Jeremy Singer-Vine

Would something like this satisfy your curiosity?: > For text corpora, Markovify begins the process of building its Markov models by splitting each corpus into a series of sentences, and...

Hi @wsricardo, and thanks for your interest in this library. Without access to the code or text corpus you're using, it's a bit hard to diagnose your issue definitively. But...

Hi @mooseyboots, and thanks for your interesting in this library. I'm having a bit of trouble, however, understanding the specifics of your inquiry. Could you provide some code, inputs, and...

Hi @mooseyboots, and thanks for the additional details. Judging from the sample of the corpus you shared, which seems to place each sentence on a new line, the easiest solution...

Hi @AlliedToasters, and thanks for sharing this. It seems like an interesting, well-scoped addition. Would you be open to adding test coverage for it? If not, no worries — I...

Thanks for flagging @JGCoelho. Judging by the error messages, this seems to be an issue with character encoding — possibly tied to Windows and/or Anaconda, but it's hard to tell....

Hi @yorkshirelandscape, and glad the library's been working well for you! Just thinking through how Markov chains work (aside from the particular implementation here), I'm not aware of a way...

There's no built-in method to do this in `markovify`. The easiest way for you to do it would probably be to have a `while` generate sentences until it generates one...

Hi @voltaxvoltax, and thanks for reminding me about this thread. Implementing a more efficient version of `make_sentence_that_contains` would require a nontrivial amount of experimentation and testing. That said, I’m open...

Hi @erikrakuscek, and thanks for this note. You raise a really interesting philosophical question. As you're thinking about it, what does "random" signify to you? (I ask because Markov chains...