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This template converts user input into pirate speak. It shows how you can allow configurable_alternatives in the Runnable, allowing you to select from OpenAI, Anthropic, or Cohere as your LLM Provider in the playground (or via API).

Environment Setup​

Set the following environment variables to access all 3 configurable alternative model providers:



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 pirate-speak-configurable

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

langchain app add pirate-speak-configurable

And add the following code to your file:

from pirate_speak_configurable import chain as pirate_speak_configurable_chain

add_routes(app, pirate_speak_configurable_chain, path="/pirate-speak-configurable")

(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/pirate-speak-configurable")

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