README.md

metadata

title: Chatbot
emoji: 🤖
colorFrom: indigo
colorTo: blue
sdk: docker
sdk_version: '1.0'
app_file: app.py
pinned: false

CampVerse Chatbot Microservice

Features

• Gemini AI Integration: Enhanced NLP understanding using Google's Gemini API
• Intent Classification: Smart detection of user intents (event search, greetings, help, etc.)
• Semantic Event Search: Find events using natural language queries
• FAQ Support: Answer common questions about the platform
• Real-time Chat: WebSocket support for live conversations

Quick Start for New Users

If you're new and want to run this chatbot microservice, you can choose either Docker or Python. Both methods are described below:

---

🚀 Run via Python (Local Development)

1. Clone the Repository

git clone https://github.com/CcpC-cuj/CampVerse.git
cd CampVerse/ML/chatbot

2. Install Python & Dependencies Make sure you have Python 3.10+ installed. Then install dependencies:

pip install -r requirements.txt

3. Set Environment Variables

   export BACKEND_URL=http://localhost:5001  # Backend API URL
   export GEMINI_API_KEY=your_gemini_api_key  # For enhanced NLP (optional)
   

4. Start the Backend Service

   uvicorn app:app_socket --host 0.0.0.0 --port 8000
   

5. Test with CLI Chat Client Open a new terminal and run:

python cli_chat.py

Type your questions and interact with the bot.

---

🐳 Run via Docker (Containerized)

1. Build the Docker Image

docker build -t chatbot-service .

2. Run the Docker Container

   docker run -p 8000:8000 -e BACKEND_URL=http://localhost:5001 chatbot-service
   ```3. **Test the Service**
   

• REST API:

  curl -X POST http://localhost:8000/chatbot -H "Content-Type: application/json" -d '{"question":"How do I register?"}'
  

• Socket.IO:

  python cli_chat.py
  

---

🌐 Integrate with Your Web App

Use REST API or Socket.IO as shown below to connect your frontend.

---

A production-ready chatbot microservice using FastAPI, Socket.IO, and sentence transformers for FAQ-based question answering.

Features

• 🚀 FastAPI REST API: HTTP endpoint for Q&A
• 🔌 Socket.IO Real-time: WebSocket support for live chat
• 🤖 AI-Powered: Uses sentence transformers and FAISS for semantic search
• 🎯 Intent Classification: Detects greetings, event queries, help requests, and more
• 🔍 Dynamic Event Discovery: Fetches and searches live events from backend API
• 🐳 Docker Ready: Containerized for easy deployment
• 📝 Logging: Comprehensive logging for debugging
• ✅ Input Validation: Validates question length and content
• 🌐 CORS Enabled: Ready for frontend integration

Architecture

┌─────────────────┐
│   Frontend      │
│  (React/Web)    │
└────────┬────────┘
         │
         │ HTTP POST /chatbot
         │ OR Socket.IO
         │
┌────────▼────────┐
│   app.py        │
│  FastAPI +      │
│  Socket.IO      │
└────────┬────────┘
         │
         │ Semantic Search
         │
┌────────▼────────┐
│   faq.json      │
│  (FAQ Database) │
└─────────────────┘

API Endpoints

REST API

POST /chatbot

Request:
{
  "question": "How do I register?"
}

Response:
{
  "question": "How do I register?",
  "answer": "Click on the Register button..."
}

Socket.IO Events

Client → Server

• user_question: Send a question

  socket.emit('user_question', { question: 'How do I login?' });
  

Server → Client

• bot_answer: Receive answer

  socket.on('bot_answer', (data) => {
    console.log(data.answer);
  });
  

Setup & Installation

Local Development

1. Install dependencies:

   pip install -r requirements.txt
   

2. Run the server:

   uvicorn app:app_socket --host 0.0.0.0 --port 8000
   

3. Test with CLI client:

   python cli_chat.py
   

Docker Deployment

1. Build the image:

   docker build -t chatbot-service .
   

2. Run the container:

   docker run -p 8000:8000 chatbot-service
   

3. Test the service:

   • REST API: curl -X POST http://localhost:8000/chatbot -H "Content-Type: application/json" -d '{"question":"How do I register?"}'
   • Socket.IO: python cli_chat.py

Project Structure

chatbot/
├── app.py              # Main backend (FastAPI + Socket.IO)
├── cli_chat.py         # CLI client for testing
├── Dockerfile          # Docker configuration
├── faq.json            # FAQ database
├── requirements.txt    # Python dependencies
└── README.md           # This file

Integration with Frontend

React Example (Socket.IO)

import io from 'socket.io-client';

const socket = io('http://localhost:8000');

socket.on('connect', () => {
  console.log('Connected to chatbot');
});

socket.on('bot_answer', (data) => {
  console.log('Answer:', data.answer);
});

// Send question
socket.emit('user_question', { question: 'How do I login?' });

React Example (REST API)

const response = await fetch('http://localhost:8000/chatbot', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({ question: 'How do I login?' })
});

const data = await response.json();
console.log(data.answer);

Configuration

Environment Variables

You can configure the service using environment variables:

• PORT: Server port (default: 8000)
• LOG_LEVEL: Logging level (default: INFO)

FAQ Management

Edit faq.json to add/update questions and answers:

[
  {
    "question": "How do I register?",
    "answer": "Click on the Register button on the homepage..."
  }
]

After updating, rebuild the Docker image or restart the server.

Monitoring & Logs

The service logs all:

• Client connections/disconnections
• Incoming questions
• Matched FAQ pairs
• Errors and warnings

View logs in Docker:

docker logs -f <container-id>

Security

• CORS is enabled for all origins (configure for production)
• Input validation (max 512 characters)
• Error handling to prevent crashes
• No rate limiting (add if needed for production)

Testing

Manual Testing

1. Start the service
2. Run CLI client: python cli_chat.py
3. Type questions and verify responses

Testing REST API

curl -X POST http://localhost:8000/chatbot \
  -H "Content-Type: application/json" \
  -d '{"question":"How do I register?"}'

Troubleshooting

Service won't start:

• Check if port 8000 is available
• Verify all dependencies are installed
• Check logs for errors

CLI client can't connect:

• Ensure service is running on port 8000
• Check firewall settings
• Verify python-socketio is installed

No answer returned:

• Check if faq.json exists and is valid
• Verify the question exists in FAQ database
• Check server logs for errors

Future Enhancements

• Add rate limiting for production
• Add authentication for Socket.IO
• Support multiple languages
• Add conversation history
• Implement fallback responses
• Add metrics and analytics

License

Part of the CampVerse project.