'commit'

AI/WxMini/Start.py

@@ -26,6 +26,7 @@ milvus_pool = MilvusConnectionPool(host=MS_HOST, port=MS_PORT, max_connections=M
 collection_name = MS_COLLECTION_NAME
 collection_manager = MilvusCollectionManager(collection_name)
 
+
 # 使用 Lifespan Events 处理应用启动和关闭逻辑
 @asynccontextmanager
 async def lifespan(app: FastAPI):
@@ -42,6 +43,7 @@ async def lifespan(app: FastAPI):
     await app.state.mysql_pool.wait_closed()
     logger.info("Milvus 和 MySQL 连接池已关闭。")
 
+
 # 初始化 FastAPI 应用
 app = FastAPI(lifespan=lifespan)
 
@@ -51,6 +53,7 @@ client = AsyncOpenAI(
     base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
 )
 
+
 @app.post("/reply")
 async def reply(session_id: str = Form(...), prompt: str = Form(...)):
     """
@@ -140,8 +143,6 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
             await asyncio.to_thread(collection_manager.insert_data, entities)
             logger.info("用户输入和大模型反馈已记录到向量数据库。")
 
-
-
             # 调用 TTS 生成 MP3
             uuid_str = str(uuid.uuid4())
             timestamp = int(time.time())
@@ -149,7 +150,8 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
 
             # 生成 TTS 音频数据（不落盘）
             t = TTS(None)  # 传入 None 表示不保存到本地文件
-            audio_data, duration = await asyncio.to_thread(t.generate_audio, result)  # 假设 TTS 类有一个 generate_audio 方法返回音频数据
+            audio_data, duration = await asyncio.to_thread(t.generate_audio,
+                                                           result)  # 假设 TTS 类有一个 generate_audio 方法返回音频数据
             print(f"音频时长: {duration} 秒")
 
             # 将音频数据直接上传到 OSS
@@ -160,13 +162,14 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
             url = 'https://ylt.oss-cn-hangzhou.aliyuncs.com/' + tts_file
 
             # 记录聊天数据到 MySQL
-            await save_chat_to_mysql(app.state.mysql_pool, session_id, prompt, result,url,duration)
+            await save_chat_to_mysql(app.state.mysql_pool, session_id, prompt, result, url, duration)
             logger.info("用户输入和大模型反馈已记录到 MySQL 数据库。")
 
             return {
                 "success": True,
                 "url": url,
                 "search_time": end_time - start_time,  # 返回查询耗时
+                "duration": duration,  # 返回大模型的回复时长
                 "response": result  # 返回大模型的回复
             }
         else:
@@ -182,9 +185,9 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
 # 获取聊天记录
 @app.get("/get_chat_log")
 async def get_chat_log(
-    session_id: str,
-    page: int = Query(default=1, ge=1, description="当前页码"),
-    page_size: int = Query(default=10, ge=1, le=100, description="每页记录数")
+        session_id: str,
+        page: int = Query(default=1, ge=1, description="当前页码"),
+        page_size: int = Query(default=10, ge=1, le=100, description="每页记录数")
 ):
     """
     根据 session_id 查询聊天记录，并按 id 降序分页
@@ -194,14 +197,15 @@ async def get_chat_log(
     :return: 分页数据
     """
     try:
-        result = await get_chat_log_by_session(app.state.mysql_pool,session_id, page, page_size)
+        result = await get_chat_log_by_session(app.state.mysql_pool, session_id, page, page_size)
         return result
     except Exception as e:
         logger.error(f"查询聊天记录失败: {str(e)}")
         raise HTTPException(status_code=500, detail=f"查询聊天记录失败: {str(e)}")
 
+
 # 运行 FastAPI 应用
 if __name__ == "__main__":
     import uvicorn
 
-    uvicorn.run("Start:app", host="0.0.0.0", port=5600, workers=1)
+    uvicorn.run("Start:app", host="0.0.0.0", port=5600, workers=1)