feature: 集成bert_vits

main.py

@@ -122,7 +122,16 @@ async def update_assistant_deatil_params(id: str,request: update_assistant_deati
         llm_info['temperature'] = request.temperature
         tts_info['speaker_id'] = request.speaker_id
         tts_info['length_scale'] = request.length_scale
+        tts_info['language'] = request.language
+        tts_info['style_text'] = request.style_text
+        tts_info['style_weight'] = request.style_weight
+        tts_info['sdp_ratio'] = 0.5
+        tts_info['opt_cut_by_send'] = False
+        tts_info['interval_between_para'] = 1.0
+        tts_info['interval_between_sent'] = 0.2
+        tts_info['en_ratio'] = 1.0
         user_info['llm_type'] = request.platform
+        user_info['tts_type'] = request.tts_engine
         assistant.llm_info = json.dumps(llm_info, ensure_ascii=False)
         assistant.tts_info = json.dumps(tts_info, ensure_ascii=False)
         assistant.user_info = json.dumps(user_info, ensure_ascii=False)
@@ -227,15 +236,7 @@ async def streaming_chat(ws: WebSocket):
         agent.recorder.input_text = prompt
         logger.debug("开始调用大模型")
         llm_frames = await agent.chat(assistant, prompt)
-        
-        start_time = time.time()
-        is_first_response = True
-        
         for llm_frame in llm_frames:
-            if is_first_response:
-                end_time = time.time()
-                logger.debug(f"第一帧返回耗时：{round(end_time-start_time,3)}s")
-                is_first_response = False
             resp_msgs = agent.llm_msg_process(llm_frame)
             for resp_msg in resp_msgs: 
                 llm_text += resp_msg