HugeGraph-AI

 1# 克隆仓库
 2git clone https://github.com/apache/incubator-hugegraph-ai.git
 3cd incubator-hugegraph-ai
 4
 5# 设置环境并启动服务
 6cp docker/env.template docker/.env
 7# 编辑 docker/.env 设置你的 PROJECT_PATH
 8cd docker
 9docker-compose -f docker-compose-network.yml up -d
10
11# 访问服务：
12# - HugeGraph Server: http://localhost:8080
13# - RAG 服务: http://localhost:8001

 1# 1. 启动 HugeGraph Server
 2docker run -itd --name=server -p 8080:8080 hugegraph/hugegraph
 3
 4# 2. 克隆并设置项目
 5git clone https://github.com/apache/incubator-hugegraph-ai.git
 6cd incubator-hugegraph-ai/hugegraph-llm
 7
 8# 3. 安装依赖
 9uv venv && source .venv/bin/activate
10uv pip install -e .
11
12# 4. 启动演示
13python -m hugegraph_llm.demo.rag_demo.app
14# 访问 http://127.0.0.1:8001

 1from hugegraph_llm.operators.graph_rag_task import RAGPipeline
 2
 3# 初始化 RAG 工作流
 4graph_rag = RAGPipeline()
 5
 6# 对你的图进行提问
 7result = (graph_rag
 8    .extract_keywords(text="给我讲讲 Al Pacino 的故事。")
 9    .keywords_to_vid()
10    .query_graphdb(max_deep=2, max_graph_items=30)
11    .synthesize_answer()
12    .run())

 1from hugegraph_llm.models.llms.init_llm import LLMs
 2from hugegraph_llm.operators.kg_construction_task import KgBuilder
 3
 4# 从文本构建知识图谱
 5TEXT = "你的文本内容..."
 6builder = KgBuilder(LLMs().get_chat_llm())
 7
 8(builder
 9    .import_schema(from_hugegraph="hugegraph")
10    .chunk_split(TEXT)
11    .extract_info(extract_type="property_graph")
12    .commit_to_hugegraph()
13    .run())

1from pyhugegraph.client import PyHugeClient
2# 连接 HugeGraph 并运行机器学习算法
3# 详细示例请参阅 hugegraph-ml 文档