ruff，私聊视为提及了bot

src/chat/frequency_analyzer/analyzer.py

@@ -14,6 +14,7 @@ Chat Frequency Analyzer
 - MIN_CHATS_FOR_PEAK: 在一个窗口内需要多少次聊天才能被认为是高峰时段。
 - MIN_GAP_BETWEEN_PEAKS_HOURS: 两个独立高峰时段之间的最小间隔（小时）。
 """
+
 import time as time_module
 from datetime import datetime, timedelta, time
 from typing import List, Tuple, Optional
@@ -72,12 +73,14 @@ class ChatFrequencyAnalyzer:
                 current_window_end = datetimes[i]
 
                 # 合并重叠或相邻的高峰时段
-                if peak_windows and current_window_start - peak_windows[-1][1] < timedelta(hours=MIN_GAP_BETWEEN_PEAKS_HOURS):
+                if peak_windows and current_window_start - peak_windows[-1][1] < timedelta(
+                    hours=MIN_GAP_BETWEEN_PEAKS_HOURS
+                ):
                     # 扩展上一个窗口的结束时间
                     peak_windows[-1] = (peak_windows[-1][0], current_window_end)
                 else:
                     peak_windows.append((current_window_start, current_window_end))
-        
+
         return peak_windows
 
     def get_peak_chat_times(self, chat_id: str) -> List[Tuple[time, time]]:
@@ -100,7 +103,7 @@ class ChatFrequencyAnalyzer:
             return []
 
         peak_datetime_windows = self._find_peak_windows(timestamps)
-        
+
         # 将 datetime 窗口转换为 time 窗口，并进行归一化处理
         peak_time_windows = []
         for start_dt, end_dt in peak_datetime_windows:
@@ -110,7 +113,7 @@ class ChatFrequencyAnalyzer:
 
         # 更新缓存
         self._analysis_cache[chat_id] = (time_module.time(), peak_time_windows)
-        
+
         return peak_time_windows
 
     def is_in_peak_time(self, chat_id: str, now: Optional[datetime] = None) -> bool:
@@ -126,7 +129,7 @@ class ChatFrequencyAnalyzer:
         """
         if now is None:
             now = datetime.now()
-        
+
         now_time = now.time()
         peak_times = self.get_peak_chat_times(chat_id)
 
@@ -137,7 +140,7 @@ class ChatFrequencyAnalyzer:
             else:  # 跨天
                 if now_time >= start_time or now_time <= end_time:
                     return True
-        
+
         return False
 
 

src/chat/frequency_analyzer/tracker.py

@@ -56,7 +56,7 @@ class ChatFrequencyTracker:
         now = time.time()
         if chat_id not in self._timestamps:
             self._timestamps[chat_id] = []
-        
+
         self._timestamps[chat_id].append(now)
         logger.debug(f"为 chat_id '{chat_id}' 记录了新的聊天时间: {now}")
         self._save_timestamps()

src/chat/frequency_analyzer/trigger.py

@@ -14,6 +14,7 @@ Frequency-Based Proactive Trigger
 - TRIGGER_CHECK_INTERVAL_SECONDS: 触发器检查的周期（秒）。
 - COOLDOWN_HOURS: 在同一个高峰时段内触发一次后的冷却时间（小时）。
 """
+
 import asyncio
 import time
 from datetime import datetime
@@ -21,6 +22,7 @@ from typing import Dict, Optional
 
 from src.common.logger import get_logger
 from src.chat.affinity_flow.afc_manager import afc_manager
+
 # TODO: 需要重新实现主动思考和睡眠管理功能
 from .analyzer import chat_frequency_analyzer
 
@@ -65,7 +67,7 @@ class FrequencyBasedTrigger:
                     continue
 
                 now = datetime.now()
-                
+
                 for chat_id in all_chat_ids:
                     # 3. 检查是否处于冷却时间内
                     last_triggered_time = self._last_triggered.get(chat_id, 0)
@@ -74,7 +76,6 @@ class FrequencyBasedTrigger:
 
                     # 4. 检查当前是否是该用户的高峰聊天时间
                     if chat_frequency_analyzer.is_in_peak_time(chat_id, now):
-                        
                         # 5. 检查用户当前是否已有活跃的处理任务
                         #    亲和力流系统不直接提供循环状态，通过检查最后活动时间来判断是否忙碌
                         chatter = afc_manager.get_or_create_chatter(chat_id)
@@ -87,13 +88,13 @@ class FrequencyBasedTrigger:
                         if current_time - chatter.get_activity_time() < 60:
                             logger.debug(f"用户 {chat_id} 的亲和力处理器正忙，本次不触发。")
                             continue
-                          
+
                         logger.info(f"检测到用户 {chat_id} 处于聊天高峰期，且处理器空闲，准备触发主动思考。")
-                        
+
                         # 6. TODO: 亲和力流系统的主动思考机制需要另行实现
                         #    目前先记录日志，等待后续实现
                         logger.info(f"用户 {chat_id} 处于高峰期，但亲和力流的主动思考功能暂未实现")
-                        
+
                         # 7. 更新触发时间，进入冷却
                         self._last_triggered[chat_id] = time.time()