async def test_low_score_variation(self):
qna = QnAMaker(QnaApplicationTest.tests_endpoint)
options = QnAMakerOptions(top=5, context=None)
turn_context = QnaApplicationTest._get_context("Q11", TestAdapter())
response_json = QnaApplicationTest._get_json_for_file(
"QnaMaker_TopNAnswer.json")
# active learning enabled
with patch(
"aiohttp.ClientSession.post",
return_value=aiounittest.futurized(response_json),
):
results = await qna.get_answers(turn_context, options)
self.assertIsNotNone(results)
self.assertEqual(4, len(results), "should get four results")
filtered_results = qna.get_low_score_variation(results)
self.assertIsNotNone(filtered_results)
self.assertEqual(3, len(filtered_results),
"should get three results")
# active learning disabled
turn_context = QnaApplicationTest._get_context("Q11", TestAdapter())
response_json = QnaApplicationTest._get_json_for_file(
"QnaMaker_TopNAnswer_DisableActiveLearning.json")
with patch(
"aiohttp.ClientSession.post",
return_value=aiounittest.futurized(response_json),
):
results = await qna.get_answers(turn_context, options)
self.assertIsNotNone(results)
self.assertEqual(4, len(results), "should get four results")
filtered_results = qna.get_low_score_variation(results)
self.assertIsNotNone(filtered_results)
self.assertEqual(3, len(filtered_results),
"should get three results")
async def test_should_filter_low_score_variation(self):
options = QnAMakerOptions(top=5)
qna = QnAMaker(QnaApplicationTest.tests_endpoint, options)
question: str = "Q11"
context = QnaApplicationTest._get_context(question, TestAdapter())
response_json = QnaApplicationTest._get_json_for_file("TopNAnswer.json")
with patch(
"aiohttp.ClientSession.post",
return_value=aiounittest.futurized(response_json),
):
results = await qna.get_answers(context)
self.assertEqual(4, len(results), "Should have received 4 answers.")
filtered_results = qna.get_low_score_variation(results)
self.assertEqual(
3,
len(filtered_results),
"Should have 3 filtered answers after low score variation.",
)
