fix：拯救大兵ruff 2

src/plugins/heartFC_chat/heartFC_chat.py

@@ -13,11 +13,12 @@ from src.plugins.models.utils_model import LLMRequest
 from src.config.config import global_config
 from src.plugins.chat.utils_image import image_path_to_base64  # Local import needed after move
 from src.plugins.utils.timer_calculater import Timer  # <--- Import Timer
+
 # --- Import necessary dependencies directly ---
-from .heartFC_generator import ResponseGenerator # Assuming this is the type for gpt
+from .heartFC_generator import ResponseGenerator  # Assuming this is the type for gpt
 from src.do_tool.tool_use import ToolUser
-from src.plugins.chat.emoji_manager import EmojiManager # Assuming this is the type
-from ..chat.message_sender import message_manager # <-- Import the global manager
+from src.plugins.chat.emoji_manager import EmojiManager  # Assuming this is the type
+from ..chat.message_sender import message_manager  # <-- Import the global manager
 # --- End import ---
 
 
@@ -37,7 +38,7 @@ if TYPE_CHECKING:
     # Keep this if HeartFCController methods are still needed elsewhere,
     # but the instance variable will be removed from HeartFChatting
     # from .heartFC_controler import HeartFCController
-    from src.heart_flow.heartflow import SubHeartflow, heartflow # <-- 同时导入 heartflow 实例用于类型检查
+    from src.heart_flow.heartflow import SubHeartflow, heartflow  # <-- 同时导入 heartflow 实例用于类型检查
 
 PLANNER_TOOL_DEFINITION = [
     {
@@ -74,16 +75,17 @@ class HeartFChatting:
     现在由其关联的 SubHeartflow 管理生命周期。
     """
 
-    def __init__(self,
-                chat_id: str,
-                # 显式依赖注入
-                gpt_instance: ResponseGenerator,  # 文本回复生成器
-                tool_user_instance: ToolUser,     # 工具使用实例
-                emoji_manager_instance: EmojiManager,  # 表情管理实例
-                ):
+    def __init__(
+        self,
+        chat_id: str,
+        # 显式依赖注入
+        gpt_instance: ResponseGenerator,  # 文本回复生成器
+        tool_user_instance: ToolUser,  # 工具使用实例
+        emoji_manager_instance: EmojiManager,  # 表情管理实例
+    ):
         """
         HeartFChatting 初始化函数
-        
+
         参数:
             chat_id: 聊天流唯一标识符(如stream_id)
             gpt_instance: 文本回复生成器实例
@@ -94,7 +96,7 @@ class HeartFChatting:
         self.stream_id: str = chat_id  # 聊天流ID
         self.chat_stream: Optional[ChatStream] = None  # 关联的聊天流
         self.sub_hf: Optional[SubHeartflow] = None  # 关联的子心流
-        
+
         # 初始化状态控制
         self._initialized = False  # 是否已初始化标志
         self._init_lock = asyncio.Lock()  # 初始化锁(确保只初始化一次)
@@ -145,6 +147,7 @@ class HeartFChatting:
 
                 # <-- 在这里导入 heartflow 实例
                 from src.heart_flow.heartflow import heartflow
+
                 self.sub_hf = heartflow.get_subheartflow(self.stream_id)
                 if not self.sub_hf:
                     logger.warning(f"{log_prefix} 获取SubHeartflow失败。一些功能可能受限。")
@@ -391,7 +394,9 @@ class HeartFChatting:
                                             logger.info(f"{log_prefix} 等待新消息的 sleep 被中断。")
                                             raise  # 重新抛出取消错误，以便外层循环处理
                             else:
-                                logger.warning(f"{log_prefix} HeartFChatting: 无法获取 Observation 实例，无法等待新消息。")
+                                logger.warning(
+                                    f"{log_prefix} HeartFChatting: 无法获取 Observation 实例，无法等待新消息。"
+                                )
                             # --- 等待结束 ---
 
                         elif action == "error":  # Action specifically set to error by planner
@@ -413,9 +418,7 @@ class HeartFChatting:
                             timer_strings.append(f"{name}: {formatted_time}")
 
                         if timer_strings:  # 如果有有效计时器数据才打印
-                            logger.debug(
-                                f"{log_prefix} 该次决策耗时: {'; '.join(timer_strings)}"
-                            )
+                            logger.debug(f"{log_prefix} 该次决策耗时: {'; '.join(timer_strings)}")
 
                     # --- Timer Decrement --- #
                     cycle_duration = time.monotonic() - loop_cycle_start_time
@@ -484,8 +487,12 @@ class HeartFChatting:
             self.sub_hf = heartflow.get_subheartflow(self.stream_id)
             if not self.sub_hf:
                 logger.error(f"{log_prefix}[Planner] SubHeartflow is not available. Cannot proceed.")
-                return {"action": "error", "reasoning": "SubHeartflow unavailable", "llm_error": True, "observed_messages": []}
-
+                return {
+                    "action": "error",
+                    "reasoning": "SubHeartflow unavailable",
+                    "llm_error": True,
+                    "observed_messages": [],
+                }
 
         try:
             # Access observation via self.sub_hf
@@ -503,9 +510,7 @@ class HeartFChatting:
         # --- (Moved from _replier_work) 1. 思考前使用工具 --- #
         try:
             # Access tool_user directly
-            tool_result = await self.tool_user.use_tool(
-                message_txt=observed_messages_str, sub_heartflow=self.sub_hf
-            )
+            tool_result = await self.tool_user.use_tool(message_txt=observed_messages_str, sub_heartflow=self.sub_hf)
             if tool_result.get("used_tools", False):
                 tool_result_info = tool_result.get("structured_info", {})
                 logger.debug(f"{log_prefix}[Planner] 规划前工具结果: {tool_result_info}")
@@ -620,7 +625,6 @@ class HeartFChatting:
         """
 
         try:
-
             # --- Create Placeholder --- #
             placeholder_id = f"mid_pf_{int(time.time() * 1000)}"
             placeholder_user = UserInfo(

src/plugins/heartFC_chat/heartFC_generator.py

@@ -11,6 +11,7 @@ from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager
 from ..utils.timer_calculater import Timer
 
 from src.plugins.moods.moods import MoodManager
+
 # 定义日志配置
 llm_config = LogConfig(
     # 使用消息发送专用样式
@@ -78,7 +79,6 @@ class ResponseGenerator:
 
         sender_name = f"<{message.chat_stream.user_info.platform}:{message.chat_stream.user_info.user_id}:{message.chat_stream.user_info.user_nickname}:{message.chat_stream.user_info.user_cardname}>"
 
-        
         with Timer() as t_build_prompt:
             prompt = await prompt_builder.build_prompt(
                 build_mode="focus",
@@ -86,7 +86,7 @@ class ResponseGenerator:
                 current_mind_info=current_mind_info,
                 message_txt=message.processed_plain_text,
                 sender_name=sender_name,
-                chat_stream=message.chat_stream
+                chat_stream=message.chat_stream,
             )
         logger.info(f"构建prompt时间: {t_build_prompt.human_readable}")
 

src/plugins/heartFC_chat/heartflow_prompt_builder.py

@@ -42,7 +42,7 @@ def init_prompt():
 涉及政治敏感以及违法违规的内容请规避。""",
         "moderation_prompt",
     )
-    
+
     Prompt(
         """
 {relation_prompt_all}
@@ -77,23 +77,18 @@ class PromptBuilder:
         self.prompt_built = ""
         self.activate_messages = ""
 
-    
     async def build_prompt(
-        self, build_mode,reason,current_mind_info, message_txt: str, sender_name: str = "某人",chat_stream=None
+        self, build_mode, reason, current_mind_info, message_txt: str, sender_name: str = "某人", chat_stream=None
     ) -> tuple[str, str]:
-
         if build_mode == "normal":
             return await self._build_prompt_normal(chat_stream, message_txt, sender_name)
-        
+
         elif build_mode == "focus":
             return await self._build_prompt_focus(reason, current_mind_info, chat_stream, message_txt, sender_name)
 
-
-    
     async def _build_prompt_focus(
         self, reason, current_mind_info, chat_stream, message_txt: str, sender_name: str = "某人"
     ) -> tuple[str, str]:
-
         individuality = Individuality.get_instance()
         prompt_personality = individuality.get_prompt(type="personality", x_person=2, level=1)
         prompt_identity = individuality.get_prompt(type="identity", x_person=2, level=1)
@@ -104,14 +99,14 @@ class PromptBuilder:
         if chat_stream.group_info:
             chat_in_group = True
         else:
-            chat_in_group = False 
-        
+            chat_in_group = False
+
         message_list_before_now = get_raw_msg_before_timestamp_with_chat(
-            chat_id =chat_stream.stream_id,
-            timestamp = time.time(),
+            chat_id=chat_stream.stream_id,
+            timestamp=time.time(),
             limit=global_config.MAX_CONTEXT_SIZE,
         )
-        
+
         chat_talking_prompt = await build_readable_messages(
             message_list_before_now,
             replace_bot_name=True,
@@ -147,7 +142,6 @@ class PromptBuilder:
         if random.random() < 0.02:
             prompt_ger += "你喜欢用反问句"
 
-
         logger.debug("开始构建prompt")
 
         prompt = await global_prompt_manager.format_prompt(
@@ -176,11 +170,7 @@ class PromptBuilder:
 
         return prompt
 
-
-
-    async def _build_prompt_normal(
-        self, chat_stream, message_txt: str, sender_name: str = "某人"
-    ) -> tuple[str, str]:
+    async def _build_prompt_normal(self, chat_stream, message_txt: str, sender_name: str = "某人") -> tuple[str, str]:
         # 开始构建prompt
         prompt_personality = "你"
         # person
@@ -245,14 +235,14 @@ class PromptBuilder:
         if chat_stream.group_info:
             chat_in_group = True
         else:
-            chat_in_group = False 
-        
+            chat_in_group = False
+
         message_list_before_now = get_raw_msg_before_timestamp_with_chat(
-            chat_id =chat_stream.stream_id,
-            timestamp = time.time(),
+            chat_id=chat_stream.stream_id,
+            timestamp=time.time(),
             limit=global_config.MAX_CONTEXT_SIZE,
         )
-        
+
         chat_talking_prompt = await build_readable_messages(
             message_list_before_now,
             replace_bot_name=True,
@@ -260,9 +250,7 @@ class PromptBuilder:
             timestamp_mode="relative",
             read_mark=0.0,
         )
-                
-                
-                
+
         # 关键词检测与反应
         keywords_reaction_prompt = ""
         for rule in global_config.keywords_reaction_rules:
@@ -303,11 +291,11 @@ class PromptBuilder:
         logger.debug(f"知识检索耗时: {(end_time - start_time):.3f}秒")
 
         logger.debug("开始构建prompt")
-        
-        schedule_prompt=await global_prompt_manager.format_prompt(
+
+        schedule_prompt = await global_prompt_manager.format_prompt(
             "schedule_prompt", schedule_info=bot_schedule.get_current_num_task(num=1, time_info=False)
         )
-        
+
         prompt = await global_prompt_manager.format_prompt(
             "reasoning_prompt_main",
             relation_prompt_all=await global_prompt_manager.get_prompt_async("relationship_prompt"),
@@ -558,6 +546,5 @@ class PromptBuilder:
             return "\n".join(str(result["content"]) for result in results)
 
 
-
 init_prompt()
 prompt_builder = PromptBuilder()

src/plugins/heartFC_chat/normal_chat.py

@@ -22,6 +22,7 @@ from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager
 from src.plugins.utils.timer_calculater import Timer
 from src.heart_flow.heartflow import heartflow
 from src.heart_flow.sub_heartflow import ChatState
+
 # 定义日志配置
 chat_config = LogConfig(
     console_format=CHAT_STYLE_CONFIG["console_format"],
@@ -129,7 +130,7 @@ class NormalChat:
                 is_head=not mark_head,
                 is_emoji=False,
                 thinking_start_time=thinking_start_time,
-                apply_set_reply_logic=True
+                apply_set_reply_logic=True,
             )
             if not mark_head:
                 mark_head = True
@@ -165,7 +166,7 @@ class NormalChat:
                     reply=message,
                     is_head=False,
                     is_emoji=True,
-                    apply_set_reply_logic=True
+                    apply_set_reply_logic=True,
                 )
                 await message_manager.add_message(bot_message)
 
@@ -212,13 +213,13 @@ class NormalChat:
                     if removed_item:
                         # logger.debug(f"[{stream_name}] 已从兴趣字典中移除消息 {msg_id} (因状态跳过)") # 减少日志
                         pass
-                    continue # 处理下一条消息
+                    continue  # 处理下一条消息
                 # --- 结束状态检查 --- #
 
                 # --- 检查 HeartFChatting 是否活跃 (改为检查 SubHeartflow 状态) --- #
                 is_focused = subheartflow.chat_state.chat_status == ChatState.FOCUSED
 
-                if is_focused: # New check: If the subflow is focused, NormalChat shouldn't process
+                if is_focused:  # New check: If the subflow is focused, NormalChat shouldn't process
                     removed_item = interest_dict.pop(msg_id, None)
                     if removed_item:
                         # logger.debug(f"[{stream_name}] SubHeartflow 处于 FOCUSED 状态，已跳过并移除 NormalChat 兴趣消息 {msg_id}") # Reduce noise
@@ -264,7 +265,7 @@ class NormalChat:
             )
             # 可以在这里添加 not_reply_handle 逻辑吗？ 如果不回复，也需要清理意愿。
             # 注意：willing_manager.setup 尚未调用
-            willing_manager.setup(message, chat, is_mentioned, interested_rate) # 先 setup
+            willing_manager.setup(message, chat, is_mentioned, interested_rate)  # 先 setup
             await willing_manager.not_reply_handle(message.message_info.message_id)
             willing_manager.delete(message.message_info.message_id)
             return
@@ -313,7 +314,7 @@ class NormalChat:
 
             # 生成回复
             sub_hf = heartflow.get_subheartflow(stream_id)
-            
+
             try:
                 with Timer("生成回复", timing_results):
                     response_set = await self.gpt.generate_response(

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: