GO_LIVE_CHECKLIST.md

StudioBot.ai - Go Live Checklist

This guide covers everything needed to take StudioBot.ai from mock/development to production.

✅ Completed Items

Frontend Implementation

• Login/Register pages with demo mode
• Dashboard with stats and quick actions
• Video Upload (both direct file and URL)
• Video List with filtering
• Video Detail with clips display
• Clip Manager with search and filtering
• Short Manager with mock data
• Platform Manager for social connections
• Analytics dashboard with charts
• Responsive sidebar navigation
• Logo integration support
• Favicon and page title

Backend Implementation

• Express.js API with TypeScript
• SQLite database
• User authentication
• Video upload (URL and direct file)
• Multer file upload middleware
• Basic video analysis structure
• Clips and shorts database schema

🔧 Next Steps - To Go Live

1. Logo Integration

Priority: HIGH Status: Ready (just need to add files)

• Save your logo images to client/public/:
  • logo.png - Full logo with text (for sidebar when open)
  • logo-icon.png - Icon only (for sidebar when collapsed) - Optional
  • favicon.ico - Browser tab icon - Optional

Action: Place your logo files in the client/public folder and restart the dev server.

2. AI Integration

Priority: HIGH Status: Mock implementation in place

Current state: Mock analysis that returns errors (expected)

Options:

1. OpenAI API - Use GPT-4 Vision for video analysis
2. Google Cloud Video AI - Specialized for video analysis
3. AWS Rekognition - Video analysis and transcription
4. AssemblyAI - Video transcription and sentiment
5. Custom ML Model - Host your own model

Files to update:

• src/services/video.service.ts - Replace mock analyzeVideo() method
• src/config/ai.config.ts (NEW) - Add AI service configuration
• .env - Add API keys

Example structure:

// src/services/video.service.ts
async analyzeVideo(filePath: string): Promise<VideoAnalysis> {
  // 1. Extract audio/frames from video
  // 2. Transcribe audio
  // 3. Analyze sentiment
  // 4. Identify key moments
  // 5. Generate clips
  // 6. Return analysis
}

3. Video Processing

Priority: HIGH Status: Placeholder

Required:

• Install FFmpeg for video processing
• Implement clip extraction from videos
• Generate thumbnails
• Create video player support

Libraries:

• fluent-ffmpeg - FFmpeg wrapper for Node.js
• @ffmpeg-installer/ffmpeg - Auto-install FFmpeg

Files to create/update:

• src/services/ffmpeg.service.ts (NEW)
• package.json - Add dependencies

Actions needed:

npm install fluent-ffmpeg @ffmpeg-installer/ffmpeg
npm install --save-dev @types/fluent-ffmpeg

4. Platform Integrations

Priority: MEDIUM Status: UI ready, backend needed

OAuth integrations needed:

• YouTube Data API v3
• TikTok API
• Instagram Graph API
• Facebook Graph API
• Twitter API v2

Files to create:

• src/services/platforms/youtube.service.ts
• src/services/platforms/tiktok.service.ts
• src/services/platforms/instagram.service.ts
• src/routes/oauth.routes.ts
• src/config/oauth.config.ts

Environment variables needed:

YOUTUBE_CLIENT_ID=
YOUTUBE_CLIENT_SECRET=
TIKTOK_CLIENT_ID=
TIKTOK_CLIENT_SECRET=
INSTAGRAM_CLIENT_ID=
INSTAGRAM_CLIENT_SECRET=
# ... etc

5. Database Migration

Priority: MEDIUM Status: SQLite (development)

For production, consider:

• PostgreSQL (recommended for production)
• MySQL
• MongoDB (if you prefer NoSQL)

Migration path:

1. Create database schema scripts
2. Set up migration system (e.g., Prisma, TypeORM)
3. Export data from SQLite
4. Import to production database

Files to update:

• src/config/database.ts
• .env - Add production DB credentials

6. Authentication Enhancement

Priority: MEDIUM Status: Basic JWT auth

Improvements needed:

• Password reset flow
• Email verification
• Social login (Google, GitHub, etc.)
• Session management
• Rate limiting

Libraries to add:

• nodemailer - Email sending
• express-rate-limit - Rate limiting
• passport - Social auth

7. File Storage

Priority: MEDIUM Status: Local file system

For production:

• AWS S3
• Google Cloud Storage
• Azure Blob Storage
• Cloudinary (for videos)

Files to create:

• src/services/storage.service.ts
• Update src/middleware/upload.ts

8. Environment Configuration

Priority: HIGH Status: Basic .env

Production .env.example:

# Server
NODE_ENV=production
PORT=3000
API_URL=https://api.studiobot.ai

# Database
DATABASE_URL=postgresql://user:pass@host:5432/dbname

# JWT
JWT_SECRET=your-super-secret-key-change-this
JWT_EXPIRES_IN=7d

# AI Service
OPENAI_API_KEY=
# or
GOOGLE_CLOUD_API_KEY=

# File Storage
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
AWS_S3_BUCKET=
AWS_REGION=

# OAuth
YOUTUBE_CLIENT_ID=
YOUTUBE_CLIENT_SECRET=
YOUTUBE_REDIRECT_URI=

# Email
SMTP_HOST=
SMTP_PORT=
SMTP_USER=
SMTP_PASS=

# Client
CLIENT_URL=https://studiobot.ai

9. Deployment

Frontend Deployment Options:

1. Vercel (Recommended for React)

   • Connect GitHub repo
   • Auto-deploys on push
   • Free tier available

2. Netlify

   • Similar to Vercel
   • Good for static sites

3. AWS Amplify

   • Full AWS integration

4. Custom Server

   • Build: npm run build
   • Serve dist/ folder with Nginx

Backend Deployment Options:

1. Railway (Easiest)

   • Connect GitHub
   • Auto-deploy
   • Free tier

2. Heroku

   • Easy deployment
   • Free tier limited

3. AWS EC2/ECS

   • Full control
   • More complex setup

4. DigitalOcean App Platform

   • Good middle ground

5. Docker + VPS

   • Create Dockerfile
   • Deploy to any VPS

10. Testing

Priority: HIGH Status: No tests

Add testing:

• Unit tests (Jest)
• Integration tests (Supertest)
• E2E tests (Cypress/Playwright)

Files to create:

• client/src/__tests__/ - Frontend tests
• src/__tests__/ - Backend tests
• jest.config.js - Test configuration

11. Monitoring & Logging

Priority: MEDIUM

Add:

• Error tracking (Sentry, Rollbar)
• Analytics (Google Analytics, Mixpanel)
• Application monitoring (New Relic, Datadog)
• Logging service (Winston, Pino)

12. Security

Priority: HIGH

Checklist:

• HTTPS/SSL certificates
• Rate limiting on API endpoints
• Input validation and sanitization
• SQL injection prevention (use parameterized queries)
• XSS prevention
• CORS configuration
• Security headers (helmet.js)
• File upload validation (size, type)
• API key rotation
• Environment variables secured

Files to update:

• src/index.ts - Add helmet, rate limiting
• src/middleware/ - Add security middleware

13. Documentation

Priority: LOW

Create:

• API documentation (Swagger/OpenAPI)
• User guide
• Developer documentation
• Deployment guide

🚀 Quick Start to Production

Phase 1: Core Functionality (1-2 weeks)

1. Integrate AI service for video analysis
2. Implement FFmpeg for video processing
3. Set up production database
4. Configure file storage (S3/GCS)
5. Test end-to-end flow

Phase 2: Platform Features (1-2 weeks)

1. Implement OAuth for at least YouTube
2. Add video player to frontend
3. Implement clip export functionality
4. Test short creation and publishing

Phase 3: Polish & Deploy (1 week)

1. Add logo files
2. Security hardening
3. Performance optimization
4. Set up monitoring
5. Deploy to production

📝 Current Mock Data

These features have UI but need backend implementation:

1. Short Manager - Using static mock data
2. Platform Manager - Mock platform connections
3. Analytics - Mock statistics and charts
4. Video Player - Placeholder, needs real player
5. Clip Export - Button exists, no functionality

🔍 Testing the Current Build

Start Development Servers:

Backend:

npm run build
npm start

Server runs on: http://localhost:3000

Frontend:

cd client
npm run dev

Client runs on: http://localhost:5173

Test Flow:

1. Open http://localhost:5173
2. Click "Try Demo" to login
3. Upload a video (either URL or file)
4. Check Dashboard for stats
5. Navigate through all pages to verify UI
6. Check browser console for errors

📊 Current Status Summary

Feature	Frontend	Backend	Production Ready
Authentication	✅	✅	⚠️ Needs enhancement
Video Upload	✅	✅	✅
Video Analysis	✅	⚠️ Mock	❌ Needs AI
Clip Management	✅	✅	⚠️ Needs processing
Short Creation	✅	❌ Mock	❌
Platform Publishing	✅	❌	❌
Analytics	✅	❌ Mock	❌
Logo	⚠️ Ready	N/A	⚠️ Add files

💡 Recommended Next Actions

If you want to go live quickly (MVP):

1. Add your logo files (client/public/logo.png)
2. Integrate a simple AI service (OpenAI GPT-4V or AssemblyAI)
3. Implement basic FFmpeg processing for clips
4. Deploy backend to Railway
5. Deploy frontend to Vercel
6. Set up S3 for file storage
7. Test end-to-end

If you want full features:

1. Follow Phase 1-3 above
2. Implement all platform integrations
3. Add comprehensive testing
4. Set up monitoring and logging
5. Security audit
6. Performance optimization

📞 Support

For questions about implementation:

• Check existing documentation files in the repo
• Review API_REFERENCE.md for backend APIs
• Check ARCHITECTURE.md for system design

Good luck going live! 🚀