63 lines
1.6 KiB
Python
63 lines
1.6 KiB
Python
# server.py
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#from fastapi import FastAPI
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#from fastapi_mcp import FastApiMCP
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#
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#app = FastAPI()
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#
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#@app.get("/items/{item_id}", operation_id="get_item")
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#async def read_item(item_id: int):
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# return {"item_id": item_id, "name": f"Item {item_id}"}
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#
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## MCPサーバを作成し、FastAPIアプリにマウント
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#mcp = FastApiMCP(
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# app,
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# name="My API MCP",
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# description="My API description"
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#)
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#mcp.mount()
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#
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#if __name__ == "__main__":
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# import uvicorn
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# uvicorn.run(app, host="0.0.0.0", port=8000)
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from fastapi import FastAPI
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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_messages
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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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# --- モデル定義 ---
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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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# --- ツール（エンドポイント）定義 ---
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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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# --- MCP 初期化 ---
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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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