update: 修改requests为aiohttp，实现异步http请求
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b26f3192bc
commit
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@ -10,7 +10,7 @@ from config import get_config
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import uuid
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import json
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import asyncio
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import requests
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import aiohttp
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# 依赖注入获取logger
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logger = get_logger()
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@ -266,35 +266,36 @@ async def sct_llm_handler(ws,session_id,response_type,llm_info,tts_info,db,redis
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'Authorization': f"Bearer {Config.MINIMAX_LLM.API_KEY}",
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'Content-Type': 'application/json'
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}
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response = requests.post(Config.MINIMAX_LLM.URL, headers=headers, data=payload,stream=True) #调用大模型
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except Exception as e:
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logger.error(f"llm调用发生错误: {str(e)}")
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logger.error(f"编辑http请求时发生错误: {str(e)}")
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try:
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for chunk in response.iter_lines():
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chunk_data = parseChunkDelta(chunk)
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is_end = chunk_data == "end"
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if not is_end:
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llm_response += chunk_data
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sentences,current_sentence,is_first = split_string_with_punctuation(current_sentence,chunk_data,is_first,is_end) #断句
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for sentence in sentences:
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if response_type == RESPONSE_TEXT:
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response_message = {"type": "text", "code":200, "msg": sentence}
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await ws.send_text(json.dumps(response_message, ensure_ascii=False)) #返回文本信息
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elif response_type == RESPONSE_AUDIO:
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sr,audio = tts.synthesize(sentence, tts_info["speaker_id"], tts_info["language"], tts_info["noise_scale"], tts_info["noise_scale_w"], tts_info["length_scale"],return_bytes=True)
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response_message = {"type": "text", "code":200, "msg": sentence}
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await ws.send_bytes(audio) #返回音频数据
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await ws.send_text(json.dumps(response_message, ensure_ascii=False)) #返回文本信息
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logger.debug(f"websocket返回: {sentence}")
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if is_end:
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logger.debug(f"llm返回结果: {llm_response}")
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await ws.send_text(json.dumps({"type": "end", "code": 200, "msg": ""}, ensure_ascii=False))
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is_end = False #重置is_end标志位
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messages.append({'role': 'assistant', "content": llm_response})
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session_content["messages"] = json.dumps(messages,ensure_ascii=False) #更新对话
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redis.set(session_id,json.dumps(session_content,ensure_ascii=False)) #更新session
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is_first = True
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llm_response = ""
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async with aiohttp.ClientSession() as client:
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async with client.post(Config.MINIMAX_LLM.URL, headers=headers, data=payload) as response: #发送大模型请求
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async for chunk in response.content.iter_any():
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chunk_data = parseChunkDelta(chunk)
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is_end = chunk_data == "end"
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if not is_end:
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llm_response += chunk_data
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sentences,current_sentence,is_first = split_string_with_punctuation(current_sentence,chunk_data,is_first,is_end) #断句
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for sentence in sentences:
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if response_type == RESPONSE_TEXT:
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response_message = {"type": "text", "code":200, "msg": sentence}
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await ws.send_text(json.dumps(response_message, ensure_ascii=False)) #返回文本信息
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elif response_type == RESPONSE_AUDIO:
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sr,audio = tts.synthesize(sentence, tts_info["speaker_id"], tts_info["language"], tts_info["noise_scale"], tts_info["noise_scale_w"], tts_info["length_scale"],return_bytes=True)
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response_message = {"type": "text", "code":200, "msg": sentence}
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await ws.send_bytes(audio) #返回音频数据
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await ws.send_text(json.dumps(response_message, ensure_ascii=False)) #返回文本信息
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logger.debug(f"websocket返回: {sentence}")
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if is_end:
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logger.debug(f"llm返回结果: {llm_response}")
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await ws.send_text(json.dumps({"type": "end", "code": 200, "msg": ""}, ensure_ascii=False))
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is_end = False #重置is_end标志位
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messages.append({'role': 'assistant', "content": llm_response})
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session_content["messages"] = json.dumps(messages,ensure_ascii=False) #更新对话
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redis.set(session_id,json.dumps(session_content,ensure_ascii=False)) #更新session
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is_first = True
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llm_response = ""
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except Exception as e:
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logger.error(f"处理llm返回结果发生错误: {str(e)}")
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chat_finished_event.set()
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@ -418,34 +419,35 @@ async def scl_llm_handler(ws,session_id,response_type,llm_info,tts_info,db,redis
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'Authorization': f"Bearer {Config.MINIMAX_LLM.API_KEY}",
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'Content-Type': 'application/json'
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}
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response = requests.post(Config.MINIMAX_LLM.URL, headers=headers, data=payload,stream=True)
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for chunk in response.iter_lines():
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chunk_data = parseChunkDelta(chunk)
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is_end = chunk_data == "end"
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if not is_end:
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llm_response += chunk_data
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sentences,current_sentence,is_first = split_string_with_punctuation(current_sentence,chunk_data,is_first,is_end)
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for sentence in sentences:
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if response_type == RESPONSE_TEXT:
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logger.debug(f"websocket返回: {sentence}")
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response_message = {"type": "text", "code":200, "msg": sentence}
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await ws.send_text(json.dumps(response_message, ensure_ascii=False))
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elif response_type == RESPONSE_AUDIO:
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sr,audio = tts.synthesize(sentence, tts_info["speaker_id"], tts_info["language"], tts_info["noise_scale"], tts_info["noise_scale_w"], tts_info["length_scale"],return_bytes=True)
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response_message = {"type": "text", "code":200, "msg": sentence}
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await ws.send_bytes(audio)
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await ws.send_text(json.dumps(response_message, ensure_ascii=False))
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logger.debug(f"websocket返回: {sentence}")
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if is_end:
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logger.debug(f"llm返回结果: {llm_response}")
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await ws.send_text(json.dumps({"type": "end", "code": 200, "msg": ""}, ensure_ascii=False))
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is_end = False
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async with aiohttp.ClientSession() as client:
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async with client.post(Config.MINIMAX_LLM.URL, headers=headers, data=payload) as response: #发送大模型请求
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async for chunk in response.content.iter_any():
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chunk_data = parseChunkDelta(chunk)
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is_end = chunk_data == "end"
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if not is_end:
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llm_response += chunk_data
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sentences,current_sentence,is_first = split_string_with_punctuation(current_sentence,chunk_data,is_first,is_end)
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for sentence in sentences:
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if response_type == RESPONSE_TEXT:
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logger.debug(f"websocket返回: {sentence}")
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response_message = {"type": "text", "code":200, "msg": sentence}
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await ws.send_text(json.dumps(response_message, ensure_ascii=False))
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elif response_type == RESPONSE_AUDIO:
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sr,audio = tts.synthesize(sentence, tts_info["speaker_id"], tts_info["language"], tts_info["noise_scale"], tts_info["noise_scale_w"], tts_info["length_scale"],return_bytes=True)
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response_message = {"type": "text", "code":200, "msg": sentence}
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await ws.send_bytes(audio)
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await ws.send_text(json.dumps(response_message, ensure_ascii=False))
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logger.debug(f"websocket返回: {sentence}")
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if is_end:
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logger.debug(f"llm返回结果: {llm_response}")
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await ws.send_text(json.dumps({"type": "end", "code": 200, "msg": ""}, ensure_ascii=False))
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is_end = False
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messages.append({'role': 'assistant', "content": llm_response})
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session_content["messages"] = json.dumps(messages,ensure_ascii=False) #更新对话
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redis.set(session_id,json.dumps(session_content,ensure_ascii=False)) #更新session
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is_first = True
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llm_response = ""
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messages.append({'role': 'assistant', "content": llm_response})
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session_content["messages"] = json.dumps(messages,ensure_ascii=False) #更新对话
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redis.set(session_id,json.dumps(session_content,ensure_ascii=False)) #更新session
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is_first = True
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llm_response = ""
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except asyncio.TimeoutError:
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continue
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except Exception as e:
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@ -578,29 +580,30 @@ async def voice_call_llm_handler(ws,session_id,llm_info,tts_info,db,redis,asr_re
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'Authorization': f"Bearer {Config.MINIMAX_LLM.API_KEY}",
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'Content-Type': 'application/json'
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}
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response = requests.post(Config.MINIMAX_LLM.URL, headers=headers, data=payload,stream=True)
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for chunk in response.iter_lines():
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chunk_data = parseChunkDelta(chunk)
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is_end = chunk_data == "end"
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if not is_end:
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llm_response += chunk_data
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sentences,current_sentence,is_first = split_string_with_punctuation(current_sentence,chunk_data,is_first,is_end)
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for sentence in sentences:
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sr,audio = tts.synthesize(sentence, tts_info["language"], tts_info["speaker_id"], tts_info["noise_scale"], tts_info["noise_scale_w"], tts_info["length_scale"], return_bytes=True)
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text_response = {"type": "llm_text", "code": 200, "msg": sentence}
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await ws.send_bytes(audio) #返回音频二进制流数据
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await ws.send_text(json.dumps(text_response, ensure_ascii=False)) #返回文本数据
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logger.debug(f"llm返回结果: {sentence}")
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if is_end:
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logger.debug(f"llm返回结果: {llm_response}")
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await ws.send_text(json.dumps({"type": "end", "code": 200, "msg": ""}, ensure_ascii=False))
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is_end = False
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async with aiohttp.ClientSession() as client:
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async with client.post(Config.MINIMAX_LLM.URL, headers=headers, data=payload) as response: #发送大模型请求
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async for chunk in response.content.iter_any():
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chunk_data = parseChunkDelta(chunk)
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is_end = chunk_data == "end"
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if not is_end:
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llm_response += chunk_data
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sentences,current_sentence,is_first = split_string_with_punctuation(current_sentence,chunk_data,is_first,is_end)
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for sentence in sentences:
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sr,audio = tts.synthesize(sentence, tts_info["language"], tts_info["speaker_id"], tts_info["noise_scale"], tts_info["noise_scale_w"], tts_info["length_scale"], return_bytes=True)
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text_response = {"type": "llm_text", "code": 200, "msg": sentence}
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await ws.send_bytes(audio) #返回音频二进制流数据
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await ws.send_text(json.dumps(text_response, ensure_ascii=False)) #返回文本数据
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logger.debug(f"llm返回结果: {sentence}")
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if is_end:
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logger.debug(f"llm返回结果: {llm_response}")
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await ws.send_text(json.dumps({"type": "end", "code": 200, "msg": ""}, ensure_ascii=False))
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is_end = False
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messages.append({'role': 'assistant', "content": llm_response})
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session_content["messages"] = json.dumps(messages,ensure_ascii=False) #更新对话
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redis.set(session_id,json.dumps(session_content,ensure_ascii=False)) #更新session
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is_first = True
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llm_response = ""
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messages.append({'role': 'assistant', "content": llm_response})
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session_content["messages"] = json.dumps(messages,ensure_ascii=False) #更新对话
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redis.set(session_id,json.dumps(session_content,ensure_ascii=False)) #更新session
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is_first = True
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llm_response = ""
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except asyncio.TimeoutError:
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continue
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except Exception as e:
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