professional_readme (1).md

Clippy - Autonomous Video Repurposing Agent 🎬✂️

Transform long-form content into viral short clips across YouTube Shorts, TikTok, and Instagram Reels with AI-powered automation.

Quick Start • Features • Documentation • Contributing

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🚀 Overview

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.

Key Benefits

• 🎯 Maximize Reach: Repurpose content across multiple platforms simultaneously
• 🔒 Privacy-First: Offline AI processing with local data storage
• 💰 Cost-Effective: Designed for free-tier deployment and local execution
• 📊 Data-Driven: Built-in analytics to optimize your content strategy

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✨ Features

🎥 Video Processing Automated video download and transcription Multi-format support with quality optimization Intelligent content segmentation 🤖 AI-Powered Analysis Offline LLM processing for privacy Viral moment detection and scoring Content optimization recommendations

📱 Multi-Platform Publishing YouTube Shorts automation TikTok direct posting Instagram Reels integration 📊 Performance Analytics Engagement tracking across platforms Trend analysis and optimization Viral potential prediction

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🏁 Quick Start

Prerequisites

Ensure you have the following installed:

# Required software
Python 3.10+
FFmpeg
Git

Installation

1. Clone and setup the repository

   git clone <repository-url>
   cd clippy
   pip install -r requirements.txt

2. 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'})"

3. Configure your settings

   cp config.yaml.example config.yaml
   # Edit config.yaml with your platform credentials

Usage Examples

🎬 Single Video Processing

python main.py --url "https://youtube.com/watch?v=VIDEO_ID"

📚 Batch Processing

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

⏰ Scheduler Mode

python main.py --scheduler

📈 Analytics

python main.py --analytics

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⚙️ Configuration

Configure Clippy by editing the config.yaml file:

Video Settings

video:
  download_quality: "720p"
  clip_duration_min: 30
  clip_duration_max: 60

Platform Configuration

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 Configuration

ai:
  model_name: "orca-mini-3b-gguf2-q4_0.gguf"
  highlight_threshold: 0.7

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🏗️ Architecture

Project Structure

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

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🔧 Platform Setup

📺 YouTube Shorts Setup

1. Create a Google Cloud Project

   • Visit Google Cloud Console
   • Create new project or select existing one

2. Enable YouTube Data API v3

   • Navigate to APIs & Services → Library
   • Search for "YouTube Data API v3" and enable it

3. Create OAuth 2.0 Credentials

   • Go to APIs & Services → Credentials
   • Click "Create Credentials" → "OAuth 2.0 Client IDs"
   • Configure OAuth consent screen if prompted
   • Select "Desktop application" as application type
   • Download the JSON credentials file

4. Configure credentials

   • Save the downloaded JSON file as youtube_credentials.json in your clippy folder

📱 TikTok Setup

1. Add username/password to config.yaml
2. First run will require manual 2FA verification
3. Session cookies will be saved for future use

📸 Instagram Reels Setup

1. Add username/password to config.yaml
2. Enable "Less Secure Apps" or use App Password
3. Consider using a dedicated business account

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📊 Analytics & Optimization

Clippy 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

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🐳 Docker Deployment

Quick Start with Docker

# Build and run
docker-compose up -d

# View logs
docker-compose logs -f clippy

# Stop
docker-compose down

Production Deployment

# Run with database and caching
docker-compose --profile with-database --profile with-redis up -d

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🔧 Advanced Configuration

Custom AI Models

ai:
  model_name: "custom-model.gguf"
  model_path: "/path/to/models"
  gpu_acceleration: true

Webhook Integration

webhooks:
  enabled: true
  success_url: "https://your-app.com/webhook/success"
  error_url: "https://your-app.com/webhook/error"

Advanced Scheduling

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"]

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🛠️ Development

Development Setup

# Install development dependencies
pip install -r requirements-dev.txt

# Run tests
pytest tests/

# Code formatting
black src/
flake8 src/

Adding New Platforms

1. Create new platform handler in src/platforms/
2. Implement required methods: post_video(), get_stats()
3. Add platform configuration to config.yaml
4. Register platform in platform_manager.py

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🤝 Contributing

We welcome contributions! Here's how you can help:

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

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⚖️ License

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

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⚠️ Legal Notice

Important: Please ensure compliance with platform terms of service and content rights before using this tool.

• Respect platform terms of service
• Ensure you have rights to content you're repurposing
• Use automation responsibly to avoid account restrictions
• Consider rate limiting for platform compliance

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📞 Support

Resource	Link
📖 Documentation	./docs/
🐛 Issues	Report Issues
💬 Discussions	Join Discussion
📧 Email	[email protected]

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🙏 Acknowledgments

Special thanks to the amazing open-source projects that make Clippy possible:

• OpenAI Whisper for transcription capabilities
• GPT4All for offline LLM processing
• FFmpeg for video processing
• All the incredible open-source libraries and contributors

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Made with ❤️ by Yacine Khaldi

Empowering content creators to maximize their reach across platforms

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⭐ Star this repository if you find it helpful! ⭐