/ScienceFlow

An AI to accelerate Scientific Discovery

Primary LanguageHTML

Mathematical Discovery Pipeline 🧮

An AI-powered platform that automates the process of mathematical discovery, verification, and paper generation. This system combines advanced pattern analysis with formal verification to help explore and validate new mathematical conjectures.

🌟 Features

  • Interactive Discovery Interface: User-friendly web interface for inputting mathematical queries
  • Multi-Stage Pipeline:
    • Initial Curiosity Analysis
    • Pattern Recognition & Analysis
    • Automated Discovery
    • Formal Proof Validation
    • Paper Generation
    • arXiv Publication Preparation
  • Real-Time Visualization: Dynamic progress tracking through each pipeline stage
  • Verification Reports: Detailed validation of discovered patterns and proofs
  • Peer Review System: Automated review process for quality assurance
  • PDF Paper Generation: Automatic generation of publication-ready papers
  • Mathematical Animations: Beautiful loading animations with mathematical formulas

🚀 Getting Started

Web link - https://blooming-island-05267-ef86d983a41c.herokuapp.com/discovery

Prerequisites

🔧 Usage

  1. Enter your mathematical query in the input field
  2. Click "Start Discovery" to begin the analysis
  3. Watch as the pipeline progresses through each stage
  4. Review the generated results, including:
    • Pattern analysis
    • Formal verification
    • Peer review feedback
    • Generated paper
  5. Download the final paper as PDF

🏗️ Architecture

The system consists of several key components:

  • Frontend: HTML/TailwindCSS interface with dynamic JavaScript
  • Backend: Flask-based Python server
  • Analysis Engine: Pattern recognition and mathematical analysis
  • Verification System: Formal proof checking
  • Paper Generator: LaTeX document generation
  • Review System: Automated peer review process

🛠️ Technical Stack

  • Frontend:

    • HTML5
    • TailwindCSS
    • JavaScript
    • Prism.js (syntax highlighting)
    • Marked.js (markdown parsing)

  • Backend:

    • Python
    • Flask
    • NumPy/SciPy
    • LaTeX

📝 API Endpoints

  • POST /run_pipeline: Initiates the discovery pipeline
  • POST /generate_pdf: Generates publication-ready PDF

🤝 Contributing

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add some AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

📜 License

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

👥 Authors

🙏 Acknowledgments

  • Mathematical community for inspiration
  • Open source contributors
  • LaTeX community for document generation support

🔮 Future Enhancements

  • Integration with more mathematical proof assistants
  • Enhanced pattern recognition algorithms
  • Collaborative discovery features
  • Real-time collaboration tools
  • Extended theorem database