Brian S. Stephan
26bc8bec34
the module will drop your old tables if you have them, so if there's data there, be sure to back them up and figure out some migration strategy (probably annoying and probably having to script it). the big change is that each line is associated to a context now, and channels are also associated to contexts. this should allow for a better partitioning of multiple brains, and changing which channels point to which brain. also caught in the wake is some additional logging verbosity, and a change to no longer lower() everything learned. the script to dump a file into the database has also been updated with the above changes
540 lines
21 KiB
Python
540 lines
21 KiB
Python
"""
|
|
Markov - Chatterbot via Markov chains for IRC
|
|
Copyright (C) 2010 Brian S. Stephan
|
|
|
|
This program is free software: you can redistribute it and/or modify
|
|
it under the terms of the GNU General Public License as published by
|
|
the Free Software Foundation, either version 3 of the License, or
|
|
(at your option) any later version.
|
|
|
|
This program is distributed in the hope that it will be useful,
|
|
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
|
GNU General Public License for more details.
|
|
|
|
You should have received a copy of the GNU General Public License
|
|
along with this program. If not, see <http://www.gnu.org/licenses/>.
|
|
"""
|
|
|
|
import cPickle
|
|
from datetime import datetime
|
|
import os
|
|
import random
|
|
import re
|
|
import sqlite3
|
|
import sys
|
|
import thread
|
|
import time
|
|
|
|
from dateutil.parser import *
|
|
from dateutil.relativedelta import *
|
|
from extlib import irclib
|
|
|
|
from Module import Module
|
|
|
|
class Markov(Module):
|
|
|
|
"""
|
|
Create a chatterbot very similar to a MegaHAL, but simpler and
|
|
implemented in pure Python. Proof of concept code from Ape.
|
|
|
|
Ape wrote: based on this:
|
|
http://uswaretech.com/blog/2009/06/pseudo-random-text-markov-chains-python/
|
|
and this:
|
|
http://code.activestate.com/recipes/194364-the-markov-chain-algorithm/
|
|
"""
|
|
|
|
def __init__(self, irc, config, server):
|
|
"""Create the Markov chainer, and learn text from a file if available."""
|
|
|
|
# set up some keywords for use in the chains --- don't change these
|
|
# once you've created a brain
|
|
self.start1 = '__start1'
|
|
self.start2 = '__start2'
|
|
self.stop = '__stop'
|
|
|
|
# set up regexes, for replying to specific stuff
|
|
trainpattern = '^!markov\s+train\s+(.*)$'
|
|
learnpattern = '^!markov\s+learn\s+(.*)$'
|
|
replypattern = '^!markov\s+reply(\s+min=(\d+))?(\s+max=(\d+))?(\s+(.*)$|$)'
|
|
|
|
self.trainre = re.compile(trainpattern)
|
|
self.learnre = re.compile(learnpattern)
|
|
self.replyre = re.compile(replypattern)
|
|
|
|
self.shut_up = False
|
|
self.lines_seen = []
|
|
|
|
Module.__init__(self, irc, config, server)
|
|
|
|
self.next_shut_up_check = 0
|
|
self.next_chatter_check = 0
|
|
self.connection = None
|
|
thread.start_new_thread(self.thread_do, ())
|
|
|
|
def db_init(self):
|
|
"""Create the markov chain table."""
|
|
|
|
version = self.db_module_registered(self.__class__.__name__)
|
|
if (version == None or version < 9):
|
|
db = self.get_db()
|
|
try:
|
|
version = 9
|
|
|
|
# recreating the tables, since i need to add some foreign key constraints
|
|
db.execute('''DROP INDEX IF EXISTS markov_chain_keys_and_context_index''')
|
|
db.execute('''DROP INDEX IF EXISTS markov_chain_keys_index''')
|
|
db.execute('''DROP INDEX IF EXISTS markov_chain_value_and_context_index''')
|
|
db.execute('''DROP TABLE IF EXISTS markov_chain''')
|
|
db.execute('''DROP TABLE IF EXISTS markov_target_to_context_map''')
|
|
db.execute('''DROP TABLE IF EXISTS markov_chatter_target''')
|
|
db.execute('''DROP TABLE IF EXISTS markov_context''')
|
|
|
|
db.execute('''
|
|
CREATE TABLE markov_chatter_target (
|
|
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
|
target TEXT NOT NULL,
|
|
chance INTEGER NOT NULL DEFAULT 99999
|
|
)''')
|
|
|
|
db.execute('''
|
|
CREATE TABLE markov_context (
|
|
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
|
context TEXT NOT NULL
|
|
)''')
|
|
|
|
db.execute('''
|
|
CREATE TABLE markov_target_to_context_map (
|
|
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
|
target TEXT NOT NULL,
|
|
context_id INTEGER NOT NULL,
|
|
FOREIGN KEY(context_id) REFERENCES markov_context(id)
|
|
)''')
|
|
|
|
db.execute('''
|
|
CREATE TABLE markov_chain (
|
|
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
|
k1 TEXT NOT NULL,
|
|
k2 TEXT NOT NULL,
|
|
v TEXT NOT NULL,
|
|
context_id INTEGER DEFAULT NULL,
|
|
FOREIGN KEY(context_id) REFERENCES markov_context(id)
|
|
)''')
|
|
|
|
db.execute('''
|
|
CREATE INDEX markov_chain_keys_and_context_id_index
|
|
ON markov_chain (k1, k2, context_id)''')
|
|
|
|
db.execute('''
|
|
CREATE INDEX markov_chain_value_and_context_id_index
|
|
ON markov_chain (v, context_id)''')
|
|
|
|
db.commit()
|
|
db.close()
|
|
self.db_register_module_version(self.__class__.__name__, version)
|
|
|
|
self._learn_line('','')
|
|
except sqlite3.Error as e:
|
|
db.rollback()
|
|
db.close()
|
|
print('sqlite error: ' + str(e))
|
|
raise
|
|
|
|
def register_handlers(self):
|
|
"""Handle pubmsg/privmsg, to learn and/or reply to IRC events."""
|
|
|
|
self.server.add_global_handler('pubmsg', self.on_pub_or_privmsg, self.priority())
|
|
self.server.add_global_handler('privmsg', self.on_pub_or_privmsg, self.priority())
|
|
self.server.add_global_handler('pubmsg', self.learn_from_irc_event)
|
|
self.server.add_global_handler('privmsg', self.learn_from_irc_event)
|
|
|
|
def unregister_handlers(self):
|
|
self.server.remove_global_handler('pubmsg', self.on_pub_or_privmsg)
|
|
self.server.remove_global_handler('privmsg', self.on_pub_or_privmsg)
|
|
self.server.remove_global_handler('pubmsg', self.learn_from_irc_event)
|
|
self.server.remove_global_handler('privmsg', self.learn_from_irc_event)
|
|
|
|
def learn_from_irc_event(self, connection, event):
|
|
"""Learn from IRC events."""
|
|
|
|
what = ''.join(event.arguments()[0])
|
|
my_nick = connection.get_nickname()
|
|
what = re.sub('^' + my_nick + '[:,]\s+', '', what)
|
|
target = event.target()
|
|
nick = irclib.nm_to_n(event.source())
|
|
|
|
self.lines_seen.append((nick, datetime.now()))
|
|
self.connection = connection
|
|
|
|
# don't learn from commands
|
|
if self.trainre.search(what) or self.learnre.search(what) or self.replyre.search(what):
|
|
return
|
|
|
|
self._learn_line(what, target)
|
|
|
|
def do(self, connection, event, nick, userhost, what, admin_unlocked):
|
|
"""Handle commands and inputs."""
|
|
|
|
target = event.target()
|
|
|
|
if self.trainre.search(what):
|
|
return self.reply(connection, event, self.markov_train(connection, event, nick,
|
|
userhost, what, admin_unlocked))
|
|
elif self.learnre.search(what):
|
|
return self.reply(connection, event, self.markov_learn(connection, event, nick,
|
|
userhost, what, admin_unlocked))
|
|
elif self.replyre.search(what) and not self.shut_up:
|
|
return self.reply(connection, event, self.markov_reply(connection, event, nick,
|
|
userhost, what, admin_unlocked))
|
|
|
|
if not self.shut_up:
|
|
# not a command, so see if i'm being mentioned
|
|
if re.search(connection.get_nickname(), what, re.IGNORECASE) is not None:
|
|
addressed_pattern = '^' + connection.get_nickname() + '[:,]\s+(.*)'
|
|
addressed_re = re.compile(addressed_pattern)
|
|
if addressed_re.match(what):
|
|
# i was addressed directly, so respond, addressing the speaker
|
|
self.lines_seen.append(('.self.said.', datetime.now()))
|
|
return self.reply(connection, event, '{0:s}: {1:s}'.format(nick,
|
|
self._generate_line(target, line=addressed_re.match(what).group(1))))
|
|
else:
|
|
# i wasn't addressed directly, so just respond
|
|
self.lines_seen.append(('.self.said.', datetime.now()))
|
|
return self.reply(connection, event, '{0:s}'.format(self._generate_line(target, line=what)))
|
|
|
|
def markov_train(self, connection, event, nick, userhost, what, admin_unlocked):
|
|
"""Learn lines from a file. Good for initializing a brain."""
|
|
|
|
match = self.trainre.search(what)
|
|
if match and admin_unlocked:
|
|
filename = match.group(1)
|
|
|
|
try:
|
|
for line in open(filename, 'r'):
|
|
self._learn_line(line)
|
|
|
|
return 'Learned from \'{0:s}\'.'.format(filename)
|
|
except IOError:
|
|
return 'No such file \'{0:s}\'.'.format(filename)
|
|
|
|
def markov_learn(self, connection, event, nick, userhost, what, admin_unlocked):
|
|
"""Learn one line, as provided to the command."""
|
|
|
|
target = event.target()
|
|
match = self.learnre.search(what)
|
|
if match:
|
|
line = match.group(1)
|
|
self._learn_line(line, target)
|
|
|
|
# return what was learned, for weird chaining purposes
|
|
return line
|
|
|
|
def markov_reply(self, connection, event, nick, userhost, what, admin_unlocked):
|
|
"""Generate a reply to one line, without learning it."""
|
|
|
|
target = event.target()
|
|
match = self.replyre.search(what)
|
|
if match:
|
|
min_size = 15
|
|
max_size = 100
|
|
|
|
if match.group(2):
|
|
min_size = int(match.group(2))
|
|
if match.group(4):
|
|
max_size = int(match.group(4))
|
|
|
|
if match.group(5) != '':
|
|
line = match.group(6)
|
|
self.lines_seen.append(('.self.said.', datetime.now()))
|
|
return self._generate_line(target, line=line, min_size=min_size, max_size=max_size)
|
|
else:
|
|
self.lines_seen.append(('.self.said.', datetime.now()))
|
|
return self._generate_line(target, min_size=min_size, max_size=max_size)
|
|
|
|
def thread_do(self):
|
|
"""Do various things."""
|
|
|
|
while not self.is_shutdown:
|
|
self._do_shut_up_checks()
|
|
self._do_random_chatter_check()
|
|
time.sleep(1)
|
|
|
|
def _do_random_chatter_check(self):
|
|
"""Randomly say something to a channel."""
|
|
|
|
# don't immediately potentially chatter, let the bot
|
|
# join channels first
|
|
if self.next_chatter_check == 0:
|
|
self.next_chatter_check = time.time() + 600
|
|
|
|
if self.next_chatter_check < time.time():
|
|
self.next_chatter_check = time.time() + 600
|
|
|
|
if self.connection is None:
|
|
# i haven't seen any text yet...
|
|
return
|
|
|
|
targets = self._get_chatter_targets()
|
|
for t in targets:
|
|
if t['chance'] > 0:
|
|
a = random.randint(1, t['chance'])
|
|
if a == 1:
|
|
self.sendmsg(self.connection, t['target'], self._generate_line(t['target']))
|
|
|
|
def _do_shut_up_checks(self):
|
|
"""Check to see if we've been talking too much, and shut up if so."""
|
|
|
|
if self.next_shut_up_check < time.time():
|
|
self.shut_up = False
|
|
self.next_shut_up_check = time.time() + 30
|
|
|
|
last_30_sec_lines = []
|
|
|
|
for (nick,then) in self.lines_seen:
|
|
rdelta = relativedelta(datetime.now(), then)
|
|
if (rdelta.years == 0 and rdelta.months == 0 and rdelta.days == 0 and
|
|
rdelta.hours == 0 and rdelta.minutes == 0 and rdelta.seconds <= 29):
|
|
last_30_sec_lines.append((nick,then))
|
|
|
|
if len(last_30_sec_lines) >= 8:
|
|
lines_i_said = len(filter(lambda (a,b): a == '.self.said.', last_30_sec_lines))
|
|
if lines_i_said >= 8:
|
|
self.shut_up = True
|
|
targets = self._get_chatter_targets()
|
|
for t in targets:
|
|
self.sendmsg(self.connection, t['target'],
|
|
'shutting up for 30 seconds due to last 30 seconds of activity')
|
|
|
|
def _learn_line(self, line, target):
|
|
"""Create Markov chains from the provided line."""
|
|
|
|
# set up the head of the chain
|
|
k1 = self.start1
|
|
k2 = self.start2
|
|
|
|
context_id = self._get_context_id_for_target(target)
|
|
|
|
# if there's no target, this is probably a sub-command. don't learn it
|
|
if target:
|
|
|
|
words = line.split()
|
|
if len(words) <= 0:
|
|
return line
|
|
|
|
try:
|
|
db = self.get_db()
|
|
cur = db.cursor()
|
|
statement = 'INSERT INTO markov_chain (k1, k2, v, context_id) VALUES (?, ?, ?, ?)'
|
|
for word in words:
|
|
cur.execute(statement, (k1.decode('utf-8', 'replace'),
|
|
k2.decode('utf-8', 'replace'), word.decode('utf-8', 'replace'), context_id))
|
|
k1, k2 = k2, word
|
|
cur.execute(statement, (k1.decode('utf-8', 'replace'),
|
|
k2.decode('utf-8', 'replace'), self.stop, context_id))
|
|
|
|
db.commit()
|
|
db.close()
|
|
except sqlite3.Error as e:
|
|
db.rollback()
|
|
db.close()
|
|
print("sqlite error in Markov._learn_line: " + str(e))
|
|
raise
|
|
|
|
def _generate_line(self, target, line='', min_size=15, max_size=100):
|
|
"""Reply to a line, using some text in the line as a point in the chain."""
|
|
|
|
# if the limit is too low, there's nothing to do
|
|
if (max_size <= 3):
|
|
raise Exception("max_size is too small: %d" % max_size)
|
|
|
|
# if the min is too large, abort
|
|
if (min_size > 20):
|
|
raise Exception("min_size is too large: %d" % min_size)
|
|
|
|
words = []
|
|
target_word = ''
|
|
# get a random word from the input
|
|
if line != '':
|
|
words = line.split()
|
|
target_word = words[random.randint(0, len(words)-1)]
|
|
|
|
context_id = self._get_context_id_for_target(target)
|
|
|
|
# start with an empty chain, and work from there
|
|
gen_words = [self.start1, self.start2]
|
|
|
|
# walk a chain, randomly, building the list of words
|
|
while len(gen_words) < max_size + 2 and gen_words[-1] != self.stop:
|
|
# first, see if we have an empty response and a target word.
|
|
# we'll just pick a word and work backwards
|
|
if gen_words[-1] == self.start2 and target_word != '':
|
|
working_backwards = []
|
|
key_hits = self._retrieve_k2_for_value(target_word, context_id)
|
|
if len(key_hits):
|
|
working_backwards.append(target_word)
|
|
# generate new word
|
|
found_word = ''
|
|
target_word = words[random.randint(0, len(words)-1)]
|
|
# work backwards until we randomly bump into a start
|
|
while True:
|
|
key_hits = self._retrieve_k2_for_value(working_backwards[0], context_id)
|
|
if target_word in key_hits:
|
|
found_word = target_word
|
|
# generate new word
|
|
if len(filter(lambda a: a != target_word, words)) > 1 and False:
|
|
# if we have more than one target word, get a new one (otherwise give up)
|
|
target_word = random.choice(filter(lambda a: a != target_word, words))
|
|
else:
|
|
target_word = ''
|
|
else:
|
|
found_word = random.choice(filter(lambda a: a != self.stop, key_hits))
|
|
|
|
if found_word == self.start2 or len(working_backwards) >= max_size + 2:
|
|
gen_words = gen_words + working_backwards
|
|
break
|
|
else:
|
|
working_backwards.insert(0, found_word)
|
|
|
|
key_hits = self._retrieve_chains_for_key(gen_words[-2], gen_words[-1], context_id)
|
|
# use the chain that includes the target word, if it is found
|
|
if target_word != '' and target_word in key_hits:
|
|
gen_words.append(target_word)
|
|
# generate new word
|
|
target_word = words[random.randint(0, len(words)-1)]
|
|
else:
|
|
if len(gen_words) < min_size and len(filter(lambda a: a != self.stop, key_hits)) > 0:
|
|
gen_words.append(random.choice(filter(lambda a: a != self.stop, key_hits)))
|
|
elif len(key_hits) <= 0:
|
|
gen_words.append(self.stop)
|
|
else:
|
|
gen_words.append(random.choice(key_hits))
|
|
|
|
# chop off the seed data at the start
|
|
gen_words = gen_words[2:]
|
|
|
|
# chop off the end text, if it was the keyword indicating an end of chain
|
|
if gen_words[-1] == self.stop:
|
|
gen_words = gen_words[:-1]
|
|
|
|
return ' '.join(gen_words).encode('utf-8', 'ignore')
|
|
|
|
def _retrieve_chains_for_key(self, k1, k2, context_id):
|
|
"""Get the value(s) for a given key (a pair of strings)."""
|
|
|
|
values = []
|
|
try:
|
|
db = self.get_db()
|
|
query = ''
|
|
if k1 == self.start1 and k2 == self.start2:
|
|
# hack. get a quasi-random start from the database, in
|
|
# a faster fashion than selecting all starts
|
|
max_id = self._get_max_chain_id()
|
|
rand_id = random.randint(1,max_id)
|
|
query = ('SELECT v FROM markov_chain WHERE k1 = ? AND k2 = ? AND '
|
|
'(context_id = ? OR context_id IS NULL) AND id >= {0:d} LIMIT 1'.format(rand_id))
|
|
else:
|
|
query = ('SELECT v FROM markov_chain WHERE k1 = ? AND k2 = ? AND '
|
|
'(context_id = ? OR context_id IS NULL)')
|
|
cursor = db.execute(query, (k1,k2,context_id))
|
|
results = cursor.fetchall()
|
|
|
|
for result in results:
|
|
values.append(result['v'])
|
|
|
|
db.close()
|
|
return values
|
|
except sqlite3.Error as e:
|
|
db.close()
|
|
print('sqlite error in Markov._retrieve_chains_for_key: ' + str(e))
|
|
raise
|
|
|
|
def _retrieve_k2_for_value(self, v, context_id):
|
|
"""Get the value(s) for a given key (a pair of strings)."""
|
|
|
|
values = []
|
|
try:
|
|
db = self.get_db()
|
|
query = 'SELECT k2 FROM markov_chain WHERE v = ? AND (context_id = ? OR context_id IS NULL)'
|
|
cursor = db.execute(query, (v,context_id))
|
|
results = cursor.fetchall()
|
|
|
|
for result in results:
|
|
values.append(result['k2'])
|
|
|
|
db.close()
|
|
return values
|
|
except sqlite3.Error as e:
|
|
db.close()
|
|
print('sqlite error in Markov._retrieve_k2_for_value: ' + str(e))
|
|
raise
|
|
|
|
def _get_chatter_targets(self):
|
|
"""Get all possible chatter targets."""
|
|
|
|
values = []
|
|
try:
|
|
# need to create our own db object, since this is likely going to be in a new thread
|
|
db = self.get_db()
|
|
query = 'SELECT target, chance FROM markov_chatter_target'
|
|
cursor = db.execute(query)
|
|
results = cursor.fetchall()
|
|
return results
|
|
except sqlite3.Error as e:
|
|
db.close()
|
|
print('sqlite error in Markov._get_chatter_targets: ' + str(e))
|
|
raise
|
|
|
|
def _get_one_chatter_target(self):
|
|
"""Select one random chatter target."""
|
|
|
|
targets = self._get_chatter_targets()
|
|
if targets:
|
|
return targets[random.randint(0, len(targets)-1)]
|
|
|
|
def _get_max_chain_id(self):
|
|
"""Get the highest id in the chain table."""
|
|
|
|
try:
|
|
db = self.get_db()
|
|
query = '''
|
|
SELECT id FROM markov_chain ORDER BY id DESC LIMIT 1
|
|
'''
|
|
cursor = db.execute(query)
|
|
result = cursor.fetchone()
|
|
db.close()
|
|
if result:
|
|
return result['id']
|
|
else:
|
|
return None
|
|
except sqlite3.Error as e:
|
|
db.close()
|
|
print('sqlite error in Markov._get_max_chain_id: ' + str(e))
|
|
raise
|
|
|
|
def _get_context_id_for_target(self, target):
|
|
|
|
"""Get the context ID for the desired/input target."""
|
|
|
|
try:
|
|
db = self.get_db()
|
|
query = '''
|
|
SELECT mc.id FROM markov_context mc
|
|
INNER JOIN markov_target_to_context_map mt
|
|
ON mt.context_id = mc.id
|
|
WHERE mt.target = ?
|
|
'''
|
|
cursor = db.execute(query, (target,))
|
|
result = cursor.fetchone()
|
|
db.close()
|
|
if result:
|
|
return result['id']
|
|
else:
|
|
return None
|
|
except sqlite3.Error as e:
|
|
db.close()
|
|
print('sqlite error in Markov._get_context_id_for_target: ' + str(e))
|
|
raise
|
|
|
|
# vi:tabstop=4:expandtab:autoindent
|
|
# kate: indent-mode python;indent-width 4;replace-tabs on;
|