Using Docker images for both production and development environments

[mir-am]

In #8, I published Docker images for using Type4Py locally on users' machines. This PR also creates Docker images to deploy Type4Py in both production and development environments. Specifically, it makes the following changes:

• The Type4Py server detects whether the Docker image is running in local mode or production mode based on given ENV vars.
• Creates a separate Docker file to build images that allows performing the model inference on GPUs.
• Adds GH workflows to build Docker images for production and dev. environments and also supporting CPU/GPU.
• Add a unit test to test the local model before publishing its Docker image in GH Action.
• A bash script to test all the Docker images for production, dev, local environments.
• Use one config file for both production and dev. envs.