采用向量数据库实现长期记忆

app/backend.py

@@ -12,7 +12,6 @@ from fastapi import FastAPI, HTTPException, WebSocket, WebSocketDisconnect, Depe
 from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel
 from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver
-from langgraph.store.postgres.aio import AsyncPostgresStore 
 from app.agent import AIAgentService
 from app.logger import debug, info, warning, error
 
@@ -23,23 +22,19 @@ load_dotenv()
 # 优先级：环境变量 DB_URI > Docker 内部服务名 > 本地开发地址
 DB_URI = os.getenv(
     "DB_URI",
-    "postgresql://postgres:mysecretpassword@localhost:5432/langgraph_db?sslmode=disable"
+    "postgresql://postgres:mysecretpassword@ai-postgres:5432/langgraph_db?sslmode=disable"
 )
 
 
 @asynccontextmanager
 async def lifespan(app: FastAPI):
     """应用生命周期管理：创建并注入全局服务"""
-    # 1. 创建数据库连接池并初始化表
-    async with (
-        AsyncPostgresSaver.from_conn_string(DB_URI) as checkpointer,
-        AsyncPostgresStore.from_conn_string(DB_URI) as store
-        ):
+    # 1. 创建数据库连接池并初始化表（仅 checkpointer）
+    async with AsyncPostgresSaver.from_conn_string(DB_URI) as checkpointer:
         await checkpointer.setup()
-        await store.setup()
         
         # 2. 构建 AI Agent 服务
-        agent_service = AIAgentService(checkpointer,store)
+        agent_service = AIAgentService(checkpointer)
         await agent_service.initialize()
         
         # 3. 将服务实例存入 app.state
@@ -155,4 +150,6 @@ async def websocket_endpoint(
 
 if __name__ == "__main__":
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8001)
+    # 使用环境变量或默认端口 8003（避免与 vLLM 的 8001 端口冲突）
+    port = int(os.getenv("BACKEND_PORT", "8003"))
+    uvicorn.run(app, host="0.0.0.0", port=port)