Introduce the error retransmission mechanism to enhance robustness.

QueryEngine/agent.py

@@ -51,7 +51,7 @@ class DeepSearchAgent:
         # 确保输出目录存在
         os.makedirs(self.config.output_dir, exist_ok=True)
         
-        print(f"Deep Search Agent 已初始化")
+        print(f"Query Agent已初始化")
         print(f"使用LLM: {self.llm_client.get_model_info()}")
         print(f"搜索工具集: TavilyNewsAgency (支持6种搜索工具)")
     

QueryEngine/llms/deepseek.py

@@ -4,10 +4,27 @@ DeepSeek LLM实现
 """
 
 import os
+import sys
 from typing import Optional, Dict, Any
 from openai import OpenAI
 from .base import BaseLLM
 
+# 添加utils目录到Python路径并导入重试模块
+try:
+    current_dir = os.path.dirname(os.path.abspath(__file__))
+    root_dir = os.path.dirname(os.path.dirname(current_dir))
+    utils_dir = os.path.join(root_dir, 'utils')
+    if utils_dir not in sys.path:
+        sys.path.append(utils_dir)
+    from retry_helper import with_retry, with_graceful_retry, LLM_RETRY_CONFIG
+except ImportError:
+    # 如果无法导入重试模块，使用空装饰器避免报错
+    def with_retry(config):
+        def decorator(func):
+            return func
+        return decorator
+    LLM_RETRY_CONFIG = None
+
 
 class DeepSeekLLM(BaseLLM):
     """DeepSeek LLM实现类"""
@@ -39,6 +56,7 @@ class DeepSeekLLM(BaseLLM):
         """获取默认模型名称"""
         return "deepseek-chat"
     
+    @with_retry(LLM_RETRY_CONFIG)
     def invoke(self, system_prompt: str, user_prompt: str, **kwargs) -> str:
         """
         调用DeepSeek API生成回复

QueryEngine/llms/openai_llm.py

@@ -4,10 +4,27 @@ OpenAI LLM实现
 """
 
 import os
+import sys
 from typing import Optional, Dict, Any
 from openai import OpenAI
 from .base import BaseLLM
 
+# 添加utils目录到Python路径并导入重试模块
+try:
+    current_dir = os.path.dirname(os.path.abspath(__file__))
+    root_dir = os.path.dirname(os.path.dirname(current_dir))
+    utils_dir = os.path.join(root_dir, 'utils')
+    if utils_dir not in sys.path:
+        sys.path.append(utils_dir)
+    from retry_helper import with_retry, with_graceful_retry, LLM_RETRY_CONFIG
+except ImportError:
+    # 如果无法导入重试模块，使用空装饰器避免报错
+    def with_retry(config):
+        def decorator(func):
+            return func
+        return decorator
+    LLM_RETRY_CONFIG = None
+
 
 class OpenAILLM(BaseLLM):
     """OpenAI LLM实现类"""
@@ -35,6 +52,7 @@ class OpenAILLM(BaseLLM):
         """获取默认模型名称"""
         return "gpt-4o-mini"
     
+    @with_retry(LLM_RETRY_CONFIG)
     def invoke(self, system_prompt: str, user_prompt: str, **kwargs) -> str:
         """
         调用OpenAI API生成回复

QueryEngine/tools/search.py

@@ -22,7 +22,17 @@
 """
 
 import os
+import sys
 from typing import List, Dict, Any, Optional
+
+# 添加utils目录到Python路径
+current_dir = os.path.dirname(os.path.abspath(__file__))
+root_dir = os.path.dirname(os.path.dirname(current_dir))
+utils_dir = os.path.join(root_dir, 'utils')
+if utils_dir not in sys.path:
+    sys.path.append(utils_dir)
+
+from retry_helper import with_graceful_retry, SEARCH_API_RETRY_CONFIG
 from dataclasses import dataclass, field
 
 # 运行前请确保已安装Tavily库: pip install tavily-python
@@ -82,6 +92,7 @@ class TavilyNewsAgency:
                 raise ValueError("Tavily API Key未找到！请设置TAVILY_API_KEY环境变量或在初始化时提供")
         self._client = TavilyClient(api_key=api_key)
 
+    @with_graceful_retry(SEARCH_API_RETRY_CONFIG, default_return=TavilyResponse(query="搜索失败"))
     def _search_internal(self, **kwargs) -> TavilyResponse:
         """内部通用的搜索执行器，所有工具最终都调用此方法"""
         try:
@@ -109,7 +120,7 @@ class TavilyNewsAgency:
             )
         except Exception as e:
             print(f"搜索时发生错误: {str(e)}")
-            return TavilyResponse(query=kwargs.get("query", "Unknown Query"))
+            raise e  # 让重试机制捕获并处理
 
     # --- Agent 可用的工具方法 ---