fixL:

src/heart_flow/mai_state_manager.py

@@ -13,8 +13,8 @@ mai_state_config = LogConfig(
 logger = get_module_logger("mai_state_manager", config=mai_state_config)
 
 
-enable_unlimited_hfc_chat = True
-# enable_unlimited_hfc_chat = False
+# enable_unlimited_hfc_chat = True
+enable_unlimited_hfc_chat = False
 
 
 class MaiState(enum.Enum):

src/heart_flow/sub_heartflow.py

@@ -221,9 +221,7 @@ class SubHeartflow:
 
         # 聊天状态管理
         self.chat_state: ChatStateInfo = ChatStateInfo()  # 该sub_heartflow的聊天状态信息
-        self.interest_chatting = InterestChatting(
-            state_change_callback=self.set_chat_state
-        ) 
+        self.interest_chatting = InterestChatting(state_change_callback=self.set_chat_state)
 
         # 活动状态管理
         self.last_active_time = time.time()  # 最后活跃时间
@@ -238,15 +236,11 @@ class SubHeartflow:
 
         # LLM模型配置
         self.sub_mind = SubMind(
-            subheartflow_id=self.subheartflow_id,
-            chat_state=self.chat_state,
-            observations=self.observations
+            subheartflow_id=self.subheartflow_id, chat_state=self.chat_state, observations=self.observations
         )
 
-
         self.log_prefix = chat_manager.get_stream_name(self.subheartflow_id) or self.subheartflow_id
 
-
     async def add_time_current_state(self, add_time: float):
         self.current_state_time += add_time
 
@@ -335,9 +329,7 @@ class SubHeartflow:
         logger.info(f"{log_prefix} 麦麦准备开始专注聊天 (创建新实例)...")
         try:
             self.heart_fc_instance = HeartFChatting(
-                chat_id=self.chat_id,
-                sub_mind=self.sub_mind,
-                observations=self.observations
+                chat_id=self.chat_id, sub_mind=self.sub_mind, observations=self.observations
             )
             if await self.heart_fc_instance._initialize():
                 await self.heart_fc_instance.start()  # 初始化成功后启动循环
@@ -434,7 +426,6 @@ class SubHeartflow:
 
         logger.info(f"{self.log_prefix} 子心流后台任务已停止。")
 
-
     def update_current_mind(self, response):
         self.sub_mind.update_current_mind(response)
 
@@ -523,6 +514,3 @@ class SubHeartflow:
         self.chat_state.chat_status = ChatState.ABSENT  # 状态重置为不参与
 
         logger.info(f"{self.log_prefix} 子心流关闭完成。")
-
-
-

src/heart_flow/sub_mind.py

@@ -19,7 +19,6 @@ subheartflow_config = LogConfig(
 logger = get_module_logger("subheartflow", config=subheartflow_config)
 
 
-
 def init_prompt():
     prompt = ""
     # prompt += f"麦麦的总体想法是：{self.main_heartflow_info}\n\n"
@@ -41,14 +40,8 @@ def init_prompt():
     Prompt(prompt, "sub_heartflow_prompt_before")
 
 
-
 class SubMind:
-    def __init__(
-        self,
-        subheartflow_id: str,
-        chat_state: ChatStateInfo,
-        observations: Observation
-    ):
+    def __init__(self, subheartflow_id: str, chat_state: ChatStateInfo, observations: Observation):
         self.subheartflow_id = subheartflow_id
 
         self.llm_model = LLMRequest(
@@ -151,7 +144,7 @@ class SubMind:
 
         # ---------- 5. 执行LLM请求并处理响应 ----------
         content = ""  # 初始化内容变量
-        reasoning_content = ""  # 初始化推理内容变量
+        _reasoning_content = ""  # 初始化推理内容变量
 
         try:
             # 调用LLM生成响应
@@ -212,7 +205,6 @@ class SubMind:
 
         return self.current_mind, self.past_mind
 
-    
     async def _execute_tool_calls(self, tool_calls, tool_instance):
         """
         执行一组工具调用并收集结果
@@ -245,7 +237,6 @@ class SubMind:
             logger.debug(f"工具调用收集到结构化信息: {safe_json_dumps(structured_info, ensure_ascii=False)}")
             self.structured_info = structured_info
 
-    
     def update_current_mind(self, response):
         self.past_mind.append(self.current_mind)
         self.current_mind = response

src/plugins/heartFC_chat/heartFC_chat.py

@@ -67,12 +67,7 @@ class HeartFChatting:
     其生命周期现在由其关联的 SubHeartflow 的 FOCUSED 状态控制。
     """
 
-    def __init__(
-        self,
-        chat_id: str,
-        sub_mind: SubMind,
-        observations: Observation
-    ):
+    def __init__(self, chat_id: str, sub_mind: SubMind, observations: Observation):
         """
         HeartFChatting 初始化函数
 
@@ -438,7 +433,9 @@ class HeartFChatting:
         llm_error = False  # LLM错误标志
 
         try:
-            prompt = await self._build_planner_prompt(observed_messages_str, current_mind, self.sub_mind.structured_info)
+            prompt = await self._build_planner_prompt(
+                observed_messages_str, current_mind, self.sub_mind.structured_info
+            )
             payload = {
                 "model": self.planner_llm.model_name,
                 "messages": [{"role": "user", "content": prompt}],