This example will show you how to create ebonite model object from trained sklearn model and then turn it into flask service or docker container with flask service.
First, run python model_train.py to train and save model to local repository.
Then, run either python start_service.py to run flask service, or python model_create_image.py to create and run docker container.
After that, you can run python client.py %some_number% %some_other_number% to call your model or go to http://localhost:9000/apidocs to view swagger UI
Alternatively you can run python smart_client.py %some_number% %some_other_number%. It calls your model in a more Pythonic HTTP-agnostic way via HTTPClient class.