Skip to main content


This template will perform RAG using Apache Cassandra® or Astra DB through CQL (Cassandra vector store class)

Environment Setup

For the setup, you will require:

You may also use a regular Cassandra cluster. In this case, provide the USE_CASSANDRA_CLUSTER entry as shown in .env.template and the subsequent environment variables to specify how to connect to it.

The connection parameters and secrets must be provided through environment variables. Refer to .env.template for the required variables.


To use this package, you should first have the LangChain CLI installed:

pip install -U langchain-cli

To create a new LangChain project and install this as the only package, you can do:

langchain app new my-app --package cassandra-entomology-rag

If you want to add this to an existing project, you can just run:

langchain app add cassandra-entomology-rag

And add the following code to your file:

from cassandra_entomology_rag import chain as cassandra_entomology_rag_chain

add_routes(app, cassandra_entomology_rag_chain, path="/cassandra-entomology-rag")

(Optional) Let's now configure LangSmith. LangSmith will help us trace, monitor and debug LangChain applications. You can sign up for LangSmith here. If you don't have access, you can skip this section

export LANGCHAIN_API_KEY=<your-api-key>
export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"

If you are inside this directory, then you can spin up a LangServe instance directly by:

langchain serve

This will start the FastAPI app with a server is running locally at http://localhost:8000

We can see all templates at We can access the playground at

We can access the template from code with:

from langserve.client import RemoteRunnable

runnable = RemoteRunnable("http://localhost:8000/cassandra-entomology-rag")


Stand-alone repo with LangServe chain: here.

Was this page helpful?

You can also leave detailed feedback on GitHub.