class_docstr: Reader for NLU training data.
docstr: Reads the intent and examples from respective jsons.
docstr_tok: ["Reads","the","intent","and","examples","from","respective","jsons","."]
code: def _read_intent(
      self, intent: Dict[Text, Any], examples: List[Dict[Text, Any]]
  ) -> "TrainingData":
      """Reads the intent and examples from respective jsons."""
      intent_name = intent.get("name")
  
      training_examples = []
      for ex in examples:
          text, entities = self._join_text_chunks(ex["data"])
          training_examples.append(
              Message.build(text, intent_name, entities)
          )
  
      return TrainingData(training_examples)
  
imports: import logging
  import os
  from pathlib import Path
  from typing import Any, Dict, Optional, Text, List, Tuple, Union
  import rasa.shared.nlu.training_data.util
  from rasa.shared.constants import DOCS_BASE_URL
  from rasa.shared.nlu.training_data.formats.readerwriter import TrainingDataReader
  from rasa.shared.nlu.training_data.util import transform_entity_synonyms
  import rasa.shared.utils.io
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.message import Message
label_desc: Use image node_id 2 for calling the DialogflowReader obj's underlying member method code with example usage: obj._read_intent(intent, examples) and returns: TrainingData