🧠 Python Office Generator

Automatically generate PowerPoint, Word, and PDF presentations from structured data and research content.

📘 Overview

Python Office Generator is a script that automates the creation of academic and research presentations in multiple formats PPTX, DOCX, and PDF.
This tool demonstrates how Python can integrate document-generation libraries to produce consistent, professional-quality materials for reports, lectures, and conferences.

The example included focuses on:

Machine Learning Applications in Environmental Sustainability 🌱

It extracts figures from a PDF (using PyMuPDF), creates presentation slides, generates summary PDFs, and writes accompanying lecture notes in Word.

🚀 Features

✅ Extracts images directly from a PDF file
✅ Automatically builds PowerPoint slides from structured content
✅ Generates corresponding DOCX and PDF summary documents
✅ Adds visual figures into presentation slides
✅ Uses clean and readable formatting (fonts, colors, spacing)
✅ Ideal for academic and research-oriented automation

🧩 Technologies Used

📂 Output Files

When executed, the script produces the following files automatically:

⚙️ Installation

1. Clone the repository:

   git clone https://github.com/BaseMax/python-office-generator
   cd python-office-generator

2. Install the dependencies:

   pip install -r requirements.txt

3. Add your source PDF file (e.g. pdf.pdf) to the project root.

4. Run the generator:

   python app.py

🧠 Example Topic

Machine Learning Applications in Environmental Sustainability

This example presentation includes sections like:

• Introduction to ML and sustainability
• Supervised & Unsupervised learning approaches
• Deep Learning in climate science
• Renewable energy forecasting case study
• Future research directions

🧩 Future Improvements

• Add CLI interface for dynamic content generation
• Support for LaTeX → PPTX and Markdown → DOCX conversion
• Automatic design themes and layouts
• Integration with AI summarization tools

📜 License

This project is licensed under the MIT License.

See the LICENSE file for details.

Copyright (c) 2025 Seyyed Ali Mohammadiyeh (Max Base)