LLM Academy

Interactive learning platform for AI prompt engineering — built for doctors, teachers, and other non-technical professionals who want to use AI effectively in their daily work. 23 hands-on exercises across 3 modules, no coding required.

Quick Start

# Backend
cd backend
cp ../.env.example .env    # add your OPENROUTER_API_KEY
pip install -r requirements.txt
uvicorn app.main:app --reload

# Frontend (separate terminal)
cd frontend
npm install
npm run dev

Open http://localhost:5173

Environment Variables

Copy .env.example to backend/.env and set:

Variable	Required	Description
OPENROUTER_API_KEY	Yes	Get free key at openrouter.ai/keys
SECRET_KEY	Yes	Random string for JWT signing
DATABASE_URL	No	Default: sqlite:///./llm_academy.db
CORS_ORIGINS	No	Default: http://localhost:5173

Project Structure

llm-academy/
  backend/          # Python/FastAPI
    app/
      routers/      # API endpoints (auth, llm, progress, exercises)
      services/     # Business logic (auth, llm proxy, progress)
      repositories/ # DB abstraction layer
      models/       # SQLAlchemy models
      schemas/      # Pydantic request/response schemas
    data/           # exercises.json
  frontend/         # React/Vite
    src/
      pages/        # Landing, Login, Register, Dashboard, Exercise, etc.
      components/   # NavBar, Btn, ExerciseCard, EvalResult, etc.
      services/     # API client (auth, llm, progress)
      constants/    # theme, exercises, models, modules, professions
      context/      # AuthContext
      hooks/        # useAuth, useProgress

API

Backend runs at http://localhost:8000. Swagger docs at /docs.

Endpoint	Auth	Purpose
POST /api/auth/register	No	Create account
POST /api/auth/login	No	Get JWT token
GET /api/auth/me	Yes	User profile + stats
POST /api/llm/chat	Yes	Proxy to LLM provider
POST /api/llm/evaluate	Yes	Evaluate user prompt
GET /api/progress	Yes	User's completed exercises
POST /api/progress/complete	Yes	Save exercise completion
GET /api/exercises	No	List all exercises

License

MIT