def test_pagination_hybrid_lexical_tensor_with_modifiers(self):
        """
        Show that pagination is consistent when using hybrid search with lexical retrieval, tensor ranking,
        with lexical score modifiers eliminating some results.
        """
        for index in [self.index_structured, self.index_unstructured]:
            with self.subTest(index=type(index)):
                # Add documents
                add_docs_res = self.add_documents(
                    config=self.config,
                    add_docs_params=AddDocsParams(
                        index_name=index.name,
                        docs=[
                            {"_id": "doc4", "text_field_1": "HELLO WORLD",
                             "mult_field_1": 0.5, "add_field_1": 20},  # OUT (negative)
                            {"_id": "doc5", "text_field_1": "HELLO WORLD", "mult_field_1": 1.0},  # OUT (negative)
                            {"_id": "doc6", "text_field_1": "HELLO WORLD"},  # Top result
                            {"_id": "doc7", "text_field_1": "HELLO WORLD", "add_field_1": 1.0},  # Top result
                            {"_id": "doc8", "text_field_1": "HELLO WORLD", "mult_field_1": 2.0},  # OUT (negative)
                            {"_id": "doc9", "text_field_1": "HELLO WORLD", "mult_field_1": 3.0},  # OUT (negative)
                            {"_id": "doc10", "text_field_1": "HELLO WORLD", "mult_field_2": 3.0},  # Top result
                        ],
                        tensor_fields=["text_field_1"] if isinstance(index, UnstructuredMarqoIndex) \
                            else None
                    )
                )

                full_res = tensor_search.search(
                    config=self.config,
                    index_name=index.name,
                    text="HELLO WORLD",
                    search_method="HYBRID",
                    hybrid_parameters=HybridParameters(
                        retrievalMethod=RetrievalMethod.Lexical,
                        rankingMethod=RankingMethod.Tensor,
                        scoreModifiersLexical={
                            "multiply_score_by": [
                                {"field_name": "mult_field_1", "weight": -10},
                                # Will bring down doc8 and doc9. Keep doc6, doc7, doc10
                            ]
                        },
                        scoreModifiersTensor={
                            "multiply_score_by": [
                                {"field_name": "mult_field_1", "weight": 10},
                                {"field_name": "mult_field_2", "weight": -10}
                            ],
                            "add_to_score": [
                                {"field_name": "add_field_1", "weight": 5}
                            ]
                        },
                        verbose=True
                    ),
                    result_count=3
                )

                # Paginate (3 pages of 1 result each)
                paginated_res = []
                for i in range(3):
                    paginated_res.extend(tensor_search.search(
                        config=self.config,
                        index_name=index.name,
                        text="HELLO WORLD",
                        search_method="HYBRID",
                        hybrid_parameters=HybridParameters(
                            retrievalMethod=RetrievalMethod.Lexical,
                            rankingMethod=RankingMethod.Tensor,
                            scoreModifiersLexical={
                                "multiply_score_by": [
                                    {"field_name": "mult_field_1", "weight": -10},
                                    # Will bring down doc8 and doc9. Keep doc6, doc7, doc10
                                ]
                            },
                            scoreModifiersTensor={
                                "multiply_score_by": [
                                    {"field_name": "mult_field_1", "weight": 10},
                                    {"field_name": "mult_field_2", "weight": -10}
                                ],
                                "add_to_score": [
                                    {"field_name": "add_field_1", "weight": 5}
                                ]
                            },
                            verbose=True
                        ),
                        result_count=1,
                        offset=i
                    )["hits"])

                # Compare full results to paginated results
                self.assertEqual(full_res["hits"], paginated_res)

        Show that pagination is consistent when using hybrid search with lexical retrieval, tensor ranking,
        with lexical score modifiers eliminating some results.
        
tests/integ_tests/tensor_search/test_pagination.py