This project presents a new approach to music recommendations on an app. Using the Spotify API, it retrieves playlists, album artists, and tracks from a playlist, it randomize the songs and stores the first 25 songs of the randomized playlist. This data is uploaded to the OpenAI API, which analyzes it alongside a music dataset. By evaluating factors such as popularity, duration, danceability, energy, loudness, speechiness, acousticness, instrumentalness, and liveness, the system suggests five songs the user may like. This method offers an innovative way to enhance music recommendation accuracy and user satisfaction.
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José Alfredo Arriaga Rosillo