From f6ca6a547fe759fb5dae855d7da7d4dc3a886a32 Mon Sep 17 00:00:00 2001 From: lixinyue11 <94037597+lixinyue11@users.noreply.github.com> Date: Mon, 12 Jan 2026 12:28:17 +0800 Subject: [PATCH] Fix/develop memory deail (#69) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * 新增记忆空间详情 * 新增记忆空间详情 * 新增记忆关联的数量 * 修改记忆时间线 * 修改记忆时间线 * 修改记忆时间线 * Parameterize elementId in Cypher query * 关系演化，互动频率优化 * 关系演化，互动频率优化 * 关系演化，互动频率优化 * 关系演化，互动频率优化 * 关系演化，互动频率优化 * 关系演化，互动频率优化 --------- Co-authored-by: Ke Sun <33739460+keeees@users.noreply.github.com> --- api/app/repositories/neo4j/cypher_queries.py | 46 +++----- .../memory_entity_relationship_service.py | 110 +++++++++++------- 2 files changed, 86 insertions(+), 70 deletions(-) diff --git a/api/app/repositories/neo4j/cypher_queries.py b/api/app/repositories/neo4j/cypher_queries.py index 71a18c84..7d77ad4f 100644 --- a/api/app/repositories/neo4j/cypher_queries.py +++ b/api/app/repositories/neo4j/cypher_queries.py @@ -727,7 +727,6 @@ SET m += { dialog_id: summary.dialog_id, chunk_ids: summary.chunk_ids, content: summary.content, - memory_type: summary.memory_type, summary_embedding: summary.summary_embedding, config_id: summary.config_id, importance_score: CASE WHEN summary.importance_score IS NOT NULL THEN summary.importance_score ELSE coalesce(m.importance_score, 0.5) END, @@ -942,7 +941,7 @@ RETURN """ Memory_Timeline_Statement=""" MATCH (n) -WHERE elementId(n) = "4:f6039a9b-d553-4ba2-9b1c-d9a18917801f:77003" +WHERE elementId(n) = $id CALL { WITH n @@ -995,7 +994,7 @@ RETURN """ Memory_Space_Emotion_MemorySummary=""" MATCH (n)-[]-(e) -WHERE elementId(n) = "4:f6039a9b-d553-4ba2-9b1c-d9a18917801f:77019" +WHERE elementId(n) = $id AND EXISTS { MATCH (e)-[]-(ms) WHERE ms:MemorySummary OR ms:ExtractedEntity @@ -1020,36 +1019,23 @@ RETURN DISTINCT """ '''获取实体''' -Memory_Space_Interaction_Statement=""" + +Memory_Space_User=""" +MATCH (n)-[r]->(m) +WHERE n.group_id = $group_id AND m.name="用户" +return DISTINCT elementId(m) as id +""" +Memory_Space_Entity=""" MATCH (n)-[]-(m) -WHERE elementId(n) = $id - AND m.entity_type = "Person" +WHERE elementId(m) = $id AND m.entity_type = "Person" RETURN - m.name AS name, - m.importance_score AS importance_score; - +DISTINCT m.name as name,m.group_id as group_id """ - -Memory_Space_Interaction_ExtractedEntity=""" -MATCH (n)-[]-(e) -WHERE elementId(n) = $id - AND EXISTS { - MATCH (e)-[]-(ms:ExtractedEntity) - } +Memory_Space_Associative=""" +MATCH (u)-[]-(x)-[]-(h) +WHERE elementId(u) = $user_id + AND elementId(h) = $id RETURN DISTINCT - e.name AS name, - e.importance_score AS importance_score; - + x.statement as statement,x.created_at as created_at """ -Memory_Space_Interaction_Summary=""" -MATCH (n)-[]-(e) -WHERE elementId(n) = $id - AND EXISTS { - MATCH (e)-[]-(ms:ExtractedEntity) - } -RETURN DISTINCT - e.name AS name, - e.importance_score AS importance_score; - -""" diff --git a/api/app/services/memory_entity_relationship_service.py b/api/app/services/memory_entity_relationship_service.py index cdaa9ef7..728a891d 100644 --- a/api/app/services/memory_entity_relationship_service.py +++ b/api/app/services/memory_entity_relationship_service.py @@ -6,9 +6,7 @@ Memory_Timeline_Statement, Memory_Space_Emotion_Statement, Memory_Space_Emotion_MemorySummary, Memory_Space_Emotion_ExtractedEntity, -Memory_Space_Interaction_Statement, -Memory_Space_Interaction_ExtractedEntity, -Memory_Space_Interaction_Summary +Memory_Space_Associative,Memory_Space_User,Memory_Space_Entity ) from app.repositories.neo4j.neo4j_connector import Neo4jConnector from typing import Dict, List, Any, Optional @@ -578,6 +576,7 @@ class MemoryInteraction: # 如果解析失败，返回原始字符串 return iso_string + async def get_interaction_frequency(self) -> Dict[str, Any]: """ 获取交互频率数据 @@ -588,26 +587,36 @@ class MemoryInteraction: try: logger.info(f"获取交互数据 - ID: {self.id}, Table: {self.table}") - if self.table == 'Statement': - results = await self.connector.execute_query(Memory_Space_Interaction_Statement, id=self.id) - elif self.table == 'ExtractedEntity': - results = await self.connector.execute_query(Memory_Space_Interaction_ExtractedEntity, id=self.id) - else: - # MemorySummary/Chunk类型查询 - results = await self.connector.execute_query(Memory_Space_Interaction_Summary, id=self.id) + ori_data= await self.connector.execute_query(Memory_Space_Entity, id=self.id) + if ori_data!=[]: + # name = ori_data[0]['name'] + group_id = ori_data[0]['group_id'] + Space_User = await self.connector.execute_query(Memory_Space_User, group_id=group_id) + if not Space_User: + return "不存在用户" + user_id=Space_User[0]['id'] - # 处理查询结果 - interaction_data = self._process_interaction_results(results) - - # 转换Neo4j类型 - final_data = self._convert_neo4j_types(interaction_data) - - logger.info(f"成功获取 {len(final_data)} 条交互数据") - + results = await self.connector.execute_query(Memory_Space_Associative, id=self.id,user_id=user_id) + + + + # 处理查询结果 + interaction_data = self._process_interaction_results(results) + + # 转换Neo4j类型 + final_data = self._convert_neo4j_types(interaction_data) + + logger.info(f"成功获取 {len(final_data)} 条交互数据") + + return { + 'success': True, + 'data': final_data, + 'total': len(final_data) + } return { - 'success': True, - 'data': final_data, - 'total': len(final_data) + 'success': False, + 'data': [], + 'total': 0 } except Exception as e: @@ -621,36 +630,57 @@ class MemoryInteraction: def _process_interaction_results(self, results: List[Dict[str, Any]]) -> List[Dict[str, Any]]: """ - 处理交互查询结果 + 处理交互查询结果，按季度统计交互频率 Args: results: Neo4j查询结果 Returns: - 处理后的交互数据列表 + 按季度统计的交互数据列表，格式: [{"created_at": "2026Q1", "count": 3}] """ - interaction_data = [] + from collections import defaultdict + from datetime import datetime - # 检查results是否为空或不是列表 - if not results or not isinstance(results, list): - logger.warning(f"交互查询结果为空或格式不正确: {type(results)}") - return interaction_data + # 用于按季度分组计数 + quarterly_counts = defaultdict(int) for record in results: - # 检查record是否为字典类型 - if not isinstance(record, dict): - logger.warning(f"跳过非字典类型的记录: {type(record)} - {record}") + # 过滤掉statement为None的记录 + if not isinstance(record, dict) or record.get('statement') is None: continue - # 只保留交互相关的字段 - name = record.get('name') - if name is not None: - interaction_record = { - 'name': name, - 'importance_score': record.get('importance_score', 0.0), - 'interaction_count': record.get('interaction_count', 1) # 默认交互次数为1 - } - interaction_data.append(interaction_record) + created_at = record.get('created_at') + if not created_at: + continue + + try: + # 处理不同类型的时间格式 + if isinstance(created_at, str): + # 解析ISO格式时间字符串 + dt = datetime.fromisoformat(created_at.replace('Z', '+00:00')) + elif hasattr(created_at, 'year') and hasattr(created_at, 'month'): + # 处理Neo4j DateTime对象 + dt = datetime(created_at.year, created_at.month, created_at.day) + else: + continue + # 计算季度 + quarter = (dt.month - 1) // 3 + 1 + quarter_key = f"{dt.year}.Q{quarter}" + # 增加该季度的计数 + quarterly_counts[quarter_key] += 1 + + except (ValueError, AttributeError) as e: + logger.warning(f"解析时间失败: {e}, 原始值: {created_at}") + continue + + # 转换为所需格式并按时间排序 + interaction_data = [ + {"created_at": quarter, "count": count} + for quarter, count in quarterly_counts.items() + ] + + # 按季度排序（最新的在前） + interaction_data.sort(key=lambda x: x["created_at"], reverse=True) return interaction_data