README.md

metadata

title: YouTube Creator MetaData Extractor
emoji: 🎬
colorFrom: red
colorTo: purple
sdk: gradio
sdk_version: 5.32.0
app_file: app.py
pinned: false
license: mit

🎬 YouTube Creator MetaData Extractor

AI-powered tool for content creators to analyze YouTube videos and generate professional metadata using advanced language models.

🚀 Features

• 🔍 Video Search: Search YouTube videos by keywords with advanced filters
• 📊 Video Analysis: Extract comprehensive video metadata (views, likes, duration, etc.)
• 📝 Transcript Extraction: Get video transcripts in multiple languages
• ⏱️ Smart Timecodes: AI-generated timecodes for better video navigation
• 🤖 Gemini AI Integration: Advanced timecode generation using Google's Gemini 2.0
• 🌐 Multi-language Support: Works with videos in Ukrainian, Russian, English, and more
• 📱 URL Flexibility: Supports all YouTube URL formats (regular, shorts, embed links)

⚠️ Cloud Platform Limitations

YouTube blocks transcript access from cloud IPs (Hugging Face Spaces, AWS, etc.)

What works on HF Spaces:

• ✅ Video Search
• ✅ Video Metadata
• ❌ Transcripts (limited)
• ❌ AI Timecodes (limited)

For full functionality, download and run locally:

git clone https://huggingface.co/spaces/dzianisBY/YouTube_Creator_MetaData
cd YouTube_Creator_MetaData
pip install -r requirements.txt
# Add your API keys to .env file
python main.py

🛠️ Setup

Required API Keys

To use this tool, you need two API keys:

1. YouTube Data API v3 Key

   • Go to Google Cloud Console
   • Create a new project or select existing
   • Enable "YouTube Data API v3"
   • Create credentials (API Key)

2. Gemini API Key (for AI features)

   • Visit Google AI Studio
   • Get your free API key for Gemini

Environment Variables

Set these in your Hugging Face Space settings:

YOUTUBE_API_KEY=your_youtube_api_key_here
GEMINI_API_KEY=your_gemini_api_key_here

📖 How to Use

1. Video Search

• Enter keywords to find YouTube videos
• Filter by upload date, view count, duration
• Get detailed metadata for any video

2. Transcript Analysis

• Extract transcripts from videos with subtitles
• Support for auto-generated and manual captions
• Multiple language detection and support

3. Timecode Generation

Basic Timecodes: Algorithmic segmentation based on transcript timing AI Timecodes: Intelligent topic-based segmentation using Gemini AI

Supported Formats:

• YouTube: Ready for video descriptions (e.g., 05:30 Topic description)
• Markdown: Clickable links with timestamps (e.g., - [05:30](link) Topic)

Language Codes:

• uk - Ukrainian
• ru - Russian
• en - English
• And many others (ISO 639-1 standard)

🔧 API Reference

This application provides both a web interface and REST API endpoints:

Search Videos

POST /api/search
{
  "query": "your search query",
  "max_results": 10,
  "order": "relevance"
}

Get Video Info

POST /api/video_info
{
  "video_id": "video_id_or_full_url"
}

Extract Transcript

POST /api/transcript
{
  "video_id": "video_id_or_full_url",
  "language_code": "uk"
}

Generate AI Timecodes

POST /api/gemini_timecodes
{
  "video_id": "video_id_or_full_url",
  "language_code": "uk",
  "format": "youtube",
  "model": "gemini-2.0-flash-001"
}

🏗️ Architecture

• Frontend: Gradio web interface with responsive design
• Backend: FastAPI server with async processing
• AI Integration: Google Gemini 2.0 for intelligent content analysis
• APIs: YouTube Data API v3 for video metadata
• Transcript: YouTube Transcript API for subtitle extraction

📁 Project Structure

├── main.py                     # Unified launcher (API/UI/both modes)
├── run_telegram_bot.py         # Telegram bot launcher
├── api_server.py              # FastAPI backend server
├── telegram_bot.py            # Telegram bot implementation
├── mcp_handlers.py            # Model Context Protocol handlers
├── gemini_helper.py           # Gemini AI integration
├── utils.py                   # Utility functions
├── models.py                  # Data models
├── app.py                     # Gradio app (HF Spaces entry point)
├── gradio_app.py              # Extended Gradio interface
├── requirements.txt           # Python dependencies
├── telegram_requirements.txt  # Telegram bot dependencies
├── cloudflare-config.yml      # Cloudflare tunnel configuration
├── TUNNEL_SOLUTIONS.md        # Tunnel troubleshooting guide
├── youtube-content-metagen-agent.ipynb  # Kaggle reference notebook
└── README.md                  # This file

🔬 Technology Stack

• Python 3.13+
• Gradio - Web interface framework
• FastAPI - High-performance API framework
• Google Gemini 2.0 - Advanced language model for content analysis
• YouTube APIs - Official Google APIs for video data
• AsyncIO - Asynchronous processing for better performance

🌟 Use Cases

• Content Creators: Generate professional timecodes for YouTube videos
• Educators: Extract and analyze educational content structure
• Researchers: Analyze video metadata and transcripts at scale
• Marketers: Research competitor content and trends
• Accessibility: Create better navigation for long-form content

📄 License

MIT License - feel free to use in your projects!

🤝 Contributing

Contributions welcome! This project is designed to help content creators worldwide.

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Made with ❤️ for the YouTube creator community