Karotte

Karotte is an open-source framework from Preference Model for building RL environments to train aligned AI. It is installed as a Python tool with uv and runs tasks against a model, writing a transcript of each run. The project is released under the MIT license.

What It Is

Karotte is a framework for creating and running RL environments. Users scaffold an environment from a template, define tasks and steps, and run them against a model. The repository describes it as a framework for building robust RL environments to train aligned AI.

How a Run Works

The quick start creates an environment from the default template with karotte create-env, syncs dependencies with uv, and prepares data with a setup script. karotte run then builds the image, runs the chosen task against a specified model (the example uses an Anthropic model via an API key), and writes the transcript to out/transcript.json. karotte dashboard out/ displays the transcript.

Runtimes and Setup

Karotte requires Python 3.12+ and uv. Runs go into a VM by default: Apple container on macOS and Firecracker on Linux, with docker or podman also supported. Images built from the templates are based on Amazon Linux 2023. The language-toolchains template installs additional language toolchains for the languages a user enables.

Licensing Notes

The framework is MIT licensed, and the bundled templates are MIT No Attribution, so environments created from them need no license notice. Built images contain third-party software under its own licenses, and anyone distributing a built image is responsible for complying with them.