Dependencies

(Mainly listed as shortcuts to documentation)

• FastAPI as the base for the backend part.
• Pydantic for conversion of untyped JSON to typed objects. And because FastAPI automatically supports it and gives you useful error messages if you mess up things.
• Vue for frontend, using native module support so no npm build step 🎉
• uvicorn to run the damn thing.

Paths

• data/train-parts is scanned for datasets
• filters should contain filter json (but that's not implemented yet, right now it just has a hard-coded FILTERS dict in code)

Installation for development

python3 -m venv .env
bash --init-file .env/bin/activate
pip install -r requirements.txt

mkdir -p data
mtdata get -l ara-eng -tr OPUS-elrc_2922-v1-ara-eng --compress -o data
mtdata get -l fra-eng -tr OPUS-elitr_eca-v1-eng-fra --compress -o data

cd frontend
npm clean-install
npm run build
cd ..

./main.py serve --reload

If you're doing frontend developemnt, try also running:

cd frontend
npm run dev

This will put vite in hot-reloading mode for easier javascript dev. All api requests will be proxied to the main.py serve running in 8000.

If you want to use LASER, you will also need to download its assets:

python -m laserembeddings download-models

Then go to http://127.0.0.1:8000/ for the "interface" or http://127.0.0.1:8000/docs for the API.