EssenceAI

This is a web-based summarization app built with React and Bootstrap. The app allows users to input text and generate concise summaries using a custom-trained T5 model. The T5 model has been fine-tuned on the Gigaword dataset, which provides high-quality summarization results. The input and output sections are neatly arranged side by side for a user-friendly experience.

Video demo - https://youtu.be/L2xCct6soqM

Pretrained model -

Table of Contents

• Features
• Technologies Used
• Dataset
• Installation
• Project Structure
• Contributing

Features

• User-friendly interface for text summarization
• Input and output sections side by side
• Summarization using a custom-trained T5 model fine-tuned on the Gigaword dataset
• Ability to upload documents for summarization
• Clean UI built with Bootstrap

Technologies Used

• React (Frontend)
• Django (Backend)
• Bootstrap (CSS Framework)
• Python for model training
• T5 model fine-tuned on the Gigaword dataset

Dataset

This project uses the Gigaword dataset, which consists of pairs of long text articles and their corresponding summaries. The T5 model was fine-tuned on this dataset to improve summarization capabilities and generate concise summaries based on the user's input.

Dataset paper - Paper Link

Dataset download - Kaggle Dataset Link

Installation

To get started with the project:

1. Clone the repository:

   git clone https://github.com/kazimahathir73/EssenceAI.git
   cd EssenceAI

2. Install frontend dependencies:

   cd frontend
   npm install

3. Install backend dependencies:

   cd ../backend
   pip install -r requirements.txt

4. Run the frontend and backend servers:

   • Frontend (React):

     cd frontend
     npm start

   • Backend (Django):

     cd backend
     python manage.py runserver

Project Structure

├── backend
│   ├── model.py
│   ├── admin.py
│   ├── views.py
│   ├── urls.py
│   └── ...
├── frontend
│   ├── public
│   │   └── images
│   │   └── videos
│   │   └── .... 
│   ├── src
│   │   └── components
│   │       └── homepage.css
│   │       └── homepage.js
│   │       └── summary.js
│   │       └── summary.css
│   │       └── ....    
│   │   └── Apps.js
│   │   └── index.js          
│   └── ...
├── main
│   ├── asgi.py
│   ├── setting.py
│   ├── urls.py
│   ├── wsgi.py
│   └── ...
├── summarizer_model
│   ├── weights
│   ├── gigadata_corpus.csv
│   ├── response.py
│   ├── train_model.ipynb
│   └── ...
├── README.md
└── ...

Contributing

Contributions are welcome! If you find any bugs or want to add a new feature:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes and commit them (git commit -m 'Add some feature').
4. Push to the branch (git push origin feature-branch).
5. Open a Pull Request.