AI Chatbot with NLP

A sophisticated Java-based chatbot application featuring Natural Language Processing capabilities, rule-based responses, FAQ handling, and real-time web interface interaction.

Features

• Natural Language Processing: Advanced NLP techniques for understanding user intent
• Rule-based Responses: Intelligent pattern matching for accurate responses
• FAQ System: Pre-configured frequently asked questions with smart matching
• Real-time Communication: WebSocket support for instant messaging
• Modern Web Interface: Responsive React frontend with beautiful UI
• Conversation History: Message persistence and history management
• Intent Detection: Automatic classification of user messages
• Multi-format Support: REST API and WebSocket endpoints

Technology Stack

Backend

• Java 11+ - Core programming language
• Spring Boot 2.7 - Application framework
• Spring WebSocket - Real-time communication
• Maven - Dependency management
• Jackson - JSON processing

Frontend

• React 18 - UI library
• Axios - HTTP client
• SockJS & STOMP - WebSocket communication
• Modern CSS - Responsive design with gradients and animations

Project Structure

├── backend/
│   ├── src/main/java/com/chatbot/
│   │   ├── ChatbotApplication.java
│   │   ├── controller/
│   │   │   └── ChatController.java
│   │   ├── model/
│   │   │   ├── ChatMessage.java
│   │   │   └── ChatResponse.java
│   │   ├── service/
│   │   │   ├── ChatbotService.java
│   │   │   ├── NLPService.java
│   │   │   └── FAQService.java
│   │   └── config/
│   │       └── WebSocketConfig.java
│   ├── src/main/resources/
│   │   └── application.properties
│   └── pom.xml
└── frontend/
    ├── public/
    │   └── index.html
    ├── src/
    │   ├── components/
    │   │   ├── ChatInterface.js
    │   │   ├── MessageList.js
    │   │   ├── Message.js
    │   │   ├── MessageInput.js
    │   │   ├── TypingIndicator.js
    │   │   └── Header.js
    │   ├── services/
    │   │   └── chatService.js
    │   ├── App.js
    │   └── App.css
    └── package.json

Installation & Setup

Prerequisites

• Java 11 or higher
• Node.js 14+ and npm
• Maven 3.6+

Backend Setup

1. Navigate to the backend directory:

cd backend

2. Install dependencies and run:

mvn clean install
mvn spring-boot:run

The backend will start on http://localhost:3000

Frontend Setup

1. Navigate to the frontend directory:

cd frontend

2. Install dependencies:

npm install

3. Start the development server:

npm start

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

API Endpoints

REST API

• POST /api/chat/message - Send a message to the chatbot
• GET /api/chat/history - Retrieve conversation history
• DELETE /api/chat/history - Clear conversation history

WebSocket

• /ws - WebSocket connection endpoint
• /app/chat.sendMessage - Send message via WebSocket
• /topic/public - Subscribe to public messages

NLP Features

The chatbot implements several NLP techniques:

Intent Detection

• Greeting: Recognizes various greeting patterns
• Goodbye: Detects farewell messages
• Help: Identifies requests for assistance
• Weather: Understands weather-related queries
• Time: Recognizes time-related questions
• Name: Responds to identity questions

Pattern Matching

Uses regex patterns for:

• Greeting detection: \b(hello|hi|hey|greetings)\b
• Help requests: \b(help|assist|support)\b
• Weather queries: \b(weather|temperature|forecast)\b

FAQ System

Pre-configured responses for:

• General capabilities
• Technical information
• Privacy and support inquiries
• Getting started guides

Usage Examples

Basic Conversation

User: Hello!
Bot: Hello! How can I help you today?

User: What can you do?
Bot: I can help answer questions, have conversations, provide information about various topics, and assist with general queries. I'm designed to be helpful and friendly!

User: What's the weather like?
Bot: I don't have access to real-time weather data, but I recommend checking a weather app or website for current conditions in your area.

FAQ Queries

User: How do you work?
Bot: I use natural language processing to understand your questions and provide relevant responses. I can recognize patterns in text and match them with appropriate answers.

User: Are you human?
Bot: No, I'm an AI chatbot designed to help and interact with users. I'm a computer program created to simulate conversation.

Customization

Adding New Intents

1. Add patterns to NLPService.java:

private static final Pattern CUSTOM_PATTERN = Pattern.compile("\\b(custom|specific)\\b", Pattern.CASE_INSENSITIVE);

2. Update intent detection:

private String detectIntent(String message) {
    if (CUSTOM_PATTERN.matcher(message).find()) {
        return "custom";
    }
    // ... existing patterns
}

3. Add response generation:

case "custom":
    return "Your custom response here!";

Adding FAQ Entries

Update FAQService.java:

@PostConstruct
public void initializeFAQData() {
    faqData.put("your question", "Your answer here");
    // ... existing FAQs
}

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

Future Enhancements

• Integration with external NLP services (OpenAI, Dialogflow)
• Voice input/output capabilities
• Multi-language support
• Advanced analytics and conversation insights
• Machine learning model training
• Database integration for persistent storage
• User authentication and personalization
• Mobile app development