diff --git a/llmengine/db_neo4j.py b/llmengine/db_neo4j.py new file mode 100644 index 0000000..d6f0a42 --- /dev/null +++ b/llmengine/db_neo4j.py @@ -0,0 +1,560 @@ +from typing import Dict, List, Any, Set, Tuple +from appPublic.jsonConfig import getConfig +from appPublic.log import debug, error, info +from py2neo import Graph, Node, Relationship +import re +from llmengine.base_db import BaseDBConnection, connection_register +from threading import Lock +from scipy.spatial.distance import cosine +import numpy as np +import aiohttp +import asyncio +import time + +# 嵌入缓存 +EMBED_CACHE = {} + +class Neo4jConnection(BaseDBConnection): + _instance = None + _lock = Lock() + + def __new__(cls): + with cls._lock: + if cls._instance is None: + cls._instance = super(Neo4jConnection, cls).__new__(cls) + cls._instance._initialized = False + return cls._instance + + def __init__(self): + if self._initialized: + return + try: + config = getConfig() + self.neo4j_uri = config['neo4j']['uri'] + self.neo4j_user = config['neo4j']['user'] + self.neo4j_password = config['neo4j']['password'] + self.g = Graph(self.neo4j_uri, auth=(self.neo4j_user, self.neo4j_password)) + info("Neo4jConnection initialized") + self._initialized = True + except KeyError as e: + error(f"配置文件缺少必要字段: {str(e)}") + self._initialized = False + raise RuntimeError(f"配置文件缺少必要字段: {str(e)}") + except Exception as e: + error(f"Neo4jConnection 初始化失败: {str(e)}") + self._initialized = False + raise RuntimeError(f"Neo4jConnection 初始化失败: {str(e)}") + + def _normalize_label(self, entity_type: str) -> str: + """规范化实体类型为 Neo4j 标签""" + if not entity_type or not entity_type.strip(): + return 'Entity' + entity_type = re.sub(r'[^\w\s]', '', entity_type.strip()) + words = entity_type.split() + label = '_'.join(word.capitalize() for word in words if word) + return label or 'Entity' + + def _clean_relation(self, relation: str) -> Tuple[str, str]: + """清洗关系，返回 (rel_type, rel_name)，确保 rel_type 合法""" + relation = relation.strip() + if not relation: + return 'RELATED_TO', '相关' + cleaned_relation = re.sub(r'[^\w\s]', '', relation).strip() + if not cleaned_relation: + return 'RELATED_TO', '相关' + if 'instance of' in relation.lower(): + return 'INSTANCE_OF', '实例' + elif 'subclass of' in relation.lower(): + return 'SUBCLASS_OF', '子类' + elif 'part of' in relation.lower(): + return 'PART_OF', '部分' + rel_type = re.sub(r'\s+', '_', cleaned_relation).upper() + if rel_type and rel_type[0].isdigit(): + rel_type = f'REL_{rel_type}' + if not re.match(r'^[A-Za-z][A-Za-z0-9_]*$', rel_type): + debug(f"非法关系类型 '{rel_type}'，替换为 'RELATED_TO'") + return 'RELATED_TO', relation + return rel_type, relation + + def _read_nodes(self, triples: List[Dict]) -> Tuple[Dict[str, Set], Dict[str, List], List[Dict]]: + """从三元组列表中读取节点和关系""" + nodes_by_label = {} + relations_by_type = {} + valid_triples = [] + try: + for triple in triples: + if not all(key in triple for key in ['head', 'head_type', 'type', 'tail', 'tail_type']): + debug(f"无效三元组: {triple}") + continue + head, relation, tail, head_type, tail_type = ( + triple['head'], triple['type'], triple['tail'], triple['head_type'], triple['tail_type'] + ) + head_label = self._normalize_label(head_type) + tail_label = self._normalize_label(tail_type) + debug(f"实体类型: {head_type} -> {head_label}, {tail_type} -> {tail_label}") + if head_label not in nodes_by_label: + nodes_by_label[head_label] = set() + if tail_label not in nodes_by_label: + nodes_by_label[tail_label] = set() + nodes_by_label[head_label].add(head) + nodes_by_label[tail_label].add(tail) + rel_type, rel_name = self._clean_relation(relation) + if rel_type not in relations_by_type: + relations_by_type[rel_type] = [] + relations_by_type[rel_type].append({ + 'head': head, + 'tail': tail, + 'head_label': head_label, + 'tail_label': tail_label, + 'rel_name': rel_name + }) + valid_triples.append({ + 'head': head, + 'relation': relation, + 'tail': tail, + 'head_type': head_type, + 'tail_type': tail_type + }) + info(f"读取节点: {sum(len(nodes) for nodes in nodes_by_label.values())} 个") + info(f"读取关系: {sum(len(rels) for rels in relations_by_type.values())} 条") + return nodes_by_label, relations_by_type, valid_triples + except Exception as e: + error(f"读取三元组失败: {str(e)}") + raise RuntimeError(f"读取三元组失败: {str(e)}") + + def _create_node(self, label: str, nodes: Set[str], document_id: str, knowledge_base_id: str, userid: str) -> int: + """创建节点，包含 document_id、knowledge_base_id 和 userid 属性""" + count = 0 + for node_name in nodes: + query = ( + f"MATCH (n:{label} {{name: $name, document_id: $doc_id, " + f"knowledge_base_id: $kb_id, userid: $userid}}) RETURN n" + ) + try: + if self.g.run(query, name=node_name, doc_id=document_id, + kb_id=knowledge_base_id, userid=userid).data(): + continue + node = Node( + label, + name=node_name, + document_id=document_id, + knowledge_base_id=knowledge_base_id, + userid=userid + ) + self.g.create(node) + count += 1 + debug(f"创建节点: {label} - {node_name} (document_id: {document_id}, " + f"knowledge_base_id: {knowledge_base_id}, userid: {userid})") + except Exception as e: + error(f"创建节点失败: {label} - {node_name}, 错误: {str(e)}") + info(f"创建 {label} 节点: {count}/{len(nodes)} 个") + return count + + def _create_relationship(self, rel_type: str, relations: List[Dict], document_id: str, knowledge_base_id: str, userid: str) -> int: + """创建关系，包含 document_id、knowledge_base_id 和 userid 属性""" + count = 0 + total = len(relations) + seen_edges = set() + for rel in relations: + head, tail, head_label, tail_label, rel_name = ( + rel['head'], rel['tail'], rel['head_label'], rel['tail_label'], rel['rel_name'] + ) + edge_key = f"{head_label}:{head}###{tail_label}:{tail}###{rel_type}" + if edge_key in seen_edges: + continue + seen_edges.add(edge_key) + query = ( + f"MATCH (p:{head_label} {{name: $head, document_id: $doc_id, " + f"knowledge_base_id: $kb_id, userid: $userid}}), " + f"(q:{tail_label} {{name: $tail, document_id: $doc_id, " + f"knowledge_base_id: $kb_id, userid: $userid}}) " + f"CREATE (p)-[r:{rel_type} {{name: $rel_name, document_id: $doc_id, " + f"knowledge_base_id: $kb_id, userid: $userid}}]->(q)" + ) + try: + self.g.run(query, head=head, tail=tail, rel_name=rel_name, + doc_id=document_id, kb_id=knowledge_base_id, + userid=userid) + count += 1 + debug(f"创建关系: {head} -[{rel_type}]-> {tail} (document_id: {document_id}, " + f"knowledge_base_id: {knowledge_base_id}, userid: {userid})") + except Exception as e: + error(f"创建关系失败: {query}, 错误: {str(e)}") + info(f"创建 {rel_type} 关系: {count}/{total} 条") + return count + + async def _get_embeddings(self, texts: List[str]) -> List[List[float]]: + """调用嵌入服务获取文本的向量，带缓存""" + try: + uncached_texts = [text for text in texts if text not in EMBED_CACHE] + if uncached_texts: + async with aiohttp.ClientSession() as session: + async with session.post( + "http://localhost:9998/v1/embeddings", + headers={"Content-Type": "application/json"}, + json={"input": uncached_texts} + ) as response: + if response.status != 200: + error(f"嵌入服务调用失败，状态码: {response.status}") + raise RuntimeError(f"嵌入服务调用失败: {response.status}") + result = await response.json() + if result.get("object") != "list" or not result.get("data"): + error(f"嵌入服务响应格式错误: {result}") + raise RuntimeError("嵌入服务响应格式错误") + embeddings = [item["embedding"] for item in result["data"]] + for text, embedding in zip(uncached_texts, embeddings): + EMBED_CACHE[text] = np.array(embedding) / np.linalg.norm(embedding) + debug(f"成功获取 {len(embeddings)} 个新嵌入向量，缓存大小: {len(EMBED_CACHE)}") + return [EMBED_CACHE[text] for text in texts] + except Exception as e: + error(f"嵌入服务调用失败: {str(e)}") + raise RuntimeError(f"嵌入服务调用失败: {str(e)}") + + async def handle_connection(self, action: str, params: Dict = None) -> Dict: + """处理 Neo4j 数据库操作""" + if not params: + params = {} + try: + debug(f"处理 Neo4j 操作: action={action}, params={params}") + collection_name = "neo4j" # 为了与 MilvusConnection 的返回格式一致 + document_id = params.get("document_id", "") + if not self._initialized: + error("Neo4j 服务未启动") + return { + "status": "error", + "message": "Neo4j 服务未启动", + "collection_name": collection_name, + "document_id": document_id, + "status_code": 400 + } + if action == "initialize": + return { + "status": "success", + "message": "Neo4j 服务已初始化", + "collection_name": collection_name, + "document_id": document_id, + "status_code": 200 + } + elif action == "insert_triples": + triples = params.get("triples", []) + document_id = params.get("document_id", "") + knowledge_base_id = params.get("knowledge_base_id", "") + userid = params.get("userid", "") + if not triples or not document_id or not knowledge_base_id or not userid: + return { + "status": "error", + "message": "triples、document_id、knowledge_base_id 和 userid 不能为空", + "collection_name": collection_name, + "document_id": document_id, + "status_code": 400 + } + return self._insert_triples(triples, document_id, knowledge_base_id, userid) + elif action == "delete_document": + document_id = params.get("document_id", "") + if not document_id: + return { + "status": "error", + "message": "document_id 不能为空", + "collection_name": collection_name, + "document_id": document_id, + "status_code": 400 + } + return self._delete_document(document_id) + elif action == "delete_knowledge_base": + userid = params.get("userid", "") + knowledge_base_id = params.get("knowledge_base_id", "") + if not userid or not knowledge_base_id: + return { + "status": "error", + "message": "userid 和 knowledge_base_id 不能为空", + "collection_name": collection_name, + "document_id": document_id, + "status_code": 400 + } + return self._delete_knowledge_base(userid, knowledge_base_id) + elif action == "match_triplets": + query = params.get("query", "") + query_entities = params.get("query_entities", []) + userid = params.get("userid", "") + knowledge_base_id = params.get("knowledge_base_id", "") + if not query or not query_entities or not userid or not knowledge_base_id: + return { + "status": "error", + "message": "query、query_entities、userid 和 knowledge_base_id 不能为空", + "collection_name": collection_name, + "document_id": document_id, + "status_code": 400 + } + return await self._match_triplets(query, query_entities, userid, knowledge_base_id) + else: + return { + "status": "error", + "message": f"未知的 action: {action}", + "collection_name": collection_name, + "document_id": document_id, + "status_code": 400 + } + except Exception as e: + error(f"处理 Neo4j 操作失败: action={action}, 错误: {str(e)}") + return { + "status": "error", + "message": f"服务器错误: {str(e)}", + "collection_name": collection_name, + "document_id": document_id, + "status_code": 400 + } + + def _insert_triples(self, triples: List[Dict], document_id: str, knowledge_base_id: str, userid: str) -> Dict: + """插入三元组到 Neo4j""" + try: + if not triples: + return { + "status": "success", + "message": "没有三元组需要插入", + "nodes_created": 0, + "rels_created": 0, + "collection_name": "neo4j", + "document_id": document_id, + "status_code": 200 + } + nodes_by_label, relations_by_type, _ = self._read_nodes(triples) + total_nodes = 0 + for label, nodes in nodes_by_label.items(): + total_nodes += self._create_node(label, nodes, document_id, knowledge_base_id, userid) + total_rels = 0 + for rel_type, relations in relations_by_type.items(): + total_rels += self._create_relationship(rel_type, relations, document_id, knowledge_base_id, userid) + info(f"成功插入 {total_nodes} 个节点和 {total_rels} 个关系") + return { + "status": "success", + "message": f"成功插入 {total_nodes} 个节点和 {total_rels} 个关系", + "nodes_created": total_nodes, + "rels_created": total_rels, + "collection_name": "neo4j", + "document_id": document_id, + "status_code": 200 + } + except Exception as e: + error(f"插入三元组失败: {str(e)}") + return { + "status": "error", + "message": f"插入三元组失败: {str(e)}", + "collection_name": "neo4j", + "document_id": document_id, + "status_code": 400 + } + + def _delete_document(self, document_id: str) -> Dict: + """删除 Neo4j 中指定文档的数据""" + try: + query = """ + MATCH (n {document_id: $document_id}) + OPTIONAL MATCH (n)-[r {document_id: $document_id}]->() + WITH collect(r) AS rels, collect(n) AS nodes + FOREACH (r IN rels | DELETE r) + FOREACH (n IN nodes | DELETE n) + RETURN size(nodes) AS node_count, size(rels) AS rel_count, [r IN rels | type(r)] AS rel_types + """ + result = self.g.run(query, document_id=document_id).data() + nodes_deleted = result[0]['node_count'] if result else 0 + rels_deleted = result[0]['rel_count'] if result else 0 + rel_types = result[0]['rel_types'] if result else [] + info(f"成功删除 document_id={document_id} 的 {nodes_deleted} 个节点和 {rels_deleted} 个关系，关系类型: {rel_types}") + return { + "status": "success", + "message": f"成功删除 {nodes_deleted} 个节点和 {rels_deleted} 个关系", + "nodes_deleted": nodes_deleted, + "rels_deleted": rels_deleted, + "collection_name": "neo4j", + "document_id": document_id, + "status_code": 200 + } + except Exception as e: + error(f"删除 document_id={document_id} 的 Neo4j 数据失败: {str(e)}") + return { + "status": "error", + "message": f"删除 Neo4j 数据失败: {str(e)}", + "collection_name": "neo4j", + "document_id": document_id, + "status_code": 400 + } + + def _delete_knowledge_base(self, userid: str, knowledge_base_id: str) -> Dict: + """删除 Neo4j 中指定用户和知识库的数据""" + try: + query = """ + MATCH (n {userid: $userid, knowledge_base_id: $knowledge_base_id}) + OPTIONAL MATCH (n)-[r {userid: $userid, knowledge_base_id: $knowledge_base_id}]->() + WITH collect(r) AS rels, collect(n) AS nodes + FOREACH (r IN rels | DELETE r) + FOREACH (n IN nodes | DELETE n) + RETURN size(nodes) AS node_count, size(rels) AS rel_count, [r IN rels | type(r)] AS rel_types + """ + result = self.g.run(query, userid=userid, knowledge_base_id=knowledge_base_id).data() + nodes_deleted = result[0]['node_count'] if result else 0 + rels_deleted = result[0]['rel_count'] if result else 0 + rel_types = result[0]['rel_types'] if result else [] + info(f"成功删除 userid={userid}, knowledge_base_id={knowledge_base_id} 的 {nodes_deleted} 个节点和 {rels_deleted} 个关系") + return { + "status": "success", + "message": f"成功删除 {nodes_deleted} 个节点和 {rels_deleted} 个关系", + "nodes_deleted": nodes_deleted, + "rels_deleted": rels_deleted, + "collection_name": "neo4j", + "document_id": "", + "status_code": 200 + } + except Exception as e: + error(f"删除 Neo4j 数据失败: {str(e)}") + return { + "status": "error", + "message": f"删除 Neo4j 数据失败: {str(e)}", + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 + } + + async def _match_triplets(self, query: str, query_entities: List[str], userid: str, knowledge_base_id: str) -> Dict: + """匹配查询实体与 Neo4j 中的三元组""" + start_time = time.time() + timing_stats = {} + matched_triplets = [] + ENTITY_SIMILARITY_THRESHOLD = 0.8 + try: + debug(f"已连接到 Neo4j: {self.neo4j_uri}") + timing_stats["neo4j_connect"] = time.time() - start_time + + matched_names = set() + entity_match_start = time.time() + for entity in query_entities: + normalized_entity = entity.lower().strip() + query = """ + MATCH (n {userid: $userid, knowledge_base_id: $knowledge_base_id}) + WHERE toLower(n.name) CONTAINS $entity + OR apoc.text.levenshteinSimilarity(toLower(n.name), $entity) > 0.7 + RETURN n.name, apoc.text.levenshteinSimilarity(toLower(n.name), $entity) AS sim + ORDER BY sim DESC + LIMIT 100 + """ + try: + results = self.g.run(query, userid=userid, knowledge_base_id=knowledge_base_id, entity=normalized_entity).data() + for record in results: + matched_names.add(record['n.name']) + debug(f"实体 {entity} 匹配节点: {record['n.name']} (Levenshtein 相似度: {record['sim']:.2f})") + except Exception as e: + debug(f"模糊匹配实体 {entity} 失败: {str(e)}") + continue + timing_stats["entity_match"] = time.time() - entity_match_start + debug(f"实体匹配耗时: {timing_stats['entity_match']:.3f} 秒") + + triplets = [] + if matched_names: + triplet_query_start = time.time() + query = """ + MATCH (h {userid: $userid, knowledge_base_id: $knowledge_base_id})-[r {userid: $userid, knowledge_base_id: $knowledge_base_id}]->(t {userid: $userid, knowledge_base_id: $knowledge_base_id}) + WHERE h.name IN $matched_names OR t.name IN $matched_names + RETURN h.name AS head, r.name AS type, t.name AS tail + LIMIT 100 + """ + try: + results = self.g.run(query, userid=userid, knowledge_base_id=knowledge_base_id, matched_names=list(matched_names)).data() + seen = set() + for record in results: + head, type_, tail = record['head'], record['type'], record['tail'] + triplet_key = (head.lower(), type_.lower(), tail.lower()) + if triplet_key not in seen: + seen.add(triplet_key) + triplets.append({ + 'head': head, + 'type': type_, + 'tail': tail, + 'head_type': '', + 'tail_type': '' + }) + debug(f"从 Neo4j 加载三元组: knowledge_base_id={knowledge_base_id}, 数量={len(triplets)}") + except Exception as e: + error(f"检索三元组失败: knowledge_base_id={knowledge_base_id}, 错误: {str(e)}") + return { + "status": "error", + "message": f"检索三元组失败: {str(e)}", + "triplets": [], + "timing": timing_stats, + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 + } + timing_stats["triplet_query"] = time.time() - triplet_query_start + debug(f"Neo4j 三元组查询耗时: {timing_stats['triplet_query']:.3f} 秒") + + if not triplets: + debug(f"知识库 knowledge_base_id={knowledge_base_id} 无匹配三元组") + return { + "status": "success", + "message": f"知识库 knowledge_base_id={knowledge_base_id} 无匹配三元组", + "triplets": [], + "timing": timing_stats, + "collection_name": "neo4j", + "document_id": "", + "status_code": 200 + } + + embedding_start = time.time() + texts_to_embed = query_entities + [t['head'] for t in triplets] + [t['tail'] for t in triplets] + embeddings = await self._get_embeddings(texts_to_embed) + entity_vectors = {entity: embeddings[i] for i, entity in enumerate(query_entities)} + head_vectors = {t['head']: embeddings[len(query_entities) + i] for i, t in enumerate(triplets)} + tail_vectors = {t['tail']: embeddings[len(query_entities) + len(triplets) + i] for i, t in enumerate(triplets)} + debug(f"成功获取 {len(embeddings)} 个嵌入向量（{len(query_entities)} entities + {len(triplets)} heads + {len(triplets)} tails）") + timing_stats["embedding"] = time.time() - embedding_start + debug(f"嵌入向量生成耗时: {timing_stats['embedding']:.3f} 秒") + + similarity_start = time.time() + for entity in query_entities: + entity_vec = entity_vectors[entity] + for d_triplet in triplets: + d_head_vec = head_vectors[d_triplet['head']] + d_tail_vec = tail_vectors[d_triplet['tail']] + head_similarity = 1 - cosine(entity_vec, d_head_vec) + tail_similarity = 1 - cosine(entity_vec, d_tail_vec) + if head_similarity >= ENTITY_SIMILARITY_THRESHOLD or tail_similarity >= ENTITY_SIMILARITY_THRESHOLD: + matched_triplets.append(d_triplet) + debug(f"匹配三元组: {d_triplet['head']} - {d_triplet['type']} - {d_triplet['tail']} " + f"(entity={entity}, head_sim={head_similarity:.2f}, tail_sim={tail_similarity:.2f})") + timing_stats["similarity"] = time.time() - similarity_start + debug(f"相似度计算耗时: {timing_stats['similarity']:.3f} 秒") + + unique_matched = [] + seen = set() + for t in matched_triplets: + identifier = (t['head'].lower(), t['type'].lower(), t['tail'].lower()) + if identifier not in seen: + seen.add(identifier) + unique_matched.append(t) + + timing_stats["total_time"] = time.time() - start_time + info(f"找到 {len(unique_matched)} 个匹配的三元组，总耗时: {timing_stats['total_time']:.3f} 秒") + return { + "status": "success", + "message": f"找到 {len(unique_matched)} 个匹配的三元组", + "triplets": unique_matched, + "timing": timing_stats, + "collection_name": "neo4j", + "document_id": "", + "status_code": 200 + } + + except Exception as e: + error(f"匹配三元组失败: {str(e)}") + timing_stats["total_time"] = time.time() - start_time + return { + "status": "error", + "message": f"匹配三元组失败: {str(e)}", + "triplets": [], + "timing": timing_stats, + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 + } + +connection_register('Neo4j', Neo4jConnection) +info("Neo4jconnection registered") \ No newline at end of file diff --git a/llmengine/neo4j.py b/llmengine/neo4j.py new file mode 100644 index 0000000..2d1d829 --- /dev/null +++ b/llmengine/neo4j.py @@ -0,0 +1,355 @@ +import argparse +import os +from aiohttp import web +from llmengine.db_neo4j import Neo4jConnection +from llmengine.base_db import connection_register, get_connection_class +from appPublic.registerfunction import RegisterFunction +from appPublic.log import debug, error, info +from ahserver.serverenv import ServerEnv +from ahserver.webapp import webserver +import json + +helptext = """Neo4j Connection Service API: + +1. Initialize Endpoint: +path: /v1/initialize +method: POST +headers: {"Content-Type": "application/json"} +data: {} +response: +- Success: HTTP 200, { + "status": "success", + "message": "Neo4j 服务已初始化", + "collection_name": "neo4j", + "document_id": "", + "status_code": 200 +} +- Error: HTTP 400, { + "status": "error", + "message": "", + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 +} + +2. Insert Triples Endpoint: +path: /v1/inserttriples +method: POST +headers: {"Content-Type": "application/json"} +data: { + "triples": [ + {"head": "entity1", "head_type": "Person", "type": "related_to", "tail": "entity2", "tail_type": "Organization"}, + ... + ], + "document_id": "uuid", + "knowledge_base_id": "kb123", + "userid": "user123" +} +response: +- Success: HTTP 200, { + "status": "success", + "message": "成功插入 个节点和 个关系", + "nodes_created": , + "rels_created": , + "collection_name": "neo4j", + "document_id": "", + "status_code": 200 +} +- Error: HTTP 400, { + "status": "error", + "message": "", + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 +} + +3. Delete Document Endpoint: +path: /v1/deletedocument +method: POST +headers: {"Content-Type": "application/json"} +data: { + "document_id": "uuid" +} +response: +- Success: HTTP 200, { + "status": "success", + "message": "成功删除 个节点和 个关系", + "nodes_deleted": , + "rels_deleted": , + "collection_name": "neo4j", + "document_id": "", + "status_code": 200 +} +- Error: HTTP 400, { + "status": "error", + "message": "", + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 +} + +4. Delete Knowledge Base Endpoint: +path: /v1/deleteknowledgebase +method: POST +headers: {"Content-Type": "application/json"} +data: { + "userid": "user123", + "knowledge_base_id": "kb123" +} +response: +- Success: HTTP 200, { + "status": "success", + "message": "成功删除 个节点和 个关系", + "nodes_deleted": , + "rels_deleted": , + "collection_name": "neo4j", + "document_id": "", + "status_code": 200 +} +- Error: HTTP 400, { + "status": "error", + "message": "", + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 +} + +5. Match Triplets Endpoint: +path: /v1/matchtriplets +method: POST +headers: {"Content-Type": "application/json"} +data: { + "query": "query text", + "query_entities": ["entity1", "entity2"], + "userid": "user123", + "knowledge_base_id": "kb123" +} +response: +- Success: HTTP 200, { + "status": "success", + "message": "找到 个匹配的三元组", + "triplets": [ + {"head": "entity1", "type": "related_to", "tail": "entity2", "head_type": "", "tail_type": ""}, + ... + ], + "timing": { + "neo4j_connect": , + "entity_match": , + "triplet_query": , + "embedding": , + "similarity": , + "total_time": + }, + "collection_name": "neo4j", + "document_id": "", + "status_code": 200 +} +- Error: HTTP 400, { + "status": "error", + "message": "", + "triplets": [], + "timing": {}, + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 +} + +6. Connection Endpoint: +path: /v1/connection +method: POST +headers: {"Content-Type": "application/json"} +data: { + "action": "initialize|insert_triples|delete_document|delete_knowledge_base|match_triplets", + "params": {...} +} +response: +- Success: HTTP 200, {"status": "success", ...} +- Error: HTTP 400, {"status": "error", "message": "", "collection_name": "neo4j", "document_id": "", "status_code": 400} + +7. Docs Endpoint: +path: /docs +method: GET +response: This help text +""" + +def init(): + rf = RegisterFunction() + rf.register('initialize', initialize) + rf.register('inserttriples', insert_triples) + rf.register('deletedocument', delete_document) + rf.register('deleteknowledgebase', delete_knowledge_base) + rf.register('matchtriplets', match_triplets) + rf.register('connection', handle_connection) + rf.register('docs', docs) + +async def docs(request, params_kw, *params, **kw): + return web.Response(text=helptext, content_type='text/plain') + +async def initialize(request, params_kw, *params, **kw): + debug(f'Received initialize params: {params_kw=}') + se = ServerEnv() + engine = se.engine + debug(f'Engine: {engine}') + if engine is None or not isinstance(engine, Neo4jConnection): + error("Neo4jConnection not initialized") + return web.json_response({ + "status": "error", + "message": "Neo4j 服务未启动", + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 + }, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=400) + try: + result = await engine.handle_connection("initialize", params_kw) + debug(f'Initialize result: {result=}') + status = 200 if result.get("status") == "success" else 400 + return web.json_response(result, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=status) + except Exception as e: + error(f'初始化失败: {str(e)}') + return web.json_response({ + "status": "error", + "message": str(e), + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 + }, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=400) + +async def insert_triples(request, params_kw, *params, **kw): + debug(f'Received insert_triples params: {params_kw=}') + se = ServerEnv() + engine = se.engine + try: + required_fields = ['triples', 'document_id', 'knowledge_base_id', 'userid'] + missing_fields = [field for field in required_fields if field not in params_kw or not params_kw[field]] + if missing_fields: + raise ValueError(f"缺少必填字段: {', '.join(missing_fields)}") + result = await engine.handle_connection("insert_triples", params_kw) + debug(f'Insert triples result: {result=}') + status = 200 if result.get("status") == "success" else 400 + return web.json_response(result, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=status) + except Exception as e: + error(f'插入三元组失败: {str(e)}') + return web.json_response({ + "status": "error", + "message": str(e), + "collection_name": "neo4j", + "document_id": params_kw.get("document_id", ""), + "status_code": 400 + }, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=400) + +async def delete_document(request, params_kw, *params, **kw): + debug(f'Received delete_document params: {params_kw=}') + se = ServerEnv() + engine = se.engine + try: + if not params_kw.get('document_id'): + raise ValueError("document_id 不能为空") + result = await engine.handle_connection("delete_document", params_kw) + debug(f'Delete document result: {result=}') + status = 200 if result.get("status") == "success" else 400 + return web.json_response(result, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=status) + except Exception as e: + error(f'删除文档失败: {str(e)}') + return web.json_response({ + "status": "error", + "message": str(e), + "collection_name": "neo4j", + "document_id": params_kw.get("document_id", ""), + "status_code": 400 + }, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=400) + +async def delete_knowledge_base(request, params_kw, *params, **kw): + debug(f'Received delete_knowledge_base params: {params_kw=}') + se = ServerEnv() + engine = se.engine + try: + required_fields = ['userid', 'knowledge_base_id'] + missing_fields = [field for field in required_fields if field not in params_kw or not params_kw[field]] + if missing_fields: + raise ValueError(f"缺少必填字段: {', '.join(missing_fields)}") + result = await engine.handle_connection("delete_knowledge_base", params_kw) + debug(f'Delete knowledge base result: {result=}') + status = 200 if result.get("status") == "success" else 400 + return web.json_response(result, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=status) + except Exception as e: + error(f'删除知识库失败: {str(e)}') + return web.json_response({ + "status": "error", + "message": str(e), + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 + }, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=400) + +async def match_triplets(request, params_kw, *params, **kw): + debug(f'Received match_triplets params: {params_kw=}') + se = ServerEnv() + engine = se.engine + try: + required_fields = ['query', 'query_entities', 'userid', 'knowledge_base_id'] + missing_fields = [field for field in required_fields if field not in params_kw or not params_kw[field]] + if missing_fields: + raise ValueError(f"缺少必填字段: {', '.join(missing_fields)}") + result = await engine.handle_connection("match_triplets", params_kw) + debug(f'Match triplets result: {result=}') + status = 200 if result.get("status") == "success" else 400 + return web.json_response(result, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=status) + except Exception as e: + error(f'匹配三元组失败: {str(e)}') + return web.json_response({ + "status": "error", + "message": str(e), + "triplets": [], + "timing": {}, + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 + }, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=400) + +async def handle_connection(request, params_kw, *params, **kw): + debug(f'Received connection params: {params_kw=}') + se = ServerEnv() + engine = se.engine + try: + data = await request.json() + action = data.get('action') + if not action: + debug(f'action 未提供') + return web.json_response({ + "status": "error", + "message": "action 参数未提供", + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 + }, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=400) + result = await engine.handle_connection(action, data.get('params', {})) + debug(f'Connection result: {result=}') + status = 200 if result.get("status") == "success" else 400 + return web.json_response(result, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=status) + except Exception as e: + error(f'处理连接操作失败: {str(e)}') + return web.json_response({ + "status": "error", + "message": str(e), + "collection_name": "neo4j", + "document_id": "", + "status_code": 400 + }, dumps=lambda obj: json.dumps(obj, ensure_ascii=False), status=400) + +def main(): + parser = argparse.ArgumentParser(prog="Neo4j Connection Service") + parser.add_argument('-w', '--workdir', help="Working directory") + parser.add_argument('-p', '--port', default='8885', help="Port to run the server on") + parser.add_argument('connection_path', help="Connection class path (e.g., Neo4j)") + args = parser.parse_args() + debug(f"Arguments: {args}") + Klass = get_connection_class(args.connection_path) + se = ServerEnv() + se.engine = Klass() + workdir = args.workdir or os.getcwd() + port = args.port + debug(f'{args=}') + webserver(init, workdir, port) + +if __name__ == '__main__': + main() \ No newline at end of file diff --git a/test/bgererank/=1.3.3 b/test/bgererank/=1.3.3 deleted file mode 100644 index c7a8c32..0000000 --- a/test/bgererank/=1.3.3 +++ /dev/null @@ -1,82 +0,0 @@ -Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple -Requirement already satisfied: FlagEmbedding in /share/vllm-0.8.5/lib/python3.10/site-packages (1.3.5) -Requirement already satisfied: torch>=1.6.0 in /share/vllm-0.8.5/lib/python3.10/site-packages (from FlagEmbedding) (2.6.0) -Requirement already satisfied: transformers>=4.44.2 in /share/vllm-0.8.5/lib/python3.10/site-packages (from FlagEmbedding) (4.51.3) -Requirement already satisfied: datasets>=2.19.0 in /share/vllm-0.8.5/lib/python3.10/site-packages (from FlagEmbedding) (3.6.0) -Requirement already satisfied: accelerate>=0.20.1 in 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/share/vllm-0.8.5/lib/python3.10/site-packages (from yarl<2.0,>=1.12.0->aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets>=2.19.0->FlagEmbedding) (0.3.1) diff --git a/test/bgererank/entities.service b/test/bgererank/entities.service deleted file mode 100644 index bf9fbb6..0000000 --- a/test/bgererank/entities.service +++ /dev/null @@ -1,14 +0,0 @@ -[Unit] -Wants=systemd-networkd.service - -[Service] -WorkingDirectory=/share/run/entities -ExecStart=/share/run/entities/start.sh -ExecStop=/share/run/entities/stop.sh -StandardOutput=append:/var/log/entities/entities.log -StandardError=append:/var/log/entities/entities.log -SyslogIdentifier=entities - -[Install] -WantedBy=multi-user.target - diff --git a/test/bgererank/start.sh b/test/bgererank/start.sh deleted file mode 100755 index d9f515a..0000000 --- a/test/bgererank/start.sh +++ /dev/null @@ -1,3 +0,0 @@ -#!/bin/bash - -/share/vllm-0.8.5/bin/python -m llmengine.bgererank -p 8887 /share/models/BAAI/bge-reranker-v2-m3 diff --git a/test/bgererank/stop.sh b/test/bgererank/stop.sh deleted file mode 100644 index 9ceecd4..0000000 --- a/test/bgererank/stop.sh +++ /dev/null @@ -1,10 +0,0 @@ -#!/bin/bash - -# 查找并终止运行在端口 8887 上的进程 -pid=$(lsof -t -i:8887) -if [ -n "$pid" ]; then - echo "终止进程: $pid" - kill -9 $pid -else - echo "未找到运行在端口 8887 上的进程" -fi \ No newline at end of file diff --git a/test/bgererank/conf/config.json b/test/neo4j/conf/config.json similarity index 50% rename from test/bgererank/conf/config.json rename to test/neo4j/conf/config.json index 78cc86c..7f3ef15 100644 --- a/test/bgererank/conf/config.json +++ b/test/neo4j/conf/config.json @@ -1,5 +1,10 @@ { "filesroot": "$[workdir]$/files", + "neo4j": { + "uri": "bolt://10.18.34.18:7687", + "user": "neo4j", + "password": "261229..wmh" + }, "logger": { "name": "llmengine", "levelname": "info", @@ -11,7 +16,7 @@ ], "client_max_size": 10000, "host": "0.0.0.0", - "port": 8887, + "port": 8885, "coding": "utf-8", "indexes": [ "index.html", @@ -19,11 +24,35 @@ ], "startswiths": [ { - "leading": "/v1/bgererank", - "registerfunction": "bgererank" + "leading": "/idfile", + "registerfunction": "idfile" }, { - "leading": "/v1/docs", + "leading": "/v1/connection", + "registerfunction": "connection" + }, + { + "leading": "/v1/initialize", + "registerfunction": "initialize" + }, + { + "leading": "/v1/inserttriples", + "registerfunction": "inserttriples" + }, + { + "leading": "/v1/deletedocument", + "registerfunction": "deletedocument" + }, + { + "leading": "/v1/deleteknowledgebase", + "registerfunction": "deleteknowledgebase" + }, + { + "leading": "/v1/matchtriplets", + "registerfunction": "matchtriplets" + }, + { + "leading": "/docs", "registerfunction": "docs" } ], @@ -44,4 +73,4 @@ "url": "redis://127.0.0.1:6379" } } -} \ No newline at end of file +} diff --git a/test/bgererank/logs/llmengine.log b/test/neo4j/logs/llmengine.log similarity index 100% rename from test/bgererank/logs/llmengine.log rename to test/neo4j/logs/llmengine.log diff --git a/test/neo4j/neo4j.service b/test/neo4j/neo4j.service new file mode 100644 index 0000000..9558128 --- /dev/null +++ b/test/neo4j/neo4j.service @@ -0,0 +1,15 @@ +[Unit] +Wants=systemd-networkd.service + +[Service] +Type=forking +WorkingDirectory=/share/run/neo4j +ExecStart=/share/run/neo4j/start.sh +ExecStop=/share/run/neo4j/stop.sh +StandardOutput=append:/var/log/neo4j/neo4j.log +StandardError=append:/var/log/neo4j/neo4j.log +SyslogIdentifier=/share/run/neo4j +TimeoutStartSec=300 + +[Install] +WantedBy=multi-user.target diff --git a/test/neo4j/start.sh b/test/neo4j/start.sh new file mode 100755 index 0000000..abfc3c3 --- /dev/null +++ b/test/neo4j/start.sh @@ -0,0 +1,2 @@ +#!/bin/bash +CUDA_VISIBLE_DEVICES=7 /share/vllm-0.8.5/bin/python -m llmengine.neo4j -p 8885 Neo4j & diff --git a/test/neo4j/stop.sh b/test/neo4j/stop.sh new file mode 100755 index 0000000..f9d5203 --- /dev/null +++ b/test/neo4j/stop.sh @@ -0,0 +1,12 @@ +#!/bin/bash + +PORT=8885 +PID=$(lsof -t -i:$PORT) + +if [ -n "$PID" ]; then + echo "找到端口 $PORT 的进程: PID=$PID" + kill -9 $PID + echo "已终止端口 $PORT 的进程" +else + echo "未找到端口 $PORT 的进程" +fi \ No newline at end of file