def reads(self, string: Text, **kwargs: Any) -> "TrainingData":
"""Reads TrainingData in YAML format from a string.
Args:
string: String with YAML training data.
**kwargs: Keyword arguments.
Returns:
New `TrainingData` object with parsed training data.
"""
from rasa.nlu.training_data import TrainingData
from rasa.validator import Validator
self.validate(string)
yaml_content = io_utils.read_yaml(string)
if not Validator.validate_training_data_format_version(
yaml_content, self.filename):
return TrainingData()
for key, value in yaml_content.items(): # pytype: disable=attribute-error
if key == KEY_NLU:
self._parse_nlu(value)
elif key == KEY_RESPONSES:
self.responses = value
return TrainingData(
self.training_examples,
self.entity_synonyms,
self.regex_features,
self.lookup_tables,
self.responses,
)
def read_from_parsed_yaml(
self, parsed_content: Dict[Text, Union[Dict,
List]]) -> List[StoryStep]:
"""Read stories from parsed YAML.
Args:
parsed_content: The parsed YAML as a dictionary.
Returns:
The parsed stories or rules.
"""
from rasa.validator import Validator
if not Validator.validate_training_data_format_version(
parsed_content, self.source_name):
return []
for key, parser_class in {
KEY_STORIES: StoryParser,
KEY_RULES: RuleParser,
}.items():
data = parsed_content.get(key, [])
parser = parser_class.from_reader(self)
parser.parse_data(data)
self.story_steps.extend(parser.get_steps())
return self.story_steps
def read_from_parsed_yaml(
self, parsed_content: Dict[Text, Union[Dict,
List]]) -> List[StoryStep]:
"""Read stories from parsed YAML.
Args:
parsed_content: The parsed YAML as a dictionary.
Returns:
The parsed stories or rules.
"""
from rasa.validator import Validator
if not Validator.validate_training_data_format_version(
parsed_content, self.source_name):
return []
stories = parsed_content.get(KEY_STORIES, [])
self._parse_data(stories, is_rule_data=False)
rules = parsed_content.get(KEY_RULES, [])
self._parse_data(rules, is_rule_data=True)
self._add_current_stories_to_result()
return self.story_steps
async def test_invalid_training_data_format_version_warns():
invalid_version_1 = {KEY_TRAINING_DATA_FORMAT_VERSION: 2.0}
invalid_version_2 = {KEY_TRAINING_DATA_FORMAT_VERSION: "Rasa"}
for version in [invalid_version_1, invalid_version_2]:
with pytest.warns(UserWarning):
assert Validator.validate_training_data_format_version(version, "")
async def test_future_training_data_format_version_not_compatible():
next_minor = str(Version(LATEST_TRAINING_DATA_FORMAT_VERSION).next_minor())
incompatible_version = {KEY_TRAINING_DATA_FORMAT_VERSION: next_minor}
with pytest.warns(UserWarning):
assert not Validator.validate_training_data_format_version(
incompatible_version, "")
async def test_compatible_training_data_format_version():
prev_major = str(Version("1.0"))
compatible_version_1 = {KEY_TRAINING_DATA_FORMAT_VERSION: prev_major}
compatible_version_2 = {
KEY_TRAINING_DATA_FORMAT_VERSION: LATEST_TRAINING_DATA_FORMAT_VERSION
}
for version in [compatible_version_1, compatible_version_2]:
with pytest.warns(None):
assert Validator.validate_training_data_format_version(version, "")
def from_yaml(cls, yaml: Text, original_filename: Text = "") -> "Domain":
from rasa.validator import Validator
try:
validate_yaml_schema(yaml, DOMAIN_SCHEMA_FILE)
except InvalidYamlFileError as e:
raise InvalidDomain(str(e))
data = rasa.utils.io.read_yaml(yaml)
if not Validator.validate_training_data_format_version(data, original_filename):
return Domain.empty()
return cls.from_dict(data)
