feat(graph_engine): Support pausing workflow graph executions (#26585)

Signed-off-by: -LAN- <laipz8200@outlook.com>

api/core/app/apps/advanced_chat/app_generator.py

@@ -447,6 +447,8 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
                 "message_id": message.id,
                 "context": context,
                 "variable_loader": variable_loader,
+                "workflow_execution_repository": workflow_execution_repository,
+                "workflow_node_execution_repository": workflow_node_execution_repository,
             },
         )
 
@@ -466,8 +468,6 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             conversation=conversation,
             message=message,
             user=user,
-            workflow_execution_repository=workflow_execution_repository,
-            workflow_node_execution_repository=workflow_node_execution_repository,
             stream=stream,
             draft_var_saver_factory=self._get_draft_var_saver_factory(invoke_from, account=user),
         )
@@ -483,6 +483,8 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
         message_id: str,
         context: contextvars.Context,
         variable_loader: VariableLoader,
+        workflow_execution_repository: WorkflowExecutionRepository,
+        workflow_node_execution_repository: WorkflowNodeExecutionRepository,
     ):
         """
         Generate worker in a new thread.
@@ -538,6 +540,8 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
                 workflow=workflow,
                 system_user_id=system_user_id,
                 app=app,
+                workflow_execution_repository=workflow_execution_repository,
+                workflow_node_execution_repository=workflow_node_execution_repository,
             )
 
             try:
@@ -570,8 +574,6 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
         conversation: Conversation,
         message: Message,
         user: Union[Account, EndUser],
-        workflow_execution_repository: WorkflowExecutionRepository,
-        workflow_node_execution_repository: WorkflowNodeExecutionRepository,
         draft_var_saver_factory: DraftVariableSaverFactory,
         stream: bool = False,
     ) -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStreamResponse, None, None]]:
@@ -584,7 +586,6 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
         :param message: message
         :param user: account or end user
         :param stream: is stream
-        :param workflow_node_execution_repository: optional repository for workflow node execution
         :return:
         """
         # init generate task pipeline
@@ -596,8 +597,6 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             message=message,
             user=user,
             dialogue_count=self._dialogue_count,
-            workflow_execution_repository=workflow_execution_repository,
-            workflow_node_execution_repository=workflow_node_execution_repository,
             stream=stream,
             draft_var_saver_factory=draft_var_saver_factory,
         )

api/core/app/apps/advanced_chat/app_runner.py

@@ -23,8 +23,12 @@ from core.app.features.annotation_reply.annotation_reply import AnnotationReplyF
 from core.moderation.base import ModerationError
 from core.moderation.input_moderation import InputModeration
 from core.variables.variables import VariableUnion
-from core.workflow.entities import GraphRuntimeState, VariablePool
+from core.workflow.enums import WorkflowType
 from core.workflow.graph_engine.command_channels.redis_channel import RedisChannel
+from core.workflow.graph_engine.layers.persistence import PersistenceWorkflowInfo, WorkflowPersistenceLayer
+from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
+from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
+from core.workflow.runtime import GraphRuntimeState, VariablePool
 from core.workflow.system_variable import SystemVariable
 from core.workflow.variable_loader import VariableLoader
 from core.workflow.workflow_entry import WorkflowEntry
@@ -55,6 +59,8 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
         workflow: Workflow,
         system_user_id: str,
         app: App,
+        workflow_execution_repository: WorkflowExecutionRepository,
+        workflow_node_execution_repository: WorkflowNodeExecutionRepository,
     ):
         super().__init__(
             queue_manager=queue_manager,
@@ -68,11 +74,24 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
         self._workflow = workflow
         self.system_user_id = system_user_id
         self._app = app
+        self._workflow_execution_repository = workflow_execution_repository
+        self._workflow_node_execution_repository = workflow_node_execution_repository
 
     def run(self):
         app_config = self.application_generate_entity.app_config
         app_config = cast(AdvancedChatAppConfig, app_config)
 
+        system_inputs = SystemVariable(
+            query=self.application_generate_entity.query,
+            files=self.application_generate_entity.files,
+            conversation_id=self.conversation.id,
+            user_id=self.system_user_id,
+            dialogue_count=self._dialogue_count,
+            app_id=app_config.app_id,
+            workflow_id=app_config.workflow_id,
+            workflow_execution_id=self.application_generate_entity.workflow_run_id,
+        )
+
         with Session(db.engine, expire_on_commit=False) as session:
             app_record = session.scalar(select(App).where(App.id == app_config.app_id))
 
@@ -89,7 +108,6 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
         else:
             inputs = self.application_generate_entity.inputs
             query = self.application_generate_entity.query
-            files = self.application_generate_entity.files
 
             # moderation
             if self.handle_input_moderation(
@@ -114,17 +132,6 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
             conversation_variables = self._initialize_conversation_variables()
 
             # Create a variable pool.
-            system_inputs = SystemVariable(
-                query=query,
-                files=files,
-                conversation_id=self.conversation.id,
-                user_id=self.system_user_id,
-                dialogue_count=self._dialogue_count,
-                app_id=app_config.app_id,
-                workflow_id=app_config.workflow_id,
-                workflow_execution_id=self.application_generate_entity.workflow_run_id,
-            )
-
             # init variable pool
             variable_pool = VariablePool(
                 system_variables=system_inputs,
@@ -172,6 +179,23 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
             command_channel=command_channel,
         )
 
+        self._queue_manager.graph_runtime_state = graph_runtime_state
+
+        persistence_layer = WorkflowPersistenceLayer(
+            application_generate_entity=self.application_generate_entity,
+            workflow_info=PersistenceWorkflowInfo(
+                workflow_id=self._workflow.id,
+                workflow_type=WorkflowType(self._workflow.type),
+                version=self._workflow.version,
+                graph_data=self._workflow.graph_dict,
+            ),
+            workflow_execution_repository=self._workflow_execution_repository,
+            workflow_node_execution_repository=self._workflow_node_execution_repository,
+            trace_manager=self.application_generate_entity.trace_manager,
+        )
+
+        workflow_entry.graph_engine.layer(persistence_layer)
+
         generator = workflow_entry.run()
 
         for event in generator:

api/core/app/apps/advanced_chat/generate_task_pipeline.py

@@ -11,6 +11,7 @@ from sqlalchemy.orm import Session
 
 from constants.tts_auto_play_timeout import TTS_AUTO_PLAY_TIMEOUT, TTS_AUTO_PLAY_YIELD_CPU_TIME
 from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
+from core.app.apps.common.graph_runtime_state_support import GraphRuntimeStateSupport
 from core.app.apps.common.workflow_response_converter import WorkflowResponseConverter
 from core.app.entities.app_invoke_entities import (
     AdvancedChatAppGenerateEntity,
@@ -60,14 +61,11 @@ from core.app.task_pipeline.message_cycle_manager import MessageCycleManager
 from core.base.tts import AppGeneratorTTSPublisher, AudioTrunk
 from core.model_runtime.entities.llm_entities import LLMUsage
 from core.ops.ops_trace_manager import TraceQueueManager
-from core.workflow.entities import GraphRuntimeState
-from core.workflow.enums import WorkflowExecutionStatus, WorkflowType
+from core.workflow.enums import WorkflowExecutionStatus
 from core.workflow.nodes import NodeType
 from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory
-from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
-from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
+from core.workflow.runtime import GraphRuntimeState
 from core.workflow.system_variable import SystemVariable
-from core.workflow.workflow_cycle_manager import CycleManagerWorkflowInfo, WorkflowCycleManager
 from extensions.ext_database import db
 from libs.datetime_utils import naive_utc_now
 from models import Account, Conversation, EndUser, Message, MessageFile
@@ -77,7 +75,7 @@ from models.workflow import Workflow
 logger = logging.getLogger(__name__)
 
 
-class AdvancedChatAppGenerateTaskPipeline:
+class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
     """
     AdvancedChatAppGenerateTaskPipeline is a class that generate stream output and state management for Application.
     """
@@ -92,8 +90,6 @@ class AdvancedChatAppGenerateTaskPipeline:
         user: Union[Account, EndUser],
         stream: bool,
         dialogue_count: int,
-        workflow_execution_repository: WorkflowExecutionRepository,
-        workflow_node_execution_repository: WorkflowNodeExecutionRepository,
         draft_var_saver_factory: DraftVariableSaverFactory,
     ):
         self._base_task_pipeline = BasedGenerateTaskPipeline(
@@ -113,31 +109,20 @@ class AdvancedChatAppGenerateTaskPipeline:
         else:
             raise NotImplementedError(f"User type not supported: {type(user)}")
 
-        self._workflow_cycle_manager = WorkflowCycleManager(
-            application_generate_entity=application_generate_entity,
-            workflow_system_variables=SystemVariable(
-                query=message.query,
-                files=application_generate_entity.files,
-                conversation_id=conversation.id,
-                user_id=user_session_id,
-                dialogue_count=dialogue_count,
-                app_id=application_generate_entity.app_config.app_id,
-                workflow_id=workflow.id,
-                workflow_execution_id=application_generate_entity.workflow_run_id,
-            ),
-            workflow_info=CycleManagerWorkflowInfo(
-                workflow_id=workflow.id,
-                workflow_type=WorkflowType(workflow.type),
-                version=workflow.version,
-                graph_data=workflow.graph_dict,
-            ),
-            workflow_execution_repository=workflow_execution_repository,
-            workflow_node_execution_repository=workflow_node_execution_repository,
+        self._workflow_system_variables = SystemVariable(
+            query=message.query,
+            files=application_generate_entity.files,
+            conversation_id=conversation.id,
+            user_id=user_session_id,
+            dialogue_count=dialogue_count,
+            app_id=application_generate_entity.app_config.app_id,
+            workflow_id=workflow.id,
+            workflow_execution_id=application_generate_entity.workflow_run_id,
         )
-
         self._workflow_response_converter = WorkflowResponseConverter(
             application_generate_entity=application_generate_entity,
             user=user,
+            system_variables=self._workflow_system_variables,
         )
 
         self._task_state = WorkflowTaskState()
@@ -156,6 +141,8 @@ class AdvancedChatAppGenerateTaskPipeline:
         self._recorded_files: list[Mapping[str, Any]] = []
         self._workflow_run_id: str = ""
         self._draft_var_saver_factory = draft_var_saver_factory
+        self._graph_runtime_state: GraphRuntimeState | None = None
+        self._seed_graph_runtime_state_from_queue_manager()
 
     def process(self) -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStreamResponse, None, None]]:
         """
@@ -288,12 +275,6 @@ class AdvancedChatAppGenerateTaskPipeline:
         if not self._workflow_run_id:
             raise ValueError("workflow run not initialized.")
 
-    def _ensure_graph_runtime_initialized(self, graph_runtime_state: GraphRuntimeState | None) -> GraphRuntimeState:
-        """Fluent validation for graph runtime state."""
-        if not graph_runtime_state:
-            raise ValueError("graph runtime state not initialized.")
-        return graph_runtime_state
-
     def _handle_ping_event(self, event: QueuePingEvent, **kwargs) -> Generator[PingStreamResponse, None, None]:
         """Handle ping events."""
         yield self._base_task_pipeline.ping_stream_response()
@@ -304,21 +285,28 @@ class AdvancedChatAppGenerateTaskPipeline:
             err = self._base_task_pipeline.handle_error(event=event, session=session, message_id=self._message_id)
         yield self._base_task_pipeline.error_to_stream_response(err)
 
-    def _handle_workflow_started_event(self, *args, **kwargs) -> Generator[StreamResponse, None, None]:
+    def _handle_workflow_started_event(
+        self,
+        event: QueueWorkflowStartedEvent,
+        **kwargs,
+    ) -> Generator[StreamResponse, None, None]:
         """Handle workflow started events."""
-        with self._database_session() as session:
-            workflow_execution = self._workflow_cycle_manager.handle_workflow_run_start()
-            self._workflow_run_id = workflow_execution.id_
+        runtime_state = self._resolve_graph_runtime_state()
+        run_id = self._extract_workflow_run_id(runtime_state)
+        self._workflow_run_id = run_id
 
+        with self._database_session() as session:
             message = self._get_message(session=session)
             if not message:
                 raise ValueError(f"Message not found: {self._message_id}")
 
-            message.workflow_run_id = workflow_execution.id_
-            workflow_start_resp = self._workflow_response_converter.workflow_start_to_stream_response(
-                task_id=self._application_generate_entity.task_id,
-                workflow_execution=workflow_execution,
-            )
+            message.workflow_run_id = run_id
+
+        workflow_start_resp = self._workflow_response_converter.workflow_start_to_stream_response(
+            task_id=self._application_generate_entity.task_id,
+            workflow_run_id=run_id,
+            workflow_id=self._workflow_id,
+        )
 
         yield workflow_start_resp
 
@@ -326,13 +314,9 @@ class AdvancedChatAppGenerateTaskPipeline:
         """Handle node retry events."""
         self._ensure_workflow_initialized()
 
-        workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_retried(
-            workflow_execution_id=self._workflow_run_id, event=event
-        )
         node_retry_resp = self._workflow_response_converter.workflow_node_retry_to_stream_response(
             event=event,
             task_id=self._application_generate_entity.task_id,
-            workflow_node_execution=workflow_node_execution,
         )
 
         if node_retry_resp:
@@ -344,14 +328,9 @@ class AdvancedChatAppGenerateTaskPipeline:
         """Handle node started events."""
         self._ensure_workflow_initialized()
 
-        workflow_node_execution = self._workflow_cycle_manager.handle_node_execution_start(
-            workflow_execution_id=self._workflow_run_id, event=event
-        )
-
         node_start_resp = self._workflow_response_converter.workflow_node_start_to_stream_response(
             event=event,
             task_id=self._application_generate_entity.task_id,
-            workflow_node_execution=workflow_node_execution,
         )
 
         if node_start_resp:
@@ -367,14 +346,12 @@ class AdvancedChatAppGenerateTaskPipeline:
                 self._workflow_response_converter.fetch_files_from_node_outputs(event.outputs or {})
             )
 
-        workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_success(event=event)
         node_finish_resp = self._workflow_response_converter.workflow_node_finish_to_stream_response(
             event=event,
             task_id=self._application_generate_entity.task_id,
-            workflow_node_execution=workflow_node_execution,
         )
 
-        self._save_output_for_event(event, workflow_node_execution.id)
+        self._save_output_for_event(event, event.node_execution_id)
 
         if node_finish_resp:
             yield node_finish_resp
@@ -385,16 +362,13 @@ class AdvancedChatAppGenerateTaskPipeline:
         **kwargs,
     ) -> Generator[StreamResponse, None, None]:
         """Handle various node failure events."""
-        workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_failed(event=event)
-
         node_finish_resp = self._workflow_response_converter.workflow_node_finish_to_stream_response(
             event=event,
             task_id=self._application_generate_entity.task_id,
-            workflow_node_execution=workflow_node_execution,
         )
 
         if isinstance(event, QueueNodeExceptionEvent):
-            self._save_output_for_event(event, workflow_node_execution.id)
+            self._save_output_for_event(event, event.node_execution_id)
 
         if node_finish_resp:
             yield node_finish_resp
@@ -504,29 +478,19 @@ class AdvancedChatAppGenerateTaskPipeline:
         self,
         event: QueueWorkflowSucceededEvent,
         *,
-        graph_runtime_state: GraphRuntimeState | None = None,
         trace_manager: TraceQueueManager | None = None,
         **kwargs,
     ) -> Generator[StreamResponse, None, None]:
         """Handle workflow succeeded events."""
+        _ = trace_manager
         self._ensure_workflow_initialized()
-        validated_state = self._ensure_graph_runtime_initialized(graph_runtime_state)
-
-        with self._database_session() as session:
-            workflow_execution = self._workflow_cycle_manager.handle_workflow_run_success(
-                workflow_run_id=self._workflow_run_id,
-                total_tokens=validated_state.total_tokens,
-                total_steps=validated_state.node_run_steps,
-                outputs=event.outputs,
-                conversation_id=self._conversation_id,
-                trace_manager=trace_manager,
-                external_trace_id=self._application_generate_entity.extras.get("external_trace_id"),
-            )
-            workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
-                session=session,
-                task_id=self._application_generate_entity.task_id,
-                workflow_execution=workflow_execution,
-            )
+        validated_state = self._ensure_graph_runtime_initialized()
+        workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
+            task_id=self._application_generate_entity.task_id,
+            workflow_id=self._workflow_id,
+            status=WorkflowExecutionStatus.SUCCEEDED,
+            graph_runtime_state=validated_state,
+        )
 
         yield workflow_finish_resp
         self._base_task_pipeline.queue_manager.publish(QueueAdvancedChatMessageEndEvent(), PublishFrom.TASK_PIPELINE)
@@ -535,30 +499,20 @@ class AdvancedChatAppGenerateTaskPipeline:
         self,
         event: QueueWorkflowPartialSuccessEvent,
         *,
-        graph_runtime_state: GraphRuntimeState | None = None,
         trace_manager: TraceQueueManager | None = None,
         **kwargs,
     ) -> Generator[StreamResponse, None, None]:
         """Handle workflow partial success events."""
+        _ = trace_manager
         self._ensure_workflow_initialized()
-        validated_state = self._ensure_graph_runtime_initialized(graph_runtime_state)
-
-        with self._database_session() as session:
-            workflow_execution = self._workflow_cycle_manager.handle_workflow_run_partial_success(
-                workflow_run_id=self._workflow_run_id,
-                total_tokens=validated_state.total_tokens,
-                total_steps=validated_state.node_run_steps,
-                outputs=event.outputs,
-                exceptions_count=event.exceptions_count,
-                conversation_id=self._conversation_id,
-                trace_manager=trace_manager,
-                external_trace_id=self._application_generate_entity.extras.get("external_trace_id"),
-            )
-            workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
-                session=session,
-                task_id=self._application_generate_entity.task_id,
-                workflow_execution=workflow_execution,
-            )
+        validated_state = self._ensure_graph_runtime_initialized()
+        workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
+            task_id=self._application_generate_entity.task_id,
+            workflow_id=self._workflow_id,
+            status=WorkflowExecutionStatus.PARTIAL_SUCCEEDED,
+            graph_runtime_state=validated_state,
+            exceptions_count=event.exceptions_count,
+        )
 
         yield workflow_finish_resp
         self._base_task_pipeline.queue_manager.publish(QueueAdvancedChatMessageEndEvent(), PublishFrom.TASK_PIPELINE)
@@ -567,32 +521,25 @@ class AdvancedChatAppGenerateTaskPipeline:
         self,
         event: QueueWorkflowFailedEvent,
         *,
-        graph_runtime_state: GraphRuntimeState | None = None,
         trace_manager: TraceQueueManager | None = None,
         **kwargs,
     ) -> Generator[StreamResponse, None, None]:
         """Handle workflow failed events."""
+        _ = trace_manager
         self._ensure_workflow_initialized()
-        validated_state = self._ensure_graph_runtime_initialized(graph_runtime_state)
+        validated_state = self._ensure_graph_runtime_initialized()
+
+        workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
+            task_id=self._application_generate_entity.task_id,
+            workflow_id=self._workflow_id,
+            status=WorkflowExecutionStatus.FAILED,
+            graph_runtime_state=validated_state,
+            error=event.error,
+            exceptions_count=event.exceptions_count,
+        )
 
         with self._database_session() as session:
-            workflow_execution = self._workflow_cycle_manager.handle_workflow_run_failed(
-                workflow_run_id=self._workflow_run_id,
-                total_tokens=validated_state.total_tokens,
-                total_steps=validated_state.node_run_steps,
-                status=WorkflowExecutionStatus.FAILED,
-                error_message=event.error,
-                conversation_id=self._conversation_id,
-                trace_manager=trace_manager,
-                exceptions_count=event.exceptions_count,
-                external_trace_id=self._application_generate_entity.extras.get("external_trace_id"),
-            )
-            workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
-                session=session,
-                task_id=self._application_generate_entity.task_id,
-                workflow_execution=workflow_execution,
-            )
-            err_event = QueueErrorEvent(error=ValueError(f"Run failed: {workflow_execution.error_message}"))
+            err_event = QueueErrorEvent(error=ValueError(f"Run failed: {event.error}"))
             err = self._base_task_pipeline.handle_error(event=err_event, session=session, message_id=self._message_id)
 
         yield workflow_finish_resp
@@ -607,25 +554,23 @@ class AdvancedChatAppGenerateTaskPipeline:
         **kwargs,
     ) -> Generator[StreamResponse, None, None]:
         """Handle stop events."""
-        if self._workflow_run_id and graph_runtime_state:
+        _ = trace_manager
+        resolved_state = None
+        if self._workflow_run_id:
+            resolved_state = self._resolve_graph_runtime_state(graph_runtime_state)
+
+        if self._workflow_run_id and resolved_state:
+            workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
+                task_id=self._application_generate_entity.task_id,
+                workflow_id=self._workflow_id,
+                status=WorkflowExecutionStatus.STOPPED,
+                graph_runtime_state=resolved_state,
+                error=event.get_stop_reason(),
+            )
+
             with self._database_session() as session:
-                workflow_execution = self._workflow_cycle_manager.handle_workflow_run_failed(
-                    workflow_run_id=self._workflow_run_id,
-                    total_tokens=graph_runtime_state.total_tokens,
-                    total_steps=graph_runtime_state.node_run_steps,
-                    status=WorkflowExecutionStatus.STOPPED,
-                    error_message=event.get_stop_reason(),
-                    conversation_id=self._conversation_id,
-                    trace_manager=trace_manager,
-                    external_trace_id=self._application_generate_entity.extras.get("external_trace_id"),
-                )
-                workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
-                    session=session,
-                    task_id=self._application_generate_entity.task_id,
-                    workflow_execution=workflow_execution,
-                )
                 # Save message
-                self._save_message(session=session, graph_runtime_state=graph_runtime_state)
+                self._save_message(session=session, graph_runtime_state=resolved_state)
 
             yield workflow_finish_resp
         elif event.stopped_by in (
@@ -647,7 +592,7 @@ class AdvancedChatAppGenerateTaskPipeline:
         **kwargs,
     ) -> Generator[StreamResponse, None, None]:
         """Handle advanced chat message end events."""
-        self._ensure_graph_runtime_initialized(graph_runtime_state)
+        resolved_state = self._ensure_graph_runtime_initialized(graph_runtime_state)
 
         output_moderation_answer = self._base_task_pipeline.handle_output_moderation_when_task_finished(
             self._task_state.answer
@@ -661,7 +606,7 @@ class AdvancedChatAppGenerateTaskPipeline:
 
         # Save message
         with self._database_session() as session:
-            self._save_message(session=session, graph_runtime_state=graph_runtime_state)
+            self._save_message(session=session, graph_runtime_state=resolved_state)
 
         yield self._message_end_to_stream_response()
 
@@ -670,10 +615,6 @@ class AdvancedChatAppGenerateTaskPipeline:
     ) -> Generator[StreamResponse, None, None]:
         """Handle retriever resources events."""
         self._message_cycle_manager.handle_retriever_resources(event)
-
-        with self._database_session() as session:
-            message = self._get_message(session=session)
-            message.message_metadata = self._task_state.metadata.model_dump_json()
         return
         yield  # Make this a generator
 
@@ -682,10 +623,6 @@ class AdvancedChatAppGenerateTaskPipeline:
     ) -> Generator[StreamResponse, None, None]:
         """Handle annotation reply events."""
         self._message_cycle_manager.handle_annotation_reply(event)
-
-        with self._database_session() as session:
-            message = self._get_message(session=session)
-            message.message_metadata = self._task_state.metadata.model_dump_json()
         return
         yield  # Make this a generator
 
@@ -739,7 +676,6 @@ class AdvancedChatAppGenerateTaskPipeline:
         self,
         event: Any,
         *,
-        graph_runtime_state: GraphRuntimeState | None = None,
         tts_publisher: AppGeneratorTTSPublisher | None = None,
         trace_manager: TraceQueueManager | None = None,
         queue_message: Union[WorkflowQueueMessage, MessageQueueMessage] | None = None,
@@ -752,7 +688,6 @@ class AdvancedChatAppGenerateTaskPipeline:
         if handler := handlers.get(event_type):
             yield from handler(
                 event,
-                graph_runtime_state=graph_runtime_state,
                 tts_publisher=tts_publisher,
                 trace_manager=trace_manager,
                 queue_message=queue_message,
@@ -769,7 +704,6 @@ class AdvancedChatAppGenerateTaskPipeline:
         ):
             yield from self._handle_node_failed_events(
                 event,
-                graph_runtime_state=graph_runtime_state,
                 tts_publisher=tts_publisher,
                 trace_manager=trace_manager,
                 queue_message=queue_message,
@@ -788,15 +722,12 @@ class AdvancedChatAppGenerateTaskPipeline:
         Process stream response using elegant Fluent Python patterns.
         Maintains exact same functionality as original 57-if-statement version.
         """
-        # Initialize graph runtime state
-        graph_runtime_state: GraphRuntimeState | None = None
-
         for queue_message in self._base_task_pipeline.queue_manager.listen():
             event = queue_message.event
 
             match event:
                 case QueueWorkflowStartedEvent():
-                    graph_runtime_state = event.graph_runtime_state
+                    self._resolve_graph_runtime_state()
                     yield from self._handle_workflow_started_event(event)
 
                 case QueueErrorEvent():
@@ -804,15 +735,11 @@ class AdvancedChatAppGenerateTaskPipeline:
                     break
 
                 case QueueWorkflowFailedEvent():
-                    yield from self._handle_workflow_failed_event(
-                        event, graph_runtime_state=graph_runtime_state, trace_manager=trace_manager
-                    )
+                    yield from self._handle_workflow_failed_event(event, trace_manager=trace_manager)
                     break
 
                 case QueueStopEvent():
-                    yield from self._handle_stop_event(
-                        event, graph_runtime_state=graph_runtime_state, trace_manager=trace_manager
-                    )
+                    yield from self._handle_stop_event(event, graph_runtime_state=None, trace_manager=trace_manager)
                     break
 
                 # Handle all other events through elegant dispatch
@@ -820,7 +747,6 @@ class AdvancedChatAppGenerateTaskPipeline:
                     if responses := list(
                         self._dispatch_event(
                             event,
-                            graph_runtime_state=graph_runtime_state,
                             tts_publisher=tts_publisher,
                             trace_manager=trace_manager,
                             queue_message=queue_message,
@@ -878,6 +804,12 @@ class AdvancedChatAppGenerateTaskPipeline:
         else:
             self._task_state.metadata.usage = LLMUsage.empty_usage()
 
+    def _seed_graph_runtime_state_from_queue_manager(self) -> None:
+        """Bootstrap the cached runtime state from the queue manager when present."""
+        candidate = self._base_task_pipeline.queue_manager.graph_runtime_state
+        if candidate is not None:
+            self._graph_runtime_state = candidate
+
     def _message_end_to_stream_response(self) -> MessageEndStreamResponse:
         """
         Message end to stream response.

api/core/app/apps/base_app_queue_manager.py

@@ -20,6 +20,7 @@ from core.app.entities.queue_entities import (
     QueueStopEvent,
     WorkflowQueueMessage,
 )
+from core.workflow.runtime import GraphRuntimeState
 from extensions.ext_redis import redis_client
 
 logger = logging.getLogger(__name__)
@@ -47,6 +48,7 @@ class AppQueueManager:
         q: queue.Queue[WorkflowQueueMessage | MessageQueueMessage | None] = queue.Queue()
 
         self._q = q
+        self._graph_runtime_state: GraphRuntimeState | None = None
         self._stopped_cache: TTLCache[tuple, bool] = TTLCache(maxsize=1, ttl=1)
         self._cache_lock = threading.Lock()
 
@@ -109,6 +111,16 @@ class AppQueueManager:
         """
         self.publish(QueueErrorEvent(error=e), pub_from)
 
+    @property
+    def graph_runtime_state(self) -> GraphRuntimeState | None:
+        """Retrieve the attached graph runtime state, if available."""
+        return self._graph_runtime_state
+
+    @graph_runtime_state.setter
+    def graph_runtime_state(self, graph_runtime_state: GraphRuntimeState | None) -> None:
+        """Attach the live graph runtime state reference for downstream consumers."""
+        self._graph_runtime_state = graph_runtime_state
+
     def publish(self, event: AppQueueEvent, pub_from: PublishFrom):
         """
         Publish event to queue

api/core/app/apps/common/graph_runtime_state_support.py

@@ -0,0 +1,55 @@
+"""Shared helpers for managing GraphRuntimeState across task pipelines."""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+from core.workflow.runtime import GraphRuntimeState
+
+if TYPE_CHECKING:
+    from core.app.task_pipeline.based_generate_task_pipeline import BasedGenerateTaskPipeline
+
+
+class GraphRuntimeStateSupport:
+    """
+    Mixin that centralises common GraphRuntimeState access patterns used by task pipelines.
+
+    Subclasses are expected to provide:
+      * `_base_task_pipeline` – exposing the queue manager with an optional cached runtime state.
+      * `_graph_runtime_state` attribute used as the local cache for the runtime state.
+    """
+
+    _base_task_pipeline: BasedGenerateTaskPipeline
+    _graph_runtime_state: GraphRuntimeState | None = None
+
+    def _ensure_graph_runtime_initialized(
+        self,
+        graph_runtime_state: GraphRuntimeState | None = None,
+    ) -> GraphRuntimeState:
+        """Validate and return the active graph runtime state."""
+        return self._resolve_graph_runtime_state(graph_runtime_state)
+
+    def _extract_workflow_run_id(self, graph_runtime_state: GraphRuntimeState) -> str:
+        system_variables = graph_runtime_state.variable_pool.system_variables
+        if not system_variables or not system_variables.workflow_execution_id:
+            raise ValueError("workflow_execution_id missing from runtime state")
+        return str(system_variables.workflow_execution_id)
+
+    def _resolve_graph_runtime_state(
+        self,
+        graph_runtime_state: GraphRuntimeState | None = None,
+    ) -> GraphRuntimeState:
+        """Return the cached runtime state or bootstrap it from the queue manager."""
+        if graph_runtime_state is not None:
+            self._graph_runtime_state = graph_runtime_state
+            return graph_runtime_state
+
+        if self._graph_runtime_state is None:
+            candidate = self._base_task_pipeline.queue_manager.graph_runtime_state
+            if candidate is not None:
+                self._graph_runtime_state = candidate
+
+        if self._graph_runtime_state is None:
+            raise ValueError("graph runtime state not initialized.")
+
+        return self._graph_runtime_state

api/core/app/apps/common/workflow_response_converter.py

@@ -1,9 +1,8 @@
 import time
 from collections.abc import Mapping, Sequence
-from datetime import UTC, datetime
-from typing import Any, Union
-
-from sqlalchemy.orm import Session
+from dataclasses import dataclass
+from datetime import datetime
+from typing import Any, NewType, Union
 
 from core.app.entities.app_invoke_entities import AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity
 from core.app.entities.queue_entities import (
@@ -39,16 +38,36 @@ from core.plugin.impl.datasource import PluginDatasourceManager
 from core.tools.entities.tool_entities import ToolProviderType
 from core.tools.tool_manager import ToolManager
 from core.variables.segments import ArrayFileSegment, FileSegment, Segment
-from core.workflow.entities import WorkflowExecution, WorkflowNodeExecution
-from core.workflow.enums import NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import (
+    NodeType,
+    SystemVariableKey,
+    WorkflowExecutionStatus,
+    WorkflowNodeExecutionMetadataKey,
+    WorkflowNodeExecutionStatus,
+)
+from core.workflow.runtime import GraphRuntimeState
+from core.workflow.system_variable import SystemVariable
+from core.workflow.workflow_entry import WorkflowEntry
 from core.workflow.workflow_type_encoder import WorkflowRuntimeTypeConverter
 from libs.datetime_utils import naive_utc_now
-from models import (
-    Account,
-    EndUser,
-)
+from models import Account, EndUser
 from services.variable_truncator import VariableTruncator
 
+NodeExecutionId = NewType("NodeExecutionId", str)
+
+
+@dataclass(slots=True)
+class _NodeSnapshot:
+    """In-memory cache for node metadata between start and completion events."""
+
+    title: str
+    index: int
+    start_at: datetime
+    iteration_id: str = ""
+    """Empty string means the node is not executing inside an iteration."""
+    loop_id: str = ""
+    """Empty string means the node is not executing inside a loop."""
+
 
 class WorkflowResponseConverter:
     def __init__(
@@ -56,37 +75,151 @@ class WorkflowResponseConverter:
         *,
         application_generate_entity: Union[AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity],
         user: Union[Account, EndUser],
+        system_variables: SystemVariable,
     ):
         self._application_generate_entity = application_generate_entity
         self._user = user
+        self._system_variables = system_variables
+        self._workflow_inputs = self._prepare_workflow_inputs()
         self._truncator = VariableTruncator.default()
+        self._node_snapshots: dict[NodeExecutionId, _NodeSnapshot] = {}
+        self._workflow_execution_id: str | None = None
+        self._workflow_started_at: datetime | None = None
+
+    # ------------------------------------------------------------------
+    # Workflow lifecycle helpers
+    # ------------------------------------------------------------------
+    def _prepare_workflow_inputs(self) -> Mapping[str, Any]:
+        inputs = dict(self._application_generate_entity.inputs)
+        for field_name, value in self._system_variables.to_dict().items():
+            # TODO(@future-refactor): store system variables separately from user inputs so we don't
+            # need to flatten `sys.*` entries into the input payload just for rerun/export tooling.
+            if field_name == SystemVariableKey.CONVERSATION_ID:
+                # Conversation IDs are session-scoped; omitting them keeps workflow inputs
+                # reusable without pinning new runs to a prior conversation.
+                continue
+            inputs[f"sys.{field_name}"] = value
+        handled = WorkflowEntry.handle_special_values(inputs)
+        return dict(handled or {})
+
+    def _ensure_workflow_run_id(self, workflow_run_id: str | None = None) -> str:
+        """Return the memoized workflow run id, optionally seeding it during start events."""
+        if workflow_run_id is not None:
+            self._workflow_execution_id = workflow_run_id
+        if not self._workflow_execution_id:
+            raise ValueError("workflow_run_id missing before streaming workflow events")
+        return self._workflow_execution_id
+
+    # ------------------------------------------------------------------
+    # Node snapshot helpers
+    # ------------------------------------------------------------------
+    def _store_snapshot(self, event: QueueNodeStartedEvent) -> _NodeSnapshot:
+        snapshot = _NodeSnapshot(
+            title=event.node_title,
+            index=event.node_run_index,
+            start_at=event.start_at,
+            iteration_id=event.in_iteration_id or "",
+            loop_id=event.in_loop_id or "",
+        )
+        node_execution_id = NodeExecutionId(event.node_execution_id)
+        self._node_snapshots[node_execution_id] = snapshot
+        return snapshot
+
+    def _get_snapshot(self, node_execution_id: str) -> _NodeSnapshot | None:
+        return self._node_snapshots.get(NodeExecutionId(node_execution_id))
+
+    def _pop_snapshot(self, node_execution_id: str) -> _NodeSnapshot | None:
+        return self._node_snapshots.pop(NodeExecutionId(node_execution_id), None)
+
+    @staticmethod
+    def _merge_metadata(
+        base_metadata: Mapping[WorkflowNodeExecutionMetadataKey, Any] | None,
+        snapshot: _NodeSnapshot | None,
+    ) -> Mapping[WorkflowNodeExecutionMetadataKey, Any] | None:
+        if not base_metadata and not snapshot:
+            return base_metadata
+
+        merged: dict[WorkflowNodeExecutionMetadataKey, Any] = {}
+        if base_metadata:
+            merged.update(base_metadata)
+
+        if snapshot:
+            if snapshot.iteration_id:
+                merged[WorkflowNodeExecutionMetadataKey.ITERATION_ID] = snapshot.iteration_id
+            if snapshot.loop_id:
+                merged[WorkflowNodeExecutionMetadataKey.LOOP_ID] = snapshot.loop_id
+
+        return merged or None
+
+    def _truncate_mapping(
+        self,
+        mapping: Mapping[str, Any] | None,
+    ) -> tuple[Mapping[str, Any] | None, bool]:
+        if mapping is None:
+            return None, False
+        if not mapping:
+            return {}, False
+
+        normalized = WorkflowEntry.handle_special_values(dict(mapping))
+        if normalized is None:
+            return None, False
+
+        truncated, is_truncated = self._truncator.truncate_variable_mapping(dict(normalized))
+        return truncated, is_truncated
+
+    @staticmethod
+    def _encode_outputs(outputs: Mapping[str, Any] | None) -> Mapping[str, Any] | None:
+        if outputs is None:
+            return None
+        converter = WorkflowRuntimeTypeConverter()
+        return converter.to_json_encodable(outputs)
 
     def workflow_start_to_stream_response(
         self,
         *,
         task_id: str,
-        workflow_execution: WorkflowExecution,
+        workflow_run_id: str,
+        workflow_id: str,
     ) -> WorkflowStartStreamResponse:
+        run_id = self._ensure_workflow_run_id(workflow_run_id)
+        started_at = naive_utc_now()
+        self._workflow_started_at = started_at
+
         return WorkflowStartStreamResponse(
             task_id=task_id,
-            workflow_run_id=workflow_execution.id_,
+            workflow_run_id=run_id,
             data=WorkflowStartStreamResponse.Data(
-                id=workflow_execution.id_,
-                workflow_id=workflow_execution.workflow_id,
-                inputs=workflow_execution.inputs,
-                created_at=int(workflow_execution.started_at.timestamp()),
+                id=run_id,
+                workflow_id=workflow_id,
+                inputs=self._workflow_inputs,
+                created_at=int(started_at.timestamp()),
             ),
         )
 
     def workflow_finish_to_stream_response(
         self,
         *,
-        session: Session,
         task_id: str,
-        workflow_execution: WorkflowExecution,
+        workflow_id: str,
+        status: WorkflowExecutionStatus,
+        graph_runtime_state: GraphRuntimeState,
+        error: str | None = None,
+        exceptions_count: int = 0,
     ) -> WorkflowFinishStreamResponse:
-        created_by = None
+        run_id = self._ensure_workflow_run_id()
+        started_at = self._workflow_started_at
+        if started_at is None:
+            raise ValueError(
+                "workflow_finish_to_stream_response called before workflow_start_to_stream_response",
+            )
 
+        finished_at = naive_utc_now()
+        elapsed_time = (finished_at - started_at).total_seconds()
+
+        outputs_mapping = graph_runtime_state.outputs or {}
+        encoded_outputs = WorkflowRuntimeTypeConverter().to_json_encodable(outputs_mapping)
+
+        created_by: Mapping[str, object] | None
         user = self._user
         if isinstance(user, Account):
             created_by = {
@@ -94,38 +227,29 @@ class WorkflowResponseConverter:
                 "name": user.name,
                 "email": user.email,
             }
-        elif isinstance(user, EndUser):
+        else:
             created_by = {
                 "id": user.id,
                 "user": user.session_id,
             }
-        else:
-            raise NotImplementedError(f"User type not supported: {type(user)}")
-
-        # Handle the case where finished_at is None by using current time as default
-        finished_at_timestamp = (
-            int(workflow_execution.finished_at.timestamp())
-            if workflow_execution.finished_at
-            else int(datetime.now(UTC).timestamp())
-        )
 
         return WorkflowFinishStreamResponse(
             task_id=task_id,
-            workflow_run_id=workflow_execution.id_,
+            workflow_run_id=run_id,
             data=WorkflowFinishStreamResponse.Data(
-                id=workflow_execution.id_,
-                workflow_id=workflow_execution.workflow_id,
-                status=workflow_execution.status,
-                outputs=WorkflowRuntimeTypeConverter().to_json_encodable(workflow_execution.outputs),
-                error=workflow_execution.error_message,
-                elapsed_time=workflow_execution.elapsed_time,
-                total_tokens=workflow_execution.total_tokens,
-                total_steps=workflow_execution.total_steps,
+                id=run_id,
+                workflow_id=workflow_id,
+                status=status.value,
+                outputs=encoded_outputs,
+                error=error,
+                elapsed_time=elapsed_time,
+                total_tokens=graph_runtime_state.total_tokens,
+                total_steps=graph_runtime_state.node_run_steps,
                 created_by=created_by,
-                created_at=int(workflow_execution.started_at.timestamp()),
-                finished_at=finished_at_timestamp,
-                files=self.fetch_files_from_node_outputs(workflow_execution.outputs),
-                exceptions_count=workflow_execution.exceptions_count,
+                created_at=int(started_at.timestamp()),
+                finished_at=int(finished_at.timestamp()),
+                files=self.fetch_files_from_node_outputs(outputs_mapping),
+                exceptions_count=exceptions_count,
             ),
         )
 
@@ -134,38 +258,28 @@ class WorkflowResponseConverter:
         *,
         event: QueueNodeStartedEvent,
         task_id: str,
-        workflow_node_execution: WorkflowNodeExecution,
     ) -> NodeStartStreamResponse | None:
-        if workflow_node_execution.node_type in {NodeType.ITERATION, NodeType.LOOP}:
-            return None
-        if not workflow_node_execution.workflow_execution_id:
+        if event.node_type in {NodeType.ITERATION, NodeType.LOOP}:
             return None
+        run_id = self._ensure_workflow_run_id()
+        snapshot = self._store_snapshot(event)
 
         response = NodeStartStreamResponse(
             task_id=task_id,
-            workflow_run_id=workflow_node_execution.workflow_execution_id,
+            workflow_run_id=run_id,
             data=NodeStartStreamResponse.Data(
-                id=workflow_node_execution.id,
-                node_id=workflow_node_execution.node_id,
-                node_type=workflow_node_execution.node_type,
-                title=workflow_node_execution.title,
-                index=workflow_node_execution.index,
-                predecessor_node_id=workflow_node_execution.predecessor_node_id,
-                inputs=workflow_node_execution.get_response_inputs(),
-                inputs_truncated=workflow_node_execution.inputs_truncated,
-                created_at=int(workflow_node_execution.created_at.timestamp()),
-                parallel_id=event.parallel_id,
-                parallel_start_node_id=event.parallel_start_node_id,
-                parent_parallel_id=event.parent_parallel_id,
-                parent_parallel_start_node_id=event.parent_parallel_start_node_id,
+                id=event.node_execution_id,
+                node_id=event.node_id,
+                node_type=event.node_type,
+                title=snapshot.title,
+                index=snapshot.index,
+                created_at=int(snapshot.start_at.timestamp()),
                 iteration_id=event.in_iteration_id,
                 loop_id=event.in_loop_id,
-                parallel_run_id=event.parallel_mode_run_id,
                 agent_strategy=event.agent_strategy,
             ),
         )
 
-        # extras logic
         if event.node_type == NodeType.TOOL:
             response.data.extras["icon"] = ToolManager.get_tool_icon(
                 tenant_id=self._application_generate_entity.app_config.tenant_id,
@@ -189,41 +303,54 @@ class WorkflowResponseConverter:
         *,
         event: QueueNodeSucceededEvent | QueueNodeFailedEvent | QueueNodeExceptionEvent,
         task_id: str,
-        workflow_node_execution: WorkflowNodeExecution,
     ) -> NodeFinishStreamResponse | None:
-        if workflow_node_execution.node_type in {NodeType.ITERATION, NodeType.LOOP}:
-            return None
-        if not workflow_node_execution.workflow_execution_id:
-            return None
-        if not workflow_node_execution.finished_at:
+        if event.node_type in {NodeType.ITERATION, NodeType.LOOP}:
             return None
+        run_id = self._ensure_workflow_run_id()
+        snapshot = self._pop_snapshot(event.node_execution_id)
 
-        json_converter = WorkflowRuntimeTypeConverter()
+        start_at = snapshot.start_at if snapshot else event.start_at
+        finished_at = naive_utc_now()
+        elapsed_time = (finished_at - start_at).total_seconds()
+
+        inputs, inputs_truncated = self._truncate_mapping(event.inputs)
+        process_data, process_data_truncated = self._truncate_mapping(event.process_data)
+        encoded_outputs = self._encode_outputs(event.outputs)
+        outputs, outputs_truncated = self._truncate_mapping(encoded_outputs)
+        metadata = self._merge_metadata(event.execution_metadata, snapshot)
+
+        if isinstance(event, QueueNodeSucceededEvent):
+            status = WorkflowNodeExecutionStatus.SUCCEEDED.value
+            error_message = event.error
+        elif isinstance(event, QueueNodeFailedEvent):
+            status = WorkflowNodeExecutionStatus.FAILED.value
+            error_message = event.error
+        else:
+            status = WorkflowNodeExecutionStatus.EXCEPTION.value
+            error_message = event.error
 
         return NodeFinishStreamResponse(
             task_id=task_id,
-            workflow_run_id=workflow_node_execution.workflow_execution_id,
+            workflow_run_id=run_id,
             data=NodeFinishStreamResponse.Data(
-                id=workflow_node_execution.id,
-                node_id=workflow_node_execution.node_id,
-                node_type=workflow_node_execution.node_type,
-                index=workflow_node_execution.index,
-                title=workflow_node_execution.title,
-                predecessor_node_id=workflow_node_execution.predecessor_node_id,
-                inputs=workflow_node_execution.get_response_inputs(),
-                inputs_truncated=workflow_node_execution.inputs_truncated,
-                process_data=workflow_node_execution.get_response_process_data(),
-                process_data_truncated=workflow_node_execution.process_data_truncated,
-                outputs=json_converter.to_json_encodable(workflow_node_execution.get_response_outputs()),
-                outputs_truncated=workflow_node_execution.outputs_truncated,
-                status=workflow_node_execution.status,
-                error=workflow_node_execution.error,
-                elapsed_time=workflow_node_execution.elapsed_time,
-                execution_metadata=workflow_node_execution.metadata,
-                created_at=int(workflow_node_execution.created_at.timestamp()),
-                finished_at=int(workflow_node_execution.finished_at.timestamp()),
-                files=self.fetch_files_from_node_outputs(workflow_node_execution.outputs or {}),
-                parallel_id=event.parallel_id,
+                id=event.node_execution_id,
+                node_id=event.node_id,
+                node_type=event.node_type,
+                index=snapshot.index if snapshot else 0,
+                title=snapshot.title if snapshot else "",
+                inputs=inputs,
+                inputs_truncated=inputs_truncated,
+                process_data=process_data,
+                process_data_truncated=process_data_truncated,
+                outputs=outputs,
+                outputs_truncated=outputs_truncated,
+                status=status,
+                error=error_message,
+                elapsed_time=elapsed_time,
+                execution_metadata=metadata,
+                created_at=int(start_at.timestamp()),
+                finished_at=int(finished_at.timestamp()),
+                files=self.fetch_files_from_node_outputs(event.outputs or {}),
                 iteration_id=event.in_iteration_id,
                 loop_id=event.in_loop_id,
             ),
@@ -234,44 +361,45 @@ class WorkflowResponseConverter:
         *,
         event: QueueNodeRetryEvent,
         task_id: str,
-        workflow_node_execution: WorkflowNodeExecution,
-    ) -> Union[NodeRetryStreamResponse, NodeFinishStreamResponse] | None:
-        if workflow_node_execution.node_type in {NodeType.ITERATION, NodeType.LOOP}:
-            return None
-        if not workflow_node_execution.workflow_execution_id:
-            return None
-        if not workflow_node_execution.finished_at:
+    ) -> NodeRetryStreamResponse | None:
+        if event.node_type in {NodeType.ITERATION, NodeType.LOOP}:
             return None
+        run_id = self._ensure_workflow_run_id()
 
-        json_converter = WorkflowRuntimeTypeConverter()
+        snapshot = self._get_snapshot(event.node_execution_id)
+        if snapshot is None:
+            raise AssertionError("node retry event arrived without a stored snapshot")
+        finished_at = naive_utc_now()
+        elapsed_time = (finished_at - event.start_at).total_seconds()
+
+        inputs, inputs_truncated = self._truncate_mapping(event.inputs)
+        process_data, process_data_truncated = self._truncate_mapping(event.process_data)
+        encoded_outputs = self._encode_outputs(event.outputs)
+        outputs, outputs_truncated = self._truncate_mapping(encoded_outputs)
+        metadata = self._merge_metadata(event.execution_metadata, snapshot)
 
         return NodeRetryStreamResponse(
             task_id=task_id,
-            workflow_run_id=workflow_node_execution.workflow_execution_id,
+            workflow_run_id=run_id,
             data=NodeRetryStreamResponse.Data(
-                id=workflow_node_execution.id,
-                node_id=workflow_node_execution.node_id,
-                node_type=workflow_node_execution.node_type,
-                index=workflow_node_execution.index,
-                title=workflow_node_execution.title,
-                predecessor_node_id=workflow_node_execution.predecessor_node_id,
-                inputs=workflow_node_execution.get_response_inputs(),
-                inputs_truncated=workflow_node_execution.inputs_truncated,
-                process_data=workflow_node_execution.get_response_process_data(),
-                process_data_truncated=workflow_node_execution.process_data_truncated,
-                outputs=json_converter.to_json_encodable(workflow_node_execution.get_response_outputs()),
-                outputs_truncated=workflow_node_execution.outputs_truncated,
-                status=workflow_node_execution.status,
-                error=workflow_node_execution.error,
-                elapsed_time=workflow_node_execution.elapsed_time,
-                execution_metadata=workflow_node_execution.metadata,
-                created_at=int(workflow_node_execution.created_at.timestamp()),
-                finished_at=int(workflow_node_execution.finished_at.timestamp()),
-                files=self.fetch_files_from_node_outputs(workflow_node_execution.outputs or {}),
-                parallel_id=event.parallel_id,
-                parallel_start_node_id=event.parallel_start_node_id,
-                parent_parallel_id=event.parent_parallel_id,
-                parent_parallel_start_node_id=event.parent_parallel_start_node_id,
+                id=event.node_execution_id,
+                node_id=event.node_id,
+                node_type=event.node_type,
+                index=snapshot.index,
+                title=snapshot.title,
+                inputs=inputs,
+                inputs_truncated=inputs_truncated,
+                process_data=process_data,
+                process_data_truncated=process_data_truncated,
+                outputs=outputs,
+                outputs_truncated=outputs_truncated,
+                status=WorkflowNodeExecutionStatus.RETRY.value,
+                error=event.error,
+                elapsed_time=elapsed_time,
+                execution_metadata=metadata,
+                created_at=int(snapshot.start_at.timestamp()),
+                finished_at=int(finished_at.timestamp()),
+                files=self.fetch_files_from_node_outputs(event.outputs or {}),
                 iteration_id=event.in_iteration_id,
                 loop_id=event.in_loop_id,
                 retry_index=event.retry_index,
@@ -379,8 +507,6 @@ class WorkflowResponseConverter:
                 inputs=new_inputs,
                 inputs_truncated=truncated,
                 metadata=event.metadata or {},
-                parallel_id=event.parallel_id,
-                parallel_start_node_id=event.parallel_start_node_id,
             ),
         )
 
@@ -405,9 +531,6 @@ class WorkflowResponseConverter:
                 pre_loop_output={},
                 created_at=int(time.time()),
                 extras={},
-                parallel_id=event.parallel_id,
-                parallel_start_node_id=event.parallel_start_node_id,
-                parallel_mode_run_id=event.parallel_mode_run_id,
             ),
         )
 
@@ -446,8 +569,6 @@ class WorkflowResponseConverter:
                 execution_metadata=event.metadata,
                 finished_at=int(time.time()),
                 steps=event.steps,
-                parallel_id=event.parallel_id,
-                parallel_start_node_id=event.parallel_start_node_id,
             ),
         )
 

api/core/app/apps/pipeline/pipeline_generator.py

@@ -352,6 +352,8 @@ class PipelineGenerator(BaseAppGenerator):
                     "application_generate_entity": application_generate_entity,
                     "workflow_thread_pool_id": workflow_thread_pool_id,
                     "variable_loader": variable_loader,
+                    "workflow_execution_repository": workflow_execution_repository,
+                    "workflow_node_execution_repository": workflow_node_execution_repository,
                 },
             )
 
@@ -367,8 +369,6 @@ class PipelineGenerator(BaseAppGenerator):
                 workflow=workflow,
                 queue_manager=queue_manager,
                 user=user,
-                workflow_execution_repository=workflow_execution_repository,
-                workflow_node_execution_repository=workflow_node_execution_repository,
                 stream=streaming,
                 draft_var_saver_factory=draft_var_saver_factory,
             )
@@ -573,6 +573,8 @@ class PipelineGenerator(BaseAppGenerator):
         queue_manager: AppQueueManager,
         context: contextvars.Context,
         variable_loader: VariableLoader,
+        workflow_execution_repository: WorkflowExecutionRepository,
+        workflow_node_execution_repository: WorkflowNodeExecutionRepository,
         workflow_thread_pool_id: str | None = None,
     ) -> None:
         """
@@ -620,6 +622,8 @@ class PipelineGenerator(BaseAppGenerator):
                         variable_loader=variable_loader,
                         workflow=workflow,
                         system_user_id=system_user_id,
+                        workflow_execution_repository=workflow_execution_repository,
+                        workflow_node_execution_repository=workflow_node_execution_repository,
                     )
 
                     runner.run()
@@ -648,8 +652,6 @@ class PipelineGenerator(BaseAppGenerator):
         workflow: Workflow,
         queue_manager: AppQueueManager,
         user: Union[Account, EndUser],
-        workflow_execution_repository: WorkflowExecutionRepository,
-        workflow_node_execution_repository: WorkflowNodeExecutionRepository,
         draft_var_saver_factory: DraftVariableSaverFactory,
         stream: bool = False,
     ) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]:
@@ -660,7 +662,6 @@ class PipelineGenerator(BaseAppGenerator):
         :param queue_manager: queue manager
         :param user: account or end user
         :param stream: is stream
-        :param workflow_node_execution_repository: optional repository for workflow node execution
         :return:
         """
         # init generate task pipeline
@@ -670,8 +671,6 @@ class PipelineGenerator(BaseAppGenerator):
             queue_manager=queue_manager,
             user=user,
             stream=stream,
-            workflow_node_execution_repository=workflow_node_execution_repository,
-            workflow_execution_repository=workflow_execution_repository,
             draft_var_saver_factory=draft_var_saver_factory,
         )
 

api/core/app/apps/pipeline/pipeline_runner.py

@@ -11,11 +11,14 @@ from core.app.entities.app_invoke_entities import (
 )
 from core.variables.variables import RAGPipelineVariable, RAGPipelineVariableInput
 from core.workflow.entities.graph_init_params import GraphInitParams
-from core.workflow.entities.graph_runtime_state import GraphRuntimeState
-from core.workflow.entities.variable_pool import VariablePool
+from core.workflow.enums import WorkflowType
 from core.workflow.graph import Graph
+from core.workflow.graph_engine.layers.persistence import PersistenceWorkflowInfo, WorkflowPersistenceLayer
 from core.workflow.graph_events import GraphEngineEvent, GraphRunFailedEvent
 from core.workflow.nodes.node_factory import DifyNodeFactory
+from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
+from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
+from core.workflow.runtime import GraphRuntimeState, VariablePool
 from core.workflow.system_variable import SystemVariable
 from core.workflow.variable_loader import VariableLoader
 from core.workflow.workflow_entry import WorkflowEntry
@@ -40,6 +43,8 @@ class PipelineRunner(WorkflowBasedAppRunner):
         variable_loader: VariableLoader,
         workflow: Workflow,
         system_user_id: str,
+        workflow_execution_repository: WorkflowExecutionRepository,
+        workflow_node_execution_repository: WorkflowNodeExecutionRepository,
         workflow_thread_pool_id: str | None = None,
     ) -> None:
         """
@@ -56,6 +61,8 @@ class PipelineRunner(WorkflowBasedAppRunner):
         self.workflow_thread_pool_id = workflow_thread_pool_id
         self._workflow = workflow
         self._sys_user_id = system_user_id
+        self._workflow_execution_repository = workflow_execution_repository
+        self._workflow_node_execution_repository = workflow_node_execution_repository
 
     def _get_app_id(self) -> str:
         return self.application_generate_entity.app_config.app_id
@@ -163,6 +170,23 @@ class PipelineRunner(WorkflowBasedAppRunner):
             variable_pool=variable_pool,
         )
 
+        self._queue_manager.graph_runtime_state = graph_runtime_state
+
+        persistence_layer = WorkflowPersistenceLayer(
+            application_generate_entity=self.application_generate_entity,
+            workflow_info=PersistenceWorkflowInfo(
+                workflow_id=workflow.id,
+                workflow_type=WorkflowType(workflow.type),
+                version=workflow.version,
+                graph_data=workflow.graph_dict,
+            ),
+            workflow_execution_repository=self._workflow_execution_repository,
+            workflow_node_execution_repository=self._workflow_node_execution_repository,
+            trace_manager=self.application_generate_entity.trace_manager,
+        )
+
+        workflow_entry.graph_engine.layer(persistence_layer)
+
         generator = workflow_entry.run()
 
         for event in generator:

api/core/app/apps/workflow/app_generator.py

@@ -231,6 +231,8 @@ class WorkflowAppGenerator(BaseAppGenerator):
                 "queue_manager": queue_manager,
                 "context": context,
                 "variable_loader": variable_loader,
+                "workflow_execution_repository": workflow_execution_repository,
+                "workflow_node_execution_repository": workflow_node_execution_repository,
             },
         )
 
@@ -244,8 +246,6 @@ class WorkflowAppGenerator(BaseAppGenerator):
             workflow=workflow,
             queue_manager=queue_manager,
             user=user,
-            workflow_execution_repository=workflow_execution_repository,
-            workflow_node_execution_repository=workflow_node_execution_repository,
             draft_var_saver_factory=draft_var_saver_factory,
             stream=streaming,
         )
@@ -424,6 +424,8 @@ class WorkflowAppGenerator(BaseAppGenerator):
         queue_manager: AppQueueManager,
         context: contextvars.Context,
         variable_loader: VariableLoader,
+        workflow_execution_repository: WorkflowExecutionRepository,
+        workflow_node_execution_repository: WorkflowNodeExecutionRepository,
     ) -> None:
         """
         Generate worker in a new thread.
@@ -465,6 +467,8 @@ class WorkflowAppGenerator(BaseAppGenerator):
                 variable_loader=variable_loader,
                 workflow=workflow,
                 system_user_id=system_user_id,
+                workflow_execution_repository=workflow_execution_repository,
+                workflow_node_execution_repository=workflow_node_execution_repository,
             )
 
             try:
@@ -493,8 +497,6 @@ class WorkflowAppGenerator(BaseAppGenerator):
         workflow: Workflow,
         queue_manager: AppQueueManager,
         user: Union[Account, EndUser],
-        workflow_execution_repository: WorkflowExecutionRepository,
-        workflow_node_execution_repository: WorkflowNodeExecutionRepository,
         draft_var_saver_factory: DraftVariableSaverFactory,
         stream: bool = False,
     ) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]:
@@ -514,8 +516,6 @@ class WorkflowAppGenerator(BaseAppGenerator):
             workflow=workflow,
             queue_manager=queue_manager,
             user=user,
-            workflow_execution_repository=workflow_execution_repository,
-            workflow_node_execution_repository=workflow_node_execution_repository,
             draft_var_saver_factory=draft_var_saver_factory,
             stream=stream,
         )

api/core/app/apps/workflow/app_runner.py

@@ -5,12 +5,13 @@ from typing import cast
 from core.app.apps.base_app_queue_manager import AppQueueManager
 from core.app.apps.workflow.app_config_manager import WorkflowAppConfig
 from core.app.apps.workflow_app_runner import WorkflowBasedAppRunner
-from core.app.entities.app_invoke_entities import (
-    InvokeFrom,
-    WorkflowAppGenerateEntity,
-)
-from core.workflow.entities import GraphRuntimeState, VariablePool
+from core.app.entities.app_invoke_entities import InvokeFrom, WorkflowAppGenerateEntity
+from core.workflow.enums import WorkflowType
 from core.workflow.graph_engine.command_channels.redis_channel import RedisChannel
+from core.workflow.graph_engine.layers.persistence import PersistenceWorkflowInfo, WorkflowPersistenceLayer
+from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
+from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
+from core.workflow.runtime import GraphRuntimeState, VariablePool
 from core.workflow.system_variable import SystemVariable
 from core.workflow.variable_loader import VariableLoader
 from core.workflow.workflow_entry import WorkflowEntry
@@ -34,6 +35,8 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
         variable_loader: VariableLoader,
         workflow: Workflow,
         system_user_id: str,
+        workflow_execution_repository: WorkflowExecutionRepository,
+        workflow_node_execution_repository: WorkflowNodeExecutionRepository,
     ):
         super().__init__(
             queue_manager=queue_manager,
@@ -43,6 +46,8 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
         self.application_generate_entity = application_generate_entity
         self._workflow = workflow
         self._sys_user_id = system_user_id
+        self._workflow_execution_repository = workflow_execution_repository
+        self._workflow_node_execution_repository = workflow_node_execution_repository
 
     def run(self):
         """
@@ -51,6 +56,14 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
         app_config = self.application_generate_entity.app_config
         app_config = cast(WorkflowAppConfig, app_config)
 
+        system_inputs = SystemVariable(
+            files=self.application_generate_entity.files,
+            user_id=self._sys_user_id,
+            app_id=app_config.app_id,
+            workflow_id=app_config.workflow_id,
+            workflow_execution_id=self.application_generate_entity.workflow_execution_id,
+        )
+
         # if only single iteration or single loop run is requested
         if self.application_generate_entity.single_iteration_run or self.application_generate_entity.single_loop_run:
             graph, variable_pool, graph_runtime_state = self._prepare_single_node_execution(
@@ -60,18 +73,9 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
             )
         else:
             inputs = self.application_generate_entity.inputs
-            files = self.application_generate_entity.files
 
             # Create a variable pool.
 
-            system_inputs = SystemVariable(
-                files=files,
-                user_id=self._sys_user_id,
-                app_id=app_config.app_id,
-                workflow_id=app_config.workflow_id,
-                workflow_execution_id=self.application_generate_entity.workflow_execution_id,
-            )
-
             variable_pool = VariablePool(
                 system_variables=system_inputs,
                 user_inputs=inputs,
@@ -96,6 +100,8 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
         channel_key = f"workflow:{task_id}:commands"
         command_channel = RedisChannel(redis_client, channel_key)
 
+        self._queue_manager.graph_runtime_state = graph_runtime_state
+
         workflow_entry = WorkflowEntry(
             tenant_id=self._workflow.tenant_id,
             app_id=self._workflow.app_id,
@@ -115,6 +121,21 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
             command_channel=command_channel,
         )
 
+        persistence_layer = WorkflowPersistenceLayer(
+            application_generate_entity=self.application_generate_entity,
+            workflow_info=PersistenceWorkflowInfo(
+                workflow_id=self._workflow.id,
+                workflow_type=WorkflowType(self._workflow.type),
+                version=self._workflow.version,
+                graph_data=self._workflow.graph_dict,
+            ),
+            workflow_execution_repository=self._workflow_execution_repository,
+            workflow_node_execution_repository=self._workflow_node_execution_repository,
+            trace_manager=self.application_generate_entity.trace_manager,
+        )
+
+        workflow_entry.graph_engine.layer(persistence_layer)
+
         generator = workflow_entry.run()
 
         for event in generator:

api/core/app/apps/workflow/generate_task_pipeline.py

@@ -8,11 +8,9 @@ from sqlalchemy.orm import Session
 
 from constants.tts_auto_play_timeout import TTS_AUTO_PLAY_TIMEOUT, TTS_AUTO_PLAY_YIELD_CPU_TIME
 from core.app.apps.base_app_queue_manager import AppQueueManager
+from core.app.apps.common.graph_runtime_state_support import GraphRuntimeStateSupport
 from core.app.apps.common.workflow_response_converter import WorkflowResponseConverter
-from core.app.entities.app_invoke_entities import (
-    InvokeFrom,
-    WorkflowAppGenerateEntity,
-)
+from core.app.entities.app_invoke_entities import InvokeFrom, WorkflowAppGenerateEntity
 from core.app.entities.queue_entities import (
     AppQueueEvent,
     MessageQueueMessage,
@@ -53,27 +51,20 @@ from core.app.entities.task_entities import (
 from core.app.task_pipeline.based_generate_task_pipeline import BasedGenerateTaskPipeline
 from core.base.tts import AppGeneratorTTSPublisher, AudioTrunk
 from core.ops.ops_trace_manager import TraceQueueManager
-from core.workflow.entities import GraphRuntimeState, WorkflowExecution
-from core.workflow.enums import WorkflowExecutionStatus, WorkflowType
+from core.workflow.enums import WorkflowExecutionStatus
 from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory
-from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
-from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
+from core.workflow.runtime import GraphRuntimeState
 from core.workflow.system_variable import SystemVariable
-from core.workflow.workflow_cycle_manager import CycleManagerWorkflowInfo, WorkflowCycleManager
 from extensions.ext_database import db
 from models import Account
 from models.enums import CreatorUserRole
 from models.model import EndUser
-from models.workflow import (
-    Workflow,
-    WorkflowAppLog,
-    WorkflowAppLogCreatedFrom,
-)
+from models.workflow import Workflow, WorkflowAppLog, WorkflowAppLogCreatedFrom
 
 logger = logging.getLogger(__name__)
 
 
-class WorkflowAppGenerateTaskPipeline:
+class WorkflowAppGenerateTaskPipeline(GraphRuntimeStateSupport):
     """
     WorkflowAppGenerateTaskPipeline is a class that generate stream output and state management for Application.
     """
@@ -85,8 +76,6 @@ class WorkflowAppGenerateTaskPipeline:
         queue_manager: AppQueueManager,
         user: Union[Account, EndUser],
         stream: bool,
-        workflow_execution_repository: WorkflowExecutionRepository,
-        workflow_node_execution_repository: WorkflowNodeExecutionRepository,
         draft_var_saver_factory: DraftVariableSaverFactory,
     ):
         self._base_task_pipeline = BasedGenerateTaskPipeline(
@@ -99,42 +88,30 @@ class WorkflowAppGenerateTaskPipeline:
             self._user_id = user.id
             user_session_id = user.session_id
             self._created_by_role = CreatorUserRole.END_USER
-        elif isinstance(user, Account):
+        else:
             self._user_id = user.id
             user_session_id = user.id
             self._created_by_role = CreatorUserRole.ACCOUNT
-        else:
-            raise ValueError(f"Invalid user type: {type(user)}")
-
-        self._workflow_cycle_manager = WorkflowCycleManager(
-            application_generate_entity=application_generate_entity,
-            workflow_system_variables=SystemVariable(
-                files=application_generate_entity.files,
-                user_id=user_session_id,
-                app_id=application_generate_entity.app_config.app_id,
-                workflow_id=workflow.id,
-                workflow_execution_id=application_generate_entity.workflow_execution_id,
-            ),
-            workflow_info=CycleManagerWorkflowInfo(
-                workflow_id=workflow.id,
-                workflow_type=WorkflowType(workflow.type),
-                version=workflow.version,
-                graph_data=workflow.graph_dict,
-            ),
-            workflow_execution_repository=workflow_execution_repository,
-            workflow_node_execution_repository=workflow_node_execution_repository,
-        )
-
-        self._workflow_response_converter = WorkflowResponseConverter(
-            application_generate_entity=application_generate_entity,
-            user=user,
-        )
 
         self._application_generate_entity = application_generate_entity
         self._workflow_features_dict = workflow.features_dict
-        self._workflow_run_id = ""
+        self._workflow_execution_id = ""
         self._invoke_from = queue_manager.invoke_from
         self._draft_var_saver_factory = draft_var_saver_factory
+        self._workflow = workflow
+        self._workflow_system_variables = SystemVariable(
+            files=application_generate_entity.files,
+            user_id=user_session_id,
+            app_id=application_generate_entity.app_config.app_id,
+            workflow_id=workflow.id,
+            workflow_execution_id=application_generate_entity.workflow_execution_id,
+        )
+        self._workflow_response_converter = WorkflowResponseConverter(
+            application_generate_entity=application_generate_entity,
+            user=user,
+            system_variables=self._workflow_system_variables,
+        )
+        self._graph_runtime_state: GraphRuntimeState | None = self._base_task_pipeline.queue_manager.graph_runtime_state
 
     def process(self) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]:
         """
@@ -261,15 +238,9 @@ class WorkflowAppGenerateTaskPipeline:
 
     def _ensure_workflow_initialized(self):
         """Fluent validation for workflow state."""
-        if not self._workflow_run_id:
+        if not self._workflow_execution_id:
             raise ValueError("workflow run not initialized.")
 
-    def _ensure_graph_runtime_initialized(self, graph_runtime_state: GraphRuntimeState | None) -> GraphRuntimeState:
-        """Fluent validation for graph runtime state."""
-        if not graph_runtime_state:
-            raise ValueError("graph runtime state not initialized.")
-        return graph_runtime_state
-
     def _handle_ping_event(self, event: QueuePingEvent, **kwargs) -> Generator[PingStreamResponse, None, None]:
         """Handle ping events."""
         yield self._base_task_pipeline.ping_stream_response()
@@ -283,12 +254,14 @@ class WorkflowAppGenerateTaskPipeline:
         self, event: QueueWorkflowStartedEvent, **kwargs
     ) -> Generator[StreamResponse, None, None]:
         """Handle workflow started events."""
-        # init workflow run
-        workflow_execution = self._workflow_cycle_manager.handle_workflow_run_start()
-        self._workflow_run_id = workflow_execution.id_
+        runtime_state = self._resolve_graph_runtime_state()
+
+        run_id = self._extract_workflow_run_id(runtime_state)
+        self._workflow_execution_id = run_id
         start_resp = self._workflow_response_converter.workflow_start_to_stream_response(
             task_id=self._application_generate_entity.task_id,
-            workflow_execution=workflow_execution,
+            workflow_run_id=run_id,
+            workflow_id=self._workflow.id,
         )
         yield start_resp
 
@@ -296,14 +269,9 @@ class WorkflowAppGenerateTaskPipeline:
         """Handle node retry events."""
         self._ensure_workflow_initialized()
 
-        workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_retried(
-            workflow_execution_id=self._workflow_run_id,
-            event=event,
-        )
         response = self._workflow_response_converter.workflow_node_retry_to_stream_response(
             event=event,
             task_id=self._application_generate_entity.task_id,
-            workflow_node_execution=workflow_node_execution,
         )
 
         if response:
@@ -315,13 +283,9 @@ class WorkflowAppGenerateTaskPipeline:
         """Handle node started events."""
         self._ensure_workflow_initialized()
 
-        workflow_node_execution = self._workflow_cycle_manager.handle_node_execution_start(
-            workflow_execution_id=self._workflow_run_id, event=event
-        )
         node_start_response = self._workflow_response_converter.workflow_node_start_to_stream_response(
             event=event,
             task_id=self._application_generate_entity.task_id,
-            workflow_node_execution=workflow_node_execution,
         )
 
         if node_start_response:
@@ -331,14 +295,12 @@ class WorkflowAppGenerateTaskPipeline:
         self, event: QueueNodeSucceededEvent, **kwargs
     ) -> Generator[StreamResponse, None, None]:
         """Handle node succeeded events."""
-        workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_success(event=event)
         node_success_response = self._workflow_response_converter.workflow_node_finish_to_stream_response(
             event=event,
             task_id=self._application_generate_entity.task_id,
-            workflow_node_execution=workflow_node_execution,
         )
 
-        self._save_output_for_event(event, workflow_node_execution.id)
+        self._save_output_for_event(event, event.node_execution_id)
 
         if node_success_response:
             yield node_success_response
@@ -349,17 +311,13 @@ class WorkflowAppGenerateTaskPipeline:
         **kwargs,
     ) -> Generator[StreamResponse, None, None]:
         """Handle various node failure events."""
-        workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_failed(
-            event=event,
-        )
         node_failed_response = self._workflow_response_converter.workflow_node_finish_to_stream_response(
             event=event,
             task_id=self._application_generate_entity.task_id,
-            workflow_node_execution=workflow_node_execution,
         )
 
         if isinstance(event, QueueNodeExceptionEvent):
-            self._save_output_for_event(event, workflow_node_execution.id)
+            self._save_output_for_event(event, event.node_execution_id)
 
         if node_failed_response:
             yield node_failed_response
@@ -372,7 +330,7 @@ class WorkflowAppGenerateTaskPipeline:
 
         iter_start_resp = self._workflow_response_converter.workflow_iteration_start_to_stream_response(
             task_id=self._application_generate_entity.task_id,
-            workflow_execution_id=self._workflow_run_id,
+            workflow_execution_id=self._workflow_execution_id,
             event=event,
         )
         yield iter_start_resp
@@ -385,7 +343,7 @@ class WorkflowAppGenerateTaskPipeline:
 
         iter_next_resp = self._workflow_response_converter.workflow_iteration_next_to_stream_response(
             task_id=self._application_generate_entity.task_id,
-            workflow_execution_id=self._workflow_run_id,
+            workflow_execution_id=self._workflow_execution_id,
             event=event,
         )
         yield iter_next_resp
@@ -398,7 +356,7 @@ class WorkflowAppGenerateTaskPipeline:
 
         iter_finish_resp = self._workflow_response_converter.workflow_iteration_completed_to_stream_response(
             task_id=self._application_generate_entity.task_id,
-            workflow_execution_id=self._workflow_run_id,
+            workflow_execution_id=self._workflow_execution_id,
             event=event,
         )
         yield iter_finish_resp
@@ -409,7 +367,7 @@ class WorkflowAppGenerateTaskPipeline:
 
         loop_start_resp = self._workflow_response_converter.workflow_loop_start_to_stream_response(
             task_id=self._application_generate_entity.task_id,
-            workflow_execution_id=self._workflow_run_id,
+            workflow_execution_id=self._workflow_execution_id,
             event=event,
         )
         yield loop_start_resp
@@ -420,7 +378,7 @@ class WorkflowAppGenerateTaskPipeline:
 
         loop_next_resp = self._workflow_response_converter.workflow_loop_next_to_stream_response(
             task_id=self._application_generate_entity.task_id,
-            workflow_execution_id=self._workflow_run_id,
+            workflow_execution_id=self._workflow_execution_id,
             event=event,
         )
         yield loop_next_resp
@@ -433,7 +391,7 @@ class WorkflowAppGenerateTaskPipeline:
 
         loop_finish_resp = self._workflow_response_converter.workflow_loop_completed_to_stream_response(
             task_id=self._application_generate_entity.task_id,
-            workflow_execution_id=self._workflow_run_id,
+            workflow_execution_id=self._workflow_execution_id,
             event=event,
         )
         yield loop_finish_resp
@@ -442,33 +400,22 @@ class WorkflowAppGenerateTaskPipeline:
         self,
         event: QueueWorkflowSucceededEvent,
         *,
-        graph_runtime_state: GraphRuntimeState | None = None,
         trace_manager: TraceQueueManager | None = None,
         **kwargs,
     ) -> Generator[StreamResponse, None, None]:
         """Handle workflow succeeded events."""
+        _ = trace_manager
         self._ensure_workflow_initialized()
-        validated_state = self._ensure_graph_runtime_initialized(graph_runtime_state)
+        validated_state = self._ensure_graph_runtime_initialized()
+        workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
+            task_id=self._application_generate_entity.task_id,
+            workflow_id=self._workflow.id,
+            status=WorkflowExecutionStatus.SUCCEEDED,
+            graph_runtime_state=validated_state,
+        )
 
         with self._database_session() as session:
-            workflow_execution = self._workflow_cycle_manager.handle_workflow_run_success(
-                workflow_run_id=self._workflow_run_id,
-                total_tokens=validated_state.total_tokens,
-                total_steps=validated_state.node_run_steps,
-                outputs=event.outputs,
-                conversation_id=None,
-                trace_manager=trace_manager,
-                external_trace_id=self._application_generate_entity.extras.get("external_trace_id"),
-            )
-
-            # save workflow app log
-            self._save_workflow_app_log(session=session, workflow_execution=workflow_execution)
-
-            workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
-                session=session,
-                task_id=self._application_generate_entity.task_id,
-                workflow_execution=workflow_execution,
-            )
+            self._save_workflow_app_log(session=session, workflow_run_id=self._workflow_execution_id)
 
         yield workflow_finish_resp
 
@@ -476,34 +423,23 @@ class WorkflowAppGenerateTaskPipeline:
         self,
         event: QueueWorkflowPartialSuccessEvent,
         *,
-        graph_runtime_state: GraphRuntimeState | None = None,
         trace_manager: TraceQueueManager | None = None,
         **kwargs,
     ) -> Generator[StreamResponse, None, None]:
         """Handle workflow partial success events."""
+        _ = trace_manager
         self._ensure_workflow_initialized()
-        validated_state = self._ensure_graph_runtime_initialized(graph_runtime_state)
+        validated_state = self._ensure_graph_runtime_initialized()
+        workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
+            task_id=self._application_generate_entity.task_id,
+            workflow_id=self._workflow.id,
+            status=WorkflowExecutionStatus.PARTIAL_SUCCEEDED,
+            graph_runtime_state=validated_state,
+            exceptions_count=event.exceptions_count,
+        )
 
         with self._database_session() as session:
-            workflow_execution = self._workflow_cycle_manager.handle_workflow_run_partial_success(
-                workflow_run_id=self._workflow_run_id,
-                total_tokens=validated_state.total_tokens,
-                total_steps=validated_state.node_run_steps,
-                outputs=event.outputs,
-                exceptions_count=event.exceptions_count,
-                conversation_id=None,
-                trace_manager=trace_manager,
-                external_trace_id=self._application_generate_entity.extras.get("external_trace_id"),
-            )
-
-            # save workflow app log
-            self._save_workflow_app_log(session=session, workflow_execution=workflow_execution)
-
-            workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
-                session=session,
-                task_id=self._application_generate_entity.task_id,
-                workflow_execution=workflow_execution,
-            )
+            self._save_workflow_app_log(session=session, workflow_run_id=self._workflow_execution_id)
 
         yield workflow_finish_resp
 
@@ -511,37 +447,33 @@ class WorkflowAppGenerateTaskPipeline:
         self,
         event: Union[QueueWorkflowFailedEvent, QueueStopEvent],
         *,
-        graph_runtime_state: GraphRuntimeState | None = None,
         trace_manager: TraceQueueManager | None = None,
         **kwargs,
     ) -> Generator[StreamResponse, None, None]:
         """Handle workflow failed and stop events."""
+        _ = trace_manager
         self._ensure_workflow_initialized()
-        validated_state = self._ensure_graph_runtime_initialized(graph_runtime_state)
+        validated_state = self._ensure_graph_runtime_initialized()
+
+        if isinstance(event, QueueWorkflowFailedEvent):
+            status = WorkflowExecutionStatus.FAILED
+            error = event.error
+            exceptions_count = event.exceptions_count
+        else:
+            status = WorkflowExecutionStatus.STOPPED
+            error = event.get_stop_reason()
+            exceptions_count = 0
+        workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
+            task_id=self._application_generate_entity.task_id,
+            workflow_id=self._workflow.id,
+            status=status,
+            graph_runtime_state=validated_state,
+            error=error,
+            exceptions_count=exceptions_count,
+        )
 
         with self._database_session() as session:
-            workflow_execution = self._workflow_cycle_manager.handle_workflow_run_failed(
-                workflow_run_id=self._workflow_run_id,
-                total_tokens=validated_state.total_tokens,
-                total_steps=validated_state.node_run_steps,
-                status=WorkflowExecutionStatus.FAILED
-                if isinstance(event, QueueWorkflowFailedEvent)
-                else WorkflowExecutionStatus.STOPPED,
-                error_message=event.error if isinstance(event, QueueWorkflowFailedEvent) else event.get_stop_reason(),
-                conversation_id=None,
-                trace_manager=trace_manager,
-                exceptions_count=event.exceptions_count if isinstance(event, QueueWorkflowFailedEvent) else 0,
-                external_trace_id=self._application_generate_entity.extras.get("external_trace_id"),
-            )
-
-            # save workflow app log
-            self._save_workflow_app_log(session=session, workflow_execution=workflow_execution)
-
-            workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
-                session=session,
-                task_id=self._application_generate_entity.task_id,
-                workflow_execution=workflow_execution,
-            )
+            self._save_workflow_app_log(session=session, workflow_run_id=self._workflow_execution_id)
 
         yield workflow_finish_resp
 
@@ -601,7 +533,6 @@ class WorkflowAppGenerateTaskPipeline:
         self,
         event: AppQueueEvent,
         *,
-        graph_runtime_state: GraphRuntimeState | None = None,
         tts_publisher: AppGeneratorTTSPublisher | None = None,
         trace_manager: TraceQueueManager | None = None,
         queue_message: Union[WorkflowQueueMessage, MessageQueueMessage] | None = None,
@@ -614,7 +545,6 @@ class WorkflowAppGenerateTaskPipeline:
         if handler := handlers.get(event_type):
             yield from handler(
                 event,
-                graph_runtime_state=graph_runtime_state,
                 tts_publisher=tts_publisher,
                 trace_manager=trace_manager,
                 queue_message=queue_message,
@@ -631,7 +561,6 @@ class WorkflowAppGenerateTaskPipeline:
         ):
             yield from self._handle_node_failed_events(
                 event,
-                graph_runtime_state=graph_runtime_state,
                 tts_publisher=tts_publisher,
                 trace_manager=trace_manager,
                 queue_message=queue_message,
@@ -642,7 +571,6 @@ class WorkflowAppGenerateTaskPipeline:
         if isinstance(event, (QueueWorkflowFailedEvent, QueueStopEvent)):
             yield from self._handle_workflow_failed_and_stop_events(
                 event,
-                graph_runtime_state=graph_runtime_state,
                 tts_publisher=tts_publisher,
                 trace_manager=trace_manager,
                 queue_message=queue_message,
@@ -661,15 +589,12 @@ class WorkflowAppGenerateTaskPipeline:
         Process stream response using elegant Fluent Python patterns.
         Maintains exact same functionality as original 44-if-statement version.
         """
-        # Initialize graph runtime state
-        graph_runtime_state = None
-
         for queue_message in self._base_task_pipeline.queue_manager.listen():
             event = queue_message.event
 
             match event:
                 case QueueWorkflowStartedEvent():
-                    graph_runtime_state = event.graph_runtime_state
+                    self._resolve_graph_runtime_state()
                     yield from self._handle_workflow_started_event(event)
 
                 case QueueTextChunkEvent():
@@ -681,12 +606,19 @@ class WorkflowAppGenerateTaskPipeline:
                     yield from self._handle_error_event(event)
                     break
 
+                case QueueWorkflowFailedEvent():
+                    yield from self._handle_workflow_failed_and_stop_events(event)
+                    break
+
+                case QueueStopEvent():
+                    yield from self._handle_workflow_failed_and_stop_events(event)
+                    break
+
                 # Handle all other events through elegant dispatch
                 case _:
                     if responses := list(
                         self._dispatch_event(
                             event,
-                            graph_runtime_state=graph_runtime_state,
                             tts_publisher=tts_publisher,
                             trace_manager=trace_manager,
                             queue_message=queue_message,
@@ -697,7 +629,7 @@ class WorkflowAppGenerateTaskPipeline:
         if tts_publisher:
             tts_publisher.publish(None)
 
-    def _save_workflow_app_log(self, *, session: Session, workflow_execution: WorkflowExecution):
+    def _save_workflow_app_log(self, *, session: Session, workflow_run_id: str | None):
         invoke_from = self._application_generate_entity.invoke_from
         if invoke_from == InvokeFrom.SERVICE_API:
             created_from = WorkflowAppLogCreatedFrom.SERVICE_API
@@ -709,11 +641,14 @@ class WorkflowAppGenerateTaskPipeline:
             # not save log for debugging
             return
 
+        if not workflow_run_id:
+            return
+
         workflow_app_log = WorkflowAppLog()
         workflow_app_log.tenant_id = self._application_generate_entity.app_config.tenant_id
         workflow_app_log.app_id = self._application_generate_entity.app_config.app_id
-        workflow_app_log.workflow_id = workflow_execution.workflow_id
-        workflow_app_log.workflow_run_id = workflow_execution.id_
+        workflow_app_log.workflow_id = self._workflow.id
+        workflow_app_log.workflow_run_id = workflow_run_id
         workflow_app_log.created_from = created_from.value
         workflow_app_log.created_by_role = self._created_by_role
         workflow_app_log.created_by = self._user_id

api/core/app/apps/workflow_app_runner.py

@@ -25,7 +25,7 @@ from core.app.entities.queue_entities import (
     QueueWorkflowStartedEvent,
     QueueWorkflowSucceededEvent,
 )
-from core.workflow.entities import GraphInitParams, GraphRuntimeState, VariablePool
+from core.workflow.entities import GraphInitParams
 from core.workflow.graph import Graph
 from core.workflow.graph_events import (
     GraphEngineEvent,
@@ -54,6 +54,7 @@ from core.workflow.graph_events.graph import GraphRunAbortedEvent
 from core.workflow.nodes import NodeType
 from core.workflow.nodes.node_factory import DifyNodeFactory
 from core.workflow.nodes.node_mapping import NODE_TYPE_CLASSES_MAPPING
+from core.workflow.runtime import GraphRuntimeState, VariablePool
 from core.workflow.system_variable import SystemVariable
 from core.workflow.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader, load_into_variable_pool
 from core.workflow.workflow_entry import WorkflowEntry
@@ -346,9 +347,7 @@ class WorkflowBasedAppRunner:
         :param event: event
         """
         if isinstance(event, GraphRunStartedEvent):
-            self._publish_event(
-                QueueWorkflowStartedEvent(graph_runtime_state=workflow_entry.graph_engine.graph_runtime_state)
-            )
+            self._publish_event(QueueWorkflowStartedEvent())
         elif isinstance(event, GraphRunSucceededEvent):
             self._publish_event(QueueWorkflowSucceededEvent(outputs=event.outputs))
         elif isinstance(event, GraphRunPartialSucceededEvent):
@@ -372,7 +371,6 @@ class WorkflowBasedAppRunner:
                     node_title=event.node_title,
                     node_type=event.node_type,
                     start_at=event.start_at,
-                    predecessor_node_id=event.predecessor_node_id,
                     in_iteration_id=event.in_iteration_id,
                     in_loop_id=event.in_loop_id,
                     inputs=inputs,
@@ -393,7 +391,6 @@ class WorkflowBasedAppRunner:
                     node_title=event.node_title,
                     node_type=event.node_type,
                     start_at=event.start_at,
-                    predecessor_node_id=event.predecessor_node_id,
                     in_iteration_id=event.in_iteration_id,
                     in_loop_id=event.in_loop_id,
                     agent_strategy=event.agent_strategy,
@@ -494,7 +491,6 @@ class WorkflowBasedAppRunner:
                     start_at=event.start_at,
                     node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
                     inputs=event.inputs,
-                    predecessor_node_id=event.predecessor_node_id,
                     metadata=event.metadata,
                 )
             )
@@ -536,7 +532,6 @@ class WorkflowBasedAppRunner:
                     start_at=event.start_at,
                     node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
                     inputs=event.inputs,
-                    predecessor_node_id=event.predecessor_node_id,
                     metadata=event.metadata,
                 )
             )

api/core/app/entities/queue_entities.py

@@ -3,11 +3,11 @@ from datetime import datetime
 from enum import StrEnum, auto
 from typing import Any
 
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field
 
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk
 from core.rag.entities.citation_metadata import RetrievalSourceMetadata
-from core.workflow.entities import AgentNodeStrategyInit, GraphRuntimeState
+from core.workflow.entities import AgentNodeStrategyInit
 from core.workflow.enums import WorkflowNodeExecutionMetadataKey
 from core.workflow.nodes import NodeType
 
@@ -54,6 +54,7 @@ class AppQueueEvent(BaseModel):
     """
 
     event: QueueEvent
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
 
 class QueueLLMChunkEvent(AppQueueEvent):
@@ -80,7 +81,6 @@ class QueueIterationStartEvent(AppQueueEvent):
 
     node_run_index: int
     inputs: Mapping[str, object] = Field(default_factory=dict)
-    predecessor_node_id: str | None = None
     metadata: Mapping[str, object] = Field(default_factory=dict)
 
 
@@ -132,19 +132,10 @@ class QueueLoopStartEvent(AppQueueEvent):
     node_id: str
     node_type: NodeType
     node_title: str
-    parallel_id: str | None = None
-    """parallel id if node is in parallel"""
-    parallel_start_node_id: str | None = None
-    """parallel start node id if node is in parallel"""
-    parent_parallel_id: str | None = None
-    """parent parallel id if node is in parallel"""
-    parent_parallel_start_node_id: str | None = None
-    """parent parallel start node id if node is in parallel"""
     start_at: datetime
 
     node_run_index: int
     inputs: Mapping[str, object] = Field(default_factory=dict)
-    predecessor_node_id: str | None = None
     metadata: Mapping[str, object] = Field(default_factory=dict)
 
 
@@ -160,16 +151,6 @@ class QueueLoopNextEvent(AppQueueEvent):
     node_id: str
     node_type: NodeType
     node_title: str
-    parallel_id: str | None = None
-    """parallel id if node is in parallel"""
-    parallel_start_node_id: str | None = None
-    """parallel start node id if node is in parallel"""
-    parent_parallel_id: str | None = None
-    """parent parallel id if node is in parallel"""
-    parent_parallel_start_node_id: str | None = None
-    """parent parallel start node id if node is in parallel"""
-    parallel_mode_run_id: str | None = None
-    """iteration run in parallel mode run id"""
     node_run_index: int
     output: Any = None  # output for the current loop
 
@@ -185,14 +166,6 @@ class QueueLoopCompletedEvent(AppQueueEvent):
     node_id: str
     node_type: NodeType
     node_title: str
-    parallel_id: str | None = None
-    """parallel id if node is in parallel"""
-    parallel_start_node_id: str | None = None
-    """parallel start node id if node is in parallel"""
-    parent_parallel_id: str | None = None
-    """parent parallel id if node is in parallel"""
-    parent_parallel_start_node_id: str | None = None
-    """parent parallel start node id if node is in parallel"""
     start_at: datetime
 
     node_run_index: int
@@ -285,12 +258,9 @@ class QueueAdvancedChatMessageEndEvent(AppQueueEvent):
 
 
 class QueueWorkflowStartedEvent(AppQueueEvent):
-    """
-    QueueWorkflowStartedEvent entity
-    """
+    """QueueWorkflowStartedEvent entity."""
 
     event: QueueEvent = QueueEvent.WORKFLOW_STARTED
-    graph_runtime_state: GraphRuntimeState
 
 
 class QueueWorkflowSucceededEvent(AppQueueEvent):
@@ -334,15 +304,9 @@ class QueueNodeStartedEvent(AppQueueEvent):
     node_title: str
     node_type: NodeType
     node_run_index: int = 1  # FIXME(-LAN-): may not used
-    predecessor_node_id: str | None = None
-    parallel_id: str | None = None
-    parallel_start_node_id: str | None = None
-    parent_parallel_id: str | None = None
-    parent_parallel_start_node_id: str | None = None
     in_iteration_id: str | None = None
     in_loop_id: str | None = None
     start_at: datetime
-    parallel_mode_run_id: str | None = None
     agent_strategy: AgentNodeStrategyInit | None = None
 
     # FIXME(-LAN-): only for ToolNode, need to refactor
@@ -360,14 +324,6 @@ class QueueNodeSucceededEvent(AppQueueEvent):
     node_execution_id: str
     node_id: str
     node_type: NodeType
-    parallel_id: str | None = None
-    """parallel id if node is in parallel"""
-    parallel_start_node_id: str | None = None
-    """parallel start node id if node is in parallel"""
-    parent_parallel_id: str | None = None
-    """parent parallel id if node is in parallel"""
-    parent_parallel_start_node_id: str | None = None
-    """parent parallel start node id if node is in parallel"""
     in_iteration_id: str | None = None
     """iteration id if node is in iteration"""
     in_loop_id: str | None = None
@@ -423,14 +379,6 @@ class QueueNodeExceptionEvent(AppQueueEvent):
     node_execution_id: str
     node_id: str
     node_type: NodeType
-    parallel_id: str | None = None
-    """parallel id if node is in parallel"""
-    parallel_start_node_id: str | None = None
-    """parallel start node id if node is in parallel"""
-    parent_parallel_id: str | None = None
-    """parent parallel id if node is in parallel"""
-    parent_parallel_start_node_id: str | None = None
-    """parent parallel start node id if node is in parallel"""
     in_iteration_id: str | None = None
     """iteration id if node is in iteration"""
     in_loop_id: str | None = None
@@ -455,7 +403,6 @@ class QueueNodeFailedEvent(AppQueueEvent):
     node_execution_id: str
     node_id: str
     node_type: NodeType
-    parallel_id: str | None = None
     in_iteration_id: str | None = None
     """iteration id if node is in iteration"""
     in_loop_id: str | None = None

api/core/app/entities/task_entities.py

@@ -257,13 +257,8 @@ class NodeStartStreamResponse(StreamResponse):
         inputs_truncated: bool = False
         created_at: int
         extras: dict[str, object] = Field(default_factory=dict)
-        parallel_id: str | None = None
-        parallel_start_node_id: str | None = None
-        parent_parallel_id: str | None = None
-        parent_parallel_start_node_id: str | None = None
         iteration_id: str | None = None
         loop_id: str | None = None
-        parallel_run_id: str | None = None
         agent_strategy: AgentNodeStrategyInit | None = None
 
     event: StreamEvent = StreamEvent.NODE_STARTED
@@ -285,10 +280,6 @@ class NodeStartStreamResponse(StreamResponse):
                 "inputs": None,
                 "created_at": self.data.created_at,
                 "extras": {},
-                "parallel_id": self.data.parallel_id,
-                "parallel_start_node_id": self.data.parallel_start_node_id,
-                "parent_parallel_id": self.data.parent_parallel_id,
-                "parent_parallel_start_node_id": self.data.parent_parallel_start_node_id,
                 "iteration_id": self.data.iteration_id,
                 "loop_id": self.data.loop_id,
             },
@@ -324,10 +315,6 @@ class NodeFinishStreamResponse(StreamResponse):
         created_at: int
         finished_at: int
         files: Sequence[Mapping[str, Any]] | None = []
-        parallel_id: str | None = None
-        parallel_start_node_id: str | None = None
-        parent_parallel_id: str | None = None
-        parent_parallel_start_node_id: str | None = None
         iteration_id: str | None = None
         loop_id: str | None = None
 
@@ -357,10 +344,6 @@ class NodeFinishStreamResponse(StreamResponse):
                 "created_at": self.data.created_at,
                 "finished_at": self.data.finished_at,
                 "files": [],
-                "parallel_id": self.data.parallel_id,
-                "parallel_start_node_id": self.data.parallel_start_node_id,
-                "parent_parallel_id": self.data.parent_parallel_id,
-                "parent_parallel_start_node_id": self.data.parent_parallel_start_node_id,
                 "iteration_id": self.data.iteration_id,
                 "loop_id": self.data.loop_id,
             },
@@ -396,10 +379,6 @@ class NodeRetryStreamResponse(StreamResponse):
         created_at: int
         finished_at: int
         files: Sequence[Mapping[str, Any]] | None = []
-        parallel_id: str | None = None
-        parallel_start_node_id: str | None = None
-        parent_parallel_id: str | None = None
-        parent_parallel_start_node_id: str | None = None
         iteration_id: str | None = None
         loop_id: str | None = None
         retry_index: int = 0
@@ -430,10 +409,6 @@ class NodeRetryStreamResponse(StreamResponse):
                 "created_at": self.data.created_at,
                 "finished_at": self.data.finished_at,
                 "files": [],
-                "parallel_id": self.data.parallel_id,
-                "parallel_start_node_id": self.data.parallel_start_node_id,
-                "parent_parallel_id": self.data.parent_parallel_id,
-                "parent_parallel_start_node_id": self.data.parent_parallel_start_node_id,
                 "iteration_id": self.data.iteration_id,
                 "loop_id": self.data.loop_id,
                 "retry_index": self.data.retry_index,
@@ -541,8 +516,6 @@ class LoopNodeStartStreamResponse(StreamResponse):
         metadata: Mapping = {}
         inputs: Mapping = {}
         inputs_truncated: bool = False
-        parallel_id: str | None = None
-        parallel_start_node_id: str | None = None
 
     event: StreamEvent = StreamEvent.LOOP_STARTED
     workflow_run_id: str
@@ -567,9 +540,6 @@ class LoopNodeNextStreamResponse(StreamResponse):
         created_at: int
         pre_loop_output: Any = None
         extras: Mapping[str, object] = Field(default_factory=dict)
-        parallel_id: str | None = None
-        parallel_start_node_id: str | None = None
-        parallel_mode_run_id: str | None = None
 
     event: StreamEvent = StreamEvent.LOOP_NEXT
     workflow_run_id: str
@@ -603,8 +573,6 @@ class LoopNodeCompletedStreamResponse(StreamResponse):
         execution_metadata: Mapping[str, object] = Field(default_factory=dict)
         finished_at: int
         steps: int
-        parallel_id: str | None = None
-        parallel_start_node_id: str | None = None
 
     event: StreamEvent = StreamEvent.LOOP_COMPLETED
     workflow_run_id: str