"""
Unit tests for WorkflowResponseConverter focusing on process_data truncation functionality.
"""

import uuid
from collections.abc import Mapping
from dataclasses import dataclass
from typing import Any
from unittest.mock import Mock

import pytest

from core.app.app_config.entities import WorkflowUIBasedAppConfig
from core.app.apps.common.workflow_response_converter import WorkflowResponseConverter
from core.app.entities.app_invoke_entities import InvokeFrom, WorkflowAppGenerateEntity
from core.app.entities.queue_entities import (
    QueueEvent,
    QueueIterationStartEvent,
    QueueLoopStartEvent,
    QueueNodeExceptionEvent,
    QueueNodeFailedEvent,
    QueueNodeRetryEvent,
    QueueNodeStartedEvent,
    QueueNodeSucceededEvent,
)
from core.workflow.entities.workflow_start_reason import WorkflowStartReason
from core.workflow.enums import NodeType
from core.workflow.system_variable import SystemVariable
from libs.datetime_utils import naive_utc_now
from models import Account
from models.model import AppMode


class TestWorkflowResponseConverter:
    """Test truncation in WorkflowResponseConverter."""

    def create_mock_generate_entity(self) -> WorkflowAppGenerateEntity:
        """Create a mock WorkflowAppGenerateEntity."""
        mock_entity = Mock(spec=WorkflowAppGenerateEntity)
        mock_app_config = Mock()
        mock_app_config.tenant_id = "test-tenant-id"
        mock_entity.invoke_from = InvokeFrom.WEB_APP
        mock_entity.app_config = mock_app_config
        mock_entity.inputs = {}
        return mock_entity

    def create_workflow_response_converter(self) -> WorkflowResponseConverter:
        """Create a WorkflowResponseConverter for testing."""

        mock_entity = self.create_mock_generate_entity()
        mock_user = Mock(spec=Account)
        mock_user.id = "test-user-id"
        mock_user.name = "Test User"
        mock_user.email = "test@example.com"

        system_variables = SystemVariable(workflow_id="wf-id", workflow_execution_id="initial-run-id")
        return WorkflowResponseConverter(
            application_generate_entity=mock_entity,
            user=mock_user,
            system_variables=system_variables,
        )

    def create_node_started_event(self, *, node_execution_id: str | None = None) -> QueueNodeStartedEvent:
        """Create a QueueNodeStartedEvent for testing."""
        return QueueNodeStartedEvent(
            node_execution_id=node_execution_id or str(uuid.uuid4()),
            node_id="test-node-id",
            node_title="Test Node",
            node_type=NodeType.CODE,
            start_at=naive_utc_now(),
            in_iteration_id=None,
            in_loop_id=None,
            provider_type="built-in",
            provider_id="code",
        )

    def create_node_succeeded_event(
        self,
        *,
        node_execution_id: str,
        process_data: Mapping[str, Any] | None = None,
    ) -> QueueNodeSucceededEvent:
        """Create a QueueNodeSucceededEvent for testing."""
        return QueueNodeSucceededEvent(
            node_id="test-node-id",
            node_type=NodeType.CODE,
            node_execution_id=node_execution_id,
            start_at=naive_utc_now(),
            in_iteration_id=None,
            in_loop_id=None,
            inputs={},
            process_data=process_data or {},
            outputs={},
            execution_metadata={},
        )

    def create_node_retry_event(
        self,
        *,
        node_execution_id: str,
        process_data: Mapping[str, Any] | None = None,
    ) -> QueueNodeRetryEvent:
        """Create a QueueNodeRetryEvent for testing."""
        return QueueNodeRetryEvent(
            inputs={"data": "inputs"},
            outputs={"data": "outputs"},
            process_data=process_data or {},
            error="oops",
            retry_index=1,
            node_id="test-node-id",
            node_type=NodeType.CODE,
            node_title="test code",
            provider_type="built-in",
            provider_id="code",
            node_execution_id=node_execution_id,
            start_at=naive_utc_now(),
            in_iteration_id=None,
            in_loop_id=None,
        )

    def test_workflow_node_finish_response_uses_truncated_process_data(self):
        """Test that node finish response uses get_response_process_data()."""
        converter = self.create_workflow_response_converter()

        original_data = {"large_field": "x" * 10000, "metadata": "info"}
        truncated_data = {"large_field": "[TRUNCATED]", "metadata": "info"}

        converter.workflow_start_to_stream_response(
            task_id="bootstrap",
            workflow_run_id="run-id",
            workflow_id="wf-id",
            reason=WorkflowStartReason.INITIAL,
        )
        start_event = self.create_node_started_event()
        converter.workflow_node_start_to_stream_response(
            event=start_event,
            task_id="test-task-id",
        )

        event = self.create_node_succeeded_event(
            node_execution_id=start_event.node_execution_id,
            process_data=original_data,
        )

        def fake_truncate(mapping):
            if mapping == dict(original_data):
                return truncated_data, True
            return mapping, False

        converter._truncator.truncate_variable_mapping = fake_truncate  # type: ignore[assignment]

        response = converter.workflow_node_finish_to_stream_response(
            event=event,
            task_id="test-task-id",
        )

        # Response should use truncated data, not original
        assert response is not None
        assert response.data.process_data == truncated_data
        assert response.data.process_data != original_data
        assert response.data.process_data_truncated is True

    def test_workflow_node_finish_response_without_truncation(self):
        """Test node finish response when no truncation is applied."""
        converter = self.create_workflow_response_converter()

        original_data = {"small": "data"}

        converter.workflow_start_to_stream_response(
            task_id="bootstrap",
            workflow_run_id="run-id",
            workflow_id="wf-id",
            reason=WorkflowStartReason.INITIAL,
        )
        start_event = self.create_node_started_event()
        converter.workflow_node_start_to_stream_response(
            event=start_event,
            task_id="test-task-id",
        )

        event = self.create_node_succeeded_event(
            node_execution_id=start_event.node_execution_id,
            process_data=original_data,
        )

        def fake_truncate(mapping):
            return mapping, False

        converter._truncator.truncate_variable_mapping = fake_truncate  # type: ignore[assignment]

        response = converter.workflow_node_finish_to_stream_response(
            event=event,
            task_id="test-task-id",
        )

        # Response should use original data
        assert response is not None
        assert response.data.process_data == original_data
        assert response.data.process_data_truncated is False

    def test_workflow_node_finish_response_with_none_process_data(self):
        """Test node finish response when process_data is None."""
        converter = self.create_workflow_response_converter()

        converter.workflow_start_to_stream_response(
            task_id="bootstrap",
            workflow_run_id="run-id",
            workflow_id="wf-id",
            reason=WorkflowStartReason.INITIAL,
        )
        start_event = self.create_node_started_event()
        converter.workflow_node_start_to_stream_response(
            event=start_event,
            task_id="test-task-id",
        )

        event = self.create_node_succeeded_event(
            node_execution_id=start_event.node_execution_id,
            process_data=None,
        )

        def fake_truncate(mapping):
            return mapping, False

        converter._truncator.truncate_variable_mapping = fake_truncate  # type: ignore[assignment]

        response = converter.workflow_node_finish_to_stream_response(
            event=event,
            task_id="test-task-id",
        )

        # Response should normalize missing process_data to an empty mapping
        assert response is not None
        assert response.data.process_data == {}
        assert response.data.process_data_truncated is False

    def test_workflow_node_retry_response_uses_truncated_process_data(self):
        """Test that node retry response uses get_response_process_data()."""
        converter = self.create_workflow_response_converter()

        original_data = {"large_field": "x" * 10000, "metadata": "info"}
        truncated_data = {"large_field": "[TRUNCATED]", "metadata": "info"}

        converter.workflow_start_to_stream_response(
            task_id="bootstrap",
            workflow_run_id="run-id",
            workflow_id="wf-id",
            reason=WorkflowStartReason.INITIAL,
        )
        start_event = self.create_node_started_event()
        converter.workflow_node_start_to_stream_response(
            event=start_event,
            task_id="test-task-id",
        )

        event = self.create_node_retry_event(
            node_execution_id=start_event.node_execution_id,
            process_data=original_data,
        )

        def fake_truncate(mapping):
            if mapping == dict(original_data):
                return truncated_data, True
            return mapping, False

        converter._truncator.truncate_variable_mapping = fake_truncate  # type: ignore[assignment]

        response = converter.workflow_node_retry_to_stream_response(
            event=event,
            task_id="test-task-id",
        )

        # Response should use truncated data, not original
        assert response is not None
        assert response.data.process_data == truncated_data
        assert response.data.process_data != original_data
        assert response.data.process_data_truncated is True

    def test_workflow_node_retry_response_without_truncation(self):
        """Test node retry response when no truncation is applied."""
        converter = self.create_workflow_response_converter()

        original_data = {"small": "data"}

        converter.workflow_start_to_stream_response(
            task_id="bootstrap",
            workflow_run_id="run-id",
            workflow_id="wf-id",
            reason=WorkflowStartReason.INITIAL,
        )
        start_event = self.create_node_started_event()
        converter.workflow_node_start_to_stream_response(
            event=start_event,
            task_id="test-task-id",
        )

        event = self.create_node_retry_event(
            node_execution_id=start_event.node_execution_id,
            process_data=original_data,
        )

        def fake_truncate(mapping):
            return mapping, False

        converter._truncator.truncate_variable_mapping = fake_truncate  # type: ignore[assignment]

        response = converter.workflow_node_retry_to_stream_response(
            event=event,
            task_id="test-task-id",
        )

        assert response is not None
        assert response.data.process_data == original_data
        assert response.data.process_data_truncated is False

    def test_iteration_and_loop_nodes_return_none(self):
        """Test that iteration and loop nodes return None (no streaming events)."""
        converter = self.create_workflow_response_converter()

        iteration_event = QueueNodeSucceededEvent(
            node_id="iteration-node",
            node_type=NodeType.ITERATION,
            node_execution_id=str(uuid.uuid4()),
            start_at=naive_utc_now(),
            in_iteration_id=None,
            in_loop_id=None,
            inputs={},
            process_data={},
            outputs={},
            execution_metadata={},
        )

        response = converter.workflow_node_finish_to_stream_response(
            event=iteration_event,
            task_id="test-task-id",
        )
        assert response is None

        loop_event = iteration_event.model_copy(update={"node_type": NodeType.LOOP})
        response = converter.workflow_node_finish_to_stream_response(
            event=loop_event,
            task_id="test-task-id",
        )
        assert response is None

    def test_finish_without_start_raises(self):
        """Ensure finish responses require a prior workflow start."""
        converter = self.create_workflow_response_converter()
        event = self.create_node_succeeded_event(
            node_execution_id=str(uuid.uuid4()),
            process_data={},
        )

        with pytest.raises(ValueError):
            converter.workflow_node_finish_to_stream_response(
                event=event,
                task_id="test-task-id",
            )


@dataclass
class TestCase:
    """Test case data for table-driven tests."""

    name: str
    invoke_from: InvokeFrom
    expected_truncation_enabled: bool
    description: str


class TestWorkflowResponseConverterServiceApiTruncation:
    """Test class for Service API truncation functionality in WorkflowResponseConverter."""

    def create_test_app_generate_entity(self, invoke_from: InvokeFrom) -> WorkflowAppGenerateEntity:
        """Create a test WorkflowAppGenerateEntity with specified invoke_from."""
        # Create a minimal WorkflowUIBasedAppConfig for testing
        app_config = WorkflowUIBasedAppConfig(
            tenant_id="test_tenant",
            app_id="test_app",
            app_mode=AppMode.WORKFLOW,
            workflow_id="test_workflow_id",
        )

        entity = WorkflowAppGenerateEntity(
            task_id="test_task_id",
            app_id="test_app_id",
            app_config=app_config,
            tenant_id="test_tenant",
            app_mode=AppMode.WORKFLOW,
            invoke_from=invoke_from,
            inputs={"test_input": "test_value"},
            user_id="test_user_id",
            stream=True,
            files=[],
            workflow_execution_id="test_workflow_exec_id",
        )
        return entity

    def create_test_user(self) -> Account:
        """Create a test user account."""
        account = Account(
            name="Test User",
            email="test@example.com",
        )
        # Manually set the ID for testing purposes
        account.id = "test_user_id"
        return account

    def create_test_system_variables(self) -> SystemVariable:
        """Create test system variables."""
        return SystemVariable()

    def create_test_converter(self, invoke_from: InvokeFrom) -> WorkflowResponseConverter:
        """Create WorkflowResponseConverter with specified invoke_from."""
        entity = self.create_test_app_generate_entity(invoke_from)
        user = self.create_test_user()
        system_variables = self.create_test_system_variables()

        converter = WorkflowResponseConverter(
            application_generate_entity=entity,
            user=user,
            system_variables=system_variables,
        )
        # ensure `workflow_run_id` is set.
        converter.workflow_start_to_stream_response(
            task_id="test-task-id",
            workflow_run_id="test-workflow-run-id",
            workflow_id="test-workflow-id",
            reason=WorkflowStartReason.INITIAL,
        )
        return converter

    @pytest.mark.parametrize(
        "test_case",
        [
            TestCase(
                name="service_api_truncation_disabled",
                invoke_from=InvokeFrom.SERVICE_API,
                expected_truncation_enabled=False,
                description="Service API calls should have truncation disabled",
            ),
            TestCase(
                name="web_app_truncation_enabled",
                invoke_from=InvokeFrom.WEB_APP,
                expected_truncation_enabled=True,
                description="Web app calls should have truncation enabled",
            ),
            TestCase(
                name="debugger_truncation_enabled",
                invoke_from=InvokeFrom.DEBUGGER,
                expected_truncation_enabled=True,
                description="Debugger calls should have truncation enabled",
            ),
            TestCase(
                name="explore_truncation_enabled",
                invoke_from=InvokeFrom.EXPLORE,
                expected_truncation_enabled=True,
                description="Explore calls should have truncation enabled",
            ),
            TestCase(
                name="published_pipeline_truncation_enabled",
                invoke_from=InvokeFrom.PUBLISHED_PIPELINE,
                expected_truncation_enabled=True,
                description="Published pipeline calls should have truncation enabled",
            ),
        ],
        ids=lambda x: x.name,
    )
    def test_truncator_selection_based_on_invoke_from(self, test_case: TestCase):
        """Test that the correct truncator is selected based on invoke_from."""
        converter = self.create_test_converter(test_case.invoke_from)

        # Test truncation behavior instead of checking private attribute

        # Create a test event with large data
        large_value = {"key": ["x"] * 2000}  # Large data that would be truncated

        event = QueueNodeSucceededEvent(
            node_execution_id="test_node_exec_id",
            node_id="test_node",
            node_type=NodeType.LLM,
            start_at=naive_utc_now(),
            inputs=large_value,
            process_data=large_value,
            outputs=large_value,
            error=None,
            execution_metadata=None,
            in_iteration_id=None,
            in_loop_id=None,
        )

        response = converter.workflow_node_finish_to_stream_response(
            event=event,
            task_id="test_task",
        )

        # Verify response is not None
        assert response is not None

        # Verify truncation behavior matches expectations
        if test_case.expected_truncation_enabled:
            # Truncation should be enabled for non-service-api calls
            assert response.data.inputs_truncated
            assert response.data.process_data_truncated
            assert response.data.outputs_truncated
        else:
            # SERVICE_API should not truncate
            assert not response.data.inputs_truncated
            assert not response.data.process_data_truncated
            assert not response.data.outputs_truncated

    def test_service_api_truncator_no_op_mapping(self):
        """Test that Service API truncator doesn't truncate variable mappings."""
        converter = self.create_test_converter(InvokeFrom.SERVICE_API)

        # Create a test event with large data
        large_value: dict[str, Any] = {
            "large_string": "x" * 10000,  # Large string
            "large_list": list(range(2000)),  # Large array
            "nested_data": {"deep_nested": {"very_deep": {"value": "x" * 5000}}},
        }

        event = QueueNodeSucceededEvent(
            node_execution_id="test_node_exec_id",
            node_id="test_node",
            node_type=NodeType.LLM,
            start_at=naive_utc_now(),
            inputs=large_value,
            process_data=large_value,
            outputs=large_value,
            error=None,
            execution_metadata=None,
            in_iteration_id=None,
            in_loop_id=None,
        )

        response = converter.workflow_node_finish_to_stream_response(
            event=event,
            task_id="test_task",
        )

        # Verify response is not None
        data = response.data
        assert data.inputs == large_value
        assert data.process_data == large_value
        assert data.outputs == large_value
        # Service API should not truncate
        assert data.inputs_truncated is False
        assert data.process_data_truncated is False
        assert data.outputs_truncated is False

    def test_web_app_truncator_works_normally(self):
        """Test that web app truncator still works normally."""
        converter = self.create_test_converter(InvokeFrom.WEB_APP)

        # Create a test event with large data
        large_value = {
            "large_string": "x" * 10000,  # Large string
            "large_list": list(range(2000)),  # Large array
        }

        event = QueueNodeSucceededEvent(
            node_execution_id="test_node_exec_id",
            node_id="test_node",
            node_type=NodeType.LLM,
            start_at=naive_utc_now(),
            inputs=large_value,
            process_data=large_value,
            outputs=large_value,
            error=None,
            execution_metadata=None,
            in_iteration_id=None,
            in_loop_id=None,
        )

        response = converter.workflow_node_finish_to_stream_response(
            event=event,
            task_id="test_task",
        )

        # Verify response is not None
        assert response is not None

        # Web app should truncate
        data = response.data
        assert data.inputs != large_value
        assert data.process_data != large_value
        assert data.outputs != large_value
        # The exact behavior depends on VariableTruncator implementation
        # Just verify that truncation flags are present
        assert data.inputs_truncated is True
        assert data.process_data_truncated is True
        assert data.outputs_truncated is True

    @staticmethod
    def _create_event_by_type(
        type_: QueueEvent, inputs: Mapping[str, Any], process_data: Mapping[str, Any], outputs: Mapping[str, Any]
    ) -> QueueNodeSucceededEvent | QueueNodeFailedEvent | QueueNodeExceptionEvent:
        if type_ == QueueEvent.NODE_SUCCEEDED:
            return QueueNodeSucceededEvent(
                node_execution_id="test_node_exec_id",
                node_id="test_node",
                node_type=NodeType.LLM,
                start_at=naive_utc_now(),
                inputs=inputs,
                process_data=process_data,
                outputs=outputs,
                error=None,
                execution_metadata=None,
                in_iteration_id=None,
                in_loop_id=None,
            )
        elif type_ == QueueEvent.NODE_FAILED:
            return QueueNodeFailedEvent(
                node_execution_id="test_node_exec_id",
                node_id="test_node",
                node_type=NodeType.LLM,
                start_at=naive_utc_now(),
                inputs=inputs,
                process_data=process_data,
                outputs=outputs,
                error="oops",
                execution_metadata=None,
                in_iteration_id=None,
                in_loop_id=None,
            )
        elif type_ == QueueEvent.NODE_EXCEPTION:
            return QueueNodeExceptionEvent(
                node_execution_id="test_node_exec_id",
                node_id="test_node",
                node_type=NodeType.LLM,
                start_at=naive_utc_now(),
                inputs=inputs,
                process_data=process_data,
                outputs=outputs,
                error="oops",
                execution_metadata=None,
                in_iteration_id=None,
                in_loop_id=None,
            )
        else:
            raise Exception("unknown type.")

    @pytest.mark.parametrize(
        "event_type",
        [
            QueueEvent.NODE_SUCCEEDED,
            QueueEvent.NODE_FAILED,
            QueueEvent.NODE_EXCEPTION,
        ],
    )
    def test_service_api_node_finish_event_no_truncation(self, event_type: QueueEvent):
        """Test that Service API doesn't truncate node finish events."""
        converter = self.create_test_converter(InvokeFrom.SERVICE_API)
        # Create test event with large data
        large_inputs = {"input1": "x" * 5000, "input2": list(range(2000))}
        large_process_data = {"process1": "y" * 5000, "process2": {"nested": ["z"] * 2000}}
        large_outputs = {"output1": "result" * 1000, "output2": list(range(2000))}

        event = TestWorkflowResponseConverterServiceApiTruncation._create_event_by_type(
            event_type, large_inputs, large_process_data, large_outputs
        )

        response = converter.workflow_node_finish_to_stream_response(
            event=event,
            task_id="test_task",
        )

        # Verify response is not None
        assert response is not None

        # Verify response contains full data (not truncated)
        assert response.data.inputs == large_inputs
        assert response.data.process_data == large_process_data
        assert response.data.outputs == large_outputs
        assert not response.data.inputs_truncated
        assert not response.data.process_data_truncated
        assert not response.data.outputs_truncated

    def test_service_api_node_retry_event_no_truncation(self):
        """Test that Service API doesn't truncate node retry events."""
        converter = self.create_test_converter(InvokeFrom.SERVICE_API)

        # Create test event with large data
        large_inputs = {"retry_input": "x" * 5000}
        large_process_data = {"retry_process": "y" * 5000}
        large_outputs = {"retry_output": "z" * 5000}

        # First, we need to store a snapshot by simulating a start event
        start_event = QueueNodeStartedEvent(
            node_execution_id="test_node_exec_id",
            node_id="test_node",
            node_type=NodeType.LLM,
            node_title="Test Node",
            node_run_index=1,
            start_at=naive_utc_now(),
            in_iteration_id=None,
            in_loop_id=None,
            agent_strategy=None,
            provider_type="plugin",
            provider_id="test/test_plugin",
        )
        converter.workflow_node_start_to_stream_response(event=start_event, task_id="test_task")

        # Now create retry event
        event = QueueNodeRetryEvent(
            node_execution_id="test_node_exec_id",
            node_id="test_node",
            node_type=NodeType.LLM,
            node_title="Test Node",
            node_run_index=1,
            start_at=naive_utc_now(),
            inputs=large_inputs,
            process_data=large_process_data,
            outputs=large_outputs,
            error="Retry error",
            execution_metadata=None,
            in_iteration_id=None,
            in_loop_id=None,
            retry_index=1,
            provider_type="plugin",
            provider_id="test/test_plugin",
        )

        response = converter.workflow_node_retry_to_stream_response(
            event=event,
            task_id="test_task",
        )

        # Verify response is not None
        assert response is not None

        # Verify response contains full data (not truncated)
        assert response.data.inputs == large_inputs
        assert response.data.process_data == large_process_data
        assert response.data.outputs == large_outputs
        assert not response.data.inputs_truncated
        assert not response.data.process_data_truncated
        assert not response.data.outputs_truncated

    def test_service_api_iteration_events_no_truncation(self):
        """Test that Service API doesn't truncate iteration events."""
        converter = self.create_test_converter(InvokeFrom.SERVICE_API)

        # Test iteration start event
        large_value = {"iteration_input": ["x"] * 2000}

        start_event = QueueIterationStartEvent(
            node_execution_id="test_iter_exec_id",
            node_id="test_iteration",
            node_type=NodeType.ITERATION,
            node_title="Test Iteration",
            node_run_index=0,
            start_at=naive_utc_now(),
            inputs=large_value,
            metadata={},
        )

        response = converter.workflow_iteration_start_to_stream_response(
            task_id="test_task",
            workflow_execution_id="test_workflow_exec_id",
            event=start_event,
        )

        assert response is not None
        assert response.data.inputs == large_value
        assert not response.data.inputs_truncated

    def test_service_api_loop_events_no_truncation(self):
        """Test that Service API doesn't truncate loop events."""
        converter = self.create_test_converter(InvokeFrom.SERVICE_API)

        # Test loop start event
        large_inputs = {"loop_input": ["x"] * 2000}

        start_event = QueueLoopStartEvent(
            node_execution_id="test_loop_exec_id",
            node_id="test_loop",
            node_type=NodeType.LOOP,
            node_title="Test Loop",
            start_at=naive_utc_now(),
            inputs=large_inputs,
            metadata={},
            node_run_index=0,
        )

        response = converter.workflow_loop_start_to_stream_response(
            task_id="test_task",
            workflow_execution_id="test_workflow_exec_id",
            event=start_event,
        )

        assert response is not None
        assert response.data.inputs == large_inputs
        assert not response.data.inputs_truncated

    def test_web_app_node_finish_event_truncation_works(self):
        """Test that web app still truncates node finish events."""
        converter = self.create_test_converter(InvokeFrom.WEB_APP)

        # Create test event with large data that should be truncated
        large_inputs = {"input1": ["x"] * 2000}
        large_process_data = {"process1": ["y"] * 2000}
        large_outputs = {"output1": ["z"] * 2000}

        event = QueueNodeSucceededEvent(
            node_execution_id="test_node_exec_id",
            node_id="test_node",
            node_type=NodeType.LLM,
            start_at=naive_utc_now(),
            inputs=large_inputs,
            process_data=large_process_data,
            outputs=large_outputs,
            error=None,
            execution_metadata=None,
            in_iteration_id=None,
            in_loop_id=None,
        )

        response = converter.workflow_node_finish_to_stream_response(
            event=event,
            task_id="test_task",
        )

        # Verify response is not None
        assert response is not None

        # Verify response contains truncated data
        # The exact behavior depends on VariableTruncator implementation
        # Just verify truncation flags are set correctly (may or may not be truncated depending on size)
        # At minimum, the truncation mechanism should work
        assert isinstance(response.data.inputs, dict)
        assert response.data.inputs_truncated
        assert isinstance(response.data.process_data, dict)
        assert response.data.process_data_truncated
        assert isinstance(response.data.outputs, dict)
        assert response.data.outputs_truncated
