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Show HN: Karotte, a framework for building robust RL envs

Preference Model released Karotte, an open-source framework for building robust reinforcement learning environments, installable via `uv tool install karotte` and requiring Python 3.12+. Karotte runs tasks in a VM by default — Apple `container` on macOS and Firecracker on Linux, with docker or podman also supported — and writes each run's transcript to `out/transcript.json` for viewing with `karotte dashboard out/`. The framework is MIT licensed, while its environment templates in `src/karotte/templates/` use MIT No Attribution (MIT-0), and every merge to `main` is released.

read1 min views1 publishedOct 7, 2026
Show HN: Karotte, a framework for building robust RL envs
Image: Michielbdejong (auto-discovered)

Karotte is an open-source framework for building robust RL environments, made by Preference Model.

Documentation: karotte.dev

Karotte needs Python 3.12+ and uv. Runs go into a VM by default: Apple container on macOS, Firecracker on Linux. docker or podman work too. See Installation and Runtimes for what each needs.

uv tool install karotte

Create an environment from the default template and run its example task:

karotte create-env my_env
cd my_env
uv sync --extra dev
uv run setup_data.py
export ANTHROPIC_API_KEY=...
uv run karotte run --task example-task --model anthropic/claude-opus-5-5

karotte run builds the image, runs the task, and writes the transcript to out/transcript.json. karotte dashboard out/ shows it. The quick start explains each step, and Writing tasks shows how to add your own.

just lint
just test
just test-template default

Every merge to main is released. See Developing Karotte.

Karotte is under the MIT license. The templates in src/karotte/templates/ are under MIT No Attribution (MIT-0), so environments created from them need no license notice.

Images built from the templates contain third-party software under its own licenses. They are based on Amazon Linux 2023. The language-toolchains template installs GPL and LGPL software (gcc, GnuCOBOL, GNU Prolog, Free Pascal, the libraries bundled with Julia, and others), Amazon Corretto (GPL-2.0 with the Classpath Exception) and Clojure (EPL-1.0) for the languages you enable. Mojo, off by default, has its own license terms; check them for the version you enable. If you distribute a built image, you're responsible for complying with the licenses of the software in it.

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