langchain/templates/cassandra-entomology-rag

RAG LangServe chain template

A basic chain template showing the RAG pattern using a vector store on 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.

Populate the vector store

Make sure you have the environment variables all set (see previous section), then, from this directory, launch the following just once:

poetry run bash -c "cd [...]/cassandra_entomology_rag; python setup.py"

The output will be something like Done (29 lines inserted)..

Note: In a full application, the vector store might be populated in other ways: this step is to pre-populate the vector store with some rows for the demo RAG chains to sensibly work.

Sample inputs

The chain's prompt is engineered to stay on topic and only use the provided context.

To put this to test, experiment with these example questions:

"Are there more coleoptera or bugs?"
"Do Odonata have wings?"
"Do birds have wings?"                <-- no entomology here!

Reference

Stand-alone repo with LangServe chain: here.