def _validate_json_training_payload(rjs: Dict):
if "config" not in rjs:
raise ErrorResponse(
400,
"BadRequest",
"The training request is missing the required key `config`.",
{"parameter": "config", "in": "body"},
)
if "nlu" not in rjs and "stories" not in rjs:
raise ErrorResponse(
400,
"BadRequest",
"To train a Rasa model you need to specify at least one type of "
"training data. Add `nlu` and/or `stories` to the request.",
{"parameters": ["nlu", "stories"], "in": "body"},
)
if "stories" in rjs and "domain" not in rjs:
raise ErrorResponse(
400,
"BadRequest",
"To train a Rasa model with story training data, you also need to "
"specify the `domain`.",
{"parameter": "domain", "in": "body"},
)
if "force" in rjs or "save_to_default_model_directory" in rjs:
common_utils.raise_deprecation_warning(
"Specifying 'force' and 'save_to_default_model_directory' as part of the "
"JSON payload is deprecated. Please use the header arguments "
"'force_training' and 'save_to_default_model_directory'.",
docs=_docs("/api/http-api"),
)
def __init__(
self,
priority: int = FALLBACK_POLICY_PRIORITY,
nlu_threshold: float = 0.3,
ambiguity_threshold: float = 0.1,
core_threshold: float = 0.3,
fallback_action_name: Text = ACTION_DEFAULT_FALLBACK_NAME,
) -> None:
"""Create a new Fallback policy.
Args:
core_threshold: if NLU confidence threshold is met,
predict fallback action with confidence `core_threshold`.
If this is the highest confidence in the ensemble,
the fallback action will be executed.
nlu_threshold: minimum threshold for NLU confidence.
If intent prediction confidence is lower than this,
predict fallback action with confidence 1.0.
ambiguity_threshold: threshold for minimum difference
between confidences of the top two predictions
fallback_action_name: name of the action to execute as a fallback
"""
super().__init__(priority=priority)
self.nlu_threshold = nlu_threshold
self.ambiguity_threshold = ambiguity_threshold
self.core_threshold = core_threshold
self.fallback_action_name = fallback_action_name
common_utils.raise_deprecation_warning(
f"'{self.__class__.__name__}' is deprecated and will be removed "
"in the future. It is recommended to use the 'RulePolicy' instead.",
docs=DOCS_URL_MIGRATION_GUIDE,
)
def _replace_deprecated_option(
old_option: Text,
new_option: Union[Text, List[Text]],
config: Dict[Text, Any],
warn_until_version: Text = NEXT_MAJOR_VERSION_FOR_DEPRECATIONS,
) -> Dict[Text, Any]:
if old_option in config:
if isinstance(new_option, str):
common_utils.raise_deprecation_warning(
f"Option '{old_option}' got renamed to '{new_option}'. "
f"Please update your configuration file.",
warn_until_version=warn_until_version,
)
config[new_option] = config[old_option]
else:
common_utils.raise_deprecation_warning(
f"Option '{old_option}' got renamed to "
f"a dictionary '{new_option[0]}' with a key '{new_option[1]}'. "
f"Please update your configuration file.",
warn_until_version=warn_until_version,
)
option_dict = config.get(new_option[0], {})
option_dict[new_option[1]] = config[old_option]
config[new_option[0]] = option_dict
return config
def test_raise_deprecation_warning_default():
with pytest.warns(FutureWarning) as record:
raise_deprecation_warning("This feature is deprecated.")
assert len(record) == 1
assert record[0].message.args[0] == (
f"This feature is deprecated. "
f"(will be removed in {NEXT_MAJOR_VERSION_FOR_DEPRECATIONS})")
def test_raise_deprecation_warning():
with pytest.warns(FutureWarning) as record:
raise_deprecation_warning("This feature is deprecated.",
warn_until_version="3.0.0")
assert len(record) == 1
assert (record[0].message.args[0] ==
"This feature is deprecated. (will be removed in 3.0.0)")
def __init__(self, priority: int = MAPPING_POLICY_PRIORITY) -> None:
"""Create a new Mapping policy."""
super().__init__(priority=priority)
common_utils.raise_deprecation_warning(
f"'{MappingPolicy.__name__}' is deprecated and will be removed in "
"the future. It is recommended to use the 'RulePolicy' instead.",
docs=DOCS_URL_MIGRATION_GUIDE,
)
def test_raise_deprecation_warning_version_already_in_message():
with pytest.warns(FutureWarning) as record:
raise_deprecation_warning(
"This feature is deprecated and will be removed in 3.0.0!",
warn_until_version="3.0.0",
)
assert len(record) == 1
assert (record[0].message.args[0] ==
"This feature is deprecated and will be removed in 3.0.0!")
def _deserialise_dialogue_from_pickle(
sender_id: Text, serialised_tracker: bytes
) -> Dialogue:
common_utils.raise_deprecation_warning(
f"Found pickled tracker for "
f"conversation ID '{sender_id}'. Deserialisation of pickled "
f"trackers is deprecated. Rasa will perform any "
f"future save operations of this tracker using json serialisation.",
)
return pickle.loads(serialised_tracker)
def __init__(
self,
featurizer: Optional[TrackerFeaturizer] = None,
priority: int = FORM_POLICY_PRIORITY,
lookup: Optional[Dict] = None,
) -> None:
# max history is set to 2 in order to capture
# previous meaningful action before action listen
super().__init__(featurizer=featurizer,
priority=priority,
max_history=2,
lookup=lookup)
common_utils.raise_deprecation_warning(
f"'{FormPolicy.__name__}' is deprecated and will be removed in "
"in the future. It is recommended to use the 'RulePolicy' instead.",
docs=DOCS_URL_MIGRATION_GUIDE,
)
def from_credentials(cls, credentials: Optional[Dict[Text, Any]]) -> InputChannel:
if credentials is None:
cls.raise_missing_credentials_exception()
# pytype: disable=attribute-error
if credentials.get("pw") is not None or credentials.get("user") is not None:
common_utils.raise_deprecation_warning(
"Mattermost recently switched to bot accounts. 'user' and 'pw' "
"should not be used anymore, you should rather convert your "
"account to a bot account and use a token. Password based "
"authentication will be removed in a future Rasa Open Source version.",
docs=DOCS_URL_CONNECTORS + "mattermost/",
)
token = MattermostBot.token_from_login(
credentials.get("url"), credentials.get("user"), credentials.get("pw")
)
else:
token = credentials.get("token")
return cls(credentials.get("url"), token, credentials.get("webhook_url"))
