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Implement TextRazor NLP Analyzer with frontend and backend integration
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‎New_APIs/TextRazor_API/PROJECT_SUMMARY.md‎

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# TextRazor API Integration - Project Summary
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✅ **Complete Implementation Ready!**
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## What's Been Built
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### 🔧 Backend (Node.js + Express)
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- **Server**: Full REST API server with TextRazor integration
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- **Routes**: Comprehensive API endpoints for all NLP features
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- **Security**: Rate limiting, CORS, helmet protection
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- **Error Handling**: Robust error management and validation
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### 🎨 Frontend (HTML/CSS/JavaScript)
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- **Interface**: Clean, modern, responsive web interface
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- **Features**: Entity extraction, sentiment analysis, topic classification
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- **UX**: Real-time feedback, loading states, error handling
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- **Export**: JSON export functionality for results
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### 📁 Project Structure
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```
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TextRazor_API/
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├── README.md
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├── PROJECT_SUMMARY.md
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└── server/
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├── package.json
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├── package-lock.json
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├── server.js
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├── .env.example
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├── .env
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├── node_modules/
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├── routes/
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│ └── textrazor.js
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└── public/
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├── index.html
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├── styles.css
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└── script.js
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```
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## 🚀 Ready to Use
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### Server Endpoints Available:
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- `POST /api/analyze` - Full text analysis
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- `POST /api/entities` - Entity extraction only
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- `POST /api/sentiment` - Sentiment analysis only
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- `POST /api/topics` - Topic classification only
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- `POST /api/language` - Language detection only
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- `GET /health` - Health check
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### Frontend Features:
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- Interactive text input with sample texts
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- Checkbox options for analysis types (entities, sentiment, topics, relations, language)
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- Real-time results display with visual indicators
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- Export functionality (JSON download)
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- Mobile-responsive design
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- Loading states and error handling
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## 🔑 Next Steps
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1. Get TextRazor API key from textrazor.com
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2. Create .env file with your API key in the server directory
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3. Run the server: `cd server && npm start`
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4. Open server/public/index.html in browser or visit http://localhost:5000
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5. Start analyzing text!
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**All ready for deployment and use! 🎉**

‎New_APIs/TextRazor_API/README.md‎

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# TextRazor API Integration
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## Description
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This API integration provides natural language processing capabilities using TextRazor's powerful NLP service. It offers entity extraction, sentiment analysis, topic classification, and relationship extraction from text documents. The application features a clean HTML/CSS/JavaScript frontend for interactive text analysis and a Node.js backend for API integration.
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## Features
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1. **Entity Extraction** - Identify and extract entities (people, places, organizations, etc.) from text
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2. **Sentiment Analysis** - Analyze the emotional tone and sentiment of text content
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3. **Topic Classification** - Automatically categorize text into relevant topics
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4. **Relationship Extraction** - Discover relationships between entities in the text
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5. **Language Detection** - Automatically detect the language of input text
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6. **Interactive Web Interface** - User-friendly HTML/CSS/JavaScript frontend for text analysis
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## Requirements
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- Node.js (v14 or higher)
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- npm or yarn
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- TextRazor API key (free tier available)
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- Modern web browser
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## Installation
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### 1. Clone the Repository:
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```bash
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git clone <repository-url>
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cd TextRazor_API
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```
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### 2. Install Server Dependencies:
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```bash
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cd server
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npm install
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```
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### 3. Setup Environment Variables:
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Create a `.env` file in the server directory:
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```env
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TEXTRAZOR_API_KEY=your_textrazor_api_key_here
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PORT=5000
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```
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### 4. Get TextRazor API Key:
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1. Visit [TextRazor](https://www.textrazor.com/)
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2. Sign up for a free account
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3. Get your API key from the dashboard
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4. Add it to your `.env` file
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## Usage
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### Start the Server:
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```bash
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cd server
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npm start
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```
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### Access the Application:
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The server serves both the API and the web interface:
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- **Web Interface**: Open your browser and go to `http://localhost:5000`
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- **API Endpoints**: Available at `http://localhost:5000/api/`
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Alternatively, you can directly open the HTML file:
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```bash
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# Navigate to server/public and open index.html in your browser
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cd server/public
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# Open index.html in your default browser (double-click or right-click -> Open with -> Browser)
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```
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## API Endpoints
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### 1. Analyze Text
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```http
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POST /api/analyze
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Content-Type: application/json
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{
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"text": "Your text to analyze here",
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"extractors": ["entities", "sentiment", "topics", "relations", "language"]
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}
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```
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### 2. Extract Entities Only
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```http
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POST /api/entities
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Content-Type: application/json
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{
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"text": "Your text here"
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}
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```
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### 3. Sentiment Analysis Only
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```http
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POST /api/sentiment
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Content-Type: application/json
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{
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"text": "Your text here"
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}
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```
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### 4. Topic Classification
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```http
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POST /api/topics
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Content-Type: application/json
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{
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"text": "Your text here"
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}
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```
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### 5. Language Detection
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```http
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POST /api/language
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Content-Type: application/json
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{
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"text": "Your text here"
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}
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```
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## Example Response
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### Entity Extraction Response:
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```json
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{
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"success": true,
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"entities": [
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{
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"id": "Apple Inc.",
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"type": "Company",
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"confidence": 0.95,
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"relevanceScore": 0.8,
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"matchedText": "Apple"
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}
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],
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"sentiment": {
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"score": 0.2,
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"label": "positive"
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},
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"topics": [
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{
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"id": "Technology",
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"score": 0.85
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}
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]
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}
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```
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### Language Detection Response:
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```json
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{
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"success": true,
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"language": {
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"code": "eng",
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"isReliable": true
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},
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"metadata": {
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"textLength": 150
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}
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}
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```
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## Technology Stack
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- **Frontend**: HTML5, CSS3, JavaScript (Vanilla)
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- **Backend**: Node.js, Express.js
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- **API**: TextRazor NLP API
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- **HTTP Client**: Fetch API (built-in)
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## Features Demo
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1. **Text Input**: Large textarea for entering text to analyze with auto-resize functionality
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2. **Analysis Options**: Checkboxes to select which analysis to perform (entities, sentiment, topics, relations, language)
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3. **Results Display**: Organized sections showing entities, sentiment, topics, relationships, and language detection
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4. **Visual Indicators**: Color-coded sentiment results and confidence scores
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5. **Export Results**: Download analysis results as JSON file
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6. **Responsive Design**: Works on desktop, tablet, and mobile devices
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7. **Real-time Feedback**: Loading states and error handling
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8. **Sample Texts**: Pre-loaded example texts for quick testing
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## Notes
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- Free TextRazor account includes 500 requests per day
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- Ensure your API key is kept secure and not committed to version control
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- The application handles various text formats and languages
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- Error handling is implemented for API failures and network issues
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- The server serves both API endpoints and the web interface on the same port
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## Contributing
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Please follow the project's contributing guidelines and ensure all code is properly tested before submitting pull requests.
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## License
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This project is licensed under the MIT License.
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## Project Structure
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```
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TextRazor_API/
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├── README.md
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├── PROJECT_SUMMARY.md
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└── server/
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├── package.json
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├── package-lock.json
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├── server.js
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├── .env.example
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├── .env
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├── node_modules/
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├── routes/
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│ └── textrazor.js
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└── public/
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├── index.html
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├── styles.css
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└── script.js
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```

‎New_APIs/TextRazor_API/server/.env.example‎

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# TextRazor API Configuration
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TEXTRAZOR_API_KEY=your_textrazor_api_key_here
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# Server Configuration
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PORT=5000
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NODE_ENV=development
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# Client Configuration
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CLIENT_URL=http://localhost:3000

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