Version: 3.x

rasa.core.nlg.generator

NaturalLanguageGenerator Objects

class NaturalLanguageGenerator()

Generate bot utterances based on a dialogue state.

generate

async def generate(utter_action: Text, tracker: "DialogueStateTracker",
output_channel: Text,
**kwargs: Any) -> Optional[Dict[Text, Any]]

Generate a response for the requested utter action.

There are a lot of different methods to implement this, e.g. the generation can be based on responses or be fully ML based by feeding the dialogue state into a machine learning NLG model.

create

@staticmethod
def create(obj: Union["NaturalLanguageGenerator", EndpointConfig, None],
domain: Optional[Domain]) -> "NaturalLanguageGenerator"

Factory to create a generator.

ResponseVariationFilter Objects

class ResponseVariationFilter()

Filters response variations based on the channel, action and condition.

responses_for_utter_action

def responses_for_utter_action(
utter_action: Text, output_channel: Text,
filled_slots: Dict[Text, Any]) -> List[Dict[Text, Any]]

Returns array of responses that fit the channel, action and condition.

get_response_variation_id

def get_response_variation_id(utter_action: Text,
tracker: DialogueStateTracker,
output_channel: Text) -> Optional[Text]

Returns the first matched response variation ID.

This ID corresponds to the response variation that fits the channel, action and condition.