Graph RAG

In this example, we will show how to use the Graph RAG framework in DB-GPT. Using a graph database to implement RAG can, to some extent, alleviate the uncertainty and interpretability issues brought about by vector database retrieval.

You can refer to the python example file DB-GPT/examples/rag/graph_rag_example.py in the source code. This example demonstrates how to load knowledge from a document and store it in a graph store. Subsequently, it recalls knowledge relevant to your question by searching for triplets in the graph store.

Install Dependencies

First, you need to install the dbgpt graph_rag library.

uv sync --all-packages \
--extra "base" \
--extra "proxy_openai" \
--extra "rag" \
--extra "storage_chromadb" \
--extra "dbgpts" \
--extra "graph_rag"

Prepare Graph Database

To store the knowledge in graph, we need an graph database, TuGraph is the first graph database supported by DB-GPT.

Visit github repository of TuGraph to view Quick Start document, follow the instructions to pull the TuGraph database docker image (latest / version >= 4.5.1) and launch it.

docker pull tugraph/tugraph-runtime-centos7:4.5.1
docker run -d -p 7070:7070  -p 7687:7687 -p 9090:9090 --name tugraph_demo tugraph/tugraph-runtime-centos7:latest lgraph_server -d run --enable_plugin true

The default port for the bolt protocol is 7687.

Download Tips:

There is also a corresponding version of the TuGraph Docker image package on OSS. You can also directly download and import it.

wget 'https://tugraph-web.oss-cn-beijing.aliyuncs.com/tugraph/tugraph-4.5.1/tugraph-runtime-centos7-4.5.1.tar' -O tugraph-runtime-centos7-4.5.1.tar
docker load -i tugraph-runtime-centos7-4.5.1.tar

TuGraph Configuration

Set variables below in configs/dbgpt-graphrag.toml file, let DB-GPT know how to connect to TuGraph.

[rag.storage.graph]
type = "TuGraph"
host="127.0.0.1"
port=7687
username="admin"
password="73@TuGraph"
enable_summary="True"
enable_similarity_search="True"

Then run the following command to start the webserver:

uv run python packages/dbgpt-app/src/dbgpt_app/dbgpt_server.py --config configs/dbgpt-graphrag.toml

Optionally, you can also use the following command to start the webserver: uv run python packages/dbgpt-app/src/dbgpt_app/dbgpt_server.py --config configs/dbgpt-proxy-openai.toml