def test_travel_form():
domain = TemplateDomain.load("data/test_domains/travel_form.yml")
tracker_store = InMemoryTrackerStore(domain)
out = CollectingOutputChannel()
sender_id = "test-travel"
dispatcher = Dispatcher(sender_id, out, domain)
tracker = tracker_store.get_or_create_tracker(sender_id)
# first user utterance
tracker.update(UserUttered("", intent={"name": "inform"}))
events = ActionSearchTravel().run(dispatcher, tracker, domain)
assert len(events) == 1
assert isinstance(events[0], SlotSet)
assert events[0].key == "requested_slot"
assert events[0].value == "GPE_origin"
tracker.update(events[0])
# second user utterance
entities = [{"entity": "GPE", "value": "Berlin"}]
tracker.update(UserUttered("",
intent={"name": "inform"},
entities=entities))
events = ActionSearchTravel().run(dispatcher, tracker, domain)
for e in events:
print(e.as_story_string())
assert len(events) == 2
assert isinstance(events[0], SlotSet)
assert events[0].key == "GPE_origin"
assert events[0].value == "Berlin"
assert events[1].key == "requested_slot"
assert events[1].value == "GPE_destination"
def test_restaurant_form_unhappy_1():
domain = TemplateDomain.load("data/test_domains/restaurant_form.yml")
tracker_store = InMemoryTrackerStore(domain)
out = CollectingOutputChannel()
sender_id = "test-restaurant"
dispatcher = Dispatcher(sender_id, out, domain)
tracker = tracker_store.get_or_create_tracker(sender_id)
# first user utterance
tracker.update(UserUttered("", intent={"name": "inform"}))
events = ActionSearchRestaurants().run(dispatcher, tracker, domain)
assert len(events) == 1
assert isinstance(events[0], SlotSet)
assert events[0].key == "requested_slot"
assert events[0].value == "cuisine"
tracker.update(events[0])
# second user utterance does not provide what's asked
tracker.update(
UserUttered("",
intent={"name": "inform"}))
events = ActionSearchRestaurants().run(dispatcher, tracker, domain)
print([(e.key, e.value) for e in events])
assert len(events) == 1
assert isinstance(events[0], SlotSet)
# same slot requested again
assert events[0].key == "requested_slot"
assert events[0].value == "cuisine"
def test_people_form():
domain = TemplateDomain.load("data/test_domains/people_form.yml")
tracker_store = InMemoryTrackerStore(domain)
out = CollectingOutputChannel()
sender_id = "test-people"
dispatcher = Dispatcher(sender_id, out, domain)
tracker = tracker_store.get_or_create_tracker(sender_id)
# first user utterance
tracker.update(UserUttered("", intent={"name": "inform"}))
events = ActionSearchPeople().run(dispatcher, tracker, domain)
assert len(events) == 1
assert isinstance(events[0], SlotSet)
assert events[0].key == "requested_slot"
assert events[0].value == "person_name"
tracker.update(events[0])
# second user utterance
name = "Rasa Due"
tracker.update(
UserUttered(name,
intent={"name": "inform"}))
events = ActionSearchPeople().run(dispatcher, tracker, domain)
assert len(events) == 1
assert isinstance(events[0], SlotSet)
assert events[0].key == "person_name"
assert events[0].value == name
def test_reminder_scheduled(default_processor):
out = CollectingOutputChannel()
sender_id = uuid.uuid4().hex
d = Dispatcher(sender_id, out, default_processor.nlg)
r = ReminderScheduled("utter_greet", datetime.datetime.now())
t = default_processor.tracker_store.get_or_create_tracker(sender_id)
t.update(UserUttered("test"))
t.update(ActionExecuted("action_reminder_reminder"))
t.update(r)
default_processor.tracker_store.save(t)
default_processor.handle_reminder(r, d)
# retrieve the updated tracker
t = default_processor.tracker_store.retrieve(sender_id)
assert t.events[-4] == UserUttered(None)
assert t.events[-3] == ActionExecuted("utter_greet")
assert t.events[-2] == BotUttered("hey there None!", {
'elements': None,
'buttons': None,
'attachment': None
})
assert t.events[-1] == ActionExecuted("action_listen")
def test_restaurant_form():
domain = TemplateDomain.load("data/test_domains/restaurant_form.yml")
tracker_store = InMemoryTrackerStore(domain)
out = CollectingOutputChannel()
sender_id = "test-restaurant"
dispatcher = Dispatcher(sender_id, out, domain)
tracker = tracker_store.get_or_create_tracker(sender_id)
# first user utterance
tracker.update(UserUttered("", intent={"name": "inform"}))
events = ActionSearchRestaurants().run(dispatcher, tracker, domain)
assert len(events) == 1
assert isinstance(events[0], SlotSet)
assert events[0].key == "requested_slot"
assert events[0].value == "cuisine"
tracker.update(events[0])
# second user utterance
entities = [{"entity": "cuisine", "value": "chinese"}]
tracker.update(
UserUttered("",
intent={"name": "inform"},
entities=entities))
events = ActionSearchRestaurants().run(dispatcher, tracker, domain)
assert len(events) == 2
assert isinstance(events[0], SlotSet)
assert isinstance(events[1], SlotSet)
assert events[0].key == "cuisine"
assert events[0].value == "chinese"
assert events[1].key == "requested_slot"
assert events[1].value == "people"
def _predict_and_execute_next_action(self, message, tracker):
# this will actually send the response to the user
dispatcher = Dispatcher(message.sender_id, message.output_channel,
self.domain)
# keep taking actions decided by the policy until it chooses to 'listen'
should_predict_another_action = True
num_predicted_actions = 0
self._log_slots(tracker)
# action loop. predicts actions until we hit action listen
while should_predict_another_action and \
self._should_handle_message(tracker) and \
num_predicted_actions < self.max_number_of_predictions:
# this actually just calls the policy's method by the same name
action = self._get_next_action(tracker)
should_predict_another_action = self._run_action(
action, tracker, dispatcher)
num_predicted_actions += 1
if num_predicted_actions == self.max_number_of_predictions and \
should_predict_another_action:
# circuit breaker was tripped
logger.warn("Circuit breaker tripped. Stopped predicting "
"more actions for sender '{}'".format(
tracker.sender_id))
if self.on_circuit_break:
# call a registered callback
self.on_circuit_break(tracker, dispatcher)
logger.debug("Current topic: {}".format(tracker.topic.name))
def test_restaurant_form_skipahead():
domain = TemplateDomain.load("data/test_domains/restaurant_form.yml")
tracker_store = InMemoryTrackerStore(domain)
out = CollectingOutputChannel()
sender_id = "test-restaurant"
dispatcher = Dispatcher(sender_id, out, domain)
tracker = tracker_store.get_or_create_tracker(sender_id)
# first user utterance
entities = [{
"entity": "cuisine",
"value": "chinese"
}, {
"entity": "number",
"value": 8
}]
tracker.update(
UserUttered("", intent={"name": "inform"}, entities=entities))
events = ActionSearchRestaurants().run(dispatcher, tracker, domain)
s = events[0].as_story_string()
print(events[0].as_story_string())
print(events[1].as_story_string())
assert len(events) == 3
assert events[2].key == "requested_slot"
assert events[2].value == "vegetarian"
def _run_next_action(self, action_name, message):
# type: (Text, UserMessage) -> Dict[Text, Any]
"""Run the next action communicating with the remote core server."""
tracker = self.core_client.tracker(message.sender_id, self.domain)
dispatcher = Dispatcher(message.sender_id, message.output_channel,
self.domain)
action = self.domain.action_for_name(action_name)
# events and return values are used to update
# the tracker state after an action has been taken
try:
action_events = action.run(dispatcher, tracker, self.domain)
except Exception:
logger.exception("Encountered an exception while running action "
"'{}'. Bot will continue, but the actions "
"events are lost. Make sure to fix the "
"exception in your custom code."
"".format(action.name()))
action_events = []
# this is similar to what is done in the processor, but instead of
# logging the events on the tracker we need to return them to the
# remote core instance
events = []
for m in dispatcher.latest_bot_messages:
events.append(BotUttered(text=m.text, data=m.data))
events.extend(action_events)
return self.core_client.continue_core(action_name, events,
message.sender_id)
def __init__(self,
interpreter, # type: NaturalLanguageInterpreter
policy_ensemble, # type: PolicyEnsemble
domain, # type: Domain
tracker_store, # type: TrackerStore
generator, # type: NaturalLanguageGenerator
max_number_of_predictions=10, # type: int
message_preprocessor=None, # type: Optional[LambdaType]
on_circuit_break=None, # type: Optional[LambdaType]
create_dispatcher=None, # type: Optional[LambdaType]
rules_file=None # type: Optional[str]
):
self.rules = Rules(rules_file) if rules_file is not None else None
super(SuperMessageProcessor, self).__init__(
interpreter,
policy_ensemble,
domain,
tracker_store,
generator,
max_number_of_predictions,
message_preprocessor,
on_circuit_break
)
self.create_dispatcher = create_dispatcher
if self.create_dispatcher is None:
self.create_dispatcher = lambda sender_id, output_channel, nlg: Dispatcher(sender_id, output_channel, nlg)
def test_query_form_set_username_in_form():
domain = TemplateDomain.load("data/test_domains/query_form.yml")
tracker_store = InMemoryTrackerStore(domain)
out = CollectingOutputChannel()
sender_id = "test-form"
dispatcher = Dispatcher(sender_id, out, domain)
tracker = tracker_store.get_or_create_tracker(sender_id)
# first user utterance
tracker.update(UserUttered("", intent={"name": "inform"}))
events = ActionSearchQuery().run(dispatcher, tracker, domain)
last_message = dispatcher.latest_bot_messages[-1]
assert len(events) == 1
assert isinstance(events[0], SlotSet)
assert events[0].key == "requested_slot"
assert events[0].value == "username"
assert last_message.text == 'what is your name?'
tracker.update(events[0])
# second user utterance
username = '******'
tracker.update(UserUttered(username, intent={"name": "inform"}))
events = ActionSearchQuery().run(dispatcher, tracker, domain)
last_message = dispatcher.latest_bot_messages[-1]
assert len(events) == 2
assert isinstance(events[0], SlotSet)
assert events[0].key == "username"
assert events[0].value == username
assert events[1].key == "requested_slot"
assert events[1].value == "query"
assert username in last_message.text
def _utter_error_and_roll_back(self, latest_bot_message, tracker, template):
dispatcher = Dispatcher(latest_bot_message.sender_id,
latest_bot_message.output_channel,
self.domain)
action = ActionInvalidUtterance(template)
self._run_action(action, tracker, dispatcher)
def test_dispatcher_utter_buttons_from_domain_templ(capsys):
domain_file = "examples/restaurant_domain.yml"
domain = TemplateDomain.load(domain_file)
bot = CollectingOutputChannel()
dispatcher = Dispatcher("my-sender", bot, domain)
dispatcher.utter_template("utter_ask_price")
assert bot.messages[0][1] == "in which price range?"
assert bot.messages[1][1] == "1: cheap (cheap)"
assert bot.messages[2][1] == "2: expensive (expensive)"
def execute_action(self, sender_id: Text, action: Text,
output_channel: OutputChannel, policy: Text,
confidence: float) -> DialogueStateTracker:
"""Handle a single message."""
processor = self.create_processor()
dispatcher = Dispatcher(sender_id, output_channel, self.nlg)
return processor.execute_action(sender_id, action, dispatcher, policy,
confidence)
def test_action():
domain = Domain.load('domain.yml')
nlg = TemplatedNaturalLanguageGenerator(domain.templates)
dispatcher = Dispatcher("my-sender", CollectingOutputChannel(), nlg)
uid = str(uuid.uuid1())
tracker = DialogueStateTracker(uid, domain.slots)
# print ("dispatcher,uid,tracker ===", dispatcher, uid, tracker)
action = QuoraSearch()
action.run(dispatcher, tracker, domain)
def test_dispatcher_utter_buttons_from_domain_templ(capsys):
domain_file = "examples/moodbot/domain.yml"
domain = TemplateDomain.load(domain_file)
bot = CollectingOutputChannel()
dispatcher = Dispatcher("my-sender", bot, domain)
dispatcher.utter_template("utter_greet")
assert bot.messages[0][1] == "Hey! How are you?"
assert bot.messages[1][1] == "1: great (great)"
assert bot.messages[2][1] == "2: super sad (super sad)"
def test_action():
domain = Domain.load('domain.yml')
nlg = TemplatedNaturalLanguageGenerator(domain.templates)
dispatcher = Dispatcher("my-sender", CollectingOutputChannel(), nlg)
uid = str(uuid.uuid1())
tracker = DialogueStateTracker(uid, domain.slots)
action = ActionJoke()
action.run(dispatcher, tracker, domain)
assert 'norris' in dispatcher.output_channel.latest_output()['text'].lower()
def modified_predict_and_execute_next_action(self, message, tracker):
# this will actually send the response to the user
response = {}
dispatcher = Dispatcher(message.sender_id, message.output_channel,
self.domain)
# keep taking actions decided by the policy until it chooses to 'listen'
should_predict_another_action = True
num_predicted_actions = 0
self._log_slots(tracker)
# action loop. predicts actions until we hit action listen
while (should_predict_another_action
and self._should_handle_message(tracker)
and num_predicted_actions < self.max_number_of_predictions):
# this actually just calls the policy's method by the same name
action = self._get_next_action(tracker)
if action.name() != "action_listen":
response["next_action"] = action.name()
should_predict_another_action = self._run_action(
action, tracker, dispatcher)
num_predicted_actions += 1
if (num_predicted_actions == self.max_number_of_predictions
and should_predict_another_action):
# circuit breaker was tripped
logger.warn("Circuit breaker tripped. Stopped predicting "
"more actions for sender '{}'".format(
tracker.sender_id))
if self.on_circuit_break:
# call a registered callback
self.on_circuit_break(tracker, dispatcher)
response["tracker"] = tracker.current_state()
# we used contexts and next action has changed so we need to change
# intent accordingly
tmp = response["tracker"]["latest_message"]["intent_ranking"][0][
"name"]
response["tracker"]["latest_message"]["intent_ranking"][0][
"name"] = response["tracker"]["latest_message"][
"intent_ranking"][1]["name"]
response["tracker"]["latest_message"]["intent_ranking"][1][
"name"] = tmp
response["tracker"]["latest_message"]["intent"] = response[
"tracker"]["latest_message"]["intent_ranking"][0]
# added to restart the bot when it becomes unstable when a followup action is triggered
# due to contexts
should_predict_another_action = self._run_action(
ActionRestart(), tracker, dispatcher)
return response
response["tracker"] = tracker.current_state()
return response
def test_dispatcher_utter_buttons_from_domain_templ():
domain_file = "examples/moodbot/domain.yml"
domain = TemplateDomain.load(domain_file)
bot = CollectingOutputChannel()
dispatcher = Dispatcher("my-sender", bot, domain)
dispatcher.utter_template("utter_greet")
assert len(bot.messages) == 1
assert bot.messages[0]['text'] == "Hey! How are you?"
assert bot.messages[0]['data'] == [
{'payload': 'great', 'title': 'great'},
{'payload': 'super sad', 'title': 'super sad'}
]
def test_dispatcher_template_invalid_vars():
domain = TemplateDomain(
[], [], [], {
"my_made_up_template": [{
"text": "a template referencing an invalid {variable}."}]},
[], [], None)
bot = CollectingOutputChannel()
dispatcher = Dispatcher("my-sender", bot, domain)
dispatcher.utter_template("my_made_up_template")
collected = dispatcher.output_channel.latest_output()
assert collected['text'].startswith(
"a template referencing an invalid {variable}.")
def execute_action(
self,
sender_id, # type: Text
action, # type: Text
output_channel # type: OutputChannel
):
# type: (...) -> DialogueStateTracker
"""Handle a single message."""
processor = self.create_processor()
dispatcher = Dispatcher(sender_id, output_channel, self.nlg)
return processor.execute_action(sender_id, action, dispatcher)
def test_dispatcher_template_invalid_vars():
templates = {
"my_made_up_template": [{
"text": "a template referencing an invalid {variable}."}]}
bot = CollectingOutputChannel()
nlg = TemplatedNaturalLanguageGenerator(templates)
dispatcher = Dispatcher("my-sender", bot, nlg)
tracker = DialogueStateTracker("my-sender", slots=[])
dispatcher.utter_template("my_made_up_template", tracker)
collected = dispatcher.output_channel.latest_output()
assert collected['text'].startswith(
"a template referencing an invalid {variable}.")
def setUp(self):
self.not_undestood = ActionNotUnderstood()
# set Interpreter (NLU) to Rasa NLU
self.interpreter = 'rasa-nlu/models/rasa-nlu/default/socialcompanionnlu'
# load the trained agent model
self.agent = Agent.load('./models/dialogue', self.interpreter)
self.agent.handle_channel(ConsoleInputChannel())
# TODO mock dispatcher, tracker and domain
self.dispatcher = Dispatcher(output_channel=ConsoleOutputChannel())
self.tracker = DialogueStateTracker()
self.domain = Domain()
def test_dispatcher_utter_buttons_from_domain_templ(default_tracker):
domain_file = "examples/moodbot/domain.yml"
domain = Domain.load(domain_file)
bot = CollectingOutputChannel()
nlg = TemplatedNaturalLanguageGenerator(domain.templates)
dispatcher = Dispatcher("my-sender", bot, nlg)
dispatcher.utter_template("utter_greet", default_tracker)
assert len(bot.messages) == 1
assert bot.messages[0]['text'] == "Hey! How are you?"
assert bot.messages[0]['data'] == [
{'payload': 'great', 'title': 'great'},
{'payload': 'super sad', 'title': 'super sad'}
]
def _set_and_execute_next_action(self, action_name, message, tracker):
"""
Sets the next action to action_name then execute
:param action_name: String
:param tracker: DialogueStateTracker
:return: void
"""
# this will actually send the response to the user
dispatcher = Dispatcher(message.sender_id, message.output_channel,
self.domain)
action = self.domain.action_map[action_name][1]
self._log_slots(tracker)
self._run_action(action, tracker, dispatcher)
self._run_action(ActionListen(), tracker, dispatcher)
def test_restaurant_form_unhappy_2():
domain = TemplateDomain.load("data/test_domains/restaurant_form.yml")
nlg = TemplatedNaturalLanguageGenerator(domain.templates)
tracker_store = InMemoryTrackerStore(domain)
out = CollectingOutputChannel()
sender_id = "test-restaurant"
dispatcher = Dispatcher(sender_id, out, nlg)
tracker = tracker_store.get_or_create_tracker(sender_id)
# first user utterance
entities = [{
"entity": "cuisine",
"value": "chinese"
}, {
"entity": "number",
"value": 8
}]
tracker.update(
UserUttered("", intent={"name": "inform"}, entities=entities))
# store all entities as slots
events = ActionSearchRestaurants().run(dispatcher, tracker, domain)
for e in events:
tracker.update(e)
cuisine = tracker.get_slot("cuisine")
people = tracker.get_slot("people")
assert cuisine == "chinese"
assert people == 8
events = ActionSearchRestaurants().run(dispatcher, tracker, domain)
assert len(events) == 3
assert isinstance(events[0], SlotSet)
assert events[2].key == "requested_slot"
assert events[2].value == "vegetarian"
tracker.update(events[2])
# second user utterance does not provide what's asked
tracker.update(UserUttered("", intent={"name": "random"}))
events = ActionSearchRestaurants().run(dispatcher, tracker, domain)
s = events[0].as_story_string()
assert len(events) == 1
assert events[0].key == "requested_slot"
assert events[0].value == "vegetarian"
def test_reminder_aborted(default_processor):
out = CollectingOutputChannel()
sender_id = uuid.uuid4().hex
d = Dispatcher(sender_id, out, default_processor.nlg)
r = ReminderScheduled("utter_greet", datetime.datetime.now(),
kill_on_user_message=True)
t = default_processor.tracker_store.get_or_create_tracker(sender_id)
t.update(r)
t.update(UserUttered("test")) # cancels the reminder
default_processor.tracker_store.save(t)
default_processor.handle_reminder(r, d)
# retrieve the updated tracker
t = default_processor.tracker_store.retrieve(sender_id)
assert len(t.events) == 3 # nothing should have been executed
def predict_and_execute_next_action(self, message, tracker):
dispatcher = Dispatcher(message.sender_id, message.output_channel,
self.message_processor.nlg)
# keep taking actions decided by the policy until it chooses to 'listen'
should_predict_another_action = True
num_predicted_actions = 0
self.log_slots(tracker)
# action loop. predicts actions until we hit action listen
while (should_predict_another_action
and self.should_handle_message(tracker)
and num_predicted_actions <
self.message_processor.max_number_of_predictions):
# this actually just calls the policy's method by the same name
probabilities, policy = self.message_processor._get_next_action_probabilities(
tracker)
max_index = int(np.argmax(probabilities))
if self.message_processor.domain.num_actions <= max_index or max_index < 0:
raise Exception("Can not access action at index {}. "
"Domain has {} actions.".format(
max_index,
self.message_processor.domain.num_actions))
action = self.ask_for_action(
self.message_processor.domain.action_names[max_index],
self.message_processor.action_endpoint)
confidence = probabilities[max_index]
# action, policy, confidence = self.agent.predict_next_action(tracker)
should_predict_another_action = self.run_action(
action, tracker, dispatcher, policy, confidence)
num_predicted_actions += 1
if (num_predicted_actions
== self.message_processor.max_number_of_predictions
and should_predict_another_action):
# circuit breaker was tripped
if self.message_processor.on_circuit_break:
# call a registered callback
self.message_processor.on_circuit_break(tracker, dispatcher)
def test_query_form_set_username_directly():
domain = TemplateDomain.load("data/test_domains/query_form.yml")
nlg = TemplatedNaturalLanguageGenerator(domain.templates)
tracker_store = InMemoryTrackerStore(domain)
out = CollectingOutputChannel()
sender_id = "test-form"
dispatcher = Dispatcher(sender_id, out, nlg)
tracker = tracker_store.get_or_create_tracker(sender_id)
# pre-fill username slot
username = "******"
tracker.update(SlotSet('username', username))
# first user utterance
tracker.update(UserUttered("", intent={"name": "inform"}))
events = ActionSearchQuery().run(dispatcher, tracker, domain)
last_message = dispatcher.latest_bot_messages[-1]
assert len(events) == 1
assert isinstance(events[0], SlotSet)
assert events[0].key == "requested_slot"
assert events[0].value == "query"
assert username in last_message.text
def _predict_and_execute_next_action(self, message, tracker):
# this will actually send the response to the user
dispatcher = Dispatcher(message.sender_id, message.output_channel,
self.domain)
# keep taking actions decided by the policy until it chooses to 'listen'
should_predict_another_action = True
num_predicted_actions = 0
self._log_slots(tracker)
# action loop. predicts actions until we hit action listen
while (should_predict_another_action
and self._should_handle_message(tracker)
and num_predicted_actions < self.max_number_of_predictions):
# this actually just calls the policy's method by the same name
action = self._get_next_action(tracker)
should_predict_another_action = self._run_action(
action, tracker, dispatcher)
num_predicted_actions += 1
if (num_predicted_actions == self.max_number_of_predictions
and should_predict_another_action):
# circuit breaker was tripped
logger.warn("Circuit breaker tripped. Stopped predicting "
"more actions for sender '{}'".format(
tracker.sender_id))
if self.on_circuit_break:
# call a registered callback
self.on_circuit_break(tracker, dispatcher)
# added to restart the bot when it becomes unstable when a followup action is triggered
# due to contexts
should_predict_another_action = self._run_action(
ActionRestart(), tracker, dispatcher)
def default_dispatcher_collecting(default_nlg):
bot = CollectingOutputChannel()
return Dispatcher("my-sender", bot, default_nlg)