import time import traceback import os import pickle import random from typing import List, Dict from src.config.config import global_config from src.common.logger import get_logger from src.chat.message_receive.chat_stream import get_chat_manager from src.person_info.relationship_manager import get_relationship_manager from src.person_info.person_info import get_person_info_manager, PersonInfoManager 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, ) logger = get_logger("relationship_builder") # 消息段清理配置 SEGMENT_CLEANUP_CONFIG = { "enable_cleanup": True, # 是否启用清理 "max_segment_age_days": 3, # 消息段最大保存天数 "max_segments_per_user": 10, # 每用户最大消息段数 "cleanup_interval_hours": 0.5, # 清理间隔（小时） } MAX_MESSAGE_COUNT = 80 / global_config.relationship.relation_frequency class RelationshipBuilder: """关系构建器 独立运行的关系构建类，基于特定的chat_id进行工作 负责跟踪用户消息活动、管理消息段、触发关系构建和印象更新 """ def __init__(self, chat_id: str): """初始化关系构建器 Args: chat_id: 聊天ID """ self.chat_id = chat_id # 新的消息段缓存结构： # {person_id: [{"start_time": float, "end_time": float, "last_msg_time": float, "message_count": int}, ...]} self.person_engaged_cache: Dict[str, List[Dict[str, any]]] = {} # 持久化存储文件路径 self.cache_file_path = os.path.join("data", "relationship", f"relationship_cache_{self.chat_id}.pkl") # 最后处理的消息时间，避免重复处理相同消息 current_time = time.time() self.last_processed_message_time = current_time # 最后清理时间，用于定期清理老消息段 self.last_cleanup_time = 0.0 # 获取聊天名称用于日志 try: chat_name = get_chat_manager().get_stream_name(self.chat_id) self.log_prefix = f"[{chat_name}] 关系构建" except Exception: self.log_prefix = f"[{self.chat_id}] 关系构建" # 加载持久化的缓存 self._load_cache() # ================================ # 缓存管理模块 # 负责持久化存储、状态管理、缓存读写 # ================================ def _load_cache(self): """从文件加载持久化的缓存""" if os.path.exists(self.cache_file_path): try: with open(self.cache_file_path, "rb") as f: cache_data = pickle.load(f) # 新格式：包含额外信息的缓存 self.person_engaged_cache = cache_data.get("person_engaged_cache", {}) self.last_processed_message_time = cache_data.get("last_processed_message_time", 0.0) self.last_cleanup_time = cache_data.get("last_cleanup_time", 0.0) logger.info( f"{self.log_prefix} 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'}" ) except Exception as e: logger.error(f"{self.log_prefix} 加载关系缓存失败: {e}") self.person_engaged_cache = {} self.last_processed_message_time = 0.0 else: logger.info(f"{self.log_prefix} 关系缓存文件不存在，使用空缓存") def _save_cache(self): """保存缓存到文件""" try: os.makedirs(os.path.dirname(self.cache_file_path), exist_ok=True) cache_data = { "person_engaged_cache": self.person_engaged_cache, "last_processed_message_time": self.last_processed_message_time, "last_cleanup_time": self.last_cleanup_time, } with open(self.cache_file_path, "wb") as f: pickle.dump(cache_data, f) logger.debug(f"{self.log_prefix} 成功保存关系缓存") except Exception as e: logger.error(f"{self.log_prefix} 保存关系缓存失败: {e}") # ================================ # 消息段管理模块 # 负责跟踪用户消息活动、管理消息段、清理过期数据 # ================================ def _update_message_segments(self, person_id: str, message_time: float): """更新用户的消息段 Args: person_id: 用户ID message_time: 消息时间戳 """ if person_id not in self.person_engaged_cache: self.person_engaged_cache[person_id] = [] segments = self.person_engaged_cache[person_id] # 获取该消息前5条消息的时间作为潜在的开始时间 before_messages = get_raw_msg_before_timestamp_with_chat(self.chat_id, message_time, limit=5) if before_messages: potential_start_time = before_messages[0]["time"] else: potential_start_time = message_time # 如果没有现有消息段，创建新的 if not segments: new_segment = { "start_time": potential_start_time, "end_time": message_time, "last_msg_time": message_time, "message_count": self._count_messages_in_timerange(potential_start_time, message_time), } segments.append(new_segment) person_name = get_person_info_manager().get_value_sync(person_id, "person_name") or person_id logger.debug( f"{self.log_prefix} 眼熟用户 {person_name} 在 {time.strftime('%H:%M:%S', time.localtime(potential_start_time))} - {time.strftime('%H:%M:%S', time.localtime(message_time))} 之间有 {new_segment['message_count']} 条消息" ) self._save_cache() return # 获取最后一个消息段 last_segment = segments[-1] # 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） messages_between = self._count_messages_between(last_segment["last_msg_time"], message_time) if messages_between <= 10: # 在10条消息内，延伸当前消息段 last_segment["end_time"] = message_time last_segment["last_msg_time"] = message_time # 重新计算整个消息段的消息数量 last_segment["message_count"] = self._count_messages_in_timerange( last_segment["start_time"], last_segment["end_time"] ) logger.debug(f"{self.log_prefix} 延伸用户 {person_id} 的消息段: {last_segment}") else: # 超过10条消息，结束当前消息段并创建新的 # 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 current_time = time.time() after_messages = get_raw_msg_by_timestamp_with_chat( self.chat_id, last_segment["last_msg_time"], current_time, limit=5, limit_mode="earliest" ) if after_messages and len(after_messages) >= 5: # 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 last_segment["end_time"] = after_messages[4]["time"] # 重新计算当前消息段的消息数量 last_segment["message_count"] = self._count_messages_in_timerange( last_segment["start_time"], last_segment["end_time"] ) # 创建新的消息段 new_segment = { "start_time": potential_start_time, "end_time": message_time, "last_msg_time": message_time, "message_count": self._count_messages_in_timerange(potential_start_time, message_time), } segments.append(new_segment) person_info_manager = get_person_info_manager() person_name = person_info_manager.get_value_sync(person_id, "person_name") or person_id logger.debug( f"{self.log_prefix} 重新眼熟用户 {person_name} 创建新消息段（超过10条消息间隔）: {new_segment}" ) self._save_cache() def _count_messages_in_timerange(self, start_time: float, end_time: float) -> int: """计算指定时间范围内的消息数量（包含边界）""" messages = get_raw_msg_by_timestamp_with_chat_inclusive(self.chat_id, start_time, end_time) return len(messages) def _count_messages_between(self, start_time: float, end_time: float) -> int: """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""" return num_new_messages_since(self.chat_id, start_time, end_time) def _get_total_message_count(self, person_id: str) -> int: """获取用户所有消息段的总消息数量""" if person_id not in self.person_engaged_cache: return 0 total_count = 0 for segment in self.person_engaged_cache[person_id]: total_count += segment["message_count"] return total_count def _cleanup_old_segments(self) -> bool: """清理老旧的消息段""" if not SEGMENT_CLEANUP_CONFIG["enable_cleanup"]: return False current_time = time.time() # 检查是否需要执行清理（基于时间间隔） cleanup_interval_seconds = SEGMENT_CLEANUP_CONFIG["cleanup_interval_hours"] * 3600 if current_time - self.last_cleanup_time < cleanup_interval_seconds: return False logger.info(f"{self.log_prefix} 开始执行老消息段清理...") cleanup_stats = { "users_cleaned": 0, "segments_removed": 0, "total_segments_before": 0, "total_segments_after": 0, } max_age_seconds = SEGMENT_CLEANUP_CONFIG["max_segment_age_days"] * 24 * 3600 max_segments_per_user = SEGMENT_CLEANUP_CONFIG["max_segments_per_user"] users_to_remove = [] for person_id, segments in self.person_engaged_cache.items(): cleanup_stats["total_segments_before"] += len(segments) original_segment_count = len(segments) # 1. 按时间清理：移除过期的消息段 segments_after_age_cleanup = [] for segment in segments: segment_age = current_time - segment["end_time"] if segment_age <= max_age_seconds: segments_after_age_cleanup.append(segment) else: cleanup_stats["segments_removed"] += 1 logger.debug( f"{self.log_prefix} 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']))}" ) # 2. 按数量清理：如果消息段数量仍然过多，保留最新的 if len(segments_after_age_cleanup) > max_segments_per_user: # 按end_time排序，保留最新的 segments_after_age_cleanup.sort(key=lambda x: x["end_time"], reverse=True) segments_removed_count = len(segments_after_age_cleanup) - max_segments_per_user cleanup_stats["segments_removed"] += segments_removed_count segments_after_age_cleanup = segments_after_age_cleanup[:max_segments_per_user] logger.debug( f"{self.log_prefix} 用户 {person_id} 消息段数量过多，移除 {segments_removed_count} 个最老的消息段" ) # 更新缓存 if len(segments_after_age_cleanup) == 0: # 如果没有剩余消息段，标记用户为待移除 users_to_remove.append(person_id) else: self.person_engaged_cache[person_id] = segments_after_age_cleanup cleanup_stats["total_segments_after"] += len(segments_after_age_cleanup) if original_segment_count != len(segments_after_age_cleanup): cleanup_stats["users_cleaned"] += 1 # 移除没有消息段的用户 for person_id in users_to_remove: del self.person_engaged_cache[person_id] logger.debug(f"{self.log_prefix} 移除用户 {person_id}：没有剩余消息段") # 更新最后清理时间 self.last_cleanup_time = current_time # 保存缓存 if cleanup_stats["segments_removed"] > 0 or len(users_to_remove) > 0: self._save_cache() logger.info( f"{self.log_prefix} 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)}" ) logger.info( f"{self.log_prefix} 消息段统计 - 清理前: {cleanup_stats['total_segments_before']}, 清理后: {cleanup_stats['total_segments_after']}" ) else: logger.debug(f"{self.log_prefix} 清理完成 - 无需清理任何内容") return cleanup_stats["segments_removed"] > 0 or len(users_to_remove) > 0 def force_cleanup_user_segments(self, person_id: str) -> bool: """强制清理指定用户的所有消息段""" if person_id in self.person_engaged_cache: segments_count = len(self.person_engaged_cache[person_id]) del self.person_engaged_cache[person_id] self._save_cache() logger.info(f"{self.log_prefix} 强制清理用户 {person_id} 的 {segments_count} 个消息段") return True return False def get_cache_status(self) -> str: """获取缓存状态信息，用于调试和监控""" if not self.person_engaged_cache: return f"{self.log_prefix} 关系缓存为空" status_lines = [f"{self.log_prefix} 关系缓存状态："] 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'}" ) 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'}" ) status_lines.append(f"总用户数：{len(self.person_engaged_cache)}") 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)" ) status_lines.append("") for person_id, segments in self.person_engaged_cache.items(): total_count = self._get_total_message_count(person_id) status_lines.append(f"用户 {person_id}:") status_lines.append(f" 总消息数：{total_count} ({total_count}/60)") status_lines.append(f" 消息段数：{len(segments)}") for i, segment in enumerate(segments): start_str = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(segment["start_time"])) end_str = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(segment["end_time"])) last_str = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(segment["last_msg_time"])) status_lines.append( f" 段{i + 1}: {start_str} -> {end_str} (最后消息: {last_str}, 消息数: {segment['message_count']})" ) status_lines.append("") return "\n".join(status_lines) # ================================ # 主要处理流程 # 统筹各模块协作、对外提供服务接口 # ================================ async def build_relation(self): """构建关系""" self._cleanup_old_segments() current_time = time.time() latest_messages = get_raw_msg_by_timestamp_with_chat( self.chat_id, self.last_processed_message_time, current_time, limit=50, # 获取自上次处理后的消息 ) if latest_messages: # 处理所有新的非bot消息 for latest_msg in latest_messages: user_id = latest_msg.get("user_id") platform = latest_msg.get("user_platform") or latest_msg.get("chat_info_platform") msg_time = latest_msg.get("time", 0) if ( user_id and platform and user_id != global_config.bot.qq_account and msg_time > self.last_processed_message_time ): person_id = PersonInfoManager.get_person_id(platform, user_id) self._update_message_segments(person_id, msg_time) logger.debug( f"{self.log_prefix} 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))}" ) self.last_processed_message_time = max(self.last_processed_message_time, msg_time) # 1. 检查是否有用户达到关系构建条件（总消息数达到45条） users_to_build_relationship = [] for person_id, segments in self.person_engaged_cache.items(): total_message_count = self._get_total_message_count(person_id) if total_message_count >= MAX_MESSAGE_COUNT: users_to_build_relationship.append(person_id) logger.debug( f"{self.log_prefix} 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.log_prefix} 用户 {person_id} 进度：{total_message_count}60 条消息，{len(segments)} 个消息段" ) # 2. 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 import asyncio asyncio.create_task(self.update_impression_on_segments(person_id, self.chat_id, segments)) # 移除已处理的用户缓存 del self.person_engaged_cache[person_id] self._save_cache() # ================================ # 关系构建模块 # 负责触发关系构建、整合消息段、更新用户印象 # ================================ async def update_impression_on_segments(self, person_id: str, chat_id: str, segments: List[Dict[str, any]]): """基于消息段更新用户印象""" original_segment_count = len(segments) logger.debug(f"开始为 {person_id} 基于 {original_segment_count} 个消息段更新印象") try: # 筛选要处理的消息段，每个消息段有10%的概率被丢弃 segments_to_process = [s for s in segments if random.random() >= 0.1] # 如果所有消息段都被丢弃，但原来有消息段，则至少保留一个（最新的） if not segments_to_process and segments: segments.sort(key=lambda x: x["end_time"], reverse=True) segments_to_process.append(segments[0]) logger.debug(f"随机丢弃了所有消息段，强制保留最新的一个以进行处理。") dropped_count = original_segment_count - len(segments_to_process) if dropped_count > 0: logger.info(f"为 {person_id} 随机丢弃了 {dropped_count} / {original_segment_count} 个消息段") processed_messages = [] # 对筛选后的消息段进行排序，确保时间顺序 segments_to_process.sort(key=lambda x: x["start_time"]) for segment in segments_to_process: start_time = segment["start_time"] end_time = segment["end_time"] 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.chat_id, start_time, end_time) logger.debug( f"消息段: {start_date} - {time.strftime('%Y-%m-%d %H:%M', time.localtime(end_time))}, 消息数: {len(segment_messages)}" ) if segment_messages: # 如果 processed_messages 不为空，说明这不是第一个被处理的消息段，在消息列表前添加间隔标识 if processed_messages: # 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": chat_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.debug(f"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 ) else: logger.info(f"没有找到 {person_id} 的消息段对应的消息，不更新印象") except Exception as e: logger.error(f"为 {person_id} 更新印象时发生错误: {e}") logger.error(traceback.format_exc())