def test_exact_match_different_capitalization(self):
"""
Test that text capitalization is ignored.
"""
statement = Statement('Hi HoW ArE yOu?')
other_statement = Statement('hI hOw are YoU?')
value = comparisons.levenshtein_distance(statement, other_statement)
self.assertEqual(value, 1)
def test_levenshtein_distance_other_statement_false(self):
"""
Falsy values should match by zero.
"""
statement = Statement('Hello')
other_statement = Statement('')
value = comparisons.levenshtein_distance(statement, other_statement)
self.assertEqual(value, 0)
def test_exact_match_different_capitalization(self):
"""
Test that text capitalization is ignored.
"""
statement = Statement(text='Hi HoW ArE yOu?')
other_statement = Statement(text='hI hOw are YoU?')
value = comparisons.levenshtein_distance(statement, other_statement)
self.assertEqual(value, 1)
def test_levenshtein_distance_other_statement_false(self):
"""
Falsy values should match by zero.
"""
statement = Statement(text='Hello')
other_statement = Statement(text='')
value = comparisons.levenshtein_distance(statement, other_statement)
self.assertEqual(value, 0)
def test_levenshtein_distance_statement_integer(self):
"""
Test that an exception is not raised if a statement is initialized
with an integer value as its text attribute.
"""
statement = Statement(2)
other_statement = Statement('Hello')
value = comparisons.levenshtein_distance(statement, other_statement)
self.assertEqual(value, 0)
def test_levenshtein_distance_statement_integer(self):
"""
Test that an exception is not raised if a statement is initialized
with an integer value as its text attribute.
"""
statement = Statement(text=2)
other_statement = Statement(text='Hello')
value = comparisons.levenshtein_distance(statement, other_statement)
self.assertEqual(value, 0)
def similar_statement(input_statement): closest_match = input_statement closest_match.confidence = 0 statement_list = database.keys() # Find the closest matching known statement for statement in statement_list: confidence = (comparisons.levenshtein_distance(input_statement, statement) + comparisons.synset_distance(input_statement,statement)+comparisons.jaccard_similarity(input_statement,statement)+ comparisons.sentiment_comparison(input_statement,statement))*1.0/4 #comparisons.sentiment_comparison(input_statement,statement)+ if confidence > closest_match.confidence: statement.confidence = confidence closest_match = statement print closest_match.confidence return (closest_match.confidence,closest_match)
def get(self, input_statement):
statement_list = self.chatbot.storage.get_response_statements()
if not statement_list:
if self.chatbot.storage.count():
# Use a randomly picked statement
self.logger.info('No statements have known responses. ' +
'Choosing a random response to return.')
random_response = self.chatbot.storage.get_random()
random_response.confidence = 0
return random_response
else:
raise self.EmptyDatasetException()
closest_match = input_statement
closest_match.confidence = 0
closest_match.lev = 0
closest_match.cos = 0
# Find the closest chatbot known statement
questionVector = self.getVector(input_statement.tokens, True)
if not all(x == 0 for x in questionVector):
# If there is a vector for the statement compare it with all other
# statements in the database
for statement in statement_list:
vec = self.getStatementVec(statement)
lev_similarity = comparisons.levenshtein_distance(
Statement(input_statement.text), Statement(statement.text))
cosine_similarity = self.cosine_similarity(questionVector, vec)
# normalize
cosine_similarity = (cosine_similarity + 1) / 2
if all(x == 0 for x in vec):
# There is no vector for the statement so the comparison is meaningless
lev_similarity = 0
cosine_similarity = 0
# print(statement.text,cosine_similarity,lev_similarity)
if cosine_similarity > closest_match.cos:
closest_match = statement
closest_match.lev = lev_similarity
closest_match.cos = cosine_similarity
elif abs(cosine_similarity - closest_match.cos
) < 0.01 and lev_similarity > closest_match.lev:
closest_match = statement
closest_match.lev = lev_similarity
closest_match.cos = cosine_similarity
closest_match.confidence = closest_match.cos
print("Closest Match:", closest_match,\
"Lev:",closest_match.lev, \
"Cos:",closest_match.cos, "Confidence:",closest_match.confidence)
return closest_match
