input: Write a python function to identify the intent of a question using Rasa NLU.
  assert identify_intent("What is a while loop?") == 'python_while_loop'
  assert identify_intent("What is the difference between a list and a dictionary?") == 'python_list_dictionary'
  assert identify_intent("How do you create a function in Python?") == 'python_function_creation'
output: def identify_intent(question: str) -> str:
      import spacy
      from spacy.tokens import DocBin
      from rasa.nlu.training_data import load_data
      from rasa.nlu.model import Trainer
      from rasa.nlu import config
  
      # Load the Rasa NLU configuration
      nlu_config = config.load("config.yml")
      
      # Load the training data
      training_data = load_data("nlu.md")
      
      # Create a trainer using the Rasa NLU configuration
      trainer = Trainer(nlu_config)
      
      # Train the model
      interpreter = trainer.train(training_data)
      
      # Parse the question using the trained model
      parsed_data = interpreter.parse(question)
      
      # Extract the intent from the parsed data
      intent = parsed_data['intent']['name']
      
      return intent