Music Mood Tagger Automates Playlist Mood Classification

This n8n workflow automates the process of analyzing and tagging music playlists based on their mood or theme. It begins with a webhook trigger that receives playlist data, then processes the input text by splitting it into manageable segments. Using OpenAI embeddings, the workflow stores and retrieves textual representations from a Redis vector database to determine the mood of each playlist. It employs LangChain’s language models to generate descriptive tags and classifications, which are then logged into a Google Sheet for record-keeping. This automation is ideal for music curators, playlist generators, and streaming services seeking to enhance playlist organization and user experience through smart, AI-driven mood tagging.