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LearnMate 2.0

AI-assisted personalized learning platform with roadmap generation, gamification, and career guidance.


⚠️ Project Status: Stabilization Phase

This project is currently in a stabilization and hardening phase before archival.

  • ✅ Core features complete
  • 🔧 Accepting bug fixes and security patches
  • ❌ Not accepting new features
  • 📦 Will be archived after hardening

See CONTRIBUTING.md for contribution guidelines.


Overview

LearnMate is a multi-service web application that generates personalized learning roadmaps based on user assessments and career goals. It was developed as an academic project and is being prepared for clean archival.

Core Functionality

Feature Description
Roadmap Generation AI-generated learning paths based on assessments
Gamification XP, levels, streaks, and achievements
Career Guidance Recommendations based on performance
Authentication OAuth 2.0 (Google, GitHub) + JWT

Architecture

Frontend (React)  ─────►  Backend (Express)  ─────►  AI Service (Flask)
    :3000                     :5000                      :5001
                                │
                                ▼
                           MongoDB

For detailed architecture, see docs/ARCHITECTURE.md.


Tech Stack

Layer Technologies
Frontend React 18, Vite, TailwindCSS, Zustand
Backend Node.js, Express, MongoDB, Passport.js
AI Service Python, Flask, Google Gemini API

Getting Started

Prerequisites

  • Node.js v18+
  • Python 3.9+
  • MongoDB (local or Atlas)

Setup

# Clone
git clone https://github.com/dipak0000812/learnmate-2.0.git
cd learnmate-2.0

# Backend
cd learnmate-backend
cp .env.example .env  # Configure your secrets
npm install

# Frontend
cd ../learnmate-frontend
cp .env.example .env
npm install

# AI Service
cd ../AI-Model
cp .env.example .env  # Add Gemini API key
pip install -r requirements.txt

Run

# Terminal 1: Backend
cd learnmate-backend && npm run dev

# Terminal 2: Frontend
cd learnmate-frontend && npm start

# Terminal 3: AI Service
cd AI-Model && python app.py

Documentation

Document Description
ARCHITECTURE.md System design
DEPLOYMENT.md Deployment guide
SECURITY.md Security practices
SECRETS.md Secrets management

Contributing

This project follows a maintainer-led model. See:


License

MIT License — see LICENSE


Maintainer

Dipak Dhangar — Final decision authority


This is an academic project undergoing stabilization. It is not production-ready.