{"repo":"Milor123/notebooklm-unified","free":true,"listed":false,"github":"https://github.com/Milor123/notebooklm-unified","clone":"git clone https://github.com/Milor123/notebooklm-unified.git","description":"Unifies, cleans and converts NotebookLM presentations in a single step. Join multiple PPTXs, remove watermark, output clean PPTX.","language":"Python","stars":23,"topics":["automation","notebooklm","pdf","pptx","python","watermark-remover","workflow"],"license":"MIT","category":"workflow-automation","readme_excerpt":"NotebookLM Unified Workflow Unifies, cleans and converts NotebookLM presentations in a single step. What does it do? This script automates the entire NotebookLM presentation cleaning process: 1. Merges multiple PPTX files into one 2. Converts to lossless PDF 3. Removes NotebookLM watermark 4. Converts back to clean PPTX Why this project? NotebookLM generates presentations with a maximum of 15 slides per file. For longer documents, you end up with multiple PPTXs that need to be: - Merged into one - Converted to PDF - Cleaned from watermark - Converted back to PPTX This script does ALL of that with a single command. Installation Usage Options Option Description -------- ------------- -i, --input Input folder or PPTX file -o, --output Output filename (default: presentacion limpia.pptx) -v, --verbose Verbose mode -d, --debug Debug: shows watermark coordinates Example Requirements - Python 3.8+ - Windows, macOS or Linux Dependencies are automatically installed the first time you run the script. How it works Credits - Watermark Remover : Algorithm based on work by neosun100/notebooklm-watermark-remover - Libraries : python-pptx, img2pdf, PyMuPDF License MIT License - see LICENSE --- ⭐️ If this script was useful to you, consider giving the project a star!","default_branch":null,"files":null,"tree":[],"storefront":"/r/Milor123","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Milor123/notebooklm-unified/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}