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This project is an AI-powered Text Summarizer application designed with Tailwind CSS for a clean and responsive user interface. The application uses machine learning models to generate concise summaries from large blocks of text, enhancing productivity and readability.

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krishnasingh-09/short_summary

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🚀AI Summarizer

🧠AI Summarizer Using URL is a web application that automatically extracts and condenses the key points of any online article or webpage by simply entering its URL. Leveraging advanced machine learning and natural language processing, it generates concise, customizable summaries to help users quickly understand the core content without having to read through lengthy text. This project is ideal for busy professionals, researchers, students, and anyone who needs rapid insights from diverse online sources.

🌟Features

  • Efficient Summarization: Utilizes state-of-the-art AI models to produce summaries quickly and accurately.
  • User-Friendly Interface: Simple design focused on usability.
  • Customizable Outputs: Adjust summary length and detail based on user preferences.
  • Scalable Architecture: Built to handle a variety of text inputs from small articles to extensive reports.

📥Installation

Follow these steps to set up the project locally:

Clone the Repository:

 git clone https://github.com/krishnasingh-09/short_summary.git

Navigate to the Project Directory:

cd short_summary

Install Dependencies:

npm install

🎯Usage

Run the Application:

npm run dev

Access the Web Interface:

Open your web browser and navigate to http://localhost:5173

Generate a Summary:

1. Paste your text into the input field.
2. Click the "Summarize" button to generate the summary.

👏Acknowledgements

  • 💻Developed by Krishnasingh-09
  • 🎨Inspired by advanced AI summarization techniques and aimed at making information more accessible and digestible.

About

This project is an AI-powered Text Summarizer application designed with Tailwind CSS for a clean and responsive user interface. The application uses machine learning models to generate concise summaries from large blocks of text, enhancing productivity and readability.

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