Shortsmachine V2 Community

An automated content creation and upload system for YouTube Shorts, running on Raspberry Pi. Generates engaging short-form videos from multiple content sources including Reddit stories, news articles, Wikipedia facts, trending video clips, and viral shorts reposts.

🎬 Features

Content Generation

Reddit Stories: Narrated stories from r/nosleep, r/AITAH, and other subreddits with synchronized captions
Breaking News: AI-summarized news articles with professional narration
Wikipedia Facts: Educational content with fun facts and images
Inspirational Quotes: Beautiful quote overlays with scenic backgrounds
Trending Clips: Smart extraction of viral moments from YouTube videos using hybrid AI approach
Viral Reposts: Automatic reposting of high-performing YouTube Shorts

Advanced Video Creation

Professional TTS: OpenAI text-to-speech with multiple voice options
Word-Level Captions: Synchronized subtitles using Whisper transcription
Smart Cropping: Face detection for intelligent video framing
Quality Optimization: FFmpeg-enhanced encoding for maximum YouTube quality
Dynamic Backgrounds: Random background video/audio selection
Variable Playback Speed: Configurable speed multipliers (1.0x - 1.25x)

Automation

Systemd Integration: Runs as a service with automatic scheduling
Auto-Updates: Daily git pulls to keep code current
Smart Cleanup: Automatic file management to prevent storage overflow
Error Recovery: Robust retry logic and fallback mechanisms
Resource Management: Optimized for Raspberry Pi 4 constraints

📋 Requirements

Hardware

Raspberry Pi 4 (4GB+ RAM recommended)
32GB+ microSD card
Stable internet connection

Software

Ubuntu 24 or Raspberry Pi OS
Python 3.8+
FFmpeg
Git

API Keys

OpenAI API key (for TTS, Whisper, GPT-4)
YouTube Data API v3 credentials (OAuth 2.0)

🚀 Installation

Quick Setup

# Clone the repository
git clone https://github.com/nicksimpkins/shortsmachine-v2c.git
cd shortsmachine

# Run automated setup
chmod +x setup.sh
./setup.sh

The setup script will:

Install system dependencies (Python, FFmpeg, etc.)
Create Python virtual environment
Install Python packages
Create necessary directories
Install systemd services
Run system tests

Manual Setup

# 1. Install system dependencies
sudo apt update
sudo apt install -y python3 python3-venv python3-pip ffmpeg git \
    libjpeg-dev zlib1g-dev

# 2. Install Deno (for enhanced YouTube access)
curl -fsSL https://deno.land/install.sh | sh
export DENO_INSTALL="/home/$(whoami)/.deno"
export PATH="$DENO_INSTALL/bin:$PATH"

# 3. Create virtual environment
python3 -m venv venv
source venv/bin/activate

# 4. Install Python dependencies
pip install -r requirements.txt

# 5. Create directories
mkdir -p temp output backgrounds/video backgrounds/audio logs

# 6. Install systemd services
sudo cp youtube-shorts-automation.service /etc/systemd/system/
sudo cp youtube-shorts-automation.timer /etc/systemd/system/
sudo cp youtube-shorts-git-update.service /etc/systemd/system/
sudo cp youtube-shorts-git-update.timer /etc/systemd/system/
sudo systemctl daemon-reload

⚙️ Configuration

1. YouTube API Setup

Go to Google Cloud Console
Create a new project
Enable YouTube Data API v3
Create OAuth 2.0 credentials
Download client_secrets.json to project directory

2. OpenAI API Key

Edit config.py:

OPENAI_API_KEY = "sk-your-api-key-here"

Or set environment variable:

export OPENAI_API_KEY="sk-your-api-key-here"

3. Content Configuration

Edit config.py to customize:

# Select content types
CONTENT_TYPES = ["repost", "clips", "reddit", "news", "fun_fact", "quote"]
CONTENT_MODE = "random"  # or "sequential"

# Set content weights for random mode
CONTENT_WEIGHTS = {
    "repost": 50,
    "clips": 30,
    "reddit": 10,
    "news": 5,
    "fun_fact": 3,
    "quote": 2
}

# Configure upload schedule
UPLOAD_INTERVAL_HOURS = 1  # Upload every N hours

# Content-specific settings
REDDIT_MAX_CHARS = 1710  # ~2 minutes of narration
REDDIT_PLAYBACK_SPEED = 1.25  # Speed up playback

NEWS_MAX_CHARS = 850  # ~60 seconds
CLIPS_MIN_VIEWS = 25_000  # Minimum views for clip source
REPOST_MIN_VIEWS = 100_000  # Minimum views for repost

4. Background Media

Add your background videos and audio:

# Background videos (poker-background.mp4 is default)
cp your-video.mp4 backgrounds/video/

# Background audio (backgroundaudio1.m4a is default)
cp your-audio.m4a backgrounds/audio/

Enable random selection:

RANDOMIZE_BACKGROUNDS = True

🎯 Usage

Test Run

# Activate virtual environment
source venv/bin/activate

# Test with single video
python3 main.py once

# Test specific content type
python3 main.py once --type reddit
python3 main.py once --type clips
python3 main.py once --type news

List Available Content Types

python3 main.py --list-types

Start Automation Service

# Enable and start the timer
sudo systemctl enable youtube-shorts-automation.timer
sudo systemctl start youtube-shorts-automation.timer

# Check status
systemctl list-timers
sudo systemctl status youtube-shorts-automation.timer

Monitor Logs

# Live service logs
sudo journalctl -u youtube-shorts-automation.service -f

# Application logs
tail -f logs/automation_*.log

Manual Control

# Stop automation
sudo systemctl stop youtube-shorts-automation.timer

# Start automation
sudo systemctl start youtube-shorts-automation.timer

# Restart service
sudo systemctl restart youtube-shorts-automation.service

# Run one-time upload
sudo systemctl start youtube-shorts-automation.service

📁 Project Structure

shortsmachine-v2c/
├── main.py                          # Main orchestration
├── config.py                        # Configuration settings
├── setup.sh                         # Automated setup script
├── requirements.txt                 # Python dependencies
│
├── content_generators/              # Content generation modules
│   ├── __init__.py
│   ├── base_generator.py           # Abstract base class
│   ├── registry.py                 # Generator registry
│   ├── reddit_generator.py         # Reddit stories
│   ├── news_generator.py           # Breaking news
│   ├── fun_fact_generator.py       # Wikipedia facts
│   ├── quote_generator.py          # Inspirational quotes
│   ├── clips_generator.py          # Trending video clips
│   └── repost_generator.py         # Viral shorts reposts
│
├── video_creator.py                 # Video composition engine
├── youtube_uploader.py              # YouTube API integration
├── cleanup_manager.py               # File cleanup utilities
├── wikipedia_scraper.py             # Wikipedia content fetcher
├── llm_extractor.py                # LLM integration (OpenAI/Ollama)
│
├── test_system.py                   # System diagnostics
├── test_ollama.py                   # LLM testing
│
├── youtube-shorts-automation.service    # Systemd service
├── youtube-shorts-automation.timer      # Upload scheduler
├── youtube-shorts-git-update.service    # Auto-update service
├── youtube-shorts-git-update.timer      # Update scheduler
│
├── backgrounds/                     # Media assets
│   ├── video/                      # Background videos
│   └── audio/                      # Background music
│
├── temp/                           # Temporary files
├── output/                         # Generated videos
└── logs/                           # Application logs

🔧 System Tests

Run comprehensive diagnostics:

python3 test_system.py

This checks:

✓ Python package installation
✓ Directory structure
✓ FFmpeg availability
✓ LLM connectivity (OpenAI/Ollama)
✓ YouTube credentials
✓ Wikipedia API access

📊 Content Types Deep Dive

Reddit Stories

Duration: 30-180 seconds (configurable)
Subreddits: nosleep, AITAH, ScaryStories, etc.
Features: TTS narration, word-synced captions, dramatic pacing
Cost: ~$0.05 per video (OpenAI TTS + Whisper)

News Articles

Duration: ~60 seconds
Sources: BBC, CNN, Guardian RSS feeds
Features: GPT-4 summarization, professional narration
Cost: ~$0.10 per video (GPT-4 + TTS + Whisper)

Wikipedia Facts

Duration: ~30 seconds
Features: Educational content, article images, GPT-4/Ollama extraction
Cost: ~$0.05 per video (if using OpenAI)

Trending Clips

Duration: 45 seconds (configurable)
Approach: Hybrid - Most Replayed data + GPT-4 validation
Features: Smart segment selection, face detection cropping
Cost: ~$0.001 per video (GPT-4 validation optional)

Viral Reposts

Sources: Popular YouTube Shorts channels
Minimum Views: 1M+ (configurable)
Features: Automatic download and re-upload
Cost: $0 (no AI processing)

💡 Tips & Best Practices

Content Strategy

Mix Content Types: Use weighted random mode for variety
Monitor Performance: Track which content types perform best
Adjust Thresholds: Lower view requirements if struggling to find content
Schedule Wisely: Upload during peak hours for your audience

Resource Management

Storage: Keep cleanup settings aggressive on Pi
Processing: Avoid running multiple generators simultaneously
Network: Ensure stable connection for downloads/uploads
Temperature: Monitor Pi temperature during video encoding

Quality Optimization

Backgrounds: Use high-quality 1080x1920 videos
Audio: 192kbps AAC recommended
Encoding: crf=18-23 for best quality/size balance
Captions: Ensure good contrast with background

🐛 Troubleshooting

YouTube Blocking Downloads

# Update yt-dlp
pip install --upgrade yt-dlp

# Clear cookies (if using authentication)
rm -f ~/.cache/yt-dlp/cookies.txt

OpenAI API Errors

# Check API key
python3 -c "import config; print(config.OPENAI_API_KEY[:8])"

# Test connection
curl https://api.openai.com/v1/models \
  -H "Authorization: Bearer $OPENAI_API_KEY"

Service Won't Start

# Check service status
sudo systemctl status youtube-shorts-automation.service

# View recent logs
sudo journalctl -u youtube-shorts-automation.service -n 50

# Check permissions
ls -la /home/shortsmachine/shortsmachine-v2c

# Verify paths in service file
cat /etc/systemd/system/youtube-shorts-automation.service

FFmpeg Encoding Errors

# Verify FFmpeg installation
ffmpeg -version

# Test encoding
ffmpeg -i input.mp4 -c:v libx264 -crf 23 test_output.mp4

# Check available codecs
ffmpeg -codecs | grep h264

Memory Issues on Pi

# Check memory usage
free -h

# Monitor during encoding
watch -n 1 free -h

# Reduce parallel processing in config
# Lower video bitrates/quality if needed

📈 Performance & Costs

Raspberry Pi 4 Performance

Video Generation: 2-5 minutes per video
Upload Speed: Depends on internet (usually 1-2 min)
Total Cycle: ~5-10 minutes per video
Concurrent Limit: 1 video at a time recommended

API Costs (Approximate)

Reddit Story: $0.05 (TTS + Whisper)
News Article: $0.10 (GPT-4 + TTS + Whisper)
Wikipedia Fact: $0.05 (GPT-4-mini + TTS + Whisper)
Trending Clip: $0.001 (Optional GPT-4 validation)
Viral Repost: $0 (No AI processing)

Monthly Estimates (1 upload/hour)

720 videos/month
Mixed content: ~$30-40/month
Clips/Reposts only: ~$0-5/month

🔒 Security & Privacy

API Keys: Never commit to Git (use environment variables)
OAuth Tokens: Stored locally in token.pickle
Temporary Files: Automatically cleaned after upload
Source Attribution: Metadata includes original sources
Content Rights: Ensure compliance with copyright and fair use

🤝 Contributing

Contributions welcome! Areas for improvement:

Additional content generators
Better segment detection algorithms
Performance optimizations
Multi-language support
Advanced caption styling

📝 License

This project is for educational purposes. Ensure compliance with:

YouTube Terms of Service
OpenAI Usage Policies
Content creator rights and licensing
Copyright and fair use laws

🙏 Credits

Technologies Used:

yt-dlp - YouTube download
MoviePy - Video editing
OpenAI - TTS, Whisper, GPT-4
FFmpeg - Video encoding
Google YouTube API - Upload automation

📞 Support

For issues and questions:

Check existing logs in logs/ directory
Run python3 test_system.py for diagnostics
Review configuration in config.py
Open an issue with full error logs

Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
backgrounds		backgrounds
content_generators		content_generators
.gitignore		.gitignore
README.md		README.md
cleanup_manager.py		cleanup_manager.py
client_secrets.json		client_secrets.json
config.py		config.py
llm_extractor.py		llm_extractor.py
main.py		main.py
requirements.txt		requirements.txt
setup.sh		setup.sh
test_ollama.py		test_ollama.py
test_system.py		test_system.py
video_creator.py		video_creator.py
wikipedia_scraper.py		wikipedia_scraper.py
youtube-shorts-automation.service		youtube-shorts-automation.service
youtube-shorts-automation.timer		youtube-shorts-automation.timer
youtube-shorts-git-update.service		youtube-shorts-git-update.service
youtube-shorts-git-update.timer		youtube-shorts-git-update.timer
youtube_uploader.py		youtube_uploader.py

nicksimpkins/shortsmachine-v2c

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