This program generates a sentence's worth of "real-looking" text using a Markov model and sample textual training input. Given some sample text from which to build a model, the program prints out a sentence based on a Markov chain. Use it thus:
$ ./sentence-generator.py filename [chain length]
where filename is a file containing some training text for the sentence to imitate (one of Project Gutenberg's books fits the bill nicely) and chain length optionally represents the number of words taken into account when choosing the next word. Chain length defaults to 1 (which is fastest), but increasing this may generate more realistic text, albeit slightly more slowly. Depending on the text, increasing the chain length past 6 or 7 words probably won't do much good -- at that point you're usually plucking out whole sentences anyway, so using a Markov model is kind of redundant.
The texts of Portrait of the Artist as a Young Man and Leaves of Grass (in snippet.txt) are taken from Project Gutenberg. The usual copyright headers had to be removed so that they could serve as useful sample input, but naturally all the rights and restrictions of a Gutenberg book still apply.