diff --git a/app/controllers/chat_controller.py b/app/controllers/chat_controller.py index 6520d4a..8a7c51c 100644 --- a/app/controllers/chat_controller.py +++ b/app/controllers/chat_controller.py @@ -54,7 +54,7 @@ def get_session_content(session_id,redis,db): def parseChunkDelta(chunk): try: if chunk == b"": - return "" + return 1,"" decoded_data = chunk.decode('utf-8') parsed_data = json.loads(decoded_data[6:]) if 'delta' in parsed_data['choices'][0]: @@ -63,11 +63,11 @@ def parseChunkDelta(chunk): else: return parsed_data['usage']['total_tokens'] , "" except KeyError: - logger.error(f"error chunk: {chunk}") - return "" + logger.error(f"error chunk: {decoded_data}") + return 1,"" except json.JSONDecodeError: - logger.error(f"error chunk: {chunk}") - return "" + logger.error(f"error chunk: {decoded_data}") + return 1,"" #断句函数 def split_string_with_punctuation(current_sentence,text,is_first,is_end): @@ -318,15 +318,15 @@ async def sct_llm_handler(ws,session_id,response_type,llm_info,tts_info,db,redis redis.set(session_id,json.dumps(session_content,ensure_ascii=False)) #更新session is_first = True llm_response = "" - if is_end and token_count > summarizer.max_token * 0.6: #如果llm返回的token数大于60%的最大token数，则进行文本摘要 + if token_count > summarizer.max_token * 0.7: #如果llm返回的token数大于60%的最大token数，则进行文本摘要 system_prompt = messages[0]['content'] summary = await summarizer.summarize(messages) events = user_info['events'] events.append(summary['event']) - session_content['messages'] = [{'role':'system','content':system_prompt}] - session_content['user_info'] = json.dumps({'character': summary['character'], 'events': json.dumps(events,ensure_ascii=False)}, ensure_ascii=False) + session_content['messages'] = json.dumps([{'role':'system','content':system_prompt}],ensure_ascii=False) + session_content['user_info'] = json.dumps({'character': summary['character'], 'events': events}, ensure_ascii=False) redis.set(session_id,json.dumps(session_content,ensure_ascii=False)) - logger.debug(f"文本摘要后的session: {session_content}") + logger.debug(f"总结后session_content: {session_content}") except Exception as e: logger.error(f"处理llm返回结果发生错误: {str(e)}") chat_finished_event.set() @@ -418,11 +418,10 @@ async def scl_asr_handler(session_id,user_input_q,llm_input_q,input_finished_eve if not isinstance(emotion_dict, str): max_index = emotion_dict['scores'].index(max(emotion_dict['scores'])) current_message = f"{current_message}当前说话人的情绪：{emotion_dict['labels'][max_index]}" - print(current_message) await llm_input_q.put(current_message) + logger.debug(f"接收到用户消息: {current_message}") current_message = "" audio = "" - logger.debug(f"接收到用户消息: {current_message}") else: asr_result = asr.streaming_recognize(session_id,aduio_frame['audio']) audio += aduio_frame['audio'] @@ -446,6 +445,7 @@ async def scl_llm_handler(ws,session_id,response_type,llm_info,tts_info,db,redis try: session_content = get_session_content(session_id,redis,db) messages = json.loads(session_content["messages"]) + user_info = json.loads(session_content["user_info"]) current_message = await asyncio.wait_for(llm_input_q.get(),timeout=3) messages.append({'role': 'user', "content": current_message}) payload = json.dumps({ @@ -483,17 +483,25 @@ async def scl_llm_handler(ws,session_id,response_type,llm_info,tts_info,db,redis logger.debug(f"llm返回结果: {llm_response}") await ws.send_text(json.dumps({"type": "end", "code": 200, "msg": ""}, ensure_ascii=False)) is_end = False - messages.append({'role': 'assistant', "content": llm_response}) session_content["messages"] = json.dumps(messages,ensure_ascii=False) #更新对话 redis.set(session_id,json.dumps(session_content,ensure_ascii=False)) #更新session is_first = True llm_response = "" + if token_count > summarizer.max_token * 0.7: #如果llm返回的token数大于60%的最大token数，则进行文本摘要 + system_prompt = messages[0]['content'] + summary = await summarizer.summarize(messages) + events = user_info['events'] + events.append(summary['event']) + session_content['messages'] = json.dumps([{'role':'system','content':system_prompt}],ensure_ascii=False) + session_content['user_info'] = json.dumps({'character': summary['character'], 'events': events}, ensure_ascii=False) + redis.set(session_id,json.dumps(session_content,ensure_ascii=False)) + logger.debug(f"总结后session_content: {session_content}") except asyncio.TimeoutError: continue - except Exception as e: - logger.error(f"处理llm返回结果发生错误: {str(e)}") - break + # except Exception as e: + # logger.error(f"处理llm返回结果发生错误: {str(e)}") + # break chat_finished_event.set() async def streaming_chat_lasting_handler(ws,db,redis): @@ -615,6 +623,7 @@ async def voice_call_llm_handler(ws,session_id,llm_info,tts_info,db,redis,asr_re try: session_content = get_session_content(session_id,redis,db) messages = json.loads(session_content["messages"]) + user_info = json.loads(session_content["user_info"]) current_message = await asyncio.wait_for(asr_result_q.get(),timeout=3) messages.append({'role': 'user', "content": current_message}) payload = json.dumps({ @@ -648,12 +657,20 @@ async def voice_call_llm_handler(ws,session_id,llm_info,tts_info,db,redis,asr_re logger.debug(f"llm返回结果: {llm_response}") await ws.send_text(json.dumps({"type": "end", "code": 200, "msg": ""}, ensure_ascii=False)) is_end = False - messages.append({'role': 'assistant', "content": llm_response}) session_content["messages"] = json.dumps(messages,ensure_ascii=False) #更新对话 redis.set(session_id,json.dumps(session_content,ensure_ascii=False)) #更新session is_first = True llm_response = "" + if token_count > summarizer.max_token * 0.7: #如果llm返回的token数大于60%的最大token数，则进行文本摘要 + system_prompt = messages[0]['content'] + summary = await summarizer.summarize(messages) + events = user_info['events'] + events.append(summary['event']) + session_content['messages'] = json.dumps([{'role':'system','content':system_prompt}],ensure_ascii=False) + session_content['user_info'] = json.dumps({'character': summary['character'], 'events': events}, ensure_ascii=False) + redis.set(session_id,json.dumps(session_content,ensure_ascii=False)) + logger.debug(f"总结后session_content: {session_content}") except asyncio.TimeoutError: continue except Exception as e: