首次提交：上传本地文件夹
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ruxia
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import os
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from neo4j import GraphDatabase
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from typing import List, Dict, Any, Optional
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class KnowledgeGraphQuerier:
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def __init__(self, uri, auth):
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"""
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初始化知识图谱查询器
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参数:
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uri: Neo4j数据库URI
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auth: Neo4j认证信息，格式为(username, password)
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"""
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self.uri = uri
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self.auth = auth
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self.driver = GraphDatabase.driver(uri, auth=auth)
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# 初始化session属性
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self.session = self.driver.session()
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print(f"已连接到Neo4j数据库: {uri}")
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def close(self):
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"""关闭数据库连接"""
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if hasattr(self, 'session') and self.session:
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self.session.close()
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if hasattr(self, 'driver') and self.driver:
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self.driver.close()
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print("已关闭Neo4j数据库连接")
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def get_node_by_name(self, name: str, node_type: Optional[str] = None) -> List[Dict[str, Any]]:
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"""
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通过名称查询节点
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参数:
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name: 节点名称
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node_type: 节点类型（可选）
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返回:
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节点列表
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"""
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with self.driver.session() as session:
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if node_type:
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query = f"""
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MATCH (n:{node_type})
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WHERE n.original_name = $name OR n.display_name = $name
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RETURN n
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"""
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else:
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query = """
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MATCH (n)
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WHERE n.original_name = $name OR n.display_name = $name
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RETURN n
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"""
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result = session.run(query, name=name)
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nodes = []
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for record in result:
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node = record["n"]
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nodes.append(dict(node))
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return nodes
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def get_related_nodes(self, node_name: str, relationship_type: Optional[str] = None,
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max_depth: int = 2) -> List[Dict[str, Any]]:
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"""
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获取与指定节点相关的节点
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参数:
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node_name: 节点名称
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relationship_type: 关系类型（可选）
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max_depth: 最大深度
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返回:
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相关节点列表
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"""
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with self.driver.session() as session:
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if relationship_type:
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query = f"""
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MATCH (n)-[r:{relationship_type}*1..{max_depth}]-(related)
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WHERE n.original_name = $name OR n.display_name = $name
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RETURN related
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"""
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else:
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query = f"""
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MATCH (n)-[r*1..{max_depth}]-(related)
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WHERE n.original_name = $name OR n.display_name = $name
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RETURN related
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"""
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result = session.run(query, name=node_name)
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related_nodes = []
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for record in result:
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node = record["related"]
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related_nodes.append(dict(node))
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return related_nodes
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def search_by_keyword(self, keyword: str) -> List[Dict[str, Any]]:
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"""
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通过关键词搜索知识图谱
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参数:
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keyword: 搜索关键词
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返回:
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匹配的节点列表
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"""
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# 使用简化的查询，不包含路径查询
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query = """
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MATCH (n)
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WHERE n.name CONTAINS $keyword
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OR n.display_name CONTAINS $keyword
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OR n.original_name CONTAINS $keyword
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OR n.描述 CONTAINS $keyword
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RETURN n
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LIMIT 50
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"""
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result = self.session.run(query, keyword=keyword)
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nodes = []
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for record in result:
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node = dict(record["n"])
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node["labels"] = list(record["n"].labels)
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nodes.append(node)
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return nodes
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def get_path_between_nodes(self, start_name: str, end_name: str) -> List[List[Dict[str, Any]]]:
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"""
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获取两个节点之间的路径
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参数:
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start_name: 起始节点名称
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end_name: 结束节点名称
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返回:
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路径列表，每个路径是节点字典的列表
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"""
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with self.driver.session() as session:
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query = """
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MATCH p = shortestPath((a)-[*]-(b))
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WHERE (a.original_name = $start_name OR a.display_name = $start_name)
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AND (b.original_name = $end_name OR b.display_name = $end_name)
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RETURN p
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"""
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result = session.run(query, start_name=start_name, end_name=end_name)
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paths = []
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for record in result:
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path = record["p"]
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path_nodes = []
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for node in path.nodes:
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path_nodes.append(dict(node))
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paths.append(path_nodes)
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return paths
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def get_function_details(self, function_name: str) -> Dict[str, Any]:
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"""
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获取功能详情
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参数:
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function_name: 功能名称
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返回:
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功能详情字典，包含功能描述和路径
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"""
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with self.driver.session() as session:
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query = """
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MATCH (n:功能名称 {original_name: $name})
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RETURN n
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"""
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result = session.run(query, name=function_name)
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record = result.single()
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if record:
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node = dict(record["n"])
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# 获取功能的完整路径
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path_query = """
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MATCH p = (root:软件)-[*]->(func:功能名称 {original_name: $name})
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RETURN p
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"""
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path_result = session.run(path_query, name=function_name)
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path_record = path_result.single()
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if path_record:
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path = path_record["p"]
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node_path = []
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for path_node in path.nodes:
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node_path.append(dict(path_node).get("original_name", ""))
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node["path"] = " > ".join(filter(None, node_path))
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return node
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return {}
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