def test_preprocess_selector_multiple_retrieval_intents():
# use some available data
training_data = rasa.shared.nlu.training_data.loading.load_data(
"data/examples/rasa/demo-rasa.yml"
)
training_data_responses = rasa.shared.nlu.training_data.loading.load_data(
"data/examples/rasa/demo-rasa-responses.yml"
)
training_data_extra_intent = TrainingData(
[
Message.build(
text="Is it possible to detect the version?", intent="faq/q1"
),
Message.build(text="How can I get a new virtual env", intent="faq/q2"),
]
)
training_data = training_data.merge(training_data_responses).merge(
training_data_extra_intent
)
response_selector = ResponseSelector()
response_selector.preprocess_train_data(training_data)
assert sorted(response_selector.all_retrieval_intents) == ["chitchat", "faq"]
def test_resolve_intent_response_key_from_label(
predicted_label, train_on_text, resolved_intent_response_key
):
# use data that include some responses
training_data = rasa.shared.nlu.training_data.loading.load_data(
"data/examples/rasa/demo-rasa.yml"
)
training_data_responses = rasa.shared.nlu.training_data.loading.load_data(
"data/examples/rasa/demo-rasa-responses.yml"
)
training_data = training_data.merge(training_data_responses)
response_selector = ResponseSelector(
component_config={"use_text_as_label": train_on_text}
)
response_selector.preprocess_train_data(training_data)
label_intent_response_key = response_selector._resolve_intent_response_key(
{"id": hash(predicted_label), "name": predicted_label}
)
assert resolved_intent_response_key == label_intent_response_key
assert (
response_selector.responses[
util.intent_response_key_to_template_key(label_intent_response_key)
]
== training_data.responses[
util.intent_response_key_to_template_key(resolved_intent_response_key)
]
)
def test_ground_truth_for_training(use_text_as_label, label_values):
# use data that include some responses
training_data = load_data("data/examples/rasa/demo-rasa.md")
training_data_responses = load_data(
"data/examples/rasa/demo-rasa-responses.md")
training_data = training_data.merge(training_data_responses)
response_selector = ResponseSelector(
component_config={"use_text_as_label": use_text_as_label})
response_selector.preprocess_train_data(training_data)
assert response_selector.responses == training_data.responses
assert (sorted(list(
response_selector.index_label_id_mapping.values())) == label_values)
