Train Server

FastAPI server to help in training the ML model and generate the HTML templates for Flask application over here

Procedure:

• The Flask application first pings the server with the dataset.
• The server trains the dataset based on the model specified by the user
• The server then pickles the model and sends it back to the Flask app
• The server then sends a request to generate the HTML file for the application.
• It generates the HTML based on the data given to it.
• Finally it zips up the HTML templates and sends it back to the user.

Setup

To set up this project, you require the following:

• Python (Preferably >=3.8)
• Pipenv
  • Can be installed with python -m pip install pipenv

Once all this is set up, just run:

$ pipenv shell
$ pipenv install

Finally, the server can be run by typing this: uvicorn main:app --reload

Putting reload is up to you.