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---
title: Multilingual Text Summarizer
emoji: 📝
colorFrom: blue
colorTo: pink
sdk: gradio
sdk_version: 5.29.0
app_file: app.py
pinned: false
license: apache-2.0
---
# 🧠 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](https://huggingface.co/docs/transformers/index) - Pre-trained models (BART, T5...)
- [Streamlit](https://streamlit.io) - Web interface
- [Gradio](https://www.gradio.app/) - Web interface
- [Python](https://www.python.org) - Processing & pipeline
- [Data](https://huggingface.co/datasets/abisee/cnn_dailymail/viewer/2.0.0?views%5B%5D=_200_train) - 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
```bash
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](https://...)
📸 See screenshots below
## 📂 Project structure
```bash
SmartSummarizer/
│
├── app_gradio.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
``` |