HugeGraph-AI

hugegraph-ai provides Python clients for HugeGraph, graph machine learning tools, and LLM tools for knowledge graph construction and GraphRAG applications.

Apache License 2.0 · Ask DeepWiki

Modules

• hugegraph-llm: knowledge graph construction, GraphRAG, and natural-language graph queries.
• hugegraph-ml: reads graph data from HugeGraph and runs graph learning models.
• hugegraph-python-client: a Python SDK for managing schemas and graph data and running Gremlin queries.
• vermeer-python-client: a Python SDK for the Vermeer graph computing service.

The repository uses a uv workspace whose members are hugegraph-llm and hugegraph-python-client. hugegraph-ml and vermeer-python-client are editable path dependencies rather than workspace members. The current repository version is 1.7.0. The client source directory is named hugegraph-python-client, but its distribution name is hugegraph-python.

Requirements

• HugeGraph-AI root workspace: Python 3.10 or later; HugeGraph-LLM additionally requires a version below 3.12
• HugeGraph-ML: Python 3.10 or later
• PyPI hugegraph-python 1.5.0: Python 3.9 or later; current repository source uses Python 3.10 or later with the workspace
• Vermeer Python client: current source requires Python 3.10 or later, although package metadata still says >=3.9; see the client guide
• uv 0.7 or later
• HugeGraph Server 1.5.0 or later; the current workspace client rejects detectable older versions

Optional Dependency Groups

The root project declares one extra per module plus a few combined ones:

hugegraph-llm itself declares a vectordb extra that adds pymilvus and qdrant-client.

Deploy with Docker Compose

The repository includes a Compose file that starts both HugeGraph Server and the RAG service:

git clone https://github.com/apache/hugegraph-ai.git
cd hugegraph-ai
cp docker/env.template docker/.env
# Edit docker/.env and set PROJECT_PATH to the absolute path of this repository
touch hugegraph-llm/.env
# Set GRAPH_URL=server:8080 in hugegraph-llm/.env and supply matching Server credentials
cd docker
docker compose -f docker-compose-network.yml up -d

Default addresses:

• HugeGraph Server: http://localhost:8080
• RAG service and Web UI: http://localhost:8001

Start the RAG Service from Source

git clone https://github.com/apache/hugegraph-ai.git
cd hugegraph-ai
uv sync --extra llm
source .venv/bin/activate
cd hugegraph-llm
python -m hugegraph_llm.demo.rag_demo.app

uv sync creates .venv at the repository root. Installing from the root resolves workspace members and path dependencies together. The repository does not track uv.lock; uv sync resolves the declarations and version constraints in pyproject.toml.

Install ML Dependencies

cd hugegraph-ai
uv sync --extra ml
source .venv/bin/activate
cd hugegraph-ml/src

Example scripts are under hugegraph-ml/src/hugegraph_ml/examples/.

Next Steps

• HugeGraph-LLM
• HugeGraph-LLM workflow
• Configuration reference
• REST API
• HugeGraph-ML
• Python client
• Vermeer Python Client