GitHub - BaseMax/python-office-generator: Automatically generate PowerPoint, Word, and PDF presentations from structured data and research content.

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

Library	Purpose
`python-pptx`	Generate PowerPoint slides
`python-docx`	Create Word documents
`reportlab`	Build formatted PDF summaries
`PyMuPDF (fitz)`	Extract images from PDFs
`os`	File system management

📂 Output Files

When executed, the script produces the following files automatically:

File	Description
`Presentation_ML_Sustainability.pptx`	Generated PowerPoint presentation
`Presentation_ML_Sustainability.pdf`	Summary document in PDF format
`Presentation_ML_Sustainability.docx`	Presentation notes in Word format
`figure_*.png`	Extracted images from source PDF

⚙️ Installation

Clone the repository:

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

Install the dependencies:
```
pip install -r requirements.txt
```
Add your source PDF file (e.g. pdf.pdf) to the project root.
Run the generator:

🧠 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.