code: def sentiment(X):
      global classifier
      model_name = "SA_GENERAL_V131"
      model_path = ModelFetcher.get_model_path(model_name)
  
      if not classifier:
          if not os.path.exists(model_path):
              ModelFetcher.download(model_name)
          classifier = TextClassifier.load(model_path)
  
      sentence = Sentence(X)
      classifier.predict(sentence)
      labels = sentence.labels
      try:
          label_map = {"POS": "positive", "NEG": "negative"}
          label = label_map[labels[0]]
          return label
      except Exception:
          return None
  
imports: import os
  import sys
  from underthesea.corpus.data import Sentence
  from underthesea.model_fetcher import ModelFetcher
  from underthesea.models.text_classifier import TextClassifier
  from os.path import dirname
label_desc: Use image node_id 1 for calling a global function with example usage: sentiment(X) and returns: label, None