In today's fast-paced world, keeping up with the latest news from diverse sources can be overwhelming. This project presents a Newspaper Summary Generator, an AI-powered tool designed to aid readers in quickly digesting key information from news articles. The generator utilizes natural language processing (NLP) techniques to extract essential content, condensing lengthy articles into concise summaries. The system begins by fetching news articles from various sources, leveraging the newspaper3k library for article scraping. Once the articles are retrieved, the system employs NLP algorithms to analyze and summarize the content. Techniques such as sentence tokenization, keyword extraction, and sentence ranking are utilized to identify crucial information. To generate the summaries, the system ranks sentences based on their relevance and importance within the context of the article. The sentences with the highest significance are then stitched together to form a coherent and informative summary. Users have the flexibility to specify the number of sentences or paragraphs they wish to include in the summary, tailoring the output to their preferences. The Newspaper Summary Generator aims to enhance the efficiency of news consumption, allowing users to stay informed without the need to sift through extensive articles. By providing condensed yet comprehensive summaries, this tool empowers readers to grasp the essence of news stories quickly and efficiently.