github.com/nitrajsinh-solanki/hackathon_may_stackup
04 / 11
🎖 $20 Merit Prize
Moodify — AI Music Streaming App
Moodify is a context-aware music platform built with a two-person team. The Gemini AI engine ingests your current weather (OpenWeather API), location, time of day, and listening history to generate hyper-personalised track recommendations. Users can stream from three independent sources — Jamendo, Deezer, and Audius — through a single unified interface, upload their own tracks to Cloudinary, and chat with an AI music assistant in a conversational interface.
Built in a team of 2 — Nitrajsinh Solanki (AI, APIs, Auth, Architecture) & Amar Tiwari (UI/UX, Music Player, Geo/Weather)
Engineering Case Study
- Challenge
- Music discovery can feel generic when it ignores a listener’s context, and tracks from different streaming catalogues are fragmented across services.
- Approach
- Use Gemini AI with weather, location, time of day and listening history to guide recommendations, while bringing Jamendo, Deezer and Audius into one Next.js interface.
- Contribution
- In a two-person team, focused on AI integration, API orchestration, authentication and application architecture; the project also includes an AI music chat, unified player, playlists and user uploads.
- Outcome
- Delivered a context-aware, multi-source music experience and received a $20 merit prize in the StackUp Hackathon.
Key Features
- Weather + location based AI music recommendations via Gemini
- Behavioural recommendations from listening history and liked tracks
- Multi-source streaming — Jamendo, Deezer, Audius in one UI
- Conversational AI music chat — describe mood, get track suggestions
- Custom music player with audio visualizer and queue system
- Upload your own tracks to Cloudinary with metadata
- Personal library — saved albums, playlists, liked tracks
- AI-generated listening behaviour summaries
Tech Stack
Next.js 15React 19MongoDBGoogle Gemini AICloudinaryJamendo APIDeezer APIAudius APIOpenWeather APITheAudioDBJWTTailwind CSS