RAG LangChain template with Cassandra

A basic chain template showing the RAG pattern using a vector store on (CQL) Astra DB / Apache Cassandra®.

Setup:

You need:

• an Astra Vector Database (free tier is fine!). You need a Database Administrator token, in particular the string starting with AstraCS:...;
• likewise, get your Database ID ready, you will have to enter it below;
• an OpenAI API Key. (More info here, note that out-of-the-box this demo supports OpenAI unless you tinker with the code.)

Note: you can alternatively use a regular Cassandra cluster: to do so, make sure you provide the USE_CASSANDRA_CLUSTER entry as shown in .env.template and the subsequent environment variables to specify how to connect to it.

You need to provide the connection parameters and secrets through environment variables. Please refer to .env.template for what variables are required.

Running the chain

Within a LangChain app

Assuming you have already created the app (i.e. langchain app new MyApp; cd MyApp), this is what you'll need:

langchain app add --repo "hemidactylus/langserve_cassandra_entomology_rag" --branch main

Important: adjust the project's server.py as instructed in the output of the above.

Now, make sure all required environment variables are set, and run

langchain serve

that's it. You can now test the new endpoints by opening http://127.0.0.1:8000/docs, or visiting directly http://127.0.0.1:8000/cassandra_entomology_rag/playground/.

Suggestions:

• for a negative test, try Do birds have wings?
• for a positive test, try Do Odonata have wings?

Stand-alone

For a standalone usage (outside of langchain serve), clone this repo, cd to its root directory, ensure you set all environment variables, then launch:

poetry install
poetry run python main.py

Note: In a full application, the vector store might be populated in other ways than what done here. The populate step here is done for the demo RAG chains to sensibly work.