feat: Split WorkflowCycleManager (#20071)
Signed-off-by: -LAN- <laipz8200@outlook.com>
This commit is contained in:
-LAN-
0
api/core/app/apps/common/__init__.py
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0
api/core/app/apps/common/__init__.py
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564
api/core/app/apps/common/workflow_response_converter.py
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564
api/core/app/apps/common/workflow_response_converter.py
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@@ -0,0 +1,564 @@
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import time
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from collections.abc import Mapping, Sequence
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from datetime import UTC, datetime
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from typing import Any, Optional, Union, cast
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from sqlalchemy import select
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from sqlalchemy.orm import Session
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from core.app.entities.app_invoke_entities import AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity
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from core.app.entities.queue_entities import (
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QueueAgentLogEvent,
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QueueIterationCompletedEvent,
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QueueIterationNextEvent,
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QueueIterationStartEvent,
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QueueLoopCompletedEvent,
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QueueLoopNextEvent,
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QueueLoopStartEvent,
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QueueNodeExceptionEvent,
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QueueNodeFailedEvent,
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QueueNodeInIterationFailedEvent,
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QueueNodeInLoopFailedEvent,
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QueueNodeRetryEvent,
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QueueNodeStartedEvent,
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QueueNodeSucceededEvent,
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QueueParallelBranchRunFailedEvent,
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QueueParallelBranchRunStartedEvent,
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QueueParallelBranchRunSucceededEvent,
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)
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from core.app.entities.task_entities import (
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AgentLogStreamResponse,
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IterationNodeCompletedStreamResponse,
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IterationNodeNextStreamResponse,
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IterationNodeStartStreamResponse,
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LoopNodeCompletedStreamResponse,
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LoopNodeNextStreamResponse,
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LoopNodeStartStreamResponse,
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NodeFinishStreamResponse,
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NodeRetryStreamResponse,
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NodeStartStreamResponse,
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ParallelBranchFinishedStreamResponse,
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ParallelBranchStartStreamResponse,
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WorkflowFinishStreamResponse,
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WorkflowStartStreamResponse,
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)
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from core.file import FILE_MODEL_IDENTITY, File
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from core.tools.tool_manager import ToolManager
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from core.workflow.entities.node_execution_entities import NodeExecution
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from core.workflow.entities.workflow_execution_entities import WorkflowExecution
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from core.workflow.nodes import NodeType
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from core.workflow.nodes.tool.entities import ToolNodeData
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from models import (
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Account,
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CreatorUserRole,
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EndUser,
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WorkflowNodeExecutionStatus,
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WorkflowRun,
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)
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class WorkflowResponseConverter:
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def __init__(
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self,
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*,
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application_generate_entity: Union[AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity],
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) -> None:
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self._application_generate_entity = application_generate_entity
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def workflow_start_to_stream_response(
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self,
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*,
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task_id: str,
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workflow_execution: WorkflowExecution,
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) -> WorkflowStartStreamResponse:
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return WorkflowStartStreamResponse(
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task_id=task_id,
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workflow_run_id=workflow_execution.id,
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data=WorkflowStartStreamResponse.Data(
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id=workflow_execution.id,
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workflow_id=workflow_execution.workflow_id,
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sequence_number=workflow_execution.sequence_number,
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inputs=workflow_execution.inputs,
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created_at=int(workflow_execution.started_at.timestamp()),
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),
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)
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def workflow_finish_to_stream_response(
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self,
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*,
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session: Session,
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task_id: str,
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workflow_execution: WorkflowExecution,
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) -> WorkflowFinishStreamResponse:
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created_by = None
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workflow_run = session.scalar(select(WorkflowRun).where(WorkflowRun.id == workflow_execution.id))
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assert workflow_run is not None
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if workflow_run.created_by_role == CreatorUserRole.ACCOUNT:
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stmt = select(Account).where(Account.id == workflow_run.created_by)
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account = session.scalar(stmt)
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if account:
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created_by = {
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"id": account.id,
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"name": account.name,
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"email": account.email,
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}
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elif workflow_run.created_by_role == CreatorUserRole.END_USER:
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stmt = select(EndUser).where(EndUser.id == workflow_run.created_by)
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end_user = session.scalar(stmt)
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if end_user:
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created_by = {
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"id": end_user.id,
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"user": end_user.session_id,
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}
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else:
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raise NotImplementedError(f"unknown created_by_role: {workflow_run.created_by_role}")
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# Handle the case where finished_at is None by using current time as default
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finished_at_timestamp = (
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int(workflow_execution.finished_at.timestamp())
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if workflow_execution.finished_at
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else int(datetime.now(UTC).timestamp())
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)
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return WorkflowFinishStreamResponse(
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task_id=task_id,
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workflow_run_id=workflow_execution.id,
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data=WorkflowFinishStreamResponse.Data(
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id=workflow_execution.id,
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workflow_id=workflow_execution.workflow_id,
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sequence_number=workflow_execution.sequence_number,
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status=workflow_execution.status,
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outputs=workflow_execution.outputs,
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error=workflow_execution.error_message,
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elapsed_time=workflow_execution.elapsed_time,
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total_tokens=workflow_execution.total_tokens,
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total_steps=workflow_execution.total_steps,
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created_by=created_by,
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created_at=int(workflow_execution.started_at.timestamp()),
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finished_at=finished_at_timestamp,
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files=self.fetch_files_from_node_outputs(workflow_execution.outputs),
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exceptions_count=workflow_execution.exceptions_count,
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),
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)
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def workflow_node_start_to_stream_response(
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self,
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*,
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event: QueueNodeStartedEvent,
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task_id: str,
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workflow_node_execution: NodeExecution,
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) -> Optional[NodeStartStreamResponse]:
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if workflow_node_execution.node_type in {NodeType.ITERATION, NodeType.LOOP}:
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return None
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if not workflow_node_execution.workflow_run_id:
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return None
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response = NodeStartStreamResponse(
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task_id=task_id,
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workflow_run_id=workflow_node_execution.workflow_run_id,
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data=NodeStartStreamResponse.Data(
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id=workflow_node_execution.id,
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node_id=workflow_node_execution.node_id,
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node_type=workflow_node_execution.node_type,
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title=workflow_node_execution.title,
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index=workflow_node_execution.index,
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predecessor_node_id=workflow_node_execution.predecessor_node_id,
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inputs=workflow_node_execution.inputs,
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created_at=int(workflow_node_execution.created_at.timestamp()),
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parallel_id=event.parallel_id,
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parallel_start_node_id=event.parallel_start_node_id,
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parent_parallel_id=event.parent_parallel_id,
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parent_parallel_start_node_id=event.parent_parallel_start_node_id,
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iteration_id=event.in_iteration_id,
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loop_id=event.in_loop_id,
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parallel_run_id=event.parallel_mode_run_id,
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agent_strategy=event.agent_strategy,
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),
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)
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# extras logic
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if event.node_type == NodeType.TOOL:
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node_data = cast(ToolNodeData, event.node_data)
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response.data.extras["icon"] = ToolManager.get_tool_icon(
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tenant_id=self._application_generate_entity.app_config.tenant_id,
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provider_type=node_data.provider_type,
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provider_id=node_data.provider_id,
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)
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return response
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def workflow_node_finish_to_stream_response(
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self,
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*,
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event: QueueNodeSucceededEvent
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| QueueNodeFailedEvent
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| QueueNodeInIterationFailedEvent
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| QueueNodeInLoopFailedEvent
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| QueueNodeExceptionEvent,
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task_id: str,
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workflow_node_execution: NodeExecution,
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) -> Optional[NodeFinishStreamResponse]:
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if workflow_node_execution.node_type in {NodeType.ITERATION, NodeType.LOOP}:
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return None
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if not workflow_node_execution.workflow_run_id:
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return None
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if not workflow_node_execution.finished_at:
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return None
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return NodeFinishStreamResponse(
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task_id=task_id,
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workflow_run_id=workflow_node_execution.workflow_run_id,
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data=NodeFinishStreamResponse.Data(
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id=workflow_node_execution.id,
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node_id=workflow_node_execution.node_id,
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node_type=workflow_node_execution.node_type,
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index=workflow_node_execution.index,
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title=workflow_node_execution.title,
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predecessor_node_id=workflow_node_execution.predecessor_node_id,
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inputs=workflow_node_execution.inputs,
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process_data=workflow_node_execution.process_data,
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outputs=workflow_node_execution.outputs,
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status=workflow_node_execution.status,
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error=workflow_node_execution.error,
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elapsed_time=workflow_node_execution.elapsed_time,
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execution_metadata=workflow_node_execution.metadata,
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created_at=int(workflow_node_execution.created_at.timestamp()),
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finished_at=int(workflow_node_execution.finished_at.timestamp()),
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files=self.fetch_files_from_node_outputs(workflow_node_execution.outputs or {}),
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parallel_id=event.parallel_id,
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parallel_start_node_id=event.parallel_start_node_id,
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parent_parallel_id=event.parent_parallel_id,
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parent_parallel_start_node_id=event.parent_parallel_start_node_id,
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iteration_id=event.in_iteration_id,
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loop_id=event.in_loop_id,
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),
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)
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def workflow_node_retry_to_stream_response(
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self,
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*,
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event: QueueNodeRetryEvent,
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task_id: str,
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workflow_node_execution: NodeExecution,
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) -> Optional[Union[NodeRetryStreamResponse, NodeFinishStreamResponse]]:
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if workflow_node_execution.node_type in {NodeType.ITERATION, NodeType.LOOP}:
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return None
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if not workflow_node_execution.workflow_run_id:
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return None
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if not workflow_node_execution.finished_at:
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return None
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return NodeRetryStreamResponse(
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task_id=task_id,
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workflow_run_id=workflow_node_execution.workflow_run_id,
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data=NodeRetryStreamResponse.Data(
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id=workflow_node_execution.id,
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node_id=workflow_node_execution.node_id,
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node_type=workflow_node_execution.node_type,
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index=workflow_node_execution.index,
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title=workflow_node_execution.title,
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predecessor_node_id=workflow_node_execution.predecessor_node_id,
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inputs=workflow_node_execution.inputs,
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process_data=workflow_node_execution.process_data,
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outputs=workflow_node_execution.outputs,
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status=workflow_node_execution.status,
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error=workflow_node_execution.error,
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elapsed_time=workflow_node_execution.elapsed_time,
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execution_metadata=workflow_node_execution.metadata,
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created_at=int(workflow_node_execution.created_at.timestamp()),
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finished_at=int(workflow_node_execution.finished_at.timestamp()),
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files=self.fetch_files_from_node_outputs(workflow_node_execution.outputs or {}),
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parallel_id=event.parallel_id,
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parallel_start_node_id=event.parallel_start_node_id,
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parent_parallel_id=event.parent_parallel_id,
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parent_parallel_start_node_id=event.parent_parallel_start_node_id,
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iteration_id=event.in_iteration_id,
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loop_id=event.in_loop_id,
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retry_index=event.retry_index,
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),
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)
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def workflow_parallel_branch_start_to_stream_response(
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self,
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*,
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task_id: str,
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workflow_execution_id: str,
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event: QueueParallelBranchRunStartedEvent,
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) -> ParallelBranchStartStreamResponse:
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return ParallelBranchStartStreamResponse(
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task_id=task_id,
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workflow_run_id=workflow_execution_id,
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data=ParallelBranchStartStreamResponse.Data(
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parallel_id=event.parallel_id,
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parallel_branch_id=event.parallel_start_node_id,
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parent_parallel_id=event.parent_parallel_id,
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parent_parallel_start_node_id=event.parent_parallel_start_node_id,
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iteration_id=event.in_iteration_id,
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loop_id=event.in_loop_id,
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created_at=int(time.time()),
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),
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)
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def workflow_parallel_branch_finished_to_stream_response(
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self,
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*,
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task_id: str,
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workflow_execution_id: str,
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event: QueueParallelBranchRunSucceededEvent | QueueParallelBranchRunFailedEvent,
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) -> ParallelBranchFinishedStreamResponse:
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return ParallelBranchFinishedStreamResponse(
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task_id=task_id,
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workflow_run_id=workflow_execution_id,
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data=ParallelBranchFinishedStreamResponse.Data(
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parallel_id=event.parallel_id,
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parallel_branch_id=event.parallel_start_node_id,
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parent_parallel_id=event.parent_parallel_id,
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parent_parallel_start_node_id=event.parent_parallel_start_node_id,
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iteration_id=event.in_iteration_id,
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loop_id=event.in_loop_id,
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status="succeeded" if isinstance(event, QueueParallelBranchRunSucceededEvent) else "failed",
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error=event.error if isinstance(event, QueueParallelBranchRunFailedEvent) else None,
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created_at=int(time.time()),
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),
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)
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def workflow_iteration_start_to_stream_response(
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self,
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*,
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task_id: str,
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workflow_execution_id: str,
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event: QueueIterationStartEvent,
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) -> IterationNodeStartStreamResponse:
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return IterationNodeStartStreamResponse(
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task_id=task_id,
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workflow_run_id=workflow_execution_id,
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data=IterationNodeStartStreamResponse.Data(
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id=event.node_id,
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node_id=event.node_id,
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node_type=event.node_type.value,
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title=event.node_data.title,
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created_at=int(time.time()),
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extras={},
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inputs=event.inputs or {},
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metadata=event.metadata or {},
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parallel_id=event.parallel_id,
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parallel_start_node_id=event.parallel_start_node_id,
|
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),
|
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)
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def workflow_iteration_next_to_stream_response(
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self,
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*,
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task_id: str,
|
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workflow_execution_id: str,
|
||||
event: QueueIterationNextEvent,
|
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) -> IterationNodeNextStreamResponse:
|
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return IterationNodeNextStreamResponse(
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task_id=task_id,
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workflow_run_id=workflow_execution_id,
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data=IterationNodeNextStreamResponse.Data(
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id=event.node_id,
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node_id=event.node_id,
|
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node_type=event.node_type.value,
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title=event.node_data.title,
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index=event.index,
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pre_iteration_output=event.output,
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created_at=int(time.time()),
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extras={},
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parallel_id=event.parallel_id,
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parallel_start_node_id=event.parallel_start_node_id,
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parallel_mode_run_id=event.parallel_mode_run_id,
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duration=event.duration,
|
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),
|
||||
)
|
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|
||||
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,
|
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outputs=event.outputs,
|
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created_at=int(time.time()),
|
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extras={},
|
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inputs=event.inputs or {},
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status=WorkflowNodeExecutionStatus.SUCCEEDED
|
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if event.error is None
|
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else WorkflowNodeExecutionStatus.FAILED,
|
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error=None,
|
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elapsed_time=(datetime.now(UTC).replace(tzinfo=None) - event.start_at).total_seconds(),
|
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total_tokens=event.metadata.get("total_tokens", 0) if event.metadata else 0,
|
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execution_metadata=event.metadata,
|
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finished_at=int(time.time()),
|
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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 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,
|
||||
),
|
||||
)
|
||||
Reference in New Issue
Block a user