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Quick Start Guide

Prerequisites

  • Python 3.11+
  • Node.js 18+
  • Poetry (recommended) or pip
  • SQLite3

Installation Steps

  1. Clone and navigate to the project

    cd llm-sql-auditor

  2. Set up environment

    cp .env.example .env
# Edit .env and add OPENAI_API_KEY if you want LLM features

  3. Install Python dependencies

    poetry install
# OR
pip install -r requirements.txt

  4. Seed the demo database

    ./scripts/seed_demo.sh

  5. Start the application

    Option A: Use the dev script

    ./scripts/dev_up.sh

    Option B: Manual start

    # Terminal 1: Backend
poetry run uvicorn backend.app:app --reload --port 8000

# Terminal 2: Frontend
cd frontend
npm install
npm run dev

  6. Access the application

    • Frontend: Available on the configured port (default: 5173)
    • API: Available on the configured port (default: 8000)
    • API Docs: Available at /docs endpoint

Docker Quick Start

docker-compose up --build

Testing

# Run all tests
poetry run pytest

# Run with coverage
poetry run pytest --cov=backend --cov-report=html

Example Usage

Via Web UI

  1. Open the frontend application in your browser
  2. Paste schema DDL
  3. Enter SQL queries (separate with ---)
  4. Click "Analyze Queries"

Via API

curl -X POST <API_URL>/api/audit \
  -H "Content-Type: application/json" \
  -d '{
    "schema": "CREATE TABLE users (id INTEGER, email TEXT);",
    "queries": ["SELECT * FROM users;"],
    "dialect": "postgres"
  }'

Troubleshooting

  • Port already in use: Change ports in docker-compose.yml or use different ports
  • Database not found: Run ./scripts/seed_demo.sh
  • LLM features not working: Ensure OPENAI_API_KEY is set in .env
  • Frontend not connecting: Check that backend is running on port 8000