code: from unittest.mock import MagicMock, patch
  
  import pytest
  from llama_index.legacy.schema import NodeRelationship, RelatedNodeInfo, TextNode
  from llama_index.legacy.vector_stores.types import (
      ExactMatchFilter,
      MetadataFilters,
      VectorStoreQuery,
  )
  
  try:
      import google.ai.generativelanguage as genai
  
      has_google = True
  except ImportError:
      has_google = False
  
  from llama_index.legacy.vector_stores.google.generativeai import (
      GoogleVectorStore,
      set_google_config,
  )
  
  SKIP_TEST_REASON = "Google GenerativeAI is not installed"
  
  
  if has_google:
      import llama_index.legacy.vector_stores.google.generativeai.genai_extension as genaix
  
      # Make sure the tests do not hit actual production servers.
      set_google_config(
          api_endpoint="No-such-endpoint-to-prevent-hitting-real-backend",
          testing=True,
      )
  
  
  @pytest.mark.skipif(not has_google, reason=SKIP_TEST_REASON)
  @patch("google.auth.credentials.Credentials")
  def test_set_google_config(mock_credentials: MagicMock) -> None:
      set_google_config(auth_credentials=mock_credentials)
      config = genaix.get_config()
      assert config.auth_credentials == mock_credentials
  
  
  @pytest.mark.skipif(not has_google, reason=SKIP_TEST_REASON)
  @patch("google.ai.generativelanguage.RetrieverServiceClient.create_corpus")
  def test_create_corpus(mock_create_corpus: MagicMock) -> None:
      def fake_create_corpus(request: genai.CreateCorpusRequest) -> genai.Corpus:
          return request.corpus
  
      # Arrange
      mock_create_corpus.side_effect = fake_create_corpus
  
      # Act
      store = GoogleVectorStore.create_corpus(display_name="My first corpus")
  
      # Assert
      assert len(store.corpus_id) > 0
      assert mock_create_corpus.call_count == 1
  
      request = mock_create_corpus.call_args.args[0]
      assert request.corpus.name == f"corpora/{store.corpus_id}"
      assert request.corpus.display_name == "My first corpus"
  
  
  @pytest.mark.skipif(not has_google, reason=SKIP_TEST_REASON)
  @patch("google.ai.generativelanguage.RetrieverServiceClient.get_corpus")
  def test_from_corpus(mock_get_corpus: MagicMock) -> None:
      # Arrange
      mock_get_corpus.return_value = genai.Corpus(name="corpora/123")
  
      # Act
      store = GoogleVectorStore.from_corpus(corpus_id="123")
  
      # Assert
      assert store.corpus_id == "123"
  
  
  @pytest.mark.skipif(not has_google, reason=SKIP_TEST_REASON)
  def test_class_name() -> None:
      # Act
      class_name = GoogleVectorStore.class_name()
  
      # Assert
      assert class_name == "GoogleVectorStore"
  
  
  @pytest.mark.skipif(not has_google, reason=SKIP_TEST_REASON)
  @patch("google.ai.generativelanguage.RetrieverServiceClient.batch_create_chunks")
  @patch("google.ai.generativelanguage.RetrieverServiceClient.create_document")
  @patch("google.ai.generativelanguage.RetrieverServiceClient.get_document")
  @patch("google.ai.generativelanguage.RetrieverServiceClient.get_corpus")
  def test_add(
      mock_get_corpus: MagicMock,
      mock_get_document: MagicMock,
      mock_create_document: MagicMock,
      mock_batch_create_chunks: MagicMock,
  ) -> None:
      from google.api_core import exceptions as gapi_exception
  
      # Arrange
      # We will use a max requests per batch to be 2.
      # Then, we send 3 requests.
      # We expect to have 2 batches where the last batch has only 1 request.
      genaix._MAX_REQUEST_PER_CHUNK = 2
      mock_get_corpus.return_value = genai.Corpus(name="corpora/123")
      mock_get_document.side_effect = gapi_exception.NotFound("")
      mock_create_document.return_value = genai.Document(name="corpora/123/documents/456")
      mock_batch_create_chunks.side_effect = [
          genai.BatchCreateChunksResponse(
              chunks=[
                  genai.Chunk(name="corpora/123/documents/456/chunks/777"),
                  genai.Chunk(name="corpora/123/documents/456/chunks/888"),
              ]
          ),
          genai.BatchCreateChunksResponse(
              chunks=[
                  genai.Chunk(name="corpora/123/documents/456/chunks/999"),
              ]
          ),
      ]
  
      # Act
      store = GoogleVectorStore.from_corpus(corpus_id="123")
      response = store.add(
          [
              TextNode(
                  text="Hello my baby",
                  relationships={
                      NodeRelationship.SOURCE: RelatedNodeInfo(
                          node_id="456",
                          metadata={"file_name": "Title for doc 456"},
                      )
                  },
                  metadata={"position": 100},
              ),
              TextNode(
                  text="Hello my honey",
                  relationships={
                      NodeRelationship.SOURCE: RelatedNodeInfo(
                          node_id="456",
                          metadata={"file_name": "Title for doc 456"},
                      )
                  },
                  metadata={"position": 200},
              ),
              TextNode(
                  text="Hello my ragtime gal",
                  relationships={
                      NodeRelationship.SOURCE: RelatedNodeInfo(
                          node_id="456",
                          metadata={"file_name": "Title for doc 456"},
                      )
                  },
                  metadata={"position": 300},
              ),
          ]
      )
  
      # Assert
      assert response == [
          "corpora/123/documents/456/chunks/777",
          "corpora/123/documents/456/chunks/888",
          "corpora/123/documents/456/chunks/999",
      ]
  
      create_document_request = mock_create_document.call_args.args[0]
      assert create_document_request == genai.CreateDocumentRequest(
          parent="corpora/123",
          document=genai.Document(
              name="corpora/123/documents/456",
              display_name="Title for doc 456",
              custom_metadata=[
                  genai.CustomMetadata(
                      key="file_name",
                      string_value="Title for doc 456",
                  ),
              ],
          ),
      )
  
      assert mock_batch_create_chunks.call_count == 2
      mock_batch_create_chunks_calls = mock_batch_create_chunks.call_args_list
  
      first_batch_create_chunks_request = mock_batch_create_chunks_calls[0].args[0]
      assert first_batch_create_chunks_request == genai.BatchCreateChunksRequest(
          parent="corpora/123/documents/456",
          requests=[
              genai.CreateChunkRequest(
                  parent="corpora/123/documents/456",
                  chunk=genai.Chunk(
                      data=genai.ChunkData(string_value="Hello my baby"),
                      custom_metadata=[
                          genai.CustomMetadata(
                              key="position",
                              numeric_value=100,
                          ),
                      ],
                  ),
              ),
              genai.CreateChunkRequest(
                  parent="corpora/123/documents/456",
                  chunk=genai.Chunk(
                      data=genai.ChunkData(string_value="Hello my honey"),
                      custom_metadata=[
                          genai.CustomMetadata(
                              key="position",
                              numeric_value=200,
                          ),
                      ],
                  ),
              ),
          ],
      )
  
      second_batch_create_chunks_request = mock_batch_create_chunks_calls[1].args[0]
      assert second_batch_create_chunks_request == genai.BatchCreateChunksRequest(
          parent="corpora/123/documents/456",
          requests=[
              genai.CreateChunkRequest(
                  parent="corpora/123/documents/456",
                  chunk=genai.Chunk(
                      data=genai.ChunkData(string_value="Hello my ragtime gal"),
                      custom_metadata=[
                          genai.CustomMetadata(
                              key="position",
                              numeric_value=300,
                          ),
                      ],
                  ),
              ),
          ],
      )
  
  
  @pytest.mark.skipif(not has_google, reason=SKIP_TEST_REASON)
  @patch("google.ai.generativelanguage.RetrieverServiceClient.delete_document")
  @patch("google.ai.generativelanguage.RetrieverServiceClient.get_corpus")
  def test_delete(
      mock_get_corpus: MagicMock,
      mock_delete_document: MagicMock,
  ) -> None:
      # Arrange
      mock_get_corpus.return_value = genai.Corpus(name="corpora/123")
  
      # Act
      store = GoogleVectorStore.from_corpus(corpus_id="123")
      store.delete(ref_doc_id="doc-456")
  
      # Assert
      delete_document_request = mock_delete_document.call_args.args[0]
      assert delete_document_request == genai.DeleteDocumentRequest(
          name="corpora/123/documents/doc-456",
          force=True,
      )
  
  
  @pytest.mark.skipif(not has_google, reason=SKIP_TEST_REASON)
  @patch("google.ai.generativelanguage.RetrieverServiceClient.query_corpus")
  @patch("google.ai.generativelanguage.RetrieverServiceClient.get_corpus")
  def test_query(
      mock_get_corpus: MagicMock,
      mock_query_corpus: MagicMock,
  ) -> None:
      # Arrange
      mock_get_corpus.return_value = genai.Corpus(name="corpora/123")
      mock_query_corpus.return_value = genai.QueryCorpusResponse(
          relevant_chunks=[
              genai.RelevantChunk(
                  chunk=genai.Chunk(
                      name="corpora/123/documents/456/chunks/789",
                      data=genai.ChunkData(string_value="42"),
                  ),
                  chunk_relevance_score=0.9,
              )
          ]
      )
  
      # Act
      store = GoogleVectorStore.from_corpus(corpus_id="123")
      store.query(
          query=VectorStoreQuery(
              query_str="What is the meaning of life?",
              filters=MetadataFilters(
                  filters=[
                      ExactMatchFilter(
                          key="author",
                          value="Arthur Schopenhauer",
                      )
                  ]
              ),
              similarity_top_k=1,
          )
      )
  
      # Assert
      assert mock_query_corpus.call_count == 1
      query_corpus_request = mock_query_corpus.call_args.args[0]
      assert query_corpus_request == genai.QueryCorpusRequest(
          name="corpora/123",
          query="What is the meaning of life?",
          metadata_filters=[
              genai.MetadataFilter(
                  key="author",
                  conditions=[
                      genai.Condition(
                          operation=genai.Condition.Operator.EQUAL,
                          string_value="Arthur Schopenhauer",
                      )
                  ],
              )
          ],
          results_count=1,
      )
  
apis: llama_index.legacy.vector_stores.google.generativeai.GoogleVectorStore.create_corpus llama_index.legacy.vector_stores.types.ExactMatchFilter llama_index.legacy.vector_stores.google.generativeai.genai_extension.get_config llama_index.legacy.vector_stores.google.generativeai.GoogleVectorStore.from_corpus llama_index.legacy.vector_stores.google.generativeai.GoogleVectorStore.class_name llama_index.legacy.vector_stores.google.generativeai.set_google_config llama_index.legacy.schema.RelatedNodeInfo
extract_api: [((855, 914), 'pytest.mark.skipif', 'pytest.mark.skipif', (['(not has_google)'], {'reason': 'SKIP_TEST_REASON'}), '(not has_google, reason=SKIP_TEST_REASON)\n', (873, 914), False, 'import pytest\n'), ((916, 960), 'unittest.mock.patch', 'patch', (['"""google.auth.credentials.Credentials"""'], {}), "('google.auth.credentials.Credentials')\n", (921, 960), False, 'from unittest.mock import MagicMock, patch\n'), ((1174, 1233), 'pytest.mark.skipif', 'pytest.mark.skipif', (['(not has_google)'], {'reason': 'SKIP_TEST_REASON'}), '(not has_google, reason=SKIP_TEST_REASON)\n', (1192, 1233), False, 'import pytest\n'), ((1235, 1309), 'unittest.mock.patch', 'patch', (['"""google.ai.generativelanguage.RetrieverServiceClient.create_corpus"""'], {}), "('google.ai.generativelanguage.RetrieverServiceClient.create_corpus')\n", (1240, 1309), False, 'from unittest.mock import MagicMock, patch\n'), ((1915, 1974), 'pytest.mark.skipif', 'pytest.mark.skipif', (['(not has_google)'], {'reason': 'SKIP_TEST_REASON'}), '(not has_google, reason=SKIP_TEST_REASON)\n', (1933, 1974), False, 'import pytest\n'), ((1976, 2047), 'unittest.mock.patch', 'patch', (['"""google.ai.generativelanguage.RetrieverServiceClient.get_corpus"""'], {}), "('google.ai.generativelanguage.RetrieverServiceClient.get_corpus')\n", (1981, 2047), False, 'from unittest.mock import MagicMock, patch\n'), ((2311, 2370), 'pytest.mark.skipif', 'pytest.mark.skipif', (['(not has_google)'], {'reason': 'SKIP_TEST_REASON'}), '(not has_google, reason=SKIP_TEST_REASON)\n', (2329, 2370), False, 'import pytest\n'), ((2522, 2581), 'pytest.mark.skipif', 'pytest.mark.skipif', (['(not has_google)'], {'reason': 'SKIP_TEST_REASON'}), '(not has_google, reason=SKIP_TEST_REASON)\n', (2540, 2581), False, 'import pytest\n'), ((2583, 2668), 'unittest.mock.patch', 'patch', (['"""google.ai.generativelanguage.RetrieverServiceClient.batch_create_chunks"""'], {}), "('google.ai.generativelanguage.RetrieverServiceClient.batch_create_chunks'\n    )\n", (2588, 2668), False, 'from unittest.mock import MagicMock, patch\n'), ((2665, 2741), 'unittest.mock.patch', 'patch', (['"""google.ai.generativelanguage.RetrieverServiceClient.create_document"""'], {}), "('google.ai.generativelanguage.RetrieverServiceClient.create_document')\n", (2670, 2741), False, 'from unittest.mock import MagicMock, patch\n'), ((2743, 2816), 'unittest.mock.patch', 'patch', (['"""google.ai.generativelanguage.RetrieverServiceClient.get_document"""'], {}), "('google.ai.generativelanguage.RetrieverServiceClient.get_document')\n", (2748, 2816), False, 'from unittest.mock import MagicMock, patch\n'), ((2818, 2889), 'unittest.mock.patch', 'patch', (['"""google.ai.generativelanguage.RetrieverServiceClient.get_corpus"""'], {}), "('google.ai.generativelanguage.RetrieverServiceClient.get_corpus')\n", (2823, 2889), False, 'from unittest.mock import MagicMock, patch\n'), ((7904, 7963), 'pytest.mark.skipif', 'pytest.mark.skipif', (['(not has_google)'], {'reason': 'SKIP_TEST_REASON'}), '(not has_google, reason=SKIP_TEST_REASON)\n', (7922, 7963), False, 'import pytest\n'), ((7965, 8041), 'unittest.mock.patch', 'patch', (['"""google.ai.generativelanguage.RetrieverServiceClient.delete_document"""'], {}), "('google.ai.generativelanguage.RetrieverServiceClient.delete_document')\n", (7970, 8041), False, 'from unittest.mock import MagicMock, patch\n'), ((8043, 8114), 'unittest.mock.patch', 'patch', (['"""google.ai.generativelanguage.RetrieverServiceClient.get_corpus"""'], {}), "('google.ai.generativelanguage.RetrieverServiceClient.get_corpus')\n", (8048, 8114), False, 'from unittest.mock import MagicMock, patch\n'), ((8628, 8687), 'pytest.mark.skipif', 'pytest.mark.skipif', (['(not has_google)'], {'reason': 'SKIP_TEST_REASON'}), '(not has_google, reason=SKIP_TEST_REASON)\n', (8646, 8687), False, 'import pytest\n'), ((8689, 8762), 'unittest.mock.patch', 'patch', (['"""google.ai.generativelanguage.RetrieverServiceClient.query_corpus"""'], {}), "('google.ai.generativelanguage.RetrieverServiceClient.query_corpus')\n", (8694, 8762), False, 'from unittest.mock import MagicMock, patch\n'), ((8764, 8835), 'unittest.mock.patch', 'patch', (['"""google.ai.generativelanguage.RetrieverServiceClient.get_corpus"""'], {}), "('google.ai.generativelanguage.RetrieverServiceClient.get_corpus')\n", (8769, 8835), False, 'from unittest.mock import MagicMock, patch\n'), ((732, 833), 'llama_index.legacy.vector_stores.google.generativeai.set_google_config', 'set_google_config', ([], {'api_endpoint': '"""No-such-endpoint-to-prevent-hitting-real-backend"""', 'testing': '(True)'}), "(api_endpoint=\n    'No-such-endpoint-to-prevent-hitting-real-backend', testing=True)\n", (749, 833), False, 'from llama_index.legacy.vector_stores.google.generativeai import GoogleVectorStore, set_google_config\n'), ((1030, 1082), 'llama_index.legacy.vector_stores.google.generativeai.set_google_config', 'set_google_config', ([], {'auth_credentials': 'mock_credentials'}), '(auth_credentials=mock_credentials)\n', (1047, 1082), False, 'from llama_index.legacy.vector_stores.google.generativeai import GoogleVectorStore, set_google_config\n'), ((1096, 1115), 'llama_index.legacy.vector_stores.google.generativeai.genai_extension.get_config', 'genaix.get_config', ([], {}), '()\n', (1113, 1115), True, 'import llama_index.legacy.vector_stores.google.generativeai.genai_extension as genaix\n'), ((1577, 1640), 'llama_index.legacy.vector_stores.google.generativeai.GoogleVectorStore.create_corpus', 'GoogleVectorStore.create_corpus', ([], {'display_name': '"""My first corpus"""'}), "(display_name='My first corpus')\n", (1608, 1640), False, 'from llama_index.legacy.vector_stores.google.generativeai import GoogleVectorStore, set_google_config\n'), ((2155, 2187), 'google.ai.generativelanguage.Corpus', 'genai.Corpus', ([], {'name': '"""corpora/123"""'}), "(name='corpora/123')\n", (2167, 2187), True, 'import google.ai.generativelanguage as genai\n'), ((2211, 2257), 'llama_index.legacy.vector_stores.google.generativeai.GoogleVectorStore.from_corpus', 'GoogleVectorStore.from_corpus', ([], {'corpus_id': '"""123"""'}), "(corpus_id='123')\n", (2240, 2257), False, 'from llama_index.legacy.vector_stores.google.generativeai import GoogleVectorStore, set_google_config\n'), ((2429, 2459), 'llama_index.legacy.vector_stores.google.generativeai.GoogleVectorStore.class_name', 'GoogleVectorStore.class_name', ([], {}), '()\n', (2457, 2459), False, 'from llama_index.legacy.vector_stores.google.generativeai import GoogleVectorStore, set_google_config\n'), ((3367, 3399), 'google.ai.generativelanguage.Corpus', 'genai.Corpus', ([], {'name': '"""corpora/123"""'}), "(name='corpora/123')\n", (3379, 3399), True, 'import google.ai.generativelanguage as genai\n'), ((3436, 3463), 'google.api_core.exceptions.NotFound', 'gapi_exception.NotFound', (['""""""'], {}), "('')\n", (3459, 3463), True, 'from google.api_core import exceptions as gapi_exception\n'), ((3504, 3552), 'google.ai.generativelanguage.Document', 'genai.Document', ([], {'name': '"""corpora/123/documents/456"""'}), "(name='corpora/123/documents/456')\n", (3518, 3552), True, 'import google.ai.generativelanguage as genai\n'), ((4023, 4069), 'llama_index.legacy.vector_stores.google.generativeai.GoogleVectorStore.from_corpus', 'GoogleVectorStore.from_corpus', ([], {'corpus_id': '"""123"""'}), "(corpus_id='123')\n", (4052, 4069), False, 'from llama_index.legacy.vector_stores.google.generativeai import GoogleVectorStore, set_google_config\n'), ((8261, 8293), 'google.ai.generativelanguage.Corpus', 'genai.Corpus', ([], {'name': '"""corpora/123"""'}), "(name='corpora/123')\n", (8273, 8293), True, 'import google.ai.generativelanguage as genai\n'), ((8317, 8363), 'llama_index.legacy.vector_stores.google.generativeai.GoogleVectorStore.from_corpus', 'GoogleVectorStore.from_corpus', ([], {'corpus_id': '"""123"""'}), "(corpus_id='123')\n", (8346, 8363), False, 'from llama_index.legacy.vector_stores.google.generativeai import GoogleVectorStore, set_google_config\n'), ((8978, 9010), 'google.ai.generativelanguage.Corpus', 'genai.Corpus', ([], {'name': '"""corpora/123"""'}), "(name='corpora/123')\n", (8990, 9010), True, 'import google.ai.generativelanguage as genai\n'), ((9410, 9456), 'llama_index.legacy.vector_stores.google.generativeai.GoogleVectorStore.from_corpus', 'GoogleVectorStore.from_corpus', ([], {'corpus_id': '"""123"""'}), "(corpus_id='123')\n", (9439, 9456), False, 'from llama_index.legacy.vector_stores.google.generativeai import GoogleVectorStore, set_google_config\n'), ((8524, 8601), 'google.ai.generativelanguage.DeleteDocumentRequest', 'genai.DeleteDocumentRequest', ([], {'name': '"""corpora/123/documents/doc-456"""', 'force': '(True)'}), "(name='corpora/123/documents/doc-456', force=True)\n", (8551, 8601), True, 'import google.ai.generativelanguage as genai\n'), ((3676, 3732), 'google.ai.generativelanguage.Chunk', 'genai.Chunk', ([], {'name': '"""corpora/123/documents/456/chunks/777"""'}), "(name='corpora/123/documents/456/chunks/777')\n", (3687, 3732), True, 'import google.ai.generativelanguage as genai\n'), ((3750, 3806), 'google.ai.generativelanguage.Chunk', 'genai.Chunk', ([], {'name': '"""corpora/123/documents/456/chunks/888"""'}), "(name='corpora/123/documents/456/chunks/888')\n", (3761, 3806), True, 'import google.ai.generativelanguage as genai\n'), ((3911, 3967), 'google.ai.generativelanguage.Chunk', 'genai.Chunk', ([], {'name': '"""corpora/123/documents/456/chunks/999"""'}), "(name='corpora/123/documents/456/chunks/999')\n", (3922, 3967), True, 'import google.ai.generativelanguage as genai\n'), ((4243, 4318), 'llama_index.legacy.schema.RelatedNodeInfo', 'RelatedNodeInfo', ([], {'node_id': '"""456"""', 'metadata': "{'file_name': 'Title for doc 456'}"}), "(node_id='456', metadata={'file_name': 'Title for doc 456'})\n", (4258, 4318), False, 'from llama_index.legacy.schema import NodeRelationship, RelatedNodeInfo, TextNode\n'), ((4606, 4681), 'llama_index.legacy.schema.RelatedNodeInfo', 'RelatedNodeInfo', ([], {'node_id': '"""456"""', 'metadata': "{'file_name': 'Title for doc 456'}"}), "(node_id='456', metadata={'file_name': 'Title for doc 456'})\n", (4621, 4681), False, 'from llama_index.legacy.schema import NodeRelationship, RelatedNodeInfo, TextNode\n'), ((4975, 5050), 'llama_index.legacy.schema.RelatedNodeInfo', 'RelatedNodeInfo', ([], {'node_id': '"""456"""', 'metadata': "{'file_name': 'Title for doc 456'}"}), "(node_id='456', metadata={'file_name': 'Title for doc 456'})\n", (4990, 5050), False, 'from llama_index.legacy.schema import NodeRelationship, RelatedNodeInfo, TextNode\n'), ((5743, 5814), 'google.ai.generativelanguage.CustomMetadata', 'genai.CustomMetadata', ([], {'key': '"""file_name"""', 'string_value': '"""Title for doc 456"""'}), "(key='file_name', string_value='Title for doc 456')\n", (5763, 5814), True, 'import google.ai.generativelanguage as genai\n'), ((9259, 9293), 'google.ai.generativelanguage.ChunkData', 'genai.ChunkData', ([], {'string_value': '"""42"""'}), "(string_value='42')\n", (9274, 9293), True, 'import google.ai.generativelanguage as genai\n'), ((9643, 9702), 'llama_index.legacy.vector_stores.types.ExactMatchFilter', 'ExactMatchFilter', ([], {'key': '"""author"""', 'value': '"""Arthur Schopenhauer"""'}), "(key='author', value='Arthur Schopenhauer')\n", (9659, 9702), False, 'from llama_index.legacy.vector_stores.types import ExactMatchFilter, MetadataFilters, VectorStoreQuery\n'), ((10252, 10350), 'google.ai.generativelanguage.Condition', 'genai.Condition', ([], {'operation': 'genai.Condition.Operator.EQUAL', 'string_value': '"""Arthur Schopenhauer"""'}), "(operation=genai.Condition.Operator.EQUAL, string_value=\n    'Arthur Schopenhauer')\n", (10267, 10350), True, 'import google.ai.generativelanguage as genai\n'), ((6413, 6458), 'google.ai.generativelanguage.ChunkData', 'genai.ChunkData', ([], {'string_value': '"""Hello my baby"""'}), "(string_value='Hello my baby')\n", (6428, 6458), True, 'import google.ai.generativelanguage as genai\n'), ((6869, 6915), 'google.ai.generativelanguage.ChunkData', 'genai.ChunkData', ([], {'string_value': '"""Hello my honey"""'}), "(string_value='Hello my honey')\n", (6884, 6915), True, 'import google.ai.generativelanguage as genai\n'), ((7571, 7623), 'google.ai.generativelanguage.ChunkData', 'genai.ChunkData', ([], {'string_value': '"""Hello my ragtime gal"""'}), "(string_value='Hello my ragtime gal')\n", (7586, 7623), True, 'import google.ai.generativelanguage as genai\n'), ((6522, 6577), 'google.ai.generativelanguage.CustomMetadata', 'genai.CustomMetadata', ([], {'key': '"""position"""', 'numeric_value': '(100)'}), "(key='position', numeric_value=100)\n", (6542, 6577), True, 'import google.ai.generativelanguage as genai\n'), ((6979, 7034), 'google.ai.generativelanguage.CustomMetadata', 'genai.CustomMetadata', ([], {'key': '"""position"""', 'numeric_value': '(200)'}), "(key='position', numeric_value=200)\n", (6999, 7034), True, 'import google.ai.generativelanguage as genai\n'), ((7687, 7742), 'google.ai.generativelanguage.CustomMetadata', 'genai.CustomMetadata', ([], {'key': '"""position"""', 'numeric_value': '(300)'}), "(key='position', numeric_value=300)\n", (7707, 7742), True, 'import google.ai.generativelanguage as genai\n')]