1. Navigate to the directory where the main.py file is located.
2. Enter uvicorn main:app --reload in the terminal.
3. Click on the address uvicorn is running on.

Endpoints

There are 3 separate POST endpoints for

1. uploading the csv file
   @app.post("/upload/")

2. train the model on the data
   @app.post("/train/")

3. make predictions on unseen data
   @app.post("/predict/")

I have also added a rate limiter that limits the number of processing requests, currently set at 2 requests per minute.
@limiter.limit("2/minute")

Homepage

FastAPI serves a plain HTML page, to upload the Boston.csv file, then select a visualization type. Clicking on submit redirects to another page with the visualization. The visualization is saved to disk in static folder with a date and timestamp.

Visualization page

This page contains a table of some regression coefficients along with the corresponding visualization. This example shows a heatmap.

Histogram

This example shows a histogram of medv values.