Automated Generative AI Text Summarization Engine for Efficient Content Extraction, Document Analysis, and Knowledge Discovery

Abstract

The rapid growth of digital information has made it difficult for users to read and understand large volumes of textual content. This project focuses on developing a Smart Text Summarization system using the PEGASUS generative AI model to automatically generate concise summaries from lengthy text. The main objective of the system is to help users quickly grasp important information without reading the entire document. The application allows users to enter text or upload documents such as PDF and DOCX files for summarization. The PEGASUS transformer model is used to perform abstractive summarization by understanding the context and meaning of the text. The system is developed using Python and Flask for backend processing and HTML, CSS, and JavaScript for creating an interactive web interface. Additional libraries such as PyPDF2 and python-docx are used to extract text from documents. ReportLab is used to generate downloadable PDF summaries.