🤖 AutoTube - Automated YouTube Shorts Factory

Fully automated YouTube Shorts creation system using n8n, AI image generation, and video processing

AutoTube is a complete automation pipeline for generating, creating, and publishing YouTube Shorts using AI. It combines n8n workflow automation, AI-powered script generation, dynamic image slideshows, text-to-speech, and video editing into one powerful system.

✨ Features

• 🎬 End-to-End Automation: From topic to published video, fully automated
• 🧠 AI Script Generation: Uses Ollama/LLaMA for engaging script writing
• 🎨 AI Image Slideshows: Generates multiple AI images per video using Pollinations.ai or Z-Image
• 🎞️ Professional Video Creation: Ken Burns zoom effects, crossfade transitions, text overlays
• 🔊 Text-to-Speech: OpenTTS for natural voiceovers
• 📤 YouTube Upload: Direct upload to YouTube with metadata
• 🐳 Docker-Based: All services containerized for easy deployment
• 🔄 n8n Workflow: Visual automation with error handling and monitoring

🏗️ Architecture

┌─────────────────────────────────────────────────────────────────┐
│                        AutoTube System                          │
├─────────────────────────────────────────────────────────────────┤
│                                                                 │
│  ┌──────────┐    ┌─────────┐    ┌──────────┐    ┌──────────┐    │
│  │   n8n    │──▶│ Ollama   │──▶│  Python  │──▶│ YouTube   │   │
│  │ Workflow │    │   AI    │    │ Video API│    │   API    │    │
│  └──────────┘    └─────────┘    └──────────┘    └──────────┘    │
│       │               │                │              │         │
│       │               │                │              │         │
│       ▼               ▼                ▼              ▼         │
│  ┌──────────┐    ┌─────────┐    ┌──────────┐    ┌──────────┐    │
│  │PostgreSQL│    │ OpenTTS │    │   AI     │    │  Redis   │    │
│  │    DB    │    │  Voice  │    │  Images  │    │  Cache   │    │
│  └──────────┘    └─────────┘    └──────────┘    └──────────┘    │
│                                                                 │
└─────────────────────────────────────────────────────────────────┘

System Components

Component	Purpose	Port
n8n	Workflow automation orchestrator	5678
Ollama	Local AI for script generation (LLaMA 3.1)	11434
OpenTTS	Text-to-speech conversion	5500
Python API	Video creation & AI image generation	5001
PostgreSQL	n8n database	5432
Redis	Caching layer	6379
FileBrowser	File management UI	8080

🚀 Quick Start

Prerequisites

• Docker Desktop (Windows/Mac) or Docker Engine (Linux)
• Docker Compose v2.0+
• Git
• 4GB RAM minimum (8GB recommended)
• 10GB free disk space

Installation

1. Clone the repository

   git clone https://github.com/Hritikraj8804/Autotube.git
   cd Autotube

2. Configure environment variables

   cd short_automation
   cp .env.example .env

   Edit .env and set:

   N8N_BASIC_AUTH_ACTIVE=true
   N8N_BASIC_AUTH_USER=your_email@example.com
   N8N_BASIC_AUTH_PASSWORD=your_secure_password
   N8N_ENCRYPTION_KEY=generate-a-random-key-here
   POSTGRES_PASSWORD=your_secure_db_password

3. Start the system

   Windows:

   START-ROBOT.bat

   Linux/Mac:

   cd short_automation
   docker-compose up -d

4. Access services

   • n8n Dashboard: http://localhost:5678
   • File Browser: http://localhost:8080
   • AI Server: http://localhost:11434

5. Import the workflow

   • Open n8n at http://localhost:5678
   • Click Workflows → Import from File
   • Select short_automation/workflows/autotube-complete.json
   • Activate the workflow

6. Download AI model

   docker exec youtube-ai ollama pull llama3.1:8b

📖 Usage

Creating Your First Video

1. Open n8n at http://localhost:5678
2. Find the AutoTube workflow and open it
3. Configure the Manual Trigger node with your video topic:

   {
     "topic": "Top 5 AI Tools in 2025"
   }

4. Click "Test Workflow" and watch the magic happen!

How It Works

1. Script Generation: AI generates a 30-second script with hook, content, and CTA
2. Image Creation: Multiple AI images are generated based on script sections
3. Voice Generation: Text-to-speech creates professional voiceover
4. Video Compilation: Images are assembled with transitions, zoom effects, and text overlays
5. YouTube Upload: Video is uploaded with title, description, and tags

Video Specifications

• Format: Vertical 9:16 (1080x1920)
• Duration: ~30 seconds (YouTube Shorts)
• FPS: 30
• Effects: Ken Burns zoom, crossfade transitions
• Audio: OpenTTS voice synthesis

⚙️ Configuration

Environment Variables

Create a .env file in the short_automation directory:

# n8n Authentication
N8N_BASIC_AUTH_ACTIVE=true
N8N_BASIC_AUTH_USER=your_email@example.com
N8N_BASIC_AUTH_PASSWORD=your_secure_password

# Encryption
N8N_ENCRYPTION_KEY=your-random-32-char-key

# Database
POSTGRES_USER=n8n
POSTGRES_PASSWORD=your_secure_db_password
POSTGRES_DB=n8n

# Optional: HuggingFace token for Z-Image (better quality)
HUGGINGFACE_TOKEN=your_hf_token_here

YouTube API Setup

1. Create a project in Google Cloud Console
2. Enable YouTube Data API v3
3. Create OAuth 2.0 credentials
4. Download credentials as client_secret_*.json
5. Place in short_automation/ directory (already gitignored)

AI Image Generation

AutoTube supports two AI image providers:

Pollinations.ai (Default - Free, Unlimited)

• No API key required
• Good quality
• Fast generation
• Already configured

Z-Image via HuggingFace (Better Quality)

• Requires free HuggingFace account
• Set HUGGINGFACE_TOKEN in .env
• Edit workflow to enable Z-Image

🛠️ Development

Project Structure

Autotube/
├── short_automation/
│   ├── docker-compose.yml      # Service definitions
│   ├── .env.example            # Environment template
│   ├── workflows/              # n8n workflow files
│   │   └── autotube-complete.json
│   ├── scripts/                # Python automation
│   │   ├── ai_generator.py     # AI image generation
│   │   ├── create_video.py     # Video creation
│   │   └── video_api.py        # Flask API server
│   ├── videos/                 # Generated content (gitignored)
│   └── data/                   # Persistent data (gitignored)
├── START-ROBOT.bat             # Windows start script
├── STOP-ROBOT.bat              # Windows stop script
├── TEST-ALL.bat                # Service testing script
├── docs/                       # Documentation
└── README.md                   # This file

Python API Endpoints

The Python video API runs on http://localhost:5001:

• GET /health - Health check
• POST /generate - Generate video
• GET /info - API information

Example Request:

curl -X POST http://localhost:5001/generate \
  -H "Content-Type: application/json" \
  -d '{
    "hook": "Did you know?",
    "content": "Amazing facts here",
    "cta": "Follow for more!",
    "title": "Cool Video",
    "useAiImages": true
  }'

Local Development

1. Install Python dependencies

   docker exec youtube-python pip install -r /scripts/requirements.txt

2. Test video generation

   docker exec youtube-python python /scripts/create_video.py

3. View logs

   docker-compose logs -f

🐛 Troubleshooting

Services won't start

# Check Docker is running
docker ps

# Restart all services
docker-compose down
docker-compose up -d

# Check logs
docker-compose logs

n8n won't connect

• Verify port 5678 is not in use
• Check .env file is configured correctly
• Wait 30 seconds after startup for initialization

AI model not found

docker exec youtube-ai ollama pull llama3.1:8b

Video generation fails

• Check Python container is running: docker ps
• Verify videos directory is writable
• Check logs: docker logs youtube-python

More troubleshooting

See docs/TROUBLESHOOTING.md for detailed solutions.

📚 Documentation

• Architecture Overview
• Detailed Setup Guide
• n8n Workflow Guide
• Python API Documentation
• Troubleshooting

🤝 Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

Quick Contribution Guide

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📜 License

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

🙏 Acknowledgments

• n8n - Workflow automation platform
• Ollama - Local AI inference
• Pollinations.ai - Free AI image generation
• OpenTTS - Text-to-speech engine
• MoviePy - Video editing library
• YouTube API - Video publishing

📞 Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions

🗺️ Roadmap

• Support for multiple AI models (GPT-4, Claude, Gemini)
• Advanced video editing (effects, filters)
• Thumbnail generation
• Multi-language support
• Scheduled posting
• Analytics dashboard
• Music integration
• Custom brand templates

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Made with ❤️ by the AutoTube team

Star ⭐ this repo if you find it useful!