def test_supported_large_integer_and_float_number(self):
        """Test to ensure large integer and float numbers are handled correctly for long and double data types
        in the unstructured index schema"""
        test_case = [
            ({"long_field_1": 1}, False),  # small positive integer
            ({"long_field_1": -1}, False),  # small negative integer
            ({"long_field_1": -100232142002}, False),  # large positive integer that can't be handled by int
            ({"long_field_1": -923217213231}, False),  # large negative integer that can't be handled by int
            ({'long_field_1': int("1" * 50)}, True),  # overlarge positive integer, should raise error in long field
            # overlarge negative integer, should raise error in long field
            ({'long_field_1': -1 * int("1" * 50)}, True),
            ({"double_field_1": 1e10}, False),  # large positive integer mathematical expression
            ({"double_field_1": -1e12}, False),  # large negative integer mathematical expression
            ({"double_field_1": 1e10 + 0.123249357987123}, False),  # large positive float
            ({"double_field_1": - 1e10 + 0.123249357987123}, False),  # large negative float
        ]

        for doc, error in test_case:
            with self.subTest():
                res = self.add_documents(
                    config=self.config, add_docs_params=AddDocsParams(
                        index_name=self.default_text_index, docs=[doc], device="cpu",
                        tensor_fields=[]
                    )
                ).dict(exclude_none=True, by_alias=True)
                print(res)
                self.assertEqual(res['errors'], error)
Test to ensure large integer and float numbers are handled correctly for long and double data types
        in the unstructured index schema
tests/integ_tests/tensor_search/integ_tests/test_add_documents_unstructured.py