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song-recommendation-qdrant's Introduction

Song-Recommendation-Qdrant

Quickstart

  • Clone this repo into a directory of your choice.
  • Install Qdrant via Docker. (refer:https://qdrant.tech/documentation/quick-start/)
  • Note: The commands are shown in UNIX-shell, refer qdrant_commands_for_windows.txt for the windows alternatives.
  • The ipynb notebook is for demonstration purposes.
  • For the actual app, navigate to the directory in your terminal and run streamlit run song_rec_streamlit.py.

Project Description

  • This is an implementation of a recommendation engine using the Qdrant Recommendation API.
  • We source the data from https://www.kaggle.com/datasets/geomack/spotifyclassification. (Note: You can get your own data using the spotify API).
  • The data is vectorized and stored in a Qdrant collection.
  • The Recommendation API takes positive and negative feedback from the user as well as artist filters and uses vector similarity to assign a score to each of the songs in our data.
  • The top 5 songs are displayed back to the user.

song-recommendation-qdrant's People

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