{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/2cff3d786df143879fc79fadf8e35af5\" frameborder=\"0\" width=\"1280\" height=\"960\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":960,"width":1280,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":960,"thumbnail_width":1280,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/2cff3d786df143879fc79fadf8e35af5-00001.gif","duration":146.52500000000003,"title":"Movies app + recommendation","description":"Hey there! In this Loom, I'll walk you through a project I worked on last week where I explored vector databases and created a movie recommendation app using v8. The app has a main dashboard with trending movies and personalized recommendations. You can also search for movies by title and get detailed information, including similar movies based on title and overview. I'll show you how bookmarking works too. It's made with Next.js, CSS, TypeScript, and has a Python Flask backend with VV8 as the vector database. Check it out!"}