""" Episodic Memory Service 处理情景记忆相关的业务逻辑，包括情景记忆总览、详情查询等。 """ from datetime import datetime, timedelta from typing import Any, Dict, List, Optional, Tuple import pytz from app.core.logging_config import get_logger from app.services.memory_base_service import MemoryBaseService logger = get_logger(__name__) class MemoryEpisodicService(MemoryBaseService): """情景记忆服务类""" def __init__(self): super().__init__() logger.info("MemoryEpisodicService initialized") async def _get_title_and_type( self, summary_id: str, end_user_id: str ) -> Tuple[str, str]: """ 读取情景记忆的标题(title)和类型(type) 仅负责读取已存在的title和type，不进行生成 title从name属性读取，type从memory_type属性读取 Args: summary_id: Summary节点的ID end_user_id: 终端用户ID (end_user_id) Returns: (标题, 类型)元组，如果不存在则返回默认值 """ try: # 查询Summary节点的name(作为title)和memory_type(作为type) query = """ MATCH (s:MemorySummary) WHERE elementId(s) = $summary_id AND s.end_user_id = $end_user_id RETURN s.name AS title, s.memory_type AS type """ result = await self.neo4j_connector.execute_query( query, summary_id=summary_id, end_user_id=end_user_id ) if not result or len(result) == 0: logger.warning(f"未找到 summary_id={summary_id} 的节点") return ("未知标题", "其他") record = result[0] title = record.get("title") or "未命名" episodic_type = record.get("type") or "其他" return (title, episodic_type) except Exception as e: logger.error(f"读取标题和类型时出错: {str(e)}", exc_info=True) return ("错误", "其他") async def _extract_involved_objects( self, summary_id: str, end_user_id: str ) -> List[str]: """ 提取情景记忆涉及的前3个最重要实体 Args: summary_id: Summary节点的ID end_user_id: 终端用户ID (end_user_id) Returns: 前3个实体的name属性列表 """ try: # 查询Summary节点指向的Statement节点,再查询Statement指向的ExtractedEntity节点 # 按activation_value降序排序,返回前3个 query = """ MATCH (s:MemorySummary) WHERE elementId(s) = $summary_id AND s.end_user_id = $end_user_id MATCH (s)-[:DERIVED_FROM_STATEMENT]->(stmt:Statement) MATCH (stmt)-[:REFERENCES_ENTITY]->(entity:ExtractedEntity) WHERE entity.activation_value IS NOT NULL RETURN DISTINCT entity.name AS name, entity.activation_value AS activation ORDER BY activation DESC LIMIT 3 """ result = await self.neo4j_connector.execute_query( query, summary_id=summary_id, end_user_id=end_user_id ) # 提取实体名称 involved_objects = [record["name"] for record in result if record.get("name")] logger.info(f"成功提取 summary_id={summary_id} 的涉及对象: {involved_objects}") return involved_objects except Exception as e: logger.error(f"提取涉及对象时出错: {str(e)}", exc_info=True) return [] async def _extract_content_records( self, summary_id: str, end_user_id: str ) -> List[str]: """ 提取情景记忆的内容记录 Args: summary_id: Summary节点的ID end_user_id: 终端用户ID (end_user_id) Returns: 所有Statement节点的statement属性内容列表 """ try: # 查询Summary节点指向的所有Statement节点 query = """ MATCH (s:MemorySummary) WHERE elementId(s) = $summary_id AND s.end_user_id = $end_user_id MATCH (s)-[:DERIVED_FROM_STATEMENT]->(stmt:Statement) WHERE stmt.statement IS NOT NULL AND stmt.statement <> '' RETURN stmt.statement AS statement """ result = await self.neo4j_connector.execute_query( query, summary_id=summary_id, end_user_id=end_user_id ) # 提取statement内容 content_records = [record["statement"] for record in result if record.get("statement")] logger.info(f"成功提取 summary_id={summary_id} 的内容记录,共 {len(content_records)} 条") return content_records except Exception as e: logger.error(f"提取内容记录时出错: {str(e)}", exc_info=True) return [] def _calculate_time_filter(self, time_range: str) -> Optional[str]: """ 根据时间范围计算过滤的起始时间 Args: time_range: 时间范围 (all/today/this_week/this_month) Returns: ISO格式的时间字符串，如果是"all"则返回None """ if time_range == "all": return None # 获取当前时间（UTC） now = datetime.now(pytz.UTC) if time_range == "today": # 今天的开始时间（00:00:00） start_time = now.replace(hour=0, minute=0, second=0, microsecond=0) elif time_range == "this_week": # 本周的开始时间（周一00:00:00） days_since_monday = now.weekday() start_time = (now - timedelta(days=days_since_monday)).replace( hour=0, minute=0, second=0, microsecond=0 ) elif time_range == "this_month": # 本月的开始时间（1号00:00:00） start_time = now.replace(day=1, hour=0, minute=0, second=0, microsecond=0) else: return None # 返回ISO格式字符串 return start_time.isoformat() async def get_episodic_memory_overview( self, end_user_id: str, time_range: str = "all", episodic_type: str = "all", title_keyword: Optional[str] = None ) -> Dict[str, Any]: """ 获取情景记忆总览信息 Args: end_user_id: 终端用户ID time_range: 时间范围筛选 episodic_type: 情景类型筛选 title_keyword: 标题关键词（可选，用于模糊搜索） """ try: logger.info( f"开始查询 end_user_id={end_user_id} 的情景记忆总览, " f"time_range={time_range}, episodic_type={episodic_type}, title_keyword={title_keyword}" ) # 1. 先查询所有情景记忆的总数（不受筛选条件限制） total_all_query = """ MATCH (s:MemorySummary) WHERE s.end_user_id = $end_user_id RETURN count(s) AS total_all """ total_all_result = await self.neo4j_connector.execute_query( total_all_query, end_user_id=end_user_id ) total_all = total_all_result[0]["total_all"] if total_all_result else 0 # 2. 计算时间范围的起始时间戳 time_filter = self._calculate_time_filter(time_range) # 3. 构建Cypher查询 query = """ MATCH (s:MemorySummary) WHERE s.end_user_id = $end_user_id """ # 添加时间范围过滤 if time_filter: query += " AND s.created_at >= $time_filter" # 添加标题关键词过滤（如果提供了title_keyword） if title_keyword: query += " AND toLower(s.name) CONTAINS toLower($title_keyword)" query += """ RETURN elementId(s) AS id, s.created_at AS created_at, s.memory_type AS type, s.name AS title ORDER BY s.created_at DESC """ params = {"end_user_id": end_user_id} if time_filter: params["time_filter"] = time_filter if title_keyword: params["title_keyword"] = title_keyword result = await self.neo4j_connector.execute_query(query, **params) # 4. 如果没有数据，返回空列表 if not result: logger.info(f"end_user_id={end_user_id} 没有情景记忆数据") return { "total": 0, "total_all": total_all, "episodic_memories": [] } # 5. 对每个节点读取标题和类型，并应用类型筛选 episodic_memories = [] for record in result: summary_id = record["id"] created_at_str = record.get("created_at") memory_type = record.get("type", "其他") title = record.get("title") or "未命名" # 直接从查询结果获取标题 # 应用情景类型筛选 if episodic_type != "all": # 检查类型是否匹配 # 注意：Neo4j 中存储的 memory_type 现在应该是英文格式（如 "conversation", "project_work"） # 但为了兼容旧数据，我们也支持中文格式的匹配 type_mapping = { "conversation": "对话", "project_work": "项目/工作", "learning": "学习", "decision": "决策", "important_event": "重要事件" } # 获取对应的中文类型（用于兼容旧数据） chinese_type = type_mapping.get(episodic_type) # 检查类型是否匹配（支持新的英文格式和旧的中文格式） if memory_type != episodic_type and memory_type != chinese_type: continue # 使用基类方法转换时间戳 created_at_timestamp = self.parse_timestamp(created_at_str) episodic_memories.append({ "id": summary_id, "title": title, "type": memory_type, "created_at": created_at_timestamp }) logger.info( f"成功获取 end_user_id={end_user_id} 的情景记忆总览," f"筛选后 {len(episodic_memories)} 条，总共 {total_all} 条" ) return { "total": len(episodic_memories), "total_all": total_all, "episodic_memories": episodic_memories } except Exception as e: logger.error(f"获取情景记忆总览时出错: {str(e)}", exc_info=True) raise async def get_episodic_memory_details( self, end_user_id: str, summary_id: str ) -> Dict[str, Any]: """ 获取单个情景记忆的详细信息 """ try: logger.info(f"开始查询 end_user_id={end_user_id}, summary_id={summary_id} 的情景记忆详情") # 1. 查询指定的MemorySummary节点 query = """ MATCH (s:MemorySummary) WHERE elementId(s) = $summary_id AND s.end_user_id = $end_user_id RETURN elementId(s) AS id, s.created_at AS created_at """ result = await self.neo4j_connector.execute_query( query, summary_id=summary_id, end_user_id=end_user_id ) # 2. 如果节点不存在，返回错误 if not result or len(result) == 0: logger.warning(f"未找到 summary_id={summary_id} 的情景记忆") raise ValueError(f"情景记忆不存在: summary_id={summary_id}") # 3. 获取基本信息 record = result[0] created_at_str = record.get("created_at") # 使用基类方法转换时间戳 created_at_timestamp = self.parse_timestamp(created_at_str) # 4. 调用_get_title_and_type读取标题和类型 title, episodic_type = await self._get_title_and_type( summary_id=summary_id, end_user_id=end_user_id ) # 5. 调用_extract_involved_objects提取涉及对象 involved_objects = await self._extract_involved_objects( summary_id=summary_id, end_user_id=end_user_id ) # 6. 调用_extract_content_records提取内容记录 content_records = await self._extract_content_records( summary_id=summary_id, end_user_id=end_user_id ) # 7. 使用基类方法提取情绪 emotion = await self.extract_episodic_emotion( summary_id=summary_id, end_user_id=end_user_id ) # 8. 返回完整的详情信息 details = { "id": summary_id, "created_at": created_at_timestamp, "involved_objects": involved_objects, "episodic_type": episodic_type, "content_records": content_records, "emotion": emotion } logger.info(f"成功获取 summary_id={summary_id} 的情景记忆详情") return details except ValueError: # 重新抛出ValueError，让Controller层处理 raise except Exception as e: logger.error(f"获取情景记忆详情时出错: {str(e)}", exc_info=True) raise # 创建全局服务实例（供控制器层使用） memory_episodic_service = MemoryEpisodicService()