def test_embed_prefix_content_type(self):
        """
        Ensure that the embedding returned by embed endpoint with hardcoded prefix matches the one created by
        add_docs with prefix set.
        Embedding from add_docs is retrieved using get_document_by_id with show_vectors=True.
        """
        for index in [self.unstructured_image_index_with_test_prefix, self.structured_image_index_with_test_prefix]:
            with self.subTest(index=index.type):
                # Embed request with hardcoded prefix
                embed_res_hardcoded = embed(
                    marqo_config=self.config, index_name=index.name,
                    embedding_request=EmbedRequest(
                        content=["test query: I am the GOAT."],
                        content_type=None,
                    ),
                    device="cpu"
                )

                # Embed request with prefix set
                embed_res_prefix_query = embed(
                    marqo_config=self.config, index_name=index.name,
                    embedding_request=EmbedRequest(
                        content=["I am the GOAT."],
                        content_type="query"
                    ),
                    device="cpu"
                )

                # Assert vectors are equal
                self.assertEqual(embed_res_hardcoded["content"], ["test query: I am the GOAT."])
                self.assertTrue(np.allclose(embed_res_hardcoded["embeddings"][0], embed_res_prefix_query["embeddings"][0]))

                # Embed request with hardcoded prefix
                embed_res_hardcoded = embed(
                    marqo_config=self.config, index_name=index.name,
                    embedding_request=EmbedRequest(
                        content=["test passage: I am the GOAT."],
                        content_type=None
                    ),
                    device="cpu"
                )

                # Embed request with prefix set
                embed_res_prefix_query = embed(
                    marqo_config=self.config, index_name=index.name,
                    embedding_request=EmbedRequest(
                        content=["I am the GOAT."],
                        content_type="document"
                    ),
                    device="cpu"
                )

                # Assert vectors are equal
                self.assertEqual(embed_res_hardcoded["content"], ["test passage: I am the GOAT."])
                self.assertTrue(np.allclose(embed_res_hardcoded["embeddings"][0], embed_res_prefix_query["embeddings"][0]))

        Ensure that the embedding returned by embed endpoint with hardcoded prefix matches the one created by
        add_docs with prefix set.
        Embedding from add_docs is retrieved using get_document_by_id with show_vectors=True.
        
tests/integ_tests/tensor_search/integ_tests/test_embed.py