Rasa-server | 2023-01-19 07:30:56 ERROR rasa.core.agent - Could not load model due to Error initializing graph component for node run_LanguageModelFeaturizer1

hi, I am using ktrain distilbert model for intent classification, i am trying to build custom graph components, from typing import Dict, Text, Any, List import os from typing import Dict, Any, Union 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 import ktrain

@DefaultV1Recipe.register( [DefaultV1Recipe.ComponentType.INTENT_CLASSIFIER], is_trainable=True )

class KtrainIntentClassifier(GraphComponent):

def __init__(self, component_config: Dict[str, Any]):
    super().__init__(component_config)
    # load your pre-trained model here
    self.model = ktrain.load_predictor("distil_bert/distilbert_model_40epochs")

def train(self, training_data, cfg, **kwargs) -> Dict[str, Any]:
    # this component doesn't need to be trained as it's pre-trained
    return {"model_file": "distil_bert/distilbert_model_40epochs"}

def process(self, message, **kwargs):
    # use the pre-trained model to predict the intent of the message
    intent = self.model.predict(message.text)[0]
    message.set("intent", {"name": intent, "confidence": 1.0}, add_to_output=True)

@classmethod
def load(cls, model_dir=None, model_metadata=None, cached_component=None, **kwargs):
    model_file = model_metadata.get("model_file")
    component = cls(model_metadata)
    component.model = ktrain.load_predictor(model_file)
    return component

def persist(self, file_name: Text, model_dir: Text) -> Dict[Text, Any]:
    pass

can anybody, please help me with correcting the code, using RASA 3 version