refactor(chat): 重构消息管理器以使用集中式上下文管理和能量系统

- 将流上下文管理从MessageManager迁移到专门的ContextManager
- 使用统一的能量系统计算focus_energy和分发间隔
- 重构ChatStream的消息数据转换逻辑，支持更完整的数据字段
- 更新数据库模型，移除interest_degree字段，统一使用interest_value
- 集成新的兴趣度管理系统替代原有的评分系统
- 添加消息存储的interest_value修复功能

src/chat/energy_system/__init__.py

@@ -0,0 +1,28 @@
+"""
+能量系统模块
+提供稳定、高效的聊天流能量计算和管理功能
+"""
+
+from .energy_manager import (
+    EnergyManager,
+    EnergyLevel,
+    EnergyComponent,
+    EnergyCalculator,
+    InterestEnergyCalculator,
+    ActivityEnergyCalculator,
+    RecencyEnergyCalculator,
+    RelationshipEnergyCalculator,
+    energy_manager
+)
+
+__all__ = [
+    "EnergyManager",
+    "EnergyLevel",
+    "EnergyComponent",
+    "EnergyCalculator",
+    "InterestEnergyCalculator",
+    "ActivityEnergyCalculator",
+    "RecencyEnergyCalculator",
+    "RelationshipEnergyCalculator",
+    "energy_manager"
+]

src/chat/energy_system/energy_manager.py

@@ -0,0 +1,480 @@
+"""
+重构后的 focus_energy 管理系统
+提供稳定、高效的聊天流能量计算和管理功能
+"""
+
+import time
+from typing import Dict, List, Optional, Tuple, Any, Union, TypedDict
+from dataclasses import dataclass, field
+from enum import Enum
+from abc import ABC, abstractmethod
+
+from src.common.logger import get_logger
+from src.config.config import global_config
+
+logger = get_logger("energy_system")
+
+
+class EnergyLevel(Enum):
+    """能量等级"""
+    VERY_LOW = 0.1  # 非常低
+    LOW = 0.3      # 低
+    NORMAL = 0.5   # 正常
+    HIGH = 0.7     # 高
+    VERY_HIGH = 0.9 # 非常高
+
+
+@dataclass
+class EnergyComponent:
+    """能量组件"""
+    name: str
+    value: float
+    weight: float = 1.0
+    decay_rate: float = 0.05  # 衰减率
+    last_updated: float = field(default_factory=time.time)
+
+    def get_current_value(self) -> float:
+        """获取当前值（考虑时间衰减）"""
+        age = time.time() - self.last_updated
+        decay_factor = max(0.1, 1.0 - (age * self.decay_rate / (24 * 3600)))  # 按天衰减
+        return self.value * decay_factor
+
+    def update_value(self, new_value: float) -> None:
+        """更新值"""
+        self.value = max(0.0, min(1.0, new_value))
+        self.last_updated = time.time()
+
+
+class EnergyContext(TypedDict):
+    """能量计算上下文"""
+    stream_id: str
+    messages: List[Any]
+    user_id: Optional[str]
+
+
+class EnergyResult(TypedDict):
+    """能量计算结果"""
+    energy: float
+    level: EnergyLevel
+    distribution_interval: float
+    component_scores: Dict[str, float]
+    cached: bool
+
+
+class EnergyCalculator(ABC):
+    """能量计算器抽象基类"""
+
+    @abstractmethod
+    def calculate(self, context: Dict[str, Any]) -> float:
+        """计算能量值"""
+        pass
+
+    @abstractmethod
+    def get_weight(self) -> float:
+        """获取权重"""
+        pass
+
+
+class InterestEnergyCalculator(EnergyCalculator):
+    """兴趣度能量计算器"""
+
+    def calculate(self, context: Dict[str, Any]) -> float:
+        """基于消息兴趣度计算能量"""
+        messages = context.get("messages", [])
+        if not messages:
+            return 0.3
+
+        # 计算平均兴趣度
+        total_interest = 0.0
+        valid_messages = 0
+
+        for msg in messages:
+            interest_value = getattr(msg, "interest_value", None)
+            if interest_value is not None:
+                try:
+                    interest_float = float(interest_value)
+                    if 0.0 <= interest_float <= 1.0:
+                        total_interest += interest_float
+                        valid_messages += 1
+                except (ValueError, TypeError):
+                    continue
+
+        if valid_messages > 0:
+            avg_interest = total_interest / valid_messages
+            logger.debug(f"平均消息兴趣度: {avg_interest:.3f} (基于 {valid_messages} 条消息)")
+            return avg_interest
+        else:
+            return 0.3
+
+    def get_weight(self) -> float:
+        return 0.5
+
+
+class ActivityEnergyCalculator(EnergyCalculator):
+    """活跃度能量计算器"""
+
+    def __init__(self):
+        self.action_weights = {
+            "reply": 0.4,
+            "react": 0.3,
+            "mention": 0.2,
+            "other": 0.1
+        }
+
+    def calculate(self, context: Dict[str, Any]) -> float:
+        """基于活跃度计算能量"""
+        messages = context.get("messages", [])
+        if not messages:
+            return 0.2
+
+        total_score = 0.0
+        max_possible_score = len(messages) * 0.4  # 最高可能分数
+
+        for msg in messages:
+            actions = getattr(msg, "actions", [])
+            if isinstance(actions, list) and actions:
+                for action in actions:
+                    weight = self.action_weights.get(action, self.action_weights["other"])
+                    total_score += weight
+
+        if max_possible_score > 0:
+            activity_score = min(1.0, total_score / max_possible_score)
+            logger.debug(f"活跃度分数: {activity_score:.3f}")
+            return activity_score
+        else:
+            return 0.2
+
+    def get_weight(self) -> float:
+        return 0.3
+
+
+class RecencyEnergyCalculator(EnergyCalculator):
+    """最近性能量计算器"""
+
+    def calculate(self, context: Dict[str, Any]) -> float:
+        """基于最近性计算能量"""
+        messages = context.get("messages", [])
+        if not messages:
+            return 0.1
+
+        # 获取最新消息时间
+        latest_time = 0.0
+        for msg in messages:
+            msg_time = getattr(msg, "time", None)
+            if msg_time and msg_time > latest_time:
+                latest_time = msg_time
+
+        if latest_time == 0.0:
+            return 0.1
+
+        # 计算时间衰减
+        current_time = time.time()
+        age = current_time - latest_time
+
+        # 时间衰减策略：
+        # 1小时内：1.0
+        # 1-6小时：0.8
+        # 6-24小时：0.5
+        # 1-7天：0.3
+        # 7天以上：0.1
+        if age < 3600:  # 1小时内
+            recency_score = 1.0
+        elif age < 6 * 3600:  # 6小时内
+            recency_score = 0.8
+        elif age < 24 * 3600:  # 24小时内
+            recency_score = 0.5
+        elif age < 7 * 24 * 3600:  # 7天内
+            recency_score = 0.3
+        else:
+            recency_score = 0.1
+
+        logger.debug(f"最近性分数: {recency_score:.3f} (年龄: {age/3600:.1f}小时)")
+        return recency_score
+
+    def get_weight(self) -> float:
+        return 0.2
+
+
+class RelationshipEnergyCalculator(EnergyCalculator):
+    """关系能量计算器"""
+
+    def calculate(self, context: Dict[str, Any]) -> float:
+        """基于关系计算能量"""
+        user_id = context.get("user_id")
+        if not user_id:
+            return 0.3
+
+        try:
+            # 使用新的兴趣度管理系统获取用户关系分
+            from src.chat.interest_system import interest_manager
+
+            # 获取用户交互历史作为关系分的基础
+            interaction_calc = interest_manager.calculators.get(
+                interest_manager.InterestSourceType.USER_INTERACTION
+            )
+            if interaction_calc:
+                relationship_score = interaction_calc.calculate({"user_id": user_id})
+                logger.debug(f"用户关系分数: {relationship_score:.3f}")
+                return max(0.0, min(1.0, relationship_score))
+            else:
+                # 默认基础分
+                return 0.3
+        except Exception:
+            # 默认基础分
+            return 0.3
+
+    def get_weight(self) -> float:
+        return 0.1
+
+
+class EnergyManager:
+    """能量管理器 - 统一管理所有能量计算"""
+
+    def __init__(self) -> None:
+        self.calculators: List[EnergyCalculator] = [
+            InterestEnergyCalculator(),
+            ActivityEnergyCalculator(),
+            RecencyEnergyCalculator(),
+            RelationshipEnergyCalculator(),
+        ]
+
+        # 能量缓存
+        self.energy_cache: Dict[str, Tuple[float, float]] = {}  # stream_id -> (energy, timestamp)
+        self.cache_ttl: int = 60  # 1分钟缓存
+
+        # AFC阈值配置
+        self.thresholds: Dict[str, float] = {
+            "high_match": 0.8,
+            "reply": 0.4,
+            "non_reply": 0.2
+        }
+
+        # 统计信息
+        self.stats: Dict[str, Union[int, float, str]] = {
+            "total_calculations": 0,
+            "cache_hits": 0,
+            "cache_misses": 0,
+            "average_calculation_time": 0.0,
+            "last_threshold_update": time.time(),
+        }
+
+        # 从配置加载阈值
+        self._load_thresholds_from_config()
+
+        logger.info("能量管理器初始化完成")
+
+    def _load_thresholds_from_config(self) -> None:
+        """从配置加载AFC阈值"""
+        try:
+            if hasattr(global_config, "affinity_flow") and global_config.affinity_flow is not None:
+                self.thresholds["high_match"] = getattr(global_config.affinity_flow, "high_match_interest_threshold", 0.8)
+                self.thresholds["reply"] = getattr(global_config.affinity_flow, "reply_action_interest_threshold", 0.4)
+                self.thresholds["non_reply"] = getattr(global_config.affinity_flow, "non_reply_action_interest_threshold", 0.2)
+
+                # 确保阈值关系合理
+                self.thresholds["high_match"] = max(self.thresholds["high_match"], self.thresholds["reply"] + 0.1)
+                self.thresholds["reply"] = max(self.thresholds["reply"], self.thresholds["non_reply"] + 0.1)
+
+                self.stats["last_threshold_update"] = time.time()
+                logger.info(f"加载AFC阈值: {self.thresholds}")
+        except Exception as e:
+            logger.warning(f"加载AFC阈值失败，使用默认值: {e}")
+
+    def calculate_focus_energy(self, stream_id: str, messages: List[Any], user_id: Optional[str] = None) -> float:
+        """计算聊天流的focus_energy"""
+        start_time = time.time()
+
+        # 更新统计
+        self.stats["total_calculations"] += 1
+
+        # 检查缓存
+        if stream_id in self.energy_cache:
+            cached_energy, cached_time = self.energy_cache[stream_id]
+            if time.time() - cached_time < self.cache_ttl:
+                self.stats["cache_hits"] += 1
+                logger.debug(f"使用缓存能量: {stream_id} = {cached_energy:.3f}")
+                return cached_energy
+        else:
+            self.stats["cache_misses"] += 1
+
+        # 构建计算上下文
+        context: EnergyContext = {
+            "stream_id": stream_id,
+            "messages": messages,
+            "user_id": user_id,
+        }
+
+        # 计算各组件能量
+        component_scores: Dict[str, float] = {}
+        total_weight = 0.0
+
+        for calculator in self.calculators:
+            try:
+                score = calculator.calculate(context)
+                weight = calculator.get_weight()
+
+                component_scores[calculator.__class__.__name__] = score
+                total_weight += weight
+
+                logger.debug(f"{calculator.__class__.__name__} 能量: {score:.3f} (权重: {weight:.3f})")
+
+            except Exception as e:
+                logger.warning(f"计算 {calculator.__class__.__name__} 能量失败: {e}")
+
+        # 加权计算总能量
+        if total_weight > 0:
+            total_energy = 0.0
+            for calculator in self.calculators:
+                if calculator.__class__.__name__ in component_scores:
+                    score = component_scores[calculator.__class__.__name__]
+                    weight = calculator.get_weight()
+                    total_energy += score * (weight / total_weight)
+        else:
+            total_energy = 0.5
+
+        # 应用阈值调整和变换
+        final_energy = self._apply_threshold_adjustment(total_energy)
+
+        # 缓存结果
+        self.energy_cache[stream_id] = (final_energy, time.time())
+
+        # 清理过期缓存
+        self._cleanup_cache()
+
+        # 更新平均计算时间
+        calculation_time = time.time() - start_time
+        total_calculations = self.stats["total_calculations"]
+        self.stats["average_calculation_time"] = (
+            (self.stats["average_calculation_time"] * (total_calculations - 1) + calculation_time)
+            / total_calculations
+        )
+
+        logger.info(f"聊天流 {stream_id} 最终能量: {final_energy:.3f} (原始: {total_energy:.3f}, 耗时: {calculation_time:.3f}s)")
+        return final_energy
+
+    def _apply_threshold_adjustment(self, energy: float) -> float:
+        """应用阈值调整和变换"""
+        # 获取参考阈值
+        high_threshold = self.thresholds["high_match"]
+        reply_threshold = self.thresholds["reply"]
+
+        # 计算与阈值的相对位置
+        if energy >= high_threshold:
+            # 高能量区域：指数增强
+            adjusted = 0.7 + (energy - 0.7) ** 0.8
+        elif energy >= reply_threshold:
+            # 中等能量区域：线性保持
+            adjusted = energy
+        else:
+            # 低能量区域：对数压缩
+            adjusted = 0.4 * (energy / 0.4) ** 1.2
+
+        # 确保在合理范围内
+        return max(0.1, min(1.0, adjusted))
+
+    def get_energy_level(self, energy: float) -> EnergyLevel:
+        """获取能量等级"""
+        if energy >= EnergyLevel.VERY_HIGH.value:
+            return EnergyLevel.VERY_HIGH
+        elif energy >= EnergyLevel.HIGH.value:
+            return EnergyLevel.HIGH
+        elif energy >= EnergyLevel.NORMAL.value:
+            return EnergyLevel.NORMAL
+        elif energy >= EnergyLevel.LOW.value:
+            return EnergyLevel.LOW
+        else:
+            return EnergyLevel.VERY_LOW
+
+    def get_distribution_interval(self, energy: float) -> float:
+        """基于能量等级获取分发周期"""
+        energy_level = self.get_energy_level(energy)
+
+        # 根据能量等级确定基础分发周期
+        if energy_level == EnergyLevel.VERY_HIGH:
+            base_interval = 1.0  # 1秒
+        elif energy_level == EnergyLevel.HIGH:
+            base_interval = 3.0  # 3秒
+        elif energy_level == EnergyLevel.NORMAL:
+            base_interval = 8.0  # 8秒
+        elif energy_level == EnergyLevel.LOW:
+            base_interval = 15.0  # 15秒
+        else:
+            base_interval = 30.0  # 30秒
+
+        # 添加随机扰动避免同步
+        import random
+        jitter = random.uniform(0.8, 1.2)
+        final_interval = base_interval * jitter
+
+        # 确保在配置范围内
+        min_interval = getattr(global_config.chat, "dynamic_distribution_min_interval", 1.0)
+        max_interval = getattr(global_config.chat, "dynamic_distribution_max_interval", 60.0)
+
+        return max(min_interval, min(max_interval, final_interval))
+
+    def invalidate_cache(self, stream_id: str) -> None:
+        """失效指定流的缓存"""
+        if stream_id in self.energy_cache:
+            del self.energy_cache[stream_id]
+            logger.debug(f"已清除聊天流 {stream_id} 的能量缓存")
+
+    def _cleanup_cache(self) -> None:
+        """清理过期缓存"""
+        current_time = time.time()
+        expired_keys = [
+            stream_id for stream_id, (_, timestamp) in self.energy_cache.items()
+            if current_time - timestamp > self.cache_ttl
+        ]
+
+        for key in expired_keys:
+            del self.energy_cache[key]
+
+        if expired_keys:
+            logger.debug(f"清理了 {len(expired_keys)} 个过期能量缓存")
+
+    def get_statistics(self) -> Dict[str, Any]:
+        """获取统计信息"""
+        return {
+            "cache_size": len(self.energy_cache),
+            "calculators": [calc.__class__.__name__ for calc in self.calculators],
+            "thresholds": self.thresholds,
+            "performance_stats": self.stats.copy(),
+        }
+
+    def update_thresholds(self, new_thresholds: Dict[str, float]) -> None:
+        """更新阈值"""
+        self.thresholds.update(new_thresholds)
+
+        # 确保阈值关系合理
+        self.thresholds["high_match"] = max(self.thresholds["high_match"], self.thresholds["reply"] + 0.1)
+        self.thresholds["reply"] = max(self.thresholds["reply"], self.thresholds["non_reply"] + 0.1)
+
+        self.stats["last_threshold_update"] = time.time()
+        logger.info(f"更新AFC阈值: {self.thresholds}")
+
+    def add_calculator(self, calculator: EnergyCalculator) -> None:
+        """添加计算器"""
+        self.calculators.append(calculator)
+        logger.info(f"添加能量计算器: {calculator.__class__.__name__}")
+
+    def remove_calculator(self, calculator: EnergyCalculator) -> None:
+        """移除计算器"""
+        if calculator in self.calculators:
+            self.calculators.remove(calculator)
+            logger.info(f"移除能量计算器: {calculator.__class__.__name__}")
+
+    def clear_cache(self) -> None:
+        """清空缓存"""
+        self.energy_cache.clear()
+        logger.info("清空能量缓存")
+
+    def get_cache_hit_rate(self) -> float:
+        """获取缓存命中率"""
+        total_requests = self.stats.get("cache_hits", 0) + self.stats.get("cache_misses", 0)
+        if total_requests == 0:
+            return 0.0
+        return self.stats["cache_hits"] / total_requests
+
+
+# 全局能量管理器实例
+energy_manager = EnergyManager()

src/chat/interest_system/__init__.py

@@ -1,12 +1,30 @@
 """
-机器人兴趣标签系统
-基于人设生成兴趣标签，使用embedding计算匹配度
+兴趣度系统模块
+提供统一、稳定的消息兴趣度计算和管理功能
 """
 
+from .interest_manager import (
+    InterestManager,
+    InterestSourceType,
+    InterestFactor,
+    InterestCalculator,
+    MessageContentInterestCalculator,
+    TopicInterestCalculator,
+    UserInteractionInterestCalculator,
+    interest_manager
+)
 from .bot_interest_manager import BotInterestManager, bot_interest_manager
 from src.common.data_models.bot_interest_data_model import BotInterestTag, BotPersonalityInterests, InterestMatchResult
 
 __all__ = [
+    "InterestManager",
+    "InterestSourceType",
+    "InterestFactor",
+    "InterestCalculator",
+    "MessageContentInterestCalculator",
+    "TopicInterestCalculator",
+    "UserInteractionInterestCalculator",
+    "interest_manager",
     "BotInterestManager",
     "bot_interest_manager",
     "BotInterestTag",

src/chat/interest_system/interest_manager.py

@@ -0,0 +1,430 @@
+"""
+重构后的消息兴趣值计算系统
+提供稳定、可靠的消息兴趣度计算和管理功能
+"""
+
+import time
+from typing import Dict, List, Optional, Tuple, Any, Union, TypedDict
+from dataclasses import dataclass, field
+from enum import Enum
+from abc import ABC, abstractmethod
+
+from src.common.logger import get_logger
+
+logger = get_logger("interest_system")
+
+
+class InterestSourceType(Enum):
+    """兴趣度来源类型"""
+    MESSAGE_CONTENT = "message_content"  # 消息内容
+    USER_INTERACTION = "user_interaction"  # 用户交互
+    TOPIC_RELEVANCE = "topic_relevance"  # 话题相关性
+    RELATIONSHIP_SCORE = "relationship_score"  # 关系分数
+    HISTORICAL_PATTERN = "historical_pattern"  # 历史模式
+
+
+@dataclass
+class InterestFactor:
+    """兴趣度因子"""
+    source_type: InterestSourceType
+    value: float
+    weight: float = 1.0
+    decay_rate: float = 0.1  # 衰减率
+    last_updated: float = field(default_factory=time.time)
+
+    def get_current_value(self) -> float:
+        """获取当前值（考虑时间衰减）"""
+        age = time.time() - self.last_updated
+        decay_factor = max(0.1, 1.0 - (age * self.decay_rate / (24 * 3600)))  # 按天衰减
+        return self.value * decay_factor
+
+    def update_value(self, new_value: float) -> None:
+        """更新值"""
+        self.value = max(0.0, min(1.0, new_value))
+        self.last_updated = time.time()
+
+
+class InterestCalculator(ABC):
+    """兴趣度计算器抽象基类"""
+
+    @abstractmethod
+    def calculate(self, context: Dict[str, Any]) -> float:
+        """计算兴趣度"""
+        pass
+
+    @abstractmethod
+    def get_confidence(self) -> float:
+        """获取计算置信度"""
+        pass
+
+
+class MessageData(TypedDict):
+    """消息数据类型定义"""
+    message_id: str
+    processed_plain_text: str
+    is_emoji: bool
+    is_picid: bool
+    is_mentioned: bool
+    is_command: bool
+    key_words: str
+    user_id: str
+    time: float
+
+
+class InterestContext(TypedDict):
+    """兴趣度计算上下文"""
+    stream_id: str
+    user_id: Optional[str]
+    message: MessageData
+
+
+class InterestResult(TypedDict):
+    """兴趣度计算结果"""
+    value: float
+    confidence: float
+    source_scores: Dict[InterestSourceType, float]
+    cached: bool
+
+
+class MessageContentInterestCalculator(InterestCalculator):
+    """消息内容兴趣度计算器"""
+
+    def calculate(self, context: Dict[str, Any]) -> float:
+        """基于消息内容计算兴趣度"""
+        message = context.get("message", {})
+        if not message:
+            return 0.3  # 默认值
+
+        # 提取消息特征
+        text_length = len(message.get("processed_plain_text", ""))
+        has_emoji = message.get("is_emoji", False)
+        has_image = message.get("is_picid", False)
+        is_mentioned = message.get("is_mentioned", False)
+        is_command = message.get("is_command", False)
+
+        # 基础分数
+        base_score = 0.3
+
+        # 文本长度加权
+        if text_length > 0:
+            text_score = min(0.3, text_length / 200)  # 200字符为满分
+            base_score += text_score * 0.3
+
+        # 多媒体内容加权
+        if has_emoji:
+            base_score += 0.1
+        if has_image:
+            base_score += 0.2
+
+        # 交互特征加权
+        if is_mentioned:
+            base_score += 0.2
+        if is_command:
+            base_score += 0.1
+
+        return min(1.0, base_score)
+
+    def get_confidence(self) -> float:
+        return 0.8
+
+
+class TopicInterestCalculator(InterestCalculator):
+    """话题兴趣度计算器"""
+
+    def __init__(self):
+        self.topic_interests: Dict[str, float] = {}
+        self.topic_decay_rate = 0.05  # 话题兴趣度衰减率
+
+    def update_topic_interest(self, topic: str, interest_value: float):
+        """更新话题兴趣度"""
+        current_interest = self.topic_interests.get(topic, 0.3)
+        # 平滑更新
+        new_interest = current_interest * 0.7 + interest_value * 0.3
+        self.topic_interests[topic] = max(0.0, min(1.0, new_interest))
+
+        logger.debug(f"更新话题 '{topic}' 兴趣度: {current_interest:.3f} -> {new_interest:.3f}")
+
+    def calculate(self, context: Dict[str, Any]) -> float:
+        """基于话题相关性计算兴趣度"""
+        message = context.get("message", {})
+        keywords = message.get("key_words", "[]")
+
+        try:
+            import json
+            keyword_list = json.loads(keywords) if keywords else []
+        except (json.JSONDecodeError, TypeError):
+            keyword_list = []
+
+        if not keyword_list:
+            return 0.4  # 无关键词时的默认值
+
+        # 计算相关话题的平均兴趣度
+        total_interest = 0.0
+        relevant_topics = 0
+
+        for keyword in keyword_list[:5]:  # 最多取前5个关键词
+            # 查找相关话题
+            for topic, interest in self.topic_interests.items():
+                if keyword.lower() in topic.lower() or topic.lower() in keyword.lower():
+                    total_interest += interest
+                    relevant_topics += 1
+                    break
+
+        if relevant_topics > 0:
+            return min(1.0, total_interest / relevant_topics)
+        else:
+            # 新话题，给予基础兴趣度
+            for keyword in keyword_list[:3]:
+                self.topic_interests[keyword] = 0.5
+            return 0.5
+
+    def get_confidence(self) -> float:
+        return 0.7
+
+
+class UserInteractionInterestCalculator(InterestCalculator):
+    """用户交互兴趣度计算器"""
+
+    def __init__(self):
+        self.interaction_history: List[Dict] = []
+        self.max_history_size = 100
+
+    def add_interaction(self, user_id: str, interaction_type: str, value: float):
+        """添加交互记录"""
+        self.interaction_history.append({
+            "user_id": user_id,
+            "type": interaction_type,
+            "value": value,
+            "timestamp": time.time()
+        })
+
+        # 保持历史记录大小
+        if len(self.interaction_history) > self.max_history_size:
+            self.interaction_history = self.interaction_history[-self.max_history_size:]
+
+    def calculate(self, context: Dict[str, Any]) -> float:
+        """基于用户交互历史计算兴趣度"""
+        user_id = context.get("user_id")
+        if not user_id:
+            return 0.3
+
+        # 获取该用户的最近交互记录
+        user_interactions = [
+            interaction for interaction in self.interaction_history
+            if interaction["user_id"] == user_id
+        ]
+
+        if not user_interactions:
+            return 0.3
+
+        # 计算加权平均（最近的交互权重更高）
+        total_weight = 0.0
+        weighted_sum = 0.0
+
+        for interaction in user_interactions[-20:]:  # 最近20次交互
+            age = time.time() - interaction["timestamp"]
+            weight = max(0.1, 1.0 - age / (7 * 24 * 3600))  # 7天内衰减
+
+            weighted_sum += interaction["value"] * weight
+            total_weight += weight
+
+        if total_weight > 0:
+            return min(1.0, weighted_sum / total_weight)
+        else:
+            return 0.3
+
+    def get_confidence(self) -> float:
+        return 0.6
+
+
+class InterestManager:
+    """兴趣度管理器 - 统一管理所有兴趣度计算"""
+
+    def __init__(self) -> None:
+        self.calculators: Dict[InterestSourceType, InterestCalculator] = {
+            InterestSourceType.MESSAGE_CONTENT: MessageContentInterestCalculator(),
+            InterestSourceType.TOPIC_RELEVANCE: TopicInterestCalculator(),
+            InterestSourceType.USER_INTERACTION: UserInteractionInterestCalculator(),
+        }
+
+        # 权重配置
+        self.source_weights: Dict[InterestSourceType, float] = {
+            InterestSourceType.MESSAGE_CONTENT: 0.4,
+            InterestSourceType.TOPIC_RELEVANCE: 0.3,
+            InterestSourceType.USER_INTERACTION: 0.3,
+        }
+
+        # 兴趣度缓存
+        self.interest_cache: Dict[str, Tuple[float, float]] = {}  # message_id -> (value, timestamp)
+        self.cache_ttl: int = 300  # 5分钟缓存
+
+        # 统计信息
+        self.stats: Dict[str, Union[int, float, List[str]]] = {
+            "total_calculations": 0,
+            "cache_hits": 0,
+            "cache_misses": 0,
+            "average_calculation_time": 0.0,
+            "calculator_usage": {calc_type.value: 0 for calc_type in InterestSourceType}
+        }
+
+        logger.info("兴趣度管理器初始化完成")
+
+    def calculate_message_interest(self, message: Dict[str, Any], context: Dict[str, Any]) -> float:
+        """计算消息兴趣度"""
+        start_time = time.time()
+        message_id = message.get("message_id", "")
+
+        # 更新统计
+        self.stats["total_calculations"] += 1
+
+        # 检查缓存
+        if message_id in self.interest_cache:
+            cached_value, cached_time = self.interest_cache[message_id]
+            if time.time() - cached_time < self.cache_ttl:
+                self.stats["cache_hits"] += 1
+                logger.debug(f"使用缓存兴趣度: {message_id} = {cached_value:.3f}")
+                return cached_value
+        else:
+            self.stats["cache_misses"] += 1
+
+        # 构建计算上下文
+        calc_context: Dict[str, Any] = {
+            "message": message,
+            "user_id": message.get("user_id"),
+            **context
+        }
+
+        # 计算各来源的兴趣度
+        source_scores: Dict[InterestSourceType, float] = {}
+        total_confidence = 0.0
+
+        for source_type, calculator in self.calculators.items():
+            try:
+                score = calculator.calculate(calc_context)
+                confidence = calculator.get_confidence()
+
+                source_scores[source_type] = score
+                total_confidence += confidence
+
+                # 更新计算器使用统计
+                self.stats["calculator_usage"][source_type.value] += 1
+
+                logger.debug(f"{source_type.value} 兴趣度: {score:.3f} (置信度: {confidence:.3f})")
+
+            except Exception as e:
+                logger.warning(f"计算 {source_type.value} 兴趣度失败: {e}")
+                source_scores[source_type] = 0.3
+
+        # 加权计算最终兴趣度
+        final_interest = 0.0
+        total_weight = 0.0
+
+        for source_type, score in source_scores.items():
+            weight = self.source_weights.get(source_type, 0.0)
+            final_interest += score * weight
+            total_weight += weight
+
+        if total_weight > 0:
+            final_interest /= total_weight
+
+        # 确保在合理范围内
+        final_interest = max(0.0, min(1.0, final_interest))
+
+        # 缓存结果
+        self.interest_cache[message_id] = (final_interest, time.time())
+
+        # 清理过期缓存
+        self._cleanup_cache()
+
+        # 更新平均计算时间
+        calculation_time = time.time() - start_time
+        total_calculations = self.stats["total_calculations"]
+        self.stats["average_calculation_time"] = (
+            (self.stats["average_calculation_time"] * (total_calculations - 1) + calculation_time)
+            / total_calculations
+        )
+
+        logger.info(f"消息 {message_id} 最终兴趣度: {final_interest:.3f} (耗时: {calculation_time:.3f}s)")
+        return final_interest
+
+    def update_topic_interest(self, message: Dict[str, Any], interest_value: float) -> None:
+        """更新话题兴趣度"""
+        topic_calc = self.calculators.get(InterestSourceType.TOPIC_RELEVANCE)
+        if isinstance(topic_calc, TopicInterestCalculator):
+            # 提取关键词作为话题
+            keywords = message.get("key_words", "[]")
+            try:
+                import json
+                keyword_list: List[str] = json.loads(keywords) if keywords else []
+                for keyword in keyword_list[:3]:  # 更新前3个关键词
+                    topic_calc.update_topic_interest(keyword, interest_value)
+            except (json.JSONDecodeError, TypeError):
+                pass
+
+    def add_user_interaction(self, user_id: str, interaction_type: str, value: float) -> None:
+        """添加用户交互记录"""
+        interaction_calc = self.calculators.get(InterestSourceType.USER_INTERACTION)
+        if isinstance(interaction_calc, UserInteractionInterestCalculator):
+            interaction_calc.add_interaction(user_id, interaction_type, value)
+
+    def get_topic_interests(self) -> Dict[str, float]:
+        """获取所有话题兴趣度"""
+        topic_calc = self.calculators.get(InterestSourceType.TOPIC_RELEVANCE)
+        if isinstance(topic_calc, TopicInterestCalculator):
+            return topic_calc.topic_interests.copy()
+        return {}
+
+    def _cleanup_cache(self) -> None:
+        """清理过期缓存"""
+        current_time = time.time()
+        expired_keys = [
+            message_id for message_id, (_, timestamp) in self.interest_cache.items()
+            if current_time - timestamp > self.cache_ttl
+        ]
+
+        for key in expired_keys:
+            del self.interest_cache[key]
+
+        if expired_keys:
+            logger.debug(f"清理了 {len(expired_keys)} 个过期兴趣度缓存")
+
+    def get_statistics(self) -> Dict[str, Any]:
+        """获取统计信息"""
+        return {
+            "cache_size": len(self.interest_cache),
+            "topic_count": len(self.get_topic_interests()),
+            "calculators": list(self.calculators.keys()),
+            "performance_stats": self.stats.copy(),
+        }
+
+    def add_calculator(self, source_type: InterestSourceType, calculator: InterestCalculator) -> None:
+        """添加自定义计算器"""
+        self.calculators[source_type] = calculator
+        logger.info(f"添加计算器: {source_type.value}")
+
+    def remove_calculator(self, source_type: InterestSourceType) -> None:
+        """移除计算器"""
+        if source_type in self.calculators:
+            del self.calculators[source_type]
+            logger.info(f"移除计算器: {source_type.value}")
+
+    def set_source_weight(self, source_type: InterestSourceType, weight: float) -> None:
+        """设置来源权重"""
+        self.source_weights[source_type] = max(0.0, min(1.0, weight))
+        logger.info(f"设置 {source_type.value} 权重: {weight}")
+
+    def clear_cache(self) -> None:
+        """清空缓存"""
+        self.interest_cache.clear()
+        logger.info("清空兴趣度缓存")
+
+    def get_cache_hit_rate(self) -> float:
+        """获取缓存命中率"""
+        total_requests = self.stats.get("cache_hits", 0) + self.stats.get("cache_misses", 0)
+        if total_requests == 0:
+            return 0.0
+        return self.stats["cache_hits"] / total_requests
+
+
+# 全局兴趣度管理器实例
+interest_manager = InterestManager()

src/chat/message_manager/__init__.py

@@ -1,14 +1,26 @@
 """
-消息管理模块
-管理每个聊天流的上下文信息，包含历史记录和未读消息，定期检查并处理新消息
+消息管理器模块
+提供统一的消息管理、上下文管理和分发调度功能
 """
 
 from .message_manager import MessageManager, message_manager
-from src.common.data_models.message_manager_data_model import (
-    StreamContext,
-    MessageStatus,
-    MessageManagerStats,
-    StreamStats,
+from .context_manager import StreamContextManager, context_manager
+from .distribution_manager import (
+    DistributionManager,
+    DistributionPriority,
+    DistributionTask,
+    StreamDistributionState,
+    distribution_manager
 )
 
-__all__ = ["MessageManager", "message_manager", "StreamContext", "MessageStatus", "MessageManagerStats", "StreamStats"]
+__all__ = [
+    "MessageManager",
+    "message_manager",
+    "StreamContextManager",
+    "context_manager",
+    "DistributionManager",
+    "DistributionPriority",
+    "DistributionTask",
+    "StreamDistributionState",
+    "distribution_manager"
+]

src/chat/message_manager/message_manager.py

@@ -18,6 +18,7 @@ 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
+from . import context_manager
 
 if TYPE_CHECKING:
     from src.common.data_models.message_manager_data_model import StreamContext
@@ -29,7 +30,6 @@ class MessageManager:
     """消息管理器"""
 
     def __init__(self, check_interval: float = 5.0):
-        self.stream_contexts: Dict[str, StreamContext] = {}
         self.check_interval = check_interval  # 检查间隔（秒）
         self.is_running = False
         self.manager_task: Optional[asyncio.Task] = None
@@ -45,6 +45,9 @@ class MessageManager:
         self.sleep_manager = SleepManager()
         self.wakeup_manager = WakeUpManager(self.sleep_manager)
 
+        # 初始化上下文管理器
+        self.context_manager = context_manager.context_manager
+
     async def start(self):
         """启动消息管理器"""
         if self.is_running:
@@ -54,6 +57,7 @@ class MessageManager:
         self.is_running = True
         self.manager_task = asyncio.create_task(self._manager_loop())
         await self.wakeup_manager.start()
+        await self.context_manager.start()
         logger.info("消息管理器已启动")
 
     async def stop(self):
@@ -64,48 +68,44 @@ class MessageManager:
         self.is_running = False
 
         # 停止所有流处理任务
-        for context in self.stream_contexts.values():
-            if context.processing_task and not context.processing_task.done():
-                context.processing_task.cancel()
-
-        # 停止管理器任务
+        # 注意：context_manager 会自己清理任务
         if self.manager_task and not self.manager_task.done():
             self.manager_task.cancel()
 
         await self.wakeup_manager.stop()
+        await self.context_manager.stop()
 
         logger.info("消息管理器已停止")
 
     def add_message(self, stream_id: str, message: DatabaseMessages):
         """添加消息到指定聊天流"""
-        # 获取或创建流上下文
-        if stream_id not in self.stream_contexts:
-            self.stream_contexts[stream_id] = StreamContext(stream_id=stream_id)
-            self.stats.total_streams += 1
-
-        context = self.stream_contexts[stream_id]
-        context.set_chat_mode(ChatMode.FOCUS)
-        context.add_message(message)
+        # 使用 context_manager 添加消息
+        success = self.context_manager.add_message_to_context(stream_id, message)
 
+        if success:
             logger.debug(f"添加消息到聊天流 {stream_id}: {message.message_id}")
+        else:
+            logger.warning(f"添加消息到聊天流 {stream_id} 失败")
 
     def update_message_and_refresh_energy(
         self,
         stream_id: str,
         message_id: str,
-        interest_degree: float = None,
+        interest_value: float = None,
         actions: list = None,
         should_reply: bool = None,
     ):
         """更新消息信息"""
-        if stream_id in self.stream_contexts:
-            context = self.stream_contexts[stream_id]
-            context.update_message_info(message_id, interest_degree, actions, should_reply)
+        # 使用 context_manager 更新消息信息
+        context = self.context_manager.get_stream_context(stream_id)
+        if context:
+            context.update_message_info(message_id, interest_value, actions, should_reply)
 
     def add_action_and_refresh_energy(self, stream_id: str, message_id: str, action: str):
         """添加动作到消息"""
-        if stream_id in self.stream_contexts:
-            context = self.stream_contexts[stream_id]
+        # 使用 context_manager 添加动作到消息
+        context = self.context_manager.get_stream_context(stream_id)
+        if context:
             context.add_action_to_message(message_id, action)
 
     async def _manager_loop(self):
@@ -136,19 +136,23 @@ class MessageManager:
         active_streams = 0
         total_unread = 0
 
-        for stream_id, context in self.stream_contexts.items():
-            if not context.is_active:
+        # 使用 context_manager 获取活跃的流
+        active_stream_ids = self.context_manager.get_active_streams()
+
+        for stream_id in active_stream_ids:
+            context = self.context_manager.get_stream_context(stream_id)
+            if not context:
                 continue
 
             active_streams += 1
 
             # 检查是否有未读消息
-            unread_messages = context.get_unread_messages()
+            unread_messages = self.context_manager.get_unread_messages(stream_id)
             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():
+                if not hasattr(context, 'processing_task') or not context.processing_task or context.processing_task.done():
                     context.processing_task = asyncio.create_task(self._process_stream_messages(stream_id))
 
         # 更新统计
@@ -157,14 +161,13 @@ class MessageManager:
 
     async def _process_stream_messages(self, stream_id: str):
         """处理指定聊天流的消息"""
-        if stream_id not in self.stream_contexts:
+        context = self.context_manager.get_stream_context(stream_id)
+        if not context:
             return
 
-        context = self.stream_contexts[stream_id]
-
         try:
             # 获取未读消息
-            unread_messages = context.get_unread_messages()
+            unread_messages = self.context_manager.get_unread_messages(stream_id)
             if not unread_messages:
                 return
 
@@ -205,7 +208,7 @@ class MessageManager:
 
                     # 处理结果，标记消息为已读
                     if results.get("success", False):
-                        self._clear_all_unread_messages(context)
+                        self._clear_all_unread_messages(stream_id)
                         logger.debug(f"聊天流 {stream_id} 处理成功，清除了 {len(unread_messages)} 条未读消息")
                     else:
                         logger.warning(f"聊天流 {stream_id} 处理失败: {results.get('error_message', '未知错误')}")
@@ -213,7 +216,7 @@ class MessageManager:
                 except Exception as e:
                     logger.error(f"处理聊天流 {stream_id} 时发生异常，将清除所有未读消息: {e}")
                     # 出现异常时也清除未读消息，避免重复处理
-                    self._clear_all_unread_messages(context)
+                    self._clear_all_unread_messages(stream_id)
                     raise
 
             logger.debug(f"聊天流 {stream_id} 消息处理完成")
@@ -226,35 +229,36 @@ class MessageManager:
 
     def deactivate_stream(self, stream_id: str):
         """停用聊天流"""
-        if stream_id in self.stream_contexts:
-            context = self.stream_contexts[stream_id]
+        context = self.context_manager.get_stream_context(stream_id)
+        if context:
             context.is_active = False
 
             # 取消处理任务
-            if context.processing_task and not context.processing_task.done():
+            if hasattr(context, 'processing_task') and context.processing_task and not context.processing_task.done():
                 context.processing_task.cancel()
 
             logger.info(f"停用聊天流: {stream_id}")
 
     def activate_stream(self, stream_id: str):
         """激活聊天流"""
-        if stream_id in self.stream_contexts:
-            self.stream_contexts[stream_id].is_active = True
+        context = self.context_manager.get_stream_context(stream_id)
+        if context:
+            context.is_active = True
             logger.info(f"激活聊天流: {stream_id}")
 
     def get_stream_stats(self, stream_id: str) -> Optional[StreamStats]:
         """获取聊天流统计"""
-        if stream_id not in self.stream_contexts:
+        context = self.context_manager.get_stream_context(stream_id)
+        if not context:
             return None
 
-        context = self.stream_contexts[stream_id]
         return StreamStats(
             stream_id=stream_id,
             is_active=context.is_active,
-            unread_count=len(context.get_unread_messages()),
+            unread_count=len(self.context_manager.get_unread_messages(stream_id)),
             history_count=len(context.history_messages),
             last_check_time=context.last_check_time,
-            has_active_task=bool(context.processing_task and not context.processing_task.done()),
+            has_active_task=bool(hasattr(context, 'processing_task') and context.processing_task and not context.processing_task.done()),
         )
 
     def get_manager_stats(self) -> Dict[str, Any]:
@@ -270,18 +274,9 @@ class MessageManager:
 
     def cleanup_inactive_streams(self, max_inactive_hours: int = 24):
         """清理不活跃的聊天流"""
-        current_time = time.time()
-        max_inactive_seconds = max_inactive_hours * 3600
-
-        inactive_streams = []
-        for stream_id, context in self.stream_contexts.items():
-            if current_time - context.last_check_time > max_inactive_seconds and not context.get_unread_messages():
-                inactive_streams.append(stream_id)
-
-        for stream_id in inactive_streams:
-            self.deactivate_stream(stream_id)
-            del self.stream_contexts[stream_id]
-            logger.info(f"清理不活跃聊天流: {stream_id}")
+        # 使用 context_manager 的自动清理功能
+        self.context_manager.cleanup_inactive_contexts(max_inactive_hours * 3600)
+        logger.info("已启动不活跃聊天流清理")
 
     async def _check_and_handle_interruption(self, context: StreamContext, stream_id: str):
         """检查并处理消息打断"""
@@ -330,90 +325,29 @@ class MessageManager:
                 logger.debug(f"聊天流 {stream_id} 未触发打断，打断概率: {interruption_probability:.2f}")
 
     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"""
+        """计算单个聊天流的分发周期 - 使用重构后的能量管理器"""
         if not global_config.chat.dynamic_distribution_enabled:
             return self.check_interval  # 使用固定间隔
 
+        try:
+            from src.chat.energy_system import energy_manager
             from src.plugin_system.apis.chat_api import get_chat_manager
 
+            # 获取聊天流和能量
             chat_stream = get_chat_manager().get_stream(context.stream_id)
-        # 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 chat_stream:
                 focus_energy = chat_stream.focus_energy
-            # 获取平均消息兴趣度用于更精确的计算 - 从StreamContext获取
-            history_messages = context.get_history_messages(limit=100)
-            unread_messages = context.get_unread_messages()
-            all_messages = history_messages + unread_messages
-
-            if all_messages:
-                message_interests = [msg.interest_degree for msg in all_messages if hasattr(msg, "interest_degree")]
-                avg_message_interest = sum(message_interests) / len(message_interests) if message_interests else 0.5
-
-        # 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
+                # 使用能量管理器获取分发周期
+                interval = energy_manager.get_distribution_interval(focus_energy)
+                logger.debug(f"流 {context.stream_id} 分发周期: {interval:.2f}s (能量: {focus_energy:.3f})")
+                return interval
             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
+                # 默认间隔
+                return self.check_interval
 
-        # 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
+        except Exception as e:
+            logger.error(f"计算分发周期失败: {e}")
+            return self.check_interval
 
     def _calculate_next_manager_delay(self) -> float:
         """计算管理器下次检查的延迟时间"""
@@ -421,8 +355,10 @@ class MessageManager:
         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:
+        active_stream_ids = self.context_manager.get_active_streams()
+        for stream_id in active_stream_ids:
+            context = self.context_manager.get_stream_context(stream_id)
+            if not context or not context.is_active:
                 continue
 
             time_until_check = context.next_check_time - current_time
@@ -444,8 +380,12 @@ class MessageManager:
         current_time = time.time()
         processed_streams = 0
 
-        for stream_id, context in self.stream_contexts.items():
-            if not context.is_active:
+        # 使用 context_manager 获取活跃的流
+        active_stream_ids = self.context_manager.get_active_streams()
+
+        for stream_id in active_stream_ids:
+            context = self.context_manager.get_stream_context(stream_id)
+            if not context or not context.is_active:
                 continue
 
             # 检查是否达到检查时间
@@ -463,7 +403,7 @@ class MessageManager:
                 context.next_check_time = current_time + context.distribution_interval
 
                 # 检查未读消息
-                unread_messages = context.get_unread_messages()
+                unread_messages = self.context_manager.get_unread_messages(stream_id)
                 if unread_messages:
                     processed_streams += 1
                     self.stats.total_unread_messages = len(unread_messages)
@@ -493,7 +433,7 @@ class MessageManager:
                         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)
+        active_count = len(self.context_manager.get_active_streams())
         self.stats.active_streams = active_count
 
         if processed_streams > 0:
@@ -501,13 +441,16 @@ class MessageManager:
 
     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:
+        if not self.context_manager.get_active_streams():
             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:
+        active_stream_ids = self.context_manager.get_active_streams()
+
+        for stream_id in active_stream_ids:
+            context = self.context_manager.get_stream_context(stream_id)
+            if not context or not context.is_active:
                 continue
 
             # 获取focus_energy，如果不存在则使用默认值
@@ -533,12 +476,12 @@ class MessageManager:
             active_stream_count += 1
 
             # 检查是否有未读消息
-            unread_messages = context.get_unread_messages()
+            unread_messages = self.context_manager.get_unread_messages(stream_id)
             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():
+                if not hasattr(context, 'processing_task') or 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
@@ -554,56 +497,33 @@ class MessageManager:
         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"""
-        from src.plugin_system.apis.chat_api import get_chat_manager
-
-        chat_stream = get_chat_manager().get_stream(context.stream_id)
-        # 基础优先级：focus_energy
+        """计算聊天流的优先级分数 - 简化版本，主要使用focus_energy"""
+        # 使用重构后的能量管理器，主要依赖focus_energy
         base_priority = focus_energy
 
-        # 未读消息数量加权
+        # 简单的未读消息加权
         unread_count = len(context.get_unread_messages())
-        message_count_bonus = min(unread_count * 0.1, 0.3)  # 最多30%加成
+        message_bonus = min(unread_count * 0.05, 0.2)  # 最多20%加成
 
-        # 时间加权：最近活跃的流优先级更高
+        # 简单的时间加权
         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 - 从StreamContext历史消息计算
-        if chat_stream:
-            # 计算连续无回复次数
-            consecutive_no_reply = 0
-            all_messages = context.get_history_messages(limit=50) + context.get_unread_messages()
-            for msg in reversed(all_messages):
-                if hasattr(msg, "should_reply") and msg.should_reply:
-                    if not (hasattr(msg, "actions") and "reply" in (msg.actions or [])):
-                        consecutive_no_reply += 1
-                    else:
-                        break
-            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%
-        )
+        time_bonus = max(0, 1.0 - time_since_active / 7200.0) * 0.1  # 2小时内衰减
 
+        final_priority = base_priority + message_bonus + time_bonus
         return max(0.0, min(1.0, final_priority))
 
-    def _clear_all_unread_messages(self, context: StreamContext):
+    def _clear_all_unread_messages(self, stream_id: str):
         """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()
+        unread_messages = self.context_manager.get_unread_messages(stream_id)
         if not unread_messages:
             return
 
         logger.warning(f"正在清除 {len(unread_messages)} 条未读消息")
 
-        # 将所有未读消息标记为已读并移动到历史记录
+        # 将所有未读消息标记为已读
+        context = self.context_manager.get_stream_context(stream_id)
+        if context:
             for msg in unread_messages[:]:  # 使用切片复制避免迭代时修改列表
                 try:
                     context.mark_message_as_read(msg.message_id)

src/chat/message_receive/chat_stream.py

@@ -120,186 +120,209 @@ class ChatStream:
         """设置聊天消息上下文"""
         # 将MessageRecv转换为DatabaseMessages并设置到stream_context
         from src.common.data_models.database_data_model import DatabaseMessages
+        import json
 
-        # 简化转换，实际可能需要更完整的转换逻辑
+        # 安全获取message_info中的数据
+        message_info = getattr(message, "message_info", {})
+        user_info = getattr(message_info, "user_info", {})
+        group_info = getattr(message_info, "group_info", {})
+
+        # 提取reply_to信息（从message_segment中查找reply类型的段）
+        reply_to = None
+        if hasattr(message, "message_segment") and message.message_segment:
+            reply_to = self._extract_reply_from_segment(message.message_segment)
+
+        # 完整的数据转移逻辑
         db_message = DatabaseMessages(
+            # 基础消息信息
             message_id=getattr(message, "message_id", ""),
             time=getattr(message, "time", time.time()),
-            chat_id=getattr(message, "chat_id", ""),
-            user_id=str(getattr(message.message_info, "user_info", {}).user_id)
-            if hasattr(message, "message_info") and hasattr(message.message_info, "user_info")
-            else "",
-            user_nickname=getattr(message.message_info, "user_info", {}).user_nickname
-            if hasattr(message, "message_info") and hasattr(message.message_info, "user_info")
-            else "",
-            user_platform=getattr(message.message_info, "user_info", {}).platform
-            if hasattr(message, "message_info") and hasattr(message.message_info, "user_info")
-            else "",
-            priority_mode=getattr(message, "priority_mode", None),
-            priority_info=str(getattr(message, "priority_info", None))
-            if hasattr(message, "priority_info") and message.priority_info
+            chat_id=self._generate_chat_id(message_info),
+            reply_to=reply_to,
+            # 兴趣度相关
+            interest_value=getattr(message, "interest_value", 0.0),
+            # 关键词
+            key_words=json.dumps(getattr(message, "key_words", []), ensure_ascii=False)
+            if getattr(message, "key_words", None)
             else None,
-            additional_config=getattr(getattr(message, "message_info", {}), "additional_config", None),
+            key_words_lite=json.dumps(getattr(message, "key_words_lite", []), ensure_ascii=False)
+            if getattr(message, "key_words_lite", None)
+            else None,
+            # 消息状态标记
+            is_mentioned=getattr(message, "is_mentioned", None),
+            is_at=getattr(message, "is_at", False),
+            is_emoji=getattr(message, "is_emoji", False),
+            is_picid=getattr(message, "is_picid", False),
+            is_voice=getattr(message, "is_voice", False),
+            is_video=getattr(message, "is_video", False),
+            is_command=getattr(message, "is_command", False),
+            is_notify=getattr(message, "is_notify", False),
+            # 消息内容
+            processed_plain_text=getattr(message, "processed_plain_text", ""),
+            display_message=getattr(message, "processed_plain_text", ""),  # 默认使用processed_plain_text
+            # 优先级信息
+            priority_mode=getattr(message, "priority_mode", None),
+            priority_info=json.dumps(getattr(message, "priority_info", None))
+            if getattr(message, "priority_info", None)
+            else None,
+            # 额外配置
+            additional_config=getattr(message_info, "additional_config", None),
+            # 用户信息
+            user_id=str(getattr(user_info, "user_id", "")),
+            user_nickname=getattr(user_info, "user_nickname", ""),
+            user_cardname=getattr(user_info, "user_cardname", None),
+            user_platform=getattr(user_info, "platform", ""),
+            # 群组信息
+            chat_info_group_id=getattr(group_info, "group_id", None),
+            chat_info_group_name=getattr(group_info, "group_name", None),
+            chat_info_group_platform=getattr(group_info, "platform", None),
+            # 聊天流信息
+            chat_info_user_id=str(getattr(user_info, "user_id", "")),
+            chat_info_user_nickname=getattr(user_info, "user_nickname", ""),
+            chat_info_user_cardname=getattr(user_info, "user_cardname", None),
+            chat_info_user_platform=getattr(user_info, "platform", ""),
+            chat_info_stream_id=self.stream_id,
+            chat_info_platform=self.platform,
+            chat_info_create_time=self.create_time,
+            chat_info_last_active_time=self.last_active_time,
+            # 新增兴趣度系统字段 - 添加安全处理
+            actions=self._safe_get_actions(message),
+            should_reply=getattr(message, "should_reply", False),
         )
 
         self.stream_context.set_current_message(db_message)
         self.stream_context.priority_mode = getattr(message, "priority_mode", None)
         self.stream_context.priority_info = getattr(message, "priority_info", None)
 
+        # 调试日志：记录数据转移情况
+        logger.debug(f"消息数据转移完成 - message_id: {db_message.message_id}, "
+                    f"chat_id: {db_message.chat_id}, "
+                    f"is_mentioned: {db_message.is_mentioned}, "
+                    f"is_emoji: {db_message.is_emoji}, "
+                    f"is_picid: {db_message.is_picid}, "
+                    f"interest_value: {db_message.interest_value}")
+
+    def _safe_get_actions(self, message: "MessageRecv") -> Optional[list]:
+        """安全获取消息的actions字段"""
+        try:
+            actions = getattr(message, "actions", None)
+            if actions is None:
+                return None
+
+            # 如果是字符串，尝试解析为JSON
+            if isinstance(actions, str):
+                try:
+                    import json
+                    actions = json.loads(actions)
+                except json.JSONDecodeError:
+                    logger.warning(f"无法解析actions JSON字符串: {actions}")
+                    return None
+
+            # 确保返回列表类型
+            if isinstance(actions, list):
+                # 过滤掉空值和非字符串元素
+                filtered_actions = [action for action in actions if action is not None and isinstance(action, str)]
+                return filtered_actions if filtered_actions else None
+            else:
+                logger.warning(f"actions字段类型不支持: {type(actions)}")
+                return None
+
+        except Exception as e:
+            logger.warning(f"获取actions字段失败: {e}")
+            return None
+
+    def _extract_reply_from_segment(self, segment) -> Optional[str]:
+        """从消息段中提取reply_to信息"""
+        try:
+            if hasattr(segment, "type") and segment.type == "seglist":
+                # 递归搜索seglist中的reply段
+                if hasattr(segment, "data") and segment.data:
+                    for seg in segment.data:
+                        reply_id = self._extract_reply_from_segment(seg)
+                        if reply_id:
+                            return reply_id
+            elif hasattr(segment, "type") and segment.type == "reply":
+                # 找到reply段，返回message_id
+                return str(segment.data) if segment.data else None
+        except Exception as e:
+            logger.warning(f"提取reply_to信息失败: {e}")
+        return None
+
+    def _generate_chat_id(self, message_info) -> str:
+        """生成chat_id，基于群组或用户信息"""
+        try:
+            group_info = getattr(message_info, "group_info", None)
+            user_info = getattr(message_info, "user_info", None)
+
+            if group_info and hasattr(group_info, "group_id") and group_info.group_id:
+                # 群聊：使用群组ID
+                return f"{self.platform}_{group_info.group_id}"
+            elif user_info and hasattr(user_info, "user_id") and user_info.user_id:
+                # 私聊：使用用户ID
+                return f"{self.platform}_{user_info.user_id}_private"
+            else:
+                # 默认：使用stream_id
+                return self.stream_id
+        except Exception as e:
+            logger.warning(f"生成chat_id失败: {e}")
+            return self.stream_id
+
     @property
     def focus_energy(self) -> float:
-        """动态计算的聊天流总体兴趣度，访问时自动更新"""
-        self._focus_energy = self._calculate_dynamic_focus_energy()
+        """使用重构后的能量管理器计算focus_energy"""
+        try:
+            from src.chat.energy_system import energy_manager
+
+            # 获取所有消息
+            history_messages = self.stream_context.get_history_messages(limit=global_config.chat.max_context_size)
+            unread_messages = self.stream_context.get_unread_messages()
+            all_messages = history_messages + unread_messages
+
+            # 获取用户ID
+            user_id = None
+            if self.user_info and hasattr(self.user_info, "user_id"):
+                user_id = str(self.user_info.user_id)
+
+            # 使用能量管理器计算
+            energy = energy_manager.calculate_focus_energy(
+                stream_id=self.stream_id,
+                messages=all_messages,
+                user_id=user_id
+            )
+
+            # 更新内部存储
+            self._focus_energy = energy
+
+            logger.debug(f"聊天流 {self.stream_id} 能量: {energy:.3f}")
+            return energy
+
+        except Exception as e:
+            logger.error(f"获取focus_energy失败: {e}", exc_info=True)
+            # 返回缓存的值或默认值
+            if hasattr(self, '_focus_energy'):
                 return self._focus_energy
+            else:
+                return 0.5
 
     @focus_energy.setter
     def focus_energy(self, value: float):
         """设置focus_energy值（主要用于初始化或特殊场景）"""
         self._focus_energy = max(0.0, min(1.0, value))
 
-    def _calculate_dynamic_focus_energy(self) -> float:
-        """动态计算聊天流的总体兴趣度，使用StreamContext历史消息"""
-        try:
-            # 从StreamContext获取历史消息计算统计数据
-            history_messages = self.stream_context.get_history_messages(limit=global_config.chat.max_context_size)
-            unread_messages = self.stream_context.get_unread_messages()
-            all_messages = history_messages + unread_messages
-
-            # 计算基于历史消息的统计数据
-            if all_messages:
-                # 基础分：平均消息兴趣度
-                message_interests = [msg.interest_degree for msg in all_messages if hasattr(msg, "interest_degree")]
-                avg_message_interest = sum(message_interests) / len(message_interests) if message_interests else 0.3
-
-                # 动作参与度：有动作的消息比例
-                messages_with_actions = [msg for msg in all_messages if hasattr(msg, "actions") and msg.actions]
-                action_rate = len(messages_with_actions) / len(all_messages)
-
-                # 回复活跃度：应该回复且已回复的消息比例
-                should_reply_messages = [
-                    msg for msg in all_messages if hasattr(msg, "should_reply") and msg.should_reply
-                ]
-                replied_messages = [
-                    msg for msg in should_reply_messages if hasattr(msg, "actions") and "reply" in (msg.actions or [])
-                ]
-                reply_rate = len(replied_messages) / len(should_reply_messages) if should_reply_messages else 0.0
-
-                # 获取最后交互时间
-                if all_messages:
-                    self.last_interaction_time = max(msg.time for msg in all_messages)
-
-                # 连续无回复计算：从最近的未回复消息计数
-                consecutive_no_reply = 0
-                for msg in reversed(all_messages):
-                    if hasattr(msg, "should_reply") and msg.should_reply:
-                        if not (hasattr(msg, "actions") and "reply" in (msg.actions or [])):
-                            consecutive_no_reply += 1
-                        else:
-                            break
-            else:
-                # 没有历史消息时的默认值
-                avg_message_interest = 0.3
-                action_rate = 0.0
-                reply_rate = 0.0
-                consecutive_no_reply = 0
-                self.last_interaction_time = time.time()
-
-            # 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 hasattr(self, "last_interaction_time") or 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 - 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"""
+        """从新的兴趣度管理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,
-            )
+            # 使用新的兴趣度管理系统
+            from src.chat.interest_system import interest_manager
 
             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))
+                user_id = str(self.user_info.user_id)
+                # 获取用户交互历史作为关系分的基础
+                interaction_calc = interest_manager.calculators.get(
+                    interest_manager.InterestSourceType.USER_INTERACTION
+                )
+                if interaction_calc:
+                    return interaction_calc.calculate({"user_id": user_id})
         except Exception:
             pass
 
@@ -378,12 +401,13 @@ class ChatStream:
                             chat_info_platform=db_msg.chat_info_platform,
                             chat_info_create_time=db_msg.chat_info_create_time,
                             chat_info_last_active_time=db_msg.chat_info_last_active_time,
-                            # 新增的兴趣度系统字段
-                            interest_degree=getattr(db_msg, "interest_degree", 0.0) or 0.0,
                             actions=actions,
                             should_reply=getattr(db_msg, "should_reply", False) or False,
                         )
 
+                        # 添加调试日志：检查从数据库加载的interest_value
+                        logger.debug(f"加载历史消息 {db_message.message_id} - interest_value: {db_message.interest_value}")
+
                         # 标记为已读并添加到历史消息
                         db_message.is_read = True
                         self.stream_context.history_messages.append(db_message)

src/chat/message_receive/storage.py

@@ -218,4 +218,93 @@ class MessageStorage:
             except Exception:
                 return match.group(0)
 
-        return re.sub(r"\[图片：([^\]]+)\]", replace_match, text)
+    @staticmethod
+    def update_message_interest_value(message_id: str, interest_value: float) -> None:
+        """
+        更新数据库中消息的interest_value字段
+
+        Args:
+            message_id: 消息ID
+            interest_value: 兴趣度值
+        """
+        try:
+            with get_db_session() as session:
+                # 更新消息的interest_value字段
+                stmt = update(Messages).where(Messages.message_id == message_id).values(interest_value=interest_value)
+                result = session.execute(stmt)
+                session.commit()
+
+                if result.rowcount > 0:
+                    logger.debug(f"成功更新消息 {message_id} 的interest_value为 {interest_value}")
+                else:
+                    logger.warning(f"未找到消息 {message_id}，无法更新interest_value")
+
+        except Exception as e:
+            logger.error(f"更新消息 {message_id} 的interest_value失败: {e}")
+            raise
+
+    @staticmethod
+    def fix_zero_interest_values(chat_id: str, since_time: float) -> int:
+        """
+        修复指定聊天中interest_value为0或null的历史消息记录
+
+        Args:
+            chat_id: 聊天ID
+            since_time: 从指定时间开始修复（时间戳）
+
+        Returns:
+            修复的记录数量
+        """
+        try:
+            with get_db_session() as session:
+                from sqlalchemy import select, update
+                from src.common.database.sqlalchemy_models import Messages
+
+                # 查找需要修复的记录：interest_value为0、null或很小的值
+                query = select(Messages).where(
+                    (Messages.chat_id == chat_id) &
+                    (Messages.time >= since_time) &
+                    (
+                        (Messages.interest_value == 0) |
+                        (Messages.interest_value.is_(None)) |
+                        (Messages.interest_value < 0.1)
+                    )
+                ).limit(50)  # 限制每次修复的数量，避免性能问题
+
+                messages_to_fix = session.execute(query).scalars().all()
+                fixed_count = 0
+
+                for msg in messages_to_fix:
+                    # 为这些消息设置一个合理的默认兴趣度
+                    # 可以基于消息长度、内容或其他因素计算
+                    default_interest = 0.3  # 默认中等兴趣度
+
+                    # 如果消息内容较长，可能是重要消息，兴趣度稍高
+                    if hasattr(msg, 'processed_plain_text') and msg.processed_plain_text:
+                        text_length = len(msg.processed_plain_text)
+                        if text_length > 50:  # 长消息
+                            default_interest = 0.4
+                        elif text_length > 20:  # 中等长度消息
+                            default_interest = 0.35
+
+                    # 如果是被@的消息，兴趣度更高
+                    if getattr(msg, 'is_mentioned', False):
+                        default_interest = min(default_interest + 0.2, 0.8)
+
+                    # 执行更新
+                    update_stmt = update(Messages).where(
+                        Messages.message_id == msg.message_id
+                    ).values(interest_value=default_interest)
+
+                    result = session.execute(update_stmt)
+                    if result.rowcount > 0:
+                        fixed_count += 1
+                        logger.debug(f"修复消息 {msg.message_id} 的interest_value为 {default_interest}")
+
+                session.commit()
+                logger.info(f"共修复了 {fixed_count} 条历史消息的interest_value值")
+                return fixed_count
+
+        except Exception as e:
+            logger.error(f"修复历史消息interest_value失败: {e}")
+            return 0

src/common/data_models/database_data_model.py

@@ -96,7 +96,6 @@ class DatabaseMessages(BaseDataModel):
         chat_info_create_time: float = 0.0,
         chat_info_last_active_time: float = 0.0,
         # 新增字段
-        interest_degree: float = 0.0,
         actions: Optional[list] = None,
         should_reply: bool = False,
         **kwargs: Any,
@@ -108,7 +107,6 @@ class DatabaseMessages(BaseDataModel):
         self.interest_value = interest_value
 
         # 新增字段
-        self.interest_degree = interest_degree
         self.actions = actions
         self.should_reply = should_reply
 
@@ -201,7 +199,6 @@ class DatabaseMessages(BaseDataModel):
             "selected_expressions": self.selected_expressions,
             "is_read": self.is_read,
             # 新增字段
-            "interest_degree": self.interest_degree,
             "actions": self.actions,
             "should_reply": self.should_reply,
             "user_id": self.user_info.user_id,
@@ -221,17 +218,17 @@ class DatabaseMessages(BaseDataModel):
             "chat_info_user_cardname": self.chat_info.user_info.user_cardname,
         }
 
-    def update_message_info(self, interest_degree: float = None, actions: list = None, should_reply: bool = None):
+    def update_message_info(self, interest_value: float = None, actions: list = None, should_reply: bool = None):
         """
         更新消息信息
 
         Args:
-            interest_degree: 兴趣度值
+            interest_value: 兴趣度值
             actions: 执行的动作列表
             should_reply: 是否应该回复
         """
-        if interest_degree is not None:
-            self.interest_degree = interest_degree
+        if interest_value is not None:
+            self.interest_value = interest_value
         if actions is not None:
             self.actions = actions
         if should_reply is not None:
@@ -268,7 +265,7 @@ class DatabaseMessages(BaseDataModel):
         return {
             "message_id": self.message_id,
             "time": self.time,
-            "interest_degree": self.interest_degree,
+            "interest_value": self.interest_value,
             "actions": self.actions,
             "should_reply": self.should_reply,
             "user_nickname": self.user_info.user_nickname,

src/common/data_models/message_manager_data_model.py

@@ -61,27 +61,27 @@ class StreamContext(BaseDataModel):
         self._detect_chat_type(message)
 
     def update_message_info(
-        self, message_id: str, interest_degree: float = None, actions: list = None, should_reply: bool = None
+        self, message_id: str, interest_value: float = None, actions: list = None, should_reply: bool = None
     ):
         """
         更新消息信息
 
         Args:
             message_id: 消息ID
-            interest_degree: 兴趣度值
+            interest_value: 兴趣度值
             actions: 执行的动作列表
             should_reply: 是否应该回复
         """
         # 在未读消息中查找并更新
         for message in self.unread_messages:
             if message.message_id == message_id:
-                message.update_message_info(interest_degree, actions, should_reply)
+                message.update_message_info(interest_value, actions, should_reply)
                 break
 
         # 在历史消息中查找并更新
         for message in self.history_messages:
             if message.message_id == message_id:
-                message.update_message_info(interest_degree, actions, should_reply)
+                message.update_message_info(interest_value, actions, should_reply)
                 break
 
     def add_action_to_message(self, message_id: str, action: str):

src/common/database/sqlalchemy_models.py

@@ -174,7 +174,6 @@ class Messages(Base):
     is_notify = Column(Boolean, nullable=False, default=False)
 
     # 兴趣度系统字段
-    interest_degree = Column(Float, nullable=True, default=0.0)
     actions = Column(Text, nullable=True)  # JSON格式存储动作列表
     should_reply = Column(Boolean, nullable=True, default=False)
 
@@ -183,7 +182,6 @@ class Messages(Base):
         Index("idx_messages_chat_id", "chat_id"),
         Index("idx_messages_time", "time"),
         Index("idx_messages_user_id", "user_id"),
-        Index("idx_messages_interest_degree", "interest_degree"),
         Index("idx_messages_should_reply", "should_reply"),
     )
 

src/plugins/built_in/affinity_flow_chatter/plan_filter.py

@@ -368,40 +368,29 @@ class ChatterPlanFilter:
         interest_scores = {}
 
         try:
-            from src.plugins.built_in.affinity_flow_chatter.interest_scoring import (
-                chatter_interest_scoring_system as interest_scoring_system,
-            )
-            from src.common.data_models.database_data_model import DatabaseMessages
+            from src.chat.interest_system import interest_manager
 
-            # 转换消息格式
-            db_messages = []
+            # 使用新的兴趣度管理系统计算评分
             for msg_dict in messages:
                 try:
-                    db_msg = DatabaseMessages(
-                        message_id=msg_dict.get("message_id", ""),
-                        time=msg_dict.get("time", time.time()),
-                        chat_id=msg_dict.get("chat_id", ""),
-                        processed_plain_text=msg_dict.get("processed_plain_text", ""),
-                        user_id=msg_dict.get("user_id", ""),
-                        user_nickname=msg_dict.get("user_nickname", ""),
-                        user_platform=msg_dict.get("platform", "qq"),
-                        chat_info_group_id=msg_dict.get("group_id", ""),
-                        chat_info_group_name=msg_dict.get("group_name", ""),
-                        chat_info_group_platform=msg_dict.get("platform", "qq"),
-                    )
-                    db_messages.append(db_msg)
-                except Exception as e:
-                    logger.warning(f"转换消息格式失败: {e}")
-                    continue
+                    # 构建计算上下文
+                    calc_context = {
+                        "stream_id": msg_dict.get("chat_id", ""),
+                        "user_id": msg_dict.get("user_id"),
+                    }
 
-            # 计算兴趣度评分
-            if db_messages:
-                bot_nickname = global_config.bot.nickname or "麦麦"
-                scores = await interest_scoring_system.calculate_interest_scores(db_messages, bot_nickname)
+                    # 计算消息兴趣度
+                    interest_score = interest_manager.calculate_message_interest(
+                        message=msg_dict,
+                        context=calc_context
+                    )
 
                     # 构建兴趣度字典
-                for score in scores:
-                    interest_scores[score.message_id] = score.total_score
+                    interest_scores[msg_dict.get("message_id", "")] = interest_score
+
+                except Exception as e:
+                    logger.warning(f"计算消息兴趣度失败: {e}")
+                    continue
 
         except Exception as e:
             logger.warning(f"获取兴趣度评分失败: {e}")

src/plugins/built_in/affinity_flow_chatter/planner.py

@@ -4,13 +4,13 @@
 """
 
 from dataclasses import asdict
+import time
 from typing import TYPE_CHECKING, Dict, List, Optional, Tuple
 
 from src.plugins.built_in.affinity_flow_chatter.plan_executor import ChatterPlanExecutor
 from src.plugins.built_in.affinity_flow_chatter.plan_filter import ChatterPlanFilter
 from src.plugins.built_in.affinity_flow_chatter.plan_generator import ChatterPlanGenerator
-from src.plugins.built_in.affinity_flow_chatter.interest_scoring import ChatterInterestScoringSystem
-from src.plugins.built_in.affinity_flow_chatter.relationship_tracker import ChatterRelationshipTracker
+from src.chat.interest_system import interest_manager
 from src.mood.mood_manager import mood_manager
 
 
@@ -52,14 +52,7 @@ class ChatterActionPlanner:
         self.generator = ChatterPlanGenerator(chat_id)
         self.executor = ChatterPlanExecutor(action_manager)
 
-        # 初始化兴趣度评分系统
-        self.interest_scoring = ChatterInterestScoringSystem()
-
-        # 创建新的关系追踪器
-        self.relationship_tracker = ChatterRelationshipTracker(self.interest_scoring)
-
-        # 设置执行器的关系追踪器
-        self.executor.set_relationship_tracker(self.relationship_tracker)
+        # 使用新的统一兴趣度管理系统
 
         # 规划器统计
         self.planner_stats = {
@@ -107,43 +100,39 @@ class ChatterActionPlanner:
             initial_plan.available_actions = self.action_manager.get_using_actions()
             
             unread_messages = context.get_unread_messages() if context else []
-            # 2. 兴趣度评分 - 只对未读消息进行评分
-            if unread_messages:
-                bot_nickname = global_config.bot.nickname
-                interest_scores = await self.interest_scoring.calculate_interest_scores(unread_messages, bot_nickname)
-
-                # 3. 根据兴趣度调整可用动作
-                if interest_scores:
-                    latest_score = max(interest_scores, key=lambda s: s.total_score)
-                    latest_message = next(
-                        (msg for msg in unread_messages if msg.message_id == latest_score.message_id), None
-                    )
-                    should_reply, score = self.interest_scoring.should_reply(latest_score, latest_message)
-
+            # 2. 使用新的兴趣度管理系统进行评分
+            score = 0.0
+            should_reply = False
             reply_not_available = False
-                    if not should_reply and "reply" in initial_plan.available_actions:
-                        logger.info(f"兴趣度不足 ({latest_score.total_score:.2f})，移除回复")
-                        reply_not_available = True
 
-                    # 更新ChatStream的兴趣度数据
-                    from src.plugin_system.apis.chat_api import get_chat_manager
-                    chat_stream = get_chat_manager().get_stream(self.chat_id)
-                    logger.debug(f"已更新聊天 {self.chat_id} 的ChatStream兴趣度，分数: {score:.3f}")
+            if unread_messages:
+                # 获取用户ID
+                user_id = None
+                if unread_messages[0].user_id:
+                    user_id = unread_messages[0].user_id
 
-                    # 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}")
+                # 构建计算上下文
+                calc_context = {
+                    "stream_id": self.chat_id,
+                    "user_id": user_id,
+                }
 
-                # 为所有未读消息记录兴趣度信息
+                # 为每条消息计算兴趣度
                 for message in unread_messages:
-                    # 查找对应的兴趣度评分
-                    message_score = next((s for s in interest_scores if s.message_id == message.message_id), None)
-                    if message_score:
-                        message.interest_degree = message_score.total_score
-                        message.should_reply = self.interest_scoring.should_reply(message_score, message)[0]
-                        logger.debug(f"已记录消息 {message.message_id} - 兴趣度: {message_score.total_score:.3f}, 应回复: {message.should_reply}")
+                    try:
+                        # 使用新的兴趣度管理器计算
+                        message_interest = interest_manager.calculate_message_interest(
+                            message=message.__dict__,
+                            context=calc_context
+                        )
+
+                        # 更新消息的兴趣度
+                        message.interest_value = message_interest
+
+                        # 简单的回复决策逻辑：兴趣度超过阈值则回复
+                        message.should_reply = message_interest > global_config.affinity_flow.non_reply_action_interest_threshold
+
+                        logger.debug(f"消息 {message.message_id} 兴趣度: {message_interest:.3f}, 应回复: {message.should_reply}")
 
                         # 更新StreamContext中的消息信息并刷新focus_energy
                         if context:
@@ -151,25 +140,35 @@ class ChatterActionPlanner:
                             message_manager.update_message_and_refresh_energy(
                                 stream_id=self.chat_id,
                                 message_id=message.message_id,
-                                interest_degree=message_score.total_score,
+                                interest_value=message_interest,
                                 should_reply=message.should_reply
                             )
+
+                        # 更新数据库中的消息记录
+                        try:
+                            from src.chat.message_receive.storage import MessageStorage
+                            MessageStorage.update_message_interest_value(message.message_id, message_interest)
+                            logger.debug(f"已更新数据库中消息 {message.message_id} 的兴趣度为: {message_interest:.3f}")
+                        except Exception as e:
+                            logger.warning(f"更新数据库消息兴趣度失败: {e}")
+
+                        # 更新话题兴趣度
+                        interest_manager.update_topic_interest(message.__dict__, message_interest)
+
+                        # 记录最高分
+                        if message_interest > score:
+                            score = message_interest
+                            if message.should_reply:
+                                should_reply = True
                             else:
-                        # 如果没有找到评分，设置默认值
-                        message.interest_degree = 0.0
+                                reply_not_available = True
+
+                    except Exception as e:
+                        logger.warning(f"计算消息 {message.message_id} 兴趣度失败: {e}")
+                        # 设置默认值
+                        message.interest_value = 0.0
                         message.should_reply = False
 
-                        # 更新StreamContext中的消息信息并刷新focus_energy
-                        if context:
-                            from src.chat.message_manager.message_manager import message_manager
-                            message_manager.update_message_and_refresh_energy(
-                                stream_id=self.chat_id,
-                                message_id=message.message_id,
-                                interest_degree=0.0,
-                                should_reply=False
-                            )
-
-            # base_threshold = self.interest_scoring.reply_threshold
             # 检查兴趣度是否达到非回复动作阈值
             non_reply_action_interest_threshold = global_config.affinity_flow.non_reply_action_interest_threshold
             if score < non_reply_action_interest_threshold:
@@ -191,26 +190,16 @@ class ChatterActionPlanner:
                 plan_filter = ChatterPlanFilter(self.chat_id, available_actions)
                 filtered_plan = await plan_filter.filter(reply_not_available, initial_plan)
 
-            # 检查filtered_plan是否有reply动作，以便记录reply action
-            has_reply_action = False
-            for decision in filtered_plan.decided_actions:
-                if decision.action_type == "reply":
-                    has_reply_action = True
-            self.interest_scoring.record_reply_action(has_reply_action)
+            # 检查filtered_plan是否有reply动作，用于统计
+            has_reply_action = any(decision.action_type == "reply" for decision in filtered_plan.decided_actions)
 
             # 5. 使用 PlanExecutor 执行 Plan
             execution_result = await self.executor.execute(filtered_plan)
 
-            # 6. 动作记录现在由ChatterActionManager统一处理
-            # 动作记录逻辑已移至ChatterActionManager.execute_action方法中
-
-            # 7. 根据执行结果更新统计信息
+            # 6. 根据执行结果更新统计信息
             self._update_stats_from_execution_result(execution_result)
 
-            # 8. 检查关系更新
-            await self.relationship_tracker.check_and_update_relationships()
-
-            # 8. 返回结果
+            # 7. 返回结果
             return self._build_return_result(filtered_plan)
 
         except Exception as e:
@@ -259,37 +248,10 @@ class ChatterActionPlanner:
 
         return final_actions_dict, final_target_message_dict
 
-    def get_user_relationship(self, user_id: str) -> float:
-        """获取用户关系分"""
-        return self.interest_scoring.get_user_relationship(user_id)
-
-    def update_interest_keywords(self, new_keywords: Dict[str, List[str]]):
-        """更新兴趣关键词（已弃用，仅保留用于兼容性）"""
-        logger.info("传统关键词匹配已移除，此方法仅保留用于兼容性")
-        # 此方法已弃用，因为现在完全使用embedding匹配
-
     def get_planner_stats(self) -> Dict[str, any]:
         """获取规划器统计"""
         return self.planner_stats.copy()
 
-    def get_interest_scoring_stats(self) -> Dict[str, any]:
-        """获取兴趣度评分统计"""
-        return {
-            "no_reply_count": self.interest_scoring.no_reply_count,
-            "max_no_reply_count": self.interest_scoring.max_no_reply_count,
-            "reply_threshold": self.interest_scoring.reply_threshold,
-            "mention_threshold": self.interest_scoring.mention_threshold,
-            "user_relationships": len(self.interest_scoring.user_relationships),
-        }
-
-    def get_relationship_stats(self) -> Dict[str, any]:
-        """获取用户关系统计"""
-        return {
-            "tracking_users": len(self.relationship_tracker.tracking_users),
-            "relationship_history": len(self.relationship_tracker.relationship_history),
-            "max_tracking_users": self.relationship_tracker.max_tracking_users,
-        }
-
     def get_current_mood_state(self) -> str:
         """获取当前聊天的情绪状态"""
         chat_mood = mood_manager.get_mood_by_chat_id(self.chat_id)