notice

This is unreleased documentation for Rasa Open Source Documentation Master/Unreleased version.
For the latest released documentation, see the latest version (2.5.x).

Version: Master/Unreleased

rasa.core.policies.rule_policy

InvalidRule Objects

class InvalidRule(RasaException)

Exception that can be raised when rules are not valid.

RulePolicy Objects

class RulePolicy(MemoizationPolicy)

Policy which handles all the rules

supported_data

| @staticmethod
| supported_data() -> SupportedData

The type of data supported by this policy.

Returns:

The data type supported by this policy (ML and rule data).

__init__

| __init__(featurizer: Optional[TrackerFeaturizer] = None, priority: int = RULE_POLICY_PRIORITY, lookup: Optional[Dict] = None, core_fallback_threshold: float = DEFAULT_CORE_FALLBACK_THRESHOLD, core_fallback_action_name: Text = ACTION_DEFAULT_FALLBACK_NAME, enable_fallback_prediction: bool = True, restrict_rules: bool = True, check_for_contradictions: bool = True, **kwargs: Any, ,) -> None

Create a RulePolicy object.

Arguments:

  • featurizer - Featurizer which is used to convert conversation states to features.
  • priority - Priority of the policy which is used if multiple policies predict actions with the same confidence.
  • lookup - Lookup table which is used to pick matching rules for a conversation state.
  • core_fallback_threshold - Confidence of the prediction if no rule matched and de-facto threshold for a core fallback.
  • core_fallback_action_name - Name of the action which should be predicted if no rule matched.
  • enable_fallback_prediction - If True core_fallback_action_name is predicted in case no rule matched.
  • restrict_rules - If True rules are restricted to contain a maximum of 1 user message. This is used to avoid that users build a state machine using the rules.
  • check_for_contradictions - Check for contradictions.

train

| train(training_trackers: List[TrackerWithCachedStates], domain: Domain, interpreter: NaturalLanguageInterpreter, **kwargs: Any, ,) -> None

Trains the policy on given training trackers.

Arguments:

  • training_trackers - The list of the trackers.
  • domain - The domain.
  • interpreter - Interpreter which can be used by the polices for featurization.

predict_action_probabilities

| predict_action_probabilities(tracker: DialogueStateTracker, domain: Domain, interpreter: NaturalLanguageInterpreter, **kwargs: Any, ,) -> "PolicyPrediction"

Predicts the next action (see parent class for more information).

get_rule_only_data

| get_rule_only_data() -> Dict[Text, Any]

Gets the slots and loops that are used only in rule data.

Returns:

Slots and loops that are used only in rule data.