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PyVisionAI: Content Extractor and Image Description with Vision LLM

Transforming Content Processing with Vision Language Models

Features

  • 📄 Extract text and images from PDF, DOCX, PPTX, and HTML files
  • 🖼️ Capture interactive HTML pages as images with full rendering
  • 📝 Describe images using local (Ollama) or cloud-based (OpenAI) Vision Language Models
  • 💾 Save extracted text and image descriptions in markdown format
  • 🛠️ Support for both CLI and library usage
  • 📊 Multiple extraction methods for different use cases
  • 📋 Detailed logging with timestamps for all operations
  • ⚙️ Customizable image description prompts

System Requirements

Hardware and OS

  • Python 3.8 or higher
  • Operating system: Windows, macOS, or Linux
  • Disk space: At least 1GB free space (more if using local Llama model)

Required Software

  • LibreOffice: Required for DOCX/PPTX processing
  • Poppler: Required for PDF processing
  • Playwright: Required for HTML processing

See Installation Guide for detailed setup instructions.

Latest Release: v0.2.5 (January 20, 2025)

PyVisionAI is continuously updated to ensure security and reliability. All versions to date have been certified secure, with no known vulnerabilities reported across any release.

Traction

PyVisionAI is gaining traction ([sources: PyPI Stats, GitHub Traffic]):

  • 📦 722 monthly PyPI downloads
  • 📈 171 weekly PyPI downloads
  • 👀 326 repository views from 123 unique visitors
  • 🔄 34 repository clones from 31 unique developers

Why Choose PyVisionAI?

  • ✨ Simplified installation and setup
  • 🔧 A robust framework designed for diverse file formats
  • 👥 Active community support and regular updates
  • 🔒 Prioritized security and performance with every release

Quick Start

# Install PyVisionAI
pip install pyvisionai

# Process your first file
file-extract -t pdf -s path/to/file.pdf -o output_dir

Get Started → View on GitHub →

Special Thanks

This project wouldn't exist without the incredible Python community, especially:

These podcasts transformed me from a Python enthusiast to a library author. Thank you for making Python accessible and exciting!