fix：拯救大兵ruff 2

src/plugins/heartFC_chat/normal_chat_generator.py

@@ -9,6 +9,7 @@ from ..utils.timer_calculater import Timer
 from src.common.logger import get_module_logger, LogConfig, LLM_STYLE_CONFIG
 from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager
 from src.heart_flow.sub_heartflow import SubHeartflow
+
 # 定义日志配置
 llm_config = LogConfig(
     # 使用消息发送专用样式
@@ -40,7 +41,9 @@ class ResponseGenerator:
         self.current_model_type = "r1"  # 默认使用 R1
         self.current_model_name = "unknown model"
 
-    async def generate_response(self, sub_hf: SubHeartflow, message: MessageThinking, thinking_id: str) -> Optional[Union[str, List[str]]]:
+    async def generate_response(
+        self, sub_hf: SubHeartflow, message: MessageThinking, thinking_id: str
+    ) -> Optional[Union[str, List[str]]]:
         """根据当前模型类型选择对应的生成函数"""
         # 从global_config中获取模型概率值并选择模型
         if random.random() < global_config.model_reasoning_probability:
@@ -67,7 +70,9 @@ class ResponseGenerator:
             logger.info(f"{self.current_model_type}思考，失败")
             return None
 
-    async def _generate_response_with_model(self, sub_hf: SubHeartflow, message: MessageThinking, model: LLMRequest, thinking_id: str):
+    async def _generate_response_with_model(
+        self, sub_hf: SubHeartflow, message: MessageThinking, model: LLMRequest, thinking_id: str
+    ):
         info_catcher = info_catcher_manager.get_info_catcher(thinking_id)
 
         if message.chat_stream.user_info.user_cardname and message.chat_stream.user_info.user_nickname:
@@ -85,7 +90,7 @@ class ResponseGenerator:
         with Timer() as t_build_prompt:
             prompt = await prompt_builder.build_prompt(
                 build_mode="normal",
-                reason= "",
+                reason="",
                 current_mind_info="",
                 message_txt=message.processed_plain_text,
                 sender_name=sender_name,
@@ -95,7 +100,7 @@ class ResponseGenerator:
 
         try:
             content, reasoning_content, self.current_model_name = await model.generate_response(prompt)
-            
+
             logger.info(f"prompt:{prompt}\n生成回复：{content}")
 
             info_catcher.catch_after_llm_generated(
@@ -108,7 +113,6 @@ class ResponseGenerator:
 
         return content
 
-
     async def _get_emotion_tags(self, content: str, processed_plain_text: str):
         """提取情感标签，结合立场和情绪"""
         try: