async def test_remove_path_value(self):
test = {}
ObjectPath.set_path_value(test, "x.y.z", 15)
ObjectPath.set_path_value(test, "x.p", "hello")
ObjectPath.set_path_value(test, "foo", {"Bar": 15, "Blat": "yo"})
ObjectPath.set_path_value(test, "x.a[1]", "yabba")
ObjectPath.set_path_value(test, "x.a[0]", "dabba")
ObjectPath.remove_path_value(test, "x.y.z")
with self.assertRaises(KeyError):
ObjectPath.get_path_value(test, "x.y.z")
assert ObjectPath.get_path_value(test, "x.y.z", 99) == 99
ObjectPath.remove_path_value(test, "x.a[1]")
assert not ObjectPath.try_get_path_value(test, "x.a[1]")
assert ObjectPath.try_get_path_value(test, "x.a[0]") == "dabba"
async def test_set_value(self):
test = {}
ObjectPath.set_path_value(test, "x.y.z", 15)
ObjectPath.set_path_value(test, "x.p", "hello")
ObjectPath.set_path_value(test, "foo", {"Bar": 15, "Blat": "yo"})
ObjectPath.set_path_value(test, "x.a[1]", "yabba")
ObjectPath.set_path_value(test, "x.a[0]", "dabba")
ObjectPath.set_path_value(test, "null", None)
assert ObjectPath.get_path_value(test, "x.y.z") == 15
assert ObjectPath.get_path_value(test, "x.p") == "hello"
assert ObjectPath.get_path_value(test, "foo.bar") == 15
assert not ObjectPath.try_get_path_value(test, "foo.Blatxxx")
assert ObjectPath.try_get_path_value(test, "x.a[1]") == "yabba"
assert ObjectPath.try_get_path_value(test, "x.a[0]") == "dabba"
assert not ObjectPath.try_get_path_value(test, "null")
async def __call_train(self, step_context: WaterfallStepContext):
dialog_options: QnAMakerDialogOptions = ObjectPath.get_path_value(
step_context.active_dialog.state, QnAMakerDialog.KEY_OPTIONS)
train_responses: [
QueryResult
] = step_context.values[QnAMakerDialog.PROPERTY_QNA_DATA]
current_query = step_context.values[
QnAMakerDialog.PROPERTY_CURRENT_QUERY]
reply = step_context.context.activity.text
if len(train_responses) > 1:
qna_results = [
result for result in train_responses
if result.questions[0] == reply
]
if qna_results:
qna_result = qna_results[0]
step_context.values[QnAMakerDialog.PROPERTY_QNA_DATA] = [
qna_result
]
feedback_records = [
FeedbackRecord(
user_id=step_context.context.activity.id,
user_question=current_query,
qna_id=qna_result.id,
)
]
# Call Active Learning Train API
qna_client = self._get_qnamaker_client(step_context)
await qna_client.call_train(feedback_records)
await qna_client.close()
return await step_context.next([qna_result])
if (reply.lower() == dialog_options.response_options.
card_no_match_text.lower()):
activity = dialog_options.response_options.card_no_match_response
if not activity:
await step_context.context.send_activity(
QnAMakerDialog.DEFAULT_CARD_NO_MATCH_RESPONSE)
else:
await step_context.context.send_activity(activity)
return await step_context.end_dialog()
return await super().run_step(step_context,
index=0,
reason=DialogReason.BeginCalled,
result=None)
return await step_context.next(step_context.result)
async def __check_for_multiturn_prompt(self, step_context: WaterfallStepContext):
dialog_options: QnAMakerDialogOptions = ObjectPath.get_path_value(
step_context.active_dialog.state, QnAMakerDialog.KEY_OPTIONS
)
response = step_context.result
if response and isinstance(response, List):
answer = response[0]
if answer.context and answer.context.prompts:
previous_context_data = ObjectPath.get_path_value(
step_context.active_dialog.state,
QnAMakerDialog.KEY_QNA_CONTEXT_DATA,
{},
)
for prompt in answer.context.prompts:
previous_context_data[prompt.display_text] = prompt.qna_id
ObjectPath.set_path_value(
step_context.active_dialog.state,
QnAMakerDialog.KEY_QNA_CONTEXT_DATA,
previous_context_data,
)
ObjectPath.set_path_value(
step_context.active_dialog.state,
QnAMakerDialog.KEY_PREVIOUS_QNA_ID,
answer.id,
)
ObjectPath.set_path_value(
step_context.active_dialog.state,
QnAMakerDialog.KEY_OPTIONS,
dialog_options,
)
# Get multi-turn prompts card activity.
message = QnACardBuilder.get_qna_prompts_card(
answer, dialog_options.response_options.card_no_match_text
)
await step_context.context.send_activity(message)
return DialogTurnResult(DialogTurnStatus.Waiting)
return await step_context.next(step_context.result)
async def __display_qna_result(self, step_context: WaterfallStepContext):
dialog_options: QnAMakerDialogOptions = ObjectPath.get_path_value(
step_context.active_dialog.state, QnAMakerDialog.KEY_OPTIONS
)
reply = step_context.context.activity.text
if reply.lower() == dialog_options.response_options.card_no_match_text.lower():
activity = dialog_options.response_options.card_no_match_response
if not activity:
await step_context.context.send_activity(
QnAMakerDialog.DEFAULT_CARD_NO_MATCH_RESPONSE
)
else:
await step_context.context.send_activity(activity)
return await step_context.end_dialog()
# If previous QnAId is present, replace the dialog
previous_qna_id = ObjectPath.get_path_value(
step_context.active_dialog.state, QnAMakerDialog.KEY_PREVIOUS_QNA_ID, 0
)
if previous_qna_id > 0:
return await super().run_step(
step_context, index=0, reason=DialogReason.BeginCalled, result=None
)
# If response is present then show that response, else default answer.
response = step_context.result
if response and isinstance(response, List):
await step_context.context.send_activity(response[0].answer)
else:
activity = dialog_options.response_options.no_answer
if not activity:
await step_context.context.send_activity(
QnAMakerDialog.DEFAULT_NO_ANSWER
)
else:
await step_context.context.send_activity(activity)
return await step_context.end_dialog()
async def __call_generate_answer(self, step_context: WaterfallStepContext):
dialog_options: QnAMakerDialogOptions = ObjectPath.get_path_value(
step_context.active_dialog.state, QnAMakerDialog.KEY_OPTIONS
)
# Resetting context and QnAId
dialog_options.options.qna_id = 0
dialog_options.options.context = QnARequestContext()
# Storing the context info
step_context.values[
QnAMakerDialog.PROPERTY_CURRENT_QUERY
] = step_context.context.activity.text
# -Check if previous context is present, if yes then put it with the query
# -Check for id if query is present in reverse index.
previous_context_data = ObjectPath.get_path_value(
step_context.active_dialog.state, QnAMakerDialog.KEY_QNA_CONTEXT_DATA, {}
)
previous_qna_id = ObjectPath.get_path_value(
step_context.active_dialog.state, QnAMakerDialog.KEY_PREVIOUS_QNA_ID, 0
)
if previous_qna_id > 0:
dialog_options.options.context = QnARequestContext(
previous_qna_id=previous_qna_id
)
current_qna_id = previous_context_data.get(
step_context.context.activity.text
)
if current_qna_id:
dialog_options.options.qna_id = current_qna_id
# Calling QnAMaker to get response.
qna_client = self._get_qnamaker_client(step_context)
response = await qna_client.get_answers_raw(
step_context.context, dialog_options.options
)
is_active_learning_enabled = response.active_learning_enabled
step_context.values[QnAMakerDialog.PROPERTY_QNA_DATA] = response.answers
# Resetting previous query.
previous_qna_id = -1
ObjectPath.set_path_value(
step_context.active_dialog.state,
QnAMakerDialog.KEY_PREVIOUS_QNA_ID,
previous_qna_id,
)
# Check if active learning is enabled and send card
# maximum_score_for_low_score_variation is the score above which no need to check for feedback.
if (
response.answers
and response.answers[0].score <= self.maximum_score_for_low_score_variation
):
# Get filtered list of the response that support low score variation criteria.
response.answers = qna_client.get_low_score_variation(response.answers)
if len(response.answers) > 1 and is_active_learning_enabled:
suggested_questions = [qna.questions[0] for qna in response.answers]
message = QnACardBuilder.get_suggestions_card(
suggested_questions,
dialog_options.response_options.active_learning_card_title,
dialog_options.response_options.card_no_match_text,
)
await step_context.context.send_activity(message)
ObjectPath.set_path_value(
step_context.active_dialog.state,
QnAMakerDialog.KEY_OPTIONS,
dialog_options,
)
await qna_client.close()
return DialogTurnResult(DialogTurnStatus.Waiting)
# If card is not shown, move to next step with top qna response.
result = [response.answers[0]] if response.answers else []
step_context.values[QnAMakerDialog.PROPERTY_QNA_DATA] = result
ObjectPath.set_path_value(
step_context.active_dialog.state, QnAMakerDialog.KEY_OPTIONS, dialog_options
)
await qna_client.close()
return await step_context.next(result)