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