diff --git a/dsLightRag/Routes/XueBanRoute.py b/dsLightRag/Routes/XueBanRoute.py
index 0ef0f98a..fc027b66 100644
--- a/dsLightRag/Routes/XueBanRoute.py
+++ b/dsLightRag/Routes/XueBanRoute.py
@@ -18,95 +18,6 @@ router = APIRouter(prefix="/api", tags=["学伴"])
 # 配置日志
 logger = logging.getLogger(__name__)
 
-# 保留原有的HTTP接口，用于向后兼容
-@router.post("/xueban/upload-audio")
-async def upload_audio(file: UploadFile = File(...)):
-    """
-    上传音频文件并进行ASR处理 - 原有接口，用于向后兼容
-    - 参数: file - 音频文件
-    - 返回: JSON包含识别结果
-    """
-    try:
-        # 记录日志
-        logger.info(f"接收到音频文件: {file.filename}")
-
-        # 保存临时文件
-        timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
-        file_ext = os.path.splitext(file.filename)[1]
-        temp_file_name = f"temp_audio_{timestamp}{file_ext}"
-        temp_file_path = os.path.join(tempfile.gettempdir(), temp_file_name)
-
-        with open(temp_file_path, "wb") as f:
-            content = await file.read()
-            f.write(content)
-
-        logger.info(f"音频文件已保存至临时目录: {temp_file_path}")
-
-        # 调用ASR服务进行处理
-        asr_result = await process_asr(temp_file_path)
-
-        # 删除临时文件
-        os.remove(temp_file_path)
-        logger.info(f"临时文件已删除: {temp_file_path}")
-
-        # 使用大模型生成反馈
-        logger.info(f"使用大模型生成反馈，输入文本: {asr_result['text']}")
-        response_generator = get_xueban_response_async(asr_result['text'], stream=False)
-        feedback_text = ""
-        async for chunk in response_generator:
-            feedback_text += chunk
-        logger.info(f"大模型反馈生成完成: {feedback_text}")
-
-        # 使用流式TTS生成语音
-        import io
-        audio_chunks = []
-        
-        # 定义音频回调函数，收集音频块
-        def audio_callback(audio_chunk):
-            audio_chunks.append(audio_chunk)
-        
-        # 获取LLM流式输出并断句
-        text_stream = stream_and_split_text(asr_result['text'])
-        
-        # 初始化TTS处理器
-        tts = StreamingVolcanoTTS(max_concurrency=2)
-        
-        # 流式处理文本并生成音频
-        await tts.synthesize_stream(text_stream, audio_callback)
-        
-        # 合并所有音频块
-        if audio_chunks:
-            tts_temp_file = os.path.join(tempfile.gettempdir(), f"tts_{timestamp}.mp3")
-            with open(tts_temp_file, "wb") as f:
-                for chunk in audio_chunks:
-                    f.write(chunk)
-            logger.info(f"TTS语音合成成功，文件保存至: {tts_temp_file}")
-        else:
-            raise Exception("TTS语音合成失败，未生成音频数据")
-
-        # 上传TTS音频文件到OBS
-        tts_audio_url = upload_file_to_obs(tts_temp_file)
-        os.remove(tts_temp_file)  # 删除临时TTS文件
-        logger.info(f"TTS文件已上传至OBS: {tts_audio_url}")
-
-        # 返回结果，包含ASR文本和TTS音频URL
-        return JSONResponse(content={
-            "success": True,
-            "message": "音频处理和语音反馈生成成功",
-            "data": {
-                "asr_text": asr_result['text'],
-                "feedback_text": feedback_text,
-                "audio_url": tts_audio_url
-            }
-        })
-
-    except Exception as e:
-        logger.error(f"音频处理失败: {str(e)}")
-        return JSONResponse(content={
-            "success": False,
-            "message": f"音频处理失败: {str(e)}"
-        }, status_code=500)
-
 # 新增WebSocket接口，用于流式处理
 @router.websocket("/xueban/streaming-chat")
 async def streaming_chat(websocket: WebSocket):
diff --git a/dsLightRag/Routes/__pycache__/XueBanRoute.cpython-310.pyc b/dsLightRag/Routes/__pycache__/XueBanRoute.cpython-310.pyc
index b319f121..2125f9d3 100644
Binary files a/dsLightRag/Routes/__pycache__/XueBanRoute.cpython-310.pyc and b/dsLightRag/Routes/__pycache__/XueBanRoute.cpython-310.pyc differ