Innovating with Mood-Based Music Curation: A Web App Powered by Gemini and Spotify APIs

In today’s digital landscape, personalized experiences are more important than ever. Recently, I developed a web application that transforms natural language mood descriptions into tailored Spotify playlists—an intuitive tool that taps into cutting-edge AI for mood understanding and music curation.

What Does It Do?

Users can type in any mood or feeling—ranging from “motivated for the gym” to “nostalgic without feeling sad”—and receive a carefully curated playlist that matches their emotional state. This approach bridges the gap between abstract human emotions and concrete musical experiences, offering a new way to discover music that resonates personally.

Technology Behind the Project

• Frontend Framework: Built with Next.js 14, ensuring a fast, server-rendered experience.
• Mood Analysis & Song Curation: Leveraging the Gemini API, which intelligently interprets natural language descriptions and suggests relevant tracks.
• Music Integration: Utilizing the Spotify Web API to generate and create playlists directly within Spotify.
• Design & Styling: Styled with Tailwind CSS complemented by custom CSS variables for a consistent and appealing aesthetic.
• Deployment: Hosted seamlessly on Vercel for reliable access.

This project showcases how combining AI-powered mood interpretation with popular streaming services can elevate personal music experiences, making music discovery more intuitive and emotionally aligned.

Experience it firsthand at https://beats-on-feels.vercel.app/.

Discover how technology can deepen your connection to music—one mood at a time.