class TextSearchComparisonFunctionSpacySimilarityTests(ChatBotTestCase):
"""
Test that the search algorithm works correctly with the
spacy similarity comparison function.
"""
def setUp(self):
super().setUp()
self.search_algorithm = TextSearch(
self.chatbot,
statement_comparison_function=comparisons.SpacySimilarity
)
def test_get_closest_statement(self):
"""
Note, the content of the in_response_to field for each of the
test statements is only required because the logic adapter will
filter out any statements that are not in response to a known statement.
"""
self.chatbot.storage.create_many([
Statement(text='This is a lovely bog.', in_response_to='This is a lovely bog.'),
Statement(text='This is a beautiful swamp.', in_response_to='This is a beautiful swamp.'),
Statement(text='It smells like a swamp.', in_response_to='It smells like a swamp.')
])
statement = Statement(text='This is a lovely swamp.')
results = list(self.search_algorithm.search(statement))
self.assertIsLength(results, 2)
self.assertEqual(results[-1].text, 'This is a beautiful swamp.')
self.assertGreater(results[-1].confidence, 0)
def test_different_punctuation(self):
self.chatbot.storage.create_many([
Statement(text='Who are you?'),
Statement(text='Are you good?'),
Statement(text='You are good')
])
statement = Statement(text='Are you good')
results = list(self.search_algorithm.search(statement))
self.assertEqual(len(results), 2)
# Note: the last statement in the list always has the highest confidence
self.assertEqual(results[-1].text, 'Are you good?')
class TextSearchComparisonFunctionLevenshteinDistanceComparisonTests(ChatBotTestCase):
"""
Test that the search algorithm works correctly with the
Levenshtein distance comparison function.
"""
def setUp(self):
super().setUp()
self.search_algorithm = TextSearch(
self.chatbot,
statement_comparison_function=comparisons.LevenshteinDistance
)
def test_get_closest_statement(self):
"""
Note, the content of the in_response_to field for each of the
test statements is only required because the search process will
filter out any statements that are not in response to something.
"""
self.chatbot.storage.create_many([
Statement(text='What is the meaning of life?', in_response_to='...'),
Statement(text='I am Iron Man.', in_response_to='...'),
Statement(text='What... is your quest?', in_response_to='...'),
Statement(text='Yuck, black licorice jelly beans.', in_response_to='...'),
Statement(text='I hear you are going on a quest?', in_response_to='...'),
])
statement = Statement(text='What is your quest?')
results = list(self.search_algorithm.search(statement))
self.assertEqual(len(results), 2)
self.assertEqual(results[-1].text, 'What... is your quest?', msg=results[-1].confidence)
def test_confidence_exact_match(self):
self.chatbot.storage.create(text='What is your quest?', in_response_to='What is your quest?')
statement = Statement(text='What is your quest?')
results = list(self.search_algorithm.search(statement))
self.assertIsLength(results, 1)
self.assertEqual(results[0].confidence, 1)
def test_confidence_half_match(self):
from unittest.mock import MagicMock
# Assume that the storage adapter returns a partial match
self.chatbot.storage.filter = MagicMock(return_value=[
Statement(text='xxyy')
])
statement = Statement(text='wwxx')
results = list(self.search_algorithm.search(statement))
self.assertIsLength(results, 1)
self.assertEqual(results[0].confidence, 0.5)
def test_confidence_no_match(self):
from unittest.mock import MagicMock
# Assume that the storage adapter returns a partial match
self.search_algorithm.chatbot.storage.filter = MagicMock(return_value=[
Statement(text='xxx', in_response_to='xxx')
])
statement = Statement(text='yyy')
results = list(self.search_algorithm.search(statement))
self.assertIsLength(results, 0)
