def test_use_existing_tensors_getting_non_tensorised(self):
        """
        During the initial index, one field is set as a non_tensor_field.
        When we insert the doc again, with use_existing_tensors, because the content
        hasn't changed, we use the existing (non-existent) vectors
        """
        self.add_documents(config=self.config, add_docs_params=AddDocsParams(
            index_name=self.index_name_1, docs=[
                {
                    "_id": "123",
                    "title 1": "content 1",
                    "non-tensor-field": "content 2. blah blah blah"
                }], auto_refresh=True, non_tensor_fields=["non-tensor-field"], device="cpu"))
        d1 = tensor_search.get_document_by_id(
            config=self.config, index_name=self.index_name_1,
            document_id="123", show_vectors=True)
        assert len(d1["_tensor_facets"]) == 1
        assert "title 1" in d1["_tensor_facets"][0]

        self.add_documents(config=self.config, add_docs_params=AddDocsParams(
            index_name=self.index_name_1, docs=[
                {
                    "_id": "123",
                    "title 1": "content 1",
                    "non-tensor-field": "content 2. blah blah blah"
                }], auto_refresh=True, use_existing_tensors=True, device="cpu"))
        d2 = tensor_search.get_document_by_id(
            config=self.config, index_name=self.index_name_1,
            document_id="123", show_vectors=True)
        self.assertEqual(d1["_tensor_facets"], d2["_tensor_facets"])

        # The only field is a non-tensor field. This makes a chunkless doc.
        self.add_documents(config=self.config, add_docs_params=AddDocsParams(
            index_name=self.index_name_1, docs=[
                {
                    "_id": "999",
                    "non-tensor-field": "content 2. blah blah blah"
                }], auto_refresh=True, non_tensor_fields=["non-tensor-field"], device="cpu"))
        d1 = tensor_search.get_document_by_id(
            config=self.config, index_name=self.index_name_1,
            document_id="999", show_vectors=True)
        assert len(d1["_tensor_facets"]) == 0

        self.add_documents(config=self.config, add_docs_params=AddDocsParams(
            index_name=self.index_name_1, docs=[
                {
                    "_id": "999",
                    "non-tensor-field": "content 2. blah blah blah"
                }], auto_refresh=True, use_existing_tensors=True, device="cpu"))
        d2 = tensor_search.get_document_by_id(
            config=self.config, index_name=self.index_name_1,
            document_id="999", show_vectors=True)
        self.assertEqual(d1["_tensor_facets"], d2["_tensor_facets"])

        During the initial index, one field is set as a non_tensor_field.
        When we insert the doc again, with use_existing_tensors, because the content
        hasn't changed, we use the existing (non-existent) vectors
        
tests/integ_tests/tensor_search/test_add_documents_use_existing_tensors.py