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It allows users to generate summaries from various sources like plain text, PDFs, DOCX files, video transcripts, and website URLs, using advanced NLP model - Trained T5-base, which trained on abisee/cnn_dailymail , 3.0.0. dataset of hugging face.\n\n## Table of Contents\n- [Description](#description)\n- [Features](#features)\n- [Technologies Used](#technologies-used)\n- [Requirements](#requirements)\n- [Installation](#installation)\n- [Usage](#usage)\n- [Project Structure](#project-structure)\n- [Contribution Guidelines](#contribution-guidelines)\n- [License](#license)\n\n## Description\nInformation Summarizer is designed to streamline the summarization process for various content types, leveraging AI models to produce concise, meaningful summaries. Users can upload text files, PDFs, and input URLs or video links to generate summaries.\n\n## Features\n- Summarize various content types:\n  - Plain text\n  - PDF files\n  - Video transcripts from YouTube\n  - Web URLs\n- User authentication (login and signup)\n- PDF and text file upload and summary generation\n- Video transcription and summarization using the `youtube-transcript-api`\n- Summarization models -  Trained T5-base, which trained on abisee/cnn_dailymail , 3.0.0. dataset of hugging face\n\n## Technologies Used\n- **Frontend**: React, Tailwind CSS\n- **Backend**: Django, Django REST Framework\n- **Database**: SQLite\n- **OCR and Summarization**:  Trained T5-base, which trained on abisee/cnn_dailymail , 3.0.0. dataset of hugging face\n- **Other Libraries**: `youtube-transcript-api` for video transcription\n\n## Requirements\n- Python 3.12\n- Django (version compatible with your Python version)\n- Required Python libraries (see `requirements.txt`)\n\n## Installation\n1. **Clone the Repository**\n   ```bash\n   git clone https://github.com/patilprathamesh07/Information_Summarizer.git\n   cd Information_Summarizer\n    ```\n2. Install Python Dependencies\n  ```bash\n  pip install -r requirements.txt\n  ```\n\n## All set to start the program :\n```bash\ncd Information_Summarizer\n```\n```bash\npython manage.py migrate\npython manage.py runserver\n```\n## Usage\n1.  Login and Signup: Access authentication features at the login page.\n2.  Upload Content: Go to the upload page to submit text, PDF, url , or video links.\n3.  Summary Generation: Choose the content type and receive a summarized version on the result page.\n## Project Structure\n```\nInformation_Summarizer/\n├── info_summarizer/\n│   ├── __init__.py\n│   ├── asgi.py\n│   ├── settings.py\n│   ├── urls.py\n│   ├── wsgi.py\n├── pdfs/\n├── transcripts/\n├── summarizer/\n│   ├── __init__.py\n│   ├── admin.py\n│   ├── apps.py\n│   ├── models.py\n│   ├── tests.py\n│   ├── views.py\n│   └── templates/\n│       ├── login.html\n│       ├── upload.html\n│       └── result.html\n├── README.md\n├── db.sqlite3\n├── manage.py\n└── requirements.txt\n\n```\n## Contribution Guidelines\n1.  Fork the repository.\n2.  Create a feature branch (git checkout -b feature/AmazingFeature).\n3.  Commit your changes (git commit -m 'Add some AmazingFeature').\n4.  Push to the branch (git push origin feature/AmazingFeature).\n5.  Open a pull request.\n## License\nThis project is licensed under the MIT License.\n\n## Screenshots:\n![image](https://github.com/user-attachments/assets/e791fae1-5043-4eb6-bdd8-243d4992cc37)\n\n![image](https://github.com/user-attachments/assets/2fd2c03b-2a4d-4881-a2d4-fc009794d49d)\n\n![image](https://github.com/user-attachments/assets/1c981543-9557-46ab-89fa-cacf97ed6975)\n\n![image](https://github.com/user-attachments/assets/bd596064-df7b-4ba2-8072-9c835d67cd45)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprathamesh-patil-5090%2Finformation_summarizer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fprathamesh-patil-5090%2Finformation_summarizer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprathamesh-patil-5090%2Finformation_summarizer/lists"}