--- 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 ```