feat: 完全分离回复 兴趣和 消息阅读；添加概率回复机制，优化兴趣监控逻辑，重构相关功能以支持更灵活的回复触发条件

src/heart_flow/sub_heartflow.py

@@ -4,6 +4,9 @@ from src.plugins.moods.moods import MoodManager
 from src.plugins.models.utils_model import LLMRequest
 from src.config.config import global_config
 import time
+from typing import Optional
+from datetime import datetime
+import traceback
 from src.plugins.chat.message import UserInfo
 from src.plugins.chat.utils import parse_text_timestamps
 
@@ -113,6 +116,8 @@ class SubHeartflow:
 
         self.running_knowledges = []
 
+        self._thinking_lock = asyncio.Lock() # 添加思考锁，防止并发思考
+
         self.bot_name = global_config.BOT_NICKNAME
 
     def add_observation(self, observation: Observation):
@@ -138,144 +143,172 @@ class SubHeartflow:
         """清空所有observation对象"""
         self.observations.clear()
 
+    def _get_primary_observation(self) -> Optional[ChattingObservation]:
+        """获取主要的（通常是第一个）ChattingObservation实例"""
+        if self.observations and isinstance(self.observations[0], ChattingObservation):
+            return self.observations[0]
+        logger.warning(f"SubHeartflow {self.subheartflow_id} 没有找到有效的 ChattingObservation")
+        return None
+
     async def subheartflow_start_working(self):
         while True:
             current_time = time.time()
-            if (
-                current_time - self.last_reply_time > global_config.sub_heart_flow_freeze_time
-            ):  # 120秒无回复/不在场，冻结
-                self.is_active = False
-                await asyncio.sleep(global_config.sub_heart_flow_update_interval)  # 每60秒检查一次
-            else:
-                self.is_active = True
-                self.last_active_time = current_time  # 更新最后激活时间
+            # --- 调整后台任务逻辑 --- #
+            # 这个后台循环现在主要负责检查是否需要自我销毁
+            # 不再主动进行思考或状态更新，这些由 HeartFC_Chat 驱动
 
-                self.current_state.update_current_state_info()
+            # 检查是否需要冻结（这个逻辑可能需要重新审视，因为激活状态现在由外部驱动）
+            # if current_time - self.last_reply_time > global_config.sub_heart_flow_freeze_time:
+            #     self.is_active = False
+            # else:
+            #     self.is_active = True
+            #     self.last_active_time = current_time # 由外部调用（如 thinking）更新
 
-                # await self.do_a_thinking()
-                # await self.judge_willing()
-                await asyncio.sleep(global_config.sub_heart_flow_update_interval)
+            # 检查是否超过指定时间没有激活 (例如，没有被调用进行思考)
+            if current_time - self.last_active_time > global_config.sub_heart_flow_stop_time:  # 例如 5 分钟
+                logger.info(f"子心流 {self.subheartflow_id} 超过 {global_config.sub_heart_flow_stop_time} 秒没有激活，正在销毁..."
+                            f" (Last active: {datetime.fromtimestamp(self.last_active_time).strftime('%Y-%m-%d %H:%M:%S')})")
+                # 在这里添加实际的销毁逻辑，例如从主 Heartflow 管理器中移除自身
+                # heartflow.remove_subheartflow(self.subheartflow_id) # 假设有这样的方法
+                break  # 退出循环以停止任务
 
-            # 检查是否超过10分钟没有激活
-            if (
-                current_time - self.last_active_time > global_config.sub_heart_flow_stop_time
-            ):  # 5分钟无回复/不在场，销毁
-                logger.info(f"子心流 {self.subheartflow_id} 已经5分钟没有激活，正在销毁...")
-                break  # 退出循环，销毁自己
+            # 不再需要内部驱动的状态更新和思考
+            # self.current_state.update_current_state_info()
+            # await self.do_a_thinking()
+            # await self.judge_willing()
+
+            await asyncio.sleep(global_config.sub_heart_flow_update_interval) # 定期检查销毁条件
+
+    async def ensure_observed(self):
+        """确保在思考前执行了观察"""
+        observation = self._get_primary_observation()
+        if observation:
+            try:
+                await observation.observe()
+                logger.trace(f"[{self.subheartflow_id}] Observation updated before thinking.")
+            except Exception as e:
+                logger.error(f"[{self.subheartflow_id}] Error during pre-thinking observation: {e}")
+                logger.error(traceback.format_exc())
 
     async def do_observe(self):
-        observation = self.observations[0]
-        await observation.observe()
+        # 现在推荐使用 ensure_observed()，但保留此方法以兼容旧用法（或特定场景）
+        observation = self._get_primary_observation()
+        if observation:
+            await observation.observe()
+        else:
+            logger.error(f"[{self.subheartflow_id}] do_observe called but no valid observation found.")
 
     async def do_thinking_before_reply(
-        self, message_txt: str, sender_info: UserInfo, chat_stream: ChatStream, extra_info: str, obs_id: int = None
+        self, message_txt: str, sender_info: UserInfo, chat_stream: ChatStream, extra_info: str, obs_id: list[str] = None # 修改 obs_id 类型为 list[str]
     ):
-        current_thinking_info = self.current_mind
-        mood_info = self.current_state.mood
-        # mood_info = "你很生气，很愤怒"
-        observation = self.observations[0]
-        if obs_id:
-            print(f"11111111111有id,开始获取观察信息{obs_id}")
-            chat_observe_info = observation.get_observe_info(obs_id)
-        else:
-            chat_observe_info = observation.get_observe_info()
+        async with self._thinking_lock: # 获取思考锁
+            # --- 在思考前确保观察已执行 --- #
+            await self.ensure_observed()
 
-        extra_info_prompt = ""
-        for tool_name, tool_data in extra_info.items():
-            extra_info_prompt += f"{tool_name} 相关信息:\n"
-            for item in tool_data:
-                extra_info_prompt += f"- {item['name']}: {item['content']}\n"
+            self.last_active_time = time.time() # 更新最后激活时间戳
 
-        # 开始构建prompt
-        prompt_personality = f"你的名字是{self.bot_name},你"
-        # person
-        individuality = Individuality.get_instance()
+            current_thinking_info = self.current_mind
+            mood_info = self.current_state.mood
+            observation = self._get_primary_observation()
+            if not observation:
+                logger.error(f"[{self.subheartflow_id}] Cannot perform thinking without observation.")
+                return "", [] # 返回空结果
 
-        personality_core = individuality.personality.personality_core
-        prompt_personality += personality_core
+            # --- 获取观察信息 --- #
+            chat_observe_info = ""
+            if obs_id:
+                try:
+                    chat_observe_info = observation.get_observe_info(obs_id)
+                    logger.debug(f"[{self.subheartflow_id}] Using specific observation IDs: {obs_id}")
+                except Exception as e:
+                    logger.error(f"[{self.subheartflow_id}] Error getting observe info with IDs {obs_id}: {e}. Falling back.")
+                    chat_observe_info = observation.get_observe_info() # 出错时回退到默认观察
+            else:
+                chat_observe_info = observation.get_observe_info()
+                logger.debug(f"[{self.subheartflow_id}] Using default observation info.")
 
-        personality_sides = individuality.personality.personality_sides
-        random.shuffle(personality_sides)
-        prompt_personality += f",{personality_sides[0]}"
 
-        identity_detail = individuality.identity.identity_detail
-        random.shuffle(identity_detail)
-        prompt_personality += f",{identity_detail[0]}"
+            # --- 构建 Prompt (基本逻辑不变) --- #
+            extra_info_prompt = ""
+            if extra_info:
+                for tool_name, tool_data in extra_info.items():
+                    extra_info_prompt += f"{tool_name} 相关信息:\n"
+                    for item in tool_data:
+                        extra_info_prompt += f"- {item['name']}: {item['content']}\n"
+            else:
+                extra_info_prompt = "无工具信息。\n" # 提供默认值
 
-        # 关系
-        who_chat_in_group = [
-            (chat_stream.user_info.platform, chat_stream.user_info.user_id, chat_stream.user_info.user_nickname)
-        ]
-        who_chat_in_group += get_recent_group_speaker(
-            chat_stream.stream_id,
-            (chat_stream.user_info.platform, chat_stream.user_info.user_id),
-            limit=global_config.MAX_CONTEXT_SIZE,
-        )
+            individuality = Individuality.get_instance()
+            prompt_personality = f"你的名字是{self.bot_name},你"
+            prompt_personality += individuality.personality.personality_core
+            personality_sides = individuality.personality.personality_sides
+            if personality_sides: random.shuffle(personality_sides); prompt_personality += f",{personality_sides[0]}"
+            identity_detail = individuality.identity.identity_detail
+            if identity_detail: random.shuffle(identity_detail); prompt_personality += f",{identity_detail[0]}"
 
-        relation_prompt = ""
-        for person in who_chat_in_group:
-            relation_prompt += await relationship_manager.build_relationship_info(person)
+            who_chat_in_group = [
+                (chat_stream.platform, sender_info.user_id, sender_info.user_nickname) # 先添加当前发送者
+            ]
+            # 获取最近发言者，排除当前发送者，避免重复
+            recent_speakers = get_recent_group_speaker(
+                chat_stream.stream_id,
+                (chat_stream.platform, sender_info.user_id),
+                limit=global_config.MAX_CONTEXT_SIZE -1 # 减去当前发送者
+            )
+            who_chat_in_group.extend(recent_speakers)
 
-        # relation_prompt_all = (
-        #     f"{relation_prompt}关系等级越大，关系越好，请分析聊天记录，"
-        #     f"根据你和说话者{sender_name}的关系和态度进行回复，明确你的立场和情感。"
-        # )
-        relation_prompt_all = (await global_prompt_manager.get_prompt_async("relationship_prompt")).format(
-            relation_prompt, sender_info.user_nickname
-        )
+            relation_prompt = ""
+            unique_speakers = set() # 确保人物信息不重复
+            for person_tuple in who_chat_in_group:
+                person_key = (person_tuple[0], person_tuple[1]) # 使用 platform+id 作为唯一标识
+                if person_key not in unique_speakers:
+                    relation_prompt += await relationship_manager.build_relationship_info(person_tuple)
+                    unique_speakers.add(person_key)
 
-        sender_name_sign = (
-            f"<{chat_stream.platform}:{sender_info.user_id}:{sender_info.user_nickname}:{sender_info.user_cardname}>"
-        )
+            relation_prompt_all = (await global_prompt_manager.get_prompt_async("relationship_prompt")).format(
+                relation_prompt, sender_info.user_nickname
+            )
 
-        # prompt = ""
-        # # prompt += f"麦麦的总体想法是：{self.main_heartflow_info}\n\n"
-        # if tool_result.get("used_tools", False):
-        #     prompt += f"{collected_info}\n"
-        # prompt += f"{relation_prompt_all}\n"
-        # prompt += f"{prompt_personality}\n"
-        # prompt += f"刚刚你的想法是{current_thinking_info}。如果有新的内容，记得转换话题\n"
-        # prompt += "-----------------------------------\n"
-        # prompt += f"现在你正在上网，和qq群里的网友们聊天，群里正在聊的话题是：{chat_observe_info}\n"
-        # prompt += f"你现在{mood_info}\n"
-        # prompt += f"你注意到{sender_name}刚刚说：{message_txt}\n"
-        # prompt += "现在你接下去继续思考，产生新的想法，不要分点输出，输出连贯的内心独白"
-        # prompt += "思考时可以想想如何对群聊内容进行回复。回复的要求是：平淡一些，简短一些，说中文，尽量不要说你说过的话\n"
-        # prompt += "请注意不要输出多余内容(包括前后缀，冒号和引号，括号， 表情，等)，不要带有括号和动作描写"
-        # prompt += f"记得结合上述的消息，生成内心想法，文字不要浮夸，注意你就是{self.bot_name}，{self.bot_name}指的就是你。"
+            sender_name_sign = (
+                f"<{chat_stream.platform}:{sender_info.user_id}:{sender_info.user_nickname}:{sender_info.user_cardname or 'NoCard'}>"
+            )
 
-        time_now = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
+            time_now = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
 
-        prompt = (await global_prompt_manager.get_prompt_async("sub_heartflow_prompt_before")).format(
-            extra_info_prompt,
-            # prompt_schedule,
-            relation_prompt_all,
-            prompt_personality,
-            current_thinking_info,
-            time_now,
-            chat_observe_info,
-            mood_info,
-            sender_name_sign,
-            message_txt,
-            self.bot_name,
-        )
+            prompt = (await global_prompt_manager.get_prompt_async("sub_heartflow_prompt_before")).format(
+                extra_info=extra_info_prompt,
+                relation_prompt_all=relation_prompt_all,
+                prompt_personality=prompt_personality,
+                current_thinking_info=current_thinking_info,
+                time_now=time_now,
+                chat_observe_info=chat_observe_info,
+                mood_info=mood_info,
+                sender_name=sender_name_sign,
+                message_txt=message_txt,
+                bot_name=self.bot_name,
+            )
 
-        prompt = await relationship_manager.convert_all_person_sign_to_person_name(prompt)
-        prompt = parse_text_timestamps(prompt, mode="lite")
+            prompt = await relationship_manager.convert_all_person_sign_to_person_name(prompt)
+            prompt = parse_text_timestamps(prompt, mode="lite")
 
-        try:
-            response, reasoning_content = await self.llm_model.generate_response_async(prompt)
-        except Exception as e:
-            logger.error(f"回复前内心独白获取失败: {e}")
-            response = ""
-        self.update_current_mind(response)
+            logger.debug(f"[{self.subheartflow_id}] Thinking Prompt:\n{prompt}")
 
-        self.current_mind = response
+            try:
+                response, reasoning_content = await self.llm_model.generate_response_async(prompt)
+                if not response: # 如果 LLM 返回空，给一个默认想法
+                    response = "(不知道该想些什么...)"
+                    logger.warning(f"[{self.subheartflow_id}] LLM returned empty response for thinking.")
+            except Exception as e:
+                logger.error(f"[{self.subheartflow_id}] 内心独白获取失败: {e}")
+                response = "(思考时发生错误...)" # 错误时的默认想法
+
+            self.update_current_mind(response)
+
+            # self.current_mind 已经在 update_current_mind 中更新
+
+            logger.info(f"[{self.subheartflow_id}] 思考前脑内状态：{self.current_mind}")
+            return self.current_mind, self.past_mind
 
-        logger.info(f"prompt:\n{prompt}\n")
-        logger.info(f"麦麦的思考前脑内状态：{self.current_mind}")
-        return self.current_mind, self.past_mind
-    
     async def do_thinking_after_observe(
         self, message_txt: str, sender_info: UserInfo, chat_stream: ChatStream, extra_info: str, obs_id: int = None
     ):
@@ -337,7 +370,6 @@ class SubHeartflow:
             f"<{chat_stream.platform}:{sender_info.user_id}:{sender_info.user_nickname}:{sender_info.user_cardname}>"
         )
 
-
         time_now = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
 
         prompt = (await global_prompt_manager.get_prompt_async("sub_heartflow_prompt_after_observe")).format(
@@ -436,6 +468,24 @@ class SubHeartflow:
         self.past_mind.append(self.current_mind)
         self.current_mind = response
 
+    async def check_reply_trigger(self) -> bool:
+        """根据观察到的信息和内部状态，判断是否应该触发一次回复。
+           TODO: 实现具体的判断逻辑。
+           例如：检查 self.observations[0].now_message_info 是否包含提及、问题，
+           或者 self.current_mind 中是否包含强烈的回复意图等。
+        """
+        # Placeholder: 目前始终返回 False，需要后续实现
+        logger.trace(f"[{self.subheartflow_id}] check_reply_trigger called. (Logic Pending)")
+        # --- 实现触发逻辑 --- #
+        # 示例：如果观察到的最新消息包含自己的名字，则有一定概率触发
+        # observation = self._get_primary_observation()
+        # if observation and self.bot_name in observation.now_message_info[-100:]: # 检查最后100个字符
+        #     if random.random() < 0.3: # 30% 概率触发
+        #         logger.info(f"[{self.subheartflow_id}] Triggering reply based on mention.")
+        #         return True
+        # ------------------ #
+        return False # 默认不触发
+
 
 init_prompt()
 # subheartflow = SubHeartflow()