docs: def create_training_example(self,
                                  environment_id,
                                  collection_id,
                                  query_id,
                                  document_id=None,
                                  cross_reference=None,
                                  relevance=None,
                                  **kwargs):
          """
          Add example to training data query.
  
          Adds a example to this training data query.
  
          :param str environment_id: The ID of the environment.
          :param str collection_id: The ID of the collection.
          :param str query_id: The ID of the query used for training.
          :param str document_id: The document ID associated with this training example.
          :param str cross_reference: The cross reference associated with this training
          example.
          :param int relevance: The relevance of the training example.
          :param dict headers: A `dict` containing the request headers
          :return: A `DetailedResponse` containing the result, headers and HTTP status code.
          :rtype: DetailedResponse
          """
  
          if environment_id is None:
              raise ValueError('environment_id must be provided')
          if collection_id is None:
              raise ValueError('collection_id must be provided')
          if query_id is None:
              raise ValueError('query_id must be provided')
  
          headers = {}
          if 'headers' in kwargs:
              headers.update(kwargs.get('headers'))
          sdk_headers = get_sdk_headers('discovery', 'V1',
                                        'create_training_example')
          headers.update(sdk_headers)
  
          params = {'version': self.version}
  
          data = {
              'document_id': document_id,
              'cross_reference': cross_reference,
              'relevance': relevance
          }
  
          url = '/v1/environments/{0}/collections/{1}/training_data/{2}/examples'.format(
              *self._encode_path_vars(environment_id, collection_id, query_id))
          response = self.request(
              method='POST',
              url=url,
              headers=headers,
              params=params,
              json=data,
              accept_json=True)
          return response