This only works if the sound and themes desired are vast enough for that. It's fine if a casual listener is a fan of something like anything house, pop, or electro. It's more difficult if your taste level is more obscure- a specific artist's style, or a specific juxtaposition produced from a one-off album. In that case there is quite literally not enough data to train on to produce further.

Even when there's not enough data to train on, it might still be possible to generate something in a desired rare style - provided this style is a mixture of several more common styles. Modern generative models are pretty good at interpolating.