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Sentiment Analysis LLM Web Application

A modern, real-time sentiment analysis web application powered by Hugging Face transformer models. This project provides an intuitive interface for analyzing text sentiment with animated visualizations and confidence scores.

Sentiment Analysis Demo React Node.js Express

🚀 Features

  • Real-time Sentiment Analysis: Instant text analysis using state-of-the-art transformer models
  • Interactive UI: Clean, responsive React interface with animated progress bars
  • Multi-language Support: Powered by BERT-based multilingual sentiment classifier
  • Confidence Scoring: Detailed sentiment breakdown with percentage confidence levels
  • Visual Feedback: Animated progress bars showing positive/negative sentiment distribution
  • RESTful API: Clean backend architecture with proper error handling

🛠️ Technologies Used

Frontend

  • React.js - Modern UI library for component-based architecture
  • Axios - HTTP client for API communication
  • CSS3 - Custom styling with animations and responsive design
  • HTML5 - Semantic markup structure

Backend

  • Node.js - JavaScript runtime environment
  • Express.js - Fast, minimalist web framework
  • Hugging Face Inference API - Access to transformer models
  • CORS - Cross-origin resource sharing middleware
  • dotenv - Environment variable management

AI/ML

  • Hugging Face Transformers - Pre-trained sentiment analysis models
  • BERT-based Models - Multilingual sentiment classification
  • nlptown/bert-base-multilingual-uncased-sentiment - 5-star rating sentiment model

📋 Prerequisites

Before running this application, make sure you have:

  • Node.js (v16 or higher)
  • npm or yarn package manager
  • Hugging Face API token (free registration required)

🔧 Installation & Setup

1. Clone the Repository

git clone https://github.com/maheera421/Sentiment-Analysis-LLM.git
cd Sentiment-Analysis-LLM

2. Backend Setup

cd Backend
npm install

Create a .env file in the Backend directory:

HF_API_KEY=your_huggingface_api_token_here
PORT=5000

3. Frontend Setup

cd sentiment-frontend
npm install

4. Get Hugging Face API Token

  1. Visit Hugging Face
  2. Create a free account
  3. Go to Settings → Access Tokens
  4. Create a new token with "Read" permissions
  5. Copy the token to your .env file

🚀 Running the Application

Start the Backend Server

cd Backend
npm start

The backend will run on http://localhost:5000

Start the Frontend Development Server

cd sentiment-frontend
npm start

The frontend will run on http://localhost:3000

🔍 API Endpoints

POST /api/sentiment-analysis

Analyzes the sentiment of provided text.