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feat: Parallel Execution of Nodes in Workflows (#8192)

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Co-authored-by: StyleZhang <jasonapring2015@outlook.com>
Co-authored-by: Yi <yxiaoisme@gmail.com>
Co-authored-by: -LAN- <laipz8200@outlook.com>
This commit is contained in:
takatost
2024-09-10 15:23:16 +08:00
committed by GitHub
parent 5da0182800
commit dabfd74622
156 changed files with 11158 additions and 5605 deletions
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14
api/core/app/task_pipeline/based_generate_task_pipeline.py
View File

@@ -68,16 +68,18 @@ class BasedGenerateTaskPipeline:
err = Exception(e.description if getattr(e, 'description', None) is not None else str(e))
if message:
message = db.session.query(Message).filter(Message.id == message.id).first()
err_desc = self._error_to_desc(err)
message.status = 'error'
message.error = err_desc
refetch_message = db.session.query(Message).filter(Message.id == message.id).first()
db.session.commit()
if refetch_message:
err_desc = self._error_to_desc(err)
refetch_message.status = 'error'
refetch_message.error = err_desc
db.session.commit()
return err
def _error_to_desc(cls, e: Exception) -> str:
def _error_to_desc(self, e: Exception) -> str:
"""
Error to desc.
:param e: exception

36
api/core/app/task_pipeline/message_cycle_manage.py
View File

@@ -8,7 +8,6 @@ from core.app.entities.app_invoke_entities import (
AgentChatAppGenerateEntity,
ChatAppGenerateEntity,
CompletionAppGenerateEntity,
InvokeFrom,
)
from core.app.entities.queue_entities import (
QueueAnnotationReplyEvent,
@@ -16,11 +15,11 @@ from core.app.entities.queue_entities import (
QueueRetrieverResourcesEvent,
)
from core.app.entities.task_entities import (
AdvancedChatTaskState,
EasyUITaskState,
MessageFileStreamResponse,
MessageReplaceStreamResponse,
MessageStreamResponse,
WorkflowTaskState,
)
from core.llm_generator.llm_generator import LLMGenerator
from core.tools.tool_file_manager import ToolFileManager
@@ -36,7 +35,7 @@ class MessageCycleManage:
AgentChatAppGenerateEntity,
AdvancedChatAppGenerateEntity
]
_task_state: Union[EasyUITaskState, AdvancedChatTaskState]
_task_state: Union[EasyUITaskState, WorkflowTaskState]
def _generate_conversation_name(self, conversation: Conversation, query: str) -> Optional[Thread]:
"""
@@ -45,6 +44,9 @@ class MessageCycleManage:
:param query: query
:return: thread
"""
if isinstance(self._application_generate_entity, CompletionAppGenerateEntity):
return None
is_first_message = self._application_generate_entity.conversation_id is None
extras = self._application_generate_entity.extras
auto_generate_conversation_name = extras.get('auto_generate_conversation_name', True)
@@ -52,7 +54,7 @@ class MessageCycleManage:
if auto_generate_conversation_name and is_first_message:
# start generate thread
thread = Thread(target=self._generate_conversation_name_worker, kwargs={
'flask_app': current_app._get_current_object(),
'flask_app': current_app._get_current_object(), # type: ignore
'conversation_id': conversation.id,
'query': query
})
@@ -75,6 +77,9 @@ class MessageCycleManage:
.first()
)
if not conversation:
return
if conversation.mode != AppMode.COMPLETION.value:
app_model = conversation.app
if not app_model:
@@ -121,34 +126,13 @@ class MessageCycleManage:
if self._application_generate_entity.app_config.additional_features.show_retrieve_source:
self._task_state.metadata['retriever_resources'] = event.retriever_resources
def _get_response_metadata(self) -> dict:
"""
Get response metadata by invoke from.
:return:
"""
metadata = {}
# show_retrieve_source
if 'retriever_resources' in self._task_state.metadata:
metadata['retriever_resources'] = self._task_state.metadata['retriever_resources']
# show annotation reply
if 'annotation_reply' in self._task_state.metadata:
metadata['annotation_reply'] = self._task_state.metadata['annotation_reply']
# show usage
if self._application_generate_entity.invoke_from in [InvokeFrom.DEBUGGER, InvokeFrom.SERVICE_API]:
metadata['usage'] = self._task_state.metadata['usage']
return metadata
def _message_file_to_stream_response(self, event: QueueMessageFileEvent) -> Optional[MessageFileStreamResponse]:
"""
Message file to stream response.
:param event: event
:return:
"""
message_file: MessageFile = (
message_file = (
db.session.query(MessageFile)
.filter(MessageFile.id == event.message_file_id)
.first()

663
api/core/app/task_pipeline/workflow_cycle_manage.py
View File

@@ -1,33 +1,41 @@
import json
import time
from datetime import datetime, timezone
from typing import Optional, Union, cast
from typing import Any, Optional, Union, cast
from core.app.entities.app_invoke_entities import InvokeFrom
from core.app.entities.app_invoke_entities import AdvancedChatAppGenerateEntity, InvokeFrom, WorkflowAppGenerateEntity
from core.app.entities.queue_entities import (
QueueIterationCompletedEvent,
QueueIterationNextEvent,
QueueIterationStartEvent,
QueueNodeFailedEvent,
QueueNodeStartedEvent,
QueueNodeSucceededEvent,
QueueStopEvent,
QueueWorkflowFailedEvent,
QueueWorkflowSucceededEvent,
QueueParallelBranchRunFailedEvent,
QueueParallelBranchRunStartedEvent,
QueueParallelBranchRunSucceededEvent,
)
from core.app.entities.task_entities import (
NodeExecutionInfo,
IterationNodeCompletedStreamResponse,
IterationNodeNextStreamResponse,
IterationNodeStartStreamResponse,
NodeFinishStreamResponse,
NodeStartStreamResponse,
ParallelBranchFinishedStreamResponse,
ParallelBranchStartStreamResponse,
WorkflowFinishStreamResponse,
WorkflowStartStreamResponse,
WorkflowTaskState,
)
from core.app.task_pipeline.workflow_iteration_cycle_manage import WorkflowIterationCycleManage
from core.file.file_obj import FileVar
from core.model_runtime.utils.encoders import jsonable_encoder
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, NodeType
from core.workflow.entities.node_entities import NodeType
from core.workflow.enums import SystemVariableKey
from core.workflow.nodes.tool.entities import ToolNodeData
from core.workflow.workflow_engine_manager import WorkflowEngineManager
from core.workflow.workflow_entry import WorkflowEntry
from extensions.ext_database import db
from models.account import Account
from models.model import EndUser
@@ -41,54 +49,56 @@ from models.workflow import (
WorkflowRunStatus,
WorkflowRunTriggeredFrom,
)
from services.workflow_service import WorkflowService
class WorkflowCycleManage(WorkflowIterationCycleManage):
def _init_workflow_run(self, workflow: Workflow,
triggered_from: WorkflowRunTriggeredFrom,
user: Union[Account, EndUser],
user_inputs: dict,
system_inputs: Optional[dict] = None) -> WorkflowRun:
"""
Init workflow run
:param workflow: Workflow instance
:param triggered_from: triggered from
:param user: account or end user
:param user_inputs: user variables inputs
:param system_inputs: system inputs, like: query, files
:return:
"""
max_sequence = db.session.query(db.func.max(WorkflowRun.sequence_number)) \
.filter(WorkflowRun.tenant_id == workflow.tenant_id) \
.filter(WorkflowRun.app_id == workflow.app_id) \
.scalar() or 0
class WorkflowCycleManage:
_application_generate_entity: Union[AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity]
_workflow: Workflow
_user: Union[Account, EndUser]
_task_state: WorkflowTaskState
_workflow_system_variables: dict[SystemVariableKey, Any]
def _handle_workflow_run_start(self) -> WorkflowRun:
max_sequence = (
db.session.query(db.func.max(WorkflowRun.sequence_number))
.filter(WorkflowRun.tenant_id == self._workflow.tenant_id)
.filter(WorkflowRun.app_id == self._workflow.app_id)
.scalar()
or 0
)
new_sequence_number = max_sequence + 1
inputs = {**user_inputs}
for key, value in (system_inputs or {}).items():
inputs = {**self._application_generate_entity.inputs}
for key, value in (self._workflow_system_variables or {}).items():
if key.value == 'conversation':
continue
inputs[f'sys.{key.value}'] = value
inputs = WorkflowEngineManager.handle_special_values(inputs)
inputs = WorkflowEntry.handle_special_values(inputs)
triggered_from= (
WorkflowRunTriggeredFrom.DEBUGGING
if self._application_generate_entity.invoke_from == InvokeFrom.DEBUGGER
else WorkflowRunTriggeredFrom.APP_RUN
)
# init workflow run
workflow_run = WorkflowRun(
tenant_id=workflow.tenant_id,
app_id=workflow.app_id,
sequence_number=new_sequence_number,
workflow_id=workflow.id,
type=workflow.type,
triggered_from=triggered_from.value,
version=workflow.version,
graph=workflow.graph,
inputs=json.dumps(inputs),
status=WorkflowRunStatus.RUNNING.value,
created_by_role=(CreatedByRole.ACCOUNT.value
if isinstance(user, Account) else CreatedByRole.END_USER.value),
created_by=user.id
workflow_run = WorkflowRun()
workflow_run.tenant_id = self._workflow.tenant_id
workflow_run.app_id = self._workflow.app_id
workflow_run.sequence_number = new_sequence_number
workflow_run.workflow_id = self._workflow.id
workflow_run.type = self._workflow.type
workflow_run.triggered_from = triggered_from.value
workflow_run.version = self._workflow.version
workflow_run.graph = self._workflow.graph
workflow_run.inputs = json.dumps(inputs)
workflow_run.status = WorkflowRunStatus.RUNNING.value
workflow_run.created_by_role = (
CreatedByRole.ACCOUNT.value if isinstance(self._user, Account) else CreatedByRole.END_USER.value
)
workflow_run.created_by = self._user.id
db.session.add(workflow_run)
db.session.commit()
@@ -97,33 +107,37 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
return workflow_run
def _workflow_run_success(
self, workflow_run: WorkflowRun,
def _handle_workflow_run_success(
self,
workflow_run: WorkflowRun,
start_at: float,
total_tokens: int,
total_steps: int,
outputs: Optional[str] = None,
conversation_id: Optional[str] = None,
trace_manager: Optional[TraceQueueManager] = None
trace_manager: Optional[TraceQueueManager] = None,
) -> WorkflowRun:
"""
Workflow run success
:param workflow_run: workflow run
:param start_at: start time
:param total_tokens: total tokens
:param total_steps: total steps
:param outputs: outputs
:param conversation_id: conversation id
:return:
"""
workflow_run = self._refetch_workflow_run(workflow_run.id)
workflow_run.status = WorkflowRunStatus.SUCCEEDED.value
workflow_run.outputs = outputs
workflow_run.elapsed_time = WorkflowService.get_elapsed_time(workflow_run_id=workflow_run.id)
workflow_run.elapsed_time = time.perf_counter() - start_at
workflow_run.total_tokens = total_tokens
workflow_run.total_steps = total_steps
workflow_run.finished_at = datetime.now(timezone.utc).replace(tzinfo=None)
db.session.commit()
db.session.refresh(workflow_run)
db.session.close()
if trace_manager:
trace_manager.add_trace_task(
@@ -135,34 +149,58 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
)
)
db.session.close()
return workflow_run
def _workflow_run_failed(
self, workflow_run: WorkflowRun,
def _handle_workflow_run_failed(
self,
workflow_run: WorkflowRun,
start_at: float,
total_tokens: int,
total_steps: int,
status: WorkflowRunStatus,
error: str,
conversation_id: Optional[str] = None,
trace_manager: Optional[TraceQueueManager] = None
trace_manager: Optional[TraceQueueManager] = None,
) -> WorkflowRun:
"""
Workflow run failed
:param workflow_run: workflow run
:param start_at: start time
:param total_tokens: total tokens
:param total_steps: total steps
:param status: status
:param error: error message
:return:
"""
workflow_run = self._refetch_workflow_run(workflow_run.id)
workflow_run.status = status.value
workflow_run.error = error
workflow_run.elapsed_time = WorkflowService.get_elapsed_time(workflow_run_id=workflow_run.id)
workflow_run.elapsed_time = time.perf_counter() - start_at
workflow_run.total_tokens = total_tokens
workflow_run.total_steps = total_steps
workflow_run.finished_at = datetime.now(timezone.utc).replace(tzinfo=None)
db.session.commit()
running_workflow_node_executions = db.session.query(WorkflowNodeExecution).filter(
WorkflowNodeExecution.tenant_id == workflow_run.tenant_id,
WorkflowNodeExecution.app_id == workflow_run.app_id,
WorkflowNodeExecution.workflow_id == workflow_run.workflow_id,
WorkflowNodeExecution.triggered_from == WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN.value,
WorkflowNodeExecution.workflow_run_id == workflow_run.id,
WorkflowNodeExecution.status == WorkflowNodeExecutionStatus.RUNNING.value
).all()
for workflow_node_execution in running_workflow_node_executions:
workflow_node_execution.status = WorkflowNodeExecutionStatus.FAILED.value
workflow_node_execution.error = error
workflow_node_execution.finished_at = datetime.now(timezone.utc).replace(tzinfo=None)
workflow_node_execution.elapsed_time = (workflow_node_execution.finished_at - workflow_node_execution.created_at).total_seconds()
db.session.commit()
db.session.refresh(workflow_run)
db.session.close()
@@ -178,39 +216,24 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
return workflow_run
def _init_node_execution_from_workflow_run(self, workflow_run: WorkflowRun,
node_id: str,
node_type: NodeType,
node_title: str,
node_run_index: int = 1,
predecessor_node_id: Optional[str] = None) -> WorkflowNodeExecution:
"""
Init workflow node execution from workflow run
:param workflow_run: workflow run
:param node_id: node id
:param node_type: node type
:param node_title: node title
:param node_run_index: run index
:param predecessor_node_id: predecessor node id if exists
:return:
"""
def _handle_node_execution_start(self, workflow_run: WorkflowRun, event: QueueNodeStartedEvent) -> WorkflowNodeExecution:
# init workflow node execution
workflow_node_execution = WorkflowNodeExecution(
tenant_id=workflow_run.tenant_id,
app_id=workflow_run.app_id,
workflow_id=workflow_run.workflow_id,
triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN.value,
workflow_run_id=workflow_run.id,
predecessor_node_id=predecessor_node_id,
index=node_run_index,
node_id=node_id,
node_type=node_type.value,
title=node_title,
status=WorkflowNodeExecutionStatus.RUNNING.value,
created_by_role=workflow_run.created_by_role,
created_by=workflow_run.created_by,
created_at=datetime.now(timezone.utc).replace(tzinfo=None)
)
workflow_node_execution = WorkflowNodeExecution()
workflow_node_execution.tenant_id = workflow_run.tenant_id
workflow_node_execution.app_id = workflow_run.app_id
workflow_node_execution.workflow_id = workflow_run.workflow_id
workflow_node_execution.triggered_from = WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN.value
workflow_node_execution.workflow_run_id = workflow_run.id
workflow_node_execution.predecessor_node_id = event.predecessor_node_id
workflow_node_execution.index = event.node_run_index
workflow_node_execution.node_execution_id = event.node_execution_id
workflow_node_execution.node_id = event.node_id
workflow_node_execution.node_type = event.node_type.value
workflow_node_execution.title = event.node_data.title
workflow_node_execution.status = WorkflowNodeExecutionStatus.RUNNING.value
workflow_node_execution.created_by_role = workflow_run.created_by_role
workflow_node_execution.created_by = workflow_run.created_by
workflow_node_execution.created_at = datetime.now(timezone.utc).replace(tzinfo=None)
db.session.add(workflow_node_execution)
db.session.commit()
@@ -219,33 +242,26 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
return workflow_node_execution
def _workflow_node_execution_success(self, workflow_node_execution: WorkflowNodeExecution,
start_at: float,
inputs: Optional[dict] = None,
process_data: Optional[dict] = None,
outputs: Optional[dict] = None,
execution_metadata: Optional[dict] = None) -> WorkflowNodeExecution:
def _handle_workflow_node_execution_success(self, event: QueueNodeSucceededEvent) -> WorkflowNodeExecution:
"""
Workflow node execution success
:param workflow_node_execution: workflow node execution
:param start_at: start time
:param inputs: inputs
:param process_data: process data
:param outputs: outputs
:param execution_metadata: execution metadata
:param event: queue node succeeded event
:return:
"""
inputs = WorkflowEngineManager.handle_special_values(inputs)
outputs = WorkflowEngineManager.handle_special_values(outputs)
workflow_node_execution = self._refetch_workflow_node_execution(event.node_execution_id)
inputs = WorkflowEntry.handle_special_values(event.inputs)
outputs = WorkflowEntry.handle_special_values(event.outputs)
workflow_node_execution.status = WorkflowNodeExecutionStatus.SUCCEEDED.value
workflow_node_execution.elapsed_time = time.perf_counter() - start_at
workflow_node_execution.inputs = json.dumps(inputs) if inputs else None
workflow_node_execution.process_data = json.dumps(process_data) if process_data else None
workflow_node_execution.process_data = json.dumps(event.process_data) if event.process_data else None
workflow_node_execution.outputs = json.dumps(outputs) if outputs else None
workflow_node_execution.execution_metadata = json.dumps(jsonable_encoder(execution_metadata)) \
if execution_metadata else None
workflow_node_execution.execution_metadata = (
json.dumps(jsonable_encoder(event.execution_metadata)) if event.execution_metadata else None
)
workflow_node_execution.finished_at = datetime.now(timezone.utc).replace(tzinfo=None)
workflow_node_execution.elapsed_time = (workflow_node_execution.finished_at - event.start_at).total_seconds()
db.session.commit()
db.session.refresh(workflow_node_execution)
@@ -253,33 +269,24 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
return workflow_node_execution
def _workflow_node_execution_failed(self, workflow_node_execution: WorkflowNodeExecution,
start_at: float,
error: str,
inputs: Optional[dict] = None,
process_data: Optional[dict] = None,
outputs: Optional[dict] = None,
execution_metadata: Optional[dict] = None
) -> WorkflowNodeExecution:
def _handle_workflow_node_execution_failed(self, event: QueueNodeFailedEvent) -> WorkflowNodeExecution:
"""
Workflow node execution failed
:param workflow_node_execution: workflow node execution
:param start_at: start time
:param error: error message
:param event: queue node failed event
:return:
"""
inputs = WorkflowEngineManager.handle_special_values(inputs)
outputs = WorkflowEngineManager.handle_special_values(outputs)
workflow_node_execution = self._refetch_workflow_node_execution(event.node_execution_id)
inputs = WorkflowEntry.handle_special_values(event.inputs)
outputs = WorkflowEntry.handle_special_values(event.outputs)
workflow_node_execution.status = WorkflowNodeExecutionStatus.FAILED.value
workflow_node_execution.error = error
workflow_node_execution.elapsed_time = time.perf_counter() - start_at
workflow_node_execution.error = event.error
workflow_node_execution.finished_at = datetime.now(timezone.utc).replace(tzinfo=None)
workflow_node_execution.inputs = json.dumps(inputs) if inputs else None
workflow_node_execution.process_data = json.dumps(process_data) if process_data else None
workflow_node_execution.process_data = json.dumps(event.process_data) if event.process_data else None
workflow_node_execution.outputs = json.dumps(outputs) if outputs else None
workflow_node_execution.execution_metadata = json.dumps(jsonable_encoder(execution_metadata)) \
if execution_metadata else None
workflow_node_execution.elapsed_time = (workflow_node_execution.finished_at - event.start_at).total_seconds()
db.session.commit()
db.session.refresh(workflow_node_execution)
@@ -287,8 +294,13 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
return workflow_node_execution
def _workflow_start_to_stream_response(self, task_id: str,
workflow_run: WorkflowRun) -> WorkflowStartStreamResponse:
#################################################
# to stream responses #
#################################################
def _workflow_start_to_stream_response(
self, task_id: str, workflow_run: WorkflowRun
) -> WorkflowStartStreamResponse:
"""
Workflow start to stream response.
:param task_id: task id
@@ -302,13 +314,14 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
id=workflow_run.id,
workflow_id=workflow_run.workflow_id,
sequence_number=workflow_run.sequence_number,
inputs=workflow_run.inputs_dict,
created_at=int(workflow_run.created_at.timestamp())
)
inputs=workflow_run.inputs_dict or {},
created_at=int(workflow_run.created_at.timestamp()),
),
)
def _workflow_finish_to_stream_response(self, task_id: str,
workflow_run: WorkflowRun) -> WorkflowFinishStreamResponse:
def _workflow_finish_to_stream_response(
self, task_id: str, workflow_run: WorkflowRun
) -> WorkflowFinishStreamResponse:
"""
Workflow finish to stream response.
:param task_id: task id
@@ -320,16 +333,16 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
created_by_account = workflow_run.created_by_account
if created_by_account:
created_by = {
"id": created_by_account.id,
"name": created_by_account.name,
"email": created_by_account.email,
'id': created_by_account.id,
'name': created_by_account.name,
'email': created_by_account.email,
}
else:
created_by_end_user = workflow_run.created_by_end_user
if created_by_end_user:
created_by = {
"id": created_by_end_user.id,
"user": created_by_end_user.session_id,
'id': created_by_end_user.id,
'user': created_by_end_user.session_id,
}
return WorkflowFinishStreamResponse(
@@ -348,14 +361,13 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
created_by=created_by,
created_at=int(workflow_run.created_at.timestamp()),
finished_at=int(workflow_run.finished_at.timestamp()),
files=self._fetch_files_from_node_outputs(workflow_run.outputs_dict)
)
files=self._fetch_files_from_node_outputs(workflow_run.outputs_dict or {}),
),
)
def _workflow_node_start_to_stream_response(self, event: QueueNodeStartedEvent,
task_id: str,
workflow_node_execution: WorkflowNodeExecution) \
-> NodeStartStreamResponse:
def _workflow_node_start_to_stream_response(
self, event: QueueNodeStartedEvent, task_id: str, workflow_node_execution: WorkflowNodeExecution
) -> Optional[NodeStartStreamResponse]:
"""
Workflow node start to stream response.
:param event: queue node started event
@@ -363,6 +375,9 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
:param workflow_node_execution: workflow node execution
:return:
"""
if workflow_node_execution.node_type in [NodeType.ITERATION.value, NodeType.LOOP.value]:
return None
response = NodeStartStreamResponse(
task_id=task_id,
workflow_run_id=workflow_node_execution.workflow_run_id,
@@ -374,8 +389,13 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
index=workflow_node_execution.index,
predecessor_node_id=workflow_node_execution.predecessor_node_id,
inputs=workflow_node_execution.inputs_dict,
created_at=int(workflow_node_execution.created_at.timestamp())
)
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,
),
)
# extras logic
@@ -384,19 +404,27 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
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
provider_id=node_data.provider_id,
)
return response
def _workflow_node_finish_to_stream_response(self, task_id: str, workflow_node_execution: WorkflowNodeExecution) \
-> NodeFinishStreamResponse:
def _workflow_node_finish_to_stream_response(
self,
event: QueueNodeSucceededEvent | QueueNodeFailedEvent,
task_id: str,
workflow_node_execution: WorkflowNodeExecution
) -> Optional[NodeFinishStreamResponse]:
"""
Workflow node finish to stream response.
:param event: queue node succeeded or failed event
:param task_id: task id
:param workflow_node_execution: workflow node execution
:return:
"""
if workflow_node_execution.node_type in [NodeType.ITERATION.value, NodeType.LOOP.value]:
return None
return NodeFinishStreamResponse(
task_id=task_id,
workflow_run_id=workflow_node_execution.workflow_run_id,
@@ -416,181 +444,155 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
execution_metadata=workflow_node_execution.execution_metadata_dict,
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_dict)
files=self._fetch_files_from_node_outputs(workflow_node_execution.outputs_dict 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,
),
)
def _workflow_parallel_branch_start_to_stream_response(
self,
task_id: str,
workflow_run: WorkflowRun,
event: QueueParallelBranchRunStartedEvent
) -> ParallelBranchStartStreamResponse:
"""
Workflow parallel branch start to stream response
:param task_id: task id
:param workflow_run: workflow run
:param event: parallel branch run started event
:return:
"""
return ParallelBranchStartStreamResponse(
task_id=task_id,
workflow_run_id=workflow_run.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,
created_at=int(time.time()),
)
)
def _workflow_parallel_branch_finished_to_stream_response(
self,
task_id: str,
workflow_run: WorkflowRun,
event: QueueParallelBranchRunSucceededEvent | QueueParallelBranchRunFailedEvent
) -> ParallelBranchFinishedStreamResponse:
"""
Workflow parallel branch finished to stream response
:param task_id: task id
:param workflow_run: workflow run
:param event: parallel branch run succeeded or failed event
:return:
"""
return ParallelBranchFinishedStreamResponse(
task_id=task_id,
workflow_run_id=workflow_run.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,
status='succeeded' if isinstance(event, QueueParallelBranchRunSucceededEvent) else 'failed',
error=event.error if isinstance(event, QueueParallelBranchRunFailedEvent) else None,
created_at=int(time.time()),
)
)
def _handle_workflow_start(self) -> WorkflowRun:
self._task_state.start_at = time.perf_counter()
workflow_run = self._init_workflow_run(
workflow=self._workflow,
triggered_from=WorkflowRunTriggeredFrom.DEBUGGING
if self._application_generate_entity.invoke_from == InvokeFrom.DEBUGGER
else WorkflowRunTriggeredFrom.APP_RUN,
user=self._user,
user_inputs=self._application_generate_entity.inputs,
system_inputs=self._workflow_system_variables
def _workflow_iteration_start_to_stream_response(
self,
task_id: str,
workflow_run: WorkflowRun,
event: QueueIterationStartEvent
) -> IterationNodeStartStreamResponse:
"""
Workflow iteration start to stream response
:param task_id: task id
:param workflow_run: workflow run
:param event: iteration start event
:return:
"""
return IterationNodeStartStreamResponse(
task_id=task_id,
workflow_run_id=workflow_run.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,
)
)
self._task_state.workflow_run_id = workflow_run.id
db.session.close()
return workflow_run
def _handle_node_start(self, event: QueueNodeStartedEvent) -> WorkflowNodeExecution:
workflow_run = db.session.query(WorkflowRun).filter(WorkflowRun.id == self._task_state.workflow_run_id).first()
workflow_node_execution = self._init_node_execution_from_workflow_run(
workflow_run=workflow_run,
node_id=event.node_id,
node_type=event.node_type,
node_title=event.node_data.title,
node_run_index=event.node_run_index,
predecessor_node_id=event.predecessor_node_id
def _workflow_iteration_next_to_stream_response(self, task_id: str, workflow_run: WorkflowRun, event: QueueIterationNextEvent) -> IterationNodeNextStreamResponse:
"""
Workflow iteration next to stream response
:param task_id: task id
:param workflow_run: workflow run
:param event: iteration next event
:return:
"""
return IterationNodeNextStreamResponse(
task_id=task_id,
workflow_run_id=workflow_run.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,
)
)
latest_node_execution_info = NodeExecutionInfo(
workflow_node_execution_id=workflow_node_execution.id,
node_type=event.node_type,
start_at=time.perf_counter()
)
self._task_state.ran_node_execution_infos[event.node_id] = latest_node_execution_info
self._task_state.latest_node_execution_info = latest_node_execution_info
self._task_state.total_steps += 1
db.session.close()
return workflow_node_execution
def _handle_node_finished(self, event: QueueNodeSucceededEvent | QueueNodeFailedEvent) -> WorkflowNodeExecution:
current_node_execution = self._task_state.ran_node_execution_infos[event.node_id]
workflow_node_execution = db.session.query(WorkflowNodeExecution).filter(
WorkflowNodeExecution.id == current_node_execution.workflow_node_execution_id).first()
execution_metadata = event.execution_metadata if isinstance(event, QueueNodeSucceededEvent) else None
if self._iteration_state and self._iteration_state.current_iterations:
if not execution_metadata:
execution_metadata = {}
current_iteration_data = None
for iteration_node_id in self._iteration_state.current_iterations:
data = self._iteration_state.current_iterations[iteration_node_id]
if data.parent_iteration_id == None:
current_iteration_data = data
break
if current_iteration_data:
execution_metadata[NodeRunMetadataKey.ITERATION_ID] = current_iteration_data.iteration_id
execution_metadata[NodeRunMetadataKey.ITERATION_INDEX] = current_iteration_data.current_index
if isinstance(event, QueueNodeSucceededEvent):
workflow_node_execution = self._workflow_node_execution_success(
workflow_node_execution=workflow_node_execution,
start_at=current_node_execution.start_at,
inputs=event.inputs,
process_data=event.process_data,
def _workflow_iteration_completed_to_stream_response(self, task_id: str, workflow_run: WorkflowRun, event: QueueIterationCompletedEvent) -> IterationNodeCompletedStreamResponse:
"""
Workflow iteration completed to stream response
:param task_id: task id
:param workflow_run: workflow run
:param event: iteration completed event
:return:
"""
return IterationNodeCompletedStreamResponse(
task_id=task_id,
workflow_run_id=workflow_run.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,
execution_metadata=execution_metadata
created_at=int(time.time()),
extras={},
inputs=event.inputs or {},
status=WorkflowNodeExecutionStatus.SUCCEEDED,
error=None,
elapsed_time=(datetime.now(timezone.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,
)
if execution_metadata and execution_metadata.get(NodeRunMetadataKey.TOTAL_TOKENS):
self._task_state.total_tokens += (
int(execution_metadata.get(NodeRunMetadataKey.TOTAL_TOKENS)))
if self._iteration_state:
for iteration_node_id in self._iteration_state.current_iterations:
data = self._iteration_state.current_iterations[iteration_node_id]
if execution_metadata.get(NodeRunMetadataKey.TOTAL_TOKENS):
data.total_tokens += int(execution_metadata.get(NodeRunMetadataKey.TOTAL_TOKENS))
if workflow_node_execution.node_type == NodeType.LLM.value:
outputs = workflow_node_execution.outputs_dict
usage_dict = outputs.get('usage', {})
self._task_state.metadata['usage'] = usage_dict
else:
workflow_node_execution = self._workflow_node_execution_failed(
workflow_node_execution=workflow_node_execution,
start_at=current_node_execution.start_at,
error=event.error,
inputs=event.inputs,
process_data=event.process_data,
outputs=event.outputs,
execution_metadata=execution_metadata
)
db.session.close()
return workflow_node_execution
def _handle_workflow_finished(
self, event: QueueStopEvent | QueueWorkflowSucceededEvent | QueueWorkflowFailedEvent,
conversation_id: Optional[str] = None,
trace_manager: Optional[TraceQueueManager] = None
) -> Optional[WorkflowRun]:
workflow_run = db.session.query(WorkflowRun).filter(
WorkflowRun.id == self._task_state.workflow_run_id).first()
if not workflow_run:
return None
if conversation_id is None:
conversation_id = self._application_generate_entity.inputs.get('sys.conversation_id')
if isinstance(event, QueueStopEvent):
workflow_run = self._workflow_run_failed(
workflow_run=workflow_run,
total_tokens=self._task_state.total_tokens,
total_steps=self._task_state.total_steps,
status=WorkflowRunStatus.STOPPED,
error='Workflow stopped.',
conversation_id=conversation_id,
trace_manager=trace_manager
)
latest_node_execution_info = self._task_state.latest_node_execution_info
if latest_node_execution_info:
workflow_node_execution = db.session.query(WorkflowNodeExecution).filter(
WorkflowNodeExecution.id == latest_node_execution_info.workflow_node_execution_id).first()
if (workflow_node_execution
and workflow_node_execution.status == WorkflowNodeExecutionStatus.RUNNING.value):
self._workflow_node_execution_failed(
workflow_node_execution=workflow_node_execution,
start_at=latest_node_execution_info.start_at,
error='Workflow stopped.'
)
elif isinstance(event, QueueWorkflowFailedEvent):
workflow_run = self._workflow_run_failed(
workflow_run=workflow_run,
total_tokens=self._task_state.total_tokens,
total_steps=self._task_state.total_steps,
status=WorkflowRunStatus.FAILED,
error=event.error,
conversation_id=conversation_id,
trace_manager=trace_manager
)
else:
if self._task_state.latest_node_execution_info:
workflow_node_execution = db.session.query(WorkflowNodeExecution).filter(
WorkflowNodeExecution.id == self._task_state.latest_node_execution_info.workflow_node_execution_id).first()
outputs = workflow_node_execution.outputs
else:
outputs = None
workflow_run = self._workflow_run_success(
workflow_run=workflow_run,
total_tokens=self._task_state.total_tokens,
total_steps=self._task_state.total_steps,
outputs=outputs,
conversation_id=conversation_id,
trace_manager=trace_manager
)
self._task_state.workflow_run_id = workflow_run.id
db.session.close()
return workflow_run
)
def _fetch_files_from_node_outputs(self, outputs_dict: dict) -> list[dict]:
"""
@@ -647,3 +649,40 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
return value.to_dict()
return None
def _refetch_workflow_run(self, workflow_run_id: str) -> WorkflowRun:
"""
Refetch workflow run
:param workflow_run_id: workflow run id
:return:
"""
workflow_run = db.session.query(WorkflowRun).filter(
WorkflowRun.id == workflow_run_id).first()
if not workflow_run:
raise Exception(f'Workflow run not found: {workflow_run_id}')
return workflow_run
def _refetch_workflow_node_execution(self, node_execution_id: str) -> WorkflowNodeExecution:
"""
Refetch workflow node execution
:param node_execution_id: workflow node execution id
:return:
"""
workflow_node_execution = (
db.session.query(WorkflowNodeExecution)
.filter(
WorkflowNodeExecution.tenant_id == self._application_generate_entity.app_config.tenant_id,
WorkflowNodeExecution.app_id == self._application_generate_entity.app_config.app_id,
WorkflowNodeExecution.workflow_id == self._workflow.id,
WorkflowNodeExecution.triggered_from == WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN.value,
WorkflowNodeExecution.node_execution_id == node_execution_id,
)
.first()
)
if not workflow_node_execution:
raise Exception(f'Workflow node execution not found: {node_execution_id}')
return workflow_node_execution

16
api/core/app/task_pipeline/workflow_cycle_state_manager.py
View File

@@ -1,16 +0,0 @@
from typing import Any, Union
from core.app.entities.app_invoke_entities import AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity
from core.app.entities.task_entities import AdvancedChatTaskState, WorkflowTaskState
from core.workflow.enums import SystemVariableKey
from models.account import Account
from models.model import EndUser
from models.workflow import Workflow
class WorkflowCycleStateManager:
_application_generate_entity: Union[AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity]
_workflow: Workflow
_user: Union[Account, EndUser]
_task_state: Union[AdvancedChatTaskState, WorkflowTaskState]
_workflow_system_variables: dict[SystemVariableKey, Any]

290
api/core/app/task_pipeline/workflow_iteration_cycle_manage.py
View File

@@ -1,290 +0,0 @@
import json
import time
from collections.abc import Generator
from datetime import datetime, timezone
from typing import Optional, Union
from core.app.entities.queue_entities import (
QueueIterationCompletedEvent,
QueueIterationNextEvent,
QueueIterationStartEvent,
)
from core.app.entities.task_entities import (
IterationNodeCompletedStreamResponse,
IterationNodeNextStreamResponse,
IterationNodeStartStreamResponse,
NodeExecutionInfo,
WorkflowIterationState,
)
from core.app.task_pipeline.workflow_cycle_state_manager import WorkflowCycleStateManager
from core.workflow.entities.node_entities import NodeType
from core.workflow.workflow_engine_manager import WorkflowEngineManager
from extensions.ext_database import db
from models.workflow import (
WorkflowNodeExecution,
WorkflowNodeExecutionStatus,
WorkflowNodeExecutionTriggeredFrom,
WorkflowRun,
)
class WorkflowIterationCycleManage(WorkflowCycleStateManager):
_iteration_state: WorkflowIterationState = None
def _init_iteration_state(self) -> WorkflowIterationState:
if not self._iteration_state:
self._iteration_state = WorkflowIterationState(
current_iterations={}
)
def _handle_iteration_to_stream_response(self, task_id: str, event: QueueIterationStartEvent | QueueIterationNextEvent | QueueIterationCompletedEvent) \
-> Union[IterationNodeStartStreamResponse, IterationNodeNextStreamResponse, IterationNodeCompletedStreamResponse]:
"""
Handle iteration to stream response
:param task_id: task id
:param event: iteration event
:return:
"""
if isinstance(event, QueueIterationStartEvent):
return IterationNodeStartStreamResponse(
task_id=task_id,
workflow_run_id=self._task_state.workflow_run_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,
metadata=event.metadata
)
)
elif isinstance(event, QueueIterationNextEvent):
current_iteration = self._iteration_state.current_iterations[event.node_id]
return IterationNodeNextStreamResponse(
task_id=task_id,
workflow_run_id=self._task_state.workflow_run_id,
data=IterationNodeNextStreamResponse.Data(
id=event.node_id,
node_id=event.node_id,
node_type=event.node_type.value,
title=current_iteration.node_data.title,
index=event.index,
pre_iteration_output=event.output,
created_at=int(time.time()),
extras={}
)
)
elif isinstance(event, QueueIterationCompletedEvent):
current_iteration = self._iteration_state.current_iterations[event.node_id]
return IterationNodeCompletedStreamResponse(
task_id=task_id,
workflow_run_id=self._task_state.workflow_run_id,
data=IterationNodeCompletedStreamResponse.Data(
id=event.node_id,
node_id=event.node_id,
node_type=event.node_type.value,
title=current_iteration.node_data.title,
outputs=event.outputs,
created_at=int(time.time()),
extras={},
inputs=current_iteration.inputs,
status=WorkflowNodeExecutionStatus.SUCCEEDED,
error=None,
elapsed_time=time.perf_counter() - current_iteration.started_at,
total_tokens=current_iteration.total_tokens,
execution_metadata={
'total_tokens': current_iteration.total_tokens,
},
finished_at=int(time.time()),
steps=current_iteration.current_index
)
)
def _init_iteration_execution_from_workflow_run(self,
workflow_run: WorkflowRun,
node_id: str,
node_type: NodeType,
node_title: str,
node_run_index: int = 1,
inputs: Optional[dict] = None,
predecessor_node_id: Optional[str] = None
) -> WorkflowNodeExecution:
workflow_node_execution = WorkflowNodeExecution(
tenant_id=workflow_run.tenant_id,
app_id=workflow_run.app_id,
workflow_id=workflow_run.workflow_id,
triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN.value,
workflow_run_id=workflow_run.id,
predecessor_node_id=predecessor_node_id,
index=node_run_index,
node_id=node_id,
node_type=node_type.value,
inputs=json.dumps(inputs) if inputs else None,
title=node_title,
status=WorkflowNodeExecutionStatus.RUNNING.value,
created_by_role=workflow_run.created_by_role,
created_by=workflow_run.created_by,
execution_metadata=json.dumps({
'started_run_index': node_run_index + 1,
'current_index': 0,
'steps_boundary': [],
}),
created_at=datetime.now(timezone.utc).replace(tzinfo=None)
)
db.session.add(workflow_node_execution)
db.session.commit()
db.session.refresh(workflow_node_execution)
db.session.close()
return workflow_node_execution
def _handle_iteration_operation(self, event: QueueIterationStartEvent | QueueIterationNextEvent | QueueIterationCompletedEvent) -> WorkflowNodeExecution:
if isinstance(event, QueueIterationStartEvent):
return self._handle_iteration_started(event)
elif isinstance(event, QueueIterationNextEvent):
return self._handle_iteration_next(event)
elif isinstance(event, QueueIterationCompletedEvent):
return self._handle_iteration_completed(event)
def _handle_iteration_started(self, event: QueueIterationStartEvent) -> WorkflowNodeExecution:
self._init_iteration_state()
workflow_run = db.session.query(WorkflowRun).filter(WorkflowRun.id == self._task_state.workflow_run_id).first()
workflow_node_execution = self._init_iteration_execution_from_workflow_run(
workflow_run=workflow_run,
node_id=event.node_id,
node_type=NodeType.ITERATION,
node_title=event.node_data.title,
node_run_index=event.node_run_index,
inputs=event.inputs,
predecessor_node_id=event.predecessor_node_id
)
latest_node_execution_info = NodeExecutionInfo(
workflow_node_execution_id=workflow_node_execution.id,
node_type=NodeType.ITERATION,
start_at=time.perf_counter()
)
self._task_state.ran_node_execution_infos[event.node_id] = latest_node_execution_info
self._task_state.latest_node_execution_info = latest_node_execution_info
self._iteration_state.current_iterations[event.node_id] = WorkflowIterationState.Data(
parent_iteration_id=None,
iteration_id=event.node_id,
current_index=0,
iteration_steps_boundary=[],
node_execution_id=workflow_node_execution.id,
started_at=time.perf_counter(),
inputs=event.inputs,
total_tokens=0,
node_data=event.node_data
)
db.session.close()
return workflow_node_execution
def _handle_iteration_next(self, event: QueueIterationNextEvent) -> WorkflowNodeExecution:
if event.node_id not in self._iteration_state.current_iterations:
return
current_iteration = self._iteration_state.current_iterations[event.node_id]
current_iteration.current_index = event.index
current_iteration.iteration_steps_boundary.append(event.node_run_index)
workflow_node_execution: WorkflowNodeExecution = db.session.query(WorkflowNodeExecution).filter(
WorkflowNodeExecution.id == current_iteration.node_execution_id
).first()
original_node_execution_metadata = workflow_node_execution.execution_metadata_dict
if original_node_execution_metadata:
original_node_execution_metadata['current_index'] = event.index
original_node_execution_metadata['steps_boundary'] = current_iteration.iteration_steps_boundary
original_node_execution_metadata['total_tokens'] = current_iteration.total_tokens
workflow_node_execution.execution_metadata = json.dumps(original_node_execution_metadata)
db.session.commit()
db.session.close()
def _handle_iteration_completed(self, event: QueueIterationCompletedEvent):
if event.node_id not in self._iteration_state.current_iterations:
return
current_iteration = self._iteration_state.current_iterations[event.node_id]
workflow_node_execution: WorkflowNodeExecution = db.session.query(WorkflowNodeExecution).filter(
WorkflowNodeExecution.id == current_iteration.node_execution_id
).first()
workflow_node_execution.status = WorkflowNodeExecutionStatus.SUCCEEDED.value
workflow_node_execution.outputs = json.dumps(WorkflowEngineManager.handle_special_values(event.outputs)) if event.outputs else None
workflow_node_execution.elapsed_time = time.perf_counter() - current_iteration.started_at
original_node_execution_metadata = workflow_node_execution.execution_metadata_dict
if original_node_execution_metadata:
original_node_execution_metadata['steps_boundary'] = current_iteration.iteration_steps_boundary
original_node_execution_metadata['total_tokens'] = current_iteration.total_tokens
workflow_node_execution.execution_metadata = json.dumps(original_node_execution_metadata)
db.session.commit()
# remove current iteration
self._iteration_state.current_iterations.pop(event.node_id, None)
# set latest node execution info
latest_node_execution_info = NodeExecutionInfo(
workflow_node_execution_id=workflow_node_execution.id,
node_type=NodeType.ITERATION,
start_at=time.perf_counter()
)
self._task_state.latest_node_execution_info = latest_node_execution_info
db.session.close()
def _handle_iteration_exception(self, task_id: str, error: str) -> Generator[IterationNodeCompletedStreamResponse, None, None]:
"""
Handle iteration exception
"""
if not self._iteration_state or not self._iteration_state.current_iterations:
return
for node_id, current_iteration in self._iteration_state.current_iterations.items():
workflow_node_execution: WorkflowNodeExecution = db.session.query(WorkflowNodeExecution).filter(
WorkflowNodeExecution.id == current_iteration.node_execution_id
).first()
workflow_node_execution.status = WorkflowNodeExecutionStatus.FAILED.value
workflow_node_execution.error = error
workflow_node_execution.elapsed_time = time.perf_counter() - current_iteration.started_at
db.session.commit()
db.session.close()
yield IterationNodeCompletedStreamResponse(
task_id=task_id,
workflow_run_id=self._task_state.workflow_run_id,
data=IterationNodeCompletedStreamResponse.Data(
id=node_id,
node_id=node_id,
node_type=NodeType.ITERATION.value,
title=current_iteration.node_data.title,
outputs={},
created_at=int(time.time()),
extras={},
inputs=current_iteration.inputs,
status=WorkflowNodeExecutionStatus.FAILED,
error=error,
elapsed_time=time.perf_counter() - current_iteration.started_at,
total_tokens=current_iteration.total_tokens,
execution_metadata={
'total_tokens': current_iteration.total_tokens,
},
finished_at=int(time.time()),
steps=current_iteration.current_index
)
)