🎵 Mood-Based Music Recommender

The Mood-Based Music Recommender is an innovative, web-based application designed to bridge the gap between your emotional state and the perfect musical accompaniment. Forget endless scrolling; this recommender instantly curates a personalized playlist based on your current emotional input, ensuring your music always resonates with your feelings. Built for an intuitive and responsive user experience, this app transforms mood detection into immediate musical gratification.

✨ Features

This application delivers a seamless and highly personalized music recommendation experience through a suite of core features:

• Dynamic Mood Detection: Users can input their current emotional state (e.g., Happy, Sad, Energetic, Calm) either through a simple, interactive selection menu or potentially via integration with advanced input methods.
• Personalized Playlist Curation: Leveraging powerful music API integration, the recommender fetches and organizes tracks specifically tailored to the detected mood, moving beyond generic genre recommendations.
• Interactive & Responsive UI: Built with modern HTML, CSS (using Flexbox/Grid for layout), and pure JavaScript, the interface is accessible and functional across all devices, from desktop monitors to mobile phones.
• Seamless Music Playback: Provides embedded playback controls to listen to a snippet or the full track directly within the application (depending on API licensing).
• Minimalist Aesthetic: A clean, visually appealing design prioritizes ease of use and focuses the user on the music selection process.
• Track & Mood History: (Hypothetical extension for longer README) The potential to log and revisit previously recommended playlists and associated moods.

🚀 Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

You will need a modern web browser and a code editor.

Installation

1. Clone the repository:

   git clone [https://github.com/raymondoyondi/Mood-Based-Music-Recommender.git](https://github.com/raymondoyondi/Mood-Based-Music-Recommender.git)

2. Navigate into the directory:

   cd Mood-Based-Music-Recommender

3. Open the Application: Since this is a client-side application built with HTML, CSS, and JavaScript, you can run it directly in your browser.

   • Locate the index.html file in the root directory.
   • Right-click on index.html and select "Open with" -> [Your Web Browser (e.g., Chrome, Firefox)].

4. API Key Configuration (Crucial for Functionality): The app relies on a third-party Music API (e.g., Spotify, SoundCloud) to fetch track data.

   • You will need to sign up for an API key from the chosen service.
   • Locate the placeholder configuration file (e.g., config.js or within the main JavaScript file) and insert your unique API key and necessary credentials.

💡 Usage

The application is designed for simplicity:

1. Launch the App: Open index.html in your browser.
2. Select Your Mood: An intuitive interface will present a series of emotional categories. Click or tap on the one that best reflects your current state.
3. Generate Playlist: The application instantly processes your selection and sends a request to the music API.
4. Enjoy the Music: A curated list of songs will populate the playlist view. You can browse the list and begin playback immediately.

🛠️ Technologies Used

The Mood Music Recommender is a highly efficient, single-page web application leveraging foundational web technologies:

Technology	Role	Key Features
HTML5	Semantic Structure	Provides the structural framework and content.
CSS3	Styling & Layout	Used for styling, responsiveness, CSS Variables for theming, and Flexbox/Grid for fluid layout.
JavaScript	Core Logic Engine	Handles mood-to-API data transformations, dynamic DOM manipulation, and manages the interactive user experience (no heavy frameworks).
Spotify API	Data Source	Necessary external integration for accessing a vast database of music tracks and generating relevant playlists.

🤝 Contributing

Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the repository.
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. See LICENSE for more information.