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Text_Summarizer

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Motivation

"Unlocking Knowledge: Elevate Your Reading Efficiency with Text Summarization

In today's fast-paced world, information is abundant and constantly flowing. The challenge lies in efficiently extracting valuable insights from the sea of text that surrounds us. This is where text summarization emerges as a game-changer. Imagine being able to distill lengthy articles, research papers, and reports into concise, yet comprehensive summaries without losing their essence.

Text summarization empowers you to make the most of your time by condensing complex ideas and multiple perspectives into easily digestible formats. Whether you're a student grappling with voluminous textbooks, a professional staying up-to-date with industry trends, or simply an avid reader exploring diverse topics, text summarization is your key to unlocking a world of knowledge without feeling overwhelmed.

By embracing text summarization tools and techniques, you're not just saving time – you're gaining a competitive edge. Sharpen your analytical skills, enhance your learning journey, and stay ahead in conversations by effortlessly grasping the core concepts of various texts. Embrace the future of efficient information consumption and embark on a journey where less becomes more. Start summarizing, start excelling!"

Installation

Firstly, clone the repository using,

git clone https://github.com/sabareeshreddy/Text_Summarizer

Once you have the source code, create a virtual environment using the following command, python3 -m venv venv

Enter the virtual environment and install dependencies using pip install -r requirements.txt.

Once all the dependencies are completed you need to create a .env file in the root directory of the project.
The .env file should contain the same variables as .env.example.

Your installation is completed and you are all set to use the API.

Contributing

To contribute to the project, fork the repository, create a new branch, and send us a pull request.

Also, thanks for contributing to Open-source!

License

Text_Summarization is under The MIT License. Read the LICENSE file for more information.

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