An open source platform to annotate and label LLM data at scale
Anudesh is an open source platform to annotate Lare language models' data at scale, built with a vision to enhance digital presence of under-represented languages in India.
git clone --recurse-submodules /~https://github.com/AI4Bharat/Anudesh
git clone /~https://github.com/AI4Bharat/Anudesh-Backend.git
python3 -m venv
Activate the virtual environment. This ensures that the packages you install are isolated from the global Python environment.
source /bin/activate
pip install -r deploy/requirements-dev.txt
cp .env.example ./backend/.env
python backend/manage.py shell
# Import the utility function to generate a secret key.
>> from django.core.management.utils import get_random_secret_key
# Generate and print a new secret key.
>> get_random_secret_key()
docker-compose -f docker-compose-local.yml build
Run the containers in detached mode (-d flag). This will start up all the services defined in the Docker Compose file.
docker-compose -f docker-compose-local.yml up -d
The following steps are required only when you run the project for the first time or after making changes to the models.
# Check if there are any pending migrations.
docker-compose exec web python backend/manage.py makemigrations
# Apply all pending migrations to the database.
docker-compose exec web python backend/manage.py migrate
docker-compose exec web python backend/manage.py createsuperuser
docker-compose exec web python backend/manage.py runserver
git clone /~https://github.com/AI4Bharat/Anudesh-Frontend.git
cd Anudesh-Frontend
npm i --force
npm run dev