2.3 KiB
rag-astradb
This template will perform RAG using Astra DB (AstraDB
vector store class)
Environment Setup
An Astra DB database is required; free tier is fine.
- You need the database API endpoint (such as
https://0123...-us-east1.apps.astra.datastax.com
) ... - ... and a token (
AstraCS:...
).
Also, an OpenAI API Key is required. Note that out-of-the-box this demo supports OpenAI only, unless you tinker with the code.
Provide the connection parameters and secrets through environment variables. Please refer to .env.template
for the variable names.
Usage
To use this package, you should first have the LangChain CLI installed:
pip install -U "langchain-cli[serve]"
To create a new LangChain project and install this as the only package, you can do:
langchain app new my-app --package rag-astradb
If you want to add this to an existing project, you can just run:
langchain app add rag-astradb
And add the following code to your server.py
file:
from astradb_entomology_rag import chain as astradb_entomology_rag_chain
add_routes(app, astradb_entomology_rag_chain, path="/rag-astradb")
(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_TRACING_V2=true
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 http://127.0.0.1:8000/docs We can access the playground at http://127.0.0.1:8000/rag-astradb/playground
We can access the template from code with:
from langserve.client import RemoteRunnable
runnable = RemoteRunnable("http://localhost:8000/rag-astradb")
Reference
Stand-alone repo with LangServe chain: here.