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copied!<p>You probably want to look into <a href="http://en.wikipedia.org/wiki/Markov_chain" rel="noreferrer">Markov Chains</a> as the basics for the bot AI. I wrote something a long time ago (the code to which I'm not proud of at all, and needs some mods to run on Python > 1.5) that may be a useful starting place for you: <a href="http://sourceforge.net/projects/benzo/" rel="noreferrer"><a href="http://sourceforge.net/projects/benzo/" rel="noreferrer">http://sourceforge.net/projects/benzo/</a></a></p> <p>EDIT: Here's a minimal example in Python of a Markov Chain that accepts input from stdin and outputs text based on the probabilities of words succeeding one another in the input. It's optimized for IRC-style chat logs, but running any decent-sized text through it should demonstrate the concepts:</p> <pre><code>import random, sys NONWORD = "\n" STARTKEY = NONWORD, NONWORD MAXGEN=1000 class MarkovChainer(object): def __init__(self): self.state = dict() def input(self, input): word1, word2 = STARTKEY for word3 in input.split(): self.state.setdefault((word1, word2), list()).append(word3) word1, word2 = word2, word3 self.state.setdefault((word1, word2), list()).append(NONWORD) def output(self): output = list() word1, word2 = STARTKEY for i in range(MAXGEN): word3 = random.choice(self.state[(word1,word2)]) if word3 == NONWORD: break output.append(word3) word1, word2 = word2, word3 return " ".join(output) if __name__ == "__main__": c = MarkovChainer() c.input(sys.stdin.read()) print c.output() </code></pre> <p>It's pretty easy from here to plug in persistence and an IRC library and have the basis of the type of bot you're talking about.</p>

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