Affective Music Finder

Goal

The objective of Affective Music Finder (AMF) is to provide users with the best selection of music related to their mood. Our plan was using Spotify API to categorized the playlists and then use telegram bot to send the music to the user. However, according to the limited time, we chose to use localhost and telegram servers to store music from the users and categorized them in the server.

What it does

The bot gets any text or emoji related to the mood of the users such as sad or :(. It then connects to the server and sends back a music which is in the sad category. Songs are chosen randomly from the queues of related songs and the user will not get the same music each time. So they can easily listen to new music each time depends on their mood.

How I built it

We used Python language and telegram bot API to build a bot which interacts with each client. Users simply express their mood with a sentence or emojis ( For example, I feel sad or send me a happy song). We then iterate through our lists of songs based on their category and pick a song randomly from the queue. The song along with a message will be then sent back to the client.