def test_multimodal_image_url_is_embedded_as_image_not_text(self):
        """
        Ensure that the image URL in a multimodal field is embedded as an image and not as text
        """
        docs = [
            {
                "_id": "1",
                "text_field_1": "This text should be ignored",
                "image_field_1": TestImageUrls.IMAGE2.value,
            }
        ]

        # Expected vector for the LanguageBind model (adjust these values based on actual output)
        expected_vector = [-0.06504671275615692, -0.03672310709953308, -0.06603428721427917,
                           -0.032505638897418976, -0.06116769462823868, -0.03929287940263748]

        for index_name in [self.structured_marqo_index_name, self.semi_structured_marqo_index_name,
                           self.unstructured_marqo_index_name]:
            with self.subTest(index_name):
                # For unstructured index, we need to define the multimodal field and its weights
                if index_name != self.structured_marqo_index_name:
                    tensor_fields = ["multimodal_field"]
                    mappings = {
                        "multimodal_field": {
                            "type": "multimodal_combination",
                            "weights": {
                                "text_field_1": 0.0,
                                "image_field_1": 1.0,  # Only consider the image
                            }
                        }
                    }
                else:
                    tensor_fields = None
                    mappings = None

                res = self.add_documents(
                    config=self.config,
                    add_docs_params=AddDocsParams(
                        index_name=index_name,
                        docs=docs,
                        tensor_fields=tensor_fields,
                        mappings=mappings
                    )
                )

                doc = tensor_search.get_documents_by_ids(
                    config=self.config,
                    index_name=index_name,
                    document_ids=["1"],
                    show_vectors=True
                ).dict(exclude_none=True, by_alias=True)

                # Get the actual vector
                actual_vector = doc['results'][0]['_tensor_facets'][0]['_embedding']

                # Assert that the vector is similar to expected_vector
                for i, expected_value in enumerate(expected_vector):
                    self.assertAlmostEqual(actual_vector[i], expected_value, places=4,
                                        msg=f"Mismatch at index {i} for {index_name}")

        Ensure that the image URL in a multimodal field is embedded as an image and not as text
        
tests/integ_tests/tensor_search/integ_tests/test_add_documents_combined.py