Vybe 🎉

Vybe is a real-time crowd feedback system for DJs. It analyzes crowd movement and energy to generate a “Vibe Score,” helping DJs select the perfect tracks to match or elevate the mood at student parties and events.

Core Features

• Real-Time Vibe Score: Generates a live score based on crowd energy using computer vision.
• DJ Dashboard: A responsive interface built with Next.js and TypeScript for monitoring the crowd and receiving track recommendations.
• Audience Voting System: Allows the audience to vote on songs, providing direct feedback.
• AI-Powered Recommendations: Uses Groq for fast inference to suggest tracks that align with the current vibe.

Tech Stack

• Frontend: Next.js, TypeScript
• Backend: Python, AWS Lambda
• API: Amazon API Gateway
• Database: Amazon DynamoDB
• Computer Vision: OpenCV
• AI/ML: Groq

Getting Started

To get a local copy up and running, follow these steps.

Prerequisites

• Node.js and npm
• Python 3

Installation

1. Clone the repo:

   git clone https://github.com/eunsongkoh/vybe.git

2. Install frontend dependencies:

   cd frontend
   npm install

3. Install backend dependencies:

   cd ../backend
   # Assuming a requirements.txt file exists
   pip install -r requirements.txt

Usage

1. Start the frontend development server:

   cd frontend
   npm run dev

2. Start the backend server:

   cd ../backend
   python app.py

Future Development

• Integration with Spotify / Apple Music APIs
• Enhanced machine learning models for more accurate Vibe Scores
• Scaling for larger venues and clubs
• A mobile app for real-time song voting and requests

Contributing

Contributions are welcome! Please follow these steps:

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License.