{"id":23683842,"url":"https://github.com/gowthamsiddarthademan/pdf_summarizer","last_synced_at":"2026-05-07T15:36:29.413Z","repository":{"id":270098322,"uuid":"909332106","full_name":"gowthamsiddarthademan/PDF_Summarizer","owner":"gowthamsiddarthademan","description":"This is a PDF Summarizer Web App built using Flask and Hugging Face Transformers. The application allows users to upload PDF files and generate summarized text. 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The application allows users to upload PDF files and generate summarized text. The backend uses pre-trained NLP models for text summarization, powered by **Hugging Face's Transformers** library and **PyTorch**.\n\n#### **Key Features:**\n\n- **PDF Upload**: Users can upload PDF files.\n- **Text Extraction**: The app extracts text from the PDF and processes it for summarization.\n- **Text Summarization**: Uses Hugging Face pre-trained models (e.g., BART or T5) to summarize the extracted text.\n- **Web Interface**: Simple and clean user interface built with HTML and CSS, making it easy for users to interact with the app.\n- **Real-time Summary**: After uploading the PDF, the app provides a summarized version of the document, displaying the result below the uploaded text.\n\n#### **Technologies Used:**\n\n- **Flask**: Lightweight web framework for serving the application.\n- **Transformers (Hugging Face)**: For text summarization using pre-trained NLP models.\n- **PyTorch**: Deep learning framework used by the Hugging Face models.\n- **PyPDF2**: A Python library used to extract text from uploaded PDFs.\n- **HTML/CSS**: For creating the front-end interface.\n\n#### **Installation:**\n\n\n1. Install the dependencies:\n\n   ```bash\n    Flask==2.3.2\n    transformers==4.35.1\n    torch==2.1.0\n    PyPDF2==3.0.0   \n    ```\n\n2. Run the Flask app:\n\n   ```bash\n   python app.py\n   ```\n\n3. Open a browser and go to `http://127.0.0.1:5000` to use the app.\n\n#### **How It Works:**\n\n1. The user uploads a PDF file using the web interface.\n2. The app extracts the text content from the PDF.\n3. The extracted text is passed through a pre-trained summarization model (e.g., BART or T5).\n4. The summarized text is displayed to the user.\n\n#### **Usage:**\n\n- Upload any PDF document.\n- The app will extract the text and generate a summary based on the content.\n- Summarized text is shown below the uploaded PDF content.\n\n#### **Note:**\n\n- The app works best for smaller PDFs. Large PDFs may require more time for processing due to the text extraction and summarization process.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgowthamsiddarthademan%2Fpdf_summarizer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgowthamsiddarthademan%2Fpdf_summarizer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgowthamsiddarthademan%2Fpdf_summarizer/lists"}