code: def classify(X, domain=None, model=None):
      """
      Text classification
  
      Args:
          X (str): The raw sentence
          domain (str, optional): The domain of the text. Defaults to None.
              Options include:
                  - None: general domain
                  - 'bank': bank domain
          model (str, optional): The classification model. Defaults to None.
              Options include:
                  - None: default underthesea classifier
                  - 'prompt': OpenAI prompt model
  
      Returns:
          list: A list containing the categories of the sentence
      """
      if X == "":
          return None
  
      if model == "prompt":
          from underthesea.pipeline.classification import (
              classification_prompt,
          )
  
          args = {"domain": domain}
          return classification_prompt.classify(X, **args)
  
      if domain == "bank":
          from underthesea.pipeline.classification import bank
  
          return bank.classify(X)
  
      from underthesea.pipeline.classification import vntc
  
      return vntc.classify(X)
  
label_desc: Use image node_id 1 for calling a global function with example usage: classify(X, domain, model) and returns: vntc, None, classification_prompt, bank