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| import asyncio
import os
from typing import Optional
from contextlib import AsyncExitStack
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
from anthropic import Anthropic
from dotenv import load_dotenv
from openai import OpenAI
class MCPClient:
def __init__(self):
self.session: Optional[ClientSession] = None
self.exit_stack = AsyncExitStack()
self.client = OpenAI(
api_key=os.getenv("OPENAI_API_KEY", ""),
base_url=os.getenv("OPENAI_BASE_URL", "https://api.deepseek.com")
)
self.model = "deepseek-chat"
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 for tool in tools])
async def process_query(self, query: str) -> str:
"""处理用户输入，调用模型 + 工具"""
messages = [
{"role": "user", "content": query},
{"role": "system", "content": "你是一位优秀的职业交易员, 擅长通过价格行为对市场进行分析, 属于波段交易者"}
]
response = await self.session.list_tools()
available_tools = [
{
"type": "function",
"function": {
"name": tool.name,
"description": tool.description,
"parameters": tool.inputSchema
}
}
for tool in response.tools
]
final_text = []
tool_results = []
completion = self.client.chat.completions.create(
model=self.model,
messages=messages,
tools=available_tools,
tool_choice="auto",
)
while completion.choices[0].finish_reason == "tool_calls":
choice = completion.choices[0]
tool_call = choice.message.tool_calls[0]
tool_name = tool_call.function.name
tool_args = eval(tool_call.function.arguments)
tool_result = await self.session.call_tool(tool_name, tool_args)
tool_results.append({"tool": tool_name, "result": tool_result})
messages.append({
"role": "assistant",
"tool_calls": [tool_call]
})
messages.append({
"role": "tool",
"tool_call_id": tool_call.id,
"content": str(tool_result.content)
})
completion = self.client.chat.completions.create(
model=self.model,
messages=messages,
tools=available_tools,
tool_choice="auto",
)
final_text.append(completion.choices[0].message.content)
return "\n".join(final_text)
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())
|
