🤖 AI TransSummarizer

A professional Full-Stack AI Application designed to streamline content consumption. This tool leverages state-of-the-art Large Language Models (LLMs) to provide two core services: Smart Text Summarization and High-Accuracy English-to-Arabic Translation.

🚀 Live Demo

Experience the application live here: AI-TransSummarizer on Hugging Face

✨ Key Features

• Smart Summarization: Uses the facebook/bart-large-cnn model to condense long articles into short, informative summaries.
• Neural Translation: Translates English content into fluent Arabic using the Helsinki-NLP translation engine.
• Dual-Mode Processing: Users can summarize and translate simultaneously in a single click.
• Responsive Dark UI: A modern, user-friendly interface with a sleek violet theme, optimized for both desktop and mobile.
• Robust Backend: Powered by FastAPI for high-speed request handling and Pydantic for data validation.

🛠️ Technical Stack

• Backend: Python 3.9, FastAPI.
• AI Framework: Hugging Face Transformers.
• Frontend: HTML5, CSS3 (Modern UI), JavaScript (Asynchronous Fetch API).
• Infrastructure: Dockerized environment deployed on Hugging Face Spaces.

⚙️ How It Works

The system follows a modular logic flow:

1. Input: User pastes English text and selects desired tasks.
2. Preprocessing: JavaScript appends hidden triggers (summarize / ترجم) based on user selection.
3. AI Pipeline:
   • If "Summarize" is triggered, the BART model reduces the text length while preserving meaning.
   • If "Translate" is triggered, the OPUS-MT model converts the resulting text into Arabic.
4. Output: The processed result is displayed instantly without page reloads.

📦 Local Setup

To run this project locally:

1. Clone the repo:

   git clone [https://github.com/PhilopateerDev/AI-TransSummarizer.git](https://github.com/PhilopateerDev/AI-TransSummarizer.git)