RAG with Multiple Indexes (Fusion)
A QA application that queries multiple domain-specific retrievers and selects the most relevant documents from across all retrieved results.
This application queries PubMed, ArXiv, Wikipedia, and Kay AI (for SEC filings).
You will need to create a free Kay AI account and get your API key here. Then set environment variable:
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 rag-multi-index-fusion
If you want to add this to an existing project, you can just run:
langchain app add rag-multi-index-fusion
And add the following code to your
from rag_multi_index_fusion import chain as rag_multi_index_fusion_chain
add_routes(app, rag_multi_index_fusion_chain, path="/rag-multi-index-fusion")
(Optional) Let's now configure LangSmith. LangSmith will help us trace, monitor and debug LangChain applications. LangSmith is currently in private beta, you can sign up here. If you don't have access, you can skip this section
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:
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-multi-index-fusion/playground
We can access the template from code with:
from langserve.client import RemoteRunnable
runnable = RemoteRunnable("http://localhost:8000/rag-multi-index-fusion")