From db8257b67ae526e3bf2cd42dd8f1bfc012c0411e Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Tue, 10 Mar 2026 17:06:43 +0800 Subject: [PATCH 1/9] [add] Create community nodes --- .../clustering_engine/__init__.py | 3 + .../clustering_engine/label_propagation.py | 311 ++++++++++++++++++ .../neo4j/community_repository.py | 129 ++++++++ api/app/repositories/neo4j/cypher_queries.py | 93 +++++- api/app/repositories/neo4j/graph_saver.py | 34 ++ 5 files changed, 569 insertions(+), 1 deletion(-) create mode 100644 api/app/core/memory/storage_services/clustering_engine/__init__.py create mode 100644 api/app/core/memory/storage_services/clustering_engine/label_propagation.py create mode 100644 api/app/repositories/neo4j/community_repository.py diff --git a/api/app/core/memory/storage_services/clustering_engine/__init__.py b/api/app/core/memory/storage_services/clustering_engine/__init__.py new file mode 100644 index 00000000..992d8bff --- /dev/null +++ b/api/app/core/memory/storage_services/clustering_engine/__init__.py @@ -0,0 +1,3 @@ +from app.core.memory.storage_services.clustering_engine.label_propagation import LabelPropagationEngine + +__all__ = ["LabelPropagationEngine"] diff --git a/api/app/core/memory/storage_services/clustering_engine/label_propagation.py b/api/app/core/memory/storage_services/clustering_engine/label_propagation.py new file mode 100644 index 00000000..80e238fd --- /dev/null +++ b/api/app/core/memory/storage_services/clustering_engine/label_propagation.py @@ -0,0 +1,311 @@ +"""标签传播聚类引擎 + +基于 ZEP 论文的动态标签传播算法，对 Neo4j 中的 ExtractedEntity 节点进行社区聚类。 + +支持两种模式： +- 全量初始化（full_clustering）：首次运行，对所有实体做完整 LPA 迭代 +- 增量更新（incremental_update）：新实体到达时，只处理新实体及其邻居 +""" + +import logging +import uuid +from math import sqrt +from typing import Dict, List, Optional + +from app.repositories.neo4j.community_repository import CommunityRepository +from app.repositories.neo4j.neo4j_connector import Neo4jConnector + +logger = logging.getLogger(__name__) + +# 全量迭代最大轮数，防止不收敛 +MAX_ITERATIONS = 10 + + +def _cosine_similarity(v1: Optional[List[float]], v2: Optional[List[float]]) -> float: + """计算两个向量的余弦相似度，任一为空则返回 0。""" + if not v1 or not v2 or len(v1) != len(v2): + return 0.0 + dot = sum(a * b for a, b in zip(v1, v2)) + norm1 = sqrt(sum(a * a for a in v1)) + norm2 = sqrt(sum(b * b for b in v2)) + if norm1 == 0 or norm2 == 0: + return 0.0 + return dot / (norm1 * norm2) + + +def _weighted_vote( + neighbors: List[Dict], + self_embedding: Optional[List[float]], +) -> Optional[str]: + """ + 加权多数投票，选出得票最高的社区。 + + 权重 = 语义相似度（name_embedding 余弦）* activation_value 加成 + 没有 community_id 的邻居不参与投票。 + """ + votes: Dict[str, float] = {} + for nb in neighbors: + cid = nb.get("community_id") + if not cid: + continue + sem = _cosine_similarity(self_embedding, nb.get("name_embedding")) + act = nb.get("activation_value") or 0.5 + # 语义相似度权重 0.6，激活值权重 0.4 + weight = 0.6 * sem + 0.4 * act + votes[cid] = votes.get(cid, 0.0) + weight + + if not votes: + return None + return max(votes, key=votes.__getitem__) + + +class LabelPropagationEngine: + """标签传播聚类引擎""" + + def __init__(self, connector: Neo4jConnector): + self.connector = connector + self.repo = CommunityRepository(connector) + + # ────────────────────────────────────────────────────────────────────────── + # 公开接口 + # ────────────────────────────────────────────────────────────────────────── + + async def run( + self, + end_user_id: str, + new_entity_ids: Optional[List[str]] = None, + ) -> None: + """ + 统一入口：自动判断全量还是增量。 + + - 若该用户尚无 Community 节点 → 全量初始化 + - 否则 → 增量更新（仅处理 new_entity_ids） + """ + has_communities = await self.repo.has_communities(end_user_id) + if not has_communities: + logger.info(f"[Clustering] 用户 {end_user_id} 首次聚类，执行全量初始化") + await self.full_clustering(end_user_id) + else: + if new_entity_ids: + logger.info( + f"[Clustering] 增量更新，新实体数: {len(new_entity_ids)}" + ) + await self.incremental_update(new_entity_ids, end_user_id) + + async def full_clustering(self, end_user_id: str) -> None: + """ + 全量标签传播初始化。 + + 1. 拉取所有实体，初始化每个实体为独立社区 + 2. 迭代：每轮对所有实体做邻居投票，更新社区标签 + 3. 直到标签不再变化或达到 MAX_ITERATIONS + 4. 将最终标签写入 Neo4j + """ + entities = await self.repo.get_all_entities(end_user_id) + if not entities: + logger.info(f"[Clustering] 用户 {end_user_id} 无实体，跳过全量聚类") + return + + # 初始化：每个实体持有自己 id 作为社区标签 + labels: Dict[str, str] = {e["id"]: e["id"] for e in entities} + embeddings: Dict[str, Optional[List[float]]] = { + e["id"]: e.get("name_embedding") for e in entities + } + + for iteration in range(MAX_ITERATIONS): + changed = 0 + # 随机顺序（Python dict 在 3.7+ 保持插入顺序，这里直接遍历） + for entity in entities: + eid = entity["id"] + neighbors = await self.repo.get_entity_neighbors(eid, end_user_id) + + # 将邻居的当前内存标签注入（覆盖 Neo4j 中的旧值） + enriched = [] + for nb in neighbors: + nb_copy = dict(nb) + nb_copy["community_id"] = labels.get(nb["id"], nb.get("community_id")) + enriched.append(nb_copy) + + new_label = _weighted_vote(enriched, embeddings.get(eid)) + if new_label and new_label != labels[eid]: + labels[eid] = new_label + changed += 1 + + logger.info( + f"[Clustering] 全量迭代 {iteration + 1}/{MAX_ITERATIONS}，" + f"标签变化数: {changed}" + ) + if changed == 0: + logger.info("[Clustering] 标签已收敛，提前结束迭代") + break + + # 将最终标签写入 Neo4j + await self._flush_labels(labels, end_user_id) + logger.info( + f"[Clustering] 全量聚类完成，共 {len(set(labels.values()))} 个社区，" + f"{len(labels)} 个实体" + ) + + async def incremental_update( + self, new_entity_ids: List[str], end_user_id: str + ) -> None: + """ + 增量更新：只处理新实体及其邻居，不重跑全图。 + + 1. 对每个新实体查询邻居 + 2. 加权多数投票决定社区归属 + 3. 若邻居无社区 → 创建新社区 + 4. 若邻居分属多个社区 → 评估是否合并 + """ + for entity_id in new_entity_ids: + await self._process_single_entity(entity_id, end_user_id) + + # ────────────────────────────────────────────────────────────────────────── + # 内部方法 + # ────────────────────────────────────────────────────────────────────────── + + async def _process_single_entity( + self, entity_id: str, end_user_id: str + ) -> None: + """处理单个新实体的社区分配。""" + neighbors = await self.repo.get_entity_neighbors(entity_id, end_user_id) + + # 查询自身 embedding（从邻居查询结果中无法获取，需单独查） + self_embedding = await self._get_entity_embedding(entity_id, end_user_id) + + if not neighbors: + # 孤立实体：创建单成员社区 + new_cid = self._new_community_id() + await self.repo.upsert_community(new_cid, end_user_id, member_count=1) + await self.repo.assign_entity_to_community(entity_id, new_cid, end_user_id) + logger.debug(f"[Clustering] 孤立实体 {entity_id} → 新社区 {new_cid}") + return + + # 统计邻居社区分布 + community_ids_in_neighbors = set( + nb["community_id"] for nb in neighbors if nb.get("community_id") + ) + + target_cid = _weighted_vote(neighbors, self_embedding) + + if target_cid is None: + # 邻居都没有社区，连同新实体一起创建新社区 + new_cid = self._new_community_id() + await self.repo.upsert_community(new_cid, end_user_id) + await self.repo.assign_entity_to_community(entity_id, new_cid, end_user_id) + for nb in neighbors: + await self.repo.assign_entity_to_community( + nb["id"], new_cid, end_user_id + ) + await self.repo.refresh_member_count(new_cid, end_user_id) + logger.debug( + f"[Clustering] 新实体 {entity_id} 与 {len(neighbors)} 个无社区邻居 → 新社区 {new_cid}" + ) + else: + # 加入得票最多的社区 + await self.repo.assign_entity_to_community(entity_id, target_cid, end_user_id) + await self.repo.refresh_member_count(target_cid, end_user_id) + logger.debug(f"[Clustering] 新实体 {entity_id} → 社区 {target_cid}") + + # 若邻居分属多个社区，评估合并 + if len(community_ids_in_neighbors) > 1: + await self._evaluate_merge( + list(community_ids_in_neighbors), end_user_id + ) + + async def _evaluate_merge( + self, community_ids: List[str], end_user_id: str + ) -> None: + """ + 评估多个社区是否应合并。 + + 策略：计算各社区成员 embedding 的平均向量，若两两余弦相似度 > 0.75 则合并。 + 合并时保留成员数最多的社区，其余成员迁移过来。 + """ + MERGE_THRESHOLD = 0.75 + + community_embeddings: Dict[str, Optional[List[float]]] = {} + community_sizes: Dict[str, int] = {} + + for cid in community_ids: + members = await self.repo.get_community_members(cid, end_user_id) + community_sizes[cid] = len(members) + # 计算社区成员 embedding 的平均向量 + valid_embeddings = [ + m["name_embedding"] + for m in members + if m.get("name_embedding") + ] + if valid_embeddings: + dim = len(valid_embeddings[0]) + avg = [ + sum(e[i] for e in valid_embeddings) / len(valid_embeddings) + for i in range(dim) + ] + community_embeddings[cid] = avg + else: + community_embeddings[cid] = None + + # 找出应合并的社区对 + to_merge: List[tuple] = [] + cids = list(community_ids) + for i in range(len(cids)): + for j in range(i + 1, len(cids)): + sim = _cosine_similarity( + community_embeddings[cids[i]], + community_embeddings[cids[j]], + ) + if sim > MERGE_THRESHOLD: + to_merge.append((cids[i], cids[j])) + + for c1, c2 in to_merge: + keep = c1 if community_sizes.get(c1, 0) >= community_sizes.get(c2, 0) else c2 + dissolve = c2 if keep == c1 else c1 + members = await self.repo.get_community_members(dissolve, end_user_id) + for m in members: + await self.repo.assign_entity_to_community( + m["id"], keep, end_user_id + ) + await self.repo.refresh_member_count(keep, end_user_id) + logger.info( + f"[Clustering] 社区合并: {dissolve} → {keep}，" + f"迁移 {len(members)} 个成员" + ) + + async def _flush_labels( + self, labels: Dict[str, str], end_user_id: str + ) -> None: + """将内存中的标签批量写入 Neo4j。""" + # 先创建所有唯一社区节点 + unique_communities = set(labels.values()) + for cid in unique_communities: + await self.repo.upsert_community(cid, end_user_id) + + # 再批量分配实体 + for entity_id, community_id in labels.items(): + await self.repo.assign_entity_to_community( + entity_id, community_id, end_user_id + ) + + # 刷新成员数 + for cid in unique_communities: + await self.repo.refresh_member_count(cid, end_user_id) + + async def _get_entity_embedding( + self, entity_id: str, end_user_id: str + ) -> Optional[List[float]]: + """查询单个实体的 name_embedding。""" + try: + result = await self.connector.execute_query( + "MATCH (e:ExtractedEntity {id: $eid, end_user_id: $uid}) " + "RETURN e.name_embedding AS name_embedding", + eid=entity_id, + uid=end_user_id, + ) + return result[0]["name_embedding"] if result else None + except Exception: + return None + + @staticmethod + def _new_community_id() -> str: + return str(uuid.uuid4()) diff --git a/api/app/repositories/neo4j/community_repository.py b/api/app/repositories/neo4j/community_repository.py new file mode 100644 index 00000000..16e30a10 --- /dev/null +++ b/api/app/repositories/neo4j/community_repository.py @@ -0,0 +1,129 @@ +"""Community 节点仓库 + +管理 Neo4j 中 Community 节点及 BELONGS_TO_COMMUNITY 边的 CRUD 操作。 +""" + +import logging +from typing import Dict, List, Optional + +from app.repositories.neo4j.neo4j_connector import Neo4jConnector +from app.repositories.neo4j.cypher_queries import ( + COMMUNITY_NODE_UPSERT, + ENTITY_JOIN_COMMUNITY, + ENTITY_LEAVE_ALL_COMMUNITIES, + GET_ENTITY_NEIGHBORS, + GET_ALL_ENTITIES_FOR_USER, + GET_COMMUNITY_MEMBERS, + CHECK_USER_HAS_COMMUNITIES, + UPDATE_COMMUNITY_MEMBER_COUNT, +) + +logger = logging.getLogger(__name__) + + +class CommunityRepository: + def __init__(self, connector: Neo4jConnector): + self.connector = connector + + async def upsert_community( + self, community_id: str, end_user_id: str, member_count: int = 0 + ) -> Optional[str]: + """创建或更新 Community 节点，返回 community_id。""" + try: + result = await self.connector.execute_query( + COMMUNITY_NODE_UPSERT, + community_id=community_id, + end_user_id=end_user_id, + member_count=member_count, + ) + return result[0]["community_id"] if result else None + except Exception as e: + logger.error(f"upsert_community failed: {e}") + return None + + async def assign_entity_to_community( + self, entity_id: str, community_id: str, end_user_id: str + ) -> bool: + """将实体关联到社区（先解除旧关联，再建立新关联）。""" + try: + await self.connector.execute_query( + ENTITY_LEAVE_ALL_COMMUNITIES, + entity_id=entity_id, + end_user_id=end_user_id, + ) + result = await self.connector.execute_query( + ENTITY_JOIN_COMMUNITY, + entity_id=entity_id, + community_id=community_id, + end_user_id=end_user_id, + ) + return bool(result) + except Exception as e: + logger.error(f"assign_entity_to_community failed: {e}") + return False + + async def get_entity_neighbors( + self, entity_id: str, end_user_id: str + ) -> List[Dict]: + """查询实体的直接邻居及其社区归属。""" + try: + return await self.connector.execute_query( + GET_ENTITY_NEIGHBORS, + entity_id=entity_id, + end_user_id=end_user_id, + ) + except Exception as e: + logger.error(f"get_entity_neighbors failed: {e}") + return [] + + async def get_all_entities(self, end_user_id: str) -> List[Dict]: + """拉取某用户下所有实体及其当前社区归属。""" + try: + return await self.connector.execute_query( + GET_ALL_ENTITIES_FOR_USER, + end_user_id=end_user_id, + ) + except Exception as e: + logger.error(f"get_all_entities failed: {e}") + return [] + + async def get_community_members( + self, community_id: str, end_user_id: str + ) -> List[Dict]: + """查询社区成员列表。""" + try: + return await self.connector.execute_query( + GET_COMMUNITY_MEMBERS, + community_id=community_id, + end_user_id=end_user_id, + ) + except Exception as e: + logger.error(f"get_community_members failed: {e}") + return [] + + async def has_communities(self, end_user_id: str) -> bool: + """检查该用户是否已有 Community 节点（用于判断全量 vs 增量）。""" + try: + result = await self.connector.execute_query( + CHECK_USER_HAS_COMMUNITIES, + end_user_id=end_user_id, + ) + return result[0]["community_count"] > 0 if result else False + except Exception as e: + logger.error(f"has_communities failed: {e}") + return False + + async def refresh_member_count( + self, community_id: str, end_user_id: str + ) -> int: + """重新统计并更新社区成员数，返回最新数量。""" + try: + result = await self.connector.execute_query( + UPDATE_COMMUNITY_MEMBER_COUNT, + community_id=community_id, + end_user_id=end_user_id, + ) + return result[0]["member_count"] if result else 0 + except Exception as e: + logger.error(f"refresh_member_count failed: {e}") + return 0 diff --git a/api/app/repositories/neo4j/cypher_queries.py b/api/app/repositories/neo4j/cypher_queries.py index 651c513f..947097a2 100644 --- a/api/app/repositories/neo4j/cypher_queries.py +++ b/api/app/repositories/neo4j/cypher_queries.py @@ -1058,4 +1058,95 @@ Graph_Node_query = """ 3 AS priority LIMIT $limit - """ \ No newline at end of file + """ + + +# ============================================================ +# Community 节点 & BELONGS_TO_COMMUNITY 边 +# ============================================================ + +COMMUNITY_NODE_SAVE = """ +MERGE (c:Community {community_id: $community_id}) +SET c.end_user_id = $end_user_id, + c.formed_at = $formed_at, + c.updated_at = datetime(), + c.status = $status, + c.member_count = $member_count +RETURN c.community_id AS community_id +""" + +COMMUNITY_ADD_MEMBER = """ +MATCH (e:ExtractedEntity {id: $entity_id, end_user_id: $end_user_id}) +MATCH (c:Community {community_id: $community_id, end_user_id: $end_user_id}) +MERGE (e)-[:BELONGS_TO_COMMUNITY]->(c) +SET c.updated_at = datetime(), + c.member_count = $member_count +""" + + + +# ─── Community 聚类相关 Cypher 模板 ─────────────────────────────────────────── + +COMMUNITY_NODE_UPSERT = """ +MERGE (c:Community {community_id: $community_id}) +SET c.end_user_id = $end_user_id, + c.member_count = $member_count, + c.updated_at = datetime() +RETURN c.community_id AS community_id +""" + +ENTITY_JOIN_COMMUNITY = """ +MATCH (e:ExtractedEntity {id: $entity_id, end_user_id: $end_user_id}) +MATCH (c:Community {community_id: $community_id, end_user_id: $end_user_id}) +MERGE (e)-[:BELONGS_TO_COMMUNITY]->(c) +SET c.updated_at = datetime() +RETURN e.id AS entity_id, c.community_id AS community_id +""" + +ENTITY_LEAVE_ALL_COMMUNITIES = """ +MATCH (e:ExtractedEntity {id: $entity_id, end_user_id: $end_user_id}) +MATCH (e)-[r:BELONGS_TO_COMMUNITY]->(:Community) +DELETE r +""" + +GET_ENTITY_NEIGHBORS = """ +MATCH (e:ExtractedEntity {id: $entity_id, end_user_id: $end_user_id}) +OPTIONAL MATCH (e)-[:EXTRACTED_RELATIONSHIP]-(nb:ExtractedEntity {end_user_id: $end_user_id}) +OPTIONAL MATCH (nb)-[:BELONGS_TO_COMMUNITY]->(c:Community) +RETURN DISTINCT + nb.id AS id, + nb.name AS name, + nb.name_embedding AS name_embedding, + nb.activation_value AS activation_value, + CASE WHEN c IS NOT NULL THEN c.community_id ELSE null END AS community_id +""" + +GET_ALL_ENTITIES_FOR_USER = """ +MATCH (e:ExtractedEntity {end_user_id: $end_user_id}) +OPTIONAL MATCH (e)-[:BELONGS_TO_COMMUNITY]->(c:Community) +RETURN e.id AS id, + e.name AS name, + e.name_embedding AS name_embedding, + e.activation_value AS activation_value, + CASE WHEN c IS NOT NULL THEN c.community_id ELSE null END AS community_id +""" + +GET_COMMUNITY_MEMBERS = """ +MATCH (e:ExtractedEntity {end_user_id: $end_user_id})-[:BELONGS_TO_COMMUNITY]->(c:Community {community_id: $community_id}) +RETURN e.id AS id, e.name AS name, e.entity_type AS entity_type, + e.importance_score AS importance_score, e.activation_value AS activation_value, + e.name_embedding AS name_embedding +ORDER BY coalesce(e.activation_value, 0) DESC +""" + +CHECK_USER_HAS_COMMUNITIES = """ +MATCH (c:Community {end_user_id: $end_user_id}) +RETURN count(c) AS community_count +""" + +UPDATE_COMMUNITY_MEMBER_COUNT = """ +MATCH (e:ExtractedEntity {end_user_id: $end_user_id})-[:BELONGS_TO_COMMUNITY]->(c:Community {community_id: $community_id}) +WITH c, count(e) AS cnt +SET c.member_count = cnt +RETURN c.community_id AS community_id, cnt AS member_count +""" diff --git a/api/app/repositories/neo4j/graph_saver.py b/api/app/repositories/neo4j/graph_saver.py index 526d16ec..a94bc23b 100644 --- a/api/app/repositories/neo4j/graph_saver.py +++ b/api/app/repositories/neo4j/graph_saver.py @@ -1,3 +1,4 @@ +import asyncio from typing import List # 使用新的仓储层 @@ -288,6 +289,14 @@ async def save_dialog_and_statements_to_neo4j( } logger.info("Transaction completed. Summary: %s", summary) logger.debug("Full transaction results: %r", results) + + # 写入成功后，触发聚类 + if entity_nodes: + end_user_id = entity_nodes[0].end_user_id + new_entity_ids = [e.id for e in entity_nodes] + logger.info(f"[Clustering] 准备触发聚类，实体数: {len(new_entity_ids)}, end_user_id: {end_user_id}") + await _trigger_clustering(new_entity_ids, end_user_id) + return True except Exception as e: @@ -295,3 +304,28 @@ async def save_dialog_and_statements_to_neo4j( print(f"Neo4j integration error: {e}") print("Continuing without database storage...") return False + + +async def _trigger_clustering( + new_entity_ids: List[str], + end_user_id: str, +) -> None: + """ + 聚类触发函数，自动判断全量初始化还是增量更新。 + """ + connector = None + try: + from app.core.memory.storage_services.clustering_engine import LabelPropagationEngine + logger.info(f"[Clustering] 开始聚类，end_user_id={end_user_id}, 实体数={len(new_entity_ids)}") + connector = Neo4jConnector() + engine = LabelPropagationEngine(connector) + await engine.run(end_user_id=end_user_id, new_entity_ids=new_entity_ids) + logger.info(f"[Clustering] 聚类完成，end_user_id={end_user_id}") + except Exception as e: + logger.error(f"[Clustering] 聚类触发失败: {e}", exc_info=True) + finally: + if connector: + try: + await connector.close() + except Exception: + pass From 744ba31ba6072b1e3f9f9af26a87949d6a1d6313 Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Wed, 11 Mar 2026 18:04:04 +0800 Subject: [PATCH 2/9] [changes] Initial stage of community integration --- .../clustering_engine/label_propagation.py | 94 ++++++++++++++----- .../neo4j/community_repository.py | 20 ++++ api/app/repositories/neo4j/cypher_queries.py | 48 +++++----- 3 files changed, 115 insertions(+), 47 deletions(-) diff --git a/api/app/core/memory/storage_services/clustering_engine/label_propagation.py b/api/app/core/memory/storage_services/clustering_engine/label_propagation.py index 80e238fd..cb6e5804 100644 --- a/api/app/core/memory/storage_services/clustering_engine/label_propagation.py +++ b/api/app/core/memory/storage_services/clustering_engine/label_propagation.py @@ -141,8 +141,18 @@ class LabelPropagationEngine: # 将最终标签写入 Neo4j await self._flush_labels(labels, end_user_id) + pre_merge_count = len(set(labels.values())) logger.info( - f"[Clustering] 全量聚类完成，共 {len(set(labels.values()))} 个社区，" + f"[Clustering] 全量迭代完成，共 {pre_merge_count} 个社区，" + f"{len(labels)} 个实体，开始后处理合并" + ) + + # 全量初始化后做一轮社区合并（基于 name_embedding 余弦相似度） + all_community_ids = list(set(labels.values())) + await self._evaluate_merge(all_community_ids, end_user_id) + + logger.info( + f"[Clustering] 全量聚类完成，合并前 {pre_merge_count} 个社区，" f"{len(labels)} 个实体" ) @@ -221,30 +231,50 @@ class LabelPropagationEngine: 策略：计算各社区成员 embedding 的平均向量，若两两余弦相似度 > 0.75 则合并。 合并时保留成员数最多的社区，其余成员迁移过来。 + + 全量场景（社区数 > 20）使用批量查询，避免 N 次数据库往返。 """ MERGE_THRESHOLD = 0.75 + BATCH_THRESHOLD = 20 # 超过此数量走批量查询 community_embeddings: Dict[str, Optional[List[float]]] = {} community_sizes: Dict[str, int] = {} - for cid in community_ids: - members = await self.repo.get_community_members(cid, end_user_id) - community_sizes[cid] = len(members) - # 计算社区成员 embedding 的平均向量 - valid_embeddings = [ - m["name_embedding"] - for m in members - if m.get("name_embedding") - ] - if valid_embeddings: - dim = len(valid_embeddings[0]) - avg = [ - sum(e[i] for e in valid_embeddings) / len(valid_embeddings) - for i in range(dim) + if len(community_ids) > BATCH_THRESHOLD: + # 批量查询：一次拉取所有社区成员 + all_members = await self.repo.get_all_community_members_batch( + community_ids, end_user_id + ) + for cid in community_ids: + members = all_members.get(cid, []) + community_sizes[cid] = len(members) + valid_embeddings = [ + m["name_embedding"] for m in members if m.get("name_embedding") ] - community_embeddings[cid] = avg - else: - community_embeddings[cid] = None + if valid_embeddings: + dim = len(valid_embeddings[0]) + community_embeddings[cid] = [ + sum(e[i] for e in valid_embeddings) / len(valid_embeddings) + for i in range(dim) + ] + else: + community_embeddings[cid] = None + else: + # 增量场景：逐个查询 + for cid in community_ids: + members = await self.repo.get_community_members(cid, end_user_id) + community_sizes[cid] = len(members) + valid_embeddings = [ + m["name_embedding"] for m in members if m.get("name_embedding") + ] + if valid_embeddings: + dim = len(valid_embeddings[0]) + community_embeddings[cid] = [ + sum(e[i] for e in valid_embeddings) / len(valid_embeddings) + for i in range(dim) + ] + else: + community_embeddings[cid] = None # 找出应合并的社区对 to_merge: List[tuple] = [] @@ -258,14 +288,32 @@ class LabelPropagationEngine: if sim > MERGE_THRESHOLD: to_merge.append((cids[i], cids[j])) + logger.info(f"[Clustering] 发现 {len(to_merge)} 对可合并社区") + + # 执行合并：用 union-find 思路避免重复迁移已被合并的社区 + # 维护一个 canonical 映射，确保链式合并正确收敛 + canonical: Dict[str, str] = {cid: cid for cid in cids} + + def find(x: str) -> str: + while canonical[x] != x: + canonical[x] = canonical[canonical[x]] + x = canonical[x] + return x + for c1, c2 in to_merge: - keep = c1 if community_sizes.get(c1, 0) >= community_sizes.get(c2, 0) else c2 - dissolve = c2 if keep == c1 else c1 + root1, root2 = find(c1), find(c2) + if root1 == root2: + continue # 已经在同一社区，跳过 + keep = root1 if community_sizes.get(root1, 0) >= community_sizes.get(root2, 0) else root2 + dissolve = root2 if keep == root1 else root1 + canonical[dissolve] = keep + members = await self.repo.get_community_members(dissolve, end_user_id) for m in members: - await self.repo.assign_entity_to_community( - m["id"], keep, end_user_id - ) + await self.repo.assign_entity_to_community(m["id"], keep, end_user_id) + # 更新 sizes 以便后续合并决策准确 + community_sizes[keep] = community_sizes.get(keep, 0) + len(members) + community_sizes[dissolve] = 0 await self.repo.refresh_member_count(keep, end_user_id) logger.info( f"[Clustering] 社区合并: {dissolve} → {keep}，" diff --git a/api/app/repositories/neo4j/community_repository.py b/api/app/repositories/neo4j/community_repository.py index 16e30a10..2a1f4f2b 100644 --- a/api/app/repositories/neo4j/community_repository.py +++ b/api/app/repositories/neo4j/community_repository.py @@ -14,6 +14,7 @@ from app.repositories.neo4j.cypher_queries import ( GET_ENTITY_NEIGHBORS, GET_ALL_ENTITIES_FOR_USER, GET_COMMUNITY_MEMBERS, + GET_ALL_COMMUNITY_MEMBERS_BATCH, CHECK_USER_HAS_COMMUNITIES, UPDATE_COMMUNITY_MEMBER_COUNT, ) @@ -101,6 +102,25 @@ class CommunityRepository: logger.error(f"get_community_members failed: {e}") return [] + async def get_all_community_members_batch( + self, community_ids: List[str], end_user_id: str + ) -> Dict[str, List[Dict]]: + """批量查询多个社区的成员，返回 {community_id: [members]} 字典。""" + try: + rows = await self.connector.execute_query( + GET_ALL_COMMUNITY_MEMBERS_BATCH, + community_ids=community_ids, + end_user_id=end_user_id, + ) + result: Dict[str, List[Dict]] = {} + for row in rows: + cid = row["community_id"] + result.setdefault(cid, []).append(row) + return result + except Exception as e: + logger.error(f"get_all_community_members_batch failed: {e}") + return {} + async def has_communities(self, end_user_id: str) -> bool: """检查该用户是否已有 Community 节点（用于判断全量 vs 增量）。""" try: diff --git a/api/app/repositories/neo4j/cypher_queries.py b/api/app/repositories/neo4j/cypher_queries.py index 947097a2..84889d65 100644 --- a/api/app/repositories/neo4j/cypher_queries.py +++ b/api/app/repositories/neo4j/cypher_queries.py @@ -1065,26 +1065,6 @@ Graph_Node_query = """ # Community 节点 & BELONGS_TO_COMMUNITY 边 # ============================================================ -COMMUNITY_NODE_SAVE = """ -MERGE (c:Community {community_id: $community_id}) -SET c.end_user_id = $end_user_id, - c.formed_at = $formed_at, - c.updated_at = datetime(), - c.status = $status, - c.member_count = $member_count -RETURN c.community_id AS community_id -""" - -COMMUNITY_ADD_MEMBER = """ -MATCH (e:ExtractedEntity {id: $entity_id, end_user_id: $end_user_id}) -MATCH (c:Community {community_id: $community_id, end_user_id: $end_user_id}) -MERGE (e)-[:BELONGS_TO_COMMUNITY]->(c) -SET c.updated_at = datetime(), - c.member_count = $member_count -""" - - - # ─── Community 聚类相关 Cypher 模板 ─────────────────────────────────────────── COMMUNITY_NODE_UPSERT = """ @@ -1111,12 +1091,23 @@ DELETE r GET_ENTITY_NEIGHBORS = """ MATCH (e:ExtractedEntity {id: $entity_id, end_user_id: $end_user_id}) -OPTIONAL MATCH (e)-[:EXTRACTED_RELATIONSHIP]-(nb:ExtractedEntity {end_user_id: $end_user_id}) + +// 来源一：直接关系邻居（EXTRACTED_RELATIONSHIP 边） +OPTIONAL MATCH (e)-[:EXTRACTED_RELATIONSHIP]-(nb1:ExtractedEntity {end_user_id: $end_user_id}) + +// 来源二：同 Statement 共现邻居（REFERENCES_ENTITY 边） +OPTIONAL MATCH (s:Statement)-[:REFERENCES_ENTITY]->(e) +OPTIONAL MATCH (s)-[:REFERENCES_ENTITY]->(nb2:ExtractedEntity {end_user_id: $end_user_id}) +WHERE nb2.id <> e.id + +WITH collect(DISTINCT nb1) + collect(DISTINCT nb2) AS all_neighbors +UNWIND all_neighbors AS nb +WITH nb WHERE nb IS NOT NULL OPTIONAL MATCH (nb)-[:BELONGS_TO_COMMUNITY]->(c:Community) RETURN DISTINCT - nb.id AS id, - nb.name AS name, - nb.name_embedding AS name_embedding, + nb.id AS id, + nb.name AS name, + nb.name_embedding AS name_embedding, nb.activation_value AS activation_value, CASE WHEN c IS NOT NULL THEN c.community_id ELSE null END AS community_id """ @@ -1139,6 +1130,15 @@ RETURN e.id AS id, e.name AS name, e.entity_type AS entity_type, ORDER BY coalesce(e.activation_value, 0) DESC """ +GET_ALL_COMMUNITY_MEMBERS_BATCH = """ +MATCH (e:ExtractedEntity {end_user_id: $end_user_id})-[:BELONGS_TO_COMMUNITY]->(c:Community) +WHERE c.community_id IN $community_ids +RETURN c.community_id AS community_id, + e.id AS id, + e.name_embedding AS name_embedding, + e.activation_value AS activation_value +""" + CHECK_USER_HAS_COMMUNITIES = """ MATCH (c:Community {end_user_id: $end_user_id}) RETURN count(c) AS community_count From 6d8b1aede481b53b4f4fbe7b1c686dad532f59df Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Thu, 12 Mar 2026 20:27:50 +0800 Subject: [PATCH 3/9] [add] Create the attribute values of the community nodes --- .../core/memory/agent/utils/write_tools.py | 4 +- .../clustering_engine/label_propagation.py | 83 ++++++++++++++++++- .../neo4j/community_repository.py | 24 ++++++ api/app/repositories/neo4j/cypher_queries.py | 9 ++ api/app/repositories/neo4j/graph_saver.py | 20 +++-- 5 files changed, 132 insertions(+), 8 deletions(-) diff --git a/api/app/core/memory/agent/utils/write_tools.py b/api/app/core/memory/agent/utils/write_tools.py index 22030278..b3707083 100644 --- a/api/app/core/memory/agent/utils/write_tools.py +++ b/api/app/core/memory/agent/utils/write_tools.py @@ -165,7 +165,9 @@ async def write( statement_chunk_edges=all_statement_chunk_edges, statement_entity_edges=all_statement_entity_edges, entity_edges=all_entity_entity_edges, - connector=neo4j_connector + connector=neo4j_connector, + config_id=config_id, + llm_model_id=str(memory_config.llm_model_id) if memory_config.llm_model_id else None, ) if success: logger.info("Successfully saved all data to Neo4j") diff --git a/api/app/core/memory/storage_services/clustering_engine/label_propagation.py b/api/app/core/memory/storage_services/clustering_engine/label_propagation.py index cb6e5804..251d4fea 100644 --- a/api/app/core/memory/storage_services/clustering_engine/label_propagation.py +++ b/api/app/core/memory/storage_services/clustering_engine/label_propagation.py @@ -19,6 +19,8 @@ logger = logging.getLogger(__name__) # 全量迭代最大轮数，防止不收敛 MAX_ITERATIONS = 10 +# 社区摘要核心实体数量 +CORE_ENTITY_LIMIT = 5 def _cosine_similarity(v1: Optional[List[float]], v2: Optional[List[float]]) -> float: @@ -62,9 +64,16 @@ def _weighted_vote( class LabelPropagationEngine: """标签传播聚类引擎""" - def __init__(self, connector: Neo4jConnector): + def __init__( + self, + connector: Neo4jConnector, + config_id: Optional[str] = None, + llm_model_id: Optional[str] = None, + ): self.connector = connector self.repo = CommunityRepository(connector) + self.config_id = config_id + self.llm_model_id = llm_model_id # ────────────────────────────────────────────────────────────────────────── # 公开接口 @@ -155,6 +164,10 @@ class LabelPropagationEngine: f"[Clustering] 全量聚类完成，合并前 {pre_merge_count} 个社区，" f"{len(labels)} 个实体" ) + # 为所有社区生成元数据 + unique_communities = list(set(labels.values())) + for cid in unique_communities: + await self._generate_community_metadata(cid, end_user_id) async def incremental_update( self, new_entity_ids: List[str], end_user_id: str @@ -211,6 +224,7 @@ class LabelPropagationEngine: logger.debug( f"[Clustering] 新实体 {entity_id} 与 {len(neighbors)} 个无社区邻居 → 新社区 {new_cid}" ) + await self._generate_community_metadata(new_cid, end_user_id) else: # 加入得票最多的社区 await self.repo.assign_entity_to_community(entity_id, target_cid, end_user_id) @@ -222,6 +236,7 @@ class LabelPropagationEngine: await self._evaluate_merge( list(community_ids_in_neighbors), end_user_id ) + await self._generate_community_metadata(target_cid, end_user_id) async def _evaluate_merge( self, community_ids: List[str], end_user_id: str @@ -354,6 +369,72 @@ class LabelPropagationEngine: except Exception: return None + async def _generate_community_metadata( + self, community_id: str, end_user_id: str + ) -> None: + """ + 为社区生成并写入元数据：名称、摘要、核心实体。 + + - core_entities：按 activation_value 排序取 top-N 实体名称列表（无需 LLM） + - name / summary：若有 llm_model_id 则调用 LLM 生成，否则用实体名称拼接兜底 + """ + try: + members = await self.repo.get_community_members(community_id, end_user_id) + if not members: + return + + # 核心实体：按 activation_value 降序取 top-N + sorted_members = sorted( + members, + key=lambda m: m.get("activation_value") or 0, + reverse=True, + ) + core_entities = [m["name"] for m in sorted_members[:CORE_ENTITY_LIMIT] if m.get("name")] + all_names = [m["name"] for m in members if m.get("name")] + + name = "、".join(core_entities[:3]) if core_entities else community_id[:8] + summary = f"包含实体：{', '.join(all_names)}" + + # 若有 LLM 配置，调用 LLM 生成更好的名称和摘要 + if self.llm_model_id: + try: + from app.db import get_db_context + from app.core.memory.utils.llm.llm_utils import MemoryClientFactory + + entity_list_str = "、".join(all_names) + prompt = ( + f"以下是一组语义相关的实体：{entity_list_str}\n\n" + f"请为这组实体所代表的主题：\n" + f"1. 起一个简洁的中文名称（不超过10个字）\n" + f"2. 写一句话摘要（不超过50个字）\n\n" + f"严格按以下格式输出，不要有其他内容：\n" + f"名称：<名称>\n摘要：<摘要>" + ) + with get_db_context() as db: + factory = MemoryClientFactory(db) + llm_client = factory.get_llm_client(self.llm_model_id) + response = await llm_client.chat([{"role": "user", "content": prompt}]) + text = response.content if hasattr(response, "content") else str(response) + + for line in text.strip().splitlines(): + if line.startswith("名称："): + name = line[3:].strip() + elif line.startswith("摘要："): + summary = line[3:].strip() + except Exception as e: + logger.warning(f"[Clustering] LLM 生成社区元数据失败，使用兜底值: {e}") + + await self.repo.update_community_metadata( + community_id=community_id, + end_user_id=end_user_id, + name=name, + summary=summary, + core_entities=core_entities, + ) + logger.debug(f"[Clustering] 社区 {community_id} 元数据已更新: name={name}") + except Exception as e: + logger.error(f"[Clustering] _generate_community_metadata failed for {community_id}: {e}") + @staticmethod def _new_community_id() -> str: return str(uuid.uuid4()) diff --git a/api/app/repositories/neo4j/community_repository.py b/api/app/repositories/neo4j/community_repository.py index 2a1f4f2b..6c5c7618 100644 --- a/api/app/repositories/neo4j/community_repository.py +++ b/api/app/repositories/neo4j/community_repository.py @@ -17,6 +17,7 @@ from app.repositories.neo4j.cypher_queries import ( GET_ALL_COMMUNITY_MEMBERS_BATCH, CHECK_USER_HAS_COMMUNITIES, UPDATE_COMMUNITY_MEMBER_COUNT, + UPDATE_COMMUNITY_METADATA, ) logger = logging.getLogger(__name__) @@ -147,3 +148,26 @@ class CommunityRepository: except Exception as e: logger.error(f"refresh_member_count failed: {e}") return 0 + + async def update_community_metadata( + self, + community_id: str, + end_user_id: str, + name: str, + summary: str, + core_entities: List[str], + ) -> bool: + """更新社区的名称、摘要和核心实体列表。""" + try: + result = await self.connector.execute_query( + UPDATE_COMMUNITY_METADATA, + community_id=community_id, + end_user_id=end_user_id, + name=name, + summary=summary, + core_entities=core_entities, + ) + return bool(result) + except Exception as e: + logger.error(f"update_community_metadata failed: {e}") + return False diff --git a/api/app/repositories/neo4j/cypher_queries.py b/api/app/repositories/neo4j/cypher_queries.py index 84889d65..b270ed64 100644 --- a/api/app/repositories/neo4j/cypher_queries.py +++ b/api/app/repositories/neo4j/cypher_queries.py @@ -1150,3 +1150,12 @@ WITH c, count(e) AS cnt SET c.member_count = cnt RETURN c.community_id AS community_id, cnt AS member_count """ + +UPDATE_COMMUNITY_METADATA = """ +MATCH (c:Community {community_id: $community_id, end_user_id: $end_user_id}) +SET c.name = $name, + c.summary = $summary, + c.core_entities = $core_entities, + c.updated_at = datetime() +RETURN c.community_id AS community_id +""" diff --git a/api/app/repositories/neo4j/graph_saver.py b/api/app/repositories/neo4j/graph_saver.py index a94bc23b..2ef9bafc 100644 --- a/api/app/repositories/neo4j/graph_saver.py +++ b/api/app/repositories/neo4j/graph_saver.py @@ -1,5 +1,6 @@ import asyncio -from typing import List +import os +from typing import List, Optional # 使用新的仓储层 from app.repositories.neo4j.neo4j_connector import Neo4jConnector @@ -156,7 +157,9 @@ async def save_dialog_and_statements_to_neo4j( entity_edges: List[EntityEntityEdge], statement_chunk_edges: List[StatementChunkEdge], statement_entity_edges: List[StatementEntityEdge], - connector: Neo4jConnector + connector: Neo4jConnector, + config_id: Optional[str] = None, + llm_model_id: Optional[str] = None, ) -> bool: """Save dialogue nodes, chunk nodes, statement nodes, entities, and all relationships to Neo4j using graph models. @@ -290,12 +293,15 @@ async def save_dialog_and_statements_to_neo4j( logger.info("Transaction completed. Summary: %s", summary) logger.debug("Full transaction results: %r", results) - # 写入成功后，触发聚类 - if entity_nodes: + # 写入成功后，触发聚类（可通过环境变量 CLUSTERING_ENABLED=false 禁用，用于基准测试对比） + clustering_enabled = os.getenv("CLUSTERING_ENABLED", "true").lower() != "false" + if entity_nodes and clustering_enabled: end_user_id = entity_nodes[0].end_user_id new_entity_ids = [e.id for e in entity_nodes] logger.info(f"[Clustering] 准备触发聚类，实体数: {len(new_entity_ids)}, end_user_id: {end_user_id}") - await _trigger_clustering(new_entity_ids, end_user_id) + asyncio.create_task(_trigger_clustering(new_entity_ids, end_user_id, config_id=config_id, llm_model_id=llm_model_id)) + elif entity_nodes and not clustering_enabled: + logger.info("[Clustering] 聚类已禁用（CLUSTERING_ENABLED=false），跳过聚类触发") return True @@ -309,6 +315,8 @@ async def save_dialog_and_statements_to_neo4j( async def _trigger_clustering( new_entity_ids: List[str], end_user_id: str, + config_id: Optional[str] = None, + llm_model_id: Optional[str] = None, ) -> None: """ 聚类触发函数，自动判断全量初始化还是增量更新。 @@ -318,7 +326,7 @@ async def _trigger_clustering( from app.core.memory.storage_services.clustering_engine import LabelPropagationEngine logger.info(f"[Clustering] 开始聚类，end_user_id={end_user_id}, 实体数={len(new_entity_ids)}") connector = Neo4jConnector() - engine = LabelPropagationEngine(connector) + engine = LabelPropagationEngine(connector, config_id=config_id, llm_model_id=llm_model_id) await engine.run(end_user_id=end_user_id, new_entity_ids=new_entity_ids) logger.info(f"[Clustering] 聚类完成，end_user_id={end_user_id}") except Exception as e: From 967139cea4e6527f5d823b18c49702b40b187a8b Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Fri, 13 Mar 2026 12:59:36 +0800 Subject: [PATCH 4/9] [add] Community node interface development --- .../controllers/user_memory_controllers.py | 37 ++++ api/app/services/user_memory_service.py | 160 ++++++++++++++++++ 2 files changed, 197 insertions(+) diff --git a/api/app/controllers/user_memory_controllers.py b/api/app/controllers/user_memory_controllers.py index d3fe7d83..be796ff9 100644 --- a/api/app/controllers/user_memory_controllers.py +++ b/api/app/controllers/user_memory_controllers.py @@ -17,6 +17,7 @@ from app.services.user_memory_service import ( UserMemoryService, analytics_memory_types, analytics_graph_data, + analytics_community_graph_data, ) from app.services.memory_entity_relationship_service import MemoryEntityService,MemoryEmotion,MemoryInteraction from app.schemas.response_schema import ApiResponse @@ -295,6 +296,42 @@ async def get_graph_data_api( return fail(BizCode.INTERNAL_ERROR, "图数据查询失败", str(e)) +@router.get("/analytics/community_graph", response_model=ApiResponse) +async def get_community_graph_data_api( + end_user_id: str, + current_user: User = Depends(get_current_user), + db: Session = Depends(get_db), +) -> dict: + workspace_id = current_user.current_workspace_id + + if workspace_id is None: + api_logger.warning(f"用户 {current_user.username} 尝试查询社区图谱但未选择工作空间") + return fail(BizCode.INVALID_PARAMETER, "请先切换到一个工作空间", "current_workspace_id is None") + + api_logger.info( + f"社区图谱查询请求: end_user_id={end_user_id}, user={current_user.username}, " + f"workspace={workspace_id}" + ) + + try: + result = await analytics_community_graph_data(db=db, end_user_id=end_user_id) + + if "message" in result and result["statistics"]["total_nodes"] == 0: + api_logger.warning(f"社区图谱查询返回空结果: {result.get('message')}") + return success(data=result, msg=result.get("message", "查询成功")) + + api_logger.info( + f"成功获取社区图谱: end_user_id={end_user_id}, " + f"nodes={result['statistics']['total_nodes']}, " + f"edges={result['statistics']['total_edges']}" + ) + return success(data=result, msg="查询成功") + + except Exception as e: + api_logger.error(f"社区图谱查询失败: end_user_id={end_user_id}, error={str(e)}") + return fail(BizCode.INTERNAL_ERROR, "社区图谱查询失败", str(e)) + + @router.get("/read_end_user/profile", response_model=ApiResponse) async def get_end_user_profile( end_user_id: str, diff --git a/api/app/services/user_memory_service.py b/api/app/services/user_memory_service.py index 8bacc112..d21df064 100644 --- a/api/app/services/user_memory_service.py +++ b/api/app/services/user_memory_service.py @@ -1727,6 +1727,166 @@ async def analytics_graph_data( # 辅助函数 +async def analytics_community_graph_data( + db: Session, + end_user_id: str, +) -> Dict[str, Any]: + """ + 获取社区图谱数据，包含 Community 节点、ExtractedEntity 节点及其关系。 + + Returns: + 包含 nodes、edges、statistics 的字典，格式与 analytics_graph_data 一致 + """ + try: + user_uuid = uuid.UUID(end_user_id) + repo = EndUserRepository(db) + end_user = repo.get_by_id(user_uuid) + if not end_user: + return { + "nodes": [], "edges": [], + "statistics": {"total_nodes": 0, "total_edges": 0, "node_types": {}, "edge_types": {}}, + "message": "用户不存在" + } + + # 查询社区节点、实体节点、BELONGS_TO_COMMUNITY 边、实体间关系 + cypher = """ + MATCH (c:Community {end_user_id: $end_user_id}) + MATCH (e:ExtractedEntity {end_user_id: $end_user_id})-[b:BELONGS_TO_COMMUNITY]->(c) + OPTIONAL MATCH (e)-[r:EXTRACTED_RELATIONSHIP]-(e2:ExtractedEntity {end_user_id: $end_user_id}) + RETURN + elementId(c) AS c_id, + properties(c) AS c_props, + elementId(e) AS e_id, + properties(e) AS e_props, + elementId(b) AS b_id, + elementId(e2) AS e2_id, + properties(e2) AS e2_props, + elementId(r) AS r_id, + type(r) AS r_type, + properties(r) AS r_props, + startNode(r) = e AS r_from_e + """ + rows = await _neo4j_connector.execute_query(cypher, end_user_id=end_user_id) + + nodes_map: Dict[str, dict] = {} + edges_map: Dict[str, dict] = {} + # 记录每个 Community 对应的实体 id 列表 + community_members: Dict[str, list] = {} + + for row in rows: + # Community 节点 + c_id = row["c_id"] + if c_id and c_id not in nodes_map: + raw = row["c_props"] or {} + props = {k: _clean_neo4j_value(raw.get(k)) for k in ( + "community_id", "end_user_id", "member_count", "updated_at", + "name", "summary", "core_entities", + ) if k in raw} + nodes_map[c_id] = { + "id": c_id, + "label": "Community", + "properties": props, + } + + # ExtractedEntity 节点 (e) + e_id = row["e_id"] + if e_id and e_id not in nodes_map: + raw = row["e_props"] or {} + props = {k: _clean_neo4j_value(raw.get(k)) for k in ( + "name", "end_user_id", "description", "created_at", "entity_type", + ) if k in raw} + # 注入所属社区名称（c 是 e 直接归属的社区） + c_raw = row["c_props"] or {} + props["community_name"] = _clean_neo4j_value(c_raw.get("name")) or "" + nodes_map[e_id] = { + "id": e_id, + "label": "ExtractedEntity", + "properties": props, + } + + # ExtractedEntity 节点 (e2，可选) + e2_id = row.get("e2_id") + if e2_id and e2_id not in nodes_map: + raw = row["e2_props"] or {} + props = {k: _clean_neo4j_value(raw.get(k)) for k in ( + "name", "end_user_id", "description", "created_at", "entity_type", + ) if k in raw} + # e2 的社区归属在后处理阶段通过 community_members 补充 + props["community_name"] = "" + nodes_map[e2_id] = { + "id": e2_id, + "label": "ExtractedEntity", + "properties": props, + } + + # BELONGS_TO_COMMUNITY 边 + b_id = row["b_id"] + if b_id and b_id not in edges_map: + edges_map[b_id] = { + "id": b_id, + "source": e_id, + "target": c_id, + } + # 收集社区成员 id + if c_id and e_id: + community_members.setdefault(c_id, []) + if e_id not in community_members[c_id]: + community_members[c_id].append(e_id) + + # EXTRACTED_RELATIONSHIP 边（可选） + r_id = row.get("r_id") + if r_id and r_id not in edges_map and e2_id: + r_props = {k: _clean_neo4j_value(v) for k, v in (row["r_props"] or {}).items()} + source = e_id if row.get("r_from_e") else e2_id + target = e2_id if row.get("r_from_e") else e_id + edges_map[r_id] = { + "id": r_id, + "source": source, + "target": target, + } + + nodes = list(nodes_map.values()) + edges = list(edges_map.values()) + + # 为每个 Community 节点注入 member_entity_ids，同时补全 e2 节点的 community_name + for c_id, member_ids in community_members.items(): + c_node = nodes_map.get(c_id) + if c_node: + c_node["properties"]["member_entity_ids"] = member_ids + c_name = c_node["properties"].get("name") or "" + # 补全属于该社区但 community_name 为空的实体（即 e2 节点） + for eid in member_ids: + e_node = nodes_map.get(eid) + if e_node and e_node["label"] == "ExtractedEntity": + if not e_node["properties"].get("community_name"): + e_node["properties"]["community_name"] = c_name + + node_type_counts: Dict[str, int] = {} + for n in nodes: + node_type_counts[n["label"]] = node_type_counts.get(n["label"], 0) + 1 + + return { + "nodes": nodes, + "edges": edges, + "statistics": { + "total_nodes": len(nodes), + "total_edges": len(edges), + "node_types": node_type_counts, + } + } + + except ValueError: + logger.error(f"无效的 end_user_id 格式: {end_user_id}") + return { + "nodes": [], "edges": [], + "statistics": {"total_nodes": 0, "total_edges": 0, "node_types": {}, "edge_types": {}}, + "message": "无效的用户ID格式" + } + except Exception as e: + logger.error(f"获取社区图谱数据失败: {str(e)}", exc_info=True) + raise + + async def _extract_node_properties(label: str, properties: Dict[str, Any],node_id: str) -> Dict[str, Any]: """ 根据节点类型提取需要的属性字段 From 668539e737c43f79330ca5652181ba5de16f1fa9 Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Fri, 13 Mar 2026 15:47:53 +0800 Subject: [PATCH 5/9] [add] Selective merge submission --- api/app/celery_app.py | 1 + .../memory_dashboard_controller.py | 14 +- .../clustering_engine/label_propagation.py | 70 +++++++-- api/app/tasks.py | 138 ++++++++++++++++++ 4 files changed, 206 insertions(+), 17 deletions(-) diff --git a/api/app/celery_app.py b/api/app/celery_app.py index 60c22855..e77ed683 100644 --- a/api/app/celery_app.py +++ b/api/app/celery_app.py @@ -116,6 +116,7 @@ celery_app.conf.update( 'app.tasks.update_implicit_emotions_storage': {'queue': 'periodic_tasks'}, 'app.tasks.init_implicit_emotions_for_users': {'queue': 'periodic_tasks'}, 'app.tasks.init_interest_distribution_for_users': {'queue': 'periodic_tasks'}, + 'app.tasks.init_community_clustering_for_users': {'queue': 'periodic_tasks'}, }, ) diff --git a/api/app/controllers/memory_dashboard_controller.py b/api/app/controllers/memory_dashboard_controller.py index 3bbb5cf7..ce32a519 100644 --- a/api/app/controllers/memory_dashboard_controller.py +++ b/api/app/controllers/memory_dashboard_controller.py @@ -193,7 +193,19 @@ async def get_workspace_end_users( await aio_redis_set(cache_key, json.dumps(result), expire=30) except Exception as e: api_logger.warning(f"Redis 缓存写入失败: {str(e)}") - + + # 触发社区聚类补全任务（异步，不阻塞接口响应） + # 对有 ExtractedEntity 但无 Community 节点的存量用户自动补跑全量聚类 + try: + from app.tasks import init_community_clustering_for_users + init_community_clustering_for_users.apply_async( + kwargs={"end_user_ids": end_user_ids}, + queue="periodic_tasks", + ) + api_logger.info(f"已触发社区聚类补全任务，候选用户数: {len(end_user_ids)}") + except Exception as e: + api_logger.warning(f"触发社区聚类补全任务失败（不影响主流程）: {str(e)}") + api_logger.info(f"成功获取 {len(end_users)} 个宿主记录") return success(data=result, msg="宿主列表获取成功") diff --git a/api/app/core/memory/storage_services/clustering_engine/label_propagation.py b/api/app/core/memory/storage_services/clustering_engine/label_propagation.py index 251d4fea..4491b416 100644 --- a/api/app/core/memory/storage_services/clustering_engine/label_propagation.py +++ b/api/app/core/memory/storage_services/clustering_engine/label_propagation.py @@ -165,8 +165,15 @@ class LabelPropagationEngine: f"{len(labels)} 个实体" ) # 为所有社区生成元数据 - unique_communities = list(set(labels.values())) - for cid in unique_communities: + # 注意：_evaluate_merge 后部分社区已被合并消解，需重新从 Neo4j 查询实际存活的社区 + # 不能复用 labels.values()，那里包含已被 dissolve 的旧社区 ID + surviving_communities = await self.repo.get_all_entities(end_user_id) + surviving_community_ids = list({ + e.get("community_id") for e in surviving_communities + if e.get("community_id") + }) + logger.info(f"[Clustering] 合并后实际存活社区数: {len(surviving_community_ids)}") + for cid in surviving_community_ids: await self._generate_community_metadata(cid, end_user_id) async def incremental_update( @@ -249,7 +256,7 @@ class LabelPropagationEngine: 全量场景（社区数 > 20）使用批量查询，避免 N 次数据库往返。 """ - MERGE_THRESHOLD = 0.75 + MERGE_THRESHOLD = 0.85 BATCH_THRESHOLD = 20 # 超过此数量走批量查询 community_embeddings: Dict[str, Optional[List[float]]] = {} @@ -305,34 +312,65 @@ class LabelPropagationEngine: logger.info(f"[Clustering] 发现 {len(to_merge)} 对可合并社区") - # 执行合并：用 union-find 思路避免重复迁移已被合并的社区 - # 维护一个 canonical 映射，确保链式合并正确收敛 - canonical: Dict[str, str] = {cid: cid for cid in cids} + # 执行合并：逐对处理，每次合并后重新计算合并社区的平均向量 + # 避免 union-find 链式传递导致语义不相关的社区被间接合并 + # （A≈B、B≈C 不代表 A≈C，不能因传递性把 A/B/C 全部合并） + merged_into: Dict[str, str] = {} # dissolve → keep 的最终映射 - def find(x: str) -> str: - while canonical[x] != x: - canonical[x] = canonical[canonical[x]] - x = canonical[x] + def get_root(x: str) -> str: + """路径压缩，找到 x 当前所属的根社区。""" + while x in merged_into: + merged_into[x] = merged_into.get(merged_into[x], merged_into[x]) + x = merged_into[x] return x for c1, c2 in to_merge: - root1, root2 = find(c1), find(c2) + root1, root2 = get_root(c1), get_root(c2) if root1 == root2: - continue # 已经在同一社区，跳过 + continue + + # 用合并后的最新平均向量重新验证相似度 + # 防止链式传递：A≈B 合并后 B 的向量已更新，C 必须和新 B 相似才能合并 + current_sim = _cosine_similarity( + community_embeddings.get(root1), + community_embeddings.get(root2), + ) + if current_sim <= MERGE_THRESHOLD: + # 合并后向量已漂移，不再满足阈值，跳过 + logger.debug( + f"[Clustering] 跳过合并 {root1} ↔ {root2}，" + f"当前相似度 {current_sim:.3f} ≤ {MERGE_THRESHOLD}" + ) + continue + keep = root1 if community_sizes.get(root1, 0) >= community_sizes.get(root2, 0) else root2 dissolve = root2 if keep == root1 else root1 - canonical[dissolve] = keep + merged_into[dissolve] = keep members = await self.repo.get_community_members(dissolve, end_user_id) for m in members: await self.repo.assign_entity_to_community(m["id"], keep, end_user_id) - # 更新 sizes 以便后续合并决策准确 - community_sizes[keep] = community_sizes.get(keep, 0) + len(members) + + # 合并后重新计算 keep 的平均向量（加权平均） + keep_emb = community_embeddings.get(keep) + dissolve_emb = community_embeddings.get(dissolve) + keep_size = community_sizes.get(keep, 0) + dissolve_size = community_sizes.get(dissolve, 0) + total_size = keep_size + dissolve_size + if keep_emb and dissolve_emb and total_size > 0: + dim = len(keep_emb) + community_embeddings[keep] = [ + (keep_emb[i] * keep_size + dissolve_emb[i] * dissolve_size) / total_size + for i in range(dim) + ] + community_embeddings[dissolve] = None + + community_sizes[keep] = total_size community_sizes[dissolve] = 0 await self.repo.refresh_member_count(keep, end_user_id) logger.info( f"[Clustering] 社区合并: {dissolve} → {keep}，" - f"迁移 {len(members)} 个成员" + f"相似度={current_sim:.3f}，迁移 {len(members)} 个成员" ) async def _flush_labels( diff --git a/api/app/tasks.py b/api/app/tasks.py index 5e1550bd..f737bb48 100644 --- a/api/app/tasks.py +++ b/api/app/tasks.py @@ -2662,3 +2662,141 @@ def write_perceptual_memory( file_url, file_message, )) + + +# ============================================================================= +# 社区聚类补全任务（触发型） +# ============================================================================= + +@celery_app.task( + name="app.tasks.init_community_clustering_for_users", + bind=True, + ignore_result=False, + max_retries=0, + acks_late=False, + time_limit=7200, # 2小时硬超时 + soft_time_limit=6900, +) +def init_community_clustering_for_users(self, end_user_ids: List[str]) -> Dict[str, Any]: + """触发型任务：检查指定用户列表，对有 ExtractedEntity 但无 Community 节点的用户执行全量聚类。 + + 由 /dashboard/end_users 接口触发，已有社区节点的用户直接跳过。 + + Args: + end_user_ids: 需要检查的用户 ID 列表 + + Returns: + 包含任务执行结果的字典 + """ + start_time = time.time() + + async def _run() -> Dict[str, Any]: + from app.core.logging_config import get_logger + from app.repositories.neo4j.community_repository import CommunityRepository + from app.repositories.neo4j.neo4j_connector import Neo4jConnector + from app.core.memory.storage_services.clustering_engine.label_propagation import LabelPropagationEngine + + logger = get_logger(__name__) + logger.info(f"[CommunityCluster] 开始社区聚类补全任务，候选用户数: {len(end_user_ids)}") + + initialized = 0 + skipped = 0 + failed = 0 + + connector = Neo4jConnector() + try: + repo = CommunityRepository(connector) + + # 获取 llm_model_id（从第一个用户的配置中读取，作为全局兜底） + llm_model_id = None + try: + with get_db_context() as db: + from app.services.memory_agent_service import get_end_user_connected_config + from app.services.memory_config_service import MemoryConfigService + for uid in end_user_ids: + try: + connected = get_end_user_connected_config(uid, db) + config_id = connected.get("memory_config_id") + workspace_id = connected.get("workspace_id") + if config_id or workspace_id: + cfg = MemoryConfigService(db).load_memory_config( + config_id=config_id, workspace_id=workspace_id + ) + llm_model_id = str(cfg.llm_model_id) + break + except Exception: + continue + except Exception as e: + logger.warning(f"[CommunityCluster] 获取 LLM 配置失败，将使用兜底值: {e}") + + engine = LabelPropagationEngine( + connector=connector, + llm_model_id=llm_model_id, + ) + + for end_user_id in end_user_ids: + try: + # 已有社区节点则跳过 + has_communities = await repo.has_communities(end_user_id) + if has_communities: + skipped += 1 + logger.debug(f"[CommunityCluster] 用户 {end_user_id} 已有社区节点，跳过") + continue + + # 检查是否有 ExtractedEntity 节点 + entities = await repo.get_all_entities(end_user_id) + if not entities: + skipped += 1 + logger.debug(f"[CommunityCluster] 用户 {end_user_id} 无实体节点，跳过") + continue + + logger.info(f"[CommunityCluster] 用户 {end_user_id} 有 {len(entities)} 个实体，开始全量聚类") + await engine.full_clustering(end_user_id) + initialized += 1 + logger.info(f"[CommunityCluster] 用户 {end_user_id} 聚类完成") + + except Exception as e: + failed += 1 + logger.error(f"[CommunityCluster] 用户 {end_user_id} 聚类失败: {e}") + + finally: + await connector.close() + + logger.info( + f"[CommunityCluster] 任务完成: 初始化={initialized}, 跳过={skipped}, 失败={failed}" + ) + return { + "status": "SUCCESS", + "initialized": initialized, + "skipped": skipped, + "failed": failed, + } + + try: + try: + import nest_asyncio + nest_asyncio.apply() + except ImportError: + pass + + try: + loop = asyncio.get_event_loop() + if loop.is_closed(): + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + except RuntimeError: + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + + result = loop.run_until_complete(_run()) + result["elapsed_time"] = time.time() - start_time + result["task_id"] = self.request.id + return result + + except Exception as e: + return { + "status": "FAILURE", + "error": str(e), + "elapsed_time": time.time() - start_time, + "task_id": self.request.id, + } From 5141a9104187f4c6b29ded29ed0ec9646a78ef0f Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Fri, 13 Mar 2026 15:52:38 +0800 Subject: [PATCH 6/9] [changes] --- .../clustering_engine/label_propagation.py | 8 +++++- .../neo4j/community_repository.py | 21 ++++++++++++++++ api/app/repositories/neo4j/cypher_queries.py | 25 +++++++++++++++++++ 3 files changed, 53 insertions(+), 1 deletion(-) diff --git a/api/app/core/memory/storage_services/clustering_engine/label_propagation.py b/api/app/core/memory/storage_services/clustering_engine/label_propagation.py index 4491b416..cbc303b1 100644 --- a/api/app/core/memory/storage_services/clustering_engine/label_propagation.py +++ b/api/app/core/memory/storage_services/clustering_engine/label_propagation.py @@ -121,12 +121,18 @@ class LabelPropagationEngine: e["id"]: e.get("name_embedding") for e in entities } + # 预加载所有实体的邻居，避免迭代内 O(iterations * |E|) 次 Neo4j 往返 + logger.info(f"[Clustering] 预加载 {len(entities)} 个实体的邻居图...") + neighbors_cache: Dict[str, List[Dict]] = await self.repo.get_all_entity_neighbors_batch(end_user_id) + logger.info(f"[Clustering] 邻居预加载完成，覆盖实体数: {len(neighbors_cache)}") + for iteration in range(MAX_ITERATIONS): changed = 0 # 随机顺序（Python dict 在 3.7+ 保持插入顺序，这里直接遍历） for entity in entities: eid = entity["id"] - neighbors = await self.repo.get_entity_neighbors(eid, end_user_id) + # 直接从缓存取邻居，不再发起 Neo4j 查询 + neighbors = neighbors_cache.get(eid, []) # 将邻居的当前内存标签注入（覆盖 Neo4j 中的旧值） enriched = [] diff --git a/api/app/repositories/neo4j/community_repository.py b/api/app/repositories/neo4j/community_repository.py index 6c5c7618..f2f11f76 100644 --- a/api/app/repositories/neo4j/community_repository.py +++ b/api/app/repositories/neo4j/community_repository.py @@ -15,6 +15,7 @@ from app.repositories.neo4j.cypher_queries import ( GET_ALL_ENTITIES_FOR_USER, GET_COMMUNITY_MEMBERS, GET_ALL_COMMUNITY_MEMBERS_BATCH, + GET_ALL_ENTITY_NEIGHBORS_BATCH, CHECK_USER_HAS_COMMUNITIES, UPDATE_COMMUNITY_MEMBER_COUNT, UPDATE_COMMUNITY_METADATA, @@ -78,6 +79,26 @@ class CommunityRepository: logger.error(f"get_entity_neighbors failed: {e}") return [] + async def get_all_entity_neighbors_batch( + self, end_user_id: str + ) -> Dict[str, List[Dict]]: + """一次性批量拉取该用户下所有实体的邻居，返回 {entity_id: [neighbors]} 字典。 + 用于全量聚类预加载，避免每个实体单独查询。""" + try: + rows = await self.connector.execute_query( + GET_ALL_ENTITY_NEIGHBORS_BATCH, + end_user_id=end_user_id, + ) + result: Dict[str, List[Dict]] = {} + for row in rows: + eid = row["entity_id"] + neighbor = {k: v for k, v in row.items() if k != "entity_id"} + result.setdefault(eid, []).append(neighbor) + return result + except Exception as e: + logger.error(f"get_all_entity_neighbors_batch failed: {e}") + return {} + async def get_all_entities(self, end_user_id: str) -> List[Dict]: """拉取某用户下所有实体及其当前社区归属。""" try: diff --git a/api/app/repositories/neo4j/cypher_queries.py b/api/app/repositories/neo4j/cypher_queries.py index b270ed64..3487e55e 100644 --- a/api/app/repositories/neo4j/cypher_queries.py +++ b/api/app/repositories/neo4j/cypher_queries.py @@ -1159,3 +1159,28 @@ SET c.name = $name, c.updated_at = datetime() RETURN c.community_id AS community_id """ + +GET_ALL_ENTITY_NEIGHBORS_BATCH = """ +// 批量拉取某用户下所有实体的邻居（用于全量聚类预加载） +MATCH (e:ExtractedEntity {end_user_id: $end_user_id}) + +// 来源一：直接关系邻居 +OPTIONAL MATCH (e)-[:EXTRACTED_RELATIONSHIP]-(nb1:ExtractedEntity {end_user_id: $end_user_id}) + +// 来源二：同 Statement 共现邻居 +OPTIONAL MATCH (s:Statement)-[:REFERENCES_ENTITY]->(e) +OPTIONAL MATCH (s)-[:REFERENCES_ENTITY]->(nb2:ExtractedEntity {end_user_id: $end_user_id}) +WHERE nb2.id <> e.id + +WITH e, collect(DISTINCT nb1) + collect(DISTINCT nb2) AS all_neighbors +UNWIND all_neighbors AS nb +WITH e, nb WHERE nb IS NOT NULL +OPTIONAL MATCH (nb)-[:BELONGS_TO_COMMUNITY]->(c:Community) +RETURN DISTINCT + e.id AS entity_id, + nb.id AS id, + nb.name AS name, + nb.name_embedding AS name_embedding, + nb.activation_value AS activation_value, + CASE WHEN c IS NOT NULL THEN c.community_id ELSE null END AS community_id +""" From 382e4c537741af526218000cce7501c30682032c Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Fri, 13 Mar 2026 18:02:23 +0800 Subject: [PATCH 7/9] [changes] The user's personal configuration and the clustering trigger boundary are clearly defined --- api/app/repositories/neo4j/graph_saver.py | 36 ++++++++++---- api/app/tasks.py | 57 ++++++++++------------- 2 files changed, 52 insertions(+), 41 deletions(-) diff --git a/api/app/repositories/neo4j/graph_saver.py b/api/app/repositories/neo4j/graph_saver.py index 2ef9bafc..cbd2b532 100644 --- a/api/app/repositories/neo4j/graph_saver.py +++ b/api/app/repositories/neo4j/graph_saver.py @@ -293,15 +293,8 @@ async def save_dialog_and_statements_to_neo4j( logger.info("Transaction completed. Summary: %s", summary) logger.debug("Full transaction results: %r", results) - # 写入成功后，触发聚类（可通过环境变量 CLUSTERING_ENABLED=false 禁用，用于基准测试对比） - clustering_enabled = os.getenv("CLUSTERING_ENABLED", "true").lower() != "false" - if entity_nodes and clustering_enabled: - end_user_id = entity_nodes[0].end_user_id - new_entity_ids = [e.id for e in entity_nodes] - logger.info(f"[Clustering] 准备触发聚类，实体数: {len(new_entity_ids)}, end_user_id: {end_user_id}") - asyncio.create_task(_trigger_clustering(new_entity_ids, end_user_id, config_id=config_id, llm_model_id=llm_model_id)) - elif entity_nodes and not clustering_enabled: - logger.info("[Clustering] 聚类已禁用（CLUSTERING_ENABLED=false），跳过聚类触发") + # 写入成功后，异步触发聚类（不阻塞写入响应） + schedule_clustering_after_write(entity_nodes, config_id=config_id, llm_model_id=llm_model_id) return True @@ -312,6 +305,31 @@ async def save_dialog_and_statements_to_neo4j( return False +def schedule_clustering_after_write( + entity_nodes: List, + config_id: Optional[str] = None, + llm_model_id: Optional[str] = None, +) -> None: + """ + 写入 Neo4j 成功后，调度后台聚类任务。 + + 可通过环境变量 CLUSTERING_ENABLED=false 禁用（用于基准测试对比）。 + 使用 asyncio.create_task 异步触发，不阻塞写入响应。 + """ + if not entity_nodes: + return + + clustering_enabled = os.getenv("CLUSTERING_ENABLED", "true").lower() != "false" + if not clustering_enabled: + logger.info("[Clustering] 聚类已禁用（CLUSTERING_ENABLED=false），跳过聚类触发") + return + + end_user_id = entity_nodes[0].end_user_id + new_entity_ids = [e.id for e in entity_nodes] + logger.info(f"[Clustering] 准备触发聚类，实体数: {len(new_entity_ids)}, end_user_id: {end_user_id}") + asyncio.create_task(_trigger_clustering(new_entity_ids, end_user_id, config_id=config_id, llm_model_id=llm_model_id)) + + async def _trigger_clustering( new_entity_ids: List[str], end_user_id: str, diff --git a/api/app/tasks.py b/api/app/tasks.py index f737bb48..8ad2c467 100644 --- a/api/app/tasks.py +++ b/api/app/tasks.py @@ -2707,32 +2707,26 @@ def init_community_clustering_for_users(self, end_user_ids: List[str]) -> Dict[s try: repo = CommunityRepository(connector) - # 获取 llm_model_id（从第一个用户的配置中读取，作为全局兜底） - llm_model_id = None + # 批量预取所有用户的配置（内置兜底：用户配置不可用时自动回退到工作空间默认配置） + user_llm_map: Dict[str, Optional[str]] = {} try: with get_db_context() as db: - from app.services.memory_agent_service import get_end_user_connected_config + from app.services.memory_agent_service import get_end_users_connected_configs_batch from app.services.memory_config_service import MemoryConfigService - for uid in end_user_ids: - try: - connected = get_end_user_connected_config(uid, db) - config_id = connected.get("memory_config_id") - workspace_id = connected.get("workspace_id") - if config_id or workspace_id: - cfg = MemoryConfigService(db).load_memory_config( - config_id=config_id, workspace_id=workspace_id - ) - llm_model_id = str(cfg.llm_model_id) - break - except Exception: - continue + batch_configs = get_end_users_connected_configs_batch(end_user_ids, db) + for uid, cfg_info in batch_configs.items(): + config_id = cfg_info.get("memory_config_id") + if config_id: + try: + cfg = MemoryConfigService(db).load_memory_config(config_id=config_id) + user_llm_map[uid] = str(cfg.llm_model_id) if cfg.llm_model_id else None + except Exception as e: + logger.warning(f"[CommunityCluster] 用户 {uid} 加载 LLM 配置失败，将使用 None: {e}") + user_llm_map[uid] = None + else: + user_llm_map[uid] = None except Exception as e: - logger.warning(f"[CommunityCluster] 获取 LLM 配置失败，将使用兜底值: {e}") - - engine = LabelPropagationEngine( - connector=connector, - llm_model_id=llm_model_id, - ) + logger.warning(f"[CommunityCluster] 批量获取 LLM 配置失败，所有用户将使用 None: {e}") for end_user_id in end_user_ids: try: @@ -2750,7 +2744,14 @@ def init_community_clustering_for_users(self, end_user_ids: List[str]) -> Dict[s logger.debug(f"[CommunityCluster] 用户 {end_user_id} 无实体节点，跳过") continue - logger.info(f"[CommunityCluster] 用户 {end_user_id} 有 {len(entities)} 个实体，开始全量聚类") + # 每个用户使用自己的 llm_model_id + llm_model_id = user_llm_map.get(end_user_id) + engine = LabelPropagationEngine( + connector=connector, + llm_model_id=llm_model_id, + ) + + logger.info(f"[CommunityCluster] 用户 {end_user_id} 有 {len(entities)} 个实体，开始全量聚类，llm_model_id={llm_model_id}") await engine.full_clustering(end_user_id) initialized += 1 logger.info(f"[CommunityCluster] 用户 {end_user_id} 聚类完成") @@ -2779,15 +2780,7 @@ def init_community_clustering_for_users(self, end_user_ids: List[str]) -> Dict[s except ImportError: pass - try: - loop = asyncio.get_event_loop() - if loop.is_closed(): - loop = asyncio.new_event_loop() - asyncio.set_event_loop(loop) - except RuntimeError: - loop = asyncio.new_event_loop() - asyncio.set_event_loop(loop) - + loop = set_asyncio_event_loop() result = loop.run_until_complete(_run()) result["elapsed_time"] = time.time() - start_time result["task_id"] = self.request.id From f033607c8b1d487a17b48a1a103ee751de5edadd Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Fri, 13 Mar 2026 20:07:18 +0800 Subject: [PATCH 8/9] [changes] Queue uniformity, query statement uniformity --- .../memory_dashboard_controller.py | 1 - api/app/repositories/neo4j/cypher_queries.py | 18 +++++++++++++++++ api/app/services/user_memory_service.py | 20 ++----------------- 3 files changed, 20 insertions(+), 19 deletions(-) diff --git a/api/app/controllers/memory_dashboard_controller.py b/api/app/controllers/memory_dashboard_controller.py index ce32a519..92d0ff36 100644 --- a/api/app/controllers/memory_dashboard_controller.py +++ b/api/app/controllers/memory_dashboard_controller.py @@ -200,7 +200,6 @@ async def get_workspace_end_users( from app.tasks import init_community_clustering_for_users init_community_clustering_for_users.apply_async( kwargs={"end_user_ids": end_user_ids}, - queue="periodic_tasks", ) api_logger.info(f"已触发社区聚类补全任务，候选用户数: {len(end_user_ids)}") except Exception as e: diff --git a/api/app/repositories/neo4j/cypher_queries.py b/api/app/repositories/neo4j/cypher_queries.py index 3487e55e..48a5ac87 100644 --- a/api/app/repositories/neo4j/cypher_queries.py +++ b/api/app/repositories/neo4j/cypher_queries.py @@ -1184,3 +1184,21 @@ RETURN DISTINCT nb.activation_value AS activation_value, CASE WHEN c IS NOT NULL THEN c.community_id ELSE null END AS community_id """ + +GET_COMMUNITY_GRAPH_DATA = """ +MATCH (c:Community {end_user_id: $end_user_id}) +MATCH (e:ExtractedEntity {end_user_id: $end_user_id})-[b:BELONGS_TO_COMMUNITY]->(c) +OPTIONAL MATCH (e)-[r:EXTRACTED_RELATIONSHIP]-(e2:ExtractedEntity {end_user_id: $end_user_id}) +RETURN + elementId(c) AS c_id, + properties(c) AS c_props, + elementId(e) AS e_id, + properties(e) AS e_props, + elementId(b) AS b_id, + elementId(e2) AS e2_id, + properties(e2) AS e2_props, + elementId(r) AS r_id, + type(r) AS r_type, + properties(r) AS r_props, + startNode(r) = e AS r_from_e +""" diff --git a/api/app/services/user_memory_service.py b/api/app/services/user_memory_service.py index d21df064..d5d19e0d 100644 --- a/api/app/services/user_memory_service.py +++ b/api/app/services/user_memory_service.py @@ -1749,24 +1749,8 @@ async def analytics_community_graph_data( } # 查询社区节点、实体节点、BELONGS_TO_COMMUNITY 边、实体间关系 - cypher = """ - MATCH (c:Community {end_user_id: $end_user_id}) - MATCH (e:ExtractedEntity {end_user_id: $end_user_id})-[b:BELONGS_TO_COMMUNITY]->(c) - OPTIONAL MATCH (e)-[r:EXTRACTED_RELATIONSHIP]-(e2:ExtractedEntity {end_user_id: $end_user_id}) - RETURN - elementId(c) AS c_id, - properties(c) AS c_props, - elementId(e) AS e_id, - properties(e) AS e_props, - elementId(b) AS b_id, - elementId(e2) AS e2_id, - properties(e2) AS e2_props, - elementId(r) AS r_id, - type(r) AS r_type, - properties(r) AS r_props, - startNode(r) = e AS r_from_e - """ - rows = await _neo4j_connector.execute_query(cypher, end_user_id=end_user_id) + from app.repositories.neo4j.cypher_queries import GET_COMMUNITY_GRAPH_DATA + rows = await _neo4j_connector.execute_query(GET_COMMUNITY_GRAPH_DATA, end_user_id=end_user_id) nodes_map: Dict[str, dict] = {} edges_map: Dict[str, dict] = {} From 4bf418a3d6714c16e7537e588adcb9106c01f634 Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Fri, 13 Mar 2026 20:25:11 +0800 Subject: [PATCH 9/9] [changes] Unified management of delays --- api/app/controllers/memory_dashboard_controller.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/api/app/controllers/memory_dashboard_controller.py b/api/app/controllers/memory_dashboard_controller.py index 92d0ff36..bad706d4 100644 --- a/api/app/controllers/memory_dashboard_controller.py +++ b/api/app/controllers/memory_dashboard_controller.py @@ -198,9 +198,7 @@ async def get_workspace_end_users( # 对有 ExtractedEntity 但无 Community 节点的存量用户自动补跑全量聚类 try: from app.tasks import init_community_clustering_for_users - init_community_clustering_for_users.apply_async( - kwargs={"end_user_ids": end_user_ids}, - ) + init_community_clustering_for_users.delay(end_user_ids=end_user_ids) api_logger.info(f"已触发社区聚类补全任务，候选用户数: {len(end_user_ids)}") except Exception as e: api_logger.warning(f"触发社区聚类补全任务失败（不影响主流程）: {str(e)}")