NLP Word Analyzer

A full-stack natural language processing application that provides comprehensive word analysis using Vue.js frontend and Python Flask backend with NLTK.

🚀 Features

🔍 Comprehensive Word Analysis

• Part of Speech Identification - Accurate grammatical categorization
• Synonyms & Antonyms - Extensive word relationship mapping
• Definitions - Clear, contextual word meanings
• Example Sentences - Real-world usage demonstrations

🎨 Beautiful User Interface

• Material Design - Clean, modern Vuetify-based UI
• Responsive Layout - Perfect on desktop, tablet, and mobile
• Dark/Light Themes - Seamless theme switching
• Smooth Animations - Polished user experience
• Real-time Feedback - Instant loading states and error handling

🛠 Technical Excellence

• RESTful API - Clean, documented endpoints
• Error Handling - Comprehensive error management
• Input Validation - Robust client and server-side validation
• CORS Support - Cross-origin resource sharing enabled
• Health Monitoring - API status tracking

📋 Prerequisites

• Python 3.13 with pip
• Node.js 16+ with npm
• Git (for cloning)

⚡ Quick Start

Local Development

1. Clone the Repository

git clone <repository-url>
cd nlp-app

2. Backend Setup (Python Flask + NLTK)

cd backend
pip install -r requirements.txt
python app.py

Backend will start at http://localhost:5000

3. Frontend Setup (Vue.js + Vuetify)

cd ../frontend
npm install
npm run serve

Frontend will start at http://localhost:8080

4. Open Your Browser

Navigate to http://localhost:8080 and start analyzing words!

🏗 Project Structure

nlp-app/
├── backend/                 # Python Flask API
│   ├── app.py              # Main Flask application
│   ├── requirements.txt    # Python dependencies
│   └── README.md          # Backend documentation
│
├── frontend/               # Vue.js Application
│   ├── src/
│   │   ├── components/     # Vue components
│   │   │   ├── WordInput.vue
│   │   │   └── AnalysisResult.vue
│   │   ├── services/       # API services
│   │   │   └── nlpService.js
│   │   ├── plugins/        # Vue plugins
│   │   │   └── vuetify.js
│   │   ├── App.vue         # Root component
│   │   └── main.js         # App entry point
│   ├── public/             # Static assets
│   ├── package.json        # Node dependencies
│   └── README.md          # Frontend documentation
│
└── README.md              # This file

🔧 API Endpoints

POST /api/analyze

Analyze a word and return comprehensive linguistic information.

Request:

{
    "word": "beautiful"
}

Response:

{
    "word": "beautiful",
    "partOfSpeech": "Adjective",
    "definition": "delighting the senses or exciting intellectual or emotional admiration",
    "synonyms": ["lovely", "attractive", "gorgeous", "stunning"],
    "antonyms": ["ugly", "hideous", "unattractive"],
    "exampleSentence": "The weather is very beautiful today.",
    "success": true
}

GET /api/health

Check API health status.

Response:

{
    "status": "healthy",
    "message": "NLP API is running"
}

🎯 Usage Examples

1. Basic Word Analysis:

   • Enter "happy" → Get part of speech, synonyms like "joyful", "cheerful"
   • Enter "run" → See verb forms, related words, example usage

2. Complex Words:

   • Enter "serendipitous" → Discover meaning, sophisticated synonyms
   • Enter "ephemeral" → Learn definition, find related concepts

3. Different Parts of Speech:

   • Nouns: "freedom", "innovation", "symphony"
   • Verbs: "create", "analyze", "discover"
   • Adjectives: "magnificent", "intricate", "luminous"
   • Adverbs: "gracefully", "thoroughly", "efficiently"

🛠 Development

Backend Development

• Framework: Flask with CORS support
• NLP Library: NLTK for comprehensive text processing
• Data Sources: WordNet for definitions, synonyms, antonyms
• API Design: RESTful with JSON responses

Frontend Development

• Framework: Vue.js 3 with Composition API
• UI Library: Vuetify 3 (Material Design)
• HTTP Client: Axios for API communication
• Styling: Material Design Icons, custom CSS

Key Dependencies

Backend:

• flask - Web framework
• nltk - Natural language processing
• flask-cors - Cross-origin resource sharing

Frontend:

• vue - JavaScript framework
• vuetify - Material Design components
• axios - HTTP client
• @mdi/font - Material Design Icons

🎨 Design Philosophy

User Experience

• Simplicity First: Clean, uncluttered interface
• Immediate Feedback: Real-time loading and error states
• Visual Hierarchy: Clear information organization
• Accessibility: Proper contrast, keyboard navigation

Technical Approach

• Separation of Concerns: Independent frontend and backend
• Scalable Architecture: Modular component design
• Error Resilience: Graceful error handling and recovery
• Performance: Optimized API calls and rendering

🚀 Production Deployment

Backend Deployment

# Using Gunicorn (recommended)
pip install gunicorn
gunicorn -w 4 -b 0.0.0.0:5000 app:app

# Or using Flask development server (not for production)
python app.py

Frontend Deployment

# Build for production
npm run build

# Serve static files with your preferred web server
# (nginx, Apache, or any static hosting service)

☁️ AWS Cloud Deployment

This application is designed to be deployed on AWS using serverless architecture:

Backend Deployment (AWS Lambda + API Gateway)

cd backend

# Create NLTK data layer
./create_nltk_layer.sh  # Linux/Mac
# or
create_nltk_layer.bat   # Windows

# Deploy with SAM CLI
sam build
sam deploy --guided

See backend/DEPLOYMENT.md for detailed instructions.

Frontend Deployment (AWS Amplify)

1. Update frontend/.env.production with your Lambda API URL
2. Deploy via AWS Amplify Console by connecting your Git repository
3. Amplify will automatically use the amplify.yml configuration

See frontend/AMPLIFY_DEPLOYMENT.md for detailed instructions.

Environment Variables

• Backend: FRONTEND_URL for CORS configuration
• Frontend: VUE_APP_API_URL for API endpoint

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• NLTK Team - Comprehensive natural language processing toolkit
• Vue.js Community - Excellent frontend framework
• Vuetify Team - Beautiful Material Design components
• WordNet - Lexical database for English language

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Built with ❤️ using Vue.js, Python, and Natural Language Processing