E.D.G.E (Early Detection & Guidance Engine)

E.D.G.E is a student wellbeing and academic performance platform that combines a React frontend, Node/Express backend, and a Python ML service to predict burnout risk and support timely interventions.

What This Repo Contains

• Frontend (React + Vite) with role-based dashboards and feature pages.
• Backend (Node.js + Express) with 157+ REST endpoints and MongoDB models.
• ML service (Flask + scikit-learn) for burnout risk prediction.

Quick Start

Prerequisites

• Node.js 18+
• MongoDB 5+
• Python 3.9+

Install

npm install
cd server
npm install
cd ../ml_service
pip install -r requirements.txt

Configure

Create server/.env:

PORT=5000
MONGO_URI=mongodb://localhost:27017/edge
JWT_SECRET=your-super-secret-key-change-this
ML_SERVICE_URL=http://localhost:5001
NODE_ENV=development

Create .env (frontend):

VITE_API_URL=http://localhost:5000/api
VITE_ML_SERVICE_URL=http://localhost:5001

Create ml_service/.env:

PORT=5001

Run

# Terminal 1: MongoDB
mongod

# Terminal 2: Backend
cd server
npm run dev

# Terminal 3: ML Service
cd ml_service
python train.py
python app.py

# Terminal 4: Frontend
npm run dev

Test Credentials

• Admin: admin@edge.com / Admin123456
• Mentor: prof.johnson@edge.com / Prof123456
• Student: john@student.com / John123456

Documentation

All documentation has been consolidated into a single file:

• SYSTEM_DOCUMENTATION.md

Project Structure

src/
  components/
  pages/
  sections/
  styles/
server/
  src/
ml_service/
  models/