{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/515e3c4222b54f608deb5dc8457a58ae\" frameborder=\"0\" width=\"1728\" height=\"1296\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1296,"width":1728,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1296,"thumbnail_width":1728,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/515e3c4222b54f608deb5dc8457a58ae-04fb5c6a978dbef4.gif","duration":265.198,"title":"AI Music Recommendation Simulation Workflow Demo","description":"In this Loom I demonstrate my Module 3 Form Music Recommendation Simulation with an end to end workflow, including retrieval content, confidence score, EES, and warning handling. I explain how the demo highlights high energy prompts and mood choices before generating recommendations. I also show the drag and cursor style flow, plus deep instinct rock as another highlighted result. Then I run the project with multiple predefined profiles and summarize guidance for different behaviors and coverage. Please review and confirm if you want any changes to the workflow or confidence score logic."}