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# conda activate rag
# pip install py2neo pyvis
from py2neo import Graph
from pyvis . network import Network
from Config import Config
# 连接Neo4j
graph = Graph ( Config . NEO4J_URI , auth = Config . NEO4J_AUTH )
# 修改后的查询语句，
query = """
MATCH p=()-[r:INCLUDES]->()
RETURN p LIMIT 250
"""
data = graph . run ( query ) . data ( )
# 创建网络图
net = Network ( height = " 750px " , width = " 100 % " , notebook = True , cdn_resources = ' in_line ' )
# 添加节点和边
for item in data :
# 提取起始节点
start_node = item [ ' p ' ] . start_node
# 提取结束节点
end_node = item [ ' p ' ] . end_node
net . add_node ( start_node . identity ,
label = start_node [ ' name ' ] ,
title = start_node . get ( ' description ' , ' ' ) ,
group = list ( start_node . labels ) [ 0 ] )
net . add_node ( end_node . identity ,
label = end_node [ ' name ' ] ,
title = end_node . get ( ' description ' , ' ' ) ,
group = list ( end_node . labels ) [ 0 ] )
net . add_edge ( start_node . identity ,
end_node . identity ,
title = " INCLUDES " )
# 生成HTML文件
with open ( " knowledge_graph.html " , " w " , encoding = ' utf-8 ' ) as f :
f . write ( net . generate_html ( ) )
# 打开HTML文件
import webbrowser
webbrowser . open ( " knowledge_graph.html " )
