We use the pole dataset to demonstrate the building of a BioCypher knowledge graph and the facilitation of querying the graph using BioChatter and ChatGSE. The dataset is a public dataset from Manchester, U.K.
To start a local instance of the Neo4j database and ChatGSE, clone the repository and run the Docker compose setup. Docker needs to be installed and running on your machine.
⚠️ Important note: For using the OpenAI GPT model that is called from ChatGSE, you need to provide your OpenAI API key through the environment variableOPENAI_API_KEY. If you do not provide a key, the query generation will fail.
git clone https://github.com/biocypher/pole.git
cd pole
export OPENAI_API_KEY=sk-... # or add it to your .bashrc or .zshrc
docker compose up -d
The Docker compose workflow will take care of building the database, importing
and deploying in Neo4j, and starting the ChatGSE app. Given you have provided
your API key, you can now open the ChatGSE app in your browser at
http://localhost:8501. To query the knowledge graph,
navigate to the Knowledge Graph tab, set the database IP to deploy (the name
of the Docker service that runs the Neo4j database). Now you should be able to
see the query text interface. Entering a query and confirming with Enter will
generate a query and execute it on the database. The generated query and results
will be displayed in the space below the interface. You can modify the query and
rerun it (CMD+Enter on Mac, Ctrl+Enter on Windows) without having to call
the LLM again. To generate a new query, simply update the query text.
Some example queries:
where happened most crimeswho committed the most crimeswho knows people that committed many crimes while not being criminal themselves
You can also visit http://localhost:7474 to access the
Neo4j browser interface. It requires no authentication (simply press Connect)
and allows you to explore the database and run Cypher queries.