# llm-graph-builder
**Repository Path**: ddgit123/llm-graph-builder
## Basic Information
- **Project Name**: llm-graph-builder
- **Description**: 项目来自：https://github.com/BinNong/llm-graph-builder
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 1
- **Forks**: 0
- **Created**: 2024-07-10
- **Last Updated**: 2025-04-07
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
## 项目本地启动（详细指导）:smile_cat:
#### 1. 安装neo4j :hamburger:
- 安装neo4j 5.21.0 （⚠️version>=5.15）
- Neo4j安装apoc插件
- [x] 下载[插件地址](https://github.com/neo4j/apoc/releases)
- [x] 以5.21.0版本为例，将插件[apoc-5.21.0-core.jar](https://github.com/neo4j/apoc/releases/download/5.21.0/apoc-5.21.0-core.jar)拷贝至neo4j安装目录中的plugins文件夹下，如图所示
- [x] 启动neo4j (启动命令在neo4j安装目录的bin文件夹中，因此切换到bin目录中)
```bash
./neo4j start
```
启动成功显示如下：
```html
Starting Neo4j.
Started neo4j (pid:17111). It is available at http://localhost:7474
There may be a short delay until the server is ready.
```
- [x] 验证apoc插件是否安装成功
- 浏览器访问http://localhost:7474，设定密码，进入neo4j可视化界面
- 输入cypher
```cypher
return apoc.version()
```
- 安装成功显示如下:
------
#### 2. 准备前端环境 :walking_man:
- 安装node.js (version >20) :package:
- 安装yarn
⚠️
- 在**frontend**文件夹下创建配置文件**.env**,配置文件内容如下：
```yaml
#后端开启的端口，默认是8000
BACKEND_API_URL="http://localhost:8000"
BLOOM_URL="https://workspace-preview.neo4j.io/workspace/explore?connectURL={CONNECT_URL}&search=Show+me+a+graph&featureGenAISuggestions=true&featureGenAISuggestionsInternal=true"
REACT_APP_SOURCES="local"
LLM_MODELS="智谱,百川,月之暗面,通义千问,深度求索,零一万物,Diffbot,OpenAI GPT 3.5,OpenAI GPT 4o"
ENV="DEV"
TIME_PER_CHUNK=4
TIME_PER_PAGE=50
CHUNK_SIZE=5242880
GOOGLE_CLIENT_ID=""
```
:facepunch:可以根据自己的需求，自行修改，也可以使用默认配置
------
#### 3. 启动前端 :leaves:
```bash
cd frontend
yarn
yarn run dev
```
运行成功显示如下：
使用浏览器访问
```html
http://localhost:5173/
```
------
#### 4. 后端配置 :dango:
- 在**backend**文件夹下创建配置文件**.env**，配置内容如下：
只需填写API key :smiley:
```yaml
OPENAI_API_KEY = ""
#智普ai
ZHIPUAI_API_KEY = "填写你的api key"
ZHIPUAI_API_URL = "https://open.bigmodel.cn/api/paas/v4/"
#通义千问
QWEN_API_KEY = "填写你的api key"
QWEN_API_URL = "https://dashscope.aliyuncs.com/compatible-mode/v1"
#百川
BAICHUAN_API_KEY = "填写你的api key"
BAICHUAN_API_URL = "https://api.baichuan-ai.com/v1/"
#月之暗面
MOONSHOT_API_KEY = "填写你的api key"
MOONSHOT_API_URL = "https://api.moonshot.cn/v1"
#deepseek
DEEPSEEK_API_KEY = "填写你的api key"
DEEPSEEK_API_URL = "https://api.deepseek.com"
#零一万物
LINGYIWANWU_API_KEY = "填写你的api key"
LINGYIWANWU_API_URL = "https://api.lingyiwanwu.com/v1"
DIFFBOT_API_KEY = ""
GROQ_API_KEY = ""
#使用从modelscope社区提供的embedding模型
EMBEDDING_MODEL = "iic/nlp_gte_sentence-embedding_chinese-base"
IS_EMBEDDING = "true"
KNN_MIN_SCORE = "0.94"
# Enable Gemini (default is False) | Can be False or True
GEMINI_ENABLED = False
# Enable Google Cloud logs (default is False) | Can be False or True
GCP_LOG_METRICS_ENABLED = False
NUMBER_OF_CHUNKS_TO_COMBINE = 6
UPDATE_GRAPH_CHUNKS_PROCESSED = 20
NEO4J_URI = ""
NEO4J_USERNAME = ""
NEO4J_PASSWORD = ""
NEO4J_DATABASE = ""
AWS_ACCESS_KEY_ID = ""
AWS_SECRET_ACCESS_KEY = ""
LANGCHAIN_API_KEY = ""
LANGCHAIN_PROJECT = ""
LANGCHAIN_TRACING_V2 = ""
LANGCHAIN_ENDPOINT = ""
GCS_FILE_CACHE = "" #save the file into GCS or local, SHould be True or False
```
------
#### 5. 后端启动 :ear_of_rice:
- 安装依赖：
```bash
pip install -r requirements.txt
```
- 启动程序（两种方式）, 后端程序在backend文件夹下
- [x] 命令行启动
```bash
uvicorn score:app --reload
```
- [x] 在pycharm或者vscode等ide中，运行score.py
成功运行如下：
------
#### 6. 回到前端即可使用本项目:earth_africa:
以上步骤顺利执行之后，即可回到前端进行操作
