对语音接口进行了简略的异常处理

app/controllers/chat.py

@@ -63,6 +63,7 @@ def parseChunkDelta(chunk):
 
 #断句函数
 def split_string_with_punctuation(current_sentence,text,is_first,is_end):
+    try:
         result = []
         if is_end:
             if current_sentence:
@@ -79,6 +80,8 @@ def split_string_with_punctuation(current_sentence,text,is_first,is_end):
                 result.append(current_sentence)
                 current_sentence = ''
         return result, current_sentence, is_first
+    except Exception as e:
+        logger.error(f"断句时出现错误: {str(e)}")
 
 #vad预处理
 def vad_preprocess(audio):
@@ -203,12 +206,15 @@ async def sct_user_input_handler(ws,user_input_q,llm_input_q,future_session_id,f
                     break
             await user_input_q.put(sct_data_json['audio'])
     except KeyError as ke:
-        if sct_data_json['state'] == 1 and sct_data_json['method'] == 'heartbeat':
+        if 'state' in sct_data_json and 'method' in sct_data_json:
             logger.debug("收到心跳包")
+    except Exception as e:
+        logger.error(f"用户输入处理函数发生错误: {str(e)}")
 
 #语音识别
 async def sct_asr_handler(user_input_q,llm_input_q,user_input_finish_event):
     logger.debug("语音识别函数启动")
+    try:
         current_message = ""
         while not (user_input_finish_event.is_set() and user_input_q.empty()):
             audio_data = await user_input_q.get()
@@ -217,11 +223,14 @@ async def sct_asr_handler(user_input_q,llm_input_q,user_input_finish_event):
         asr_result = asr.streaming_recognize(b'',is_end=True)
         current_message += ''.join(asr_result['text'])
         await llm_input_q.put(current_message)
+    except Exception as e:
+        logger.error(f"语音识别函数发生错误: {str(e)}")
     logger.debug(f"接收到用户消息: {current_message}")
 
 #大模型调用
 async def sct_llm_handler(ws,session_id,response_type,llm_info,tts_info,db,redis,llm_input_q,chat_finished_event):
     logger.debug("llm调用函数启动")
+    try:
         llm_response = ""
         current_sentence = ""
         is_first = True
@@ -242,28 +251,30 @@ async def sct_llm_handler(ws,session_id,response_type,llm_info,tts_info,db,redis
             'Authorization': f"Bearer {Config.MINIMAX_LLM.API_KEY}",
             'Content-Type': 'application/json'
         }
-    response = requests.post(Config.MINIMAX_LLM.URL, headers=headers, data=payload,stream=True)
+        response = requests.post(Config.MINIMAX_LLM.URL, headers=headers, data=payload,stream=True) #调用大模型
+    except Exception as e:
+        logger.error(f"llm调用发生错误: {str(e)}")
+    try:
         for chunk in response.iter_lines():
             chunk_data = parseChunkDelta(chunk)
             is_end = chunk_data == "end"
             if not is_end:
                 llm_response += chunk_data
-        sentences,current_sentence,is_first = split_string_with_punctuation(current_sentence,chunk_data,is_first,is_end)
+            sentences,current_sentence,is_first = split_string_with_punctuation(current_sentence,chunk_data,is_first,is_end)    #断句
             for sentence in sentences:
                 if response_type == RESPONSE_TEXT:
                     response_message = {"type": "text", "code":200, "msg": sentence}
-                await ws.send_text(json.dumps(response_message, ensure_ascii=False))
+                    await ws.send_text(json.dumps(response_message, ensure_ascii=False)) #返回文本信息
                 elif response_type == RESPONSE_AUDIO:
                     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)
                     response_message = {"type": "text", "code":200, "msg": sentence}
-                await ws.send_bytes(audio)
+                    await ws.send_bytes(audio)  #返回音频数据
-                await ws.send_text(json.dumps(response_message, ensure_ascii=False))
+                    await ws.send_text(json.dumps(response_message, ensure_ascii=False))    #返回文本信息
                 logger.debug(f"websocket返回: {sentence}")     
             if is_end:
                 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
+                is_end = False  #重置is_end标志位
-
                 session_content = get_session_content(session_id,redis,db)
                 messages = json.loads(session_content["messages"])
                 messages.append({'role': 'assistant', "content": llm_response})
@@ -271,6 +282,8 @@ 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 = ""
+    except Exception as e:
+        logger.error(f"处理llm返回结果发生错误: {str(e)}")
     chat_finished_event.set()
 
 async def streaming_chat_temporary_handler(ws: WebSocket, db, redis):
@@ -334,8 +347,9 @@ async def scl_user_input_handler(ws,user_input_q,llm_input_q,future_session_id,f
                 continue
         except asyncio.TimeoutError:
             continue
-        
+        except Exception as e:
-
+            logger.error(f"用户输入处理函数发生错误: {str(e)}")
+            break
         
 #语音识别
 async def scl_asr_handler(user_input_q,llm_input_q,input_finished_event,asr_finished_event):
@@ -354,6 +368,9 @@ async def scl_asr_handler(user_input_q,llm_input_q,input_finished_event,asr_fini
                 current_message += ''.join(asr_result['text'])
         except asyncio.TimeoutError:
             continue
+        except Exception as e:
+            logger.error(f"语音识别函数发生错误: {str(e)}")
+            break
     asr_finished_event.set()
 
 #大模型调用
@@ -413,6 +430,9 @@ async def scl_llm_handler(ws,session_id,response_type,llm_info,tts_info,db,redis
                     llm_response = ""
         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
     chat_finished_event.set()
 
 async def streaming_chat_lasting_handler(ws,db,redis):
@@ -466,9 +486,13 @@ async def voice_call_audio_producer(ws,audio_q,future,input_finished_event):
                     vad_frame,audio_data = vad_preprocess(audio_data)
                     await audio_q.put(vad_frame) #将音频数据存入audio_q
         except KeyError as ke:
+            if 'state' in voice_call_data_json and 'method' in voice_call_data_json:
                 logger.info(f"收到心跳包")
         except asyncio.TimeoutError:
             continue
+        except Exception as e:
+            logger.error(f"音频数据生产函数发生错误: {str(e)}")
+            break
 
 
 #音频数据消费函数
@@ -498,6 +522,9 @@ async def voice_call_audio_consumer(ws,audio_q,asr_result_q,input_finished_event
                     vad_count = 0
         except asyncio.TimeoutError:
             continue
+        except Exception as e:
+            logger.error(f"音频数据消费者函数发生错误: {str(e)}")
+            break
     asr_finished_event.set()
 
 #asr结果消费以及llm返回生产函数
@@ -553,6 +580,9 @@ async def voice_call_llm_handler(ws,session_id,llm_info,tts_info,db,redis,asr_re
                     llm_response = ""
         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
     voice_call_end_event.set()