57 lines
1.8 KiB
Python
57 lines
1.8 KiB
Python
# server.py
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from fastapi import FastAPI, Body
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from fastapi_mcp import FastApiMCP
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from pydantic import BaseModel
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from memory_store import save_message, load_logs, search_memory as do_search_memory
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app = FastAPI()
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mcp = FastApiMCP(app, name="aigpt-agent", description="MCP Server for AI memory")
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class ChatInput(BaseModel):
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message: str
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class MemoryInput(BaseModel):
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sender: str
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message: str
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class MemoryQuery(BaseModel):
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query: str
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@app.post("/chat", operation_id="chat")
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async def chat(input: ChatInput):
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save_message("user", input.message)
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response = f"AI: 「{input.message}」を受け取りました！"
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save_message("ai", response)
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return {"response": response}
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@app.post("/memory", operation_id="save_memory")
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async def memory_post(input: MemoryInput):
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save_message(input.sender, input.message)
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return {"status": "saved"}
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@app.get("/memory", operation_id="get_memory")
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async def memory_get():
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return {"messages": load_messages()}
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@app.post("/ask_message", operation_id="ask_message")
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async def ask_message(input: MemoryQuery):
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results = search_memory(input.query)
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return {
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"response": f"🔎 記憶から {len(results)} 件ヒット:\n" + "\n".join([f"{r['sender']}: {r['message']}" for r in results])
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}
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@app.post("/memory/search", operation_id="memory")
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async def memory_search(query: MemoryQuery):
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hits = do_search_memory(query.query)
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if not hits:
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return {"result": "🔍 記憶の中に該当する内容は見つかりませんでした。"}
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summary = "\n".join([f"{e['sender']}: {e['message']}" for e in hits])
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return {"result": f"🔎 見つかった記憶:\n{summary}"}
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mcp.mount()
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if __name__ == "__main__":
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import uvicorn
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print("🚀 Starting MCP server...")
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uvicorn.run(app, host="127.0.0.1", port=5000)
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