Project summary
SnapTune is a multimodal music recommender that uses image context to support music recommendation workflows.
Case Study
SnapTune - Multimodal Music Recommender
Multimodal music recommendation app described in the existing portfolio as combining image captioning, mood inference, and Spotify search.
Technical approach
Existing portfolio content describes BLIP captioning, GPT-based mood inference, DistilGPT2, Spotify API integration, and a Streamlit interface.
Challenges and limitations
No repository-local source code or live demo URL is available in this workspace, so this case study avoids unverifiable metrics and deployment claims.
Technology stack
Streamlit, BLIP, DistilGPT2, Spotify API, and multimodal recommendation logic are referenced in current site content.
Contact
Discuss multimodal AI ideas
Open to AI/ML internships, research collaborations, fellowships, and December 2026 full-time opportunities.