Original implementation of "Automatic, Personalized, and Flexible Playlist Generation using Reinforcement Learning".

• python3

You can check and install other dependencies in requirements.txt

$ pip3 install -r requirements.txt
# to install TensorFlow, you can refer to https://www.tensorflow.org/install/

The following are files you should prepare to train this playlist generation model. Besides, you can check sample files we prepare as a reference of formats.

[date_of_created_playlist] [song_id1] [song_id2] ....

# embedding: [value1 value2 value3 ...]
[song_id] [value1] [value2] [value3] ...

[song_id] [popularity_score] [artist_id] [release_date]

[seed_song_id]

You can add argument --debug 1 for each mode to check everything is fine before you prepare your own data.

# files mentioned above should be created first
$ ./prepare_data.sh

$ python3 main.py --mode pretrain [--debug 1]

$ python3 main.py --mode rl [--debug 1]

# input file: results/in.txt
# output file: results/out.txt
$ python3 main.py --mode test [--debug 1]

If you would like some different settings for this model, you can refer to lib/config.py.