VidXiv - ArXiv Paper to Video Generator

🎥 Convert ArXiv research papers into engaging video presentations automatically!

Fig. VidXiv Streamlit UI

Features

• 📄 Fetches papers directly from ArXiv using paper ID
• 🤖 Uses AI (Gemini) to generate video scripts from paper content
• 🎬 Creates multi-scene videos with text overlays
• 🔊 Generates narration using text-to-speech
• 📱 Supports both landscape (YouTube) and portrait (Shorts/Reels) formats
• 🎵 Optional background music support

Upcoming Features

🚀 Coming Soon:

• ✏️ Script Editing Interface - Review and modify AI-generated scripts before video creation
• 🖼️ Automatic Figure Integration - Smart extraction and placement of paper figures, charts, and diagrams
• 🎨 Manual Graphics Upload - Add custom images, logos, and visual elements to enhance presentations
• 🎭 Multiple AI Voices - Choose from different TTS voices and speaking styles
• 📊 Advanced Templates - Pre-designed video templates for different research fields
• 🔄 Batch Processing - Generate videos for multiple papers simultaneously
• 🌐 Multi-language Support - Generate videos in different languages

Installation

uv sync

Setup

1. Copy the environment template:

cp .env.template .env

2. Edit .env and add your API keys if needed (for Gemini or other LLM models)

Usage

1. Start the Streamlit app:

streamlit run main.py

2. Open your browser to the displayed URL (usually http://localhost:8501)

3. Enter an ArXiv paper ID (e.g., 2401.06015)

4. Choose video format:

   • Uncheck for landscape YouTube format (16:9)
   • Check for portrait Shorts/Reels format (9:16)

5. Optionally upload background music (MP3 format)

6. Click "Generate Video" and wait for processing

7. Download your generated video!

Requirements

• Python 3.11+
• Internet connection (for fetching papers and AI processing)
• Sufficient disk space for temporary video files

Dependencies

• arxiv - Fetching papers from ArXiv
• pymupdf - PDF processing and figure extraction
• gtts - Text-to-speech for narration
• moviepy - Video editing and composition
• streamlit - Web interface
• langchain - LLM integration
• requests - HTTP requests
• pillow - Image processing
• python-dotenv - Environment variable management

Troubleshooting

Common Issues

1. Import errors: Make sure all dependencies are installed correctly
2. MoviePy errors: Try installing with pip install moviepy[optional]
3. Font errors: Install system fonts or use the fallback font options
4. Memory issues: Try with shorter papers or reduce video quality

Error Messages

• "Could not add background music": The background music file may be corrupted or in an unsupported format
• "Error generating video": Check that all dependencies are properly installed and try again

Contributing

Feel free to submit issues and enhancement requests!

License

MIT License - see LICENSE file for details