async def test_adding_e2e_actions_to_domain(project: Text):
config_path = os.path.join(project, DEFAULT_CONFIG_PATH)
domain_path = os.path.join(project, DEFAULT_DOMAIN_PATH)
default_data_path = os.path.join(project, DEFAULT_DATA_PATH)
existing = TrainingDataImporter.load_from_dict({}, config_path,
domain_path,
[default_data_path])
additional_actions = ["Hi Joey.", "it's sunny outside."]
stories = StoryGraph([
StoryStep(events=[
UserUttered("greet_from_stories", {"name": "greet_from_stories"}),
ActionExecuted("utter_greet_from_stories"),
]),
StoryStep(events=[
UserUttered("how are you doing?", {"name": "greet_from_stories"}),
ActionExecuted(additional_actions[0],
action_text=additional_actions[0]),
ActionExecuted(additional_actions[1],
action_text=additional_actions[1]),
ActionExecuted(additional_actions[1],
action_text=additional_actions[1]),
]),
])
# Patch to return our test stories
existing.get_stories = asyncio.coroutine(lambda *args: stories)
importer = E2EImporter(existing)
domain = await importer.get_domain()
assert all(action_name in domain.action_names
for action_name in additional_actions)
async def test_without_additional_e2e_examples(tmp_path: Path):
domain_path = tmp_path / "domain.yml"
domain_path.write_text(Domain.empty().as_yaml())
config_path = tmp_path / "config.yml"
config_path.touch()
existing = TrainingDataImporter.load_from_dict({}, str(config_path),
str(domain_path), [])
stories = StoryGraph([
StoryStep(events=[
UserUttered("greet_from_stories", {"name": "greet_from_stories"}),
ActionExecuted("utter_greet_from_stories"),
])
])
# Patch to return our test stories
existing.get_stories = asyncio.coroutine(lambda *args: stories)
importer = E2EImporter(existing)
training_data = await importer.get_nlu_data()
assert training_data.training_examples
assert training_data.is_empty()
assert not training_data.without_empty_e2e_examples().training_examples
async def test_import_nlu_training_data_with_default_actions(project: Text):
config_path = os.path.join(project, DEFAULT_CONFIG_PATH)
domain_path = os.path.join(project, DEFAULT_DOMAIN_PATH)
default_data_path = os.path.join(project, DEFAULT_DATA_PATH)
importer = TrainingDataImporter.load_from_dict({}, config_path,
domain_path,
[default_data_path])
assert isinstance(importer, E2EImporter)
importer_without_e2e = importer.importer
# Check additional NLU training data from domain was added
nlu_data = await importer.get_nlu_data()
assert len(nlu_data.training_examples) > len(
(await importer_without_e2e.get_nlu_data()).training_examples)
from rasa.core.actions import action
extended_training_data = await importer.get_nlu_data()
assert all(
Message(data={
ACTION_NAME: action_name,
ACTION_TEXT: ""
}) in extended_training_data.training_examples
for action_name in action.default_action_names())
async def test_rasa_file_importer_with_invalid_domain(tmp_path: Path):
config_file = tmp_path / "config.yml"
config_file.write_text("")
importer = TrainingDataImporter.load_from_dict({}, str(config_file), None, [])
actual = await importer.get_domain()
assert actual.as_dict() == Domain.empty().as_dict()
def test_load_from_dict(config: Dict,
expected: List[Type["TrainingDataImporter"]],
project: Text):
config_path = os.path.join(project, DEFAULT_CONFIG_PATH)
domain_path = os.path.join(project, DEFAULT_DOMAIN_PATH)
default_data_path = os.path.join(project, DEFAULT_DATA_PATH)
actual = TrainingDataImporter.load_from_dict(config, config_path,
domain_path,
[default_data_path])
assert isinstance(actual, CombinedDataImporter)
actual_importers = [i.__class__ for i in actual._importers]
assert actual_importers == expected
async def test_nlu_data_domain_sync_with_retrieval_intents(project: Text):
config_path = os.path.join(project, DEFAULT_CONFIG_PATH)
domain_path = "data/test_domains/default_retrieval_intents.yml"
data_paths = [
"data/test_nlu/default_retrieval_intents.md",
"data/test_responses/default.md",
]
base_data_importer = TrainingDataImporter.load_from_dict({}, config_path,
domain_path,
data_paths)
nlu_importer = NluDataImporter(base_data_importer)
core_importer = CoreDataImporter(base_data_importer)
importer = RetrievalModelsDataImporter(
CombinedDataImporter([nlu_importer, core_importer]))
domain = await importer.get_domain()
nlu_data = await importer.get_nlu_data()
assert domain.retrieval_intents == ["chitchat"]
assert domain.intent_properties["chitchat"].get("is_retrieval_intent")
assert domain.templates == nlu_data.responses
assert "utter_chitchat" in domain.action_names
async def test_import_nlu_training_data_from_e2e_stories(project: Text):
config_path = os.path.join(project, DEFAULT_CONFIG_PATH)
domain_path = os.path.join(project, DEFAULT_DOMAIN_PATH)
default_data_path = os.path.join(project, DEFAULT_DATA_PATH)
importer = TrainingDataImporter.load_from_dict({}, config_path,
domain_path,
[default_data_path])
# The `E2EImporter` correctly wraps the underlying `CombinedDataImporter`
assert isinstance(importer, E2EImporter)
importer_without_e2e = importer.importer
stories = StoryGraph([
StoryStep(events=[
SlotSet("some slot", "doesn't matter"),
UserUttered("greet_from_stories", {"name": "greet_from_stories"}),
ActionExecuted("utter_greet_from_stories"),
]),
StoryStep(events=[
UserUttered("how are you doing?"),
ActionExecuted("utter_greet_from_stories", action_text="Hi Joey."),
]),
])
# Patch to return our test stories
importer_without_e2e.get_stories = asyncio.coroutine(lambda *args: stories)
# The wrapping `E2EImporter` simply forwards these method calls
assert (await importer_without_e2e.get_stories()).as_story_string() == (
await importer.get_stories()).as_story_string()
assert (await importer_without_e2e.get_config()) == (await
importer.get_config())
# Check additional NLU training data from stories was added
nlu_data = await importer.get_nlu_data()
# The `E2EImporter` adds NLU training data based on our training stories
assert len(nlu_data.training_examples) > len(
(await importer_without_e2e.get_nlu_data()).training_examples)
# Check if the NLU training data was added correctly from the story training data
expected_additional_messages = [
Message(data={
TEXT: "greet_from_stories",
INTENT_NAME: "greet_from_stories"
}),
Message(data={
ACTION_NAME: "utter_greet_from_stories",
ACTION_TEXT: ""
}),
Message(data={
TEXT: "how are you doing?",
INTENT_NAME: None
}),
Message(data={
ACTION_NAME: "utter_greet_from_stories",
ACTION_TEXT: "Hi Joey."
}),
]
assert all(m in nlu_data.training_examples
for m in expected_additional_messages)
