'commit'

dsLightRag/Routes/XueBanRoute.py

@@ -187,16 +187,37 @@ async def streaming_chat(websocket: WebSocket):
                 logger.error(f"发送音频块失败: {str(e)}")
                 raise
         
-        # 获取LLM流式输出并断句
-        logger.info("开始LLM处理和TTS合成...")
+        # 获取学伴响应内容（包含题目信息）
+        logger.info("获取学伴响应内容...")
+        llm_chunks = []
+        async for chunk in get_xueban_response_async(asr_result['text'], stream=True):
+            llm_chunks.append(chunk)
+        full_llm_response = ''.join(llm_chunks)
+        logger.info(f"学伴响应内容: {full_llm_response}")
+        
+        # 定义音频回调函数，将音频块发送给前端
+        async def audio_callback(audio_chunk):
+            logger.info(f"发送音频块，大小: {len(audio_chunk)}")
+            try:
+                await websocket.send_bytes(audio_chunk)
+                logger.info("音频块发送成功")
+            except Exception as e:
+                logger.error(f"发送音频块失败: {str(e)}")
+                raise
+        
+        # 实时获取LLM流式输出并处理
+        logger.info("开始LLM流式处理和TTS合成...")
         try:
-            text_stream = stream_and_split_text(asr_result['text'])
+            # 直接将LLM流式响应接入TTS
+            llm_stream = get_xueban_response_async(asr_result['text'], stream=True)
+            text_stream = stream_and_split_text(llm_stream)  # 异步函数调用
             
             # 初始化TTS处理器
-            tts = StreamingVolcanoTTS(max_concurrency=2)
+            tts = StreamingVolcanoTTS(max_concurrency=1)
             
-            # 流式处理文本并生成音频
-            await tts.synthesize_stream(text_stream, audio_callback)
+            # 异步迭代文本流
+            async for text_chunk in text_stream:
+                await tts._synthesize_single_with_semaphore(text_chunk, audio_callback)
             logger.info("TTS合成完成")
         except Exception as e:
             logger.error(f"TTS合成失败: {str(e)}")