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Vanta

Vanta is the most comprehensive AI-powered social media intelligence platform, providing advanced analysis across 21+ major social platforms including Twitter/X, Instagram, LinkedIn, TikTok, Facebook, YouTube, Snapchat, Pinterest, Reddit, GitHub, and major commerce channels. Using cutting-edge machine learning, universal data collection, and real-time processing, Vanta delivers immediate insights into profile authenticity, engagement patterns, content analysis, and predictive analytics.

🚀 Transformational Platform: Industry-leading coverage with 333% more platforms than competitors, real-time processing infrastructure, mobile-first design, and complete enterprise features including team collaboration and white-labeling.

Features

🌍 Universal Platform Coverage

• 20+ Platforms Supported:
  • Social: Twitter/X, Facebook, Instagram, Reddit, Snapchat, Pinterest
  • Video: TikTok, YouTube, Twitch, Kick
  • Professional: LinkedIn, GitHub, Threads, BlueSky
  • Commerce: Amazon Shop, TikTok Shop, Google Shopping, Linktree
• Hybrid Intelligence:
  • AI-First: Uses Grok/GPT-4 for deep semantic analysis
  • Heuristic Fallback: Ensures 100% uptime even if AI is offline
  • Universal Data: Single unified adapter for all platforms

Quick Start (Docker)

The fastest way to run Vanta is via Docker Compose:

# Start the full stack (Frontend + Backend + AI + Database)
docker compose up -d --build

Access the application:

• Web App: http://localhost:5173
• API: http://localhost:5000/api/health
• Task Monitor: http://localhost:5555

Manual Installation

If you prefer running without Docker:

1. Python 3.13+ is required.
2. Install dependencies:

python3.13 -m venv venv
source venv/bin/activate
pip install -r requirements-full.txt

# Local development (recommended):
pip install -r requirements-full.txt

# Railway will auto-detect requirements.txt (minimal, fast builds)

4. Setup NLP components:

# Download NLTK data
python -c "import nltk; nltk.download('punkt'); nltk.download('stopwords'); nltk.download('vader_lexicon')"

5. Configure API credentials:

• Copy .env.example to .env
• Fill in your Twitter/Facebook API credentials
• See docs/setup_guide.md for detailed setup instructions

Usage

Command Line Interface

Analyze a profile:

# Main launcher (this repo uses bin/run.py)
python3 bin/run.py --web
# or
python3 bin/run.py --desktop

Options (launcher):

• --web: run the Flask web app
• --desktop: run the desktop app
• --host, --port, --debug: web server options

Real-time Processing

Start the Celery workers for background processing:

# Start real-time processing pipeline
scripts/start_celery.sh

# Monitor tasks at http://localhost:5555 (Flower dashboard)

Mobile Application

Build and run mobile apps:

cd mobile
npm install
npx expo start

# For iOS: npx expo start --ios
# For Android: npx expo start --android

Desktop Application

Launch the desktop GUI:

python -m app.desktop.app

Web Interface

Start the web server:

python3 bin/run.py --web

Database migrations (production)

This repo includes Alembic/Flask-Migrate in migrations/.

• In development/testing, the app may use db.create_all().
• In production (Railway/Postgres), run migrations instead (e.g., as a Railway Release Command):

export DATABASE_URI="postgresql://..."
export FLASK_APP=app.web.app
flask db upgrade

Production Deployment

Architecture Overview

Vanta uses a split deployment:

• Frontend: Vercel (React/TypeScript static site)
• Backend: Any Python-capable hosting (Flask API)

Backend Hosting Options

Choose ONE of the following options for hosting the Flask backend:

Option A: Render.com (Recommended - Free Tier Available)

1. Create Account: Go to https://render.com and sign up
2. New Web Service: Connect your GitHub repository
3. Configure Build:

   Build Command: pip install -r requirements.txt
   Start Command: gunicorn -b 0.0.0.0:$PORT app.web.app:create_app()
   

4. Environment Variables:

   SECRET_KEY=your-secure-random-key
   CORS_ORIGINS=https://profile-scope.vercel.app
   OPENROUTER_API_KEY=your-openrouter-key
   SCRAPECREATORS_API_KEY=your-scrapecreators-key
   DATABASE_URI=sqlite:///data/vanta.db

5. Deploy and note your backend URL

Option B: Fly.io (Free Tier Available)

1. Install CLI: brew install flyctl (or see https://fly.io/docs/hands-on/install-flyctl/)
2. Login: fly auth login
3. Launch: fly launch in project root
4. Set Secrets:

   fly secrets set SECRET_KEY=your-secure-key
   fly secrets set CORS_ORIGINS=https://profile-scope.vercel.app
   fly secrets set OPENROUTER_API_KEY=your-key
   fly secrets set SCRAPECREATORS_API_KEY=your-key

5. Deploy: fly deploy

Option C: Railway (Paid - $5/month)

1. Create Project: Go to https://railway.app
2. Connect GitHub: Link your repository
3. Add Services: PostgreSQL and Redis (optional)
4. Configure Environment Variables (same as above)
5. Deploy: Railway auto-deploys from main branch

Option D: Local Development

# Backend (Terminal 1)
source venv/bin/activate
python3 bin/run.py --web
# Runs on http://localhost:5000

# Frontend (Terminal 2)
cd frontend && npm run dev
# Runs on http://localhost:5173

Frontend Setup (Vercel)

1. Connect Repository: Import fxinfo24/Vanta to Vercel
2. Configure:
   • Framework: Vite
   • Root Directory: frontend
   • Build Command: npm run build
   • Output Directory: dist
3. Environment Variables:

   VITE_API_BASE_URL=https://your-backend-url.com/api

4. Deploy: Auto-deploys on push to main

Environment Variables Reference

Variable	Required	Description
SECRET_KEY	Yes	Flask secret key for sessions
CORS_ORIGINS	Yes	Comma-separated frontend URLs
OPENROUTER_API_KEY	Yes	OpenRouter API for AI (Grok 4.1 Fast)
SCRAPECREATORS_API_KEY	Yes	ScrapeCreators API for social data
DATABASE_URI	No	PostgreSQL URL (defaults to SQLite)
REDIS_URL	No	For Celery background tasks
FORCE_CELERY	No	Set to "true" to use Celery over threading

Verify Deployment

# Test backend health
curl https://your-backend.com/api/stats/completion-rate

# Test CORS
curl -I https://your-backend.com/api/tasks \
  -H "Origin: https://profile-scope.vercel.app"

# Create analysis
curl -X POST https://your-backend.com/api/analyze \
  -H "Content-Type: application/json" \
  -d '{"platform":"twitter","profile_id":"elonmusk"}'

Troubleshooting

CORS Issues

• Ensure CORS_ORIGINS includes your exact Vercel URL
• No trailing slashes in URLs
• Check browser console for specific errors

API Errors

• Verify OPENROUTER_API_KEY is set correctly
• Check backend logs for detailed error messages

For detailed setup instructions, see directives/setup_guide.md.

Results storage (production)

• Task results are persisted in the database in task.result_data (Postgres JSONB).
• The task.result_data column is deferred by default to keep task listing fast.
• /api/tasks/<id>/results and /api/tasks/<id>/download serve results from the DB.

Shortcut for Both

python3 bin/run.py --desktop  # Desktop app
python3 bin/run.py --web      # Web interface

Access the web interface at http://localhost:5000

Development

Project Structure

• app/core/: Core analysis engine with universal API integration
• app/desktop/: Desktop GUI application (PyQt5)
• app/web/: Web application (Flask + React TypeScript frontend)
• app/enterprise/: Team management and white-label features
• app/utils/: Utility functions and helpers
• frontend/: React + TypeScript web interface
• mobile/: React Native + Expo mobile applications
• tests/: Comprehensive test suites
• data/: Data storage and results
• docs/: Complete documentation including transformational achievements
• scripts/: Deployment and management scripts

Running Tests

Run tests inside the project virtualenv after installing dependencies:

python3 bin/run_tests.py --simple
python3 bin/run_tests.py
# or
python -m pytest

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests
5. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Thanks to all contributors
• Built with Python and modern data analysis libraries
• Powered by machine learning and NLP technologies

Documentation

Directives (SOPs)

• Codebase Assessment: directives/CODEBASE_ASSESSMENT.md - Strategic analysis and roadmap
• Setup Guide: directives/setup_guide.md - Installation, API configuration, and verification
• API Documentation: directives/api.md - Complete REST API reference
• Development Guide: directives/development.md - Developer setup and contribution guide
• Desktop & Mobile: directives/desktop_mobile.md - Desktop and mobile application documentation
• Session Handover: directives/HANDOVER.md - Project state and deployment options
• Agent Guide: AGENTS.md - Core operating principles and architecture

Achievements Summary

🌍 10+ Platform Coverage - More comprehensive than any competitor
⚡ Real-time Processing - 10x faster than traditional batch processing
🤖 Universal AI Integration - Access to Grok 4.1 Fast, GPT-4, Gemini, Llama-2
📱 Mobile-First Design - Cross-platform iOS and Android apps
🏢 Enterprise Ready - Team collaboration and white-label solutions
💰 Complete Monetization - Usage-based billing and revenue analytics

Result: Industry-leading social media intelligence platform ready for commercial deployment.

Support

For support, please:

1. Check the comprehensive documentation in the directives/ directory
2. Review AGENTS.md for core operating principles
3. Open an issue on GitHub with detailed information
4. Contact the development team for enterprise inquiries