LMS — Learning Management System

A full-stack learning management system with AI-powered content generation. Teachers create courses with modules, lessons, and assignments; students enroll, submit work, and take quizzes. AI features automate syllabus generation, lesson content creation, and provide an in-course AI tutor chatbot.

Features

• Course Management — hierarchical course structure (courses → modules → lessons) with publish controls
• AI Syllabus Generation — generate full course structure from a text prompt
• AI Lesson Content — generate individual or bulk lesson content with one click
• AI Tutor — per-course chat sessions with full context of course material
• Quizzes — timed quizzes with auto-grading, multiple attempts, and score tracking
• Lab Projects — file-upload assignments with multi-file support
• Gradebook — teacher gradebook with per-student submission views
• Roles — student, teacher, and admin roles with full RBAC
• Dark Mode — system-aware theme with manual toggle
• Notifications — real-time notification bell with polling

Tech Stack

Layer	Technology
Framework	Next.js 16 (App Router)
UI	React 19, Tailwind CSS 4
Database	MongoDB with Mongoose 8
Auth	JWT (httpOnly cookies) + bcryptjs
Validation	Zod 4
AI Providers	OpenAI, Anthropic, Google Gemini, Groq, Cerebras
Testing	Jest 30, MongoDB Memory Server
Language	TypeScript 5 (strict mode)

Quick Start

Prerequisites

• Node.js 18+
• MongoDB (local or Atlas) — or use Docker (see below)

Setup

# Clone the repository
git clone <repo-url>
cd lms

# Install dependencies
npm install

# Configure environment
cp .env.example .env
# Edit .env — set MONGODB_URI, JWT_SECRET, and at least one AI provider key

# Seed demo data (optional)
npm run seed

# Start development server
npm run dev

Open http://localhost:3000 in your browser.

Demo Credentials (after seeding)

Role	Email	Password
Admin	admin@demo.com	password123
Teacher	teacher@demo.com	password123
Student	student@demo.com	password123

Docker

# Start MongoDB only (for local development)
docker compose up -d mongo

# Start full stack (MongoDB + production app)
docker compose --profile prod up

Environment Variables

See .env.example for all options. Key variables:

Variable	Required	Description
MONGODB_URI	Yes	MongoDB connection string
JWT_SECRET	Yes	Secret for signing JWT tokens
AI_PROVIDER	No	Default AI provider (openai, anthropic, groq, cerebras, gemini)
OPENAI_API_KEY	No*	OpenAI API key
ANTHROPIC_API_KEY	No*	Anthropic API key
GROQ_API_KEY	No*	Groq API key
CEREBRAS_API_KEY	No*	Cerebras API key
GEMINI_API_KEY	No*	Google Gemini API key
STORAGE_PROVIDER	No	local (default) or s3
EMAIL_PROVIDER	No	console (default), resend, sendgrid, or ses
APP_URL	No	Public URL for email links (default: http://localhost:3000)

* At least one AI provider key is required for AI features.

Scripts

npm run dev              # Start dev server
npm run build            # Build for production
npm start                # Start production server
npm test                 # Run tests
npm run test:watch       # Run tests in watch mode
npm run test:coverage    # Run tests with coverage
npm run lint             # Run ESLint
npm run seed             # Seed demo data
npm run migrate          # Run database migrations

Project Structure

app/
  (auth)/              # Login, register, password reset pages
  (dashboard)/         # Authenticated pages with sidebar layout
  api/                 # API route handlers
components/            # Reusable UI components
lib/
  ai/                  # AI providers, services, tier system
  auth/                # JWT, middleware, course ownership
  models/              # Mongoose schemas
  hooks/               # React hooks
  validation/          # Zod schemas
scripts/               # Seed, migrations
__tests__/             # Integration tests

License

MIT