LibreTranslate/CONTRIBUTING.md

Contributing

If you want to make changes to the code, you can build from source, and run the API.

Build Dependencies

• cmake

Debian / Ubuntu

sudo apt-get install cmake

Fedora / RHEL

sudo dnf install cmake

Getting Started

Install hatch to manage the projects dependencies and run dev scripts:

pipx install hatch

Clone the repository:

git clone https://github.com/LibreTranslate/LibreTranslate.git
cd LibreTranslate

Run in development:

hatch run dev --debug

Then open a web browser to http://localhost:5000

You can also start a new shell in a virtual environment with libretranslate installed:

hatch shell
libretranslate [args]
# Or
python main.py [args]

You can still use pip install -e ".[test]" directly if you don't want to use hatch.

Run the tests

Run the test suite and linting checks:

hatch run test

To display all print() when debugging:

hatch run test -s

You can also run the tests on multiple python versions:

hatch run all:test

Run with Docker

Linux/macOS: ./run.sh [args] Windows: run.bat [args]

Then open a web browser to http://localhost:5000

Build with Docker

docker build -f docker/Dockerfile [--build-arg with_models=true] -t libretranslate .

If you want to run the Docker image in a complete offline environment, you need to add the --build-arg with_models=true parameter. Then the language models are downloaded during the build process of the image. Otherwise, these models get downloaded on the first run of the image/container.

Run the built image:

docker run -it -p 5000:5000 libretranslate [args]

Or build and run using Docker Compose:

docker compose up -d --build

Feel free to change the docker-compose.yml file to adapt it to your deployment needs, or use an extra docker-compose.prod.yml file for your deployment configuration.

The models are stored inside the container under /home/libretranslate/.local/share and /home/libretranslate/.local/cache. Feel free to use volumes if you do not want to redownload the models when the container is destroyed. To update the models, use the --update-models argument.

FAQ

Externally Managed Environment

Some users may encounter the following error while installing packages:

error: externally-managed-environment

× This environment is externally managed
╰─> To install Python packages system-wide, try apt install
    python3-xyz, where xyz is the package you are trying to
    install.

    …

This occurs when your operating system depends on and manages Python for core functionality. In this case, you should install and setup venv (virtual environments) to manage project dependencies.

This prevents pip packages from being installed system-wide. This way, there are no risks of pip packages conflicting between multiple projects or the operating system.

References:

• Python venv documentation