notice
This is documentation for Rasa Documentation v2.x, which is no longer actively maintained.
For up-to-date documentation, see the latest version (3.x).
Version: 2.x
rasa.core.interpreter
create_interpreter
create_interpreter(obj: Union[
rasa.shared.nlu.interpreter.NaturalLanguageInterpreter,
EndpointConfig,
Text,
None,
]) -> "rasa.shared.nlu.interpreter.NaturalLanguageInterpreter"
Factory to create a natural language interpreter.
RasaNLUHttpInterpreter Objects
class RasaNLUHttpInterpreter(rasa.shared.nlu.interpreter.NaturalLanguageInterpreter)
parse
| async parse(text: Text, message_id: Optional[Text] = None, tracker: Optional[DialogueStateTracker] = None, metadata: Optional[Dict] = None) -> Dict[Text, Any]
Parse a text message.
Return a default value if the parsing of the text failed.
RasaNLUInterpreter Objects
class RasaNLUInterpreter(rasa.shared.nlu.interpreter.NaturalLanguageInterpreter)
parse
| async parse(text: Text, message_id: Optional[Text] = None, tracker: Optional[DialogueStateTracker] = None, metadata: Optional[Dict] = None) -> Dict[Text, Any]
Parse a text message.
Return a default value if the parsing of the text failed.
featurize_message
| featurize_message(message: Message) -> Optional[Message]
Featurize message using a trained NLU pipeline.
Arguments:
message
- storing text to process
Returns:
message containing tokens and features which are the output of the NLU pipeline