1. LLM接口改为字节级流式接口，防止超时错误，也避免utf-8长字节字符拼接错误

QueryEngine/llms/base.py

@@ -5,7 +5,8 @@ Unified OpenAI-compatible LLM client for the Query Engine, with retry support.
 import os
 import sys
 from datetime import datetime
-from typing import Any, Dict, Optional
+from typing import Any, Dict, Optional, Generator
+from loguru import logger
 
 from openai import OpenAI
 
@@ -82,6 +83,76 @@ class LLMClient:
             return self.validate_response(response.choices[0].message.content)
         return ""
 
+    @with_retry(LLM_RETRY_CONFIG)
+    def stream_invoke(self, system_prompt: str, user_prompt: str, **kwargs) -> Generator[str, None, None]:
+        """
+        流式调用LLM，逐步返回响应内容
+        
+        Args:
+            system_prompt: 系统提示词
+            user_prompt: 用户提示词
+            **kwargs: 额外参数（temperature, top_p等）
+            
+        Yields:
+            响应文本块（str）
+        """
+        current_time = datetime.now().strftime("%Y年%m月%d日%H时%M分")
+        time_prefix = f"今天的实际时间是{current_time}"
+        if user_prompt:
+            user_prompt = f"{time_prefix}\n{user_prompt}"
+        else:
+            user_prompt = time_prefix
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": user_prompt},
+        ]
+
+        allowed_keys = {"temperature", "top_p", "presence_penalty", "frequency_penalty"}
+        extra_params = {key: value for key, value in kwargs.items() if key in allowed_keys and value is not None}
+        # 强制使用流式
+        extra_params["stream"] = True
+
+        timeout = kwargs.pop("timeout", self.timeout)
+
+        try:
+            stream = self.client.chat.completions.create(
+                model=self.model_name,
+                messages=messages,
+                timeout=timeout,
+                **extra_params,
+            )
+            
+            for chunk in stream:
+                if chunk.choices and len(chunk.choices) > 0:
+                    delta = chunk.choices[0].delta
+                    if delta and delta.content:
+                        yield delta.content
+        except Exception as e:
+            logger.error(f"流式请求失败: {str(e)}")
+            raise e
+    
+    def stream_invoke_to_string(self, system_prompt: str, user_prompt: str, **kwargs) -> str:
+        """
+        流式调用LLM并安全地拼接为完整字符串（避免UTF-8多字节字符截断）
+        
+        Args:
+            system_prompt: 系统提示词
+            user_prompt: 用户提示词
+            **kwargs: 额外参数（temperature, top_p等）
+            
+        Returns:
+            完整的响应字符串
+        """
+        # 以字节形式收集所有块
+        byte_chunks = []
+        for chunk in self.stream_invoke(system_prompt, user_prompt, **kwargs):
+            byte_chunks.append(chunk.encode('utf-8'))
+        
+        # 拼接所有字节，然后一次性解码
+        if byte_chunks:
+            return b''.join(byte_chunks).decode('utf-8', errors='replace')
+        return ""
+
     @staticmethod
     def validate_response(response: Optional[str]) -> str:
         if response is None: