langchain/templates/rag-multi-index-router/README.md
Leonid Ganeline 163ef35dd1
docs: templates updated titles (#25646)
Updated titles into a consistent format. 
Fixed links to the diagrams.
Fixed typos.
Note: The Templates menu in the navbar is now sorted by the file names.
I'll try sorting the navbar menus by the page titles, not the page file
names.
2024-08-23 01:19:38 -07:00

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# RAG - multiple indexes (Routing)
A QA application that routes between different domain-specific retrievers given a user question.
## Environment Setup
This application queries PubMed, ArXiv, Wikipedia, and [Kay AI](https://www.kay.ai) (for SEC filings).
You will need to create a free Kay AI account and [get your API key here](https://www.kay.ai).
Then set environment variable:
```bash
export KAY_API_KEY="<YOUR_API_KEY>"
```
## Usage
To use this package, you should first have the LangChain CLI installed:
```shell
pip install -U langchain-cli
```
To create a new LangChain project and install this as the only package, you can do:
```shell
langchain app new my-app --package rag-multi-index-router
```
If you want to add this to an existing project, you can just run:
```shell
langchain app add rag-multi-index-router
```
And add the following code to your `server.py` file:
```python
from rag_multi_index_router import chain as rag_multi_index_router_chain
add_routes(app, rag_multi_index_router_chain, path="/rag-multi-index-router")
```
(Optional) Let's now configure LangSmith.
LangSmith will help us trace, monitor and debug LangChain applications.
You can sign up for LangSmith [here](https://smith.langchain.com/).
If you don't have access, you can skip this section
```shell
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:
```shell
langchain serve
```
This will start the FastAPI app with a server is running locally at
[http://localhost:8000](http://localhost:8000)
We can see all templates at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
We can access the playground at [http://127.0.0.1:8000/rag-multi-index-router/playground](http://127.0.0.1:8000/rag-multi-index-router/playground)
We can access the template from code with:
```python
from langserve.client import RemoteRunnable
runnable = RemoteRunnable("http://localhost:8000/rag-multi-index-router")
```