add: main.py

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2026-06-27 13:58:50 +00:00
commit 5cd2f21f0f
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import asyncio
import json
import os
from datetime import datetime
from pathlib import Path
from typing import Any, Optional
from fnmatch import fnmatch
from fastmcp import FastMCP, Client
from langchain_openai import ChatOpenAI
from langchain_core.messages import HumanMessage
from langchain.tools import tool
from deepagents import create_deep_agent
from deepagents.backends import FilesystemBackend, LocalShellBackend, CompositeBackend
# ------------------- Memory Server -------------------
class MemoryServer:
def __init__(self):
self.mcp = FastMCP("Memory-Server")
self.storage_path = Path("./memory_data.json")
def _load_memory(self) -> dict:
if not self.storage_path.exists():
return {}
with open(self.storage_path, 'r', encoding='utf-8') as f:
return json.load(f)
def _save_memory(self, data: dict):
self.storage_path.parent.mkdir(parents=True, exist_ok=True)
with open(self.storage_path, 'w', encoding='utf-8') as f:
json.dump(data, f, indent=2, ensure_ascii=False)
@self.mcp.tool()
def save(self, key: str, value: Any) -> bool:
data = self._load_memory()
data[key] = {
"value": value,
"timestamp": datetime.utcnow().isoformat()
}
self._save_memory(data)
return True
@self.mcp.tool()
def get(self, key: str) -> Optional[dict]:
data = self._load_memory()
if key in data:
return {"key": key, "value": data[key]["value"], "timestamp": data[key]["timestamp"]}
return None
@self.mcp.tool()
def delete(self, key: str) -> bool:
data = self._load_memory()
if key in data:
del data[key]
self._save_memory(data)
return True
return False
@self.mcp.tool()
def list_keys(self, pattern: str = "*") -> list[str]:
data = self._load_memory()
return [k for k in data.keys() if fnmatch(k, pattern)]
@self.mcp.tool()
def save_with_namespace(self, key: str, value: Any, namespace: str = "default") -> bool:
full_key = f"{namespace}:{key}"
return self.save(full_key, value)
@self.mcp.tool()
def get_by_namespace(self, namespace: str = "default") -> list[dict]:
data = self._load_memory()
result = []
prefix = f"{namespace}:"
for k, v in data.items():
if k.startswith(prefix):
result.append({"key": k, "value": v["value"], "timestamp": v["timestamp"]})
return result
# ------------------- DeepAgent that uses Memory Server -------------------
# The agent will use a simple tool that calls the memory server via MCP client
@tool
def memory_tool(action: str, params: dict) -> str:
"""Calls the memory server tool specified by action.
Parameters must include the tool name and its arguments.
"""
client = Client("python memory_server.py")
asyncio.run(client.connect())
try:
result = asyncio.run(client.call_tool(action, params))
return str(result)
finally:
asyncio.run(client.close())
# LLM and backend setup
llm = ChatOpenAI(
model="openai/gpt-oss-20b:free",
base_url="https://openrouter.ai/api/v1",
api_key=os.getenv("OPENAI_API_KEY"),
temperature=0.0,
)
backend = CompositeBackend([
LocalShellBackend(workspace_dir="./workspace"),
FilesystemBackend(),
])
agent = create_deep_agent(
model=llm,
tools=[memory_tool],
backend=backend,
system_prompt="You are an agent that can store and retrieve data using the memory server.",
)
async def run_agent_demo():
response = await agent.ainvoke(
{"messages": [HumanMessage(content="Store key 'greeting' with value 'Hello' in default namespace.")]},
{"configurable": {"thread_id": "demo-1"}},
)
print("Agent response:", response["messages"][-1].content)
# ------------------- Server run -------------------
if __name__ == "__main__":
# Start server in background if called directly
server = MemoryServer()
# Run server in a separate thread so that the agent demo can also run
import threading
server_thread = threading.Thread(target=lambda: server.mcp.run(transport="stdio", show_banner=False, log_level="ERROR"), daemon=True)
server_thread.start()
# Give server a moment to start
asyncio.run(asyncio.sleep(0.5))
# Run agent demo
asyncio.run(run_agent_demo())
# Keep server alive for a short while to allow manual testing
try:
while True:
pass
except KeyboardInterrupt:
print("Shutting down.")