Dhyan AI

Dhyan AI is an all-in-one health and well-being web application designed to enhance users' lifestyles through personalized yoga recommendations, habit tracking, health recipe suggestions, and productivity tools.

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🌟 Features

🧨 Yoga Recommendations

• Personalized Yogasana Recommendations based on your health issues.
• Utilizes SambaNova AI Cloud Services and the Meta LLM model to generate relevant yoga asanas.
• Detailed instructions and benefits for each yogasana are provided.

📊 Habit Tracking

• Track daily habits such as water intake, exercise, and yoga.
• View insightful monthly statistics to monitor progress and improve health.

🥗 Health Recipe Recommendations

• Get personalized health recipes by entering the ingredients you have.
• Uses Meta LLM on SambaNova AI Cloud Services to provide accurate and healthy meal suggestions.

⏱️ Pomodoro Timer

• Boost productivity with the Pomodoro Technique.
• Manage and track your activities effectively by dividing your time into focused work sessions and breaks.

🔐 AWS Cognito Authentication

• Secure and seamless login and authentication using AWS Cognito.

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🛠️ Tech Stack

• Frontend: HTML, EJS, Bootstrap
• Backend: Node.js with Express
• Database: MongoDB
• AI Services: SambaNova AI Cloud Services (Meta LLM model)
• Authentication: AWS Cognito

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🚀 Getting Started

Follow the steps below to set up and run the Dhyan AI application locally.

Prerequisites

Ensure you have the following installed:

• Node.js (v14 or above)
• MongoDB
• SambaNova API Access
• AWS Cognito Setup

Installation

1. Clone the repository:

   git clone https://github.com/Rajukrsna/DhyanAI.git
   cd dhyan-ai

2. Install dependencies:

   npm install

3. Set up environment variables:

   Create a .env file in the root directory and add the following:

   PORT=3000
   MONGODB_URI=your-mongodb-uri
   SAMBANOVA_API_KEY=your-sambanova-api-key
   AWS_COGNITO_CLIENT_ID=your-cognito-client-id
   AWS_COGNITO_USER_POOL_ID=your-cognito-user-pool-id
   

4. Run the application:

   npm start

5. Open the application:

   Visit http://localhost:3000 in your browser.

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📂 Project Structure

.
├── views/           # EJS templates
├── public/          # Static files (CSS, JS, images)
├── routes/          # Express routes
├── models/          # Mongoose models
├── app.js           # Main server file
├── package.json     # Project dependencies
└── .env             # Environment variables

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🖼 Screenshots

1. Yoga Recommendations

2. Habit Tracking

3. Nutritional Analysis

4. Food Item Chatbot

🫏️ Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature/your-feature-name

3. Commit your changes:

   git commit -m "Add new feature"

4. Push to the branch:

   git push origin feature/your-feature-name

5. Open a Pull Request.

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📄 License

This project is licensed under the MIT License.

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📩 Contact

For any questions or suggestions, reach out to:

• Email: [email protected]
• LinkedIn: Your LinkedIn Profile

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⭐ If you like this project, don't forget to star the repository!