feat：添加了心流的配置项

src/heart_flow/heartflow.py

@@ -0,0 +1,169 @@
+from .sub_heartflow import SubHeartflow
+from .observation import ChattingObservation
+from src.plugins.moods.moods import MoodManager
+from src.plugins.models.utils_model import LLM_request
+from src.plugins.config.config import global_config
+from src.plugins.schedule.schedule_generator import bot_schedule
+import asyncio
+from src.common.logger import get_module_logger, LogConfig, HEARTFLOW_STYLE_CONFIG  # noqa: E402
+import time
+
+heartflow_config = LogConfig(
+    # 使用海马体专用样式
+    console_format=HEARTFLOW_STYLE_CONFIG["console_format"],
+    file_format=HEARTFLOW_STYLE_CONFIG["file_format"],
+)
+logger = get_module_logger("heartflow", config=heartflow_config)
+
+
+class CuttentState:
+    def __init__(self):
+        self.willing = 0
+        self.current_state_info = ""
+
+        self.mood_manager = MoodManager()
+        self.mood = self.mood_manager.get_prompt()
+
+    def update_current_state_info(self):
+        self.current_state_info = self.mood_manager.get_current_mood()
+
+
+class Heartflow:
+    def __init__(self):
+        self.current_mind = "你什么也没想"
+        self.past_mind = []
+        self.current_state: CuttentState = CuttentState()
+        self.llm_model = LLM_request(
+            model=global_config.llm_heartflow, temperature=0.6, max_tokens=1000, request_type="heart_flow"
+        )
+
+        self._subheartflows = {}
+        self.active_subheartflows_nums = 0
+
+        self.personality_info = " ".join(global_config.PROMPT_PERSONALITY)
+
+    async def _cleanup_inactive_subheartflows(self):
+        """定期清理不活跃的子心流"""
+        while True:
+            current_time = time.time()
+            inactive_subheartflows = []
+
+            # 检查所有子心流
+            for subheartflow_id, subheartflow in self._subheartflows.items():
+                if current_time - subheartflow.last_active_time > global_config.sub_heart_flow_stop_time:  # 10分钟 = 600秒
+                    inactive_subheartflows.append(subheartflow_id)
+                    logger.info(f"发现不活跃的子心流: {subheartflow_id}")
+
+            # 清理不活跃的子心流
+            for subheartflow_id in inactive_subheartflows:
+                del self._subheartflows[subheartflow_id]
+                logger.info(f"已清理不活跃的子心流: {subheartflow_id}")
+
+            await asyncio.sleep(30)  # 每分钟检查一次
+
+    async def heartflow_start_working(self):
+        # 启动清理任务
+        asyncio.create_task(self._cleanup_inactive_subheartflows())
+
+        while True:
+            # 检查是否存在子心流
+            if not self._subheartflows:
+                logger.info("当前没有子心流，等待新的子心流创建...")
+                await asyncio.sleep(30)  # 每分钟检查一次是否有新的子心流
+                continue
+
+            await self.do_a_thinking()
+            await asyncio.sleep(global_config.heart_flow_update_interval)  # 5分钟思考一次
+
+    async def do_a_thinking(self):
+        logger.debug("麦麦大脑袋转起来了")
+        self.current_state.update_current_state_info()
+
+        personality_info = self.personality_info
+        current_thinking_info = self.current_mind
+        mood_info = self.current_state.mood
+        related_memory_info = "memory"
+        sub_flows_info = await self.get_all_subheartflows_minds()
+
+        schedule_info = bot_schedule.get_current_num_task(num=4, time_info=True)
+
+        prompt = ""
+        prompt += f"你刚刚在做的事情是：{schedule_info}\n"
+        prompt += f"{personality_info}\n"
+        prompt += f"你想起来{related_memory_info}。"
+        prompt += f"刚刚你的主要想法是{current_thinking_info}。"
+        prompt += f"你还有一些小想法，因为你在参加不同的群聊天，是你正在做的事情：{sub_flows_info}\n"
+        prompt += f"你现在{mood_info}。"
+        prompt += "现在你接下去继续思考，产生新的想法，但是要基于原有的主要想法，不要分点输出，"
+        prompt += "输出连贯的内心独白，不要太长，但是记得结合上述的消息，关注新内容:"
+
+        reponse, reasoning_content = await self.llm_model.generate_response_async(prompt)
+
+        self.update_current_mind(reponse)
+
+        self.current_mind = reponse
+        logger.info(f"麦麦的总体脑内状态：{self.current_mind}")
+        # logger.info("麦麦想了想，当前活动:")
+        await bot_schedule.move_doing(self.current_mind)
+
+        for _, subheartflow in self._subheartflows.items():
+            subheartflow.main_heartflow_info = reponse
+
+    def update_current_mind(self, reponse):
+        self.past_mind.append(self.current_mind)
+        self.current_mind = reponse
+
+    async def get_all_subheartflows_minds(self):
+        sub_minds = ""
+        for _, subheartflow in self._subheartflows.items():
+            sub_minds += subheartflow.current_mind
+
+        return await self.minds_summary(sub_minds)
+
+    async def minds_summary(self, minds_str):
+        personality_info = self.personality_info
+        mood_info = self.current_state.mood
+
+        prompt = ""
+        prompt += f"{personality_info}\n"
+        prompt += f"现在{global_config.BOT_NICKNAME}的想法是：{self.current_mind}\n"
+        prompt += f"现在{global_config.BOT_NICKNAME}在qq群里进行聊天，聊天的话题如下：{minds_str}\n"
+        prompt += f"你现在{mood_info}\n"
+        prompt += """现在请你总结这些聊天内容，注意关注聊天内容对原有的想法的影响，输出连贯的内心独白
+        不要太长，但是记得结合上述的消息，要记得你的人设，关注新内容:"""
+
+        reponse, reasoning_content = await self.llm_model.generate_response_async(prompt)
+
+        return reponse
+
+    def create_subheartflow(self, subheartflow_id):
+        """
+        创建一个新的SubHeartflow实例
+        添加一个SubHeartflow实例到self._subheartflows字典中
+        并根据subheartflow_id为子心流创建一个观察对象
+        """
+        if subheartflow_id not in self._subheartflows:
+            logger.debug(f"创建 subheartflow: {subheartflow_id}")
+            subheartflow = SubHeartflow(subheartflow_id)
+            # 创建一个观察对象，目前只可以用chat_id创建观察对象
+            logger.debug(f"创建 observation: {subheartflow_id}")
+            observation = ChattingObservation(subheartflow_id)
+
+            logger.debug("添加 observation ")
+            subheartflow.add_observation(observation)
+            logger.debug("添加 observation 成功")
+            # 创建异步任务
+            logger.debug("创建异步任务")
+            asyncio.create_task(subheartflow.subheartflow_start_working())
+            logger.debug("创建异步任务 成功")
+            self._subheartflows[subheartflow_id] = subheartflow
+            logger.info("添加 subheartflow 成功")
+        return self._subheartflows[subheartflow_id]
+
+    def get_subheartflow(self, observe_chat_id):
+        """获取指定ID的SubHeartflow实例"""
+        return self._subheartflows.get(observe_chat_id)
+
+
+# 创建一个全局的管理器实例
+heartflow = Heartflow()

src/heart_flow/observation.py

@@ -0,0 +1,123 @@
+# 定义了来自外部世界的信息
+# 外部世界可以是某个聊天 不同平台的聊天 也可以是任意媒体
+from datetime import datetime
+from src.plugins.models.utils_model import LLM_request
+from src.plugins.config.config import global_config
+from src.common.database import db
+
+
+# 所有观察的基类
+class Observation:
+    def __init__(self, observe_type, observe_id):
+        self.observe_info = ""
+        self.observe_type = observe_type
+        self.observe_id = observe_id
+        self.last_observe_time = datetime.now().timestamp()  # 初始化为当前时间
+
+
+# 聊天观察
+class ChattingObservation(Observation):
+    def __init__(self, chat_id):
+        super().__init__("chat", chat_id)
+        self.chat_id = chat_id
+
+        self.talking_message = []
+        self.talking_message_str = ""
+
+        self.observe_times = 0
+
+        self.summary_count = 0  # 30秒内的更新次数
+        self.max_update_in_30s = 2  # 30秒内最多更新2次
+        self.last_summary_time = 0  # 上次更新summary的时间
+
+        self.sub_observe = None
+
+        self.llm_summary = LLM_request(
+            model=global_config.llm_observation, temperature=0.7, max_tokens=300, request_type="outer_world"
+        )
+
+    # 进行一次观察 返回观察结果observe_info
+    async def observe(self):
+        # 查找新消息，限制最多30条
+        new_messages = list(
+            db.messages.find({"chat_id": self.chat_id, "time": {"$gt": self.last_observe_time}})
+            .sort("time", 1)
+            .limit(20)
+        )  # 按时间正序排列，最多20条
+
+        if not new_messages:
+            return self.observe_info  # 没有新消息，返回上次观察结果
+
+        # 将新消息转换为字符串格式
+        new_messages_str = ""
+        for msg in new_messages:
+            if "sender_name" in msg and "content" in msg:
+                new_messages_str += f"{msg['sender_name']}: {msg['content']}\n"
+
+        # 将新消息添加到talking_message，同时保持列表长度不超过20条
+        self.talking_message.extend(new_messages)
+        if len(self.talking_message) > 20:
+            self.talking_message = self.talking_message[-20:]  # 只保留最新的20条
+        self.translate_message_list_to_str()
+
+        # 更新观察次数
+        self.observe_times += 1
+        self.last_observe_time = new_messages[-1]["time"]
+
+        # 检查是否需要更新summary
+        current_time = int(datetime.now().timestamp())
+        if current_time - self.last_summary_time >= 30:  # 如果超过30秒，重置计数
+            self.summary_count = 0
+            self.last_summary_time = current_time
+
+        if self.summary_count < self.max_update_in_30s:  # 如果30秒内更新次数小于2次
+            await self.update_talking_summary(new_messages_str)
+            self.summary_count += 1
+
+        return self.observe_info
+
+    async def carefully_observe(self):
+        # 查找新消息，限制最多40条
+        new_messages = list(
+            db.messages.find({"chat_id": self.chat_id, "time": {"$gt": self.last_observe_time}})
+            .sort("time", 1)
+            .limit(30)
+        )  # 按时间正序排列，最多30条
+
+        if not new_messages:
+            return self.observe_info  # 没有新消息，返回上次观察结果
+
+        # 将新消息转换为字符串格式
+        new_messages_str = ""
+        for msg in new_messages:
+            if "sender_name" in msg and "content" in msg:
+                new_messages_str += f"{msg['sender_name']}: {msg['content']}\n"
+
+        # 将新消息添加到talking_message，同时保持列表长度不超过30条
+        self.talking_message.extend(new_messages)
+        if len(self.talking_message) > 30:
+            self.talking_message = self.talking_message[-30:]  # 只保留最新的30条
+        self.translate_message_list_to_str()
+
+        # 更新观察次数
+        self.observe_times += 1
+        self.last_observe_time = new_messages[-1]["time"]
+
+        await self.update_talking_summary(new_messages_str)
+        return self.observe_info
+
+    async def update_talking_summary(self, new_messages_str):
+        # 基于已经有的talking_summary，和新的talking_message，生成一个summary
+        # print(f"更新聊天总结：{self.talking_summary}")
+        prompt = ""
+        prompt = f"你正在参与一个qq群聊的讨论，这个群之前在聊的内容是：{self.observe_info}\n"
+        prompt += f"现在群里的群友们产生了新的讨论，有了新的发言，具体内容如下：{new_messages_str}\n"
+        prompt += """以上是群里在进行的聊天，请你对这个聊天内容进行总结，总结内容要包含聊天的大致内容，
+        以及聊天中的一些重要信息，记得不要分点，不要太长，精简的概括成一段文本\n"""
+        prompt += "总结概括："
+        self.observe_info, reasoning_content = await self.llm_summary.generate_response_async(prompt)
+
+    def translate_message_list_to_str(self):
+        self.talking_message_str = ""
+        for message in self.talking_message:
+            self.talking_message_str += message["detailed_plain_text"]

src/heart_flow/sub_heartflow.py

@@ -0,0 +1,208 @@
+from .observation import Observation
+import asyncio
+from src.plugins.moods.moods import MoodManager
+from src.plugins.models.utils_model import LLM_request
+from src.plugins.config.config import global_config
+import re
+import time
+from src.plugins.schedule.schedule_generator import bot_schedule
+from src.plugins.memory_system.Hippocampus import HippocampusManager
+from src.common.logger import get_module_logger, LogConfig, SUB_HEARTFLOW_STYLE_CONFIG  # noqa: E402
+
+subheartflow_config = LogConfig(
+    # 使用海马体专用样式
+    console_format=SUB_HEARTFLOW_STYLE_CONFIG["console_format"],
+    file_format=SUB_HEARTFLOW_STYLE_CONFIG["file_format"],
+)
+logger = get_module_logger("subheartflow", config=subheartflow_config)
+
+
+class CuttentState:
+    def __init__(self):
+        self.willing = 0
+        self.current_state_info = ""
+
+        self.mood_manager = MoodManager()
+        self.mood = self.mood_manager.get_prompt()
+
+    def update_current_state_info(self):
+        self.current_state_info = self.mood_manager.get_current_mood()
+
+
+class SubHeartflow:
+    def __init__(self, subheartflow_id):
+        self.subheartflow_id = subheartflow_id
+
+        self.current_mind = ""
+        self.past_mind = []
+        self.current_state: CuttentState = CuttentState()
+        self.llm_model = LLM_request(
+            model=global_config.llm_sub_heartflow, temperature=0.7, max_tokens=600, request_type="sub_heart_flow"
+        )
+
+        self.main_heartflow_info = ""
+
+        self.last_reply_time = time.time()
+        self.last_active_time = time.time()  # 添加最后激活时间
+
+        if not self.current_mind:
+            self.current_mind = "你什么也没想"
+
+        self.personality_info = " ".join(global_config.PROMPT_PERSONALITY)
+
+        self.is_active = False
+
+        self.observations: list[Observation] = []
+
+    def add_observation(self, observation: Observation):
+        """添加一个新的observation对象到列表中，如果已存在相同id的observation则不添加"""
+        # 查找是否存在相同id的observation
+        for existing_obs in self.observations:
+            if existing_obs.observe_id == observation.observe_id:
+                # 如果找到相同id的observation，直接返回
+                return
+        # 如果没有找到相同id的observation，则添加新的
+        self.observations.append(observation)
+
+    def remove_observation(self, observation: Observation):
+        """从列表中移除一个observation对象"""
+        if observation in self.observations:
+            self.observations.remove(observation)
+
+    def get_all_observations(self) -> list[Observation]:
+        """获取所有observation对象"""
+        return self.observations
+
+    def clear_observations(self):
+        """清空所有observation对象"""
+        self.observations.clear()
+
+    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
+
+                observation = self.observations[0]
+                await observation.observe()
+
+                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)
+
+            # 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
+
+    async def do_a_thinking(self):
+        current_thinking_info = self.current_mind
+        mood_info = self.current_state.mood
+
+        observation = self.observations[0]
+        chat_observe_info = observation.observe_info
+        print(f"chat_observe_info：{chat_observe_info}")
+
+        # 调取记忆
+        related_memory = await HippocampusManager.get_instance().get_memory_from_text(
+            text=chat_observe_info, max_memory_num=2, max_memory_length=2, max_depth=3, fast_retrieval=False
+        )
+
+        if related_memory:
+            related_memory_info = ""
+            for memory in related_memory:
+                related_memory_info += memory[1]
+        else:
+            related_memory_info = ""
+
+        # print(f"相关记忆：{related_memory_info}")
+
+        schedule_info = bot_schedule.get_current_num_task(num=1, time_info=False)
+
+        prompt = ""
+        prompt += f"你刚刚在做的事情是：{schedule_info}\n"
+        # prompt += f"麦麦的总体想法是：{self.main_heartflow_info}\n\n"
+        prompt += f"你{self.personality_info}\n"
+        if related_memory_info:
+            prompt += f"你想起来你之前见过的回忆：{related_memory_info}。\n以上是你的回忆，不一定是目前聊天里的人说的，也不一定是现在发生的事情，请记住。\n"
+        prompt += f"刚刚你的想法是{current_thinking_info}。\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 += "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，不要太长，"
+        prompt += "但是记得结合上述的消息，要记得维持住你的人设，关注聊天和新内容，不要思考太多:"
+        reponse, reasoning_content = await self.llm_model.generate_response_async(prompt)
+
+        self.update_current_mind(reponse)
+
+        self.current_mind = reponse
+        logger.debug(f"prompt:\n{prompt}\n")
+        logger.info(f"麦麦的脑内状态：{self.current_mind}")
+
+    async def do_after_reply(self, reply_content, chat_talking_prompt):
+        # print("麦麦脑袋转起来了")
+        current_thinking_info = self.current_mind
+        mood_info = self.current_state.mood
+
+        observation = self.observations[0]
+        chat_observe_info = observation.observe_info
+
+        message_new_info = chat_talking_prompt
+        reply_info = reply_content
+        schedule_info = bot_schedule.get_current_num_task(num=1, time_info=False)
+
+        prompt = ""
+        prompt += f"你现在正在做的事情是：{schedule_info}\n"
+        prompt += f"你{self.personality_info}\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"刚刚你的想法是{current_thinking_info}。"
+        prompt += f"你现在看到了网友们发的新消息:{message_new_info}\n"
+        prompt += f"你刚刚回复了群友们:{reply_info}"
+        prompt += f"你现在{mood_info}"
+        prompt += "现在你接下去继续思考，产生新的想法，记得保留你刚刚的想法，不要分点输出，输出连贯的内心独白"
+        prompt += "不要太长，但是记得结合上述的消息，要记得你的人设，关注聊天和新内容，关注你回复的内容，不要思考太多:"
+
+        reponse, reasoning_content = await self.llm_model.generate_response_async(prompt)
+
+        self.update_current_mind(reponse)
+
+        self.current_mind = reponse
+        logger.info(f"麦麦回复后的脑内状态：{self.current_mind}")
+
+        self.last_reply_time = time.time()
+
+    async def judge_willing(self):
+        # print("麦麦闹情绪了1")
+        current_thinking_info = self.current_mind
+        mood_info = self.current_state.mood
+        # print("麦麦闹情绪了2")
+        prompt = ""
+        prompt += f"{self.personality_info}\n"
+        prompt += "现在你正在上网，和qq群里的网友们聊天"
+        prompt += f"你现在的想法是{current_thinking_info}。"
+        prompt += f"你现在{mood_info}。"
+        prompt += "现在请你思考，你想不想发言或者回复，请你输出一个数字，1-10，1表示非常不想，10表示非常想。"
+        prompt += "请你用<>包裹你的回复意愿，输出<1>表示不想回复，输出<10>表示非常想回复。请你考虑，你完全可以不回复"
+
+        response, reasoning_content = await self.llm_model.generate_response_async(prompt)
+        # 解析willing值
+        willing_match = re.search(r"<(\d+)>", response)
+        if willing_match:
+            self.current_state.willing = int(willing_match.group(1))
+        else:
+            self.current_state.willing = 0
+
+        return self.current_state.willing
+
+    def update_current_mind(self, reponse):
+        self.past_mind.append(self.current_mind)
+        self.current_mind = reponse
+
+
+# subheartflow = SubHeartflow()