EduSmart

The system's overall goal is to simplify tutors' interactions with their students and make it easier for them to assess their pupils' performance using a cutting-edge AI model that can not only generate tests based on subject content, but also help match and pair students with the appropriate teacher for such best customizable and personally tailored teaching learning experience.

Technology stack

• Frontend -ReactJS, Redux state management
• Backend - NodeJS, Flask
• ML - NLP tools

Installation and usage

Frontend

• Navigate into the frontend folder
• Run yarn or npm install
• After the insatllation is over , run yarn start to start the server.Open browser and navigate to http://localhost:3000

Backend

• Create .env file (.env -sample has been given as reference) and mention the url of the hosted apis and MongoDB url in the variables
• Navigate into the backend folder
• Run yarn or npm install
• After the insatllation is over , run yarn start to start the server

NLP apis

• Run the cells of jupyter notebooks given in the nlp folders and copy-paste the ngrok urls in the .env files