📄 PDF Reader: Your AI-Powered PDF Companion

Welcome to the PDF Reader repository! This application leverages advanced AI technology to help users extract valuable insights from PDF documents. With a user-friendly interface built on Streamlit, and powered by cutting-edge NLP models from Transformers and Langchain, this tool makes PDF analysis straightforward and efficient.

Check out the latest releases here!

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🚀 Features

• AI-Powered Extraction: Utilize state-of-the-art NLP models to extract relevant information from your PDF documents.
• User-Friendly Interface: Built with Streamlit, the application offers an intuitive experience for all users.
• Seamless PDF Upload: Easily upload your PDFs and start extracting information in seconds.
• Advanced Analysis: Analyze the content of your PDFs to gain deeper insights and understanding.

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📚 Table of Contents

1. Installation
2. Usage
3. Technologies Used
4. Contributing
5. License
6. Support

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🛠️ Installation

To get started with the PDF Reader, follow these steps:

1. Clone the Repository:

   git clone https://github.com/RiddyMazumder/PDF-Reader.git

2. Navigate to the Directory:

   cd PDF-Reader

3. Install Dependencies:

   Ensure you have Python 3.7 or higher installed. Then, run:

   pip install -r requirements.txt

4. Run the Application:

   Start the Streamlit app with the following command:

   streamlit run app.py

Now, you can access the PDF Reader on your local server.

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📖 Usage

Using the PDF Reader is simple:

1. Open your web browser and navigate to the local server address provided by Streamlit.
2. Upload your PDF document using the upload button.
3. Once uploaded, click on the "Extract" button to retrieve meaningful information from the document.
4. Review the extracted data displayed on the screen.

For a deeper dive into the analysis features, refer to the Releases section for updates and enhancements.

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🧩 Technologies Used

This project incorporates several powerful technologies:

• Streamlit: A framework for building interactive web applications quickly.
• Transformers: A library by Hugging Face for state-of-the-art NLP models.
• Langchain: A framework that facilitates the integration of language models into applications.
• Python: The primary programming language used for development.
• Pandas: For data manipulation and analysis.

The combination of these technologies allows for robust PDF analysis and extraction capabilities.

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🤝 Contributing

We welcome contributions from the community! If you want to help improve the PDF Reader, follow these steps:

1. Fork the Repository.

2. Create a New Branch:

   git checkout -b feature/YourFeatureName

3. Make Your Changes.

4. Commit Your Changes:

   git commit -m "Add your message here"

5. Push to the Branch:

   git push origin feature/YourFeatureName

6. Open a Pull Request.

Please ensure your code follows the project's coding standards and includes appropriate tests.

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📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

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📞 Support

If you encounter any issues or have questions, please check the Releases section for updates. You can also open an issue in the repository for support.

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🎉 Acknowledgments

We thank the developers and contributors of the technologies used in this project. Their hard work and dedication make this application possible.

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🌟 Future Improvements

We aim to continuously enhance the PDF Reader. Here are some features we plan to implement:

• Multi-Language Support: Allow users to analyze PDFs in different languages.
• Batch Processing: Enable users to upload and analyze multiple PDFs at once.
• Export Options: Provide users with the ability to export extracted data in various formats (CSV, JSON, etc.).

Stay tuned for updates in the Releases section!

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Thank you for checking out the PDF Reader. We hope it helps you unlock the potential of your PDF documents!