def test_ask_affirmation():
policy = TwoStageFallbackPolicy.load("{}/models/two_stage_fallback".format(prj_dir))
events = [ActionExecuted(ACTION_LISTEN_NAME), user_uttered("Hi", 0.2)]
next_action = _get_next_action(policy, events, default_domain)
assert next_action == ACTION_DEFAULT_ASK_AFFIRMATION_NAME
def test_fallback_mapping_restart():
domain = Domain.load("data/test_domains/default.yml")
events = [
ActionExecuted(ACTION_DEFAULT_FALLBACK_NAME),
utilities.user_uttered(USER_INTENT_RESTART, 1),
]
tracker = DialogueStateTracker.from_events("test", events, [])
two_stage_fallback_policy = TwoStageFallbackPolicy(
priority=2, deny_suggestion_intent_name="deny"
)
mapping_policy = MappingPolicy(priority=1)
mapping_fallback_ensemble = SimplePolicyEnsemble(
[two_stage_fallback_policy, mapping_policy]
)
result, best_policy = mapping_fallback_ensemble.probabilities_using_best_policy(
tracker, domain, RegexInterpreter()
)
max_confidence_index = result.index(max(result))
index_of_mapping_policy = 1
next_action = domain.action_for_index(max_confidence_index, None)
assert best_policy == f"policy_{index_of_mapping_policy}_{MappingPolicy.__name__}"
assert next_action.name() == ACTION_RESTART_NAME
def test_ask_rephrase():
policy = TwoStageFallbackPolicy.load("{}/models/two_stage_fallback".format(prj_dir))
events = [
ActionExecuted(ACTION_LISTEN_NAME),
user_uttered("greet", 0.2),
ActionExecuted(ACTION_DEFAULT_ASK_AFFIRMATION_NAME),
ActionExecuted(ACTION_LISTEN_NAME),
user_uttered("deny", 1),
]
next_action = _get_next_action(policy, events, default_domain)
assert next_action == ACTION_DEFAULT_ASK_REPHRASE_NAME
def test_unknown_instead_affirmation():
trained_policy = TwoStageFallbackPolicy.load("{}/models/two_stage_fallback".format(prj_dir))
events = [
ActionExecuted(ACTION_LISTEN_NAME),
user_uttered("greet", 0.2),
ActionExecuted(ACTION_DEFAULT_ASK_AFFIRMATION_NAME),
ActionExecuted(ACTION_LISTEN_NAME),
user_uttered("greet", 0.2),
]
next_action = _get_next_action(trained_policy, events, default_domain)
assert next_action == ACTION_DEFAULT_FALLBACK_NAME
def test_should_nlu_fallback(
self,
trained_policy: TwoStageFallbackPolicy,
top_confidence: float,
all_confidences: List[float],
last_action_name: Text,
should_nlu_fallback: bool,
):
nlu_data = {
"intent": {"confidence": top_confidence},
"intent_ranking": [
{"confidence": confidence} for confidence in all_confidences
],
}
assert (
trained_policy.should_nlu_fallback(nlu_data, last_action_name)
is should_nlu_fallback
)
def create_policy(self, featurizer, priority):
p = TwoStageFallbackPolicy(priority=priority,
deny_suggestion_intent_name="deny")
return p
def create_policy(
self, featurizer: Optional[TrackerFeaturizer], priority: int
) -> Policy:
return TwoStageFallbackPolicy(
priority=priority, deny_suggestion_intent_name="deny"
)
async def test_train_fallback_policy():
policy = TwoStageFallbackPolicy(priority=1, deny_suggestion_intent_name="deny")
policy.persist("{}/models/two_stage_fallback".format(prj_dir))
def test_listen_after_hand_off():
trained_policy = TwoStageFallbackPolicy.load("{}/models/two_stage_fallback".format(prj_dir))
events = [ActionExecuted(ACTION_DEFAULT_FALLBACK_NAME)]
next_action = _get_next_action(trained_policy, events, default_domain)
assert next_action == ACTION_LISTEN_NAME
