text: import pathlib
  from unittest.mock import patch
  
  from auto_labeling_pipeline.mappings import AmazonComprehendSentimentTemplate
  from auto_labeling_pipeline.models import RequestModelFactory
  from rest_framework import status
  from rest_framework.reverse import reverse
  
  from ...models import DOCUMENT_CLASSIFICATION, IMAGE_CLASSIFICATION
  from .utils import (CRUDMixin, make_auto_labeling_config, make_doc, make_image,
                      prepare_project)
  
  data_dir = pathlib.Path(__file__).parent / 'data'
  
  
  class TestConfigParameter(CRUDMixin):
  
      def setUp(self):
          self.project = prepare_project(task=DOCUMENT_CLASSIFICATION)
          self.data = {
              'model_name': 'GCP Entity Analysis',
              'model_attrs': {'key': 'hoge', 'type': 'PLAIN_TEXT', 'language': 'en'},
              'text': 'example'
          }
          self.url = reverse(viewname='auto_labeling_parameter_testing', args=[self.project.item.id])
  
      @patch('api.views.auto_labeling.AutoLabelingConfigParameterTest.send_request', return_value={})
      def test_called_with_proper_model(self, mock):
          self.assert_create(self.project.users[0], status.HTTP_200_OK)
          _, kwargs = mock.call_args
          expected = RequestModelFactory.create(self.data['model_name'], self.data['model_attrs'])
          self.assertEqual(kwargs['model'], expected)
  
      @patch('api.views.auto_labeling.AutoLabelingConfigParameterTest.send_request', return_value={})
      def test_called_with_text(self, mock):
          self.assert_create(self.project.users[0], status.HTTP_200_OK)
          _, kwargs = mock.call_args
          self.assertEqual(kwargs['example'], self.data['text'])
  
      @patch('api.views.auto_labeling.AutoLabelingConfigParameterTest.send_request', return_value={})
      def test_called_with_image(self, mock):
          self.data['text'] = str(data_dir / 'images/1500x500.jpeg')
          self.assert_create(self.project.users[0], status.HTTP_200_OK)
          _, kwargs = mock.call_args
          self.assertEqual(kwargs['example'], self.data['text'])
  
  
  class TestTemplateMapping(CRUDMixin):
  
      def setUp(self):
          self.project = prepare_project(task=DOCUMENT_CLASSIFICATION)
          self.data = {
              'response': {
                  'Sentiment': 'NEUTRAL',
                  'SentimentScore': {
                      'Positive': 0.004438233096152544,
                      'Negative': 0.0005306027014739811,
                      'Neutral': 0.9950305223464966,
                      'Mixed': 5.80838445785048e-7
                  }
              },
              'template': AmazonComprehendSentimentTemplate().load()
          }
          self.url = reverse(viewname='auto_labeling_template_test', args=[self.project.item.id])
  
      def test_template_mapping(self):
          response = self.assert_create(self.project.users[0], status.HTTP_200_OK)
          expected = [{'label': 'NEUTRAL'}]
          self.assertEqual(response.json(), expected)
  
      def test_json_decode_error(self):
          self.data['template'] = ''
          self.assert_create(self.project.users[0], status.HTTP_400_BAD_REQUEST)
  
  
  class TestLabelMapping(CRUDMixin):
  
      def setUp(self):
          self.project = prepare_project(task=DOCUMENT_CLASSIFICATION)
          self.data = {
              'response': [{'label': 'NEGATIVE'}],
              'label_mapping': {'NEGATIVE': 'Negative'}
          }
          self.url = reverse(viewname='auto_labeling_mapping_test', args=[self.project.item.id])
  
      def test_label_mapping(self):
          response = self.assert_create(self.project.users[0], status.HTTP_200_OK)
          expected = [{'label': 'Negative'}]
          self.assertEqual(response.json(), expected)
  
  
  class TestConfigCreation(CRUDMixin):
  
      def setUp(self):
          self.project = prepare_project(task=DOCUMENT_CLASSIFICATION)
          self.data = {
              'model_name': 'Amazon Comprehend Sentiment Analysis',
              'model_attrs': {
                  'aws_access_key': 'str',
                  'aws_secret_access_key': 'str',
                  'region_name': 'us-east-1',
                  'language_code': 'en'
              },
              'template': AmazonComprehendSentimentTemplate().load(),
              'label_mapping': {'NEGATIVE': 'Negative'}
          }
          self.url = reverse(viewname='auto_labeling_configs', args=[self.project.item.id])
  
      def test_create_config(self):
          self.assert_create(self.project.users[0], status.HTTP_201_CREATED)
  
  
  class TestAutoLabelingText(CRUDMixin):
  
      def setUp(self):
          self.project = prepare_project(task=DOCUMENT_CLASSIFICATION)
          make_auto_labeling_config(self.project.item)
          self.example = make_doc(self.project.item)
          self.url = reverse(viewname='auto_labeling_annotation', args=[self.project.item.id, self.example.id])
  
      @patch('api.views.auto_labeling.execute_pipeline', return_value=[])
      def test_text_task(self, mock):
          self.assert_create(self.project.users[0], status.HTTP_201_CREATED)
          _, kwargs = mock.call_args
          self.assertEqual(kwargs['text'], self.example.text)
  
  
  class TestAutoLabelingImage(CRUDMixin):
  
      def setUp(self):
          self.project = prepare_project(task=IMAGE_CLASSIFICATION)
          make_auto_labeling_config(self.project.item)
          filepath = data_dir / 'images/1500x500.jpeg'
          self.example = make_image(self.project.item, str(filepath))
          self.url = reverse(viewname='auto_labeling_annotation', args=[self.project.item.id, self.example.id])
  
      @patch('api.views.auto_labeling.execute_pipeline', return_value=[])
      def test_text_task(self, mock):
          self.assert_create(self.project.users[0], status.HTTP_201_CREATED)
          _, kwargs = mock.call_args
          expected = str(self.example.filename)
          self.assertEqual(kwargs['text'], expected)
  