diff --git a/app/controllers/chat_controller.py b/app/controllers/chat_controller.py
index ff54226..2c42bfb 100644
--- a/app/controllers/chat_controller.py
+++ b/app/controllers/chat_controller.py
@@ -10,7 +10,7 @@ from config import get_config
 import uuid
 import json
 import asyncio
-import requests
+import aiohttp
 
 # 依赖注入获取logger
 logger = get_logger()
@@ -266,35 +266,36 @@ 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) #调用大模型
     except Exception as e:
-        logger.error(f"llm调用发生错误: {str(e)}")
+        logger.error(f"编辑http请求时发生错误: {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)    #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)) #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)  #返回音频数据
-                    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  #重置is_end标志位
-                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 = ""
+        async with aiohttp.ClientSession() as client:
+            async with client.post(Config.MINIMAX_LLM.URL, headers=headers, data=payload) as response:  #发送大模型请求
+                async for chunk in response.content.iter_any():
+                    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)    #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)) #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)  #返回音频数据
+                            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  #重置is_end标志位
+                        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 = ""
     except Exception as e:
         logger.error(f"处理llm返回结果发生错误: {str(e)}")
     chat_finished_event.set()
@@ -418,34 +419,35 @@ async def scl_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)
-            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)
-                for sentence in sentences:
-                    if response_type == RESPONSE_TEXT:
-                        logger.debug(f"websocket返回: {sentence}")    
-                        response_message = {"type": "text", "code":200, "msg": sentence}
-                        await ws.send_text(json.dumps(response_message, ensure_ascii=False))
-                    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_text(json.dumps(response_message, ensure_ascii=False))
-                        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
+            async with aiohttp.ClientSession() as client:
+                async with client.post(Config.MINIMAX_LLM.URL, headers=headers, data=payload) as response:  #发送大模型请求
+                    async for chunk in response.content.iter_any():
+                        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)
+                        for sentence in sentences:
+                            if response_type == RESPONSE_TEXT:
+                                logger.debug(f"websocket返回: {sentence}")    
+                                response_message = {"type": "text", "code":200, "msg": sentence}
+                                await ws.send_text(json.dumps(response_message, ensure_ascii=False))
+                            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_text(json.dumps(response_message, ensure_ascii=False))
+                                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
 
-                    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 = ""
+                            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 = ""
         except asyncio.TimeoutError:
             continue
         except Exception as e:
@@ -578,29 +580,30 @@ async def voice_call_llm_handler(ws,session_id,llm_info,tts_info,db,redis,asr_re
                 '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)
-            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)
-                for sentence in sentences:
-                    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)
-                    text_response = {"type": "llm_text", "code": 200, "msg": sentence}
-                    await ws.send_bytes(audio) #返回音频二进制流数据
-                    await ws.send_text(json.dumps(text_response, ensure_ascii=False)) #返回文本数据
-                    logger.debug(f"llm返回结果: {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
+            async with aiohttp.ClientSession() as client:
+                async with client.post(Config.MINIMAX_LLM.URL, headers=headers, data=payload) as response:  #发送大模型请求
+                    async for chunk in response.content.iter_any():
+                        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)
+                        for sentence in sentences:
+                            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)
+                            text_response = {"type": "llm_text", "code": 200, "msg": sentence}
+                            await ws.send_bytes(audio) #返回音频二进制流数据
+                            await ws.send_text(json.dumps(text_response, ensure_ascii=False)) #返回文本数据
+                            logger.debug(f"llm返回结果: {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
 
-                    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 = ""
+                            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 = ""
         except asyncio.TimeoutError:
             continue
         except Exception as e: