A framework for building robust RL environments to train aligned AI.
Python
20
51 commits
updated Oct 7, 2026
See what people are saying
README
Karotte 🥕
Karotte is an open-source framework for building robust RL environments, made by Preference Model.
Learn about the why and what:
Documentation: karotte.dev
Install
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
Quick start
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.
Development
just lint
just test
just test-template default
Every merge to main is released. See
Developing Karotte.
License
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.
Third-party software in built images
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.
Similar repos
A framework for building robust RL environments to train aligned AI.
Python
20
51 commits
updated Oct 7, 2026
See what people are saying
README
Karotte 🥕
Karotte is an open-source framework for building robust RL environments, made by Preference Model.
Learn about the why and what:
Documentation: karotte.dev
Install
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
Quick start
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.
Development
just lint
just test
just test-template default
Every merge to main is released. See
Developing Karotte.
License
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.
Third-party software in built images
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.