🧠 Multilingual Text Summarizer with Transformers

This project is a web-based application that summarizes English or French text using LLMs. It supports direct input, .txt, and .pdf files with automatic language detection.

The project uses Large Language Models (LLMs) such as BART or T5, deployed via a simple, interactive Gradio interface.

📌 Objectives

• Automate the synthesis of long texts (e-mails, reports, news...)
• Apply automatic summarization techniques with LLMs.
• Propose a simple and responsive user interface.
• Demonstrate a real-life case of NLP model industrialization.

🧠 Technical stack

• Transformers - Pre-trained models (BART, T5...)

• Streamlit - Web interface

• Gradio - Web interface

• Python - Processing & pipeline

• Data - abisee/cnn_dailymail

• (Bonus) Docker, FastAPI, GitHub Actions - MLOps

✨ Features

• Automatic language detection (English or French)
• Summarization using state-of-the-art models
• Gradio-based web interface
• Supports text, .txt and .pdf inputs

🚀 Run the App

git clone https://github.com/issa-kabore/SmartSummarizer.git
cd SmartSummarizer
pip install -r requirements.txt
python app_gradio.py

🚀 Demo

👉 Link to deployed app

📸 See screenshots below

Example: uploading file

📂 Project structure

SmartSummarizer/
│
├── app.py                # Gradio main script (user interface)
├── summarizer/
│   ├── __init__.py             
│   ├── models.py                # Loading models and pipelines
│   ├── utils.py                # Import functions .txt/.pdf and Language detection
│   └── summarize.py             # Main summary function
│
├── assets/                      # (Optional) static files: images, logos, etc.
│
├── requirements.txt             # Dependencies to install
├── README.md                    # Project presentation
└── .gitignore                   # Files to be ignored by Git