Fake-Detect Servers

Contains Flask and ASP.NET backend implementations for Fake Social Detection AIML mini project. Currently, only the Flask implementation is added. The reason for implementing with Flask is that ASP.NET isn't learned by any of the developers involved, and having a simple Flask implementation will help make the development quick when the developers eventually start building the ASP.NET backend. However only the /predict route is implemented in the current versions.

Flask is developed with Python 3.11.3. The code's requirements are present in flask-server/requirements.txt.

Click here to see the front-end code-base of this project on Github.

Routes to build in the backend:

1. /predict: (implemented)
   
   1. Page that takes inputs from user, predicts genuineness using the pre-trained model, and returns the prediction back to the user.
   2. (Feature Addition): Update this page to accept not only the 8 account details individually, but also a flag (option). When this option is set by the front-end app, the model should run a `test.csv` test-set and return it's results.
2. /dataset:
   Page that displays the training dataset.
3. /graph:
   Page that displays the training-accuracy & loss graph to the user.