3 Ways to Build a Recommendation Engine for Songs with LangChain

The text discusses the creation of a web app called FairytaleDJ that recommends Disney songs based on user input. It utilizes LangChain, OpenAI ChatGPT, Deep Lake, and Streamlit to build the recommendation system. The process involves scraping song lyrics from disneyclips.com, using Spotify Python APIs to get embedding URLs for each song, encoding data with LLMs, and matching user input with songs based on emotions. Three approaches were tried: similarity search of direct embeddings, using ChatGPT as a retrieval system, and similarity search of emotions embeddings. The last approach worked best by converting each lyric to a list of 8 emotions using ChatGPT and performing the similarity search on the vector database. A web app was created using Streamlit and hosted on an Hugging Face space for users to try.