fix(删除打印模型代码)

core/construction_write/component/outline_generator.py

@@ -638,32 +638,6 @@ class OutlineGenerator:
             return None
         return self._keyword_rules_cache.get(code)
 
-    def _resolve_llm_model_name(
-        self,
-        function_name: Optional[str] = None,
-        model_name: Optional[str] = None
-    ) -> str:
-        """解析本次 LLM 调用实际会使用的模型名，用于日志排查。"""
-        try:
-            from foundation.ai.models.model_config_loader import get_model_for_function
-
-            # 保持和 generate_model_client.get_model_generate_invoke 的解析顺序一致。
-            if function_name:
-                resolved_model = get_model_for_function(function_name)
-                if resolved_model:
-                    return resolved_model
-
-            if model_name:
-                return model_name
-
-            default_model = get_model_for_function("default")
-            if default_model:
-                return default_model
-        except Exception as e:
-            logger.warning(f"[LLM调用] 解析模型名失败: {str(e)}")
-
-        return model_name or "default"
-
     async def _call_llm(
         self,
         trace_id: str,
@@ -735,14 +709,7 @@ class OutlineGenerator:
                 "task_prompt": chat_template
             }
 
-            resolved_model_name = self._resolve_llm_model_name(
-                function_name=function_name,
-                model_name=model_name
-            )
-            logger.info(
-                f"[LLM调用] trace_id: {trace_id}, model: {resolved_model_name}, "
-                f"function_name: {function_name}, 开始生成内容"
-            )
+            logger.info(f"[LLM调用] trace_id: {trace_id}, 开始生成内容")
 
             # 调用模型生成（非流式）
             generated_content = await generate_model_client.get_model_generate_invoke(
@@ -753,26 +720,15 @@ class OutlineGenerator:
                 function_name=function_name,
             )
 
-            logger.info(
-                f"[LLM调用] trace_id: {trace_id}, model: {resolved_model_name}, "
-                f"生成完成，内容长度: {len(generated_content)}"
-            )
+            logger.info(f"[LLM调用] trace_id: {trace_id}, 生成完成，内容长度: {len(generated_content)}")
 
             return generated_content
 
         except TimeoutError as e:
-            resolved_model_name = self._resolve_llm_model_name(
-                function_name=function_name,
-                model_name=model_name
-            )
-            logger.error(f"[LLM调用] trace_id: {trace_id}, model: {resolved_model_name}, 超时: {str(e)}")
+            logger.error(f"[LLM调用] trace_id: {trace_id}, 超时: {str(e)}")
             raise
         except Exception as e:
-            resolved_model_name = self._resolve_llm_model_name(
-                function_name=function_name,
-                model_name=model_name
-            )
-            logger.error(f"[LLM调用] trace_id: {trace_id}, model: {resolved_model_name}, 异常: {str(e)}")
+            logger.error(f"[LLM调用] trace_id: {trace_id}, 异常: {str(e)}")
             raise
 
     async def _generate_single_chapter(