In part one of this tutorial series, I detailed the process of building an LLM-based movie recommender app using the TMDB (The Movie Database) API and OpenAI’s

In part one of this tutorial series, I detailed the process of building an LLM-based movie recommender app using the TMDB (The Movie Database) API and OpenAI’s GPT-3 model. The inspiration for this project came from a brainstorming interaction with ChatGPT, which led me to choose the TMDB API for its extensive film and TV show metadata. The user flow I envisioned for the app involves users inputting their movie preferences, which prompts OpenAI’s API to generate movie suggestions. I further process these suggestions into a list of movie names and send them to the TMDB API. The TMDB API then provides detailed information for each movie, including watch providers, which the Streamlit-built app finally displays to the user.