AI-Healthy-Chatbot

Overview

The AI-Healthy-Chatbot is a web application designed to provide users with health-related guidance and recommendations through a natural language chatbot interface. Users can track their health metrics, receive personalized tips, and monitor their progress over time. The project is powered by Node.js, OpenAI, and a MongoDB database.

Project Structure

Frontend

• HTML Pages:
  • index.html: Home page with an introduction to the web app.
  • chatbot.html: Chatbot interaction interface.
  • health-tips.html: Page with health-related resources and tips.
  • profile.html: User profile and activity summary.
• CSS:
  • styles.css: Main stylesheet for layout and design.
  • Responsive design for desktop and mobile.
• JavaScript:
  • main.js: Handles general page functionality and navigation.
  • chatbot.js: Contains the chatbot logic (e.g., handling user input/output).
  • health-tips.js: Fetches and displays health-related data dynamically.

Backend

• Implemented using Node.js for server-side logic.
• AI API Integration:
  • OpenAI API for chatbot responses.
• Database:
  • MongoDB to store user data (chat history, health preferences, progress tracking).
  • Database initialization handled via database.js.

Directory Structure

AI-Healthy-Chatbot/
├── index.html
├── assets/
│   ├── css/
│   │   └── styles.css
│   ├── js/
│   │   ├── main.js
│   │   ├── chatbot.js
│   │   └── health-tips.js
│   ├── images/
│   │   └── (any images used in your project)
│   └── fonts/
│       └── (custom fonts, if needed)
├── backend/
│   ├── server.js
│   └── database/
│       └── database.js
├── README.md

Features

Chatbot

• Natural Language Processing (NLP)-based chatbot for health-related queries.
• Ability to handle user-specific health inquiries (e.g., nutrition, exercise).
• Integration with OpenAI for generating responses.
• Contextual memory for better conversational experience.

Health Tracking and Recommendations

• User input form to track health metrics (e.g., weight, steps, sleep hours).
• Generate personalized health tips based on user data.
• Integration with external health APIs (e.g., fitness apps, wearable devices).

User Dashboard

• Profile management system for users to track their health data and interactions.
• Data visualization (e.g., charts for progress over time).

Advanced Features

• Sentiment Analysis: Detect user emotions during conversations.
• Voice Input/Output: Add speech-to-text and text-to-speech functionality for better accessibility.
• Predictive Analysis: Provide predictions or suggestions based on user health patterns.

Setup Instructions

Prerequisites

• Node.js (v16 or higher)
• MongoDB (local or cloud instance)
• OpenAI API Key

Installation

1. Clone the repository:

   git clone https://github.com/your-repo/AI-Healthy-Chatbot.git
   cd AI-Healthy-Chatbot

2. Install dependencies:

   npm install

3. Set up environment variables:
   • Create a .env file in the root directory.
   • Add the following variables:

     PORT=5000
     MONGO_URI=mongodb://localhost:27017/healthy_chatbot
     OPENAI_API_KEY=your_openai_api_key

Running the Application

1. Start MongoDB (if running locally):

   mongod

2. Run the server:

   npm start

3. Open index.html in your browser to access the frontend.

API Endpoints

Chatbot Endpoint

• POST /chat
• Description: Processes user messages and returns a chatbot response.
• Request Body:

  {
      "message": "Your question here",
      "userId": "user123"
  }

• Response:

  {
      "botResponse": "Chatbot's response"
  }

Health Metrics Endpoint

• POST /health-metrics
• Description: Updates and retrieves user health metrics.
• Request Body:

  {
      "userId": "user123",
      "metrics": {
          "weight": 70,
          "steps": 10000,
          "sleepHours": 8
      }
  }

• Response:

  {
      "message": "Health metrics updated successfully"
  }

Suggested Tools and Libraries

• Frontend:
  • Bootstrap or Tailwind CSS for UI components.
  • Chart.js or D3.js for visualizations.
  • Vanilla JavaScript or React.js for interactivity.
• Backend:
  • Node.js with Express.js for server setup.
  • OpenAI API for chatbot intelligence.
  • MongoDB for database.
• APIs and Services:
  • Google Cloud Text-to-Speech and Speech-to-Text.
  • Health APIs (e.g., Nutritionix, Fitbit API).

Future Enhancements

• Add an admin panel for content management and chatbot performance review.
• Enhance chatbot accuracy with custom AI models.
• Enable OAuth-based login and integration with fitness trackers.