Markov: consolidate _reply_to_line and _reply into _generate_line
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@ -182,10 +182,10 @@ class Markov(Module):
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addressed_re = re.compile(addressed_pattern)
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if addressed_re.match(what):
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# i was addressed directly, so respond, addressing the speaker
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return self.reply(connection, event, '{0:s}: {1:s}'.format(nick, self._reply_to_line(addressed_re.match(what).group(1))))
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return self.reply(connection, event, '{0:s}: {1:s}'.format(nick, self._generate_line(line=addressed_re.match(what).group(1))))
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else:
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# i wasn't addressed directly, so just respond
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return self.reply(connection, event, '{0:s}'.format(self._reply_to_line(what)))
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return self.reply(connection, event, '{0:s}'.format(self._generate_line(line=what)))
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def markov_train(self, connection, event, nick, userhost, what, admin_unlocked):
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"""Learn lines from a file. Good for initializing a brain."""
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@ -229,9 +229,9 @@ class Markov(Module):
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if match.group(5) != '':
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line = match.group(6)
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return self._reply_to_line(line, min_size=min_size, max_size=max_size)
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return self._generate_line(line=line, min_size=min_size, max_size=max_size)
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else:
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return self._reply(min_size=min_size, max_size=max_size)
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return self._generate_line(min_size=min_size, max_size=max_size)
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def _learn_line(self, line, target=None):
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"""Create Markov chains from the provided line."""
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@ -273,54 +273,7 @@ class Markov(Module):
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print("sqlite error: " + str(e))
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raise
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def _reply(self, min_size=15, max_size=100):
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"""Generate a totally random string from the chains, of specified limit of words."""
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# if the limit is too low, there's nothing to do
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if (max_size <= 3):
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raise Exception("max_size is too small: %d" % max_size)
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# if the min is too large, abort
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if (min_size > 20):
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raise Exception("min_size is too large: %d" % min_size)
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# start with an empty chain, and work from there
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gen_words = [self.start1, self.start2]
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# set up the number of times we've tried to hit the specified minimum
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min_search_tries = 0
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# walk a chain, randomly, building the list of words
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while len(gen_words) < max_size + 2 and gen_words[-1] != self.stop:
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key_hits = self._retrieve_chains_for_key(gen_words[-2], gen_words[-1])
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if len(gen_words) < min_size and len(filter(lambda a: a != self.stop, key_hits)) > 0:
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# we aren't at min size yet and we have at least one chain path
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# that isn't (yet) the end. take one of those.
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gen_words.append(random.choice(filter(lambda a: a != self.stop, key_hits)))
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min_search_tries = 0
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elif len(gen_words) < min_size and min_search_tries <= 10:
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# we aren't at min size yet and the only path we currently have is
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# a end, but we haven't retried much yet, so chop off our current
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# chain and try again.
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gen_words = gen_words[0:len(gen_words)-2]
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min_search_tries = min_search_tries + 1
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else:
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# either we have hit our min size requirement, or we haven't but
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# we also exhausted min_search_tries. either way, just pick a word
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# at random, knowing it may be the end of the chain
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gen_words.append(random.choice(key_hits))
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min_search_tries = 0
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# chop off the seed data at the start
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gen_words = gen_words[2:]
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# chop off the end text, if it was the keyword indicating an end of chain
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if gen_words[-1] == self.stop:
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gen_words = gen_words[:-1]
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return ' '.join(gen_words).encode('utf-8', 'ignore')
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def _reply_to_line(self, line, min_size=15, max_size=100):
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def _generate_line(self, line='', min_size=15, max_size=100):
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"""Reply to a line, using some text in the line as a point in the chain."""
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# if the limit is too low, there's nothing to do
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@ -331,9 +284,13 @@ class Markov(Module):
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if (min_size > 20):
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raise Exception("min_size is too large: %d" % min_size)
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words = []
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target_word = ''
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# get a random word from the input
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words = line.split()
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target_word = words[random.randint(0, len(words)-1)]
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if line != '':
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words = line.split()
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target_word = words[random.randint(0, len(words)-1)]
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print('target word ' + target_word)
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# start with an empty chain, and work from there
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gen_words = [self.start1, self.start2]
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@ -341,8 +298,9 @@ class Markov(Module):
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# walk a chain, randomly, building the list of words
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while len(gen_words) < max_size + 2 and gen_words[-1] != self.stop:
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key_hits = self._retrieve_chains_for_key(gen_words[-2], gen_words[-1])
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print(key_hits)
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# use the chain that includes the target word, if it is found
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if target_word in key_hits:
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if target_word != '' and target_word in key_hits:
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gen_words.append(target_word)
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# generate new word
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target_word = words[random.randint(0, len(words)-1)]
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