fix：优化关系构建频率
This commit is contained in:
SengokuCola
@@ -3,6 +3,8 @@ import time
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import traceback
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from random import random
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from typing import List, Optional, Dict, Any # 导入类型提示
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import os
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import pickle
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from maim_message import UserInfo, Seg
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from src.common.logger import get_logger
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from src.chat.heart_flow.utils_chat import get_chat_type_and_target_info
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@@ -22,13 +24,21 @@ from src.chat.normal_chat.normal_chat_action_modifier import NormalChatActionMod
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from src.chat.normal_chat.normal_chat_expressor import NormalChatExpressor
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from src.chat.focus_chat.replyer.default_replyer import DefaultReplyer
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from src.person_info.person_info import PersonInfoManager
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from src.chat.utils.chat_message_builder import get_raw_msg_by_timestamp_with_chat
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from src.chat.utils.chat_message_builder import get_raw_msg_by_timestamp_with_chat, get_raw_msg_by_timestamp_with_chat_inclusive, get_raw_msg_before_timestamp_with_chat, num_new_messages_since
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from src.person_info.relationship_manager import get_relationship_manager
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willing_manager = get_willing_manager()
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logger = get_logger("normal_chat")
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# 消息段清理配置
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SEGMENT_CLEANUP_CONFIG = {
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"enable_cleanup": True, # 是否启用清理
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"max_segment_age_days": 7, # 消息段最大保存天数
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"max_segments_per_user": 10, # 每用户最大消息段数
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"cleanup_interval_hours": 1, # 清理间隔（小时）
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}
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class NormalChat:
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def __init__(self, chat_stream: ChatStream, interest_dict: dict = None, on_switch_to_focus_callback=None):
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@@ -67,16 +77,307 @@ class NormalChat:
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self.recent_replies = []
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self.max_replies_history = 20 # 最多保存最近20条回复记录
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# 添加engaging_person统计
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self.engaging_persons = {} # person_id -> {first_time, last_time, receive_count, reply_count, relation_built}
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# 新的消息段缓存结构：
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# {person_id: [{"start_time": float, "end_time": float, "last_msg_time": float, "message_count": int}, ...]}
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self.person_engaged_cache: Dict[str, List[Dict[str, any]]] = {}
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# 持久化存储文件路径
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self.cache_file_path = os.path.join("data", f"relationship_cache_{self.stream_id}.pkl")
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# 最后处理的消息时间，避免重复处理相同消息
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self.last_processed_message_time = 0.0
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# 最后清理时间，用于定期清理老消息段
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self.last_cleanup_time = 0.0
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# 添加回调函数，用于在满足条件时通知切换到focus_chat模式
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self.on_switch_to_focus_callback = on_switch_to_focus_callback
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self._disabled = False # 增加停用标志
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# 加载持久化的缓存
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self._load_cache()
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logger.debug(f"[{self.stream_name}] NormalChat 初始化完成 (异步部分)。")
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# ================================
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# 缓存管理模块
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# 负责持久化存储、状态管理、缓存读写
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# ================================
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def _load_cache(self):
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"""从文件加载持久化的缓存"""
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if os.path.exists(self.cache_file_path):
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try:
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with open(self.cache_file_path, 'rb') as f:
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cache_data = pickle.load(f)
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# 新格式：包含额外信息的缓存
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self.person_engaged_cache = cache_data.get('person_engaged_cache', {})
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self.last_processed_message_time = cache_data.get('last_processed_message_time', 0.0)
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self.last_cleanup_time = cache_data.get('last_cleanup_time', 0.0)
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logger.info(f"[{self.stream_name}] 成功加载关系缓存，包含 {len(self.person_engaged_cache)} 个用户，最后处理时间：{time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(self.last_processed_message_time)) if self.last_processed_message_time > 0 else '未设置'}")
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except Exception as e:
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logger.error(f"[{self.stream_name}] 加载关系缓存失败: {e}")
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self.person_engaged_cache = {}
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self.last_processed_message_time = 0.0
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else:
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logger.info(f"[{self.stream_name}] 关系缓存文件不存在，使用空缓存")
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def _save_cache(self):
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"""保存缓存到文件"""
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try:
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os.makedirs(os.path.dirname(self.cache_file_path), exist_ok=True)
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cache_data = {
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'person_engaged_cache': self.person_engaged_cache,
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'last_processed_message_time': self.last_processed_message_time,
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'last_cleanup_time': self.last_cleanup_time
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}
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with open(self.cache_file_path, 'wb') as f:
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pickle.dump(cache_data, f)
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logger.debug(f"[{self.stream_name}] 成功保存关系缓存")
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except Exception as e:
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logger.error(f"[{self.stream_name}] 保存关系缓存失败: {e}")
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# ================================
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# 消息段管理模块
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# 负责跟踪用户消息活动、管理消息段、清理过期数据
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# ================================
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def _update_message_segments(self, person_id: str, message_time: float):
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"""更新用户的消息段
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Args:
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person_id: 用户ID
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message_time: 消息时间戳
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"""
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if person_id not in self.person_engaged_cache:
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self.person_engaged_cache[person_id] = []
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segments = self.person_engaged_cache[person_id]
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current_time = time.time()
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# 获取该消息前5条消息的时间作为潜在的开始时间
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before_messages = get_raw_msg_before_timestamp_with_chat(self.stream_id, message_time, limit=5)
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if before_messages:
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# 由于get_raw_msg_before_timestamp_with_chat返回按时间升序排序的消息，最后一个是最接近message_time的
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# 我们需要第一个消息作为开始时间，但应该确保至少包含5条消息或该用户之前的消息
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potential_start_time = before_messages[0]['time']
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else:
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# 如果没有前面的消息，就从当前消息开始
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potential_start_time = message_time
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# 如果没有现有消息段，创建新的
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if not segments:
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new_segment = {
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"start_time": potential_start_time,
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"end_time": message_time,
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"last_msg_time": message_time,
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"message_count": self._count_messages_in_timerange(potential_start_time, message_time)
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}
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segments.append(new_segment)
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logger.info(f"[{self.stream_name}] 为用户 {person_id} 创建新消息段: 时间范围 {time.strftime('%H:%M:%S', time.localtime(potential_start_time))} - {time.strftime('%H:%M:%S', time.localtime(message_time))}, 消息数: {new_segment['message_count']}")
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self._save_cache()
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return
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# 获取最后一个消息段
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last_segment = segments[-1]
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# 计算从最后一条消息到当前消息之间的消息数量（不包含边界）
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messages_between = self._count_messages_between(last_segment["last_msg_time"], message_time)
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if messages_between <= 10:
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# 在10条消息内，延伸当前消息段
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last_segment["end_time"] = message_time
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last_segment["last_msg_time"] = message_time
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# 重新计算整个消息段的消息数量
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last_segment["message_count"] = self._count_messages_in_timerange(
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last_segment["start_time"], last_segment["end_time"]
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)
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logger.debug(f"[{self.stream_name}] 延伸用户 {person_id} 的消息段: {last_segment}")
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else:
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# 超过10条消息，结束当前消息段并创建新的
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# 结束当前消息段：延伸到原消息段最后一条消息后5条消息的时间
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after_messages = get_raw_msg_by_timestamp_with_chat(
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self.stream_id, last_segment["last_msg_time"], current_time, limit=5, limit_mode="earliest"
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)
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if after_messages and len(after_messages) >= 5:
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# 如果有足够的后续消息，使用第5条消息的时间作为结束时间
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last_segment["end_time"] = after_messages[4]['time']
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else:
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# 如果没有足够的后续消息，保持原有的结束时间
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pass
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# 重新计算当前消息段的消息数量
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last_segment["message_count"] = self._count_messages_in_timerange(
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last_segment["start_time"], last_segment["end_time"]
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)
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# 创建新的消息段
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new_segment = {
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"start_time": potential_start_time,
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"end_time": message_time,
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"last_msg_time": message_time,
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"message_count": self._count_messages_in_timerange(potential_start_time, message_time)
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}
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segments.append(new_segment)
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logger.info(f"[{self.stream_name}] 为用户 {person_id} 创建新消息段（超过10条消息间隔）: {new_segment}")
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self._save_cache()
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def _count_messages_in_timerange(self, start_time: float, end_time: float) -> int:
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"""计算指定时间范围内的消息数量（包含边界）"""
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messages = get_raw_msg_by_timestamp_with_chat_inclusive(self.stream_id, start_time, end_time)
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return len(messages)
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def _count_messages_between(self, start_time: float, end_time: float) -> int:
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"""计算两个时间点之间的消息数量（不包含边界），用于间隔检查"""
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return num_new_messages_since(self.stream_id, start_time, end_time)
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def _get_total_message_count(self, person_id: str) -> int:
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"""获取用户所有消息段的总消息数量"""
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if person_id not in self.person_engaged_cache:
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return 0
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total_count = 0
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for segment in self.person_engaged_cache[person_id]:
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total_count += segment["message_count"]
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return total_count
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def _cleanup_old_segments(self) -> bool:
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"""清理老旧的消息段
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Returns:
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bool: 是否执行了清理操作
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"""
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if not SEGMENT_CLEANUP_CONFIG["enable_cleanup"]:
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return False
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current_time = time.time()
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# 检查是否需要执行清理（基于时间间隔）
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cleanup_interval_seconds = SEGMENT_CLEANUP_CONFIG["cleanup_interval_hours"] * 3600
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if current_time - self.last_cleanup_time < cleanup_interval_seconds:
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return False
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logger.info(f"[{self.stream_name}] 开始执行老消息段清理...")
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cleanup_stats = {
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"users_cleaned": 0,
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"segments_removed": 0,
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"total_segments_before": 0,
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"total_segments_after": 0
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}
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max_age_seconds = SEGMENT_CLEANUP_CONFIG["max_segment_age_days"] * 24 * 3600
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max_segments_per_user = SEGMENT_CLEANUP_CONFIG["max_segments_per_user"]
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users_to_remove = []
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for person_id, segments in self.person_engaged_cache.items():
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cleanup_stats["total_segments_before"] += len(segments)
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original_segment_count = len(segments)
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# 1. 按时间清理：移除过期的消息段
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segments_after_age_cleanup = []
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for segment in segments:
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segment_age = current_time - segment["end_time"]
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if segment_age <= max_age_seconds:
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segments_after_age_cleanup.append(segment)
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else:
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cleanup_stats["segments_removed"] += 1
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logger.debug(f"[{self.stream_name}] 移除用户 {person_id} 的过期消息段: {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(segment['start_time']))} - {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(segment['end_time']))}")
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# 2. 按数量清理：如果消息段数量仍然过多，保留最新的
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if len(segments_after_age_cleanup) > max_segments_per_user:
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# 按end_time排序，保留最新的
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segments_after_age_cleanup.sort(key=lambda x: x["end_time"], reverse=True)
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segments_removed_count = len(segments_after_age_cleanup) - max_segments_per_user
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cleanup_stats["segments_removed"] += segments_removed_count
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segments_after_age_cleanup = segments_after_age_cleanup[:max_segments_per_user]
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logger.debug(f"[{self.stream_name}] 用户 {person_id} 消息段数量过多，移除 {segments_removed_count} 个最老的消息段")
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# 使用清理后的消息段
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# 更新缓存
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if len(segments_after_age_cleanup) == 0:
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# 如果没有剩余消息段，标记用户为待移除
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users_to_remove.append(person_id)
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else:
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self.person_engaged_cache[person_id] = segments_after_age_cleanup
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cleanup_stats["total_segments_after"] += len(segments_after_age_cleanup)
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if original_segment_count != len(segments_after_age_cleanup):
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cleanup_stats["users_cleaned"] += 1
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# 移除没有消息段的用户
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for person_id in users_to_remove:
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del self.person_engaged_cache[person_id]
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logger.debug(f"[{self.stream_name}] 移除用户 {person_id}：没有剩余消息段")
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# 更新最后清理时间
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self.last_cleanup_time = current_time
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# 保存缓存
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if cleanup_stats["segments_removed"] > 0 or len(users_to_remove) > 0:
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self._save_cache()
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logger.info(f"[{self.stream_name}] 清理完成 - 影响用户: {cleanup_stats['users_cleaned']}, 移除消息段: {cleanup_stats['segments_removed']}, 移除用户: {len(users_to_remove)}")
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logger.info(f"[{self.stream_name}] 消息段统计 - 清理前: {cleanup_stats['total_segments_before']}, 清理后: {cleanup_stats['total_segments_after']}")
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else:
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logger.debug(f"[{self.stream_name}] 清理完成 - 无需清理任何内容")
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return cleanup_stats["segments_removed"] > 0 or len(users_to_remove) > 0
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def get_cache_status(self) -> str:
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"""获取缓存状态信息，用于调试和监控"""
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if not self.person_engaged_cache:
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return f"[{self.stream_name}] 关系缓存为空"
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status_lines = [f"[{self.stream_name}] 关系缓存状态："]
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status_lines.append(f"最后处理消息时间：{time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(self.last_processed_message_time)) if self.last_processed_message_time > 0 else '未设置'}")
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status_lines.append(f"最后清理时间：{time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(self.last_cleanup_time)) if self.last_cleanup_time > 0 else '未执行'}")
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status_lines.append(f"总用户数：{len(self.person_engaged_cache)}")
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status_lines.append(f"清理配置：{'启用' if SEGMENT_CLEANUP_CONFIG['enable_cleanup'] else '禁用'} (最大保存{SEGMENT_CLEANUP_CONFIG['max_segment_age_days']}天, 每用户最多{SEGMENT_CLEANUP_CONFIG['max_segments_per_user']}段)")
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status_lines.append("")
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for person_id, segments in self.person_engaged_cache.items():
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total_count = self._get_total_message_count(person_id)
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status_lines.append(f"用户 {person_id}:")
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status_lines.append(f" 总消息数：{total_count} ({total_count}/45)")
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status_lines.append(f" 消息段数：{len(segments)}")
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for i, segment in enumerate(segments):
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start_str = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(segment['start_time']))
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end_str = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(segment['end_time']))
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last_str = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(segment['last_msg_time']))
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status_lines.append(f" 段{i+1}: {start_str} -> {end_str} (最后消息: {last_str}, 消息数: {segment['message_count']})")
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status_lines.append("")
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return "\n".join(status_lines)
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def _update_user_message_segments(self, message: MessageRecv):
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"""更新用户消息段信息"""
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current_time = time.time()
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user_id = message.message_info.user_info.user_id
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platform = message.message_info.platform
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msg_time = message.message_info.time
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# 跳过机器人自己的消息
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if user_id == global_config.bot.qq_account:
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return
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# 只处理新消息（避免重复处理）
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if msg_time <= self.last_processed_message_time:
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return
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person_id = PersonInfoManager.get_person_id(platform, user_id)
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self._update_message_segments(person_id, msg_time)
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# 更新最后处理时间
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self.last_processed_message_time = max(self.last_processed_message_time, msg_time)
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logger.debug(f"[{self.stream_name}] 更新用户 {person_id} 的消息段，消息时间：{time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(msg_time))}")
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# 改为实例方法
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async def _create_thinking_message(self, message: MessageRecv, timestamp: Optional[float] = None) -> str:
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"""创建思考消息"""
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@@ -282,8 +583,11 @@ class NormalChat:
|
||||
logger.info(f"[{self.stream_name}] 已停用，忽略 normal_response。")
|
||||
return
|
||||
|
||||
# 更新engaging_persons统计信息
|
||||
self._update_engaging_person_stats(message, is_reply=False)
|
||||
# 执行定期清理
|
||||
self._cleanup_old_segments()
|
||||
|
||||
# 更新消息段信息
|
||||
self._update_user_message_segments(message)
|
||||
|
||||
# 检查是否有用户满足关系构建条件
|
||||
asyncio.create_task(self._check_relation_building_conditions())
|
||||
@@ -477,8 +781,7 @@ class NormalChat:
|
||||
|
||||
# 检查 first_bot_msg 是否为 None (例如思考消息已被移除的情况)
|
||||
if first_bot_msg:
|
||||
# 更新engaging_persons统计信息 - 标记为回复
|
||||
self._update_engaging_person_stats(message, is_reply=True)
|
||||
# 消息段已在接收消息时更新，这里不需要额外处理
|
||||
|
||||
# 记录回复信息到最近回复列表中
|
||||
reply_info = {
|
||||
@@ -769,200 +1072,91 @@ class NormalChat:
|
||||
"""获取动作管理器实例"""
|
||||
return self.action_manager
|
||||
|
||||
def _update_engaging_person_stats(self, message: MessageRecv, is_reply: bool):
|
||||
"""更新engaging_persons统计信息"""
|
||||
# 通过platform和user_id计算person_id
|
||||
platform = message.message_info.platform
|
||||
user_id = message.message_info.user_info.user_id
|
||||
person_id = PersonInfoManager.get_person_id(platform, user_id)
|
||||
current_time = time.time()
|
||||
|
||||
if person_id not in self.engaging_persons:
|
||||
self.engaging_persons[person_id] = {
|
||||
"first_time": current_time,
|
||||
"last_time": current_time,
|
||||
"receive_count": 0,
|
||||
"reply_count": 0,
|
||||
"relation_built": False,
|
||||
}
|
||||
|
||||
if is_reply:
|
||||
self.engaging_persons[person_id]["reply_count"] += 1
|
||||
logger.debug(
|
||||
f"[{self.stream_name}] 用户 {person_id} 回复次数更新: {self.engaging_persons[person_id]['reply_count']}"
|
||||
)
|
||||
else:
|
||||
self.engaging_persons[person_id]["receive_count"] += 1
|
||||
self.engaging_persons[person_id]["last_time"] = current_time
|
||||
logger.debug(
|
||||
f"[{self.stream_name}] 用户 {person_id} 消息次数更新: {self.engaging_persons[person_id]['receive_count']}"
|
||||
)
|
||||
|
||||
async def _check_relation_building_conditions(self):
|
||||
"""检查engaging_persons中是否有满足关系构建条件的用户"""
|
||||
current_time = time.time()
|
||||
|
||||
for person_id, stats in list(self.engaging_persons.items()):
|
||||
# 计算时间差和消息数量
|
||||
time_elapsed = current_time - stats["first_time"]
|
||||
total_messages = self._get_total_messages_in_timerange(stats["first_time"], stats["last_time"])
|
||||
|
||||
# print(f"person_id: {person_id}, total_messages: {total_messages}, time_elapsed: {time_elapsed}")
|
||||
|
||||
# 检查是否满足关系构建条件
|
||||
should_build_relation = (
|
||||
total_messages >= 30 # 30条消息必定满足
|
||||
or (total_messages >= 15 and time_elapsed >= 600) # 15条且10分钟
|
||||
or (total_messages >= 10 and time_elapsed >= 900) # 10条且15分钟
|
||||
or (total_messages >= 5 and time_elapsed >= 1800) # 5条且30
|
||||
)
|
||||
|
||||
if should_build_relation:
|
||||
"""检查person_engaged_cache中是否有满足关系构建条件的用户"""
|
||||
users_to_build_relationship = []
|
||||
|
||||
for person_id, segments in list(self.person_engaged_cache.items()):
|
||||
total_message_count = self._get_total_message_count(person_id)
|
||||
if total_message_count >= 45:
|
||||
users_to_build_relationship.append(person_id)
|
||||
logger.info(
|
||||
f"[{self.stream_name}] 用户 {person_id} 满足关系构建条件。"
|
||||
f"消息数：{total_messages}，时长：{time_elapsed:.0f}秒，"
|
||||
f"收到消息：{stats['receive_count']}，回复次数：{stats['reply_count']}"
|
||||
f"[{self.stream_name}] 用户 {person_id} 满足关系构建条件，总消息数：{total_message_count}，消息段数：{len(segments)}"
|
||||
)
|
||||
elif total_message_count > 0:
|
||||
# 记录进度信息
|
||||
logger.debug(
|
||||
f"[{self.stream_name}] 用户 {person_id} 进度：{total_message_count}/45 条消息，{len(segments)} 个消息段"
|
||||
)
|
||||
|
||||
# 计算构建概率并决定是否构建
|
||||
await self._evaluate_and_build_relation(person_id, stats, total_messages)
|
||||
|
||||
# 评估完成后移除该用户，重新开始统计
|
||||
del self.engaging_persons[person_id]
|
||||
logger.info(f"[{self.stream_name}] 用户 {person_id} 评估完成，已移除记录，将重新开始统计")
|
||||
|
||||
def _get_total_messages_in_timerange(self, start_time: float, end_time: float) -> int:
|
||||
"""获取指定时间范围内的总消息数量"""
|
||||
try:
|
||||
messages = get_raw_msg_by_timestamp_with_chat(self.stream_id, start_time, end_time)
|
||||
return len(messages) if messages else 0
|
||||
except Exception as e:
|
||||
logger.error(f"[{self.stream_name}] 获取时间范围内消息数量失败: {e}")
|
||||
return 0
|
||||
|
||||
async def _evaluate_and_build_relation(self, person_id: str, stats: dict, total_messages: int):
|
||||
"""评估并执行关系构建"""
|
||||
import math
|
||||
|
||||
receive_count = stats["receive_count"]
|
||||
reply_count = stats["reply_count"]
|
||||
|
||||
# 计算回复概率（reply_count在总消息中的比值）
|
||||
reply_ratio = reply_count / total_messages if total_messages > 0 else 0
|
||||
# 使用对数函数让低比率时概率上升更快：log(1 + ratio * k) / log(1 + k) + base
|
||||
# k=7时，0.05比率对应约0.4概率，0.1比率对应约0.6概率，0.2比率对应约0.8概率
|
||||
k_reply = 10 * global_config.relationship.relation_frequency
|
||||
base_reply_prob = 0.1 # 基础概率10%
|
||||
reply_build_probability = (
|
||||
(math.log(1 + reply_ratio * k_reply) / math.log(1 + k_reply)) * 0.9 + base_reply_prob
|
||||
if reply_ratio > 0
|
||||
else base_reply_prob
|
||||
)
|
||||
|
||||
# 计算接收概率（receive_count的影响）
|
||||
receive_ratio = receive_count / total_messages if total_messages > 0 else 0
|
||||
# 接收概率使用更温和的对数曲线，最大0.5，基础0.08
|
||||
k_receive = 10 * global_config.relationship.relation_frequency
|
||||
base_receive_prob = 0.08 # 基础概率8%
|
||||
receive_build_probability = (
|
||||
(math.log(1 + receive_ratio * k_receive) / math.log(1 + k_receive)) * 0.42 + base_receive_prob
|
||||
if receive_ratio > 0
|
||||
else base_receive_prob
|
||||
)
|
||||
|
||||
# 取最高概率
|
||||
final_probability = max(reply_build_probability, receive_build_probability)
|
||||
|
||||
logger.info(
|
||||
f"[{self.stream_name}] 用户 {person_id} 关系构建概率评估："
|
||||
f"回复比例：{reply_ratio:.2f}(对数概率:{reply_build_probability:.2f})"
|
||||
f"，接收比例：{receive_ratio:.2f}(对数概率:{receive_build_probability:.2f})"
|
||||
f"，最终概率：{final_probability:.2f}"
|
||||
)
|
||||
|
||||
# 使用随机数决定是否构建关系
|
||||
if random() < final_probability:
|
||||
logger.info(f"[{self.stream_name}] 决定为用户 {person_id} 构建关系")
|
||||
await self._build_relation_for_person(person_id, stats)
|
||||
else:
|
||||
logger.info(f"[{self.stream_name}] 用户 {person_id} 未通过关系构建概率判定")
|
||||
|
||||
async def _build_relation_for_person(self, person_id: str, stats: dict):
|
||||
"""为特定用户构建关系"""
|
||||
try:
|
||||
start_time = stats["first_time"]
|
||||
end_time = stats["last_time"]
|
||||
|
||||
# 获取该时间段的所有消息用于关系构建
|
||||
main_messages = get_raw_msg_by_timestamp_with_chat(self.stream_id, start_time, end_time)
|
||||
|
||||
if not main_messages:
|
||||
logger.warning(f"[{self.stream_name}] 未找到用户 {person_id} 的消息，关系构建跳过")
|
||||
return
|
||||
|
||||
# 获取第一条消息的时间戳，然后获取之前的5条消息
|
||||
first_message_time = main_messages[0]["time"]
|
||||
before_messages = self._get_messages_before_timestamp(first_message_time, 5)
|
||||
|
||||
# 获取最后一条消息的时间戳，然后获取之后的5条消息
|
||||
last_message_time = main_messages[-1]["time"]
|
||||
after_messages = self._get_messages_after_timestamp(last_message_time, 5)
|
||||
|
||||
# 合并所有消息并去重
|
||||
all_messages = before_messages + main_messages + after_messages
|
||||
|
||||
# 根据消息ID去重并按时间排序
|
||||
seen_ids = set()
|
||||
unique_messages = []
|
||||
for msg in all_messages:
|
||||
msg_id = msg["message_id"]
|
||||
if msg_id not in seen_ids:
|
||||
seen_ids.add(msg_id)
|
||||
unique_messages.append(msg)
|
||||
|
||||
# 按时间排序
|
||||
unique_messages.sort(key=lambda x: x["time"])
|
||||
|
||||
logger.info(
|
||||
f"[{self.stream_name}] 为用户 {person_id} 获取到消息用于关系构建: "
|
||||
f"原时间段内 {len(main_messages)} 条，之前 {len(before_messages)} 条，"
|
||||
f"之后 {len(after_messages)} 条，去重后总计 {len(unique_messages)} 条"
|
||||
# 为满足条件的用户构建关系
|
||||
for person_id in users_to_build_relationship:
|
||||
segments = self.person_engaged_cache[person_id]
|
||||
# 异步执行关系构建
|
||||
asyncio.create_task(
|
||||
self._build_relation_for_person_segments(person_id, segments)
|
||||
)
|
||||
# 移除已处理的用户缓存
|
||||
del self.person_engaged_cache[person_id]
|
||||
self._save_cache()
|
||||
logger.info(f"[{self.stream_name}] 用户 {person_id} 关系构建已启动，缓存已清理")
|
||||
|
||||
# 调用关系管理器更新印象
|
||||
relationship_manager = get_relationship_manager()
|
||||
await relationship_manager.update_person_impression(
|
||||
person_id=person_id, timestamp=end_time, bot_engaged_messages=unique_messages
|
||||
)
|
||||
|
||||
logger.info(f"[{self.stream_name}] 用户 {person_id} 关系构建完成")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[{self.stream_name}] 为用户 {person_id} 构建关系时出错: {e}")
|
||||
traceback.print_exc()
|
||||
|
||||
def _get_messages_before_timestamp(self, timestamp: float, limit: int = 5) -> List[Dict[str, Any]]:
|
||||
"""获取指定时间戳之前的指定数量消息"""
|
||||
async def _build_relation_for_person_segments(self, person_id: str, segments: List[Dict[str, any]]):
|
||||
"""基于消息段为特定用户构建关系"""
|
||||
logger.info(f"[{self.stream_name}] 开始为 {person_id} 基于 {len(segments)} 个消息段更新印象")
|
||||
try:
|
||||
from src.common.message_repository import find_messages
|
||||
processed_messages = []
|
||||
|
||||
for i, segment in enumerate(segments):
|
||||
start_time = segment["start_time"]
|
||||
end_time = segment["end_time"]
|
||||
message_count = segment["message_count"]
|
||||
start_date = time.strftime('%Y-%m-%d %H:%M', time.localtime(start_time))
|
||||
|
||||
# 获取该段的消息（包含边界）
|
||||
segment_messages = get_raw_msg_by_timestamp_with_chat_inclusive(self.stream_id, start_time, end_time)
|
||||
logger.info(f"[{self.stream_name}] 消息段 {i+1}: {start_date} - {time.strftime('%Y-%m-%d %H:%M', time.localtime(end_time))}, 消息数: {len(segment_messages)}")
|
||||
|
||||
if segment_messages:
|
||||
# 如果不是第一个消息段，在消息列表前添加间隔标识
|
||||
if i > 0:
|
||||
# 创建一个特殊的间隔消息
|
||||
gap_message = {
|
||||
"time": start_time - 0.1, # 稍微早于段开始时间
|
||||
"user_id": "system",
|
||||
"user_platform": "system",
|
||||
"user_nickname": "系统",
|
||||
"user_cardname": "",
|
||||
"display_message": f"...（中间省略一些消息）{start_date} 之后的消息如下...",
|
||||
"is_action_record": True,
|
||||
"chat_info_platform": segment_messages[0].get("chat_info_platform", ""),
|
||||
"chat_id": self.stream_id
|
||||
}
|
||||
processed_messages.append(gap_message)
|
||||
|
||||
# 添加该段的所有消息
|
||||
processed_messages.extend(segment_messages)
|
||||
|
||||
if processed_messages:
|
||||
# 按时间排序所有消息（包括间隔标识）
|
||||
processed_messages.sort(key=lambda x: x['time'])
|
||||
|
||||
logger.info(f"[{self.stream_name}] 为 {person_id} 获取到总共 {len(processed_messages)} 条消息（包含间隔标识）用于印象更新")
|
||||
relationship_manager = get_relationship_manager()
|
||||
|
||||
# 调用原有的更新方法
|
||||
await relationship_manager.update_person_impression(
|
||||
person_id=person_id,
|
||||
timestamp=time.time(),
|
||||
bot_engaged_messages=processed_messages
|
||||
)
|
||||
|
||||
logger.info(f"[{self.stream_name}] 用户 {person_id} 关系构建完成")
|
||||
else:
|
||||
logger.warning(f"[{self.stream_name}] 没有找到 {person_id} 的消息段对应的消息，不更新印象")
|
||||
|
||||
filter_query = {"chat_id": self.stream_id, "time": {"$lt": timestamp}}
|
||||
sort_order = [("time", -1)] # 倒序排列，取最近的几条
|
||||
messages = find_messages(message_filter=filter_query, sort=sort_order, limit=limit)
|
||||
# 返回时保持正序
|
||||
return sorted(messages, key=lambda x: x["time"])
|
||||
except Exception as e:
|
||||
logger.error(f"[{self.stream_name}] 获取时间戳之前的消息失败: {e}")
|
||||
return []
|
||||
|
||||
def _get_messages_after_timestamp(self, timestamp: float, limit: int = 5) -> List[Dict[str, Any]]:
|
||||
"""获取指定时间戳之后的指定数量消息"""
|
||||
try:
|
||||
from src.common.message_repository import find_messages
|
||||
|
||||
filter_query = {"chat_id": self.stream_id, "time": {"$gt": timestamp}}
|
||||
sort_order = [("time", 1)] # 正序排列，取最早的几条
|
||||
return find_messages(message_filter=filter_query, sort=sort_order, limit=limit)
|
||||
except Exception as e:
|
||||
logger.error(f"[{self.stream_name}] 获取时间戳之后的消息失败: {e}")
|
||||
return []
|
||||
logger.error(f"[{self.stream_name}] 为 {person_id} 更新印象时发生错误: {e}")
|
||||
logger.error(traceback.format_exc())
|
||||
|
||||
Reference in New Issue
Block a user