video1.0<iframe src="https://www.loom.com/embed/fa5b4236b9c940f38aa14a618543c071" frameborder="0" width="1440" height="1080" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>10801440Loomhttps://www.loom.com10801440https://cdn.loom.com/sessions/thumbnails/fa5b4236b9c940f38aa14a618543c071-506da8a57ff4432a.gif90.4Hi, my name is Hunter, and this Loom is my rag-powered music recommender final project. It extends my module 3 CSV scoring algorithm by letting you type how you feel in natural language, then it retrieves relevant musical context from the knowledge base and generates personalized recommendations. In my demo, I tried late night and got recommendations like Frank Ocean and Daniel Caesar, then intense workout and got a new set with workout focused picks. I also ran seven end to end tests covering retrieval input validation and logging, and all seven passed. No action was requested from viewers.