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🎬 Autonomous AI agent that transforms long-form videos into viral short-form content across YouTube Shorts, TikTok, and Instagram Reels using advanced AI analysis and automation.
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Transform long-form content into viral short clips across YouTube Shorts, TikTok, and Instagram Reels with AI-powered automation.
Quick Start • Features • Documentation • Contributing
Clippy is an intelligent video repurposing agent that automatically transforms long-form content into engaging short clips optimized for modern social media platforms. Using advanced AI analysis and offline processing, Clippy identifies viral moments and creates platform-specific content with subtitles, effects, and optimized formatting.
Selected from shared topics, language and repository description—not editorial ratings.
oguzemirtopuz /
🎬 An autonomous AI content engine that conceptualizes short-form videos, splits high-action scenes using computer vision, and renders "Top 5" compilations via FFmpeg.
64/100 healthEnsure you have the following installed:
# Required software
Python 3.10+
FFmpeg
Git
Clone and setup the repository
git clone <repository-url>
cd clippy
pip install -r requirements.txt
Download AI models (automatic on first run)
python -c "from src.ai.llm_analyzer import LLMAnalyzer; LLMAnalyzer({'model_name': 'orca-mini-3b-gguf2-q4_0.gguf'})"
Configure your settings
cp config.yaml.example config.yaml
# Edit config.yaml with your platform credentials
python main.py --url "https://youtube.com/watch?v=VIDEO_ID"
Create videos.txt:
https://youtube.com/watch?v=VIDEO1
https://youtube.com/watch?v=VIDEO2
https://youtube.com/watch?v=VIDEO3
Run batch processing:
python main.py --batch videos.txt
python main.py --scheduler
python main.py --analytics
Configure Clippy by editing the config.yaml file:
video:
download_quality: "720p"
clip_duration_min: 30
clip_duration_max: 60
platforms:
youtube:
enabled: true
client_id: "your-client-id"
client_secret: "your-client-secret"
tiktok:
enabled: true
username: "your-username"
password: "your-password"
instagram:
enabled: true
username: "your-username"
password: "your-password"
ai:
model_name: "orca-mini-3b-gguf2-q4_0.gguf"
highlight_threshold: 0.7
clippy/
├── main.py # Entry point and CLI
├── config.yaml # Configuration file
├── src/
│ ├── core/ # Core processing modules
│ │ ├── video_processor.py # Video download & transcription
│ │ ├── content_analyzer.py # AI-powered content analysis
│ │ └── platform_manager.py # Multi-platform coordination
│ ├── ai/ # AI and machine learning
│ │ ├── llm_analyzer.py # Offline LLM analysis
│ │ ├── engagement_tracker.py # Performance analytics
│ │ └── optimization_engine.py # Strategy optimization
│ ├── platforms/ # Platform-specific handlers
│ │ ├── youtube_shorts.py # YouTube Shorts API
│ │ ├── tiktok_poster.py # TikTok automation
│ │ └── instagram_reels.py # Instagram Reels API
│ └── utils/ # Utilities and helpers
│ ├── config.py # Configuration management
│ ├── file_handler.py # File operations
│ └── scheduler.py # Task scheduling
└── data/ # Local data storage
├── videos/ # Downloaded videos
├── clips/ # Generated clips
└── analytics/ # Performance data
Create a Google Cloud Project
Enable YouTube Data API v3
Create OAuth 2.0 Credentials
Configure credentials
youtube_credentials.json in your clippy folderconfig.yamlconfig.yamlClippy provides comprehensive analytics to optimize your content strategy:
| Feature | Description |
|---|---|
| Performance Tracking | Monitor engagement rates, views, and likes across all platforms |
| Trend Analysis | Identify best-performing content types and optimal posting times |
| AI Optimization | Automatically adjust content strategy based on performance data |
| Viral Prediction | Score clips for viral potential before posting |
# Build and run
docker-compose up -d
# View logs
docker-compose logs -f clippy
# Stop
docker-compose down
# Run with database and caching
docker-compose --profile with-database --profile with-redis up -d
ai:
model_name: "custom-model.gguf"
model_path: "/path/to/models"
gpu_acceleration: true
webhooks:
enabled: true
success_url: "https://your-app.com/webhook/success"
error_url: "https://your-app.com/webhook/error"
scheduler:
max_videos_per_day: 10
posting_times:
youtube: ["09:00", "15:00", "20:00"]
tiktok: ["12:00", "17:00", "21:00"]
instagram: ["10:00", "14:00", "19:00"]
# Install development dependencies
pip install -r requirements-dev.txt
# Run tests
pytest tests/
# Code formatting
black src/
flake8 src/
src/platforms/post_video(), get_stats()config.yamlplatform_manager.pyWe welcome contributions! Here's how you can help:
git checkout -b feature/amazing-feature)git commit -m 'Add amazing feature')git push origin feature/amazing-feature)This project is licensed under the MIT License. See the LICENSE file for details.
Important: Please ensure compliance with platform terms of service and content rights before using this tool.
| Resource | Link |
|---|---|
| 📖 Documentation | ./docs/ |
| 🐛 Issues | Report Issues |
| 💬 Discussions | Join Discussion |
| stylebenderkh@gmail.com |
Special thanks to the amazing open-source projects that make Clippy possible:
Made with ❤️ by Yacine Khaldi
Empowering content creators to maximize their reach across platforms
⭐ Star this repository if you find it helpful! ⭐