Create python virtual environment and install dependencies
python -m venv .venv
source ./venv/bin/activate
pip install -r requirements.txt
Dataset are saved into file data/dataset.py so it is loaded from training program train.py
./train.sh
It will use 'data/dataset.py' to create pre-trained model
./start_classifiers.py
docker build . -t classy-ai
docker run -dit -p 7000:7000 classy-ai
docker exec -it <container-name> bash
./ask.sh spacy ./test/temperature.json
or
curl -s -X POST -H "Content-Type: application/json" http://127.0.0.1:7000/spacy -d '[{"text": "How cold is it in my room?"}]'