🌐 Language Detector Web App

Detect the language of any text input instantly using Python, Flask, and LangDetect. Tracks detection history with a clean web UI and smart caching.

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## 📖 Overview

Language Detector is a full-stack Flask web application that uses the langdetect library to detect the language of any given text. It includes:

• 🧠 Automatic Language Detection using langdetect
• 💾 Detection History Tracking with SQLite (via SQLAlchemy)
• ⚡ Smart Caching for faster repeat detection
• 🖥️ Responsive Web Interface with recent detection previews

Built for fast prototyping, linguistic demos, and simple multi-language handling.

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⚙️ Features

🧠 Instant Language Detection

• Uses langdetect to identify the language code (e.g., en, fr, de, hi)
• Shows both code and full language name using pycountry

💾 Recent Detection History

• Displays last 5 detections on home page
• View complete paginated history on /history page

🚀 Fast Caching

• Avoids repeated detection for same text using a TTL-based cache (5 minutes default)

🖥️ Clean Web Interface

• Built with HTML/CSS and modular templates (using Jinja2)
• Includes 404 and 500 error pages

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🛠️ Technologies Used

Category	Tech Stack
Backend	Flask (Python)
Language Detection	langdetect, pycountry
Database	SQLite + SQLAlchemy
Frontend	HTML, CSS (custom), JS
Caching	TTL-based manual Python decorator

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🔌 Flask Endpoints

Route	Description
/	Home page with text input + recent detections
/detect	API endpoint for POST-based language detection
/history	Full history page with pagination

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🚀 Getting Started

1. Clone the Repository

git clone https://github.com/Aayushinit/LanguageDetectorApp.git
cd LanguageDetectorApp

2. Install Dependencies

pip install flask langdetect pycountry flask_sqlalchemy

3. Run the App

python app.py

4. Visit in Browser http://localhost:5000

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💡 How It Works

• Accepts user text input from the frontend
• langdetect attempts to detect language code
• pycountry maps language code to human-readable name
• Result is cached and also saved in the database
• History is displayed and paginated with timestamps

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🔮 Future Improvements

• 🔤 Display detection confidence (if supported)
• 🌍 Add language flag icons
• 💬 Translate detected text
• 💽 Export detection history as CSV
• 📱 Mobile-optimized interface with Tailwind CSS

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👨‍💻 Author

Aayush Kadam — Final Year AI & ML Student | Python & Web Enthusiast

"Giving apps the power to understand language—one line at a time."

LinkedIn · GitHub

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⭐️ Show Your Support

If you find this project helpful, please ⭐ the repo and share with your network!

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📜 License

Licensed under the MIT License.

UI and logic were developed for educational and demonstration purposes.