mirror of https://github.com/Mai-with-u/MaiBot.git
495 lines
27 KiB
Python
495 lines
27 KiB
Python
import time
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import math
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import asyncio
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import threading
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import json # 引入 json
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import os # 引入 os
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import traceback # <--- 添加导入
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from typing import Optional # <--- 添加导入
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import random # <--- 添加导入 random
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from src.common.logger import get_module_logger, LogConfig, DEFAULT_CONFIG # 引入 DEFAULT_CONFIG
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from src.plugins.chat.chat_stream import chat_manager # *** Import ChatManager ***
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from ...chat.message import MessageRecv # 导入 MessageRecv
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# 定义日志配置 (使用 loguru 格式)
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interest_log_config = LogConfig(
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console_format=DEFAULT_CONFIG["console_format"], # 使用默认控制台格式
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file_format=DEFAULT_CONFIG["file_format"] # 使用默认文件格式
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)
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logger = get_module_logger("InterestManager", config=interest_log_config)
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# 定义常量
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DEFAULT_DECAY_RATE_PER_SECOND = 0.98 # 每秒衰减率 (兴趣保留 99%)
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MAX_INTEREST = 15.0 # 最大兴趣值
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# MIN_INTEREST_THRESHOLD = 0.1 # 低于此值可能被清理 (可选)
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CLEANUP_INTERVAL_SECONDS = 3600 # 清理任务运行间隔 (例如：1小时)
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INACTIVE_THRESHOLD_SECONDS = 3600 # 不活跃时间阈值 (例如：1小时)
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LOG_INTERVAL_SECONDS = 3 # 日志记录间隔 (例如：30秒)
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LOG_DIRECTORY = "logs/interest" # 日志目录
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LOG_FILENAME = "interest_log.json" # 快照日志文件名 (保留，以防其他地方用到)
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HISTORY_LOG_FILENAME = "interest_history.log" # 新的历史日志文件名
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# 移除阈值，将移至 HeartFC_Chat
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# INTEREST_INCREASE_THRESHOLD = 0.5
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# --- 新增：概率回复相关常量 ---
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REPLY_TRIGGER_THRESHOLD = 3.0 # 触发概率回复的兴趣阈值 (示例值)
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BASE_REPLY_PROBABILITY = 0.05 # 首次超过阈值时的基础回复概率 (示例值)
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PROBABILITY_INCREASE_RATE_PER_SECOND = 0.02 # 高于阈值时，每秒概率增加量 (线性增长, 示例值)
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PROBABILITY_DECAY_FACTOR_PER_SECOND = 0.3 # 低于阈值时，每秒概率衰减因子 (指数衰减, 示例值)
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MAX_REPLY_PROBABILITY = 1 # 回复概率上限 (示例值)
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# --- 结束：概率回复相关常量 ---
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class InterestChatting:
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def __init__(self,
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decay_rate=DEFAULT_DECAY_RATE_PER_SECOND,
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max_interest=MAX_INTEREST,
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trigger_threshold=REPLY_TRIGGER_THRESHOLD,
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base_reply_probability=BASE_REPLY_PROBABILITY,
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increase_rate=PROBABILITY_INCREASE_RATE_PER_SECOND,
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decay_factor=PROBABILITY_DECAY_FACTOR_PER_SECOND,
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max_probability=MAX_REPLY_PROBABILITY):
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self.interest_level: float = 0.0
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self.last_update_time: float = time.time() # 同时作为兴趣和概率的更新时间基准
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self.decay_rate_per_second: float = decay_rate
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self.max_interest: float = max_interest
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self.last_increase_amount: float = 0.0
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self.last_interaction_time: float = self.last_update_time # 新增：最后交互时间
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# --- 新增：概率回复相关属性 ---
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self.trigger_threshold: float = trigger_threshold
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self.base_reply_probability: float = base_reply_probability
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self.probability_increase_rate: float = increase_rate
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self.probability_decay_factor: float = decay_factor
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self.max_reply_probability: float = max_probability
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self.current_reply_probability: float = 0.0
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self.is_above_threshold: bool = False # 标记兴趣值是否高于阈值
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# --- 结束：概率回复相关属性 ---
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def _calculate_decay(self, current_time: float):
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"""计算从上次更新到现在的衰减"""
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time_delta = current_time - self.last_update_time
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if time_delta > 0:
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# 指数衰减: interest = interest * (decay_rate ^ time_delta)
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# 添加处理极小兴趣值避免 math domain error
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old_interest = self.interest_level
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if self.interest_level < 1e-9:
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self.interest_level = 0.0
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else:
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# 检查 decay_rate_per_second 是否为非正数，避免 math domain error
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if self.decay_rate_per_second <= 0:
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logger.warning(f"InterestChatting encountered non-positive decay rate: {self.decay_rate_per_second}. Setting interest to 0.")
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self.interest_level = 0.0
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# 检查 interest_level 是否为负数，虽然理论上不应发生，但以防万一
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elif self.interest_level < 0:
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logger.warning(f"InterestChatting encountered negative interest level: {self.interest_level}. Setting interest to 0.")
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self.interest_level = 0.0
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else:
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try:
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decay_factor = math.pow(self.decay_rate_per_second, time_delta)
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self.interest_level *= decay_factor
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except ValueError as e:
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# 捕获潜在的 math domain error，例如对负数开非整数次方（虽然已加保护）
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logger.error(f"Math error during decay calculation: {e}. Rate: {self.decay_rate_per_second}, Delta: {time_delta}, Level: {self.interest_level}. Setting interest to 0.")
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self.interest_level = 0.0
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# 防止低于阈值 (如果需要)
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# self.interest_level = max(self.interest_level, MIN_INTEREST_THRESHOLD)
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# 只有在兴趣值发生变化时才更新时间戳
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if old_interest != self.interest_level:
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self.last_update_time = current_time
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def _update_reply_probability(self, current_time: float):
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"""根据当前兴趣是否超过阈值及时间差，更新回复概率"""
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time_delta = current_time - self.last_update_time
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if time_delta <= 0:
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return # 时间未前进，无需更新
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currently_above = self.interest_level >= self.trigger_threshold
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if currently_above:
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if not self.is_above_threshold:
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# 刚跨过阈值，重置为基础概率
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self.current_reply_probability = self.base_reply_probability
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logger.debug(f"兴趣跨过阈值 ({self.trigger_threshold}). 概率重置为基础值: {self.base_reply_probability:.4f}")
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else:
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# 持续高于阈值，线性增加概率
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increase_amount = self.probability_increase_rate * time_delta
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self.current_reply_probability += increase_amount
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# logger.debug(f"兴趣高于阈值 ({self.trigger_threshold}) 持续 {time_delta:.2f}秒. 概率增加 {increase_amount:.4f} 到 {self.current_reply_probability:.4f}")
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# 限制概率不超过最大值
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self.current_reply_probability = min(self.current_reply_probability, self.max_reply_probability)
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else: # 低于阈值
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# if self.is_above_threshold:
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# # 刚低于阈值，开始衰减
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# logger.debug(f"兴趣低于阈值 ({self.trigger_threshold}). 概率衰减开始于 {self.current_reply_probability:.4f}")
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# else: # 持续低于阈值，继续衰减
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# pass # 不需要特殊处理
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# 指数衰减概率
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# 检查 decay_factor 是否有效
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if 0 < self.probability_decay_factor < 1:
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decay_multiplier = math.pow(self.probability_decay_factor, time_delta)
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# old_prob = self.current_reply_probability
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self.current_reply_probability *= decay_multiplier
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# 避免因浮点数精度问题导致概率略微大于0，直接设为0
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if self.current_reply_probability < 1e-6:
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self.current_reply_probability = 0.0
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# logger.debug(f"兴趣低于阈值 ({self.trigger_threshold}) 持续 {time_delta:.2f}秒. 概率从 {old_prob:.4f} 衰减到 {self.current_reply_probability:.4f} (因子: {self.probability_decay_factor})")
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elif self.probability_decay_factor <= 0:
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# 如果衰减因子无效或为0，直接清零
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if self.current_reply_probability > 0:
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logger.warning(f"无效的衰减因子 ({self.probability_decay_factor}). 设置概率为0.")
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self.current_reply_probability = 0.0
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# else: decay_factor >= 1, probability will not decay or increase, which might be intended in some cases.
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# 确保概率不低于0
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self.current_reply_probability = max(self.current_reply_probability, 0.0)
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# 更新状态标记
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self.is_above_threshold = currently_above
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# 更新时间戳放在调用者处，确保 interest 和 probability 基于同一点更新
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def increase_interest(self, current_time: float, value: float):
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"""根据传入的值增加兴趣值，并记录增加量"""
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# 先更新概率和计算衰减（基于上次更新时间）
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self._update_reply_probability(current_time)
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self._calculate_decay(current_time)
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# 记录这次增加的具体数值，供外部判断是否触发
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self.last_increase_amount = value
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# 应用增加
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self.interest_level += value
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self.interest_level = min(self.interest_level, self.max_interest) # 不超过最大值
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self.last_update_time = current_time # 更新时间戳
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self.last_interaction_time = current_time # 更新最后交互时间
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def decrease_interest(self, current_time: float, value: float):
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"""降低兴趣值并更新时间 (确保不低于0)"""
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# 先更新概率（基于上次更新时间）
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self._update_reply_probability(current_time)
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# 注意：降低兴趣度是否需要先衰减？取决于具体逻辑，这里假设不衰减直接减
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self.interest_level -= value
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self.interest_level = max(self.interest_level, 0.0) # 确保不低于0
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self.last_update_time = current_time # 降低也更新时间戳
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self.last_interaction_time = current_time # 更新最后交互时间
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def reset_trigger_info(self):
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"""重置触发相关信息，在外部任务处理后调用"""
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self.last_increase_amount = 0.0
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def get_interest(self) -> float:
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"""获取当前兴趣值 (计算衰减后)"""
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# 注意：这个方法现在会触发概率和兴趣的更新
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current_time = time.time()
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self._update_reply_probability(current_time)
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self._calculate_decay(current_time)
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self.last_update_time = current_time # 更新时间戳
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return self.interest_level
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def get_state(self) -> dict:
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"""获取当前状态字典"""
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# 调用 get_interest 来确保状态已更新
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interest = self.get_interest()
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return {
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"interest_level": round(interest, 2),
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"last_update_time": self.last_update_time,
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"current_reply_probability": round(self.current_reply_probability, 4), # 添加概率到状态
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"is_above_threshold": self.is_above_threshold, # 添加阈值状态
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"last_interaction_time": self.last_interaction_time # 新增：添加最后交互时间到状态
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# 可以选择性地暴露 last_increase_amount 给状态，方便调试
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# "last_increase_amount": round(self.last_increase_amount, 2)
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}
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def should_evaluate_reply(self) -> bool:
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"""
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判断是否应该触发一次回复评估。
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首先更新概率状态，然后根据当前概率进行随机判断。
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"""
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current_time = time.time()
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# 确保概率是基于最新兴趣值计算的
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self._update_reply_probability(current_time)
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# 更新兴趣衰减（如果需要，取决于逻辑，这里保持和 get_interest 一致）
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# self._calculate_decay(current_time)
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# self.last_update_time = current_time # 更新时间戳
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if self.current_reply_probability > 0:
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# 只有在阈值之上且概率大于0时才有可能触发
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trigger = random.random() < self.current_reply_probability
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# if trigger:
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# logger.info(f"回复概率评估触发! 概率: {self.current_reply_probability:.4f}, 阈值: {self.trigger_threshold}, 兴趣: {self.interest_level:.2f}")
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# # 可选：触发后是否重置/降低概率？根据需要决定
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# # self.current_reply_probability = self.base_reply_probability # 例如，触发后降回基础概率
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# # self.current_reply_probability *= 0.5 # 例如，触发后概率减半
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# else:
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# logger.debug(f"回复概率评估未触发。概率: {self.current_reply_probability:.4f}")
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return trigger
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else:
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# logger.debug(f"Reply evaluation check: Below threshold or zero probability. Probability: {self.current_reply_probability:.4f}")
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return False
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class InterestManager:
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_instance = None
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_lock = threading.Lock()
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_initialized = False
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def __new__(cls, *args, **kwargs):
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if cls._instance is None:
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with cls._lock:
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# Double-check locking
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if cls._instance is None:
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cls._instance = super().__new__(cls)
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return cls._instance
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def __init__(self):
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if not self._initialized:
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with self._lock:
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# 确保初始化也只执行一次
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if not self._initialized:
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logger.info("Initializing InterestManager singleton...")
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# key: stream_id (str), value: InterestChatting instance
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self.interest_dict: dict[str, InterestChatting] = {}
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# 保留旧的快照文件路径变量，尽管此任务不再写入
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self._snapshot_log_file_path = os.path.join(LOG_DIRECTORY, LOG_FILENAME)
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# 定义新的历史日志文件路径
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self._history_log_file_path = os.path.join(LOG_DIRECTORY, HISTORY_LOG_FILENAME)
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self._ensure_log_directory()
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self._cleanup_task = None
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self._logging_task = None # 添加日志任务变量
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self._initialized = True
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logger.info("InterestManager initialized.") # 修改日志消息
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self._decay_task = None # 新增：衰减任务变量
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def _ensure_log_directory(self):
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"""确保日志目录存在"""
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try:
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os.makedirs(LOG_DIRECTORY, exist_ok=True)
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logger.info(f"Log directory '{LOG_DIRECTORY}' ensured.")
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except OSError as e:
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logger.error(f"Error creating log directory '{LOG_DIRECTORY}': {e}")
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async def _periodic_cleanup_task(self, interval_seconds: int, max_age_seconds: int):
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"""后台清理任务的异步函数"""
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while True:
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await asyncio.sleep(interval_seconds)
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logger.info(f"运行定期清理 (间隔: {interval_seconds}秒)...")
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self.cleanup_inactive_chats(max_age_seconds=max_age_seconds)
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async def _periodic_log_task(self, interval_seconds: int):
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"""后台日志记录任务的异步函数 (记录历史数据，包含 group_name)"""
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while True:
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await asyncio.sleep(interval_seconds)
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# logger.debug(f"运行定期历史记录 (间隔: {interval_seconds}秒)...")
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try:
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current_timestamp = time.time()
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all_states = self.get_all_interest_states() # 获取当前所有状态
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# 以追加模式打开历史日志文件
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with open(self._history_log_file_path, 'a', encoding='utf-8') as f:
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count = 0
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for stream_id, state in all_states.items():
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# *** Get group name from ChatManager ***
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group_name = stream_id # Default to stream_id
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try:
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# Use the imported chat_manager instance
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chat_stream = chat_manager.get_stream(stream_id)
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if chat_stream and chat_stream.group_info:
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group_name = chat_stream.group_info.group_name
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elif chat_stream and not chat_stream.group_info:
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# Handle private chats - maybe use user nickname?
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group_name = f"私聊_{chat_stream.user_info.user_nickname}" if chat_stream.user_info else stream_id
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except Exception as e:
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logger.warning(f"Could not get group name for stream_id {stream_id}: {e}")
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# Fallback to stream_id is already handled by default value
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log_entry = {
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"timestamp": round(current_timestamp, 2),
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"stream_id": stream_id,
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"interest_level": state.get("interest_level", 0.0), # 确保有默认值
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"group_name": group_name, # *** Add group_name ***
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# --- 新增：记录概率相关信息 ---
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"reply_probability": state.get("current_reply_probability", 0.0),
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"is_above_threshold": state.get("is_above_threshold", False)
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# --- 结束新增 ---
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}
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# 将每个条目作为单独的 JSON 行写入
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f.write(json.dumps(log_entry, ensure_ascii=False) + '\n')
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count += 1
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# logger.debug(f"Successfully appended {count} interest history entries to {self._history_log_file_path}")
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# 注意：不再写入快照文件 interest_log.json
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# 如果需要快照文件，可以在这里单独写入 self._snapshot_log_file_path
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# 例如：
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# with open(self._snapshot_log_file_path, 'w', encoding='utf-8') as snap_f:
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# json.dump(all_states, snap_f, indent=4, ensure_ascii=False)
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# logger.debug(f"Successfully wrote snapshot to {self._snapshot_log_file_path}")
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except IOError as e:
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logger.error(f"Error writing interest history log to {self._history_log_file_path}: {e}")
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except Exception as e:
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logger.error(f"Unexpected error during periodic history logging: {e}")
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async def _periodic_decay_task(self):
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"""后台衰减任务的异步函数，每秒更新一次所有实例的衰减"""
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while True:
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await asyncio.sleep(1) # 每秒运行一次
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current_time = time.time()
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# logger.debug("Running periodic decay calculation...") # 调试日志，可能过于频繁
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# 创建字典项的快照进行迭代，避免在迭代时修改字典的问题
|
||
items_snapshot = list(self.interest_dict.items())
|
||
count = 0
|
||
for stream_id, chatting in items_snapshot:
|
||
try:
|
||
# 调用 InterestChatting 实例的衰减方法
|
||
chatting._calculate_decay(current_time)
|
||
count += 1
|
||
except Exception as e:
|
||
logger.error(f"Error calculating decay for stream_id {stream_id}: {e}")
|
||
# if count > 0: # 仅在实际处理了项目时记录日志，避免空闲时刷屏
|
||
# logger.debug(f"Applied decay to {count} streams.")
|
||
|
||
async def start_background_tasks(self):
|
||
"""启动清理，启动衰减，启动记录，启动启动启动启动启动"""
|
||
if self._cleanup_task is None or self._cleanup_task.done():
|
||
self._cleanup_task = asyncio.create_task(
|
||
self._periodic_cleanup_task(
|
||
interval_seconds=CLEANUP_INTERVAL_SECONDS,
|
||
max_age_seconds=INACTIVE_THRESHOLD_SECONDS
|
||
)
|
||
)
|
||
logger.info(f"已创建定期清理任务。间隔时间: {CLEANUP_INTERVAL_SECONDS}秒, 不活跃阈值: {INACTIVE_THRESHOLD_SECONDS}秒")
|
||
else:
|
||
logger.warning("跳过创建清理任务:任务已在运行或存在。")
|
||
|
||
if self._logging_task is None or self._logging_task.done():
|
||
self._logging_task = asyncio.create_task(
|
||
self._periodic_log_task(interval_seconds=LOG_INTERVAL_SECONDS)
|
||
)
|
||
logger.info(f"已创建定期日志任务。间隔时间: {LOG_INTERVAL_SECONDS}秒")
|
||
else:
|
||
logger.warning("跳过创建日志任务:任务已在运行或存在。")
|
||
|
||
# 启动新的衰减任务
|
||
if self._decay_task is None or self._decay_task.done():
|
||
self._decay_task = asyncio.create_task(
|
||
self._periodic_decay_task()
|
||
)
|
||
logger.info("已创建定期衰减任务。间隔时间: 1秒")
|
||
else:
|
||
logger.warning("跳过创建衰减任务:任务已在运行或存在。")
|
||
|
||
def get_all_interest_states(self) -> dict[str, dict]:
|
||
"""获取所有聊天流的当前兴趣状态"""
|
||
# 不再需要 current_time, 因为 get_state 现在不接收它
|
||
states = {}
|
||
# 创建副本以避免在迭代时修改字典
|
||
items_snapshot = list(self.interest_dict.items())
|
||
for stream_id, chatting in items_snapshot:
|
||
try:
|
||
# 直接调用 get_state，它会使用内部的 get_interest 获取已更新的值
|
||
states[stream_id] = chatting.get_state()
|
||
except Exception as e:
|
||
logger.warning(f"Error getting state for stream_id {stream_id}: {e}")
|
||
return states
|
||
|
||
def get_interest_chatting(self, stream_id: str) -> Optional[InterestChatting]:
|
||
"""获取指定流的 InterestChatting 实例，如果不存在则返回 None"""
|
||
return self.interest_dict.get(stream_id)
|
||
|
||
def _get_or_create_interest_chatting(self, stream_id: str) -> InterestChatting:
|
||
"""获取或创建指定流的 InterestChatting 实例 (线程安全)"""
|
||
# 由于字典操作本身在 CPython 中大部分是原子的，
|
||
# 且主要写入发生在 __init__ 和 cleanup (由单任务执行)，
|
||
# 读取和 get_or_create 主要在事件循环线程，简单场景下可能不需要锁。
|
||
# 但为保险起见或跨线程使用考虑，可加锁。
|
||
# with self._lock:
|
||
if stream_id not in self.interest_dict:
|
||
logger.debug(f"Creating new InterestChatting for stream_id: {stream_id}")
|
||
# --- 修改：创建时传入概率相关参数 (如果需要定制化，否则使用默认值) ---
|
||
self.interest_dict[stream_id] = InterestChatting(
|
||
# decay_rate=..., max_interest=..., # 可以从配置读取
|
||
trigger_threshold=REPLY_TRIGGER_THRESHOLD, # 使用全局常量
|
||
base_reply_probability=BASE_REPLY_PROBABILITY,
|
||
increase_rate=PROBABILITY_INCREASE_RATE_PER_SECOND,
|
||
decay_factor=PROBABILITY_DECAY_FACTOR_PER_SECOND,
|
||
max_probability=MAX_REPLY_PROBABILITY
|
||
)
|
||
# --- 结束修改 ---
|
||
# 首次创建时兴趣为 0，由第一次消息的 activate rate 决定初始值
|
||
return self.interest_dict[stream_id]
|
||
|
||
def get_interest(self, stream_id: str) -> float:
|
||
"""获取指定聊天流当前的兴趣度 (值由后台任务更新)"""
|
||
# current_time = time.time() # 不再需要获取当前时间
|
||
interest_chatting = self._get_or_create_interest_chatting(stream_id)
|
||
# 直接调用修改后的 get_interest，不传入时间
|
||
return interest_chatting.get_interest()
|
||
|
||
def increase_interest(self, stream_id: str, value: float):
|
||
"""当收到消息时，增加指定聊天流的兴趣度"""
|
||
current_time = time.time()
|
||
interest_chatting = self._get_or_create_interest_chatting(stream_id)
|
||
# 调用修改后的 increase_interest，不再传入 message
|
||
interest_chatting.increase_interest(current_time, value)
|
||
stream_name = chat_manager.get_stream_name(stream_id) or stream_id # 获取流名称
|
||
logger.debug(f"增加了聊天流 {stream_name} 的兴趣度 {value:.2f}，当前值为 {interest_chatting.interest_level:.2f}") # 更新日志
|
||
|
||
def decrease_interest(self, stream_id: str, value: float):
|
||
"""降低指定聊天流的兴趣度"""
|
||
current_time = time.time()
|
||
# 尝试获取，如果不存在则不做任何事
|
||
interest_chatting = self.get_interest_chatting(stream_id)
|
||
if interest_chatting:
|
||
interest_chatting.decrease_interest(current_time, value)
|
||
stream_name = chat_manager.get_stream_name(stream_id) or stream_id # 获取流名称
|
||
logger.debug(f"降低了聊天流 {stream_name} 的兴趣度 {value:.2f}，当前值为 {interest_chatting.interest_level:.2f}")
|
||
else:
|
||
stream_name = chat_manager.get_stream_name(stream_id) or stream_id # 获取流名称
|
||
logger.warning(f"尝试降低不存在的聊天流 {stream_name} 的兴趣度")
|
||
|
||
def cleanup_inactive_chats(self, max_age_seconds=INACTIVE_THRESHOLD_SECONDS):
|
||
"""
|
||
清理长时间不活跃的聊天流记录
|
||
max_age_seconds: 超过此时间未更新的将被清理
|
||
"""
|
||
current_time = time.time()
|
||
keys_to_remove = []
|
||
initial_count = len(self.interest_dict)
|
||
# with self._lock: # 如果需要锁整个迭代过程
|
||
# 创建副本以避免在迭代时修改字典
|
||
items_snapshot = list(self.interest_dict.items())
|
||
|
||
for stream_id, chatting in items_snapshot:
|
||
# 先计算当前兴趣，确保是最新的
|
||
# 加锁保护 chatting 对象状态的读取和可能的修改
|
||
# with self._lock: # 如果 InterestChatting 内部操作不是原子的
|
||
last_interaction = chatting.last_interaction_time # 使用最后交互时间
|
||
should_remove = False
|
||
reason = ""
|
||
# 只有设置了 max_age_seconds 才检查时间
|
||
if max_age_seconds is not None and (current_time - last_interaction) > max_age_seconds: # 使用 last_interaction
|
||
should_remove = True
|
||
reason = f"inactive time ({current_time - last_interaction:.0f}s) > max age ({max_age_seconds}s)" # 更新日志信息
|
||
|
||
if should_remove:
|
||
keys_to_remove.append(stream_id)
|
||
stream_name = chat_manager.get_stream_name(stream_id) or stream_id # 获取流名称
|
||
logger.debug(f"Marking stream {stream_name} for removal. Reason: {reason}")
|
||
|
||
if keys_to_remove:
|
||
logger.info(f"清理识别到 {len(keys_to_remove)} 个不活跃/低兴趣的流。")
|
||
# with self._lock: # 确保删除操作的原子性
|
||
for key in keys_to_remove:
|
||
# 再次检查 key 是否存在，以防万一在迭代和删除之间状态改变
|
||
if key in self.interest_dict:
|
||
del self.interest_dict[key]
|
||
stream_name = chat_manager.get_stream_name(key) or key # 获取流名称
|
||
logger.debug(f"移除了流: {stream_name}")
|
||
final_count = initial_count - len(keys_to_remove)
|
||
logger.info(f"清理完成。移除了 {len(keys_to_remove)} 个流。当前数量: {final_count}")
|
||
else:
|
||
logger.info(f"清理完成。没有流符合移除条件。当前数量: {initial_count}") |