feat(chat): 实现动态消息分发系统和消息打断机制

添加基于focus_energy的动态消息分发周期调整功能，根据聊天流兴趣度智能调整检查间隔
实现消息打断系统，允许高优先级消息打断正在处理的任务
重构ChatStream类，引入动态兴趣度计算系统，包括消息兴趣度统计和用户关系评分
扩展数据库模型和配置系统以支持新功能，增加相关配置项
更新版本号至0.11.0-alpha-1以反映重大功能更新

src/chat/message_manager/message_manager.py

@@ -4,6 +4,7 @@
 """
 
 import asyncio
+import random
 import time
 import traceback
 from typing import Dict, Optional, Any, TYPE_CHECKING
@@ -16,6 +17,7 @@ from src.chat.planner_actions.action_manager import ChatterActionManager
 from src.plugin_system.base.component_types import ChatMode
 from .sleep_manager.sleep_manager import SleepManager
 from .sleep_manager.wakeup_manager import WakeUpManager
+from src.config.config import global_config
 
 if TYPE_CHECKING:
     from src.common.data_models.message_manager_data_model import StreamContext
@@ -69,7 +71,7 @@ class MessageManager:
         # 停止管理器任务
         if self.manager_task and not self.manager_task.done():
             self.manager_task.cancel()
-        
+
         await self.wakeup_manager.stop()
 
         logger.info("消息管理器已停止")
@@ -88,14 +90,22 @@ class MessageManager:
         logger.debug(f"添加消息到聊天流 {stream_id}: {message.message_id}")
 
     async def _manager_loop(self):
-        """管理器主循环"""
+        """管理器主循环 - 独立聊天流分发周期版本"""
         while self.is_running:
             try:
                 # 更新睡眠状态
                 await self.sleep_manager.update_sleep_state(self.wakeup_manager)
-                
+
-                await self._check_all_streams()
+                # 执行独立分发周期的检查
-                await asyncio.sleep(self.check_interval)
+                await self._check_streams_with_individual_intervals()
+
+                # 计算下次检查时间（使用最小间隔或固定间隔）
+                if global_config.chat.dynamic_distribution_enabled:
+                    next_check_delay = self._calculate_next_manager_delay()
+                else:
+                    next_check_delay = self.check_interval
+
+                await asyncio.sleep(next_check_delay)
             except asyncio.CancelledError:
                 break
             except Exception as e:
@@ -138,12 +148,14 @@ class MessageManager:
             unread_messages = context.get_unread_messages()
             if not unread_messages:
                 return
-            
+
+            # 检查是否需要打断现有处理
+            await self._check_and_handle_interruption(context, stream_id)
+
             # --- 睡眠状态检查 ---
-            from .sleep_manager.sleep_state import SleepState
             if self.sleep_manager.is_sleeping():
                 logger.info(f"Bot正在睡觉，检查聊天流 {stream_id} 是否有唤醒触发器。")
-                
+
                 was_woken_up = False
                 is_private = context.is_private_chat()
 
@@ -152,12 +164,12 @@ class MessageManager:
                     if is_private or is_mentioned:
                         if self.wakeup_manager.add_wakeup_value(is_private, is_mentioned):
                             was_woken_up = True
-                            break # 一旦被吵醒，就跳出循环并处理消息
+                            break  # 一旦被吵醒，就跳出循环并处理消息
-                
+
                 if not was_woken_up:
                     logger.debug(f"聊天流 {stream_id} 中没有唤醒触发器，保持消息未读状态。")
-                    return # 退出，不处理消息
+                    return  # 退出，不处理消息
-                
+
                 logger.info(f"Bot被聊天流 {stream_id} 中的消息吵醒，继续处理。")
             # --- 睡眠状态检查结束 ---
 
@@ -252,6 +264,345 @@ class MessageManager:
             del self.stream_contexts[stream_id]
             logger.info(f"清理不活跃聊天流: {stream_id}")
 
+    async def _check_and_handle_interruption(self, context: StreamContext, stream_id: str):
+        """检查并处理消息打断"""
+        if not global_config.chat.interruption_enabled:
+            return
+
+        # 检查是否有正在进行的处理任务
+        if context.processing_task and not context.processing_task.done():
+            # 计算打断概率
+            interruption_probability = context.calculate_interruption_probability(
+                global_config.chat.interruption_max_limit, global_config.chat.interruption_probability_factor
+            )
+
+            # 根据概率决定是否打断
+            if random.random() < interruption_probability:
+                logger.info(f"聊天流 {stream_id} 触发消息打断，打断概率: {interruption_probability:.2f}")
+
+                # 取消现有任务
+                context.processing_task.cancel()
+                try:
+                    await context.processing_task
+                except asyncio.CancelledError:
+                    pass
+
+                # 增加打断计数并应用afc阈值降低
+                context.increment_interruption_count()
+                context.apply_interruption_afc_reduction(global_config.chat.interruption_afc_reduction)
+                logger.info(
+                    f"聊天流 {stream_id} 已打断，当前打断次数: {context.interruption_count}/{global_config.chat.interruption_max_limit}, afc阈值调整: {context.get_afc_threshold_adjustment()}"
+                )
+            else:
+                logger.debug(f"聊天流 {stream_id} 未触发打断，打断概率: {interruption_probability:.2f}")
+
+    def _calculate_dynamic_distribution_interval(self) -> float:
+        """根据所有活跃聊天流的focus_energy动态计算分发周期"""
+        if not global_config.chat.dynamic_distribution_enabled:
+            return self.check_interval  # 使用固定间隔
+
+        if not self.stream_contexts:
+            return self.check_interval  # 默认间隔
+
+        # 计算活跃流的平均focus_energy
+        active_streams = [ctx for ctx in self.stream_contexts.values() if ctx.is_active]
+        if not active_streams:
+            return self.check_interval
+
+        total_focus_energy = 0.0
+        max_focus_energy = 0.0
+        stream_count = 0
+
+        for context in active_streams:
+            if hasattr(context, 'chat_stream') and context.chat_stream:
+                focus_energy = context.chat_stream.focus_energy
+                total_focus_energy += focus_energy
+                max_focus_energy = max(max_focus_energy, focus_energy)
+                stream_count += 1
+
+        if stream_count == 0:
+            return self.check_interval
+
+        avg_focus_energy = total_focus_energy / stream_count
+
+        # 使用配置参数
+        base_interval = global_config.chat.dynamic_distribution_base_interval
+        min_interval = global_config.chat.dynamic_distribution_min_interval
+        max_interval = global_config.chat.dynamic_distribution_max_interval
+        jitter_factor = global_config.chat.dynamic_distribution_jitter_factor
+
+        # 根据平均兴趣度调整间隔
+        # 高兴趣度 -> 更频繁检查 (间隔更短)
+        # 低兴趣度 -> 较少检查 (间隔更长)
+        if avg_focus_energy >= 0.7:
+            # 高兴趣度：1-5秒
+            interval = base_interval * (1.0 - (avg_focus_energy - 0.7) * 2.0)
+        elif avg_focus_energy >= 0.4:
+            # 中等兴趣度：5-15秒
+            interval = base_interval * (1.0 + (avg_focus_energy - 0.4) * 3.33)
+        else:
+            # 低兴趣度：15-30秒
+            interval = base_interval * (3.0 + (0.4 - avg_focus_energy) * 5.0)
+
+        # 添加随机扰动避免同步
+        import random
+        jitter = random.uniform(1.0 - jitter_factor, 1.0 + jitter_factor)
+        final_interval = interval * jitter
+
+        # 限制在合理范围内
+        final_interval = max(min_interval, min(max_interval, final_interval))
+
+        logger.debug(
+            f"动态分发周期: {final_interval:.2f}s | "
+            f"平均兴趣度: {avg_focus_energy:.3f} | "
+            f"活跃流数: {stream_count}"
+        )
+
+        return final_interval
+
+    def _calculate_stream_distribution_interval(self, context: StreamContext) -> float:
+        """计算单个聊天流的分发周期 - 基于阈值感知的focus_energy"""
+        if not global_config.chat.dynamic_distribution_enabled:
+            return self.check_interval  # 使用固定间隔
+
+        # 获取该流的focus_energy（新的阈值感知版本）
+        focus_energy = 0.5  # 默认值
+        avg_message_interest = 0.5  # 默认平均兴趣度
+
+        if hasattr(context, 'chat_stream') and context.chat_stream:
+            focus_energy = context.chat_stream.focus_energy
+            # 获取平均消息兴趣度用于更精确的计算
+            if context.chat_stream.message_count > 0:
+                avg_message_interest = context.chat_stream.message_interest_total / context.chat_stream.message_count
+
+        # 获取AFC阈值用于参考，添加None值检查
+        reply_threshold = getattr(global_config.affinity_flow, 'reply_action_interest_threshold', 0.4)
+        non_reply_threshold = getattr(global_config.affinity_flow, 'non_reply_action_interest_threshold', 0.2)
+        high_match_threshold = getattr(global_config.affinity_flow, 'high_match_interest_threshold', 0.8)
+
+        # 使用配置参数
+        base_interval = global_config.chat.dynamic_distribution_base_interval
+        min_interval = global_config.chat.dynamic_distribution_min_interval
+        max_interval = global_config.chat.dynamic_distribution_max_interval
+        jitter_factor = global_config.chat.dynamic_distribution_jitter_factor
+
+        # 基于阈值感知的智能分发周期计算
+        if avg_message_interest >= high_match_threshold:
+            # 超高兴趣度：极快响应 (1-2秒)
+            interval_multiplier = 0.3 + (focus_energy - 0.7) * 2.0
+        elif avg_message_interest >= reply_threshold:
+            # 高兴趣度：快速响应 (2-6秒)
+            gap_from_reply = (avg_message_interest - reply_threshold) / (high_match_threshold - reply_threshold)
+            interval_multiplier = 0.6 + gap_from_reply * 0.4
+        elif avg_message_interest >= non_reply_threshold:
+            # 中等兴趣度：正常响应 (6-15秒)
+            gap_from_non_reply = (avg_message_interest - non_reply_threshold) / (reply_threshold - non_reply_threshold)
+            interval_multiplier = 1.2 + gap_from_non_reply * 1.8
+        else:
+            # 低兴趣度：缓慢响应 (15-30秒)
+            gap_ratio = max(0, avg_message_interest / non_reply_threshold)
+            interval_multiplier = 3.0 + (1.0 - gap_ratio) * 3.0
+
+        # 应用focus_energy微调
+        energy_adjustment = 1.0 + (focus_energy - 0.5) * 0.5
+        interval = base_interval * interval_multiplier * energy_adjustment
+
+        # 添加随机扰动避免同步
+        import random
+        jitter = random.uniform(1.0 - jitter_factor, 1.0 + jitter_factor)
+        final_interval = interval * jitter
+
+        # 限制在合理范围内
+        final_interval = max(min_interval, min(max_interval, final_interval))
+
+        # 根据兴趣度级别调整日志级别
+        if avg_message_interest >= high_match_threshold:
+            log_level = "info"
+        elif avg_message_interest >= reply_threshold:
+            log_level = "info"
+        else:
+            log_level = "debug"
+
+        log_msg = (
+            f"流 {context.stream_id} 分发周期: {final_interval:.2f}s | "
+            f"focus_energy: {focus_energy:.3f} | "
+            f"avg_interest: {avg_message_interest:.3f} | "
+            f"阈值参考: {non_reply_threshold:.2f}/{reply_threshold:.2f}/{high_match_threshold:.2f}"
+        )
+
+        if log_level == "info":
+            logger.info(log_msg)
+        else:
+            logger.debug(log_msg)
+
+        return final_interval
+
+    def _calculate_next_manager_delay(self) -> float:
+        """计算管理器下次检查的延迟时间"""
+        current_time = time.time()
+        min_delay = float('inf')
+
+        # 找到最近需要检查的流
+        for context in self.stream_contexts.values():
+            if not context.is_active:
+                continue
+
+            time_until_check = context.next_check_time - current_time
+            if time_until_check > 0:
+                min_delay = min(min_delay, time_until_check)
+            else:
+                min_delay = 0.1  # 立即检查
+                break
+
+        # 如果没有活跃流，使用默认间隔
+        if min_delay == float('inf'):
+            return self.check_interval
+
+        # 确保最小延迟
+        return max(0.1, min(min_delay, self.check_interval))
+
+    async def _check_streams_with_individual_intervals(self):
+        """检查所有达到检查时间的聊天流"""
+        current_time = time.time()
+        processed_streams = 0
+
+        for stream_id, context in self.stream_contexts.items():
+            if not context.is_active:
+                continue
+
+            # 检查是否达到检查时间
+            if current_time >= context.next_check_time:
+                # 更新检查时间
+                context.last_check_time = current_time
+
+                # 计算下次检查时间和分发周期
+                if global_config.chat.dynamic_distribution_enabled:
+                    context.distribution_interval = self._calculate_stream_distribution_interval(context)
+                else:
+                    context.distribution_interval = self.check_interval
+
+                # 设置下次检查时间
+                context.next_check_time = current_time + context.distribution_interval
+
+                # 检查未读消息
+                unread_messages = context.get_unread_messages()
+                if unread_messages:
+                    processed_streams += 1
+                    self.stats.total_unread_messages = len(unread_messages)
+
+                    # 如果没有处理任务，创建一个
+                    if not context.processing_task or context.processing_task.done():
+                        focus_energy = context.chat_stream.focus_energy if hasattr(context, 'chat_stream') and context.chat_stream else 0.5
+
+                        # 根据优先级记录日志
+                        if focus_energy >= 0.7:
+                            logger.info(
+                                f"高优先级流 {stream_id} 开始处理 | "
+                                f"focus_energy: {focus_energy:.3f} | "
+                                f"分发周期: {context.distribution_interval:.2f}s | "
+                                f"未读消息: {len(unread_messages)}"
+                            )
+                        else:
+                            logger.debug(
+                                f"流 {stream_id} 开始处理 | "
+                                f"focus_energy: {focus_energy:.3f} | "
+                                f"分发周期: {context.distribution_interval:.2f}s"
+                            )
+
+                        context.processing_task = asyncio.create_task(self._process_stream_messages(stream_id))
+
+        # 更新活跃流计数
+        active_count = sum(1 for ctx in self.stream_contexts.values() if ctx.is_active)
+        self.stats.active_streams = active_count
+
+        if processed_streams > 0:
+            logger.debug(
+                f"本次循环处理了 {processed_streams} 个流 | "
+                f"活跃流总数: {active_count}"
+            )
+
+    async def _check_all_streams_with_priority(self):
+        """按优先级检查所有聊天流，高focus_energy的流优先处理"""
+        if not self.stream_contexts:
+            return
+
+        # 获取活跃的聊天流并按focus_energy排序
+        active_streams = []
+        for stream_id, context in self.stream_contexts.items():
+            if not context.is_active:
+                continue
+
+            # 获取focus_energy，如果不存在则使用默认值
+            focus_energy = 0.5
+            if hasattr(context, 'chat_stream') and context.chat_stream:
+                focus_energy = context.chat_stream.focus_energy
+
+            # 计算流优先级分数
+            priority_score = self._calculate_stream_priority(context, focus_energy)
+            active_streams.append((priority_score, stream_id, context))
+
+        # 按优先级降序排序
+        active_streams.sort(reverse=True, key=lambda x: x[0])
+
+        # 处理排序后的流
+        active_stream_count = 0
+        total_unread = 0
+
+        for priority_score, stream_id, context in active_streams:
+            active_stream_count += 1
+
+            # 检查是否有未读消息
+            unread_messages = context.get_unread_messages()
+            if unread_messages:
+                total_unread += len(unread_messages)
+
+                # 如果没有处理任务，创建一个
+                if not context.processing_task or context.processing_task.done():
+                    context.processing_task = asyncio.create_task(self._process_stream_messages(stream_id))
+
+                    # 高优先级流的额外日志
+                    if priority_score > 0.7:
+                        logger.info(
+                            f"高优先级流 {stream_id} 开始处理 | "
+                            f"优先级: {priority_score:.3f} | "
+                            f"未读消息: {len(unread_messages)}"
+                        )
+
+        # 更新统计
+        self.stats.active_streams = active_stream_count
+        self.stats.total_unread_messages = total_unread
+
+    def _calculate_stream_priority(self, context: StreamContext, focus_energy: float) -> float:
+        """计算聊天流的优先级分数"""
+        # 基础优先级：focus_energy
+        base_priority = focus_energy
+
+        # 未读消息数量加权
+        unread_count = len(context.get_unread_messages())
+        message_count_bonus = min(unread_count * 0.1, 0.3)  # 最多30%加成
+
+        # 时间加权：最近活跃的流优先级更高
+        current_time = time.time()
+        time_since_active = current_time - context.last_check_time
+        time_penalty = max(0, 1.0 - time_since_active / 3600.0)  # 1小时内无惩罚
+
+        # 连续无回复惩罚
+        if hasattr(context, 'chat_stream') and context.chat_stream:
+            consecutive_no_reply = context.chat_stream.consecutive_no_reply
+            no_reply_penalty = max(0, 1.0 - consecutive_no_reply * 0.05)  # 每次无回复降低5%
+        else:
+            no_reply_penalty = 1.0
+
+        # 综合优先级计算
+        final_priority = (
+            base_priority * 0.6 +           # 基础兴趣度权重60%
+            message_count_bonus * 0.2 +     # 消息数量权重20%
+            time_penalty * 0.1 +            # 时间权重10%
+            no_reply_penalty * 0.1         # 回复状态权重10%
+        )
+
+        return max(0.0, min(1.0, final_priority))
+
     def _clear_all_unread_messages(self, context: StreamContext):
         """清除指定上下文中的所有未读消息，防止意外情况导致消息一直未读"""
         unread_messages = context.get_unread_messages()

src/chat/message_receive/bot.py

@@ -360,19 +360,7 @@ class ChatBot:
         return
 
     async def message_process(self, message_data: Dict[str, Any]) -> None:
-        """处理转化后的统一格式消息
+        """处理转化后的统一格式消息"""
-        这个函数本质是预处理一些数据，根据配置信息和消息内容，预处理消息，并分发到合适的消息处理器中
-        heart_flow模式：使用思维流系统进行回复
-        - 包含思维流状态管理
-        - 在回复前进行观察和状态更新
-        - 回复后更新思维流状态
-        - 消息过滤
-        - 记忆激活
-        - 意愿计算
-        - 消息生成和发送
-        - 表情包处理
-        - 性能计时
-        """
         try:
             # 首先处理可能的切片消息重组
             from src.utils.message_chunker import reassembler
@@ -464,7 +452,8 @@ class ChatBot:
             result = await event_manager.trigger_event(EventType.ON_MESSAGE, permission_group="SYSTEM", message=message)
             if not result.all_continue_process():
                 raise UserWarning(f"插件{result.get_summary().get('stopped_handlers', '')}于消息到达时取消了消息处理")
-
+            
+            # TODO:暂不可用
             # 确认从接口发来的message是否有自定义的prompt模板信息
             if message.message_info.template_info and not message.message_info.template_info.template_default:
                 template_group_name: Optional[str] = message.message_info.template_info.template_name  # type: ignore

src/chat/message_receive/chat_stream.py

@@ -83,10 +83,18 @@ class ChatStream:
         self.sleep_pressure = data.get("sleep_pressure", 0.0) if data else 0.0
         self.saved = False
         self.context: ChatMessageContext = None  # type: ignore # 用于存储该聊天的上下文信息
-        # 从配置文件中读取focus_value，如果没有则使用默认值1.0
+
-        self.focus_energy = (
+        # 动态兴趣度系统 - 重构后的focus_energy
-            data.get("focus_energy", global_config.chat.focus_value) if data else global_config.chat.focus_value
+        self.base_interest_energy = data.get("base_interest_energy", 0.5) if data else 0.5
-        )
+        self.message_interest_total = data.get("message_interest_total", 0.0) if data else 0.0
+        self.message_count = data.get("message_count", 0) if data else 0
+        self.action_count = data.get("action_count", 0) if data else 0
+        self.reply_count = data.get("reply_count", 0) if data else 0
+        self.last_interaction_time = data.get("last_interaction_time", time.time()) if data else time.time()
+        self.consecutive_no_reply = data.get("consecutive_no_reply", 0) if data else 0
+
+        # 计算动态focus_energy
+        self.focus_energy = self._calculate_dynamic_focus_energy()
         self.no_reply_consecutive = 0
         self.breaking_accumulated_interest = 0.0
 
@@ -103,6 +111,14 @@ class ChatStream:
             "sleep_pressure": self.sleep_pressure,
             "focus_energy": self.focus_energy,
             "breaking_accumulated_interest": self.breaking_accumulated_interest,
+            # 新增动态兴趣度系统字段
+            "base_interest_energy": self.base_interest_energy,
+            "message_interest_total": self.message_interest_total,
+            "message_count": self.message_count,
+            "action_count": self.action_count,
+            "reply_count": self.reply_count,
+            "last_interaction_time": self.last_interaction_time,
+            "consecutive_no_reply": self.consecutive_no_reply,
         }
 
     @classmethod
@@ -128,6 +144,148 @@ class ChatStream:
         """设置聊天消息上下文"""
         self.context = ChatMessageContext(message)
 
+    def _calculate_dynamic_focus_energy(self) -> float:
+        """动态计算聊天流的总体兴趣度"""
+        try:
+            # 基础分：平均消息兴趣度
+            avg_message_interest = self.message_interest_total / max(self.message_count, 1)
+
+            # 动作参与度：动作执行率
+            action_rate = self.action_count / max(self.message_count, 1)
+
+            # 回复活跃度：回复率
+            reply_rate = self.reply_count / max(self.message_count, 1)
+
+            # 获取用户关系分（对于私聊，群聊无效）
+            relationship_factor = self._get_user_relationship_score()
+
+            # 时间衰减因子：最近活跃度
+            current_time = time.time()
+            if not self.last_interaction_time:
+                self.last_interaction_time = current_time
+            time_since_interaction = current_time - self.last_interaction_time
+            time_decay = max(0.3, 1.0 - min(time_since_interaction / (7 * 24 * 3600), 0.7))  # 7天衰减
+
+            # 连续无回复惩罚
+            no_reply_penalty = max(0.1, 1.0 - self.consecutive_no_reply * 0.1)
+
+            # 获取AFC系统阈值，添加None值检查
+            reply_threshold = getattr(global_config.affinity_flow, 'reply_action_interest_threshold', 0.4)
+            non_reply_threshold = getattr(global_config.affinity_flow, 'non_reply_action_interest_threshold', 0.2)
+            high_match_threshold = getattr(global_config.affinity_flow, 'high_match_interest_threshold', 0.8)
+
+            # 计算与不同阈值的差距比例
+            reply_gap_ratio = max(0, (avg_message_interest - reply_threshold) / max(0.1, (1.0 - reply_threshold)))
+            non_reply_gap_ratio = max(0, (avg_message_interest - non_reply_threshold) / max(0.1, (1.0 - non_reply_threshold)))
+            high_match_gap_ratio = max(0, (avg_message_interest - high_match_threshold) / max(0.1, (1.0 - high_match_threshold)))
+
+            # 基于阈值差距比例的基础分计算
+            threshold_based_score = (
+                reply_gap_ratio * 0.6 +      # 回复阈值差距权重60%
+                non_reply_gap_ratio * 0.2 +  # 非回复阈值差距权重20%
+                high_match_gap_ratio * 0.2   # 高匹配阈值差距权重20%
+            )
+
+            # 动态权重调整：根据平均兴趣度水平调整权重分配
+            if avg_message_interest >= high_match_threshold:
+                # 高兴趣度：更注重阈值差距
+                threshold_weight = 0.7
+                activity_weight = 0.2
+                relationship_weight = 0.1
+            elif avg_message_interest >= reply_threshold:
+                # 中等兴趣度：平衡权重
+                threshold_weight = 0.5
+                activity_weight = 0.3
+                relationship_weight = 0.2
+            else:
+                # 低兴趣度：更注重活跃度提升
+                threshold_weight = 0.3
+                activity_weight = 0.5
+                relationship_weight = 0.2
+
+            # 计算活跃度得分
+            activity_score = (action_rate * 0.6 + reply_rate * 0.4)
+
+            # 综合计算：基于阈值的动态加权
+            focus_energy = (
+                threshold_based_score * threshold_weight +  # 阈值差距基础分
+                activity_score * activity_weight +            # 活跃度得分
+                relationship_factor * relationship_weight +   # 关系得分
+                self.base_interest_energy * 0.05             # 基础兴趣微调
+            ) * time_decay * no_reply_penalty
+
+            # 确保在合理范围内
+            focus_energy = max(0.1, min(1.0, focus_energy))
+
+            # 应用非线性变换增强区分度
+            if focus_energy >= 0.7:
+                # 高兴趣度区域：指数增强，更敏感
+                focus_energy = 0.7 + (focus_energy - 0.7) ** 0.8
+            elif focus_energy >= 0.4:
+                # 中等兴趣度区域：线性保持
+                pass
+            else:
+                # 低兴趣度区域：对数压缩，减少区分度
+                focus_energy = 0.4 * (focus_energy / 0.4) ** 1.2
+
+            return max(0.1, min(1.0, focus_energy))
+
+        except Exception as e:
+            logger.error(f"计算动态focus_energy失败: {e}")
+            return self.base_interest_energy
+
+    def _get_user_relationship_score(self) -> float:
+        """从外部系统获取用户关系分"""
+        try:
+            # 尝试从兴趣评分系统获取用户关系分
+            from src.plugins.built_in.affinity_flow_chatter.interest_scoring import (
+                chatter_interest_scoring_system,
+            )
+
+            if self.user_info and hasattr(self.user_info, 'user_id'):
+                return chatter_interest_scoring_system.get_user_relationship(str(self.user_info.user_id))
+        except Exception:
+            pass
+
+        # 默认基础分
+        return 0.3
+
+    def add_message_interest(self, interest_score: float):
+        """添加消息兴趣值并更新focus_energy"""
+        self.message_interest_total += interest_score
+        self.message_count += 1
+        self.last_interaction_time = time.time()
+        self.focus_energy = self._calculate_dynamic_focus_energy()
+
+    def record_action(self, is_reply: bool = False):
+        """记录动作执行"""
+        self.action_count += 1
+        if is_reply:
+            self.reply_count += 1
+            self.consecutive_no_reply = max(0, self.consecutive_no_reply - 1)
+        self.last_interaction_time = time.time()
+        self.focus_energy = self._calculate_dynamic_focus_energy()
+
+    def record_no_reply(self):
+        """记录无回复动作"""
+        self.consecutive_no_reply += 1
+        self.last_interaction_time = time.time()
+        self.focus_energy = self._calculate_dynamic_focus_energy()
+
+    def get_adjusted_focus_energy(self) -> float:
+        """获取应用了afc调整的focus_energy"""
+        try:
+            from src.chat.message_manager.message_manager import message_manager
+            if self.stream_id in message_manager.stream_contexts:
+                context = message_manager.stream_contexts[self.stream_id]
+                afc_adjustment = context.get_afc_threshold_adjustment()
+                # 对动态计算的focus_energy应用AFC调整
+                adjusted_energy = max(0.0, self.focus_energy - afc_adjustment)
+                return adjusted_energy
+        except Exception:
+            pass
+        return self.focus_energy
+
 
 class ChatManager:
     """聊天管理器，管理所有聊天流"""
@@ -364,7 +522,16 @@ class ChatManager:
                     "group_name": group_info_d["group_name"] if group_info_d else "",
                     "energy_value": s_data_dict.get("energy_value", 5.0),
                     "sleep_pressure": s_data_dict.get("sleep_pressure", 0.0),
-                    "focus_energy": s_data_dict.get("focus_energy", global_config.chat.focus_value),
+                    "focus_energy": s_data_dict.get("focus_energy", 0.5),
+                    # 新增动态兴趣度系统字段
+                    "base_interest_energy": s_data_dict.get("base_interest_energy", 0.5),
+                    "message_interest_total": s_data_dict.get("message_interest_total", 0.0),
+                    "message_count": s_data_dict.get("message_count", 0),
+                    "action_count": s_data_dict.get("action_count", 0),
+                    "reply_count": s_data_dict.get("reply_count", 0),
+                    "last_interaction_time": s_data_dict.get("last_interaction_time", time.time()),
+                    "relationship_score": s_data_dict.get("relationship_score", 0.3),
+                    "consecutive_no_reply": s_data_dict.get("consecutive_no_reply", 0),
                 }
 
                 # 根据数据库类型选择插入语句
@@ -426,7 +593,16 @@ class ChatManager:
                         "last_active_time": model_instance.last_active_time,
                         "energy_value": model_instance.energy_value,
                         "sleep_pressure": model_instance.sleep_pressure,
-                        "focus_energy": getattr(model_instance, "focus_energy", global_config.chat.focus_value),
+                        "focus_energy": getattr(model_instance, "focus_energy", 0.5),
+                        # 新增动态兴趣度系统字段 - 使用getattr提供默认值
+                        "base_interest_energy": getattr(model_instance, "base_interest_energy", 0.5),
+                        "message_interest_total": getattr(model_instance, "message_interest_total", 0.0),
+                        "message_count": getattr(model_instance, "message_count", 0),
+                        "action_count": getattr(model_instance, "action_count", 0),
+                        "reply_count": getattr(model_instance, "reply_count", 0),
+                        "last_interaction_time": getattr(model_instance, "last_interaction_time", time.time()),
+                        "relationship_score": getattr(model_instance, "relationship_score", 0.3),
+                        "consecutive_no_reply": getattr(model_instance, "consecutive_no_reply", 0),
                     }
                     loaded_streams_data.append(data_for_from_dict)
                 session.commit()

src/chat/planner_actions/action_manager.py

@@ -15,6 +15,7 @@ from src.plugin_system.base.component_types import ComponentType, ActionInfo
 from src.plugin_system.base.base_action import BaseAction
 from src.plugin_system.apis import generator_api, database_api, send_api, message_api
 
+
 logger = get_logger("action_manager")
 
 
@@ -161,6 +162,7 @@ class ChatterActionManager:
         Returns:
             执行结果
         """
+        from src.chat.message_manager.message_manager import message_manager
         try:
             logger.debug(f"🎯 [ActionManager] execute_action接收到 target_message: {target_message}")
             # 通过chat_id获取chat_stream
@@ -207,6 +209,11 @@ class ChatterActionManager:
                     thinking_id,
                     target_message,
                 )
+
+                # 如果动作执行成功且不是no_action，重置打断计数
+                if success:
+                    await self._reset_interruption_count_after_action(chat_stream.stream_id)
+
                 return {
                     "action_type": action_name,
                     "success": success,
@@ -244,6 +251,10 @@ class ChatterActionManager:
                     thinking_id,
                     [],  # actions
                 )
+
+                # 回复成功，重置打断计数
+                await self._reset_interruption_count_after_action(chat_stream.stream_id)
+
                 return {"action_type": "reply", "success": True, "reply_text": reply_text, "loop_info": loop_info}
 
         except Exception as e:
@@ -257,6 +268,20 @@ class ChatterActionManager:
                 "error": str(e),
             }
 
+    async def _reset_interruption_count_after_action(self, stream_id: str):
+        """在动作执行成功后重置打断计数"""
+        from src.chat.message_manager.message_manager import message_manager
+        try:
+            if stream_id in message_manager.stream_contexts:
+                context = message_manager.stream_contexts[stream_id]
+                if context.interruption_count > 0:
+                    old_count = context.interruption_count
+                    old_afc_adjustment = context.get_afc_threshold_adjustment()
+                    context.reset_interruption_count()
+                    logger.debug(f"动作执行成功，重置聊天流 {stream_id} 的打断计数: {old_count} -> 0, afc调整: {old_afc_adjustment} -> 0")
+        except Exception as e:
+            logger.warning(f"重置打断计数时出错: {e}")
+
     async def _handle_action(
         self, chat_stream, action, reasoning, action_data, cycle_timers, thinking_id, action_message
     ) -> tuple[bool, str, str]:

src/common/data_models/message_manager_data_model.py

@@ -11,10 +11,13 @@ from typing import List, Optional, TYPE_CHECKING
 
 from . import BaseDataModel
 from src.plugin_system.base.component_types import ChatMode, ChatType
+from src.common.logger import get_logger
 
 if TYPE_CHECKING:
     from .database_data_model import DatabaseMessages
 
+logger = get_logger("stream_context")
+
 
 class MessageStatus(Enum):
     """消息状态枚举"""
@@ -36,6 +39,13 @@ class StreamContext(BaseDataModel):
     last_check_time: float = field(default_factory=time.time)
     is_active: bool = True
     processing_task: Optional[asyncio.Task] = None
+    interruption_count: int = 0  # 打断计数器
+    last_interruption_time: float = 0.0  # 上次打断时间
+    afc_threshold_adjustment: float = 0.0  # afc阈值调整量
+
+    # 独立分发周期字段
+    next_check_time: float = field(default_factory=time.time)  # 下次检查时间
+    distribution_interval: float = 5.0  # 当前分发周期（秒）
 
     def add_message(self, message: "DatabaseMessages"):
         """添加消息到上下文"""
@@ -50,9 +60,9 @@ class StreamContext(BaseDataModel):
         # 只有在第一次添加消息时才检测聊天类型，避免后续消息改变类型
         if len(self.unread_messages) == 1:  # 只有这条消息
             # 如果消息包含群组信息，则为群聊
-            if hasattr(message, 'chat_info_group_id') and message.chat_info_group_id:
+            if hasattr(message, "chat_info_group_id") and message.chat_info_group_id:
                 self.chat_type = ChatType.GROUP
-            elif hasattr(message, 'chat_info_group_name') and message.chat_info_group_name:
+            elif hasattr(message, "chat_info_group_name") and message.chat_info_group_name:
                 self.chat_type = ChatType.GROUP
             else:
                 self.chat_type = ChatType.PRIVATE
@@ -64,7 +74,7 @@ class StreamContext(BaseDataModel):
     def set_chat_mode(self, chat_mode: ChatMode):
         """设置聊天模式"""
         self.chat_mode = chat_mode
-        
+
     def is_group_chat(self) -> bool:
         """检查是否为群聊"""
         return self.chat_type == ChatType.GROUP
@@ -82,10 +92,6 @@ class StreamContext(BaseDataModel):
         else:
             return "未知类型"
 
-    def get_unread_messages(self) -> List["DatabaseMessages"]:
-        """获取未读消息"""
-        return [msg for msg in self.unread_messages if not msg.is_read]
-
     def mark_message_as_read(self, message_id: str):
         """标记消息为已读"""
         for msg in self.unread_messages:
@@ -94,13 +100,56 @@ class StreamContext(BaseDataModel):
                 self.history_messages.append(msg)
                 self.unread_messages.remove(msg)
                 break
-     
+
+    def get_unread_messages(self) -> List["DatabaseMessages"]:
+        """获取未读消息"""
+        return [msg for msg in self.unread_messages if not msg.is_read]
+
     def get_history_messages(self, limit: int = 20) -> List["DatabaseMessages"]:
         """获取历史消息"""
         # 优先返回最近的历史消息和所有未读消息
         recent_history = self.history_messages[-limit:] if len(self.history_messages) > limit else self.history_messages
         return recent_history
 
+    def calculate_interruption_probability(self, max_limit: int, probability_factor: float) -> float:
+        """计算打断概率"""
+        if max_limit <= 0:
+            return 0.0
+
+        # 计算打断比例
+        interruption_ratio = self.interruption_count / max_limit
+
+        # 如果超过概率因子，概率下降
+        if interruption_ratio > probability_factor:
+            # 使用指数衰减，超过限制越多，概率越低
+            excess_ratio = interruption_ratio - probability_factor
+            probability = 1.0 * (0.5**excess_ratio)  # 基础概率0.5，指数衰减
+        else:
+            # 在限制内，保持较高概率
+            probability = 0.8
+
+        return max(0.0, min(1.0, probability))
+
+    def increment_interruption_count(self):
+        """增加打断计数"""
+        self.interruption_count += 1
+        self.last_interruption_time = time.time()
+
+    def reset_interruption_count(self):
+        """重置打断计数和afc阈值调整"""
+        self.interruption_count = 0
+        self.last_interruption_time = 0.0
+        self.afc_threshold_adjustment = 0.0
+
+    def apply_interruption_afc_reduction(self, reduction_value: float):
+        """应用打断导致的afc阈值降低"""
+        self.afc_threshold_adjustment += reduction_value
+        logger.debug(f"应用afc阈值降低: {reduction_value}, 总调整量: {self.afc_threshold_adjustment}")
+
+    def get_afc_threshold_adjustment(self) -> float:
+        """获取当前的afc阈值调整量"""
+        return self.afc_threshold_adjustment
+
 
 @dataclass
 class MessageManagerStats(BaseDataModel):

src/common/database/sqlalchemy_models.py

@@ -53,7 +53,15 @@ class ChatStreams(Base):
     user_cardname = Column(Text, nullable=True)
     energy_value = Column(Float, nullable=True, default=5.0)
     sleep_pressure = Column(Float, nullable=True, default=0.0)
-    focus_energy = Column(Float, nullable=True, default=1.0)
+    focus_energy = Column(Float, nullable=True, default=0.5)
+    # 动态兴趣度系统字段
+    base_interest_energy = Column(Float, nullable=True, default=0.5)
+    message_interest_total = Column(Float, nullable=True, default=0.0)
+    message_count = Column(Integer, nullable=True, default=0)
+    action_count = Column(Integer, nullable=True, default=0)
+    reply_count = Column(Integer, nullable=True, default=0)
+    last_interaction_time = Column(Float, nullable=True, default=None)
+    consecutive_no_reply = Column(Integer, nullable=True, default=0)
 
     __table_args__ = (
         Index("idx_chatstreams_stream_id", "stream_id"),

src/common/logger.py

@@ -350,6 +350,10 @@ MODULE_COLORS = {
     "memory": "\033[38;5;117m",  # 天蓝色
     "hfc": "\033[38;5;81m",  # 稍微暗一些的青色，保持可读
     "action_manager": "\033[38;5;208m",  # 橙色，不与replyer重复
+    "message_manager": "\033[38;5;27m",  # 深蓝色，消息管理器
+    "chatter_manager": "\033[38;5;129m",  # 紫色，聊天管理器
+    "chatter_interest_scoring": "\033[38;5;214m",  # 橙黄色，兴趣评分
+    "plan_executor": "\033[38;5;172m",  # 橙褐色，计划执行器
     # 关系系统
     "relation": "\033[38;5;139m",  # 柔和的紫色，不刺眼
     # 聊天相关模块
@@ -551,6 +555,10 @@ MODULE_ALIASES = {
     "llm_models": "模型",
     "person_info": "人物",
     "chat_stream": "聊天流",
+    "message_manager": "消息管理",
+    "chatter_manager": "聊天管理",
+    "chatter_interest_scoring": "兴趣评分",
+    "plan_executor": "计划执行",
     "planner": "规划器",
     "replyer": "言语",
     "config": "配置",

src/config/config.py

@@ -67,7 +67,7 @@ TEMPLATE_DIR = os.path.join(PROJECT_ROOT, "template")
 
 # 考虑到，实际上配置文件中的mai_version是不会自动更新的,所以采用硬编码
 # 对该字段的更新，请严格参照语义化版本规范：https://semver.org/lang/zh-CN/
-MMC_VERSION = "0.10.0-alpha-2"
+MMC_VERSION = "0.11.0-alpha-1"
 
 
 def get_key_comment(toml_table, key):

src/config/official_configs.py

@@ -104,6 +104,31 @@ class ChatConfig(ValidatedConfigBase):
     )
     delta_sigma: int = Field(default=120, description="采用正态分布随机时间间隔")
 
+    # 消息打断系统配置
+    interruption_enabled: bool = Field(default=True, description="是否启用消息打断系统")
+    interruption_max_limit: int = Field(default=3, ge=0, description="每个聊天流的最大打断次数")
+    interruption_probability_factor: float = Field(
+        default=0.8, ge=0.0, le=1.0, description="打断概率因子，当前打断次数/最大打断次数超过此值时触发概率下降"
+    )
+    interruption_afc_reduction: float = Field(
+        default=0.05, ge=0.0, le=1.0, description="每次连续打断降低的afc阈值数值"
+    )
+
+    # 动态消息分发系统配置
+    dynamic_distribution_enabled: bool = Field(default=True, description="是否启用动态消息分发周期调整")
+    dynamic_distribution_base_interval: float = Field(
+        default=5.0, ge=1.0, le=60.0, description="基础分发间隔（秒）"
+    )
+    dynamic_distribution_min_interval: float = Field(
+        default=1.0, ge=0.5, le=10.0, description="最小分发间隔（秒）"
+    )
+    dynamic_distribution_max_interval: float = Field(
+        default=30.0, ge=5.0, le=300.0, description="最大分发间隔（秒）"
+    )
+    dynamic_distribution_jitter_factor: float = Field(
+        default=0.2, ge=0.0, le=0.5, description="分发间隔随机扰动因子"
+    )
+
     def get_current_talk_frequency(self, chat_stream_id: Optional[str] = None) -> float:
         """
         根据当前时间和聊天流获取对应的 talk_frequency

src/main.py

@@ -4,6 +4,7 @@ import time
 import signal
 import sys
 from functools import partial
+import traceback
 from typing import Dict, Any
 
 from maim_message import MessageServer

src/mood/mood_manager.py

@@ -150,6 +150,11 @@ class ChatMood:
 
         self.last_change_time = message_time
 
+        # 更新ChatStream的兴趣度数据
+        if hasattr(self, 'chat_stream') and self.chat_stream:
+            self.chat_stream.add_message_interest(interested_rate)
+            logger.debug(f"{self.log_prefix} 已更新ChatStream兴趣度，当前focus_energy: {self.chat_stream.focus_energy:.3f}")
+
     async def regress_mood(self):
         message_time = time.time()
         message_list_before_now = get_raw_msg_by_timestamp_with_chat_inclusive(

src/plugins/built_in/affinity_flow_chatter/planner.py

@@ -125,11 +125,17 @@ class ChatterActionPlanner:
                         logger.info(f"兴趣度不足 ({latest_score.total_score:.2f})，移除回复")
                         reply_not_available = True
 
-                    # 更新情绪状态 - 使用最新消息的兴趣度
+                    # 更新情绪状态和ChatStream兴趣度数据
                     if latest_message and score > 0:
                         chat_mood = mood_manager.get_mood_by_chat_id(self.chat_id)
                         await chat_mood.update_mood_by_message(latest_message, score)
                         logger.debug(f"已更新聊天 {self.chat_id} 的情绪状态，兴趣度: {score:.3f}")
+                    elif latest_message:
+                        # 即使不更新情绪状态，也要更新ChatStream的兴趣度数据
+                        chat_mood = mood_manager.get_mood_by_chat_id(self.chat_id)
+                        if hasattr(chat_mood, 'chat_stream') and chat_mood.chat_stream:
+                            chat_mood.chat_stream.add_message_interest(score)
+                            logger.debug(f"已更新聊天 {self.chat_id} 的ChatStream兴趣度，分数: {score:.3f}")
 
             # base_threshold = self.interest_scoring.reply_threshold
             # 检查兴趣度是否达到非回复动作阈值

src/plugins/built_in/napcat_adapter_plugin/_manifest.json

@@ -11,7 +11,7 @@
   
   "host_application": {
     "min_version": "0.10.0",
-    "max_version": "0.10.0"
+    "max_version": "0.11.0"
   },
   "homepage_url": "https://github.com/Windpicker-owo/InternetSearchPlugin",
   "repository_url": "https://github.com/Windpicker-owo/InternetSearchPlugin",

src/plugins/built_in/napcat_adapter_plugin/plugin.py

@@ -299,7 +299,7 @@ class NapcatAdapterPlugin(BasePlugin):
             "name": ConfigField(type=str, default="napcat_adapter_plugin", description="插件名称"),
             "version": ConfigField(type=str, default="1.1.0", description="插件版本"),
             "config_version": ConfigField(type=str, default="1.3.1", description="配置文件版本"),
-            "enabled": ConfigField(type=bool, default=False, description="是否启用插件"),
+            "enabled": ConfigField(type=bool, default=True, description="是否启用插件"),
         },
         "inner": {
             "version": ConfigField(type=str, default="0.2.1", description="配置版本号，请勿修改"),

template/bot_config_template.toml

@@ -1,5 +1,5 @@
 [inner]
-version = "6.9.6"
+version = "7.0.2"
 
 #----以下是给开发人员阅读的，如果你只是部署了MoFox-Bot，不需要阅读----
 #如果你想要修改配置文件，请递增version的值
@@ -114,36 +114,23 @@ learn_expression = false
 learning_strength = 0.5
 
 [chat] #MoFox-Bot的聊天通用设置
-# 群聊聊天模式设置
-group_chat_mode = "auto" # 群聊聊天模式：auto-自动切换，normal-强制普通模式，focus-强制专注模式
-talk_frequency = 1 
-# MoFox-Bot活跃度，越高，麦麦回复越多
-# 专注时能更好把握发言时机，能够进行持久的连续对话
-
-focus_value = 1
-# MoFox-Bot的专注思考能力，越高越容易持续连续对话
-
-# 在专注模式下，只在被艾特或提及时才回复的群组列表
-# 这可以让你在某些群里保持“高冷”，只在被需要时才发言
-# 格式为: ["platform:group_id1", "platform:group_id2"]
-# 例如: ["qq:123456789", "qq:987654321"]
-focus_mode_quiet_groups = []
-
-# breaking模式配置
-enable_breaking_mode = true # 是否启用自动进入breaking模式，关闭后不会自动进入breaking形式
-
-# 强制私聊回复
-force_reply_private = false # 是否强制私聊回复，开启后私聊将强制回复
-
 allow_reply_self = false # 是否允许回复自己说的话
 
 max_context_size = 25 # 上下文长度
 thinking_timeout = 40 # MoFox-Bot一次回复最长思考规划时间，超过这个时间的思考会放弃（往往是api反应太慢）
-replyer_random_probability = 0.5 # 首要replyer模型被选择的概率
 
-mentioned_bot_inevitable_reply = true # 提及 bot 必然回复
+# 消息打断系统配置
-at_bot_inevitable_reply = true # @bot 或 提及bot 必然回复
+interruption_enabled = true # 是否启用消息打断系统
-# 兼容normal、focus，在focus模式下为强制移除no_reply动作
+interruption_max_limit = 3 # 每个聊天流的最大打断次数
+interruption_probability_factor = 0.8 # 打断概率因子，当前打断次数/最大打断次数超过此值时触发概率下降
+interruption_afc_reduction = 0.05 # 每次连续打断降低的afc阈值数值
+
+# 动态消息分发系统配置
+dynamic_distribution_enabled = true # 是否启用动态消息分发周期调整
+dynamic_distribution_base_interval = 5.0 # 基础分发间隔（秒）
+dynamic_distribution_min_interval = 1.0 # 最小分发间隔（秒）
+dynamic_distribution_max_interval = 30.0 # 最大分发间隔（秒）
+dynamic_distribution_jitter_factor = 0.2 # 分发间隔随机扰动因子
 
 talk_frequency_adjust = [
     ["", "8:00,1", "12:00,1.2", "18:00,1.5", "01:00,0.6"],
@@ -288,7 +275,7 @@ enable_vector_instant_memory = true # 是否启用基于向量的瞬时记忆
 memory_ban_words = [ "表情包", "图片", "回复", "聊天记录" ]
 
 [voice]
-enable_asr = false # 是否启用语音识别，启用后MoFox-Bot可以识别语音消息，启用该功能需要配置语音识别模型[model.voice]
+enable_asr = true # 是否启用语音识别，启用后MoFox-Bot可以识别语音消息，启用该功能需要配置语音识别模型[model.voice]
 
 [lpmm_knowledge] # lpmm知识库配置
 enable = false # 是否启用lpmm知识库
@@ -341,7 +328,7 @@ enable = true # 是否启用回复分割器
 split_mode = "punctuation" # 分割模式: "llm" - 由语言模型决定, "punctuation" - 基于标点符号
 max_length = 512 # 回复允许的最大长度
 max_sentence_num = 8 # 回复允许的最大句子数
-enable_kaomoji_protection = false # 是否启用颜文字保护
+enable_kaomoji_protection = true # 是否启用颜文字保护
 
 [log]
 date_style = "m-d H:i:s" # 日期格式