Text prediction is usually called "language modeling" in NLP. Because it's useful as a weak supervision signal to improve performance on other tasks, most of the mentioned libraries support it. However, they might not always provide complete examples, instead assuming that you know how to express the model and train it using the primitives provided by the library.
It's gonna be hard to get an "off the shelf" model for text prediction, because the upcoming text depends on the author, topic, and other context. You can probably find some decent pre-trained models to get started, but you'll need to customize them for your application to get good results.
Right, I was thinking off-the-shelf in the sense of giving it a tokenised corpus and it does the rest, or it incorporates that into its existing model. Dictation software, phone keyboards, etc. do this.
Flair: https://github.com/zalandoresearch/flair/blob/master/flair/m...
Allen NLP: https://github.com/allenai/allennlp/blob/master/allennlp/dat...
PyText: https://github.com/facebookresearch/pytext/blob/master/pytex...
spaCy seems to focus on language analysis and I couldn't find an API that'd be directly usable for text generation.