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Iteratively generate schema candidates and revise them based on errors.

Environment Setup​

This template uses OpenAI function calling, so you will need to set the OPENAI_API_KEY environment variable in order to use this template.


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 basic-critique-revise

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

langchain app add basic-critique-revise

And add the following code to your file:

from basic_critique_revise import chain as basic_critique_revise_chain

add_routes(app, basic_critique_revise_chain, path="/basic-critique-revise")

(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/basic-critique-revise")

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