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Quick Start Guide

Prerequisites

Backend Setup

  1. Navigate to backend directory:
cd backend
  1. Create virtual environment:
python -m venv venv
venv\Scripts\activate  # Windows
# source venv/bin/activate  # Linux/Mac
  1. Install dependencies:
pip install -r requirements.txt
  1. Create .env file:
copy .env.example .env

Then edit .env and add your OpenRouter API key:

OPENROUTER_API_KEY=your_actual_api_key_here
OPENROUTER_MODEL=meta-llama/llama-3.3-8b-instruct:free
GEMINI_API_KEY=your_gemini_api_key_here
DATABASE_URL=sqlite:///./sql_learning.db
  1. Initialize database:
python -c "from app.database import init_db; init_db()"
  1. Start backend server:
uvicorn app.main:app --reload

Backend will run on http://localhost:8000

Frontend Setup

  1. Navigate to frontend directory:
cd frontend
  1. Install dependencies:
npm install
  1. Start development server:
npm run dev

Frontend will run on http://localhost:3000

Features

🏠 Landing Page - Cheat Sheet

  • Comprehensive SQL reference with syntax and examples
  • Search and filter by category (DDL, DML, Constraints, etc.)
  • Copy-to-clipboard functionality
  • Syntax highlighting

🧠 Practice Section

  • 6 structured learning modules:
    1. Data Definition and Data Manipulation Language
    2. Constraints
    3. Single Row Functions
    4. Operators and Group Functions
    5. Sub Query, Views and Joins
    6. High Level Language Extensions
  • Adaptive difficulty (easy → medium → hard)
  • AI-powered evaluation and feedback
  • Progress tracking per module

📊 Analysis Section

  • Overall performance metrics
  • Progress charts and visualizations
  • Module-wise performance breakdown
  • Personalized learning recommendations
  • Recent attempts history
  • Strengths and improvement areas

API Documentation

Backend API is available at http://localhost:8000/docs (Swagger UI)

Key endpoints:

  • GET /api/cheatsheet - Get cheat sheet entries
  • GET /api/modules - Get learning modules
  • POST /api/practice/submit - Submit SQL answer for evaluation
  • GET /api/analysis/{user_id} - Get user analytics

User Flow

  1. Start → Landing page shows SQL cheat sheet
  2. Practice → Select a learning module
  3. Question → AI generates questions based on difficulty
  4. Submit → User enters SQL query
  5. Feedback → AI evaluates and provides detailed feedback
  6. Adapt → System adjusts difficulty based on performance
  7. Progress → Track improvement in Analysis section

Tech Stack

  • Frontend: React 18, Vite, Tailwind CSS, React Router
  • Backend: FastAPI, SQLite, Pydantic
  • AI: OpenRouter API (GPT-3.5-turbo)
  • Charts: Recharts
  • Syntax: React Syntax Highlighter

Development Notes

  • No authentication required for MVP
  • Simple user ID system (user_123) for demo
  • Questions generated dynamically by AI
  • Adaptive difficulty based on recent performance
  • Comprehensive progress tracking and analytics