Add initial implementation of txt2graph tool for knowledge graph generation

- Created a new Streamlit application for visualizing knowledge graphs.
- Implemented text extraction from PDF, Markdown, and TXT files.
- Developed graph building logic using Zep Cloud API.
- Added support for custom entity types and relationships.
- Included interactive HTML visualization for generated graphs.
- Updated .gitignore to include new directories and files.
- Added example environment configuration file (.env.example) for API key setup.
- Created README.md with installation and usage instructions.
- Introduced various utility scripts and styles for enhanced functionality.
This commit is contained in:
666ghj 2025-11-28 14:07:42 +08:00
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.idea .idea
.pytest_cache .pytest_cache
.pytest_cache .pytest_cache
.cursor/
.mydoc/ mydoc/
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# Zep Cloud API Key
# 从 https://app.getzep.com 获取
ZEP_API_KEY=your_zep_api_key_here

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# txt2graph
将文本文件PDF/Markdown/TXT转换为知识图谱的工具。
## 功能特点
- 支持多种文件格式PDF、Markdown、TXT
- 基于 Zep Cloud 的知识图谱构建
- 自动提取真实存在的实体(人物、公司、组织、地点、产品、事件、媒体)
- 交互式图谱可视化界面
- 实体和关系的详细展示
## 实体类型
本工具只提取现实生活中真实存在的、可以有行动的实体:
| 类型 | 说明 | 示例 |
|------|------|------|
| Person | 真实的人物 | 马化腾、Elon Musk |
| Company | 注册的公司 | 腾讯、Apple Inc. |
| Organization | 组织机构 | 武汉大学、联合国 |
| Location | 地理位置 | 北京、硅谷 |
| Product | 具体产品/服务 | iPhone、微信 |
| Event | 真实事件 | 2024年巴黎奥运会 |
| Media | 媒体机构 | 人民日报、CNN |
## 安装
### 1. 激活conda环境
```bash
conda activate MiroFish
```
### 2. 安装依赖
```bash
cd txt2graph
pip install -r requirements.txt
```
### 3. 配置环境变量
复制 `.env.example``.env` 并填入你的 Zep API Key
```bash
cp .env.example .env
# 编辑 .env 文件,填入 ZEP_API_KEY
```
获取 API Key: https://app.getzep.com
## 使用方法
### 方式1: Web界面推荐
启动 Streamlit 应用:
```bash
streamlit run app.py
```
然后在浏览器中打开显示的URL通常是 http://localhost:8501
### 方式2: 命令行
```python
from text_extractor import extract_text
from graph_builder import build_graph_from_text
# 从文件提取文本
text = extract_text("your_document.pdf")
# 构建知识图谱
graph_data = build_graph_from_text(
text=text,
graph_name="我的知识图谱",
progress_callback=print
)
# 查看结果
print(f"节点数: {len(graph_data.nodes)}")
print(f"边数: {len(graph_data.edges)}")
```
## 项目结构
```
txt2graph/
├── app.py # Streamlit Web应用
├── text_extractor.py # 文本提取模块
├── graph_builder.py # 图谱构建模块
├── ontology.py # 实体类型定义
├── requirements.txt # 依赖列表
├── .env.example # 环境变量示例
└── README.md # 说明文档
```
## 注意事项
1. **处理时间**:知识图谱构建可能需要几分钟,取决于文本长度
2. **API限制**Zep Cloud 有API调用限制大文件建议分批处理
3. **文本质量**:输入文本的质量直接影响实体提取效果
4. **费用**Zep Cloud 可能会产生API调用费用请查看其定价
## 技术栈
- [Zep Cloud](https://www.getzep.com/) - 知识图谱服务
- [Streamlit](https://streamlit.io/) - Web界面框架
- [PyVis](https://pyvis.readthedocs.io/) - 图可视化
- [PyMuPDF](https://pymupdf.readthedocs.io/) - PDF处理

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"""
txt2graph 可视化界面
基于Streamlit和PyVis实现知识图谱可视化
"""
import os
import tempfile
import streamlit as st
from pathlib import Path
from pyvis.network import Network
import streamlit.components.v1 as components
from dotenv import load_dotenv
load_dotenv()
from text_extractor import extract_text, split_text_into_chunks
from graph_builder import ZepGraphBuilder, GraphData
# 页面配置
st.set_page_config(
page_title="txt2graph - 知识图谱生成器",
page_icon="🕸️",
layout="wide",
initial_sidebar_state="expanded"
)
# 自定义CSS样式
st.markdown("""
<style>
@import url('https://fonts.googleapis.com/css2?family=Noto+Sans+SC:wght@400;500;700&family=JetBrains+Mono&display=swap');
.main {
font-family: 'Noto Sans SC', sans-serif;
}
.stTitle {
font-weight: 700 !important;
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
background-clip: text;
}
.stats-card {
background: linear-gradient(135deg, #1a1a2e 0%, #16213e 100%);
border-radius: 12px;
padding: 20px;
margin: 10px 0;
border: 1px solid rgba(102, 126, 234, 0.3);
}
.stats-number {
font-size: 2.5rem;
font-weight: 700;
color: #667eea;
font-family: 'JetBrains Mono', monospace;
}
.stats-label {
font-size: 0.9rem;
color: #a0a0a0;
text-transform: uppercase;
letter-spacing: 1px;
}
.entity-tag {
display: inline-block;
padding: 4px 12px;
border-radius: 20px;
font-size: 0.8rem;
margin: 2px;
font-weight: 500;
}
.entity-Person { background: rgba(255, 107, 107, 0.2); color: #ff6b6b; border: 1px solid #ff6b6b; }
.entity-Company { background: rgba(78, 205, 196, 0.2); color: #4ecdc4; border: 1px solid #4ecdc4; }
.entity-Organization { background: rgba(69, 183, 209, 0.2); color: #45b7d1; border: 1px solid #45b7d1; }
.entity-Location { background: rgba(150, 206, 180, 0.2); color: #96ceb4; border: 1px solid #96ceb4; }
.entity-Product { background: rgba(255, 238, 173, 0.2); color: #ffeead; border: 1px solid #ffeead; }
.entity-Event { background: rgba(220, 198, 224, 0.2); color: #dcc6e0; border: 1px solid #dcc6e0; }
.entity-Media { background: rgba(255, 183, 77, 0.2); color: #ffb74d; border: 1px solid #ffb74d; }
.sidebar .stButton > button {
width: 100%;
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white;
border: none;
padding: 12px 24px;
border-radius: 8px;
font-weight: 600;
transition: all 0.3s ease;
}
.sidebar .stButton > button:hover {
transform: translateY(-2px);
box-shadow: 0 4px 20px rgba(102, 126, 234, 0.4);
}
</style>
""", unsafe_allow_html=True)
# 实体类型对应的颜色
ENTITY_COLORS = {
"Person": "#ff6b6b",
"Company": "#4ecdc4",
"Organization": "#45b7d1",
"Location": "#96ceb4",
"Product": "#ffeead",
"Event": "#dcc6e0",
"Media": "#ffb74d",
}
def create_pyvis_graph(graph_data: GraphData) -> str:
"""
创建PyVis图并返回HTML
"""
# 创建网络图
net = Network(
height="700px",
width="100%",
bgcolor="#0e1117",
font_color="white",
directed=True,
select_menu=True,
filter_menu=True,
)
# 配置物理引擎
net.set_options("""
{
"nodes": {
"font": {
"size": 14,
"face": "Noto Sans SC, Arial"
},
"borderWidth": 2,
"shadow": true
},
"edges": {
"color": {
"inherit": false,
"color": "#555555",
"highlight": "#667eea"
},
"arrows": {
"to": {
"enabled": true,
"scaleFactor": 0.5
}
},
"smooth": {
"type": "continuous",
"roundness": 0.2
},
"font": {
"size": 10,
"color": "#888888",
"face": "Noto Sans SC, Arial"
}
},
"physics": {
"enabled": true,
"barnesHut": {
"gravitationalConstant": -5000,
"centralGravity": 0.3,
"springLength": 150,
"springConstant": 0.04,
"damping": 0.09
},
"stabilization": {
"enabled": true,
"iterations": 200
}
},
"interaction": {
"hover": true,
"tooltipDelay": 100,
"navigationButtons": true,
"keyboard": true
}
}
""")
# 构建节点UUID到名称的映射
node_map = {node.uuid: node for node in graph_data.nodes}
# 添加节点
for node in graph_data.nodes:
# 确定节点类型和颜色
node_type = node.labels[0] if node.labels else "Unknown"
color = ENTITY_COLORS.get(node_type, "#888888")
# 构建工具提示
title = f"<b>{node.name}</b><br>"
title += f"<i>类型: {node_type}</i><br><br>"
if node.summary:
title += f"{node.summary[:200]}{'...' if len(node.summary) > 200 else ''}"
# 根据节点类型调整大小
size = 25 if node_type == "Person" else 30 if node_type in ["Company", "Organization"] else 20
net.add_node(
node.uuid,
label=node.name,
title=title,
color=color,
size=size,
shape="dot",
)
# 添加边
for edge in graph_data.edges:
if edge.source_node_uuid in node_map and edge.target_node_uuid in node_map:
# 构建边的工具提示
title = edge.fact if edge.fact else edge.name
net.add_edge(
edge.source_node_uuid,
edge.target_node_uuid,
title=title,
label=edge.name[:20] if edge.name else "",
)
# 生成HTML
with tempfile.NamedTemporaryFile(mode='w', suffix='.html', delete=False, encoding='utf-8') as f:
net.save_graph(f.name)
with open(f.name, 'r', encoding='utf-8') as html_file:
html_content = html_file.read()
os.unlink(f.name)
return html_content
def display_stats(graph_data: GraphData):
"""显示图谱统计信息"""
col1, col2, col3 = st.columns(3)
with col1:
st.markdown(f"""
<div class="stats-card">
<div class="stats-number">{len(graph_data.nodes)}</div>
<div class="stats-label">实体节点</div>
</div>
""", unsafe_allow_html=True)
with col2:
st.markdown(f"""
<div class="stats-card">
<div class="stats-number">{len(graph_data.edges)}</div>
<div class="stats-label">关系边</div>
</div>
""", unsafe_allow_html=True)
# 统计实体类型分布
type_counts = {}
for node in graph_data.nodes:
node_type = node.labels[0] if node.labels else "Unknown"
type_counts[node_type] = type_counts.get(node_type, 0) + 1
with col3:
st.markdown(f"""
<div class="stats-card">
<div class="stats-number">{len(type_counts)}</div>
<div class="stats-label">实体类型</div>
</div>
""", unsafe_allow_html=True)
def display_entity_list(graph_data: GraphData):
"""显示实体列表"""
st.subheader("实体列表")
# 按类型分组
entities_by_type = {}
for node in graph_data.nodes:
node_type = node.labels[0] if node.labels else "Unknown"
if node_type not in entities_by_type:
entities_by_type[node_type] = []
entities_by_type[node_type].append(node)
# 创建标签页
if entities_by_type:
tabs = st.tabs(list(entities_by_type.keys()))
for tab, (entity_type, entities) in zip(tabs, entities_by_type.items()):
with tab:
for entity in entities:
with st.expander(f"{entity.name}", expanded=False):
if entity.summary:
st.write(entity.summary)
if entity.attributes:
st.json(entity.attributes)
def main():
# 标题
st.title("txt2graph")
st.markdown("*将文本转化为知识图谱*")
# 侧边栏
with st.sidebar:
st.header("配置")
# API Key
api_key = st.text_input(
"Zep API Key",
type="password",
value=os.environ.get("ZEP_API_KEY", ""),
help="从 https://app.getzep.com 获取API Key"
)
if api_key:
os.environ["ZEP_API_KEY"] = api_key
st.divider()
# 文件上传
st.header("上传文件")
uploaded_file = st.file_uploader(
"支持 .txt, .md, .pdf 文件",
type=["txt", "md", "pdf"],
help="上传要转换为知识图谱的文本文件"
)
# 或者直接输入文本
st.divider()
st.header("或直接输入文本")
text_input = st.text_area(
"输入文本内容",
height=150,
placeholder="在此输入或粘贴文本..."
)
st.divider()
# 高级设置
with st.expander("高级设置"):
chunk_size = st.slider(
"文本分块大小",
min_value=500,
max_value=4000,
value=2000,
step=500,
help="较小的块处理更稳定,较大的块包含更多上下文"
)
graph_name = st.text_input(
"图谱名称",
value="Knowledge Graph",
help="为生成的图谱命名"
)
st.divider()
# 生成按钮
generate_btn = st.button("生成知识图谱", type="primary", use_container_width=True)
# 主内容区
if "graph_data" not in st.session_state:
st.session_state.graph_data = None
if generate_btn:
if not api_key:
st.error("请先配置 Zep API Key")
return
# 获取文本内容
text_content = None
if uploaded_file:
with st.spinner("正在提取文本..."):
# 保存上传的文件到临时位置
with tempfile.NamedTemporaryFile(delete=False, suffix=Path(uploaded_file.name).suffix) as tmp:
tmp.write(uploaded_file.getvalue())
tmp_path = tmp.name
try:
text_content = extract_text(tmp_path)
finally:
os.unlink(tmp_path)
elif text_input:
text_content = text_input
else:
st.warning("请上传文件或输入文本")
return
if text_content:
st.info(f"提取了 {len(text_content)} 个字符的文本")
# 进度显示
progress_bar = st.progress(0)
status_text = st.empty()
try:
# 创建图谱构建器
builder = ZepGraphBuilder(api_key=api_key)
# 创建图谱
status_text.text("创建图谱...")
progress_bar.progress(10)
graph_id = builder.create_graph(name=graph_name)
# 设置本体
status_text.text("配置实体类型...")
progress_bar.progress(20)
builder.set_ontology(graph_id)
# 分块
status_text.text("分割文本...")
progress_bar.progress(30)
chunks = split_text_into_chunks(text_content, max_chunk_size=chunk_size)
st.info(f"文本已分为 {len(chunks)} 个块")
# 添加到图谱
status_text.text("正在发送数据到Zep...")
progress_bar.progress(40)
def update_progress(msg):
status_text.text(msg)
# 分批发送数据
task_ids = builder.add_text_to_graph(
graph_id=graph_id,
text_chunks=chunks,
batch_size=3,
progress_callback=update_progress
)
# 等待处理完成
progress_bar.progress(60)
status_text.text("等待Zep处理数据...")
if task_ids:
builder.wait_for_tasks(
task_ids,
timeout=600,
progress_callback=update_progress
)
# 获取图数据
status_text.text("获取图谱数据...")
progress_bar.progress(90)
st.session_state.graph_data = builder.get_graph_data(graph_id)
st.session_state.graph_id = graph_id
progress_bar.progress(100)
status_text.text("完成!")
st.success(f"知识图谱生成成功! Graph ID: {graph_id}")
except Exception as e:
st.error(f"生成图谱时出错: {str(e)}")
import traceback
st.code(traceback.format_exc())
# 显示图谱
if st.session_state.graph_data:
graph_data = st.session_state.graph_data
# 统计信息
display_stats(graph_data)
st.divider()
# 图谱可视化
st.subheader("知识图谱可视化")
if graph_data.nodes:
with st.spinner("渲染图谱..."):
html_content = create_pyvis_graph(graph_data)
components.html(html_content, height=750, scrolling=True)
else:
st.warning("图谱中没有节点")
st.divider()
# 实体列表
col1, col2 = st.columns([1, 1])
with col1:
display_entity_list(graph_data)
with col2:
st.subheader("关系列表")
if graph_data.edges:
for edge in graph_data.edges[:50]: # 只显示前50条
st.markdown(f"- **{edge.fact}**" if edge.fact else f"- {edge.name}")
if len(graph_data.edges) > 50:
st.caption(f"...还有 {len(graph_data.edges) - 50} 条关系")
else:
st.info("暂无关系数据")
if __name__ == "__main__":
main()

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"""
Zep图谱构建模块
负责与Zep云服务交互构建知识图谱
"""
import os
import time
import uuid
from typing import Optional, Callable
from dataclasses import dataclass
from zep_cloud.client import Zep
from zep_cloud import EpisodeData, EntityEdgeSourceTarget
from ontology import ENTITY_TYPES, EDGE_TYPES
@dataclass
class GraphNode:
"""图节点数据结构"""
uuid: str
name: str
summary: str
labels: list[str]
attributes: dict
@dataclass
class GraphEdge:
"""图边数据结构"""
uuid: str
name: str
fact: str
source_node_uuid: str
target_node_uuid: str
attributes: dict
@dataclass
class GraphData:
"""完整图数据"""
graph_id: str
nodes: list[GraphNode]
edges: list[GraphEdge]
class ZepGraphBuilder:
"""Zep知识图谱构建器"""
def __init__(self, api_key: Optional[str] = None):
"""
初始化图谱构建器
Args:
api_key: Zep API密钥如果不提供则从环境变量ZEP_API_KEY读取
"""
self.api_key = api_key or os.environ.get("ZEP_API_KEY")
if not self.api_key:
raise ValueError("需要提供ZEP_API_KEY可以通过参数传入或设置环境变量")
self.client = Zep(api_key=self.api_key)
def create_graph(self, graph_id: Optional[str] = None, name: str = "Knowledge Graph") -> str:
"""
创建新的图谱
Args:
graph_id: 图谱ID如果不提供则自动生成
name: 图谱名称
Returns:
图谱ID
"""
if graph_id is None:
graph_id = f"graph_{uuid.uuid4().hex[:16]}"
self.client.graph.create(
graph_id=graph_id,
name=name,
description="Knowledge graph generated by txt2graph"
)
return graph_id
def set_ontology(self, graph_id: str):
"""
为图谱设置自定义本体实体和边类型
Args:
graph_id: 图谱ID
"""
# 构建边类型的源目标映射
edge_definitions = {}
# WORKS_FOR: Person -> Organization/Company
edge_definitions["WORKS_FOR"] = (
EDGE_TYPES["WORKS_FOR"],
[
EntityEdgeSourceTarget(source="Person", target="Organization"),
EntityEdgeSourceTarget(source="Person", target="Company"),
]
)
# LOCATED_IN: 多种实体 -> Location
edge_definitions["LOCATED_IN"] = (
EDGE_TYPES["LOCATED_IN"],
[
EntityEdgeSourceTarget(source="Person", target="Location"),
EntityEdgeSourceTarget(source="Organization", target="Location"),
EntityEdgeSourceTarget(source="Company", target="Location"),
EntityEdgeSourceTarget(source="Event", target="Location"),
]
)
# PART_OF: Organization -> Organization, Company -> Company
edge_definitions["PART_OF"] = (
EDGE_TYPES["PART_OF"],
[
EntityEdgeSourceTarget(source="Organization", target="Organization"),
EntityEdgeSourceTarget(source="Company", target="Company"),
]
)
# PRODUCES: Company -> Product
edge_definitions["PRODUCES"] = (
EDGE_TYPES["PRODUCES"],
[
EntityEdgeSourceTarget(source="Company", target="Product"),
EntityEdgeSourceTarget(source="Organization", target="Product"),
]
)
# PARTICIPATES_IN: Person/Organization/Company -> Event
edge_definitions["PARTICIPATES_IN"] = (
EDGE_TYPES["PARTICIPATES_IN"],
[
EntityEdgeSourceTarget(source="Person", target="Event"),
EntityEdgeSourceTarget(source="Organization", target="Event"),
EntityEdgeSourceTarget(source="Company", target="Event"),
]
)
# COLLABORATES: 各种实体之间的合作
edge_definitions["COLLABORATES"] = (
EDGE_TYPES["COLLABORATES"],
[
EntityEdgeSourceTarget(source="Person", target="Person"),
EntityEdgeSourceTarget(source="Company", target="Company"),
EntityEdgeSourceTarget(source="Organization", target="Organization"),
EntityEdgeSourceTarget(source="Company", target="Organization"),
]
)
# COMPETES: 公司之间的竞争
edge_definitions["COMPETES"] = (
EDGE_TYPES["COMPETES"],
[
EntityEdgeSourceTarget(source="Company", target="Company"),
]
)
# REPORTS: Media报道相关实体
edge_definitions["REPORTS"] = (
EDGE_TYPES["REPORTS"],
[
EntityEdgeSourceTarget(source="Media", target="Person"),
EntityEdgeSourceTarget(source="Media", target="Company"),
EntityEdgeSourceTarget(source="Media", target="Organization"),
EntityEdgeSourceTarget(source="Media", target="Event"),
]
)
# 设置本体
self.client.graph.set_ontology(
graph_ids=[graph_id],
entities=ENTITY_TYPES,
edges=edge_definitions,
)
def add_text_to_graph(
self,
graph_id: str,
text_chunks: list[str],
batch_size: int = 3,
progress_callback: Optional[Callable] = None
) -> list[str]:
"""
将文本块分批添加到图谱中
Args:
graph_id: 图谱ID
text_chunks: 文本块列表
batch_size: 每批发送的块数量
progress_callback: 进度回调函数
Returns:
任务ID列表
"""
task_ids = []
total_chunks = len(text_chunks)
# 分批处理
for i in range(0, total_chunks, batch_size):
batch_chunks = text_chunks[i:i + batch_size]
batch_num = i // batch_size + 1
total_batches = (total_chunks + batch_size - 1) // batch_size
if progress_callback:
progress_callback(f"发送第 {batch_num}/{total_batches} 批数据 ({len(batch_chunks)} 块)...")
# 构建episode数据
episodes = [
EpisodeData(data=chunk, type="text")
for chunk in batch_chunks
]
try:
# 批量添加
batch_result = self.client.graph.add_batch(
graph_id=graph_id,
episodes=episodes
)
if batch_result and batch_result[0].task_id:
task_ids.append(batch_result[0].task_id)
# 短暂等待,避免请求过快
time.sleep(1)
except Exception as e:
if progress_callback:
progress_callback(f"批次 {batch_num} 发送失败: {str(e)}")
raise
return task_ids
def wait_for_tasks(
self,
task_ids: list[str],
timeout: int = 600,
progress_callback: Optional[Callable] = None
):
"""
等待所有任务完成
Args:
task_ids: 任务ID列表
timeout: 超时时间
progress_callback: 进度回调
"""
if not task_ids:
return
start_time = time.time()
pending_tasks = set(task_ids)
completed_tasks = set()
while pending_tasks:
if time.time() - start_time > timeout:
if progress_callback:
progress_callback(f"警告: 部分任务超时,已完成 {len(completed_tasks)}/{len(task_ids)}")
break
for task_id in list(pending_tasks):
try:
task = self.client.task.get(task_id=task_id)
if task.status == "completed":
pending_tasks.remove(task_id)
completed_tasks.add(task_id)
elif task.status == "failed":
pending_tasks.remove(task_id)
if progress_callback:
progress_callback(f"任务失败: {task.error}")
except Exception as e:
if progress_callback:
progress_callback(f"检查任务状态出错: {str(e)}")
if pending_tasks:
if progress_callback:
elapsed = int(time.time() - start_time)
progress_callback(f"等待处理中... 已完成 {len(completed_tasks)}/{len(task_ids)} ({elapsed}秒)")
time.sleep(3)
if progress_callback:
progress_callback(f"所有任务处理完成: {len(completed_tasks)}/{len(task_ids)}")
def get_graph_data(self, graph_id: str) -> GraphData:
"""
获取图谱的完整数据
Args:
graph_id: 图谱ID
Returns:
GraphData对象包含所有节点和边
"""
# 获取所有节点
raw_nodes = self.client.graph.node.get_by_graph_id(graph_id=graph_id)
nodes = [
GraphNode(
uuid=node.uuid_,
name=node.name,
summary=node.summary or "",
labels=node.labels or [],
attributes=node.attributes or {}
)
for node in raw_nodes
]
# 获取所有边
raw_edges = self.client.graph.edge.get_by_graph_id(graph_id=graph_id)
edges = [
GraphEdge(
uuid=edge.uuid_,
name=edge.name or "",
fact=edge.fact or "",
source_node_uuid=edge.source_node_uuid,
target_node_uuid=edge.target_node_uuid,
attributes=edge.attributes or {}
)
for edge in raw_edges
]
return GraphData(
graph_id=graph_id,
nodes=nodes,
edges=edges
)
def delete_graph(self, graph_id: str):
"""删除图谱"""
self.client.graph.delete(graph_id=graph_id)
def build_graph_from_text(
text: str,
graph_name: str = "Knowledge Graph",
api_key: Optional[str] = None,
chunk_size: int = 2000,
progress_callback: Optional[Callable] = None
) -> GraphData:
"""
便捷函数从文本构建知识图谱
Args:
text: 输入文本
graph_name: 图谱名称
api_key: Zep API密钥
chunk_size: 文本分块大小默认2000字符
progress_callback: 进度回调
Returns:
GraphData对象
"""
from text_extractor import split_text_into_chunks
builder = ZepGraphBuilder(api_key=api_key)
# 创建图谱
graph_id = builder.create_graph(name=graph_name)
if progress_callback:
progress_callback(f"创建图谱: {graph_id}")
# 设置本体
builder.set_ontology(graph_id)
if progress_callback:
progress_callback("设置实体类型...")
# 分块处理文本
chunks = split_text_into_chunks(text, max_chunk_size=chunk_size)
if progress_callback:
progress_callback(f"文本分为 {len(chunks)} 个块")
# 分批添加到图谱
task_ids = builder.add_text_to_graph(
graph_id=graph_id,
text_chunks=chunks,
batch_size=3,
progress_callback=progress_callback
)
# 等待所有任务完成
if task_ids:
builder.wait_for_tasks(task_ids, progress_callback=progress_callback)
# 获取并返回图数据
return builder.get_graph_data(graph_id)
if __name__ == "__main__":
# 测试
from dotenv import load_dotenv
load_dotenv()
test_text = """
武汉大学是中国著名的高等学府位于湖北省武汉市
该校的樱花季每年吸引大量游客
马化腾是腾讯公司的创始人腾讯总部位于深圳
"""
result = build_graph_from_text(
text=test_text,
graph_name="测试图谱",
progress_callback=print
)
print(f"\n节点数: {len(result.nodes)}")
for node in result.nodes:
print(f" - {node.name} ({node.labels})")
print(f"\n边数: {len(result.edges)}")
for edge in result.edges:
print(f" - {edge.fact}")

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function neighbourhoodHighlight(params) {
// console.log("in nieghbourhoodhighlight");
allNodes = nodes.get({ returnType: "Object" });
// originalNodes = JSON.parse(JSON.stringify(allNodes));
// if something is selected:
if (params.nodes.length > 0) {
highlightActive = true;
var i, j;
var selectedNode = params.nodes[0];
var degrees = 2;
// mark all nodes as hard to read.
for (let nodeId in allNodes) {
// nodeColors[nodeId] = allNodes[nodeId].color;
allNodes[nodeId].color = "rgba(200,200,200,0.5)";
if (allNodes[nodeId].hiddenLabel === undefined) {
allNodes[nodeId].hiddenLabel = allNodes[nodeId].label;
allNodes[nodeId].label = undefined;
}
}
var connectedNodes = network.getConnectedNodes(selectedNode);
var allConnectedNodes = [];
// get the second degree nodes
for (i = 1; i < degrees; i++) {
for (j = 0; j < connectedNodes.length; j++) {
allConnectedNodes = allConnectedNodes.concat(
network.getConnectedNodes(connectedNodes[j])
);
}
}
// all second degree nodes get a different color and their label back
for (i = 0; i < allConnectedNodes.length; i++) {
// allNodes[allConnectedNodes[i]].color = "pink";
allNodes[allConnectedNodes[i]].color = "rgba(150,150,150,0.75)";
if (allNodes[allConnectedNodes[i]].hiddenLabel !== undefined) {
allNodes[allConnectedNodes[i]].label =
allNodes[allConnectedNodes[i]].hiddenLabel;
allNodes[allConnectedNodes[i]].hiddenLabel = undefined;
}
}
// all first degree nodes get their own color and their label back
for (i = 0; i < connectedNodes.length; i++) {
// allNodes[connectedNodes[i]].color = undefined;
allNodes[connectedNodes[i]].color = nodeColors[connectedNodes[i]];
if (allNodes[connectedNodes[i]].hiddenLabel !== undefined) {
allNodes[connectedNodes[i]].label =
allNodes[connectedNodes[i]].hiddenLabel;
allNodes[connectedNodes[i]].hiddenLabel = undefined;
}
}
// the main node gets its own color and its label back.
// allNodes[selectedNode].color = undefined;
allNodes[selectedNode].color = nodeColors[selectedNode];
if (allNodes[selectedNode].hiddenLabel !== undefined) {
allNodes[selectedNode].label = allNodes[selectedNode].hiddenLabel;
allNodes[selectedNode].hiddenLabel = undefined;
}
} else if (highlightActive === true) {
// console.log("highlightActive was true");
// reset all nodes
for (let nodeId in allNodes) {
// allNodes[nodeId].color = "purple";
allNodes[nodeId].color = nodeColors[nodeId];
// delete allNodes[nodeId].color;
if (allNodes[nodeId].hiddenLabel !== undefined) {
allNodes[nodeId].label = allNodes[nodeId].hiddenLabel;
allNodes[nodeId].hiddenLabel = undefined;
}
}
highlightActive = false;
}
// transform the object into an array
var updateArray = [];
if (params.nodes.length > 0) {
for (let nodeId in allNodes) {
if (allNodes.hasOwnProperty(nodeId)) {
// console.log(allNodes[nodeId]);
updateArray.push(allNodes[nodeId]);
}
}
nodes.update(updateArray);
} else {
// console.log("Nothing was selected");
for (let nodeId in allNodes) {
if (allNodes.hasOwnProperty(nodeId)) {
// console.log(allNodes[nodeId]);
// allNodes[nodeId].color = {};
updateArray.push(allNodes[nodeId]);
}
}
nodes.update(updateArray);
}
}
function filterHighlight(params) {
allNodes = nodes.get({ returnType: "Object" });
// if something is selected:
if (params.nodes.length > 0) {
filterActive = true;
let selectedNodes = params.nodes;
// hiding all nodes and saving the label
for (let nodeId in allNodes) {
allNodes[nodeId].hidden = true;
if (allNodes[nodeId].savedLabel === undefined) {
allNodes[nodeId].savedLabel = allNodes[nodeId].label;
allNodes[nodeId].label = undefined;
}
}
for (let i=0; i < selectedNodes.length; i++) {
allNodes[selectedNodes[i]].hidden = false;
if (allNodes[selectedNodes[i]].savedLabel !== undefined) {
allNodes[selectedNodes[i]].label = allNodes[selectedNodes[i]].savedLabel;
allNodes[selectedNodes[i]].savedLabel = undefined;
}
}
} else if (filterActive === true) {
// reset all nodes
for (let nodeId in allNodes) {
allNodes[nodeId].hidden = false;
if (allNodes[nodeId].savedLabel !== undefined) {
allNodes[nodeId].label = allNodes[nodeId].savedLabel;
allNodes[nodeId].savedLabel = undefined;
}
}
filterActive = false;
}
// transform the object into an array
var updateArray = [];
if (params.nodes.length > 0) {
for (let nodeId in allNodes) {
if (allNodes.hasOwnProperty(nodeId)) {
updateArray.push(allNodes[nodeId]);
}
}
nodes.update(updateArray);
} else {
for (let nodeId in allNodes) {
if (allNodes.hasOwnProperty(nodeId)) {
updateArray.push(allNodes[nodeId]);
}
}
nodes.update(updateArray);
}
}
function selectNode(nodes) {
network.selectNodes(nodes);
neighbourhoodHighlight({ nodes: nodes });
return nodes;
}
function selectNodes(nodes) {
network.selectNodes(nodes);
filterHighlight({nodes: nodes});
return nodes;
}
function highlightFilter(filter) {
let selectedNodes = []
let selectedProp = filter['property']
if (filter['item'] === 'node') {
let allNodes = nodes.get({ returnType: "Object" });
for (let nodeId in allNodes) {
if (allNodes[nodeId][selectedProp] && filter['value'].includes((allNodes[nodeId][selectedProp]).toString())) {
selectedNodes.push(nodeId)
}
}
}
else if (filter['item'] === 'edge'){
let allEdges = edges.get({returnType: 'object'});
// check if the selected property exists for selected edge and select the nodes connected to the edge
for (let edge in allEdges) {
if (allEdges[edge][selectedProp] && filter['value'].includes((allEdges[edge][selectedProp]).toString())) {
selectedNodes.push(allEdges[edge]['from'])
selectedNodes.push(allEdges[edge]['to'])
}
}
}
selectNodes(selectedNodes)
}

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case 40:if(!t.isOpen&&t.hasOptions)t.open()
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case 38:if(t.activeOption){let e=t.getAdjacent(t.activeOption,-1)
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case 37:return void t.advanceSelection(-1,e)
case 39:return void t.advanceSelection(1,e)
case 9:return void(t.settings.selectOnTab&&(t.isOpen&&t.activeOption&&(t.onOptionSelect(e,t.activeOption),H(e)),t.settings.create&&t.createItem()&&H(e)))
case 8:case 46:return void t.deleteSelection(e)}t.isInputHidden&&!K(V,e)&&H(e)}}onInput(e){var t=this
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t.settings.create&&t.settings.createOnBlur?t.createItem(null,!1,i):i()}}}onOptionSelect(e,t){var i,s=this
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const o=q(e),r=q(t[i.settings.valueField])
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if("string"!=typeof r)throw new Error("Value must be set in option data")
const l=i.getOption(o),a=i.getItem(o)
if(t.$order=t.$order||i.options[o].$order,delete i.options[o],i.uncacheValue(r),i.options[r]=t,l){if(i.dropdown_content.contains(l)){const e=i._render("option",t)
E(l,e),i.activeOption===l&&i.setActiveOption(e)}l.remove()}a&&(-1!==(n=i.items.indexOf(o))&&i.items.splice(n,1,r),s=i._render("item",t),a.classList.contains("active")&&C(s,"active"),E(a,s)),i.lastQuery=null}removeOption(e,t){const i=this
e=D(e),i.uncacheValue(e),delete i.userOptions[e],delete i.options[e],i.lastQuery=null,i.trigger("option_remove",e),i.removeItem(e,t)}clearOptions(){this.loadedSearches={},this.userOptions={},this.clearCache()
var e={}
y(this.options,((t,i)=>{this.items.indexOf(i)>=0&&(e[i]=this.options[i])})),this.options=this.sifter.items=e,this.lastQuery=null,this.trigger("option_clear")}getOption(e,t=!1){const i=q(e)
if(null!==i&&this.options.hasOwnProperty(i)){const e=this.options[i]
if(e.$div)return e.$div
if(t)return this._render("option",e)}return null}getAdjacent(e,t,i="option"){var s
if(!e)return null
s="item"==i?this.controlChildren():this.dropdown_content.querySelectorAll("[data-selectable]")
for(let i=0;i<s.length;i++)if(s[i]==e)return t>0?s[i+1]:s[i-1]
return null}getItem(e){if("object"==typeof e)return e
var t=q(e)
return null!==t?this.control.querySelector(`[data-value="${Q(t)}"]`):null}addItems(e,t){var i=this,s=Array.isArray(e)?e:[e]
for(let e=0,n=(s=s.filter((e=>-1===i.items.indexOf(e)))).length;e<n;e++)i.isPending=e<n-1,i.addItem(s[e],t)}addItem(e,t){R(this,t?[]:["change"],(()=>{var i,s
const n=this,o=n.settings.mode,r=q(e)
if((!r||-1===n.items.indexOf(r)||("single"===o&&n.close(),"single"!==o&&n.settings.duplicates))&&null!==r&&n.options.hasOwnProperty(r)&&("single"===o&&n.clear(t),"multi"!==o||!n.isFull())){if(i=n._render("item",n.options[r]),n.control.contains(i)&&(i=i.cloneNode(!0)),s=n.isFull(),n.items.splice(n.caretPos,0,r),n.insertAtCaret(i),n.isSetup){if(!n.isPending&&n.settings.hideSelected){let e=n.getOption(r),t=n.getAdjacent(e,1)
t&&n.setActiveOption(t)}n.isPending||n.refreshOptions(n.isFocused&&"single"!==o),0!=n.settings.closeAfterSelect&&n.isFull()?n.close():n.isPending||n.positionDropdown(),n.trigger("item_add",r,i),n.isPending||n.updateOriginalInput({silent:t})}(!n.isPending||!s&&n.isFull())&&(n.inputState(),n.refreshState())}}))}removeItem(e=null,t){const i=this
if(!(e=i.getItem(e)))return
var s,n
const o=e.dataset.value
s=L(e),e.remove(),e.classList.contains("active")&&(n=i.activeItems.indexOf(e),i.activeItems.splice(n,1),S(e,"active")),i.items.splice(s,1),i.lastQuery=null,!i.settings.persist&&i.userOptions.hasOwnProperty(o)&&i.removeOption(o,t),s<i.caretPos&&i.setCaret(i.caretPos-1),i.updateOriginalInput({silent:t}),i.refreshState(),i.positionDropdown(),i.trigger("item_remove",o,e)}createItem(e=null,t=!0,i=(()=>{})){var s,n=this,o=n.caretPos
if(e=e||n.inputValue(),!n.canCreate(e))return i(),!1
n.lock()
var r=!1,l=e=>{if(n.unlock(),!e||"object"!=typeof e)return i()
var s=q(e[n.settings.valueField])
if("string"!=typeof s)return i()
n.setTextboxValue(),n.addOption(e,!0),n.setCaret(o),n.addItem(s),n.refreshOptions(t&&"single"!==n.settings.mode),i(e),r=!0}
return s="function"==typeof n.settings.create?n.settings.create.call(this,e,l):{[n.settings.labelField]:e,[n.settings.valueField]:e},r||l(s),!0}refreshItems(){var e=this
e.lastQuery=null,e.isSetup&&e.addItems(e.items),e.updateOriginalInput(),e.refreshState()}refreshState(){const e=this
e.refreshValidityState()
const t=e.isFull(),i=e.isLocked
e.wrapper.classList.toggle("rtl",e.rtl)
const s=e.wrapper.classList
var n
s.toggle("focus",e.isFocused),s.toggle("disabled",e.isDisabled),s.toggle("required",e.isRequired),s.toggle("invalid",!e.isValid),s.toggle("locked",i),s.toggle("full",t),s.toggle("input-active",e.isFocused&&!e.isInputHidden),s.toggle("dropdown-active",e.isOpen),s.toggle("has-options",(n=e.options,0===Object.keys(n).length)),s.toggle("has-items",e.items.length>0)}refreshValidityState(){var e=this
e.input.checkValidity&&(e.isValid=e.input.checkValidity(),e.isInvalid=!e.isValid)}isFull(){return null!==this.settings.maxItems&&this.items.length>=this.settings.maxItems}updateOriginalInput(e={}){const t=this
var i,s
const n=t.input.querySelector('option[value=""]')
if(t.is_select_tag){const e=[]
function o(i,s,o){return i||(i=w('<option value="'+N(s)+'">'+N(o)+"</option>")),i!=n&&t.input.append(i),e.push(i),i.selected=!0,i}t.input.querySelectorAll("option:checked").forEach((e=>{e.selected=!1})),0==t.items.length&&"single"==t.settings.mode?o(n,"",""):t.items.forEach((n=>{if(i=t.options[n],s=i[t.settings.labelField]||"",e.includes(i.$option)){o(t.input.querySelector(`option[value="${Q(n)}"]:not(:checked)`),n,s)}else i.$option=o(i.$option,n,s)}))}else t.input.value=t.getValue()
t.isSetup&&(e.silent||t.trigger("change",t.getValue()))}open(){var e=this
e.isLocked||e.isOpen||"multi"===e.settings.mode&&e.isFull()||(e.isOpen=!0,P(e.focus_node,{"aria-expanded":"true"}),e.refreshState(),I(e.dropdown,{visibility:"hidden",display:"block"}),e.positionDropdown(),I(e.dropdown,{visibility:"visible",display:"block"}),e.focus(),e.trigger("dropdown_open",e.dropdown))}close(e=!0){var t=this,i=t.isOpen
e&&(t.setTextboxValue(),"single"===t.settings.mode&&t.items.length&&t.hideInput()),t.isOpen=!1,P(t.focus_node,{"aria-expanded":"false"}),I(t.dropdown,{display:"none"}),t.settings.hideSelected&&t.clearActiveOption(),t.refreshState(),i&&t.trigger("dropdown_close",t.dropdown)}positionDropdown(){if("body"===this.settings.dropdownParent){var e=this.control,t=e.getBoundingClientRect(),i=e.offsetHeight+t.top+window.scrollY,s=t.left+window.scrollX
I(this.dropdown,{width:t.width+"px",top:i+"px",left:s+"px"})}}clear(e){var t=this
if(t.items.length){var i=t.controlChildren()
y(i,(e=>{t.removeItem(e,!0)})),t.showInput(),e||t.updateOriginalInput(),t.trigger("clear")}}insertAtCaret(e){const t=this,i=t.caretPos,s=t.control
s.insertBefore(e,s.children[i]),t.setCaret(i+1)}deleteSelection(e){var t,i,s,n,o,r=this
t=e&&8===e.keyCode?-1:1,i={start:(o=r.control_input).selectionStart||0,length:(o.selectionEnd||0)-(o.selectionStart||0)}
const l=[]
if(r.activeItems.length)n=F(r.activeItems,t),s=L(n),t>0&&s++,y(r.activeItems,(e=>l.push(e)))
else if((r.isFocused||"single"===r.settings.mode)&&r.items.length){const e=r.controlChildren()
t<0&&0===i.start&&0===i.length?l.push(e[r.caretPos-1]):t>0&&i.start===r.inputValue().length&&l.push(e[r.caretPos])}const a=l.map((e=>e.dataset.value))
if(!a.length||"function"==typeof r.settings.onDelete&&!1===r.settings.onDelete.call(r,a,e))return!1
for(H(e,!0),void 0!==s&&r.setCaret(s);l.length;)r.removeItem(l.pop())
return r.showInput(),r.positionDropdown(),r.refreshOptions(!1),!0}advanceSelection(e,t){var i,s,n=this
n.rtl&&(e*=-1),n.inputValue().length||(K(V,t)||K("shiftKey",t)?(s=(i=n.getLastActive(e))?i.classList.contains("active")?n.getAdjacent(i,e,"item"):i:e>0?n.control_input.nextElementSibling:n.control_input.previousElementSibling)&&(s.classList.contains("active")&&n.removeActiveItem(i),n.setActiveItemClass(s)):n.moveCaret(e))}moveCaret(e){}getLastActive(e){let t=this.control.querySelector(".last-active")
if(t)return t
var i=this.control.querySelectorAll(".active")
return i?F(i,e):void 0}setCaret(e){this.caretPos=this.items.length}controlChildren(){return Array.from(this.control.querySelectorAll("[data-ts-item]"))}lock(){this.close(),this.isLocked=!0,this.refreshState()}unlock(){this.isLocked=!1,this.refreshState()}disable(){var e=this
e.input.disabled=!0,e.control_input.disabled=!0,e.focus_node.tabIndex=-1,e.isDisabled=!0,e.lock()}enable(){var e=this
e.input.disabled=!1,e.control_input.disabled=!1,e.focus_node.tabIndex=e.tabIndex,e.isDisabled=!1,e.unlock()}destroy(){var e=this,t=e.revertSettings
e.trigger("destroy"),e.off(),e.wrapper.remove(),e.dropdown.remove(),e.input.innerHTML=t.innerHTML,e.input.tabIndex=t.tabIndex,S(e.input,"tomselected","ts-hidden-accessible"),e._destroy(),delete e.input.tomselect}render(e,t){return"function"!=typeof this.settings.render[e]?null:this._render(e,t)}_render(e,t){var i,s,n=""
const o=this
return"option"!==e&&"item"!=e||(n=D(t[o.settings.valueField])),null==(s=o.settings.render[e].call(this,t,N))||(s=w(s),"option"===e||"option_create"===e?t[o.settings.disabledField]?P(s,{"aria-disabled":"true"}):P(s,{"data-selectable":""}):"optgroup"===e&&(i=t.group[o.settings.optgroupValueField],P(s,{"data-group":i}),t.group[o.settings.disabledField]&&P(s,{"data-disabled":""})),"option"!==e&&"item"!==e||(P(s,{"data-value":n}),"item"===e?(C(s,o.settings.itemClass),P(s,{"data-ts-item":""})):(C(s,o.settings.optionClass),P(s,{role:"option",id:t.$id}),o.options[n].$div=s))),s}clearCache(){y(this.options,((e,t)=>{e.$div&&(e.$div.remove(),delete e.$div)}))}uncacheValue(e){const t=this.getOption(e)
t&&t.remove()}canCreate(e){return this.settings.create&&e.length>0&&this.settings.createFilter.call(this,e)}hook(e,t,i){var s=this,n=s[t]
s[t]=function(){var t,o
return"after"===e&&(t=n.apply(s,arguments)),o=i.apply(s,arguments),"instead"===e?o:("before"===e&&(t=n.apply(s,arguments)),t)}}}return J.define("change_listener",(function(){B(this.input,"change",(()=>{this.sync()}))})),J.define("checkbox_options",(function(){var e=this,t=e.onOptionSelect
e.settings.hideSelected=!1
var i=function(e){setTimeout((()=>{var t=e.querySelector("input")
e.classList.contains("selected")?t.checked=!0:t.checked=!1}),1)}
e.hook("after","setupTemplates",(()=>{var t=e.settings.render.option
e.settings.render.option=(i,s)=>{var n=w(t.call(e,i,s)),o=document.createElement("input")
o.addEventListener("click",(function(e){H(e)})),o.type="checkbox"
const r=q(i[e.settings.valueField])
return r&&e.items.indexOf(r)>-1&&(o.checked=!0),n.prepend(o),n}})),e.on("item_remove",(t=>{var s=e.getOption(t)
s&&(s.classList.remove("selected"),i(s))})),e.hook("instead","onOptionSelect",((s,n)=>{if(n.classList.contains("selected"))return n.classList.remove("selected"),e.removeItem(n.dataset.value),e.refreshOptions(),void H(s,!0)
t.call(e,s,n),i(n)}))})),J.define("clear_button",(function(e){const t=this,i=Object.assign({className:"clear-button",title:"Clear All",html:e=>`<div class="${e.className}" title="${e.title}">&times;</div>`},e)
t.on("initialize",(()=>{var e=w(i.html(i))
e.addEventListener("click",(e=>{t.clear(),"single"===t.settings.mode&&t.settings.allowEmptyOption&&t.addItem(""),e.preventDefault(),e.stopPropagation()})),t.control.appendChild(e)}))})),J.define("drag_drop",(function(){var e=this
if(!$.fn.sortable)throw new Error('The "drag_drop" plugin requires jQuery UI "sortable".')
if("multi"===e.settings.mode){var t=e.lock,i=e.unlock
e.hook("instead","lock",(()=>{var i=$(e.control).data("sortable")
return i&&i.disable(),t.call(e)})),e.hook("instead","unlock",(()=>{var t=$(e.control).data("sortable")
return t&&t.enable(),i.call(e)})),e.on("initialize",(()=>{var t=$(e.control).sortable({items:"[data-value]",forcePlaceholderSize:!0,disabled:e.isLocked,start:(e,i)=>{i.placeholder.css("width",i.helper.css("width")),t.css({overflow:"visible"})},stop:()=>{t.css({overflow:"hidden"})
var i=[]
t.children("[data-value]").each((function(){this.dataset.value&&i.push(this.dataset.value)})),e.setValue(i)}})}))}})),J.define("dropdown_header",(function(e){const t=this,i=Object.assign({title:"Untitled",headerClass:"dropdown-header",titleRowClass:"dropdown-header-title",labelClass:"dropdown-header-label",closeClass:"dropdown-header-close",html:e=>'<div class="'+e.headerClass+'"><div class="'+e.titleRowClass+'"><span class="'+e.labelClass+'">'+e.title+'</span><a class="'+e.closeClass+'">&times;</a></div></div>'},e)
t.on("initialize",(()=>{var e=w(i.html(i)),s=e.querySelector("."+i.closeClass)
s&&s.addEventListener("click",(e=>{H(e,!0),t.close()})),t.dropdown.insertBefore(e,t.dropdown.firstChild)}))})),J.define("caret_position",(function(){var e=this
e.hook("instead","setCaret",(t=>{"single"!==e.settings.mode&&e.control.contains(e.control_input)?(t=Math.max(0,Math.min(e.items.length,t)))==e.caretPos||e.isPending||e.controlChildren().forEach(((i,s)=>{s<t?e.control_input.insertAdjacentElement("beforebegin",i):e.control.appendChild(i)})):t=e.items.length,e.caretPos=t})),e.hook("instead","moveCaret",(t=>{if(!e.isFocused)return
const i=e.getLastActive(t)
if(i){const s=L(i)
e.setCaret(t>0?s+1:s),e.setActiveItem()}else e.setCaret(e.caretPos+t)}))})),J.define("dropdown_input",(function(){var e=this
e.settings.shouldOpen=!0,e.hook("before","setup",(()=>{e.focus_node=e.control,C(e.control_input,"dropdown-input")
const t=w('<div class="dropdown-input-wrap">')
t.append(e.control_input),e.dropdown.insertBefore(t,e.dropdown.firstChild)})),e.on("initialize",(()=>{e.control_input.addEventListener("keydown",(t=>{switch(t.keyCode){case 27:return e.isOpen&&(H(t,!0),e.close()),void e.clearActiveItems()
case 9:e.focus_node.tabIndex=-1}return e.onKeyDown.call(e,t)})),e.on("blur",(()=>{e.focus_node.tabIndex=e.isDisabled?-1:e.tabIndex})),e.on("dropdown_open",(()=>{e.control_input.focus()}))
const t=e.onBlur
e.hook("instead","onBlur",(i=>{if(!i||i.relatedTarget!=e.control_input)return t.call(e)})),B(e.control_input,"blur",(()=>e.onBlur())),e.hook("before","close",(()=>{e.isOpen&&e.focus_node.focus()}))}))})),J.define("input_autogrow",(function(){var e=this
e.on("initialize",(()=>{var t=document.createElement("span"),i=e.control_input
t.style.cssText="position:absolute; top:-99999px; left:-99999px; width:auto; padding:0; white-space:pre; ",e.wrapper.appendChild(t)
for(const e of["letterSpacing","fontSize","fontFamily","fontWeight","textTransform"])t.style[e]=i.style[e]
var s=()=>{e.items.length>0?(t.textContent=i.value,i.style.width=t.clientWidth+"px"):i.style.width=""}
s(),e.on("update item_add item_remove",s),B(i,"input",s),B(i,"keyup",s),B(i,"blur",s),B(i,"update",s)}))})),J.define("no_backspace_delete",(function(){var e=this,t=e.deleteSelection
this.hook("instead","deleteSelection",(i=>!!e.activeItems.length&&t.call(e,i)))})),J.define("no_active_items",(function(){this.hook("instead","setActiveItem",(()=>{})),this.hook("instead","selectAll",(()=>{}))})),J.define("optgroup_columns",(function(){var e=this,t=e.onKeyDown
e.hook("instead","onKeyDown",(i=>{var s,n,o,r
if(!e.isOpen||37!==i.keyCode&&39!==i.keyCode)return t.call(e,i)
r=k(e.activeOption,"[data-group]"),s=L(e.activeOption,"[data-selectable]"),r&&(r=37===i.keyCode?r.previousSibling:r.nextSibling)&&(n=(o=r.querySelectorAll("[data-selectable]"))[Math.min(o.length-1,s)])&&e.setActiveOption(n)}))})),J.define("remove_button",(function(e){const t=Object.assign({label:"&times;",title:"Remove",className:"remove",append:!0},e)
var i=this
if(t.append){var s='<a href="javascript:void(0)" class="'+t.className+'" tabindex="-1" title="'+N(t.title)+'">'+t.label+"</a>"
i.hook("after","setupTemplates",(()=>{var e=i.settings.render.item
i.settings.render.item=(t,n)=>{var o=w(e.call(i,t,n)),r=w(s)
return o.appendChild(r),B(r,"mousedown",(e=>{H(e,!0)})),B(r,"click",(e=>{if(H(e,!0),!i.isLocked){var t=o.dataset.value
i.removeItem(t),i.refreshOptions(!1)}})),o}}))}})),J.define("restore_on_backspace",(function(e){const t=this,i=Object.assign({text:e=>e[t.settings.labelField]},e)
t.on("item_remove",(function(e){if(""===t.control_input.value.trim()){var s=t.options[e]
s&&t.setTextboxValue(i.text.call(t,s))}}))})),J.define("virtual_scroll",(function(){const e=this,t=e.canLoad,i=e.clearActiveOption,s=e.loadCallback
var n,o={},r=!1
if(!e.settings.firstUrl)throw"virtual_scroll plugin requires a firstUrl() method"
function l(t){return!("number"==typeof e.settings.maxOptions&&n.children.length>=e.settings.maxOptions)&&!(!(t in o)||!o[t])}e.settings.sortField=[{field:"$order"},{field:"$score"}],e.setNextUrl=function(e,t){o[e]=t},e.getUrl=function(t){if(t in o){const e=o[t]
return o[t]=!1,e}return o={},e.settings.firstUrl(t)},e.hook("instead","clearActiveOption",(()=>{if(!r)return i.call(e)})),e.hook("instead","canLoad",(i=>i in o?l(i):t.call(e,i))),e.hook("instead","loadCallback",((t,i)=>{r||e.clearOptions(),s.call(e,t,i),r=!1})),e.hook("after","refreshOptions",(()=>{const t=e.lastValue
var i
l(t)?(i=e.render("loading_more",{query:t}))&&i.setAttribute("data-selectable",""):t in o&&!n.querySelector(".no-results")&&(i=e.render("no_more_results",{query:t})),i&&(C(i,e.settings.optionClass),n.append(i))})),e.on("initialize",(()=>{n=e.dropdown_content,e.settings.render=Object.assign({},{loading_more:function(){return'<div class="loading-more-results">Loading more results ... </div>'},no_more_results:function(){return'<div class="no-more-results">No more results</div>'}},e.settings.render),n.addEventListener("scroll",(function(){n.clientHeight/(n.scrollHeight-n.scrollTop)<.95||l(e.lastValue)&&(r||(r=!0,e.load.call(e,e.lastValue)))}))}))})),J}))
var tomSelect=function(e,t){return new TomSelect(e,t)}
//# sourceMappingURL=tom-select.complete.min.js.map

View file

@ -0,0 +1,334 @@
/**
* tom-select.css (v2.0.0-rc.4)
* Copyright (c) contributors
*
* Licensed under the Apache License, Version 2.0 (the "License"); you may not use this
* file except in compliance with the License. You may obtain a copy of the License at:
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software distributed under
* the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
* ANY KIND, either express or implied. See the License for the specific language
* governing permissions and limitations under the License.
*
*/
.ts-wrapper.plugin-drag_drop.multi > .ts-control > div.ui-sortable-placeholder {
visibility: visible !important;
background: #f2f2f2 !important;
background: rgba(0, 0, 0, 0.06) !important;
border: 0 none !important;
box-shadow: inset 0 0 12px 4px #fff; }
.ts-wrapper.plugin-drag_drop .ui-sortable-placeholder::after {
content: '!';
visibility: hidden; }
.ts-wrapper.plugin-drag_drop .ui-sortable-helper {
box-shadow: 0 2px 5px rgba(0, 0, 0, 0.2); }
.plugin-checkbox_options .option input {
margin-right: 0.5rem; }
.plugin-clear_button .ts-control {
padding-right: calc( 1em + (3 * 6px)) !important; }
.plugin-clear_button .clear-button {
opacity: 0;
position: absolute;
top: 8px;
right: calc(8px - 6px);
margin-right: 0 !important;
background: transparent !important;
transition: opacity 0.5s;
cursor: pointer; }
.plugin-clear_button.single .clear-button {
right: calc(8px - 6px + 2rem); }
.plugin-clear_button.focus.has-items .clear-button,
.plugin-clear_button:hover.has-items .clear-button {
opacity: 1; }
.ts-wrapper .dropdown-header {
position: relative;
padding: 10px 8px;
border-bottom: 1px solid #d0d0d0;
background: #f8f8f8;
border-radius: 3px 3px 0 0; }
.ts-wrapper .dropdown-header-close {
position: absolute;
right: 8px;
top: 50%;
color: #303030;
opacity: 0.4;
margin-top: -12px;
line-height: 20px;
font-size: 20px !important; }
.ts-wrapper .dropdown-header-close:hover {
color: black; }
.plugin-dropdown_input.focus.dropdown-active .ts-control {
box-shadow: none;
border: 1px solid #d0d0d0; }
.plugin-dropdown_input .dropdown-input {
border: 1px solid #d0d0d0;
border-width: 0 0 1px 0;
display: block;
padding: 8px 8px;
box-shadow: none;
width: 100%;
background: transparent; }
.ts-wrapper.plugin-input_autogrow.has-items .ts-control > input {
min-width: 0; }
.ts-wrapper.plugin-input_autogrow.has-items.focus .ts-control > input {
flex: none;
min-width: 4px; }
.ts-wrapper.plugin-input_autogrow.has-items.focus .ts-control > input::-webkit-input-placeholder {
color: transparent; }
.ts-wrapper.plugin-input_autogrow.has-items.focus .ts-control > input::-ms-input-placeholder {
color: transparent; }
.ts-wrapper.plugin-input_autogrow.has-items.focus .ts-control > input::placeholder {
color: transparent; }
.ts-dropdown.plugin-optgroup_columns .ts-dropdown-content {
display: flex; }
.ts-dropdown.plugin-optgroup_columns .optgroup {
border-right: 1px solid #f2f2f2;
border-top: 0 none;
flex-grow: 1;
flex-basis: 0;
min-width: 0; }
.ts-dropdown.plugin-optgroup_columns .optgroup:last-child {
border-right: 0 none; }
.ts-dropdown.plugin-optgroup_columns .optgroup:before {
display: none; }
.ts-dropdown.plugin-optgroup_columns .optgroup-header {
border-top: 0 none; }
.ts-wrapper.plugin-remove_button .item {
display: inline-flex;
align-items: center;
padding-right: 0 !important; }
.ts-wrapper.plugin-remove_button .item .remove {
color: inherit;
text-decoration: none;
vertical-align: middle;
display: inline-block;
padding: 2px 6px;
border-left: 1px solid #d0d0d0;
border-radius: 0 2px 2px 0;
box-sizing: border-box;
margin-left: 6px; }
.ts-wrapper.plugin-remove_button .item .remove:hover {
background: rgba(0, 0, 0, 0.05); }
.ts-wrapper.plugin-remove_button .item.active .remove {
border-left-color: #cacaca; }
.ts-wrapper.plugin-remove_button.disabled .item .remove:hover {
background: none; }
.ts-wrapper.plugin-remove_button.disabled .item .remove {
border-left-color: white; }
.ts-wrapper.plugin-remove_button .remove-single {
position: absolute;
right: 0;
top: 0;
font-size: 23px; }
.ts-wrapper {
position: relative; }
.ts-dropdown,
.ts-control,
.ts-control input {
color: #303030;
font-family: inherit;
font-size: 13px;
line-height: 18px;
font-smoothing: inherit; }
.ts-control,
.ts-wrapper.single.input-active .ts-control {
background: #fff;
cursor: text; }
.ts-control {
border: 1px solid #d0d0d0;
padding: 8px 8px;
width: 100%;
overflow: hidden;
position: relative;
z-index: 1;
box-sizing: border-box;
box-shadow: none;
border-radius: 3px;
display: flex;
flex-wrap: wrap; }
.ts-wrapper.multi.has-items .ts-control {
padding: calc( 8px - 2px - 0) 8px calc( 8px - 2px - 3px - 0); }
.full .ts-control {
background-color: #fff; }
.disabled .ts-control,
.disabled .ts-control * {
cursor: default !important; }
.focus .ts-control {
box-shadow: none; }
.ts-control > * {
vertical-align: baseline;
display: inline-block; }
.ts-wrapper.multi .ts-control > div {
cursor: pointer;
margin: 0 3px 3px 0;
padding: 2px 6px;
background: #f2f2f2;
color: #303030;
border: 0 solid #d0d0d0; }
.ts-wrapper.multi .ts-control > div.active {
background: #e8e8e8;
color: #303030;
border: 0 solid #cacaca; }
.ts-wrapper.multi.disabled .ts-control > div, .ts-wrapper.multi.disabled .ts-control > div.active {
color: #7d7c7c;
background: white;
border: 0 solid white; }
.ts-control > input {
flex: 1 1 auto;
min-width: 7rem;
display: inline-block !important;
padding: 0 !important;
min-height: 0 !important;
max-height: none !important;
max-width: 100% !important;
margin: 0 !important;
text-indent: 0 !important;
border: 0 none !important;
background: none !important;
line-height: inherit !important;
-webkit-user-select: auto !important;
-moz-user-select: auto !important;
-ms-user-select: auto !important;
user-select: auto !important;
box-shadow: none !important; }
.ts-control > input::-ms-clear {
display: none; }
.ts-control > input:focus {
outline: none !important; }
.has-items .ts-control > input {
margin: 0 4px !important; }
.ts-control.rtl {
text-align: right; }
.ts-control.rtl.single .ts-control:after {
left: 15px;
right: auto; }
.ts-control.rtl .ts-control > input {
margin: 0 4px 0 -2px !important; }
.disabled .ts-control {
opacity: 0.5;
background-color: #fafafa; }
.input-hidden .ts-control > input {
opacity: 0;
position: absolute;
left: -10000px; }
.ts-dropdown {
position: absolute;
top: 100%;
left: 0;
width: 100%;
z-index: 10;
border: 1px solid #d0d0d0;
background: #fff;
margin: 0.25rem 0 0 0;
border-top: 0 none;
box-sizing: border-box;
box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1);
border-radius: 0 0 3px 3px; }
.ts-dropdown [data-selectable] {
cursor: pointer;
overflow: hidden; }
.ts-dropdown [data-selectable] .highlight {
background: rgba(125, 168, 208, 0.2);
border-radius: 1px; }
.ts-dropdown .option,
.ts-dropdown .optgroup-header,
.ts-dropdown .no-results,
.ts-dropdown .create {
padding: 5px 8px; }
.ts-dropdown .option, .ts-dropdown [data-disabled], .ts-dropdown [data-disabled] [data-selectable].option {
cursor: inherit;
opacity: 0.5; }
.ts-dropdown [data-selectable].option {
opacity: 1;
cursor: pointer; }
.ts-dropdown .optgroup:first-child .optgroup-header {
border-top: 0 none; }
.ts-dropdown .optgroup-header {
color: #303030;
background: #fff;
cursor: default; }
.ts-dropdown .create:hover,
.ts-dropdown .option:hover,
.ts-dropdown .active {
background-color: #f5fafd;
color: #495c68; }
.ts-dropdown .create:hover.create,
.ts-dropdown .option:hover.create,
.ts-dropdown .active.create {
color: #495c68; }
.ts-dropdown .create {
color: rgba(48, 48, 48, 0.5); }
.ts-dropdown .spinner {
display: inline-block;
width: 30px;
height: 30px;
margin: 5px 8px; }
.ts-dropdown .spinner:after {
content: " ";
display: block;
width: 24px;
height: 24px;
margin: 3px;
border-radius: 50%;
border: 5px solid #d0d0d0;
border-color: #d0d0d0 transparent #d0d0d0 transparent;
animation: lds-dual-ring 1.2s linear infinite; }
@keyframes lds-dual-ring {
0% {
transform: rotate(0deg); }
100% {
transform: rotate(360deg); } }
.ts-dropdown-content {
overflow-y: auto;
overflow-x: hidden;
max-height: 200px;
overflow-scrolling: touch;
scroll-behavior: smooth; }
.ts-hidden-accessible {
border: 0 !important;
clip: rect(0 0 0 0) !important;
-webkit-clip-path: inset(50%) !important;
clip-path: inset(50%) !important;
height: 1px !important;
overflow: hidden !important;
padding: 0 !important;
position: absolute !important;
width: 1px !important;
white-space: nowrap !important; }
/*# sourceMappingURL=tom-select.css.map */

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"""
自定义实体类型定义
只提取现实生活中真实存在的可以有行动的实体
"""
from pydantic import Field
from zep_cloud.external_clients.ontology import EntityModel, EntityText, EdgeModel
# ============== 实体类型定义 ==============
class Person(EntityModel):
"""A real, named individual. Must have a specific name like "马化腾" or "Elon Musk". NOT generic terms like "某人", "用户", pronouns, or abstract roles."""
role: EntityText = Field(
description="职业或职位",
default=None
)
affiliation: EntityText = Field(
description="所属组织",
default=None
)
class Organization(EntityModel):
"""A real organization with an official name like "武汉大学", "联合国". NOT generic terms like "大学", "政府", "组织"."""
org_type: EntityText = Field(
description="组织类型",
default=None
)
location: EntityText = Field(
description="所在地",
default=None
)
class Company(EntityModel):
"""A real company with registered name like "腾讯", "Apple Inc.". NOT generic terms like "科技公司", "某企业"."""
industry: EntityText = Field(
description="所属行业",
default=None
)
headquarters: EntityText = Field(
description="总部位置",
default=None
)
class Location(EntityModel):
"""A real geographic location like "北京", "硅谷", "故宫". NOT generic terms like "某地", "一个城市"."""
location_type: EntityText = Field(
description="地点类型",
default=None
)
country: EntityText = Field(
description="所属国家",
default=None
)
class Product(EntityModel):
"""A real product/service with brand name like "iPhone", "微信". NOT generic categories like "手机", "软件"."""
category: EntityText = Field(
description="产品类别",
default=None
)
manufacturer: EntityText = Field(
description="制造商",
default=None
)
class Event(EntityModel):
"""A real, documented event like "2024巴黎奥运会", "新冠疫情". NOT generic terms like "会议", "活动"."""
event_type: EntityText = Field(
description="事件类型",
default=None
)
date: EntityText = Field(
description="发生日期",
default=None
)
class Media(EntityModel):
"""A real media outlet like "人民日报", "CNN", "微博". NOT generic terms like "媒体", "新闻"."""
media_type: EntityText = Field(
description="媒体类型",
default=None
)
# ============== 边类型定义 ==============
class WorksFor(EdgeModel):
"""Employment or affiliation relationship."""
position: EntityText = Field(
description="职位",
default=None
)
class LocatedIn(EdgeModel):
"""Geographic location relationship."""
pass
class PartOf(EdgeModel):
"""Part-of or subsidiary relationship."""
pass
class Produces(EdgeModel):
"""Production or creation relationship."""
pass
class ParticipatesIn(EdgeModel):
"""Participation in an event."""
role: EntityText = Field(
description="参与角色",
default=None
)
class Collaborates(EdgeModel):
"""Collaboration or partnership relationship."""
pass
class Competes(EdgeModel):
"""Competitive relationship."""
pass
class Reports(EdgeModel):
"""Media reporting or coverage relationship."""
pass
# ============== 本体配置 ==============
# 实体类型字典
ENTITY_TYPES = {
"Person": Person,
"Organization": Organization,
"Company": Company,
"Location": Location,
"Product": Product,
"Event": Event,
"Media": Media,
}
# 边类型字典
EDGE_TYPES = {
"WORKS_FOR": WorksFor,
"LOCATED_IN": LocatedIn,
"PART_OF": PartOf,
"PRODUCES": Produces,
"PARTICIPATES_IN": ParticipatesIn,
"COLLABORATES": Collaborates,
"COMPETES": Competes,
"REPORTS": Reports,
}

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"""
Zep Graph HTML渲染器
从Zep云服务获取图谱数据并生成交互式HTML可视化
"""
import os
import json
import argparse
import tempfile
import time
from datetime import datetime
from dotenv import load_dotenv
from zep_cloud.client import Zep
from pyvis.network import Network
# 加载环境变量
load_dotenv()
# 实体类型对应的颜色
ENTITY_COLORS = {
"Person": "#ff6b6b",
"Company": "#4ecdc4",
"Organization": "#45b7d1",
"Location": "#96ceb4",
"Product": "#ffeead",
"Event": "#dcc6e0",
"Media": "#ffb74d",
"Preference": "#a29bfe",
"Topic": "#fd79a8",
"Object": "#636e72",
"Entity": "#b2bec3",
}
# 默认颜色
DEFAULT_COLOR = "#74b9ff"
def get_graph_data(client: Zep, graph_id: str, max_retries: int = 3) -> tuple[list, list]:
"""
从Zep获取图谱的所有节点和边
"""
print(f"正在获取图谱 {graph_id} 的数据...")
nodes = None
edges = None
# 获取所有节点(带重试)
for attempt in range(max_retries):
try:
nodes = client.graph.node.get_by_graph_id(graph_id=graph_id)
print(f" 获取到 {len(nodes)} 个节点")
break
except Exception as e:
if attempt < max_retries - 1:
print(f" 获取节点失败,重试中... ({attempt + 1}/{max_retries})")
time.sleep(2)
else:
raise e
# 获取所有边(带重试)
for attempt in range(max_retries):
try:
edges = client.graph.edge.get_by_graph_id(graph_id=graph_id)
print(f" 获取到 {len(edges)} 个边")
break
except Exception as e:
if attempt < max_retries - 1:
print(f" 获取边失败,重试中... ({attempt + 1}/{max_retries})")
time.sleep(2)
else:
raise e
return nodes or [], edges or []
def create_html_graph(nodes: list, edges: list, graph_id: str, output_file: str):
"""
创建交互式HTML图谱可视化
"""
print("正在生成HTML可视化...")
# 创建网络图
net = Network(
height="100vh",
width="100%",
bgcolor="#1a1a2e",
font_color="white",
directed=True,
select_menu=True,
filter_menu=True,
notebook=False,
)
# 配置物理引擎和交互
net.set_options("""
{
"nodes": {
"font": {
"size": 14,
"face": "Arial, sans-serif",
"color": "white"
},
"borderWidth": 2,
"borderWidthSelected": 4,
"shadow": {
"enabled": true,
"color": "rgba(0,0,0,0.5)",
"size": 10
}
},
"edges": {
"color": {
"color": "#555555",
"highlight": "#667eea",
"hover": "#667eea"
},
"arrows": {
"to": {
"enabled": true,
"scaleFactor": 0.5
}
},
"smooth": {
"type": "continuous",
"roundness": 0.2
},
"font": {
"size": 10,
"color": "#aaaaaa",
"face": "Arial, sans-serif",
"strokeWidth": 0,
"background": "rgba(26,26,46,0.8)"
},
"width": 1.5,
"hoverWidth": 2.5
},
"physics": {
"enabled": true,
"barnesHut": {
"gravitationalConstant": -8000,
"centralGravity": 0.3,
"springLength": 150,
"springConstant": 0.04,
"damping": 0.09,
"avoidOverlap": 0.5
},
"stabilization": {
"enabled": true,
"iterations": 300,
"updateInterval": 25
}
},
"interaction": {
"hover": true,
"tooltipDelay": 100,
"navigationButtons": true,
"keyboard": {
"enabled": true
},
"multiselect": true,
"zoomView": true
}
}
""")
# 构建节点UUID到节点的映射
node_map = {}
for node in nodes:
node_map[node.uuid_] = node
# 统计节点类型
type_counts = {}
# 添加节点
for node in nodes:
node_labels = node.labels or []
specific_labels = [l for l in node_labels if l not in ["Entity", "Node"]]
node_type = specific_labels[0] if specific_labels else (node_labels[0] if node_labels else "Unknown")
color = ENTITY_COLORS.get(node_type, DEFAULT_COLOR)
type_counts[node_type] = type_counts.get(node_type, 0) + 1
# 简化的工具提示避免复杂HTML
summary_text = (node.summary or '无摘要')[:200]
title = f"{node.name}\n类型: {', '.join(node_labels)}\n摘要: {summary_text}"
# 根据节点类型调整大小
if node_type == "Person":
size = 25
elif node_type in ["Company", "Organization"]:
size = 30
elif node_type == "Location":
size = 22
elif node_type == "Event":
size = 20
else:
size = 18
net.add_node(
node.uuid_,
label=node.name[:20] + "..." if len(node.name) > 20 else node.name,
title=title,
color=color,
size=size,
)
# 添加边
edge_count = 0
for edge in edges:
source_uuid = edge.source_node_uuid
target_uuid = edge.target_node_uuid
if source_uuid in node_map and target_uuid in node_map:
source_node = node_map[source_uuid]
target_node = node_map[target_uuid]
title = f"{source_node.name} -> {target_node.name}\n关系: {edge.name or '未命名'}\n事实: {edge.fact or '无描述'}"
edge_label = edge.name or ""
if len(edge_label) > 15:
edge_label = edge_label[:15] + "..."
net.add_edge(
source_uuid,
target_uuid,
title=title,
label=edge_label,
)
edge_count += 1
print(f" 添加了 {len(nodes)} 个节点和 {edge_count} 条边到可视化")
# 打印类型统计
print("\n节点类型统计:")
for t, count in sorted(type_counts.items(), key=lambda x: -x[1]):
print(f" {t}: {count}")
# 保存到临时文件获取原始HTML
with tempfile.NamedTemporaryFile(mode='w', suffix='.html', delete=False, encoding='utf-8') as tmp:
net.save_graph(tmp.name)
tmp_path = tmp.name
# 读取生成的HTML
with open(tmp_path, 'r', encoding='utf-8') as f:
html_content = f.read()
os.unlink(tmp_path)
# 构建自定义CSS和Header HTML
custom_css = """
<style>
#graph-header {
position: fixed;
top: 0;
left: 0;
right: 0;
z-index: 1000;
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
padding: 15px 20px;
box-shadow: 0 2px 10px rgba(0,0,0,0.3);
color: white;
font-family: Arial, sans-serif;
}
#graph-header h1 {
margin: 0;
font-size: 1.5rem;
font-weight: 600;
}
#graph-header .stats {
font-size: 0.9rem;
opacity: 0.9;
margin-top: 5px;
}
#graph-legend {
position: fixed;
top: 80px;
right: 20px;
z-index: 1000;
background: rgba(26, 26, 46, 0.95);
border: 1px solid #333;
border-radius: 8px;
padding: 15px;
max-width: 200px;
color: white;
font-family: Arial, sans-serif;
}
#graph-legend h3 {
margin: 0 0 10px 0;
font-size: 0.9rem;
border-bottom: 1px solid #444;
padding-bottom: 5px;
}
#graph-legend .item {
display: flex;
align-items: center;
margin: 5px 0;
font-size: 0.8rem;
}
#graph-legend .color-box {
width: 12px;
height: 12px;
border-radius: 3px;
margin-right: 8px;
flex-shrink: 0;
}
#mynetwork {
margin-top: 70px !important;
}
body {
background: #1a1a2e !important;
}
</style>
"""
# 构建图例HTML
legend_items = ""
for entity_type, color in ENTITY_COLORS.items():
if entity_type in type_counts:
legend_items += f'''
<div class="item">
<div class="color-box" style="background: {color};"></div>
<span>{entity_type} ({type_counts.get(entity_type, 0)})</span>
</div>'''
custom_html = f'''
<div id="graph-header">
<h1>Knowledge Graph Visualization</h1>
<div class="stats">
Graph ID: {graph_id} | 节点: {len(nodes)} | : {edge_count} | 生成时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
</div>
</div>
<div id="graph-legend">
<h3>图例</h3>
{legend_items}
</div>
'''
# 在</head>前插入自定义CSS
html_content = html_content.replace('</head>', custom_css + '</head>')
# 在<body>后插入自定义HTML
html_content = html_content.replace('<body>', '<body>' + custom_html)
# 修改标题
html_content = html_content.replace('<title>Network</title>', f'<title>Zep Graph: {graph_id}</title>')
# 写入文件
with open(output_file, 'w', encoding='utf-8') as f:
f.write(html_content)
print(f"\nHTML文件已生成: {output_file}")
def main():
parser = argparse.ArgumentParser(description='Zep Graph HTML渲染器')
parser.add_argument(
'--graph-id', '-g',
default='graph_6e3697873495400d',
help='Zep图谱ID'
)
parser.add_argument(
'--output', '-o',
default='graph_visualization.html',
help='输出HTML文件路径'
)
parser.add_argument(
'--api-key', '-k',
default=None,
help='Zep API Key (默认从环境变量ZEP_API_KEY读取)'
)
args = parser.parse_args()
# 获取API Key
api_key = args.api_key or os.environ.get('ZEP_API_KEY')
if not api_key:
print("错误: 请设置ZEP_API_KEY环境变量或通过--api-key参数提供")
return 1
# 创建客户端
client = Zep(api_key=api_key)
try:
# 获取图数据
nodes, edges = get_graph_data(client, args.graph_id)
if not nodes:
print("警告: 图谱中没有节点")
return 1
# 生成HTML
create_html_graph(nodes, edges, args.graph_id, args.output)
print(f"\n完成! 请在浏览器中打开 {args.output} 查看图谱")
return 0
except Exception as e:
print(f"错误: {str(e)}")
import traceback
traceback.print_exc()
return 1
if __name__ == "__main__":
exit(main())

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# Zep Cloud SDK
zep-cloud>=2.0.0
# PDF处理
PyMuPDF>=1.24.0
# Markdown处理
markdown>=3.5.0
# Web可视化界面
streamlit>=1.38.0
# 图可视化
pyvis>=0.3.2
# 环境变量
python-dotenv>=1.0.0

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"""
文本提取模块
支持从 .md, .txt, .pdf 文件中提取纯文本
"""
import os
from pathlib import Path
from typing import Optional
def extract_from_txt(file_path: str) -> str:
"""从TXT文件提取文本"""
with open(file_path, 'r', encoding='utf-8') as f:
return f.read()
def extract_from_md(file_path: str) -> str:
"""从Markdown文件提取文本保留原始格式不转换HTML"""
with open(file_path, 'r', encoding='utf-8') as f:
return f.read()
def extract_from_pdf(file_path: str) -> str:
"""从PDF文件提取文本"""
try:
import fitz # PyMuPDF
except ImportError:
raise ImportError("请安装 PyMuPDF: pip install PyMuPDF")
text_parts = []
with fitz.open(file_path) as doc:
for page_num, page in enumerate(doc):
text = page.get_text()
if text.strip():
text_parts.append(f"--- 第 {page_num + 1} 页 ---\n{text}")
return "\n\n".join(text_parts)
def extract_text(file_path: str) -> str:
"""
根据文件扩展名自动选择提取方法
Args:
file_path: 文件路径
Returns:
提取的纯文本内容
Raises:
ValueError: 不支持的文件格式
FileNotFoundError: 文件不存在
"""
path = Path(file_path)
if not path.exists():
raise FileNotFoundError(f"文件不存在: {file_path}")
suffix = path.suffix.lower()
extractors = {
'.txt': extract_from_txt,
'.md': extract_from_md,
'.markdown': extract_from_md,
'.pdf': extract_from_pdf,
}
extractor = extractors.get(suffix)
if extractor is None:
supported = ', '.join(extractors.keys())
raise ValueError(f"不支持的文件格式: {suffix}。支持的格式: {supported}")
return extractor(file_path)
def split_text_into_chunks(text: str, max_chunk_size: int = 8000, overlap: int = 200) -> list[str]:
"""
将长文本分割成多个小块适合Zep处理
Args:
text: 原始文本
max_chunk_size: 每个块的最大字符数
overlap: 块之间的重叠字符数
Returns:
文本块列表
"""
if len(text) <= max_chunk_size:
return [text]
chunks = []
start = 0
while start < len(text):
end = start + max_chunk_size
# 尝试在句子边界处分割
if end < len(text):
# 查找最近的句子结束符
for sep in ['', '', '', '\n\n', '. ', '! ', '? ']:
last_sep = text[start:end].rfind(sep)
if last_sep != -1 and last_sep > max_chunk_size * 0.5:
end = start + last_sep + len(sep)
break
chunk = text[start:end].strip()
if chunk:
chunks.append(chunk)
# 下一个块从重叠位置开始
start = end - overlap if end < len(text) else len(text)
return chunks
if __name__ == "__main__":
# 测试
import sys
if len(sys.argv) > 1:
file_path = sys.argv[1]
text = extract_text(file_path)
print(f"提取了 {len(text)} 个字符")
print(f"前500字符:\n{text[:500]}")