environ["DS_API_BASE"]
class MCPClient:
def __init__(self):
self.session: Optional[ClientSession] = None
self.exit_stack = AsyncExitStack()
self.openai = OpenAI(api_key=api_key, base_url=base_url)
async def connect_to_server(self, server_script_path: str):
"""Connect to an MCP server
Args:
server_script_path: Path to the server script (.py or .js)
"""
is_python = server_script_path.endswith(".py")
is_js = server_script_path.endswith(".js")
if not (is_python or is_js):
raise ValueError("Server script must be a .py or .js file")
command = "python" if is_python else "node"
server_params = StdioServerParameters(
command=command, args=[server_script_path], env=None
)
stdio_transport = await self.exit_stack.enter_async_context(
stdio_client(server_params)
)
self.stdio, self.write = stdio_transport
self.session = await self.exit_stack.enter_async_context(
ClientSession(self.stdio, self.write)
)
await self.session.initialize()
response = await self.session.list_tools()
tools = response.tools
print(
"\nConnected to server with tools:",
[[tool.name, tool.description, tool.inputSchema] for tool in tools],
)
async def process_query(self, query: str) -> str:
"""Process a query using Claude and available tools"""
messages = [{"role": "user", "content": query}]
response = await self.session.list_tools()
available_tools = []
for tool in response.tools:
tool_schema = getattr(
tool,
"inputSchema",
{"type": "object", "properties": {}, "required": []},
)
openai_tool = {
"type": "function",
"function": {
"name": tool.name,
"description": tool.description,
"parameters": tool_schema,
},
}
available_tools.append(openai_tool)
model_response = self.openai.chat.completions.create(
model="ep-20250221170925-gg4xx",
max_tokens=1000,
messages=messages,
tools=available_tools,
)
tool_results = []
final_text = []
messages.append(model_response.choices[0].message.model_dump())
print('工具调用指令：',messages[-1])
if model_response.choices[0].message.tool_calls:
tool_call = model_response.choices[0].message.tool_calls[0]
tool_args = json.loads(tool_call.function.arguments)
tool_name = tool_call.function.name
result = await self.session.call_tool(tool_name, tool_args)
print(f"工具名称： {tool_name} 调用参数： {tool_args} \n工具返回结果： {result}")
tool_results.append({"call": tool_name, "result": result})
final_text.append(f"[Calling tool {tool_name} with args {tool_args}]")
messages.append(
{
"role": "tool",
"content": f"{result}",
"tool_call_id": tool_call.id,
}
)
response = self.openai.chat.completions.create(
model="ep-20250221170925-gg4xx",
max_tokens=1000,
messages=messages,
)
messages.append(response.choices[0].message.model_dump())
print('模型回复结果：',messages[-1])
return messages[-1]["content"]
async def chat_loop(self):
"""Run an interactive chat loop"""
print("\nMCP Client Started!")
print("Type your queries or 'quit' to exit.")
while True:
try:
query = input("\nQuery: ").strip()
if query.lower() == "quit":
break
response = await self.process_query(query)
print("\n" + response)
except Exception as e:
print(f"\nError: {str(e)}")
async def cleanup(self):
"""Clean up resources"""
await self.exit_stack.aclose()
async def main():
if len(sys.argv) < 2:
print("Usage: python client.py <path_to_server_script>")
sys.exit(1)
client = MCPClient()
try:
await client.connect_to_server(sys.argv[1])
await client.chat_loop()
finally:
await client.cleanup()
if __name__ == "__main__":
import sys
asyncio.run(main())
|
