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from fastai.learner import Learner | |
import pandas as pd | |
def get_recommendations_for_user(learn: Learner, user_id: str, limit: int = 5): | |
# TODO: Fetch list of not listened songs as entries | |
not_listened_songs = ["Revelry, Kings of Leon, 2008", "Gears, Miss May I, 2010", "Sexy Bitch, David Guetta, 2009"] | |
input_dataframe = pd.DataFrame({'user_id': ["440abe26940ae9d9268157222a4a3d5735d44ed8"] * len(not_listened_songs), 'entry': not_listened_songs}) | |
test_dl = learn.dls.test_dl(input_dataframe) | |
predictions = learn.get_preds(dl=test_dl) | |
# TODO: Return recommendations in track format | |
return { | |
"user_id": user_id, | |
"limit": limit, | |
"recommendations": predictions[0].numpy().tolist() | |
} |