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Getting Started - Developer Guide

This guide will help you set up the development environment and start contributing to the AI-powered collaborative video editor.

Prerequisites

Required Software

  • Node.js (v18+) and npm/yarn
  • Python (3.9+) for AI services
  • Docker and Docker Compose
  • Git
  • PostgreSQL (14+)
  • Redis (6+)

Recommended

  • Go (1.19+) if using Go for backend
  • FFmpeg (4.4+) for video processing
  • CUDA (optional, for GPU acceleration)

Initial Setup

1. Clone the Repository

git clone https://github.com/shivansh-source/ambitious_project.git
cd ambitious_project

2. Install Dependencies

Backend

cd backend
npm install
# or if using Go:
# go mod download

Frontend

cd frontend
npm install

AI Services

cd ai-services
pip install -r requirements.txt
# or using poetry:
# poetry install

3. Environment Configuration

Create .env files in each service directory:

Backend .env

NODE_ENV=development
PORT=3000
DATABASE_URL=postgresql://user:password@localhost:5432/videdit
REDIS_URL=redis://localhost:6379
JWT_SECRET=your-secret-key
AWS_ACCESS_KEY_ID=your-key
AWS_SECRET_ACCESS_KEY=your-secret
S3_BUCKET=videdit-storage

Frontend .env

VITE_API_URL=http://localhost:3000
VITE_WS_URL=ws://localhost:3000

AI Services .env

MODEL_PATH=/path/to/models
REDIS_URL=redis://localhost:6379
GPU_ENABLED=false

4. Database Setup

# Start PostgreSQL (via Docker)
docker run -d \
  --name videdit-postgres \
  -e POSTGRES_PASSWORD=password \
  -e POSTGRES_DB=videdit \
  -p 5432:5432 \
  postgres:14

# Run migrations
cd backend
npm run migrate
# or: go run cmd/migrate/main.go

5. Start Development Servers

Using Docker Compose (Recommended)

# Start all services
docker-compose up

# Or start specific services
docker-compose up backend frontend

Manual Start

Terminal 1 - Backend:

cd backend
npm run dev

Terminal 2 - Frontend:

cd frontend
npm run dev

Terminal 3 - AI Services:

cd ai-services
python -m uvicorn main:app --reload

Terminal 4 - Redis:

docker run -p 6379:6379 redis:6

Development Workflow

Making Changes

  1. Create a feature branch
git checkout -b feature/your-feature-name
  1. Make your changes
# Edit files
# Add tests
# Update documentation
  1. Test your changes
# Backend tests
cd backend && npm test

# Frontend tests
cd frontend && npm test

# AI services tests
cd ai-services && pytest
  1. Commit and push
git add .
git commit -m "feat: add your feature description"
git push origin feature/your-feature-name
  1. Create pull request
  • Go to GitHub
  • Create PR from your branch to main
  • Request review

Code Style

JavaScript/TypeScript

  • Use ESLint and Prettier
  • Run: npm run lint
  • Auto-fix: npm run lint:fix

Python

  • Use Black and Flake8
  • Run: black . && flake8

Go

  • Use gofmt and golint
  • Run: go fmt ./... && golint ./...

Testing

Unit Tests

# Backend
npm test

# Frontend
npm test

# AI Services
pytest tests/

Integration Tests

npm run test:integration

E2E Tests

cd tests/e2e
npm run test:e2e

Project Structure Quick Reference

ambitious_project/
├── backend/              # Backend API services
│   ├── api/             # REST endpoints
│   ├── services/        # Business logic
│   └── models/          # Data models
├── frontend/            # Web application
│   └── src/
│       ├── components/  # React components
│       ├── pages/       # Application pages
│       └── store/       # State management
├── ai-services/         # AI/ML services
│   ├── video-analysis/  # Video analysis
│   ├── effects/         # AI effects
│   └── models/          # ML models
├── versioning/          # Version control engine
├── storage/             # File storage
├── infrastructure/      # Deployment configs
└── docs/               # Documentation

Common Tasks

Adding a New API Endpoint

  1. Create route in backend/api/routes/
  2. Add controller in backend/api/controllers/
  3. Add service logic in backend/services/
  4. Add tests in tests/backend/
  5. Update API documentation

Adding a New UI Component

  1. Create component in frontend/src/components/
  2. Add styles
  3. Add to Storybook (if applicable)
  4. Add tests
  5. Use in relevant pages

Adding a New AI Feature

  1. Create service in ai-services/
  2. Train/download ML model
  3. Create API endpoint
  4. Add to processing queue
  5. Integrate with backend
  6. Add UI controls

Running Specific Tests

# Single test file
npm test -- video.test.js

# With coverage
npm test -- --coverage

# Watch mode
npm test -- --watch

Debugging

Backend Debugging

# Node.js
node --inspect-brk server.js

# Attach VSCode debugger
# Use launch.json configuration

Frontend Debugging

  • Use React DevTools
  • Use Redux DevTools
  • Browser DevTools (Sources tab)

AI Services Debugging

# Python debugger
python -m pdb service.py

# Or use IPython
ipython

Troubleshooting

Port Already in Use

# Find process using port
lsof -i :3000

# Kill process
kill -9 <PID>

Database Connection Issues

# Check if PostgreSQL is running
docker ps | grep postgres

# Check logs
docker logs videdit-postgres

Video Processing Failures

# Check FFmpeg installation
ffmpeg -version

# Check logs
tail -f logs/video-processing.log

Additional Resources

Getting Help

  • Create an issue on GitHub
  • Join our Discord server
  • Check existing documentation
  • Ask in pull request comments