rasahq--rasa/data/test_classes/custom_graph_components/nlu_meta_fallback.py

from typing import Dict, Text, Any, List

from rasa.engine.graph import GraphComponent, ExecutionContext
from rasa.engine.recipes.default_recipe import DefaultV1Recipe
from rasa.engine.storage.resource import Resource
from rasa.engine.storage.storage import ModelStorage
from rasa.shared.nlu.training_data.message import Message
from rasa.shared.nlu.training_data.training_data import TrainingData
from rasa.nlu.classifiers.fallback_classifier import FallbackClassifier


@DefaultV1Recipe.register(
    [DefaultV1Recipe.ComponentType.INTENT_CLASSIFIER], is_trainable=True
)
class MetaFallback(FallbackClassifier):

    def __init__(
        self,
        config: Dict[Text, Any],
        model_storage: ModelStorage,
        resource: Resource,
        execution_context: ExecutionContext,
    ) -> None:
        super().__init__(config)

        self._model_storage = model_storage
        self._resource = resource

    @classmethod
    def create(
        cls,
        config: Dict[Text, Any],
        model_storage: ModelStorage,
        resource: Resource,
        execution_context: ExecutionContext,
    ) -> FallbackClassifier:
        """Creates a new untrained component (see parent class for full docstring)."""
        return cls(config, model_storage, resource, execution_context)

    def train(self, training_data: TrainingData) -> Resource:
        # Do something here with the messages
        return self._resource