The document describes an automatic text summarization system developed by students. It uses machine learning techniques like TextRank to generate extractive summaries by selecting important sentences from input text. The system has two main parts - a web interface built with PHP, HTML and CSS, and a machine learning module in Python that does the text summarization. The model was trained and evaluated on 250 short news articles and 250 medium-length articles, and could generate concise summaries while preserving the original meaning.