update:优化了websocket对数据库连接的获取与释放
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@@ -2,20 +2,29 @@ from fastapi import FastAPI, Depends, WebSocket, HTTPException
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from fastapi.middleware.cors import CORSMiddleware
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from config import Config
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from app.concrete import Agent
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from app.model import Assistant, User, get_db
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from app.model import Assistant, User, get_db, get_db_context
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from app.schemas import *
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from app.dependency import get_logger
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from app.exception import *
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import asyncio
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import uvicorn
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import uuid
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import json
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import time
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# 公共函数 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------
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def update_messages(messages, kid_text,llm_text):
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messages = json.loads(messages)
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def update_messages(assistant, kid_text, llm_text):
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messages = json.loads(assistant.messages)
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if not kid_text:
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raise AsrResultNoneError()
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if not llm_text:
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raise LlmResultNoneError()
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messages.append({"role":"user","content":kid_text})
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messages.append({"role":"assistant","content":llm_text})
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return json.dumps(messages,ensure_ascii=False)
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with get_db_context() as db:
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db.query(Assistant).filter(Assistant.id == assistant.id).update({"messages":json.dumps(messages,ensure_ascii=False),"token":assistant.token})
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db.commit()
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# --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
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# 引入logger对象
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@@ -177,7 +186,7 @@ async def update_user(id: str,request: update_user_request,db=Depends(get_db)):
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# 流式聊天websokct接口 ------------------------------------------------------------------------------------------------------------------------------------------------------------
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@app.websocket("/api/chat/streaming/temporary")
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async def streaming_chat(ws: WebSocket,db=Depends(get_db)):
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async def streaming_chat(ws: WebSocket):
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await ws.accept()
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logger.debug("WebSocket连接成功")
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try:
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@@ -187,57 +196,70 @@ async def streaming_chat(ws: WebSocket,db=Depends(get_db)):
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llm_text = ""
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logger.debug("开始进行ASR识别")
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while len(asr_results)==0:
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chunk = json.loads(await ws.receive_text())
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chunk = json.loads(await asyncio.wait_for(ws.receive_text(),timeout=2))
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if assistant is None:
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assistant = db.query(Assistant).filter(Assistant.id == chunk['meta_info']['session_id']).first()
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with get_db_context() as db: #使用with语句获取数据库连接，自动关闭数据库连接
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assistant = db.query(Assistant).filter(Assistant.id == chunk['meta_info']['session_id']).first()
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if assistant is None:
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raise SessionNotFoundError()
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user_info = json.loads(assistant.user_info)
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if not agent:
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agent = Agent(asr_type=user_info['asr_type'], llm_type=user_info['llm_type'], tts_type=user_info['tts_type'])
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agent.init_recorder(assistant.user_id)
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chunk["audio"] = agent.user_audio_process(chunk["audio"], db)
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asr_results = await agent.stream_recognize(chunk, db)
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chunk["audio"] = agent.user_audio_process(chunk["audio"])
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asr_results = await agent.stream_recognize(chunk)
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kid_text = asr_results[0]['text'] #asr结果的[0]默认为孩子(主要用户)的asr结果
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logger.debug(f"ASR识别成功，识别结果为：{kid_text}")
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prompt = agent.prompt_process(asr_results, db)
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prompt = agent.prompt_process(asr_results)
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agent.recorder.input_text = prompt
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logger.debug("开始调用大模型")
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llm_frames = await agent.chat(assistant, prompt, db)
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llm_frames = await agent.chat(assistant, prompt)
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async for llm_frame in llm_frames:
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resp_msgs = agent.llm_msg_process(llm_frame, db)
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resp_msgs = agent.llm_msg_process(llm_frame)
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for resp_msg in resp_msgs:
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llm_text += resp_msg
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tts_audio = agent.synthetize(assistant, resp_msg, db)
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agent.tts_audio_process(tts_audio, db)
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tts_start_time = time.time()
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tts_audio = agent.synthetize(assistant, resp_msg)
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tts_end_time = time.time()
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logger.debug(f"TTS生成音频耗时：{tts_end_time-tts_start_time}s")
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agent.tts_audio_process(tts_audio)
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await ws.send_bytes(agent.encode(resp_msg, tts_audio))
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logger.debug(f'websocket返回：{resp_msg}')
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logger.debug(f"大模型返回结束，返回结果为：{llm_text}")
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await ws.send_text(json.dumps({"type": "close", "code": 200, "msg": ""}, ensure_ascii=False))
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logger.debug("结束帧发送完毕")
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assistant.messages = update_messages(assistant.messages, kid_text ,llm_text)
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db.commit()
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update_messages(assistant, kid_text ,llm_text)
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logger.debug("聊天更新成功")
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agent.recorder.output_text = llm_text
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agent.save()
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logger.debug("音频保存成功")
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except EnterSlienceMode:
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tts_audio = agent.synthetize(assistant, "已进入沉默模式", db)
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tts_audio = agent.synthetize(assistant, "已进入沉默模式")
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await ws.send_bytes(agent.encode("已进入沉默模式", tts_audio))
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await ws.send_text(json.dumps({"type":"info","code":201,"msg":"进入沉默模式"}, ensure_ascii=False))
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except SlienceMode:
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await ws.send_text(json.dumps({"type":"info","code":201,"msg":"处于沉默模式"}, ensure_ascii=False))
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logger.debug("进入沉默模式")
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except AsrResultNoneError:
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await ws.send_text(json.dumps({"type":"error","code":501,"msg":"asr结果为空"}, ensure_ascii=False))
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logger.error("ASR结果为空")
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except AbnormalLLMFrame as e:
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await ws.send_text(json.dumps({"type":"error","code":502,"msg":str(e)}, ensure_ascii=False))
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logger.error(f"LLM模型返回异常，错误信息：{str(e)}")
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except SideNoiseError as e:
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await ws.send_text(json.dumps({"type":"error","code":503,"msg":str(e)}, ensure_ascii=False))
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await ws.send_text(json.dumps({"type":"error","code":503,"msg":"检测为噪声"}, ensure_ascii=False))
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logger.debug("检测为噪声")
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except SessionNotFoundError:
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await ws.send_text(json.dumps({"type":"error","code":504,"msg":"session不存在"}, ensure_ascii=False))
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logger.error("session不存在")
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except UnknownVolcEngineModelError:
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await ws.send_text(json.dumps({"type":"error","code":505,"msg":"未知的火山引擎模型"}, ensure_ascii=False))
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logger.error("未知的火山引擎模型")
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except LlmResultNoneError:
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await ws.send_text(json.dumps({"type":"error","code":506,"msg":"llm结果返回为空"}, ensure_ascii=False))
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logger.error("LLM结果返回为空")
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except asyncio.TimeoutError:
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await ws.send_text(json.dumps({"type":"error","code":507,"msg":"接收超时"}, ensure_ascii=False))
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logger.error("接收超时")
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logger.debug("WebSocket连接断开")
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logger.debug("")
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await ws.close()
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# --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
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