refactor(workflow_cycle_manager): Remove unused methods from WorkflowCycleManager.

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

api/core/workflow/workflow_cycle_manager.py

@@ -1,7 +1,6 @@
-import time
+from collections.abc import Mapping
-from collections.abc import Mapping, Sequence
 from datetime import UTC, datetime
-from typing import Any, Optional, Union, cast
+from typing import Any, Optional, Union
 from uuid import uuid4
 
 from sqlalchemy import func, select
@@ -9,13 +8,6 @@ from sqlalchemy.orm import Session
 
 from core.app.entities.app_invoke_entities import AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity
 from core.app.entities.queue_entities import (
-    QueueAgentLogEvent,
-    QueueIterationCompletedEvent,
-    QueueIterationNextEvent,
-    QueueIterationStartEvent,
-    QueueLoopCompletedEvent,
-    QueueLoopNextEvent,
-    QueueLoopStartEvent,
     QueueNodeExceptionEvent,
     QueueNodeFailedEvent,
     QueueNodeInIterationFailedEvent,
@@ -23,31 +15,10 @@ from core.app.entities.queue_entities import (
     QueueNodeRetryEvent,
     QueueNodeStartedEvent,
     QueueNodeSucceededEvent,
-    QueueParallelBranchRunFailedEvent,
-    QueueParallelBranchRunStartedEvent,
-    QueueParallelBranchRunSucceededEvent,
-)
-from core.app.entities.task_entities import (
-    AgentLogStreamResponse,
-    IterationNodeCompletedStreamResponse,
-    IterationNodeNextStreamResponse,
-    IterationNodeStartStreamResponse,
-    LoopNodeCompletedStreamResponse,
-    LoopNodeNextStreamResponse,
-    LoopNodeStartStreamResponse,
-    NodeFinishStreamResponse,
-    NodeRetryStreamResponse,
-    NodeStartStreamResponse,
-    ParallelBranchFinishedStreamResponse,
-    ParallelBranchStartStreamResponse,
-    WorkflowFinishStreamResponse,
-    WorkflowStartStreamResponse,
 )
 from core.app.task_pipeline.exc import WorkflowRunNotFoundError
-from core.file import FILE_MODEL_IDENTITY, File
 from core.ops.entities.trace_entity import TraceTaskName
 from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
-from core.tools.tool_manager import ToolManager
 from core.workflow.entities.node_entities import NodeRunMetadataKey
 from core.workflow.entities.node_execution_entities import (
     NodeExecution,
@@ -55,17 +26,11 @@ from core.workflow.entities.node_execution_entities import (
 )
 from core.workflow.entities.workflow_execution_entities import WorkflowExecution, WorkflowExecutionStatus, WorkflowType
 from core.workflow.enums import SystemVariableKey
-from core.workflow.nodes import NodeType
-from core.workflow.nodes.tool.entities import ToolNodeData
 from core.workflow.repository.workflow_execution_repository import WorkflowExecutionRepository
 from core.workflow.repository.workflow_node_execution_repository import WorkflowNodeExecutionRepository
 from core.workflow.workflow_entry import WorkflowEntry
 from models import (
-    Account,
-    CreatorUserRole,
-    EndUser,
     Workflow,
-    WorkflowNodeExecutionStatus,
     WorkflowRun,
     WorkflowRunStatus,
 )
@@ -416,506 +381,8 @@ class WorkflowCycleManager:
 
         return domain_execution
 
-    def workflow_start_to_stream_response(
-        self,
-        *,
-        task_id: str,
-        workflow_execution: WorkflowExecution,
-    ) -> WorkflowStartStreamResponse:
-        return WorkflowStartStreamResponse(
-            task_id=task_id,
-            workflow_run_id=workflow_execution.id,
-            data=WorkflowStartStreamResponse.Data(
-                id=workflow_execution.id,
-                workflow_id=workflow_execution.workflow_id,
-                sequence_number=workflow_execution.sequence_number,
-                inputs=workflow_execution.inputs,
-                created_at=int(workflow_execution.started_at.timestamp()),
-            ),
-        )
-
-    def workflow_finish_to_stream_response(
-        self,
-        *,
-        session: Session,
-        task_id: str,
-        workflow_execution: WorkflowExecution,
-    ) -> WorkflowFinishStreamResponse:
-        created_by = None
-        workflow_run = session.scalar(select(WorkflowRun).where(WorkflowRun.id == workflow_execution.id))
-        assert workflow_run is not None
-        if workflow_run.created_by_role == CreatorUserRole.ACCOUNT:
-            stmt = select(Account).where(Account.id == workflow_run.created_by)
-            account = session.scalar(stmt)
-            if account:
-                created_by = {
-                    "id": account.id,
-                    "name": account.name,
-                    "email": account.email,
-                }
-        elif workflow_run.created_by_role == CreatorUserRole.END_USER:
-            stmt = select(EndUser).where(EndUser.id == workflow_run.created_by)
-            end_user = session.scalar(stmt)
-            if end_user:
-                created_by = {
-                    "id": end_user.id,
-                    "user": end_user.session_id,
-                }
-        else:
-            raise NotImplementedError(f"unknown created_by_role: {workflow_run.created_by_role}")
-
-        # 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,
-            data=WorkflowFinishStreamResponse.Data(
-                id=workflow_execution.id,
-                workflow_id=workflow_execution.workflow_id,
-                sequence_number=workflow_execution.sequence_number,
-                status=workflow_execution.status,
-                outputs=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,
-                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,
-            ),
-        )
-
-    def workflow_node_start_to_stream_response(
-        self,
-        *,
-        event: QueueNodeStartedEvent,
-        task_id: str,
-        workflow_node_execution: NodeExecution,
-    ) -> Optional[NodeStartStreamResponse]:
-        if workflow_node_execution.node_type in {NodeType.ITERATION, NodeType.LOOP}:
-            return None
-        if not workflow_node_execution.workflow_run_id:
-            return None
-
-        response = NodeStartStreamResponse(
-            task_id=task_id,
-            workflow_run_id=workflow_node_execution.workflow_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.inputs,
-                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,
-                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:
-            node_data = cast(ToolNodeData, event.node_data)
-            response.data.extras["icon"] = ToolManager.get_tool_icon(
-                tenant_id=self._application_generate_entity.app_config.tenant_id,
-                provider_type=node_data.provider_type,
-                provider_id=node_data.provider_id,
-            )
-
-        return response
-
-    def workflow_node_finish_to_stream_response(
-        self,
-        *,
-        event: QueueNodeSucceededEvent
-        | QueueNodeFailedEvent
-        | QueueNodeInIterationFailedEvent
-        | QueueNodeInLoopFailedEvent
-        | QueueNodeExceptionEvent,
-        task_id: str,
-        workflow_node_execution: NodeExecution,
-    ) -> Optional[NodeFinishStreamResponse]:
-        if workflow_node_execution.node_type in {NodeType.ITERATION, NodeType.LOOP}:
-            return None
-        if not workflow_node_execution.workflow_run_id:
-            return None
-        if not workflow_node_execution.finished_at:
-            return None
-
-        return NodeFinishStreamResponse(
-            task_id=task_id,
-            workflow_run_id=workflow_node_execution.workflow_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.inputs,
-                process_data=workflow_node_execution.process_data,
-                outputs=workflow_node_execution.outputs,
-                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,
-                iteration_id=event.in_iteration_id,
-                loop_id=event.in_loop_id,
-            ),
-        )
-
-    def workflow_node_retry_to_stream_response(
-        self,
-        *,
-        event: QueueNodeRetryEvent,
-        task_id: str,
-        workflow_node_execution: NodeExecution,
-    ) -> Optional[Union[NodeRetryStreamResponse, NodeFinishStreamResponse]]:
-        if workflow_node_execution.node_type in {NodeType.ITERATION, NodeType.LOOP}:
-            return None
-        if not workflow_node_execution.workflow_run_id:
-            return None
-        if not workflow_node_execution.finished_at:
-            return None
-
-        return NodeRetryStreamResponse(
-            task_id=task_id,
-            workflow_run_id=workflow_node_execution.workflow_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.inputs,
-                process_data=workflow_node_execution.process_data,
-                outputs=workflow_node_execution.outputs,
-                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,
-                iteration_id=event.in_iteration_id,
-                loop_id=event.in_loop_id,
-                retry_index=event.retry_index,
-            ),
-        )
-
-    def workflow_parallel_branch_start_to_stream_response(
-        self,
-        *,
-        task_id: str,
-        workflow_execution_id: str,
-        event: QueueParallelBranchRunStartedEvent,
-    ) -> ParallelBranchStartStreamResponse:
-        return ParallelBranchStartStreamResponse(
-            task_id=task_id,
-            workflow_run_id=workflow_execution_id,
-            data=ParallelBranchStartStreamResponse.Data(
-                parallel_id=event.parallel_id,
-                parallel_branch_id=event.parallel_start_node_id,
-                parent_parallel_id=event.parent_parallel_id,
-                parent_parallel_start_node_id=event.parent_parallel_start_node_id,
-                iteration_id=event.in_iteration_id,
-                loop_id=event.in_loop_id,
-                created_at=int(time.time()),
-            ),
-        )
-
-    def workflow_parallel_branch_finished_to_stream_response(
-        self,
-        *,
-        task_id: str,
-        workflow_execution_id: str,
-        event: QueueParallelBranchRunSucceededEvent | QueueParallelBranchRunFailedEvent,
-    ) -> ParallelBranchFinishedStreamResponse:
-        return ParallelBranchFinishedStreamResponse(
-            task_id=task_id,
-            workflow_run_id=workflow_execution_id,
-            data=ParallelBranchFinishedStreamResponse.Data(
-                parallel_id=event.parallel_id,
-                parallel_branch_id=event.parallel_start_node_id,
-                parent_parallel_id=event.parent_parallel_id,
-                parent_parallel_start_node_id=event.parent_parallel_start_node_id,
-                iteration_id=event.in_iteration_id,
-                loop_id=event.in_loop_id,
-                status="succeeded" if isinstance(event, QueueParallelBranchRunSucceededEvent) else "failed",
-                error=event.error if isinstance(event, QueueParallelBranchRunFailedEvent) else None,
-                created_at=int(time.time()),
-            ),
-        )
-
-    def workflow_iteration_start_to_stream_response(
-        self,
-        *,
-        task_id: str,
-        workflow_execution_id: str,
-        event: QueueIterationStartEvent,
-    ) -> IterationNodeStartStreamResponse:
-        return IterationNodeStartStreamResponse(
-            task_id=task_id,
-            workflow_run_id=workflow_execution_id,
-            data=IterationNodeStartStreamResponse.Data(
-                id=event.node_id,
-                node_id=event.node_id,
-                node_type=event.node_type.value,
-                title=event.node_data.title,
-                created_at=int(time.time()),
-                extras={},
-                inputs=event.inputs or {},
-                metadata=event.metadata or {},
-                parallel_id=event.parallel_id,
-                parallel_start_node_id=event.parallel_start_node_id,
-            ),
-        )
-
-    def workflow_iteration_next_to_stream_response(
-        self,
-        *,
-        task_id: str,
-        workflow_execution_id: str,
-        event: QueueIterationNextEvent,
-    ) -> IterationNodeNextStreamResponse:
-        return IterationNodeNextStreamResponse(
-            task_id=task_id,
-            workflow_run_id=workflow_execution_id,
-            data=IterationNodeNextStreamResponse.Data(
-                id=event.node_id,
-                node_id=event.node_id,
-                node_type=event.node_type.value,
-                title=event.node_data.title,
-                index=event.index,
-                pre_iteration_output=event.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,
-                duration=event.duration,
-            ),
-        )
-
-    def workflow_iteration_completed_to_stream_response(
-        self,
-        *,
-        task_id: str,
-        workflow_execution_id: str,
-        event: QueueIterationCompletedEvent,
-    ) -> IterationNodeCompletedStreamResponse:
-        return IterationNodeCompletedStreamResponse(
-            task_id=task_id,
-            workflow_run_id=workflow_execution_id,
-            data=IterationNodeCompletedStreamResponse.Data(
-                id=event.node_id,
-                node_id=event.node_id,
-                node_type=event.node_type.value,
-                title=event.node_data.title,
-                outputs=event.outputs,
-                created_at=int(time.time()),
-                extras={},
-                inputs=event.inputs or {},
-                status=WorkflowNodeExecutionStatus.SUCCEEDED
-                if event.error is None
-                else WorkflowNodeExecutionStatus.FAILED,
-                error=None,
-                elapsed_time=(datetime.now(UTC).replace(tzinfo=None) - event.start_at).total_seconds(),
-                total_tokens=event.metadata.get("total_tokens", 0) if event.metadata else 0,
-                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,
-            ),
-        )
-
-    def workflow_loop_start_to_stream_response(
-        self, *, task_id: str, workflow_execution_id: str, event: QueueLoopStartEvent
-    ) -> LoopNodeStartStreamResponse:
-        return LoopNodeStartStreamResponse(
-            task_id=task_id,
-            workflow_run_id=workflow_execution_id,
-            data=LoopNodeStartStreamResponse.Data(
-                id=event.node_id,
-                node_id=event.node_id,
-                node_type=event.node_type.value,
-                title=event.node_data.title,
-                created_at=int(time.time()),
-                extras={},
-                inputs=event.inputs or {},
-                metadata=event.metadata or {},
-                parallel_id=event.parallel_id,
-                parallel_start_node_id=event.parallel_start_node_id,
-            ),
-        )
-
-    def workflow_loop_next_to_stream_response(
-        self,
-        *,
-        task_id: str,
-        workflow_execution_id: str,
-        event: QueueLoopNextEvent,
-    ) -> LoopNodeNextStreamResponse:
-        return LoopNodeNextStreamResponse(
-            task_id=task_id,
-            workflow_run_id=workflow_execution_id,
-            data=LoopNodeNextStreamResponse.Data(
-                id=event.node_id,
-                node_id=event.node_id,
-                node_type=event.node_type.value,
-                title=event.node_data.title,
-                index=event.index,
-                pre_loop_output=event.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,
-                duration=event.duration,
-            ),
-        )
-
-    def workflow_loop_completed_to_stream_response(
-        self,
-        *,
-        task_id: str,
-        workflow_execution_id: str,
-        event: QueueLoopCompletedEvent,
-    ) -> LoopNodeCompletedStreamResponse:
-        return LoopNodeCompletedStreamResponse(
-            task_id=task_id,
-            workflow_run_id=workflow_execution_id,
-            data=LoopNodeCompletedStreamResponse.Data(
-                id=event.node_id,
-                node_id=event.node_id,
-                node_type=event.node_type.value,
-                title=event.node_data.title,
-                outputs=event.outputs,
-                created_at=int(time.time()),
-                extras={},
-                inputs=event.inputs or {},
-                status=WorkflowNodeExecutionStatus.SUCCEEDED
-                if event.error is None
-                else WorkflowNodeExecutionStatus.FAILED,
-                error=None,
-                elapsed_time=(datetime.now(UTC).replace(tzinfo=None) - event.start_at).total_seconds(),
-                total_tokens=event.metadata.get("total_tokens", 0) if event.metadata else 0,
-                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,
-            ),
-        )
-
-    def fetch_files_from_node_outputs(self, outputs_dict: Mapping[str, Any] | None) -> Sequence[Mapping[str, Any]]:
-        """
-        Fetch files from node outputs
-        :param outputs_dict: node outputs dict
-        :return:
-        """
-        if not outputs_dict:
-            return []
-
-        files = [self._fetch_files_from_variable_value(output_value) for output_value in outputs_dict.values()]
-        # Remove None
-        files = [file for file in files if file]
-        # Flatten list
-        # Flatten the list of sequences into a single list of mappings
-        flattened_files = [file for sublist in files if sublist for file in sublist]
-
-        # Convert to tuple to match Sequence type
-        return tuple(flattened_files)
-
-    def _fetch_files_from_variable_value(self, value: Union[dict, list]) -> Sequence[Mapping[str, Any]]:
-        """
-        Fetch files from variable value
-        :param value: variable value
-        :return:
-        """
-        if not value:
-            return []
-
-        files = []
-        if isinstance(value, list):
-            for item in value:
-                file = self._get_file_var_from_value(item)
-                if file:
-                    files.append(file)
-        elif isinstance(value, dict):
-            file = self._get_file_var_from_value(value)
-            if file:
-                files.append(file)
-
-        return files
-
-    def _get_file_var_from_value(self, value: Union[dict, list]) -> Mapping[str, Any] | None:
-        """
-        Get file var from value
-        :param value: variable value
-        :return:
-        """
-        if not value:
-            return None
-
-        if isinstance(value, dict) and value.get("dify_model_identity") == FILE_MODEL_IDENTITY:
-            return value
-        elif isinstance(value, File):
-            return value.to_dict()
-
-        return None
-
     def _get_workflow_execution_or_raise_error(self, id: str, /) -> WorkflowExecution:
         execution = self._workflow_execution_repository.get(id)
         if not execution:
             raise WorkflowRunNotFoundError(id)
         return execution
-
-    def handle_agent_log(self, task_id: str, event: QueueAgentLogEvent) -> AgentLogStreamResponse:
-        """
-        Handle agent log
-        :param task_id: task id
-        :param event: agent log event
-        :return:
-        """
-        return AgentLogStreamResponse(
-            task_id=task_id,
-            data=AgentLogStreamResponse.Data(
-                node_execution_id=event.node_execution_id,
-                id=event.id,
-                parent_id=event.parent_id,
-                label=event.label,
-                error=event.error,
-                status=event.status,
-                data=event.data,
-                metadata=event.metadata,
-                node_id=event.node_id,
-            ),
-        )