Skip to main content


This package uses Azure OpenAI to do retrieval using an agent architecture. By default, this does retrieval over Arxiv.

Environment Setup​

Since we are using Azure OpenAI, we will need to set the following environment 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 retrieval-agent

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

langchain app add retrieval-agent

And add the following code to your file:

from retrieval_agent import chain as retrieval_agent_chain

add_routes(app, retrieval_agent_chain, path="/retrieval-agent")

(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/retrieval-agent")

Help us out by providing feedback on this documentation page: