def test_add_diagnostic_data_with_repeated_component_raises_warning():
message = Message()
message.add_diagnostic_data("a", {})
with pytest.warns(UserWarning):
message.add_diagnostic_data("a", {})
def process(self, message: Message, **kwargs: Any) -> None:
"""Selects most like response for message.
Args:
message: Latest user message.
kwargs: Additional key word arguments.
Returns:
the most likely response, the associated intent_response_key and its
similarity to the input.
"""
out = self._predict(message)
top_label, label_ranking = self._predict_label(out)
# Get the exact intent_response_key and the associated
# responses for the top predicted label
label_intent_response_key = (
self._resolve_intent_response_key(top_label) or top_label[INTENT_NAME_KEY]
)
label_responses = self.responses.get(
util.intent_response_key_to_template_key(label_intent_response_key)
)
if label_intent_response_key and not label_responses:
# responses seem to be unavailable,
# likely an issue with the training data
# we'll use a fallback instead
rasa.shared.utils.io.raise_warning(
f"Unable to fetch responses for {label_intent_response_key} "
f"This means that there is likely an issue with the training data."
f"Please make sure you have added responses for this intent."
)
label_responses = [{TEXT: label_intent_response_key}]
for label in label_ranking:
label[INTENT_RESPONSE_KEY] = (
self._resolve_intent_response_key(label) or label[INTENT_NAME_KEY]
)
# Remove the "name" key since it is either the same as
# "intent_response_key" or it is the response text which
# is not needed in the ranking.
label.pop(INTENT_NAME_KEY)
selector_key = (
self.retrieval_intent
if self.retrieval_intent
else RESPONSE_SELECTOR_DEFAULT_INTENT
)
logger.debug(
f"Adding following selector key to message property: {selector_key}"
)
# TODO: remove `RESPONSE_SELECTOR_RESPONSE_TEMPLATES_KEY` and
# `RESPONSE_SELECTOR_TEMPLATE_NAME_KEY` in Open Source 3.0.0
utter_action_key = util.intent_response_key_to_template_key(
label_intent_response_key
)
prediction_dict = {
RESPONSE_SELECTOR_PREDICTION_KEY: {
"id": top_label["id"],
RESPONSE_SELECTOR_RESPONSES_KEY: label_responses,
RESPONSE_SELECTOR_RESPONSE_TEMPLATES_KEY: label_responses,
PREDICTED_CONFIDENCE_KEY: top_label[PREDICTED_CONFIDENCE_KEY],
INTENT_RESPONSE_KEY: label_intent_response_key,
RESPONSE_SELECTOR_UTTER_ACTION_KEY: utter_action_key,
RESPONSE_SELECTOR_TEMPLATE_NAME_KEY: utter_action_key,
},
RESPONSE_SELECTOR_RANKING_KEY: label_ranking,
}
self._set_message_property(message, prediction_dict, selector_key)
if out and DIAGNOSTIC_DATA in out:
message.add_diagnostic_data(self.unique_name, out.get(DIAGNOSTIC_DATA))
