def test_words_from_current_pos(self):
sentence = Sentence(self._bot.brain.tokenizer, "One Two Three")
self.assertIsNotNone(sentence)
self.assertEqual("One Two Three", sentence.words_from_current_pos(0))
self.assertEqual("Two Three", sentence.words_from_current_pos(1))
self.assertEqual("Three", sentence.words_from_current_pos(2))
with self.assertRaises(Exception):
self.assertEqual("Three", sentence.words_from_current_pos(3))
self.assertEqual("One Two Three", sentence.text())
def match_sentence(self, client_context, pattern_sentence, topic_pattern, that_pattern):
topic_sentence = Sentence(client_context, topic_pattern)
that_sentence = Sentence(client_context, that_pattern)
YLogger.debug(client_context, "AIML Parser matching sentence [%s], topic=[%s], that=[%s] ",
pattern_sentence.text(client_context), topic_pattern, that_pattern)
sentence = Sentence(client_context)
sentence.append_sentence(pattern_sentence)
sentence.append_word('__TOPIC__')
sentence.append_sentence(topic_sentence)
sentence.append_word('__THAT__')
sentence.append_sentence(that_sentence)
YLogger.debug(client_context, "Matching [%s]", sentence.words_from_current_pos(client_context, 0))
context = MatchContext(max_search_depth=client_context.bot.configuration.max_search_depth,
max_search_timeout=client_context.bot.configuration.max_search_timeout)
template = self._pattern_parser.root.match(client_context, context, sentence)
if template is not None:
context.template_node = template
context.list_matches(client_context)
# Save the matched context for the associated sentence
pattern_sentence.matched_context = context
return context
return None
def test_words_from_current_pos(self):
sentence = Sentence(self._client_context, "One Two Three")
self.assertIsNotNone(sentence)
self.assertEqual(
"One Two Three",
sentence.words_from_current_pos(self._client_context, 0))
self.assertEqual(
"Two Three",
sentence.words_from_current_pos(self._client_context, 1))
self.assertEqual(
"Three", sentence.words_from_current_pos(self._client_context, 2))
with self.assertRaises(Exception):
self.assertEqual(
"Three",
sentence.words_from_current_pos(self._client_context, 3))
self.assertEqual("One Two Three", sentence.text(self._client_context))
def test_split_into_words(self):
sentence = Sentence(self._bot.brain.tokenizer, "HELLO")
self.assertIsNotNone(sentence)
self.assertEqual(1, sentence.num_words())
self.assertEqual("HELLO", sentence.word(0))
self.assertEqual("HELLO", sentence.words_from_current_pos(0))
self.assertIsNone(sentence.word(1))
self.assertEqual("HELLO", sentence.text())
def test_split_into_words(self):
sentence = Sentence(self._client_context, "HELLO")
self.assertIsNotNone(sentence)
self.assertEqual(1, sentence.num_words())
self.assertEqual("HELLO", sentence.word(0))
self.assertEqual(
"HELLO", sentence.words_from_current_pos(self._client_context, 0))
with self.assertRaises(Exception):
sentence.sentence.word(1)
self.assertEqual("HELLO", sentence.text(self._client_context))
def match_sentence(self, client_context, pattern_sentence, topic_pattern,
that_pattern):
topic_sentence = Sentence(client_context.brain.tokenizer,
topic_pattern)
if len(topic_sentence.words) == 0:
topic_sentence.words.append('*')
that_sentence = Sentence(client_context.brain.tokenizer, that_pattern)
if len(that_sentence.words) == 0:
that_sentence.words.append('*')
if client_context.match_nlu is True:
YLogger.debug(client_context,
"AIML Parser NLU matching topic=[%s], that=[%s] ",
topic_pattern, that_pattern)
else:
YLogger.debug(
client_context,
"AIML Parser matching sentence [%s], topic=[%s], that=[%s] ",
pattern_sentence.text(), topic_pattern, that_pattern)
sentence = Sentence(client_context.brain.tokenizer)
sentence.append_sentence(pattern_sentence)
sentence.append_word('__TOPIC__')
sentence.append_sentence(topic_sentence)
sentence.append_word('__THAT__')
sentence.append_sentence(that_sentence)
YLogger.debug(client_context, "Matching [%s]",
sentence.words_from_current_pos(0))
context = MatchContext(
max_search_depth=client_context.bot.configuration.max_search_depth,
max_search_timeout=client_context.bot.configuration.
max_search_timeout,
tokenizer=client_context.brain.tokenizer,
start_time=client_context.question_start_time)
template = self._pattern_parser._root_node.match(
client_context, context, sentence)
if template is not None:
context._template_node = template
context.list_matches(client_context)
# Save the matched context for the associated sentence
pattern_sentence.matched_context = context
return context
return None
