Skip to content

D
dify
Commit 6cfda369 authored by takatost's avatar takatost
Browse files
Options

refactor workflow runner

parent 5a57ed25
Hide whitespace changes
Inline Side-by-side
Showing with 996 additions and 501 deletions
api/controllers/console/app/workflow.py
View file @ 6cfda369
......@@ -147,9 +147,12 @@ class WorkflowTaskStopApi(Resource):
"""
Stop workflow task
"""
# TODO
workflow_service = WorkflowService()
workflow_service.stop_workflow_task(app_model=app_model, task_id=task_id, account=current_user)
workflow_service.stop_workflow_task(
task_id=task_id,
user=current_user,
invoke_from=InvokeFrom.DEBUGGER
)
return {
"result": "success"
......
api/core/app/apps/advanced_chat/app_generator.py
View file @ 6cfda369
......@@ -11,7 +11,7 @@ from core.app.app_config.features.file_upload.manager import FileUploadConfigMan
from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfigManager
from core.app.apps.advanced_chat.app_runner import AdvancedChatAppRunner
from core.app.apps.advanced_chat.generate_task_pipeline import AdvancedChatAppGenerateTaskPipeline
from core.app.apps.base_app_queue_manager import AppQueueManager, ConversationTaskStoppedException, PublishFrom
from core.app.apps.base_app_queue_manager import AppQueueManager, GenerateTaskStoppedException, PublishFrom
from core.app.apps.message_based_app_generator import MessageBasedAppGenerator
from core.app.apps.message_based_app_queue_manager import MessageBasedAppQueueManager
from core.app.entities.app_invoke_entities import AdvancedChatAppGenerateEntity, InvokeFrom
......@@ -123,11 +123,13 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
worker_thread.start()
# return response or stream generator
return self._handle_response(
return self._handle_advanced_chat_response(
application_generate_entity=application_generate_entity,
workflow=workflow,
queue_manager=queue_manager,
conversation=conversation,
message=message,
user=user,
stream=stream
)
......@@ -159,7 +161,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
conversation=conversation,
message=message
)
except ConversationTaskStoppedException:
except GenerateTaskStoppedException:
pass
except InvokeAuthorizationError:
queue_manager.publish_error(
......@@ -177,33 +179,40 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
finally:
db.session.remove()
def _handle_response(self, application_generate_entity: AdvancedChatAppGenerateEntity,
queue_manager: AppQueueManager,
conversation: Conversation,
message: Message,
stream: bool = False) -> Union[dict, Generator]:
def _handle_advanced_chat_response(self, application_generate_entity: AdvancedChatAppGenerateEntity,
workflow: Workflow,
queue_manager: AppQueueManager,
conversation: Conversation,
message: Message,
user: Union[Account, EndUser],
stream: bool = False) -> Union[dict, Generator]:
"""
Handle response.
:param application_generate_entity: application generate entity
:param workflow: workflow
:param queue_manager: queue manager
:param conversation: conversation
:param message: message
:param user: account or end user
:param stream: is stream
:return:
"""
# init generate task pipeline
generate_task_pipeline = AdvancedChatAppGenerateTaskPipeline(
application_generate_entity=application_generate_entity,
workflow=workflow,
queue_manager=queue_manager,
conversation=conversation,
message=message
message=message,
user=user,
stream=stream
)
try:
return generate_task_pipeline.process(stream=stream)
return generate_task_pipeline.process()
except ValueError as e:
if e.args[0] == "I/O operation on closed file.": # ignore this error
raise ConversationTaskStoppedException()
raise GenerateTaskStoppedException()
else:
logger.exception(e)
raise e
......
api/core/app/apps/advanced_chat/app_runner.py
View file @ 6cfda369
import logging
import time
from typing import cast
from typing import Optional, cast
from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfig
from core.app.apps.advanced_chat.workflow_event_trigger_callback import WorkflowEventTriggerCallback
......@@ -8,16 +8,14 @@ from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
from core.app.apps.base_app_runner import AppRunner
from core.app.entities.app_invoke_entities import (
AdvancedChatAppGenerateEntity,
InvokeFrom,
)
from core.app.entities.queue_entities import QueueAnnotationReplyEvent, QueueStopEvent, QueueTextChunkEvent
from core.moderation.base import ModerationException
from core.workflow.entities.node_entities import SystemVariable
from core.workflow.workflow_engine_manager import WorkflowEngineManager
from extensions.ext_database import db
from models.account import Account
from models.model import App, Conversation, EndUser, Message
from models.workflow import WorkflowRunTriggeredFrom
from models.model import App, Conversation, Message
from models.workflow import Workflow
logger = logging.getLogger(__name__)
......@@ -46,7 +44,7 @@ class AdvancedChatAppRunner(AppRunner):
if not app_record:
raise ValueError("App not found")
workflow = WorkflowEngineManager().get_workflow(app_model=app_record, workflow_id=app_config.workflow_id)
workflow = self.get_workflow(app_model=app_record, workflow_id=app_config.workflow_id)
if not workflow:
raise ValueError("Workflow not initialized")
......@@ -74,19 +72,10 @@ class AdvancedChatAppRunner(AppRunner):
):
return
# fetch user
if application_generate_entity.invoke_from in [InvokeFrom.DEBUGGER, InvokeFrom.EXPLORE]:
user = db.session.query(Account).filter(Account.id == application_generate_entity.user_id).first()
else:
user = db.session.query(EndUser).filter(EndUser.id == application_generate_entity.user_id).first()
# RUN WORKFLOW
workflow_engine_manager = WorkflowEngineManager()
workflow_engine_manager.run_workflow(
workflow=workflow,
triggered_from=WorkflowRunTriggeredFrom.DEBUGGING
if application_generate_entity.invoke_from == InvokeFrom.DEBUGGER else WorkflowRunTriggeredFrom.APP_RUN,
user=user,
user_inputs=inputs,
system_inputs={
SystemVariable.QUERY: query,
......@@ -99,6 +88,20 @@ class AdvancedChatAppRunner(AppRunner):
)]
)
def get_workflow(self, app_model: App, workflow_id: str) -> Optional[Workflow]:
"""
Get workflow
"""
# fetch workflow by workflow_id
workflow = db.session.query(Workflow).filter(
Workflow.tenant_id == app_model.tenant_id,
Workflow.app_id == app_model.id,
Workflow.id == workflow_id
).first()
# return workflow
return workflow
def handle_input_moderation(self, queue_manager: AppQueueManager,
app_record: App,
app_generate_entity: AdvancedChatAppGenerateEntity,
......
api/core/app/apps/advanced_chat/generate_task_pipeline.py
View file @ 6cfda369
......@@ -4,9 +4,10 @@ import time
from collections.abc import Generator
from typing import Optional, Union
from pydantic import BaseModel
from pydantic import BaseModel, Extra
from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
from core.app.apps.workflow_based_generate_task_pipeline import WorkflowBasedGenerateTaskPipeline
from core.app.entities.app_invoke_entities import (
AdvancedChatAppGenerateEntity,
InvokeFrom,
......@@ -16,25 +17,35 @@ from core.app.entities.queue_entities import (
QueueErrorEvent,
QueueMessageFileEvent,
QueueMessageReplaceEvent,
QueueNodeFinishedEvent,
QueueNodeFailedEvent,
QueueNodeStartedEvent,
QueueNodeSucceededEvent,
QueuePingEvent,
QueueRetrieverResourcesEvent,
QueueStopEvent,
QueueTextChunkEvent,
QueueWorkflowFinishedEvent,
QueueWorkflowFailedEvent,
QueueWorkflowStartedEvent,
QueueWorkflowSucceededEvent,
)
from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
from core.model_runtime.entities.llm_entities import LLMUsage
from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
from core.moderation.output_moderation import ModerationRule, OutputModeration
from core.tools.tool_file_manager import ToolFileManager
from core.workflow.entities.node_entities import NodeType
from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeType, SystemVariable
from events.message_event import message_was_created
from extensions.ext_database import db
from models.model import Conversation, Message, MessageFile
from models.workflow import WorkflowNodeExecution, WorkflowNodeExecutionStatus, WorkflowRun, WorkflowRunStatus
from models.account import Account
from models.model import Conversation, EndUser, Message, MessageFile
from models.workflow import (
Workflow,
WorkflowNodeExecution,
WorkflowNodeExecutionStatus,
WorkflowRun,
WorkflowRunStatus,
WorkflowRunTriggeredFrom,
)
from services.annotation_service import AppAnnotationService
logger = logging.getLogger(__name__)
......@@ -47,41 +58,63 @@ class TaskState(BaseModel):
answer: str = ""
metadata: dict = {}
usage: LLMUsage
workflow_run_id: Optional[str] = None
workflow_run: Optional[WorkflowRun] = None
start_at: Optional[float] = None
total_tokens: int = 0
total_steps: int = 0
current_node_execution: Optional[WorkflowNodeExecution] = None
current_node_execution_start_at: Optional[float] = None
class Config:
"""Configuration for this pydantic object."""
extra = Extra.forbid
arbitrary_types_allowed = True
class AdvancedChatAppGenerateTaskPipeline:
class AdvancedChatAppGenerateTaskPipeline(WorkflowBasedGenerateTaskPipeline):
"""
AdvancedChatAppGenerateTaskPipeline is a class that generate stream output and state management for Application.
"""
def __init__(self, application_generate_entity: AdvancedChatAppGenerateEntity,
workflow: Workflow,
queue_manager: AppQueueManager,
conversation: Conversation,
message: Message) -> None:
message: Message,
user: Union[Account, EndUser],
stream: bool) -> None:
"""
Initialize GenerateTaskPipeline.
:param application_generate_entity: application generate entity
:param workflow: workflow
:param queue_manager: queue manager
:param conversation: conversation
:param message: message
:param user: user
:param stream: stream
"""
self._application_generate_entity = application_generate_entity
self._workflow = workflow
self._queue_manager = queue_manager
self._conversation = conversation
self._message = message
self._user = user
self._task_state = TaskState(
usage=LLMUsage.empty_usage()
)
self._start_at = time.perf_counter()
self._output_moderation_handler = self._init_output_moderation()
self._stream = stream
def process(self, stream: bool) -> Union[dict, Generator]:
def process(self) -> Union[dict, Generator]:
"""
Process generate task pipeline.
:return:
"""
if stream:
if self._stream:
return self._process_stream_response()
else:
return self._process_blocking_response()
......@@ -112,22 +145,17 @@ class AdvancedChatAppGenerateTaskPipeline:
self._task_state.answer = annotation.content
elif isinstance(event, QueueWorkflowStartedEvent):
self._task_state.workflow_run_id = event.workflow_run_id
elif isinstance(event, QueueNodeFinishedEvent):
workflow_node_execution = self._get_workflow_node_execution(event.workflow_node_execution_id)
if workflow_node_execution.status == WorkflowNodeExecutionStatus.SUCCEEDED.value:
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
elif isinstance(event, QueueStopEvent | QueueWorkflowFinishedEvent):
if isinstance(event, QueueWorkflowFinishedEvent):
workflow_run = self._get_workflow_run(event.workflow_run_id)
if workflow_run.status == WorkflowRunStatus.SUCCEEDED.value:
outputs = workflow_run.outputs
self._task_state.answer = outputs.get('text', '')
else:
raise self._handle_error(QueueErrorEvent(error=ValueError(f'Run failed: {workflow_run.error}')))
self._on_workflow_start()
elif isinstance(event, QueueNodeStartedEvent):
self._on_node_start(event)
elif isinstance(event, QueueNodeSucceededEvent | QueueNodeFailedEvent):
self._on_node_finished(event)
elif isinstance(event, QueueStopEvent | QueueWorkflowSucceededEvent | QueueWorkflowFailedEvent):
self._on_workflow_finished(event)
workflow_run = self._task_state.workflow_run
if workflow_run.status != WorkflowRunStatus.SUCCEEDED.value:
raise self._handle_error(QueueErrorEvent(error=ValueError(f'Run failed: {workflow_run.error}')))
# response moderation
if self._output_moderation_handler:
......@@ -173,8 +201,9 @@ class AdvancedChatAppGenerateTaskPipeline:
yield self._yield_response(data)
break
elif isinstance(event, QueueWorkflowStartedEvent):
workflow_run = self._get_workflow_run(event.workflow_run_id)
self._task_state.workflow_run_id = workflow_run.id
self._on_workflow_start()
workflow_run = self._task_state.workflow_run
response = {
'event': 'workflow_started',
'task_id': self._application_generate_entity.task_id,
......@@ -188,7 +217,9 @@ class AdvancedChatAppGenerateTaskPipeline:
yield self._yield_response(response)
elif isinstance(event, QueueNodeStartedEvent):
workflow_node_execution = self._get_workflow_node_execution(event.workflow_node_execution_id)
self._on_node_start(event)
workflow_node_execution = self._task_state.current_node_execution
response = {
'event': 'node_started',
'task_id': self._application_generate_entity.task_id,
......@@ -204,8 +235,10 @@ class AdvancedChatAppGenerateTaskPipeline:
}
yield self._yield_response(response)
elif isinstance(event, QueueNodeFinishedEvent):
workflow_node_execution = self._get_workflow_node_execution(event.workflow_node_execution_id)
elif isinstance(event, QueueNodeSucceededEvent | QueueNodeFailedEvent):
self._on_node_finished(event)
workflow_node_execution = self._task_state.current_node_execution
if workflow_node_execution.status == WorkflowNodeExecutionStatus.SUCCEEDED.value:
if workflow_node_execution.node_type == NodeType.LLM.value:
outputs = workflow_node_execution.outputs_dict
......@@ -234,16 +267,11 @@ class AdvancedChatAppGenerateTaskPipeline:
}
yield self._yield_response(response)
elif isinstance(event, QueueStopEvent | QueueWorkflowFinishedEvent):
if isinstance(event, QueueStopEvent):
workflow_run = self._get_workflow_run(self._task_state.workflow_run_id)
else:
workflow_run = self._get_workflow_run(event.workflow_run_id)
elif isinstance(event, QueueStopEvent | QueueWorkflowSucceededEvent | QueueWorkflowFailedEvent):
self._on_workflow_finished(event)
workflow_run = self._task_state.workflow_run
if workflow_run.status == WorkflowRunStatus.SUCCEEDED.value:
outputs = workflow_run.outputs_dict
self._task_state.answer = outputs.get('text', '')
else:
if workflow_run.status != WorkflowRunStatus.SUCCEEDED.value:
err_event = QueueErrorEvent(error=ValueError(f'Run failed: {workflow_run.error}'))
data = self._error_to_stream_response_data(self._handle_error(err_event))
yield self._yield_response(data)
......@@ -252,7 +280,7 @@ class AdvancedChatAppGenerateTaskPipeline:
workflow_run_response = {
'event': 'workflow_finished',
'task_id': self._application_generate_entity.task_id,
'workflow_run_id': event.workflow_run_id,
'workflow_run_id': workflow_run.id,
'data': {
'id': workflow_run.id,
'workflow_id': workflow_run.workflow_id,
......@@ -390,6 +418,102 @@ class AdvancedChatAppGenerateTaskPipeline:
else:
continue
def _on_workflow_start(self) -> None:
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={
SystemVariable.QUERY: self._message.query,
SystemVariable.FILES: self._application_generate_entity.files,
SystemVariable.CONVERSATION: self._conversation.id,
}
)
self._task_state.workflow_run = workflow_run
def _on_node_start(self, event: QueueNodeStartedEvent) -> None:
workflow_node_execution = self._init_node_execution_from_workflow_run(
workflow_run=self._task_state.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
)
self._task_state.current_node_execution = workflow_node_execution
self._task_state.current_node_execution_start_at = time.perf_counter()
self._task_state.total_steps += 1
def _on_node_finished(self, event: QueueNodeSucceededEvent | QueueNodeFailedEvent) -> None:
if isinstance(event, QueueNodeSucceededEvent):
workflow_node_execution = self._workflow_node_execution_success(
workflow_node_execution=self._task_state.current_node_execution,
start_at=self._task_state.current_node_execution_start_at,
inputs=event.inputs,
process_data=event.process_data,
outputs=event.outputs,
execution_metadata=event.execution_metadata
)
if event.execution_metadata and event.execution_metadata.get(NodeRunMetadataKey.TOTAL_TOKENS):
self._task_state.total_tokens += (
int(event.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=self._task_state.current_node_execution,
start_at=self._task_state.current_node_execution_start_at,
error=event.error
)
self._task_state.current_node_execution = workflow_node_execution
def _on_workflow_finished(self, event: QueueStopEvent | QueueWorkflowSucceededEvent | QueueWorkflowFailedEvent) -> None:
if isinstance(event, QueueStopEvent):
workflow_run = self._workflow_run_failed(
workflow_run=self._task_state.workflow_run,
start_at=self._task_state.start_at,
total_tokens=self._task_state.total_tokens,
total_steps=self._task_state.total_steps,
status=WorkflowRunStatus.STOPPED,
error='Workflow stopped.'
)
elif isinstance(event, QueueWorkflowFailedEvent):
workflow_run = self._workflow_run_failed(
workflow_run=self._task_state.workflow_run,
start_at=self._task_state.start_at,
total_tokens=self._task_state.total_tokens,
total_steps=self._task_state.total_steps,
status=WorkflowRunStatus.FAILED,
error=event.error
)
else:
workflow_run = self._workflow_run_success(
workflow_run=self._task_state.workflow_run,
start_at=self._task_state.start_at,
total_tokens=self._task_state.total_tokens,
total_steps=self._task_state.total_steps,
outputs=self._task_state.current_node_execution.outputs
if self._task_state.current_node_execution else None
)
self._task_state.workflow_run = workflow_run
if workflow_run.status == WorkflowRunStatus.SUCCEEDED.value:
outputs = workflow_run.outputs_dict
self._task_state.answer = outputs.get('text', '')
def _get_workflow_run(self, workflow_run_id: str) -> WorkflowRun:
"""
Get workflow run.
......@@ -397,11 +521,6 @@ class AdvancedChatAppGenerateTaskPipeline:
:return:
"""
workflow_run = db.session.query(WorkflowRun).filter(WorkflowRun.id == workflow_run_id).first()
if workflow_run:
# Because the workflow_run will be modified in the sub-thread,
# and the first query in the main thread will cache the entity,
# you need to expire the entity after the query
db.session.expire(workflow_run)
return workflow_run
def _get_workflow_node_execution(self, workflow_node_execution_id: str) -> WorkflowNodeExecution:
......@@ -412,11 +531,6 @@ class AdvancedChatAppGenerateTaskPipeline:
"""
workflow_node_execution = (db.session.query(WorkflowNodeExecution)
.filter(WorkflowNodeExecution.id == workflow_node_execution_id).first())
if workflow_node_execution:
# Because the workflow_node_execution will be modified in the sub-thread,
# and the first query in the main thread will cache the entity,
# you need to expire the entity after the query
db.session.expire(workflow_node_execution)
return workflow_node_execution
def _save_message(self) -> None:
......@@ -428,7 +542,7 @@ class AdvancedChatAppGenerateTaskPipeline:
self._message.answer = self._task_state.answer
self._message.provider_response_latency = time.perf_counter() - self._start_at
self._message.workflow_run_id = self._task_state.workflow_run_id
self._message.workflow_run_id = self._task_state.workflow_run.id
if self._task_state.metadata and self._task_state.metadata.get('usage'):
usage = LLMUsage(**self._task_state.metadata['usage'])
......
api/core/app/apps/advanced_chat/workflow_event_trigger_callback.py
View file @ 6cfda369
from typing import Optional
from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
from core.app.entities.queue_entities import (
QueueNodeFinishedEvent,
QueueNodeFailedEvent,
QueueNodeStartedEvent,
QueueNodeSucceededEvent,
QueueTextChunkEvent,
QueueWorkflowFinishedEvent,
QueueWorkflowFailedEvent,
QueueWorkflowStartedEvent,
QueueWorkflowSucceededEvent,
)
from core.workflow.callbacks.base_workflow_callback import BaseWorkflowCallback
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeType
from models.workflow import Workflow, WorkflowNodeExecution, WorkflowRun
from models.workflow import Workflow
class WorkflowEventTriggerCallback(BaseWorkflowCallback):
......@@ -17,39 +22,91 @@ class WorkflowEventTriggerCallback(BaseWorkflowCallback):
self._queue_manager = queue_manager
self._streamable_node_ids = self._fetch_streamable_node_ids(workflow.graph_dict)
def on_workflow_run_started(self, workflow_run: WorkflowRun) -> None:
def on_workflow_run_started(self) -> None:
"""
Workflow run started
"""
self._queue_manager.publish(
QueueWorkflowStartedEvent(workflow_run_id=workflow_run.id),
QueueWorkflowStartedEvent(),
PublishFrom.APPLICATION_MANAGER
)
def on_workflow_run_succeeded(self) -> None:
"""
Workflow run succeeded
"""
self._queue_manager.publish(
QueueWorkflowSucceededEvent(),
PublishFrom.APPLICATION_MANAGER
)
def on_workflow_run_finished(self, workflow_run: WorkflowRun) -> None:
def on_workflow_run_failed(self, error: str) -> None:
"""
Workflow run finished
Workflow run failed
"""
self._queue_manager.publish(
QueueWorkflowFinishedEvent(workflow_run_id=workflow_run.id),
QueueWorkflowFailedEvent(
error=error
),
PublishFrom.APPLICATION_MANAGER
)
def on_workflow_node_execute_started(self, workflow_node_execution: WorkflowNodeExecution) -> None:
def on_workflow_node_execute_started(self, node_id: str,
node_type: NodeType,
node_data: BaseNodeData,
node_run_index: int = 1,
predecessor_node_id: Optional[str] = None) -> None:
"""
Workflow node execute started
"""
self._queue_manager.publish(
QueueNodeStartedEvent(workflow_node_execution_id=workflow_node_execution.id),
QueueNodeStartedEvent(
node_id=node_id,
node_type=node_type,
node_data=node_data,
node_run_index=node_run_index,
predecessor_node_id=predecessor_node_id
),
PublishFrom.APPLICATION_MANAGER
)
def on_workflow_node_execute_succeeded(self, node_id: str,
node_type: NodeType,
node_data: BaseNodeData,
inputs: Optional[dict] = None,
process_data: Optional[dict] = None,
outputs: Optional[dict] = None,
execution_metadata: Optional[dict] = None) -> None:
"""
Workflow node execute succeeded
"""
self._queue_manager.publish(
QueueNodeSucceededEvent(
node_id=node_id,
node_type=node_type,
node_data=node_data,
inputs=inputs,
process_data=process_data,
outputs=outputs,
execution_metadata=execution_metadata
),
PublishFrom.APPLICATION_MANAGER
)
def on_workflow_node_execute_finished(self, workflow_node_execution: WorkflowNodeExecution) -> None:
def on_workflow_node_execute_failed(self, node_id: str,
node_type: NodeType,
node_data: BaseNodeData,
error: str) -> None:
"""
Workflow node execute finished
Workflow node execute failed
"""
self._queue_manager.publish(
QueueNodeFinishedEvent(workflow_node_execution_id=workflow_node_execution.id),
QueueNodeFailedEvent(
node_id=node_id,
node_type=node_type,
node_data=node_data,
error=error
),
PublishFrom.APPLICATION_MANAGER
)
......
api/core/app/apps/agent_chat/app_generator.py
View file @ 6cfda369
......@@ -11,7 +11,7 @@ from core.app.app_config.easy_ui_based_app.model_config.converter import ModelCo
from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
from core.app.apps.agent_chat.app_config_manager import AgentChatAppConfigManager
from core.app.apps.agent_chat.app_runner import AgentChatAppRunner
from core.app.apps.base_app_queue_manager import AppQueueManager, ConversationTaskStoppedException, PublishFrom
from core.app.apps.base_app_queue_manager import AppQueueManager, GenerateTaskStoppedException, PublishFrom
from core.app.apps.message_based_app_generator import MessageBasedAppGenerator
from core.app.apps.message_based_app_queue_manager import MessageBasedAppQueueManager
from core.app.entities.app_invoke_entities import AgentChatAppGenerateEntity, InvokeFrom
......@@ -177,7 +177,7 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
conversation=conversation,
message=message
)
except ConversationTaskStoppedException:
except GenerateTaskStoppedException:
pass
except InvokeAuthorizationError:
queue_manager.publish_error(
......
api/core/app/apps/base_app_queue_manager.py
View file @ 6cfda369
......@@ -11,11 +11,8 @@ from core.app.entities.app_invoke_entities import InvokeFrom
from core.app.entities.queue_entities import (
AppQueueEvent,
QueueErrorEvent,
QueueMessage,
QueueMessageEndEvent,
QueuePingEvent,
QueueStopEvent,
QueueWorkflowFinishedEvent,
)
from extensions.ext_redis import redis_client
......@@ -103,22 +100,16 @@ class AppQueueManager:
:return:
"""
self._check_for_sqlalchemy_models(event.dict())
message = self.construct_queue_message(event)
self._q.put(message)
if isinstance(event, QueueStopEvent
| QueueErrorEvent
| QueueMessageEndEvent
| QueueWorkflowFinishedEvent):
self.stop_listen()
if pub_from == PublishFrom.APPLICATION_MANAGER and self._is_stopped():
raise ConversationTaskStoppedException()
self._publish(event, pub_from)
@abstractmethod
def construct_queue_message(self, event: AppQueueEvent) -> QueueMessage:
def _publish(self, event: AppQueueEvent, pub_from: PublishFrom) -> None:
"""
Publish event to queue
:param event:
:param pub_from:
:return:
"""
raise NotImplementedError
@classmethod
......@@ -182,5 +173,5 @@ class AppQueueManager:
"that cause thread safety issues is not allowed.")
class ConversationTaskStoppedException(Exception):
class GenerateTaskStoppedException(Exception):
pass
api/core/app/apps/chat/app_generator.py
View file @ 6cfda369
......@@ -9,7 +9,7 @@ from pydantic import ValidationError
from core.app.app_config.easy_ui_based_app.model_config.converter import ModelConfigConverter
from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
from core.app.apps.base_app_queue_manager import AppQueueManager, ConversationTaskStoppedException, PublishFrom
from core.app.apps.base_app_queue_manager import AppQueueManager, GenerateTaskStoppedException, PublishFrom
from core.app.apps.chat.app_config_manager import ChatAppConfigManager
from core.app.apps.chat.app_runner import ChatAppRunner
from core.app.apps.message_based_app_generator import MessageBasedAppGenerator
......@@ -177,7 +177,7 @@ class ChatAppGenerator(MessageBasedAppGenerator):
conversation=conversation,
message=message
)
except ConversationTaskStoppedException:
except GenerateTaskStoppedException:
pass
except InvokeAuthorizationError:
queue_manager.publish_error(
......
api/core/app/apps/completion/app_generator.py
View file @ 6cfda369
......@@ -9,7 +9,7 @@ from pydantic import ValidationError
from core.app.app_config.easy_ui_based_app.model_config.converter import ModelConfigConverter
from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
from core.app.apps.base_app_queue_manager import AppQueueManager, ConversationTaskStoppedException, PublishFrom
from core.app.apps.base_app_queue_manager import AppQueueManager, GenerateTaskStoppedException, PublishFrom
from core.app.apps.completion.app_config_manager import CompletionAppConfigManager
from core.app.apps.completion.app_runner import CompletionAppRunner
from core.app.apps.message_based_app_generator import MessageBasedAppGenerator
......@@ -166,7 +166,7 @@ class CompletionAppGenerator(MessageBasedAppGenerator):
queue_manager=queue_manager,
message=message
)
except ConversationTaskStoppedException:
except GenerateTaskStoppedException:
pass
except InvokeAuthorizationError:
queue_manager.publish_error(
......
api/core/app/apps/message_based_app_generator.py
View file @ 6cfda369
......@@ -7,7 +7,7 @@ from sqlalchemy import and_
from core.app.app_config.entities import EasyUIBasedAppModelConfigFrom
from core.app.apps.base_app_generator import BaseAppGenerator
from core.app.apps.base_app_queue_manager import AppQueueManager, ConversationTaskStoppedException
from core.app.apps.base_app_queue_manager import AppQueueManager, GenerateTaskStoppedException
from core.app.apps.easy_ui_based_generate_task_pipeline import EasyUIBasedGenerateTaskPipeline
from core.app.entities.app_invoke_entities import (
AdvancedChatAppGenerateEntity,
......@@ -60,7 +60,7 @@ class MessageBasedAppGenerator(BaseAppGenerator):
return generate_task_pipeline.process(stream=stream)
except ValueError as e:
if e.args[0] == "I/O operation on closed file.": # ignore this error
raise ConversationTaskStoppedException()
raise GenerateTaskStoppedException()
else:
logger.exception(e)
raise e
......
api/core/app/apps/message_based_app_queue_manager.py
View file @ 6cfda369
from core.app.apps.base_app_queue_manager import AppQueueManager
from core.app.apps.base_app_queue_manager import AppQueueManager, GenerateTaskStoppedException, PublishFrom
from core.app.entities.app_invoke_entities import InvokeFrom
from core.app.entities.queue_entities import (
AppQueueEvent,
MessageQueueMessage,
QueueErrorEvent,
QueueMessage,
QueueMessageEndEvent,
QueueStopEvent,
QueueWorkflowFailedEvent,
QueueWorkflowSucceededEvent,
)
......@@ -28,3 +33,31 @@ class MessageBasedAppQueueManager(AppQueueManager):
app_mode=self._app_mode,
event=event
)
def _publish(self, event: AppQueueEvent, pub_from: PublishFrom) -> None:
"""
Publish event to queue
:param event:
:param pub_from:
:return:
"""
message = MessageQueueMessage(
task_id=self._task_id,
message_id=self._message_id,
conversation_id=self._conversation_id,
app_mode=self._app_mode,
event=event
)
self._q.put(message)
if isinstance(event, QueueStopEvent
| QueueErrorEvent
| QueueMessageEndEvent
| QueueWorkflowSucceededEvent
| QueueWorkflowFailedEvent):
self.stop_listen()
if pub_from == PublishFrom.APPLICATION_MANAGER and self._is_stopped():
raise GenerateTaskStoppedException()
api/core/app/apps/workflow/app_generator.py
View file @ 6cfda369
......@@ -9,7 +9,7 @@ from pydantic import ValidationError
from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
from core.app.apps.base_app_generator import BaseAppGenerator
from core.app.apps.base_app_queue_manager import AppQueueManager, ConversationTaskStoppedException, PublishFrom
from core.app.apps.base_app_queue_manager import AppQueueManager, GenerateTaskStoppedException, PublishFrom
from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager
from core.app.apps.workflow.app_queue_manager import WorkflowAppQueueManager
from core.app.apps.workflow.app_runner import WorkflowAppRunner
......@@ -95,7 +95,9 @@ class WorkflowAppGenerator(BaseAppGenerator):
# return response or stream generator
return self._handle_response(
application_generate_entity=application_generate_entity,
workflow=workflow,
queue_manager=queue_manager,
user=user,
stream=stream
)
......@@ -117,7 +119,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
application_generate_entity=application_generate_entity,
queue_manager=queue_manager
)
except ConversationTaskStoppedException:
except GenerateTaskStoppedException:
pass
except InvokeAuthorizationError:
queue_manager.publish_error(
......@@ -136,19 +138,25 @@ class WorkflowAppGenerator(BaseAppGenerator):
db.session.remove()
def _handle_response(self, application_generate_entity: WorkflowAppGenerateEntity,
workflow: Workflow,
queue_manager: AppQueueManager,
user: Union[Account, EndUser],
stream: bool = False) -> Union[dict, Generator]:
"""
Handle response.
:param application_generate_entity: application generate entity
:param workflow: workflow
:param queue_manager: queue manager
:param user: account or end user
:param stream: is stream
:return:
"""
# init generate task pipeline
generate_task_pipeline = WorkflowAppGenerateTaskPipeline(
application_generate_entity=application_generate_entity,
workflow=workflow,
queue_manager=queue_manager,
user=user,
stream=stream
)
......@@ -156,7 +164,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
return generate_task_pipeline.process()
except ValueError as e:
if e.args[0] == "I/O operation on closed file.": # ignore this error
raise ConversationTaskStoppedException()
raise GenerateTaskStoppedException()
else:
logger.exception(e)
raise e
......
api/core/app/apps/workflow/app_queue_manager.py
View file @ 6cfda369
from core.app.apps.base_app_queue_manager import AppQueueManager
from core.app.apps.base_app_queue_manager import AppQueueManager, GenerateTaskStoppedException, PublishFrom
from core.app.entities.app_invoke_entities import InvokeFrom
from core.app.entities.queue_entities import (
AppQueueEvent,
QueueMessage,
QueueErrorEvent,
QueueMessageEndEvent,
QueueStopEvent,
QueueWorkflowFailedEvent,
QueueWorkflowSucceededEvent,
WorkflowQueueMessage,
)
......@@ -16,9 +20,27 @@ class WorkflowAppQueueManager(AppQueueManager):
self._app_mode = app_mode
def construct_queue_message(self, event: AppQueueEvent) -> QueueMessage:
return WorkflowQueueMessage(
def _publish(self, event: AppQueueEvent, pub_from: PublishFrom) -> None:
"""
Publish event to queue
:param event:
:param pub_from:
:return:
"""
message = WorkflowQueueMessage(
task_id=self._task_id,
app_mode=self._app_mode,
event=event
)
self._q.put(message)
if isinstance(event, QueueStopEvent
| QueueErrorEvent
| QueueMessageEndEvent
| QueueWorkflowSucceededEvent
| QueueWorkflowFailedEvent):
self.stop_listen()
if pub_from == PublishFrom.APPLICATION_MANAGER and self._is_stopped():
raise GenerateTaskStoppedException()
api/core/app/apps/workflow/app_runner.py
View file @ 6cfda369
import logging
import time
from typing import cast
from typing import Optional, cast
from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
from core.app.apps.workflow.app_config_manager import WorkflowAppConfig
from core.app.apps.workflow.workflow_event_trigger_callback import WorkflowEventTriggerCallback
from core.app.entities.app_invoke_entities import (
AppGenerateEntity,
InvokeFrom,
WorkflowAppGenerateEntity,
)
from core.app.entities.queue_entities import QueueStopEvent, QueueTextChunkEvent
......@@ -16,9 +15,8 @@ from core.moderation.input_moderation import InputModeration
from core.workflow.entities.node_entities import SystemVariable
from core.workflow.workflow_engine_manager import WorkflowEngineManager
from extensions.ext_database import db
from models.account import Account
from models.model import App, EndUser
from models.workflow import WorkflowRunTriggeredFrom
from models.model import App
from models.workflow import Workflow
logger = logging.getLogger(__name__)
......@@ -43,7 +41,7 @@ class WorkflowAppRunner:
if not app_record:
raise ValueError("App not found")
workflow = WorkflowEngineManager().get_workflow(app_model=app_record, workflow_id=app_config.workflow_id)
workflow = self.get_workflow(app_model=app_record, workflow_id=app_config.workflow_id)
if not workflow:
raise ValueError("Workflow not initialized")
......@@ -59,19 +57,10 @@ class WorkflowAppRunner:
):
return
# fetch user
if application_generate_entity.invoke_from in [InvokeFrom.DEBUGGER, InvokeFrom.EXPLORE]:
user = db.session.query(Account).filter(Account.id == application_generate_entity.user_id).first()
else:
user = db.session.query(EndUser).filter(EndUser.id == application_generate_entity.user_id).first()
# RUN WORKFLOW
workflow_engine_manager = WorkflowEngineManager()
workflow_engine_manager.run_workflow(
workflow=workflow,
triggered_from=WorkflowRunTriggeredFrom.DEBUGGING
if application_generate_entity.invoke_from == InvokeFrom.DEBUGGER else WorkflowRunTriggeredFrom.APP_RUN,
user=user,
user_inputs=inputs,
system_inputs={
SystemVariable.FILES: files
......@@ -82,6 +71,20 @@ class WorkflowAppRunner:
)]
)
def get_workflow(self, app_model: App, workflow_id: str) -> Optional[Workflow]:
"""
Get workflow
"""
# fetch workflow by workflow_id
workflow = db.session.query(Workflow).filter(
Workflow.tenant_id == app_model.tenant_id,
Workflow.app_id == app_model.id,
Workflow.id == workflow_id
).first()
# return workflow
return workflow
def handle_input_moderation(self, queue_manager: AppQueueManager,
app_record: App,
app_generate_entity: WorkflowAppGenerateEntity,
......
api/core/app/apps/workflow/generate_task_pipeline.py
View file @ 6cfda369
......@@ -4,28 +4,35 @@ import time
from collections.abc import Generator
from typing import Optional, Union
from pydantic import BaseModel
from pydantic import BaseModel, Extra
from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
from core.app.apps.workflow_based_generate_task_pipeline import WorkflowBasedGenerateTaskPipeline
from core.app.entities.app_invoke_entities import (
InvokeFrom,
WorkflowAppGenerateEntity,
)
from core.app.entities.queue_entities import (
QueueErrorEvent,
QueueMessageReplaceEvent,
QueueNodeFinishedEvent,
QueueNodeFailedEvent,
QueueNodeStartedEvent,
QueueNodeSucceededEvent,
QueuePingEvent,
QueueStopEvent,
QueueTextChunkEvent,
QueueWorkflowFinishedEvent,
QueueWorkflowFailedEvent,
QueueWorkflowStartedEvent,
QueueWorkflowSucceededEvent,
)
from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
from core.moderation.output_moderation import ModerationRule, OutputModeration
from core.workflow.entities.node_entities import NodeRunMetadataKey, SystemVariable
from extensions.ext_database import db
from models.workflow import WorkflowNodeExecution, WorkflowRun, WorkflowRunStatus
from models.account import Account
from models.model import EndUser
from models.workflow import Workflow, WorkflowNodeExecution, WorkflowRun, WorkflowRunStatus, WorkflowRunTriggeredFrom
logger = logging.getLogger(__name__)
......@@ -36,24 +43,44 @@ class TaskState(BaseModel):
"""
answer: str = ""
metadata: dict = {}
workflow_run_id: Optional[str] = None
workflow_run: Optional[WorkflowRun] = None
start_at: Optional[float] = None
total_tokens: int = 0
total_steps: int = 0
class WorkflowAppGenerateTaskPipeline:
current_node_execution: Optional[WorkflowNodeExecution] = None
current_node_execution_start_at: Optional[float] = None
class Config:
"""Configuration for this pydantic object."""
extra = Extra.forbid
arbitrary_types_allowed = True
class WorkflowAppGenerateTaskPipeline(WorkflowBasedGenerateTaskPipeline):
"""
WorkflowAppGenerateTaskPipeline is a class that generate stream output and state management for Application.
"""
def __init__(self, application_generate_entity: WorkflowAppGenerateEntity,
workflow: Workflow,
queue_manager: AppQueueManager,
user: Union[Account, EndUser],
stream: bool) -> None:
"""
Initialize GenerateTaskPipeline.
:param application_generate_entity: application generate entity
:param workflow: workflow
:param queue_manager: queue manager
:param user: user
:param stream: is stream
"""
self._application_generate_entity = application_generate_entity
self._workflow = workflow
self._queue_manager = queue_manager
self._user = user
self._task_state = TaskState()
self._start_at = time.perf_counter()
self._output_moderation_handler = self._init_output_moderation()
......@@ -79,17 +106,15 @@ class WorkflowAppGenerateTaskPipeline:
if isinstance(event, QueueErrorEvent):
raise self._handle_error(event)
elif isinstance(event, QueueStopEvent | QueueWorkflowFinishedEvent):
if isinstance(event, QueueStopEvent):
workflow_run = self._get_workflow_run(self._task_state.workflow_run_id)
else:
workflow_run = self._get_workflow_run(event.workflow_run_id)
if workflow_run.status == WorkflowRunStatus.SUCCEEDED.value:
outputs = workflow_run.outputs_dict
self._task_state.answer = outputs.get('text', '')
else:
raise self._handle_error(QueueErrorEvent(error=ValueError(f'Run failed: {workflow_run.error}')))
elif isinstance(event, QueueWorkflowStartedEvent):
self._on_workflow_start()
elif isinstance(event, QueueNodeStartedEvent):
self._on_node_start(event)
elif isinstance(event, QueueNodeSucceededEvent | QueueNodeFailedEvent):
self._on_node_finished(event)
elif isinstance(event, QueueStopEvent | QueueWorkflowSucceededEvent | QueueWorkflowFailedEvent):
self._on_workflow_finished(event)
workflow_run = self._task_state.workflow_run
# response moderation
if self._output_moderation_handler:
......@@ -100,10 +125,12 @@ class WorkflowAppGenerateTaskPipeline:
public_event=False
)
# save workflow app log
self._save_workflow_app_log()
response = {
'event': 'workflow_finished',
'task_id': self._application_generate_entity.task_id,
'workflow_run_id': event.workflow_run_id,
'workflow_run_id': workflow_run.id,
'data': {
'id': workflow_run.id,
'workflow_id': workflow_run.workflow_id,
......@@ -135,8 +162,9 @@ class WorkflowAppGenerateTaskPipeline:
yield self._yield_response(data)
break
elif isinstance(event, QueueWorkflowStartedEvent):
self._task_state.workflow_run_id = event.workflow_run_id
workflow_run = self._get_workflow_run(event.workflow_run_id)
self._on_workflow_start()
workflow_run = self._task_state.workflow_run
response = {
'event': 'workflow_started',
'task_id': self._application_generate_entity.task_id,
......@@ -150,7 +178,9 @@ class WorkflowAppGenerateTaskPipeline:
yield self._yield_response(response)
elif isinstance(event, QueueNodeStartedEvent):
workflow_node_execution = self._get_workflow_node_execution(event.workflow_node_execution_id)
self._on_node_start(event)
workflow_node_execution = self._task_state.current_node_execution
response = {
'event': 'node_started',
'task_id': self._application_generate_entity.task_id,
......@@ -166,8 +196,10 @@ class WorkflowAppGenerateTaskPipeline:
}
yield self._yield_response(response)
elif isinstance(event, QueueNodeFinishedEvent):
workflow_node_execution = self._get_workflow_node_execution(event.workflow_node_execution_id)
elif isinstance(event, QueueNodeSucceededEvent | QueueNodeFailedEvent):
self._on_node_finished(event)
workflow_node_execution = self._task_state.current_node_execution
response = {
'event': 'node_finished',
'task_id': self._application_generate_entity.task_id,
......@@ -190,20 +222,9 @@ class WorkflowAppGenerateTaskPipeline:
}
yield self._yield_response(response)
elif isinstance(event, QueueStopEvent | QueueWorkflowFinishedEvent):
if isinstance(event, QueueStopEvent):
workflow_run = self._get_workflow_run(self._task_state.workflow_run_id)
else:
workflow_run = self._get_workflow_run(event.workflow_run_id)
if workflow_run.status == WorkflowRunStatus.SUCCEEDED.value:
outputs = workflow_run.outputs_dict
self._task_state.answer = outputs.get('text', '')
else:
err_event = QueueErrorEvent(error=ValueError(f'Run failed: {workflow_run.error}'))
data = self._error_to_stream_response_data(self._handle_error(err_event))
yield self._yield_response(data)
break
elif isinstance(event, QueueStopEvent | QueueWorkflowSucceededEvent | QueueWorkflowFailedEvent):
self._on_workflow_finished(event)
workflow_run = self._task_state.workflow_run
# response moderation
if self._output_moderation_handler:
......@@ -219,7 +240,7 @@ class WorkflowAppGenerateTaskPipeline:
replace_response = {
'event': 'text_replace',
'task_id': self._application_generate_entity.task_id,
'workflow_run_id': self._task_state.workflow_run_id,
'workflow_run_id': self._task_state.workflow_run.id,
'data': {
'text': self._task_state.answer
}
......@@ -233,7 +254,7 @@ class WorkflowAppGenerateTaskPipeline:
workflow_run_response = {
'event': 'workflow_finished',
'task_id': self._application_generate_entity.task_id,
'workflow_run_id': event.workflow_run_id,
'workflow_run_id': workflow_run.id,
'data': {
'id': workflow_run.id,
'workflow_id': workflow_run.workflow_id,
......@@ -244,7 +265,7 @@ class WorkflowAppGenerateTaskPipeline:
'total_tokens': workflow_run.total_tokens,
'total_steps': workflow_run.total_steps,
'created_at': int(workflow_run.created_at.timestamp()),
'finished_at': int(workflow_run.finished_at.timestamp())
'finished_at': int(workflow_run.finished_at.timestamp()) if workflow_run.finished_at else None
}
}
......@@ -279,7 +300,7 @@ class WorkflowAppGenerateTaskPipeline:
response = {
'event': 'text_replace',
'task_id': self._application_generate_entity.task_id,
'workflow_run_id': self._task_state.workflow_run_id,
'workflow_run_id': self._task_state.workflow_run.id,
'data': {
'text': event.text
}
......@@ -291,6 +312,95 @@ class WorkflowAppGenerateTaskPipeline:
else:
continue
def _on_workflow_start(self) -> None:
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={
SystemVariable.FILES: self._application_generate_entity.files
}
)
self._task_state.workflow_run = workflow_run
def _on_node_start(self, event: QueueNodeStartedEvent) -> None:
workflow_node_execution = self._init_node_execution_from_workflow_run(
workflow_run=self._task_state.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
)
self._task_state.current_node_execution = workflow_node_execution
self._task_state.current_node_execution_start_at = time.perf_counter()
self._task_state.total_steps += 1
def _on_node_finished(self, event: QueueNodeSucceededEvent | QueueNodeFailedEvent) -> None:
if isinstance(event, QueueNodeSucceededEvent):
workflow_node_execution = self._workflow_node_execution_success(
workflow_node_execution=self._task_state.current_node_execution,
start_at=self._task_state.current_node_execution_start_at,
inputs=event.inputs,
process_data=event.process_data,
outputs=event.outputs,
execution_metadata=event.execution_metadata
)
if event.execution_metadata and event.execution_metadata.get(NodeRunMetadataKey.TOTAL_TOKENS):
self._task_state.total_tokens += (
int(event.execution_metadata.get(NodeRunMetadataKey.TOTAL_TOKENS)))
else:
workflow_node_execution = self._workflow_node_execution_failed(
workflow_node_execution=self._task_state.current_node_execution,
start_at=self._task_state.current_node_execution_start_at,
error=event.error
)
self._task_state.current_node_execution = workflow_node_execution
def _on_workflow_finished(self, event: QueueStopEvent | QueueWorkflowSucceededEvent | QueueWorkflowFailedEvent) -> None:
if isinstance(event, QueueStopEvent):
workflow_run = self._workflow_run_failed(
workflow_run=self._task_state.workflow_run,
start_at=self._task_state.start_at,
total_tokens=self._task_state.total_tokens,
total_steps=self._task_state.total_steps,
status=WorkflowRunStatus.STOPPED,
error='Workflow stopped.'
)
elif isinstance(event, QueueWorkflowFailedEvent):
workflow_run = self._workflow_run_failed(
workflow_run=self._task_state.workflow_run,
start_at=self._task_state.start_at,
total_tokens=self._task_state.total_tokens,
total_steps=self._task_state.total_steps,
status=WorkflowRunStatus.FAILED,
error=event.error
)
else:
workflow_run = self._workflow_run_success(
workflow_run=self._task_state.workflow_run,
start_at=self._task_state.start_at,
total_tokens=self._task_state.total_tokens,
total_steps=self._task_state.total_steps,
outputs=self._task_state.current_node_execution.outputs
if self._task_state.current_node_execution else None
)
self._task_state.workflow_run = workflow_run
if workflow_run.status == WorkflowRunStatus.SUCCEEDED.value:
outputs = workflow_run.outputs_dict
self._task_state.answer = outputs.get('text', '')
def _get_workflow_run(self, workflow_run_id: str) -> WorkflowRun:
"""
Get workflow run.
......@@ -298,11 +408,6 @@ class WorkflowAppGenerateTaskPipeline:
:return:
"""
workflow_run = db.session.query(WorkflowRun).filter(WorkflowRun.id == workflow_run_id).first()
if workflow_run:
# Because the workflow_run will be modified in the sub-thread,
# and the first query in the main thread will cache the entity,
# you need to expire the entity after the query
db.session.expire(workflow_run)
return workflow_run
def _get_workflow_node_execution(self, workflow_node_execution_id: str) -> WorkflowNodeExecution:
......@@ -313,11 +418,6 @@ class WorkflowAppGenerateTaskPipeline:
"""
workflow_node_execution = (db.session.query(WorkflowNodeExecution)
.filter(WorkflowNodeExecution.id == workflow_node_execution_id).first())
if workflow_node_execution:
# Because the workflow_node_execution will be modified in the sub-thread,
# and the first query in the main thread will cache the entity,
# you need to expire the entity after the query
db.session.expire(workflow_node_execution)
return workflow_node_execution
def _save_workflow_app_log(self) -> None:
......@@ -335,7 +435,7 @@ class WorkflowAppGenerateTaskPipeline:
"""
response = {
'event': 'text_chunk',
'workflow_run_id': self._task_state.workflow_run_id,
'workflow_run_id': self._task_state.workflow_run.id,
'task_id': self._application_generate_entity.task_id,
'data': {
'text': text
......@@ -398,7 +498,6 @@ class WorkflowAppGenerateTaskPipeline:
return {
'event': 'error',
'task_id': self._application_generate_entity.task_id,
'workflow_run_id': self._task_state.workflow_run_id,
**data
}
......
api/core/app/apps/workflow/workflow_event_trigger_callback.py
View file @ 6cfda369
from typing import Optional
from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
from core.app.entities.queue_entities import (
QueueNodeFinishedEvent,
QueueNodeFailedEvent,
QueueNodeStartedEvent,
QueueNodeSucceededEvent,
QueueTextChunkEvent,
QueueWorkflowFinishedEvent,
QueueWorkflowFailedEvent,
QueueWorkflowStartedEvent,
QueueWorkflowSucceededEvent,
)
from core.workflow.callbacks.base_workflow_callback import BaseWorkflowCallback
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeType
from models.workflow import Workflow, WorkflowNodeExecution, WorkflowRun
from models.workflow import Workflow
class WorkflowEventTriggerCallback(BaseWorkflowCallback):
......@@ -17,39 +22,91 @@ class WorkflowEventTriggerCallback(BaseWorkflowCallback):
self._queue_manager = queue_manager
self._streamable_node_ids = self._fetch_streamable_node_ids(workflow.graph_dict)
def on_workflow_run_started(self, workflow_run: WorkflowRun) -> None:
def on_workflow_run_started(self) -> None:
"""
Workflow run started
"""
self._queue_manager.publish(
QueueWorkflowStartedEvent(workflow_run_id=workflow_run.id),
QueueWorkflowStartedEvent(),
PublishFrom.APPLICATION_MANAGER
)
def on_workflow_run_succeeded(self) -> None:
"""
Workflow run succeeded
"""
self._queue_manager.publish(
QueueWorkflowSucceededEvent(),
PublishFrom.APPLICATION_MANAGER
)
def on_workflow_run_finished(self, workflow_run: WorkflowRun) -> None:
def on_workflow_run_failed(self, error: str) -> None:
"""
Workflow run finished
Workflow run failed
"""
self._queue_manager.publish(
QueueWorkflowFinishedEvent(workflow_run_id=workflow_run.id),
QueueWorkflowFailedEvent(
error=error
),
PublishFrom.APPLICATION_MANAGER
)
def on_workflow_node_execute_started(self, workflow_node_execution: WorkflowNodeExecution) -> None:
def on_workflow_node_execute_started(self, node_id: str,
node_type: NodeType,
node_data: BaseNodeData,
node_run_index: int = 1,
predecessor_node_id: Optional[str] = None) -> None:
"""
Workflow node execute started
"""
self._queue_manager.publish(
QueueNodeStartedEvent(workflow_node_execution_id=workflow_node_execution.id),
QueueNodeStartedEvent(
node_id=node_id,
node_type=node_type,
node_data=node_data,
node_run_index=node_run_index,
predecessor_node_id=predecessor_node_id
),
PublishFrom.APPLICATION_MANAGER
)
def on_workflow_node_execute_succeeded(self, node_id: str,
node_type: NodeType,
node_data: BaseNodeData,
inputs: Optional[dict] = None,
process_data: Optional[dict] = None,
outputs: Optional[dict] = None,
execution_metadata: Optional[dict] = None) -> None:
"""
Workflow node execute succeeded
"""
self._queue_manager.publish(
QueueNodeSucceededEvent(
node_id=node_id,
node_type=node_type,
node_data=node_data,
inputs=inputs,
process_data=process_data,
outputs=outputs,
execution_metadata=execution_metadata
),
PublishFrom.APPLICATION_MANAGER
)
def on_workflow_node_execute_finished(self, workflow_node_execution: WorkflowNodeExecution) -> None:
def on_workflow_node_execute_failed(self, node_id: str,
node_type: NodeType,
node_data: BaseNodeData,
error: str) -> None:
"""
Workflow node execute finished
Workflow node execute failed
"""
self._queue_manager.publish(
QueueNodeFinishedEvent(workflow_node_execution_id=workflow_node_execution.id),
QueueNodeFailedEvent(
node_id=node_id,
node_type=node_type,
node_data=node_data,
error=error
),
PublishFrom.APPLICATION_MANAGER
)
......
api/core/app/apps/workflow_based_generate_task_pipeline.py 0 → 100644
View file @ 6cfda369
import json
import time
from datetime import datetime
from typing import Optional, Union
from core.model_runtime.utils.encoders import jsonable_encoder
from core.workflow.entities.node_entities import NodeType
from extensions.ext_database import db
from models.account import Account
from models.model import EndUser
from models.workflow import (
CreatedByRole,
Workflow,
WorkflowNodeExecution,
WorkflowNodeExecutionStatus,
WorkflowNodeExecutionTriggeredFrom,
WorkflowRun,
WorkflowRunStatus,
WorkflowRunTriggeredFrom,
)
class WorkflowBasedGenerateTaskPipeline:
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
new_sequence_number = max_sequence + 1
# 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({**user_inputs, **jsonable_encoder(system_inputs)}),
status=WorkflowRunStatus.RUNNING.value,
created_by_role=(CreatedByRole.ACCOUNT.value
if isinstance(user, Account) else CreatedByRole.END_USER.value),
created_by=user.id
)
db.session.add(workflow_run)
db.session.commit()
return workflow_run
def _workflow_run_success(self, workflow_run: WorkflowRun,
start_at: float,
total_tokens: int,
total_steps: int,
outputs: Optional[dict] = 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
:return:
"""
workflow_run.status = WorkflowRunStatus.SUCCEEDED.value
workflow_run.outputs = outputs
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.utcnow()
db.session.commit()
return workflow_run
def _workflow_run_failed(self, workflow_run: WorkflowRun,
start_at: float,
total_tokens: int,
total_steps: int,
status: WorkflowRunStatus,
error: str) -> 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.status = status.value
workflow_run.error = error
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.utcnow()
db.session.commit()
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:
"""
# 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
)
db.session.add(workflow_node_execution)
db.session.commit()
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:
"""
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
:return:
"""
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.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.finished_at = datetime.utcnow()
db.session.commit()
return workflow_node_execution
def _workflow_node_execution_failed(self, workflow_node_execution: WorkflowNodeExecution,
start_at: float,
error: str) -> WorkflowNodeExecution:
"""
Workflow node execution failed
:param workflow_node_execution: workflow node execution
:param start_at: start time
:param error: error message
:return:
"""
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.finished_at = datetime.utcnow()
db.session.commit()
return workflow_node_execution
api/core/app/entities/queue_entities.py
View file @ 6cfda369
from enum import Enum
from typing import Any
from typing import Any, Optional
from pydantic import BaseModel
from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeType
class QueueEvent(Enum):
......@@ -16,9 +18,11 @@ class QueueEvent(Enum):
MESSAGE_REPLACE = "message_replace"
MESSAGE_END = "message_end"
WORKFLOW_STARTED = "workflow_started"
WORKFLOW_FINISHED = "workflow_finished"
WORKFLOW_SUCCEEDED = "workflow_succeeded"
WORKFLOW_FAILED = "workflow_failed"
NODE_STARTED = "node_started"
NODE_FINISHED = "node_finished"
NODE_SUCCEEDED = "node_succeeded"
NODE_FAILED = "node_failed"
RETRIEVER_RESOURCES = "retriever_resources"
ANNOTATION_REPLY = "annotation_reply"
AGENT_THOUGHT = "agent_thought"
......@@ -96,15 +100,21 @@ class QueueWorkflowStartedEvent(AppQueueEvent):
QueueWorkflowStartedEvent entity
"""
event = QueueEvent.WORKFLOW_STARTED
workflow_run_id: str
class QueueWorkflowFinishedEvent(AppQueueEvent):
class QueueWorkflowSucceededEvent(AppQueueEvent):
"""
QueueWorkflowFinishedEvent entity
QueueWorkflowSucceededEvent entity
"""
event = QueueEvent.WORKFLOW_FINISHED
workflow_run_id: str
event = QueueEvent.WORKFLOW_SUCCEEDED
class QueueWorkflowFailedEvent(AppQueueEvent):
"""
QueueWorkflowFailedEvent entity
"""
event = QueueEvent.WORKFLOW_FAILED
error: str
class QueueNodeStartedEvent(AppQueueEvent):
......@@ -112,17 +122,45 @@ class QueueNodeStartedEvent(AppQueueEvent):
QueueNodeStartedEvent entity
"""
event = QueueEvent.NODE_STARTED
workflow_node_execution_id: str
node_id: str
node_type: NodeType
node_data: BaseNodeData
node_run_index: int = 1
predecessor_node_id: Optional[str] = None
class QueueNodeFinishedEvent(AppQueueEvent):
class QueueNodeSucceededEvent(AppQueueEvent):
"""
QueueNodeFinishedEvent entity
QueueNodeSucceededEvent entity
"""
event = QueueEvent.NODE_FINISHED
workflow_node_execution_id: str
event = QueueEvent.NODE_SUCCEEDED
node_id: str
node_type: NodeType
node_data: BaseNodeData
inputs: Optional[dict] = None
process_data: Optional[dict] = None
outputs: Optional[dict] = None
execution_metadata: Optional[dict] = None
error: Optional[str] = None
class QueueNodeFailedEvent(AppQueueEvent):
"""
QueueNodeFailedEvent entity
"""
event = QueueEvent.NODE_FAILED
node_id: str
node_type: NodeType
node_data: BaseNodeData
error: str
class QueueAgentThoughtEvent(AppQueueEvent):
"""
QueueAgentThoughtEvent entity
......
api/core/workflow/callbacks/base_workflow_callback.py
View file @ 6cfda369
from abc import ABC, abstractmethod
from typing import Optional
from models.workflow import WorkflowNodeExecution, WorkflowRun
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeType
class BaseWorkflowCallback(ABC):
@abstractmethod
def on_workflow_run_started(self, workflow_run: WorkflowRun) -> None:
def on_workflow_run_started(self) -> None:
"""
Workflow run started
"""
raise NotImplementedError
@abstractmethod
def on_workflow_run_finished(self, workflow_run: WorkflowRun) -> None:
def on_workflow_run_succeeded(self) -> None:
"""
Workflow run finished
Workflow run succeeded
"""
raise NotImplementedError
@abstractmethod
def on_workflow_node_execute_started(self, workflow_node_execution: WorkflowNodeExecution) -> None:
def on_workflow_run_failed(self, error: str) -> None:
"""
Workflow run failed
"""
raise NotImplementedError
@abstractmethod
def on_workflow_node_execute_started(self, node_id: str,
node_type: NodeType,
node_data: BaseNodeData,
node_run_index: int = 1,
predecessor_node_id: Optional[str] = None) -> None:
"""
Workflow node execute started
"""
raise NotImplementedError
@abstractmethod
def on_workflow_node_execute_finished(self, workflow_node_execution: WorkflowNodeExecution) -> None:
def on_workflow_node_execute_succeeded(self, node_id: str,
node_type: NodeType,
node_data: BaseNodeData,
inputs: Optional[dict] = None,
process_data: Optional[dict] = None,
outputs: Optional[dict] = None,
execution_metadata: Optional[dict] = None) -> None:
"""
Workflow node execute finished
Workflow node execute succeeded
"""
raise NotImplementedError
@abstractmethod
def on_workflow_node_execute_failed(self, node_id: str,
node_type: NodeType,
node_data: BaseNodeData,
error: str) -> None:
"""
Workflow node execute failed
"""
raise NotImplementedError
......@@ -38,4 +67,3 @@ class BaseWorkflowCallback(ABC):
Publish text chunk
"""
raise NotImplementedError
api/core/workflow/entities/workflow_entities.py
View file @ 6cfda369
from typing import Optional
from core.workflow.entities.node_entities import NodeRunResult
from core.workflow.entities.variable_pool import VariablePool
from models.workflow import WorkflowNodeExecution, WorkflowRun
from core.workflow.nodes.base_node import BaseNode
from models.workflow import Workflow
class WorkflowNodeAndResult:
node: BaseNode
result: Optional[NodeRunResult] = None
def __init__(self, node: BaseNode, result: Optional[NodeRunResult] = None):
self.node = node
self.result = result
class WorkflowRunState:
workflow_run: WorkflowRun
workflow: Workflow
start_at: float
user_inputs: dict
variable_pool: VariablePool
total_tokens: int = 0
workflow_node_executions: list[WorkflowNodeExecution] = []
workflow_nodes_and_results: list[WorkflowNodeAndResult] = []
def __init__(self, workflow_run: WorkflowRun,
start_at: float,
user_inputs: dict,
variable_pool: VariablePool) -> None:
self.workflow_run = workflow_run
def __init__(self, workflow: Workflow, start_at: float, user_inputs: dict, variable_pool: VariablePool):
self.workflow = workflow
self.start_at = start_at
self.user_inputs = user_inputs
self.variable_pool = variable_pool
api/core/workflow/nodes/direct_answer/direct_answer_node.py
View file @ 6cfda369
......@@ -43,7 +43,7 @@ class DirectAnswerNode(BaseNode):
# publish answer as stream
for word in answer:
self.publish_text_chunk(word)
time.sleep(0.01)
time.sleep(0.01) # todo sleep 0.01
return NodeRunResult(
status=WorkflowNodeExecutionStatus.SUCCEEDED,
......
api/core/workflow/workflow_engine_manager.py
View file @ 6cfda369
import json
import time
from datetime import datetime
from typing import Optional, Union
from typing import Optional
from core.model_runtime.utils.encoders import jsonable_encoder
from core.app.apps.base_app_queue_manager import GenerateTaskStoppedException
from core.workflow.callbacks.base_workflow_callback import BaseWorkflowCallback
from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType
from core.workflow.entities.variable_pool import VariablePool, VariableValue
from core.workflow.entities.workflow_entities import WorkflowRunState
from core.workflow.entities.workflow_entities import WorkflowNodeAndResult, WorkflowRunState
from core.workflow.nodes.base_node import BaseNode
from core.workflow.nodes.code.code_node import CodeNode
from core.workflow.nodes.direct_answer.direct_answer_node import DirectAnswerNode
......@@ -21,18 +19,9 @@ from core.workflow.nodes.start.start_node import StartNode
from core.workflow.nodes.template_transform.template_transform_node import TemplateTransformNode
from core.workflow.nodes.tool.tool_node import ToolNode
from core.workflow.nodes.variable_assigner.variable_assigner_node import VariableAssignerNode
from extensions.ext_database import db
from models.account import Account
from models.model import App, EndUser
from models.workflow import (
CreatedByRole,
Workflow,
WorkflowNodeExecution,
WorkflowNodeExecutionStatus,
WorkflowNodeExecutionTriggeredFrom,
WorkflowRun,
WorkflowRunStatus,
WorkflowRunTriggeredFrom,
WorkflowType,
)
......@@ -53,20 +42,6 @@ node_classes = {
class WorkflowEngineManager:
def get_workflow(self, app_model: App, workflow_id: str) -> Optional[Workflow]:
"""
Get workflow
"""
# fetch workflow by workflow_id
workflow = db.session.query(Workflow).filter(
Workflow.tenant_id == app_model.tenant_id,
Workflow.app_id == app_model.id,
Workflow.id == workflow_id
).first()
# return workflow
return workflow
def get_default_configs(self) -> list[dict]:
"""
Get default block configs
......@@ -100,16 +75,12 @@ class WorkflowEngineManager:
return default_config
def run_workflow(self, workflow: Workflow,
triggered_from: WorkflowRunTriggeredFrom,
user: Union[Account, EndUser],
user_inputs: dict,
system_inputs: Optional[dict] = None,
callbacks: list[BaseWorkflowCallback] = None) -> None:
"""
Run workflow
: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
:param callbacks: workflow callbacks
......@@ -130,18 +101,13 @@ class WorkflowEngineManager:
raise ValueError('edges in workflow graph must be a list')
# init workflow run
workflow_run = self._init_workflow_run(
workflow=workflow,
triggered_from=triggered_from,
user=user,
user_inputs=user_inputs,
system_inputs=system_inputs,
callbacks=callbacks
)
if callbacks:
for callback in callbacks:
callback.on_workflow_run_started()
# init workflow run state
workflow_run_state = WorkflowRunState(
workflow_run=workflow_run,
workflow=workflow,
start_at=time.perf_counter(),
user_inputs=user_inputs,
variable_pool=VariablePool(
......@@ -166,7 +132,7 @@ class WorkflowEngineManager:
has_entry_node = True
# max steps 30 reached
if len(workflow_run_state.workflow_node_executions) > 30:
if len(workflow_run_state.workflow_nodes_and_results) > 30:
raise ValueError('Max steps 30 reached.')
# or max execution time 10min reached
......@@ -188,14 +154,14 @@ class WorkflowEngineManager:
if not has_entry_node:
self._workflow_run_failed(
workflow_run_state=workflow_run_state,
error='Start node not found in workflow graph.',
callbacks=callbacks
)
return
except GenerateTaskStoppedException as e:
return
except Exception as e:
self._workflow_run_failed(
workflow_run_state=workflow_run_state,
error=str(e),
callbacks=callbacks
)
......@@ -203,112 +169,33 @@ class WorkflowEngineManager:
# workflow run success
self._workflow_run_success(
workflow_run_state=workflow_run_state,
callbacks=callbacks
)
def _init_workflow_run(self, workflow: Workflow,
triggered_from: WorkflowRunTriggeredFrom,
user: Union[Account, EndUser],
user_inputs: dict,
system_inputs: Optional[dict] = None,
callbacks: list[BaseWorkflowCallback] = 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
:param callbacks: workflow callbacks
: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
new_sequence_number = max_sequence + 1
# 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({**user_inputs, **jsonable_encoder(system_inputs)}),
status=WorkflowRunStatus.RUNNING.value,
created_by_role=(CreatedByRole.ACCOUNT.value
if isinstance(user, Account) else CreatedByRole.END_USER.value),
created_by=user.id
)
db.session.add(workflow_run)
db.session.commit()
if callbacks:
for callback in callbacks:
callback.on_workflow_run_started(workflow_run)
return workflow_run
def _workflow_run_success(self, workflow_run_state: WorkflowRunState,
callbacks: list[BaseWorkflowCallback] = None) -> WorkflowRun:
def _workflow_run_success(self, callbacks: list[BaseWorkflowCallback] = None) -> None:
"""
Workflow run success
:param workflow_run_state: workflow run state
:param callbacks: workflow callbacks
:return:
"""
workflow_run = workflow_run_state.workflow_run
workflow_run.status = WorkflowRunStatus.SUCCEEDED.value
# fetch last workflow_node_executions
last_workflow_node_execution = workflow_run_state.workflow_node_executions[-1]
if last_workflow_node_execution:
workflow_run.outputs = last_workflow_node_execution.outputs
workflow_run.elapsed_time = time.perf_counter() - workflow_run_state.start_at
workflow_run.total_tokens = workflow_run_state.total_tokens
workflow_run.total_steps = len(workflow_run_state.workflow_node_executions)
workflow_run.finished_at = datetime.utcnow()
db.session.commit()
if callbacks:
for callback in callbacks:
callback.on_workflow_run_finished(workflow_run)
callback.on_workflow_run_succeeded()
return workflow_run
def _workflow_run_failed(self, workflow_run_state: WorkflowRunState,
error: str,
callbacks: list[BaseWorkflowCallback] = None) -> WorkflowRun:
def _workflow_run_failed(self, error: str,
callbacks: list[BaseWorkflowCallback] = None) -> None:
"""
Workflow run failed
:param workflow_run_state: workflow run state
:param error: error message
:param callbacks: workflow callbacks
:return:
"""
workflow_run = workflow_run_state.workflow_run
workflow_run.status = WorkflowRunStatus.FAILED.value
workflow_run.error = error
workflow_run.elapsed_time = time.perf_counter() - workflow_run_state.start_at
workflow_run.total_tokens = workflow_run_state.total_tokens
workflow_run.total_steps = len(workflow_run_state.workflow_node_executions)
workflow_run.finished_at = datetime.utcnow()
db.session.commit()
if callbacks:
for callback in callbacks:
callback.on_workflow_run_finished(workflow_run)
return workflow_run
callback.on_workflow_run_failed(
error=error
)
def _get_next_node(self, graph: dict,
predecessor_node: Optional[BaseNode] = None,
......@@ -384,18 +271,24 @@ class WorkflowEngineManager:
def _run_workflow_node(self, workflow_run_state: WorkflowRunState,
node: BaseNode,
predecessor_node: Optional[BaseNode] = None,
callbacks: list[BaseWorkflowCallback] = None) -> WorkflowNodeExecution:
# init workflow node execution
start_at = time.perf_counter()
workflow_node_execution = self._init_node_execution_from_workflow_run(
workflow_run_state=workflow_run_state,
callbacks: list[BaseWorkflowCallback] = None) -> None:
if callbacks:
for callback in callbacks:
callback.on_workflow_node_execute_started(
node_id=node.node_id,
node_type=node.node_type,
node_data=node.node_data,
node_run_index=len(workflow_run_state.workflow_nodes_and_results) + 1,
predecessor_node_id=predecessor_node.node_id if predecessor_node else None
)
workflow_nodes_and_result = WorkflowNodeAndResult(
node=node,
predecessor_node=predecessor_node,
callbacks=callbacks
result=None
)
# add to workflow node executions
workflow_run_state.workflow_node_executions.append(workflow_node_execution)
# add to workflow_nodes_and_results
workflow_run_state.workflow_nodes_and_results.append(workflow_nodes_and_result)
# run node, result must have inputs, process_data, outputs, execution_metadata
node_run_result = node.run(
......@@ -406,24 +299,34 @@ class WorkflowEngineManager:
if node_run_result.status == WorkflowNodeExecutionStatus.FAILED:
# node run failed
self._workflow_node_execution_failed(
workflow_node_execution=workflow_node_execution,
start_at=start_at,
error=node_run_result.error,
callbacks=callbacks
)
if callbacks:
for callback in callbacks:
callback.on_workflow_node_execute_failed(
node_id=node.node_id,
node_type=node.node_type,
node_data=node.node_data,
error=node_run_result.error
)
raise ValueError(f"Node {node.node_data.title} run failed: {node_run_result.error}")
# set end node output if in chat
self._set_end_node_output_if_in_chat(workflow_run_state, node, node_run_result)
workflow_nodes_and_result.result = node_run_result
# node run success
self._workflow_node_execution_success(
workflow_node_execution=workflow_node_execution,
start_at=start_at,
result=node_run_result,
callbacks=callbacks
)
if callbacks:
for callback in callbacks:
callback.on_workflow_node_execute_succeeded(
node_id=node.node_id,
node_type=node.node_type,
node_data=node.node_data,
inputs=node_run_result.inputs,
process_data=node_run_result.process_data,
outputs=node_run_result.outputs,
execution_metadata=node_run_result.metadata
)
if node_run_result.outputs:
for variable_key, variable_value in node_run_result.outputs.items():
......@@ -438,105 +341,9 @@ class WorkflowEngineManager:
if node_run_result.metadata and node_run_result.metadata.get(NodeRunMetadataKey.TOTAL_TOKENS):
workflow_run_state.total_tokens += int(node_run_result.metadata.get(NodeRunMetadataKey.TOTAL_TOKENS))
return workflow_node_execution
def _init_node_execution_from_workflow_run(self, workflow_run_state: WorkflowRunState,
node: BaseNode,
predecessor_node: Optional[BaseNode] = None,
callbacks: list[BaseWorkflowCallback] = None) -> WorkflowNodeExecution:
"""
Init workflow node execution from workflow run
:param workflow_run_state: workflow run state
:param node: current node
:param predecessor_node: predecessor node if exists
:param callbacks: workflow callbacks
:return:
"""
workflow_run = workflow_run_state.workflow_run
# 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.node_id if predecessor_node else None,
index=len(workflow_run_state.workflow_node_executions) + 1,
node_id=node.node_id,
node_type=node.node_type.value,
title=node.node_data.title,
status=WorkflowNodeExecutionStatus.RUNNING.value,
created_by_role=workflow_run.created_by_role,
created_by=workflow_run.created_by
)
db.session.add(workflow_node_execution)
db.session.commit()
if callbacks:
for callback in callbacks:
callback.on_workflow_node_execute_started(workflow_node_execution)
return workflow_node_execution
def _workflow_node_execution_success(self, workflow_node_execution: WorkflowNodeExecution,
start_at: float,
result: NodeRunResult,
callbacks: list[BaseWorkflowCallback] = None) -> WorkflowNodeExecution:
"""
Workflow node execution success
:param workflow_node_execution: workflow node execution
:param start_at: start time
:param result: node run result
:param callbacks: workflow callbacks
:return:
"""
workflow_node_execution.status = WorkflowNodeExecutionStatus.SUCCEEDED.value
workflow_node_execution.elapsed_time = time.perf_counter() - start_at
workflow_node_execution.inputs = json.dumps(result.inputs) if result.inputs else None
workflow_node_execution.process_data = json.dumps(result.process_data) if result.process_data else None
workflow_node_execution.outputs = json.dumps(result.outputs) if result.outputs else None
workflow_node_execution.execution_metadata = json.dumps(jsonable_encoder(result.metadata)) \
if result.metadata else None
workflow_node_execution.finished_at = datetime.utcnow()
db.session.commit()
if callbacks:
for callback in callbacks:
callback.on_workflow_node_execute_finished(workflow_node_execution)
return workflow_node_execution
def _workflow_node_execution_failed(self, workflow_node_execution: WorkflowNodeExecution,
start_at: float,
error: str,
callbacks: list[BaseWorkflowCallback] = None) -> WorkflowNodeExecution:
"""
Workflow node execution failed
:param workflow_node_execution: workflow node execution
:param start_at: start time
:param error: error message
:param callbacks: workflow callbacks
:return:
"""
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.finished_at = datetime.utcnow()
db.session.commit()
if callbacks:
for callback in callbacks:
callback.on_workflow_node_execute_finished(workflow_node_execution)
return workflow_node_execution
def _set_end_node_output_if_in_chat(self, workflow_run_state: WorkflowRunState,
node: BaseNode,
node_run_result: NodeRunResult):
node_run_result: NodeRunResult) -> None:
"""
Set end node output if in chat
:param workflow_run_state: workflow run state
......@@ -544,21 +351,19 @@ class WorkflowEngineManager:
:param node_run_result: node run result
:return:
"""
if workflow_run_state.workflow_run.type == WorkflowType.CHAT.value and node.node_type == NodeType.END:
workflow_node_execution_before_end = workflow_run_state.workflow_node_executions[-2]
if workflow_node_execution_before_end:
if workflow_node_execution_before_end.node_type == NodeType.LLM.value:
if workflow_run_state.workflow.type == WorkflowType.CHAT.value and node.node_type == NodeType.END:
workflow_nodes_and_result_before_end = workflow_run_state.workflow_nodes_and_results[-2]
if workflow_nodes_and_result_before_end:
if workflow_nodes_and_result_before_end.node.node_type == NodeType.LLM.value:
if not node_run_result.outputs:
node_run_result.outputs = {}
node_run_result.outputs['text'] = workflow_node_execution_before_end.outputs_dict.get('text')
elif workflow_node_execution_before_end.node_type == NodeType.DIRECT_ANSWER.value:
node_run_result.outputs['text'] = workflow_nodes_and_result_before_end.result.outputs.get('text')
elif workflow_nodes_and_result_before_end.node.node_type == NodeType.DIRECT_ANSWER.value:
if not node_run_result.outputs:
node_run_result.outputs = {}
node_run_result.outputs['text'] = workflow_node_execution_before_end.outputs_dict.get('answer')
return node_run_result
node_run_result.outputs['text'] = workflow_nodes_and_result_before_end.result.outputs.get('answer')
def _append_variables_recursively(self, variable_pool: VariablePool,
node_id: str,
......
api/services/workflow_service.py
View file @ 6cfda369
......@@ -5,6 +5,7 @@ from typing import Optional, Union
from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfigManager
from core.app.apps.advanced_chat.app_generator import AdvancedChatAppGenerator
from core.app.apps.base_app_queue_manager import AppQueueManager
from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager
from core.app.apps.workflow.app_generator import WorkflowAppGenerator
from core.app.entities.app_invoke_entities import InvokeFrom
......@@ -44,10 +45,14 @@ class WorkflowService:
if not app_model.workflow_id:
return None
workflow_engine_manager = WorkflowEngineManager()
# fetch published workflow by workflow_id
return workflow_engine_manager.get_workflow(app_model, app_model.workflow_id)
workflow = db.session.query(Workflow).filter(
Workflow.tenant_id == app_model.tenant_id,
Workflow.app_id == app_model.id,
Workflow.id == app_model.workflow_id
).first()
return workflow
def sync_draft_workflow(self, app_model: App,
graph: dict,
......@@ -201,6 +206,14 @@ class WorkflowService:
return response
def stop_workflow_task(self, task_id: str,
user: Union[Account, EndUser],
invoke_from: InvokeFrom) -> None:
"""
Stop workflow task
"""
AppQueueManager.set_stop_flag(task_id, invoke_from, user.id)
def convert_to_workflow(self, app_model: App, account: Account) -> App:
"""
Basic mode of chatbot app(expert mode) to workflow
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment