DocuMorph - PDF to Multimedia Converter

Transform boring PDF lessons into engaging multimedia content with AI-powered conversion.

Comment 1

DocuMorph - PDF to Multimedia Converter

Transform boring PDF lessons into engaging multimedia content with AI-powered conversion. Convert tutorial PDFs into interactive videos, comic-style illustrations, or structured step-by-step guides.

✨ Status: FULLY INTEGRATED & READY TO USE

All components are connected and working:

  • ✅ Frontend ↔ Backend communication
  • ✅ PDF processing with PyMuPDF
  • ✅ AI content generation with OpenAI
  • ✅ Real-time chatbot integration
  • ✅ Database storage with PostgreSQL
  • ✅ Background job processing

🚀 Quick Start: Just add your OpenAI API key and run ./start.sh

Features

  • Multiple Output Formats: Convert PDFs to videos, comics, or structured text
  • AI-Powered Processing: Advanced AI algorithms for content analysis and transformation
  • Interactive Results: View results with built-in AI chatbot for questions
  • Modern UI: Beautiful, responsive interface built with Next.js and Tailwind CSS
  • 3D Visuals: Immersive Three.js backgrounds for enhanced user experience

Architecture Overview

Frontend (Next.js)

  • Framework: Next.js 16 with React 19
  • UI Components: shadcn/ui with Radix UI primitives
  • Styling: Tailwind CSS with custom design system
  • 3D Graphics: Three.js with React Three Fiber
  • State Management: React hooks and context
  • Forms: React Hook Form with Zod validation

Backend (FastAPI/Python)

  • Framework: FastAPI for high-performance APIs
  • PDF Processing: PyMuPDF for text extraction
  • AI Integration: OpenAI API for content generation
  • Video Generation: MoviePy for video creation
  • Image Generation: DALL-E or Stable Diffusion for comics
  • Database: PostgreSQL with SQLAlchemy
  • File Storage: AWS S3 or local storage
  • Task Queue: Redis with RQ for background processing

Infrastructure

  • Containerization: Docker for consistent deployment
  • Orchestration: Docker Compose for local development
  • Reverse Proxy: Nginx for production
  • SSL: Let's Encrypt for HTTPS
  • Monitoring: Basic logging and health checks

Project Structure

Boring_PDF_Lesson_to_Multimedia_Engaging_Content/
├── frontend/                    # Next.js React application
│   ├── app/                     # Next.js app router
│   ├── components/              # Reusable UI components
│   ├── hooks/                   # Custom React hooks
│   ├── lib/                     # Utilities and configurations
│   └── public/                  # Static assets
├── backend/                     # FastAPI Python application
│   ├── app/                     # FastAPI application
│   │   ├── api/                 # API routes
│   │   ├── core/                # Core functionality
│   │   ├── models/              # Pydantic models
│   │   └── services/            # Business logic
│   ├── requirements.txt         # Python dependencies
│   └── Dockerfile               # Backend container
├── docker/                      # Docker configurations
├── docs/                        # Documentation
└── docker-compose.yml           # Development environment

🚀 Quick Start

Prerequisites

  • Node.js 18+
  • Python 3.11+
  • Docker & Docker Compose (recommended) OR PostgreSQL + Redis
  • OpenAI API Key (required)

Option 1: One-Command Start (Recommended)

# Add your OpenAI API key to backend/.env
# Then run:
./start.sh

This will:

  1. Check prerequisites
  2. Set up environment files
  3. Start all services (with Docker or manually)
  4. Open the application at http://localhost:3000

Option 2: Docker Compose

# 1. Add OpenAI API key to backend/.env
echo "OPENAI_API_KEY=your-key-here" >> backend/.env

# 2. Start all services
docker-compose up -d

# 3. Access the application
open http://localhost:3000

Option 3: Manual Setup

See SETUP.md for detailed manual installation instructions.

📍 Application URLs

Once running, access:

API Documentation

The backend provides RESTful APIs for:

  • File upload and processing
  • Conversion job management
  • Result retrieval
  • AI chatbot interactions

Development Roadmap

  • [ ] Backend API implementation
  • [ ] PDF text extraction service
  • [ ] AI content generation integration
  • [ ] Video generation pipeline
  • [ ] Comic illustration generation
  • [ ] File storage and CDN setup
  • [ ] User authentication and management
  • [ ] Advanced AI features (summarization, Q&A)
  • [ ] Real-time processing status
  • [ ] Export and sharing functionality

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests if applicable
  5. Submit a pull request

License

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

Support

For questions or support, please open an issue on GitHub or contact the development team.

Share this project:

Updates

Submission history