Build a Movie Recommendation App with OpenAI
By External Provider
About this course
In this project, you'll develop Pop Choice, an AI-powered movie recommendation app designed to simplify the decision-making process for movie night. Using AI embeddings, vector databases, and the OpenAI API, the app will recommend the perfect movie based on user preferences gathered through a series of open and close-ended questions. Users input their mood and preferences, and the app searches a database of movies to find the best match. As a stretch goal, the app can be adapted for group recommendations, with each participant's preferences being taken into account. You'll build this project from scratch, using any framework you prefer, like React or vanilla JavaScript, and integrate a vector database, such as Supabase. The provided data includes movie details like title, plot, cast, and IMDb ratings. This project emphasizes working with embeddings, querying databases, and generating personalized outputs using AI.
What you will learn
- Build a personalized movie recommendation app using AI embeddings and vector databases.
- Integrate APIs such as OpenAI for text generation and external movie poster services to enhance the user experience.
- Craft a responsive user interface based on provided Figma files for individual and group movie night recommendations.