Inspiration:
In today's world, all of us face a series of mood swings and emotions. After a long day, no one wants to scroll - they just want something that fits. This app is going to act like a personal DJ for your emotions.
What it does: The Mood-to-Music app takes how you feel — either through your words or your voice — analyzes your mood, and instantly recommends playlists that match it.
How we built it: We built this Mood-to-Music app using Python Flask for the backend and vanilla HTML/CSS/JavaScript for the frontend. The app analyzes user text to detect moods like happy, sad, calm, or energetic, then displays relevant Spotify playlists using their embed API. It supports multiple languages and provides personalized music recommendations based on emotional input.
Challenges we ran into: Some challenges included getting Spotify OAuth authentication to work properly and handling API rate limits. Finding reliable song preview URLs was difficult since many tracks don't have previews available. Also, ensuring the mood detection accurately interpreted different emotional expressions across languages required careful tuning of the keyword matching system.
Accomplishments that we're proud of: We tried our very best to accomplish the app that we wanted to build. We wanted to include more features like group chat linking and start a jam with people facing a similar mood. However, some of these advanced features were not fully accomplished, but as a team, we participated and learned a lot of new things.
What we learned: As a team, we learned how to integrate third-party APIs like Spotify into web applications and handle authentication flows. We discovered the importance of having fallback mechanisms when API responses are unreliable, and gained experience in building responsive frontends that provide a good user experience even when certain features aren't available. We also learned to iterate quickly by testing different approaches until we found the most reliable solution for delivering music recommendations.
What's next for Mood-to-music:Looking ahead, Mood-to-Music has an exciting roadmap for evolution. The immediate next steps involve implementing user accounts to enable personalized mood history tracking and saved playlists, while also developing a mobile app version for on-the-go accessibility. Beyond that, we plan to integrate AI-powered mood analysis for more nuanced emotional detection and introduce social features that allow users to share their mood playlists with friends. The ultimate vision includes full Spotify Web Playback SDK integration for seamless song playback and expanding to support multiple music platforms, transforming the app into a comprehensive mood-based music wellness ecosystem that grows with our users' emotional journeys.
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