# 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)

# 查询所有节点和关系
query = """
MATCH (n)-[r]->(m)
RETURN n, r, m
"""
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:
    net.add_node(item['n'].identity, 
                label=item['n']['name'],
                title=item['n'].get('description', ''),
                group=item['n'].labels[0])
    net.add_node(item['m'].identity, 
                label=item['m']['name'],
                title=item['m'].get('description', ''),
                group=item['m'].labels[0])
    net.add_edge(item['n'].identity, 
                item['m'].identity, 
                title=type(item['r']).__name__)

# 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")