code: def parse(training_path, query, verbose=False, intents_filter=None):
      """Load a trained NLU engine and play with its parsing API interactively"""
      import csv
      import logging
      from builtins import input, str
      from snips_nlu import SnipsNLUEngine
      from snips_nlu.cli.utils import set_nlu_logger
  
      if verbose == 1:
          set_nlu_logger(logging.INFO)
      elif verbose >= 2:
          set_nlu_logger(logging.DEBUG)
      if intents_filter:
          # use csv in order to properly handle commas and other special
          # characters in intent names
          intents_filter = next(csv.reader([intents_filter]))
      else:
          intents_filter = None
  
      engine = SnipsNLUEngine.from_path(training_path)
  
      if query:
          print_parsing_result(engine, query, intents_filter)
          return
  
      while True:
          query = input("Enter a query (type 'q' to quit): ").strip()
          if not isinstance(query, str):
              query = query.decode("utf-8")
          if query == "q":
              break
          print_parsing_result(engine, query, intents_filter)
  
imports: from __future__ import unicode_literals, print_function
label_desc: Use image node_id 3 for calling a global function with example usage: parse(training_path, query, verbose, intents_filter) without return types