diff --git a/src/llm_models/utils_model.py b/src/llm_models/utils_model.py
index 48ef0c082..b7aa0a8b8 100644
--- a/src/llm_models/utils_model.py
+++ b/src/llm_models/utils_model.py
@@ -138,6 +138,7 @@ class LLMRequest:
         temperature: Optional[float] = None,
         max_tokens: Optional[int] = None,
         tools: Optional[List[Dict[str, Any]]] = None,
+        raise_when_empty: bool = True,
     ) -> Tuple[str, Tuple[str, str, Optional[List[ToolCall]]]]:
         """
         异步生成响应
@@ -183,7 +184,9 @@ class LLMRequest:
                 endpoint="/chat/completions",
             )
         if not content:
-            logger.warning("生成的响应为空")
+            if raise_when_empty:
+                logger.warning("生成的响应为空")
+                raise RuntimeError("生成的响应为空")
             content = "生成的响应为空，请检查模型配置或输入内容是否正确"
 
         return content, (reasoning_content, model_info.name, tool_calls)
diff --git a/src/plugin_system/core/tool_use.py b/src/plugin_system/core/tool_use.py
index 9a37bc1d8..17e236856 100644
--- a/src/plugin_system/core/tool_use.py
+++ b/src/plugin_system/core/tool_use.py
@@ -111,7 +111,7 @@ class ToolExecutor:
 
         # 调用LLM进行工具决策
         response, (reasoning_content, model_name, tool_calls) = await self.llm_model.generate_response_async(
-            prompt=prompt, tools=tools
+            prompt=prompt, tools=tools, raise_when_empty=False
         )
 
         # 执行工具调用