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feat(workflow): fix iteration single debug

This commit is contained in:
takatost 2024-08-15 03:12:49 +08:00
parent 6f6b32e1ee
commit 1da5862a96
22 changed files with 378 additions and 390 deletions
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147
api/core/app/apps/advanced_chat/app_runner.py
View File

@ -7,7 +7,7 @@ from sqlalchemy import select
from sqlalchemy.orm import Session
from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfig
from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
from core.app.apps.base_app_queue_manager import AppQueueManager
from core.app.apps.workflow_app_runner import WorkflowBasedAppRunner
from core.app.apps.workflow_logging_callback import WorkflowLoggingCallback
from core.app.entities.app_invoke_entities import (
@ -15,7 +15,6 @@ from core.app.entities.app_invoke_entities import (
InvokeFrom,
)
from core.app.entities.queue_entities import (
AppQueueEvent,
QueueAnnotationReplyEvent,
QueueStopEvent,
QueueTextChunkEvent,
@ -84,86 +83,84 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
if bool(os.environ.get("DEBUG", 'False').lower() == 'true'):
workflow_callbacks.append(WorkflowLoggingCallback())
# if only single iteration run is requested
if self.application_generate_entity.single_iteration_run:
node_id = self.application_generate_entity.single_iteration_run.node_id
user_inputs = self.application_generate_entity.single_iteration_run.inputs
generator = WorkflowEntry.single_step_run_iteration(
# if only single iteration run is requested
graph, variable_pool = self._get_graph_and_variable_pool_of_single_iteration(
workflow=workflow,
node_id=node_id,
user_id=self.application_generate_entity.user_id,
user_inputs=user_inputs,
callbacks=workflow_callbacks
node_id=self.application_generate_entity.single_iteration_run.node_id,
user_inputs=self.application_generate_entity.single_iteration_run.inputs
)
else:
inputs = self.application_generate_entity.inputs
query = self.application_generate_entity.query
files = self.application_generate_entity.files
# moderation
if self.handle_input_moderation(
app_record=app_record,
app_generate_entity=self.application_generate_entity,
inputs=inputs,
query=query,
message_id=self.message.id
):
return
# annotation reply
if self.handle_annotation_reply(
app_record=app_record,
message=self.message,
query=query,
app_generate_entity=self.application_generate_entity
):
return
db.session.close()
# Init conversation variables
stmt = select(ConversationVariable).where(
ConversationVariable.app_id == self.conversation.app_id, ConversationVariable.conversation_id == self.conversation.id
)
with Session(db.engine) as session:
conversation_variables = session.scalars(stmt).all()
if not conversation_variables:
conversation_variables = [
ConversationVariable.from_variable(
app_id=self.conversation.app_id, conversation_id=self.conversation.id, variable=variable
)
for variable in workflow.conversation_variables
]
session.add_all(conversation_variables)
session.commit()
# Convert database entities to variables
conversation_variables = [item.to_variable() for item in conversation_variables]
# Create a variable pool.
system_inputs = {
SystemVariable.QUERY: query,
SystemVariable.FILES: files,
SystemVariable.CONVERSATION_ID: self.conversation.id,
SystemVariable.USER_ID: user_id,
}
# init variable pool
variable_pool = VariablePool(
system_variables=system_inputs,
user_inputs=inputs,
environment_variables=workflow.environment_variables,
conversation_variables=conversation_variables,
)
for event in generator:
# TODO
self._handle_event(workflow_entry, event)
return
inputs = self.application_generate_entity.inputs
query = self.application_generate_entity.query
files = self.application_generate_entity.files
# moderation
if self.handle_input_moderation(
app_record=app_record,
app_generate_entity=self.application_generate_entity,
inputs=inputs,
query=query,
message_id=self.message.id
):
return
# annotation reply
if self.handle_annotation_reply(
app_record=app_record,
message=self.message,
query=query,
app_generate_entity=self.application_generate_entity
):
return
db.session.close()
# Init conversation variables
stmt = select(ConversationVariable).where(
ConversationVariable.app_id == self.conversation.app_id, ConversationVariable.conversation_id == self.conversation.id
)
with Session(db.engine) as session:
conversation_variables = session.scalars(stmt).all()
if not conversation_variables:
conversation_variables = [
ConversationVariable.from_variable(
app_id=self.conversation.app_id, conversation_id=self.conversation.id, variable=variable
)
for variable in workflow.conversation_variables
]
session.add_all(conversation_variables)
session.commit()
# Convert database entities to variables
conversation_variables = [item.to_variable() for item in conversation_variables]
# Create a variable pool.
system_inputs = {
SystemVariable.QUERY: query,
SystemVariable.FILES: files,
SystemVariable.CONVERSATION_ID: self.conversation.id,
SystemVariable.USER_ID: user_id,
}
# init variable pool
variable_pool = VariablePool(
system_variables=system_inputs,
user_inputs=inputs,
environment_variables=workflow.environment_variables,
conversation_variables=conversation_variables,
)
# init graph
graph = self._init_graph(graph_config=workflow.graph_dict)
# RUN WORKFLOW
workflow_entry = WorkflowEntry(
workflow=workflow,
tenant_id=workflow.tenant_id,
app_id=workflow.app_id,
workflow_id=workflow.id,
workflow_type=workflow.type,
graph=graph,
graph_config=workflow.graph_dict,
user_id=self.application_generate_entity.user_id,
user_from=(
UserFrom.ACCOUNT

15
api/core/app/apps/advanced_chat/generate_task_pipeline.py
View File

@ -276,25 +276,34 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
event=event
)
yield self._workflow_node_start_to_stream_response(
response = self._workflow_node_start_to_stream_response(
event=event,
task_id=self._application_generate_entity.task_id,
workflow_node_execution=workflow_node_execution
)
if response:
yield response
elif isinstance(event, QueueNodeSucceededEvent):
workflow_node_execution = self._handle_workflow_node_execution_success(event)
yield self._workflow_node_finish_to_stream_response(
response = self._workflow_node_finish_to_stream_response(
task_id=self._application_generate_entity.task_id,
workflow_node_execution=workflow_node_execution
)
if response:
yield response
elif isinstance(event, QueueNodeFailedEvent):
workflow_node_execution = self._handle_workflow_node_execution_failed(event)
yield self._workflow_node_finish_to_stream_response(
response = self._workflow_node_finish_to_stream_response(
task_id=self._application_generate_entity.task_id,
workflow_node_execution=workflow_node_execution
)
if response:
yield response
elif isinstance(event, QueueIterationStartEvent):
if not workflow_run:
raise Exception('Workflow run not initialized.')

58
api/core/app/apps/workflow/app_runner.py
View File

@ -71,41 +71,41 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
# if only single iteration run is requested
if self.application_generate_entity.single_iteration_run:
node_id = self.application_generate_entity.single_iteration_run.node_id
user_inputs = self.application_generate_entity.single_iteration_run.inputs
generator = WorkflowEntry.single_step_run_iteration(
# if only single iteration run is requested
graph, variable_pool = self._get_graph_and_variable_pool_of_single_iteration(
workflow=workflow,
node_id=node_id,
user_id=self.application_generate_entity.user_id,
user_inputs=user_inputs,
callbacks=workflow_callbacks
node_id=self.application_generate_entity.single_iteration_run.node_id,
user_inputs=self.application_generate_entity.single_iteration_run.inputs
)
else:
inputs = self.application_generate_entity.inputs
files = self.application_generate_entity.files
# Create a variable pool.
system_inputs = {
SystemVariable.FILES: files,
SystemVariable.USER_ID: user_id,
}
variable_pool = VariablePool(
system_variables=system_inputs,
user_inputs=inputs,
environment_variables=workflow.environment_variables,
conversation_variables=[],
)
for event in generator:
# TODO
self._handle_event(workflow_entry, event)
return
inputs = self.application_generate_entity.inputs
files = self.application_generate_entity.files
# Create a variable pool.
system_inputs = {
SystemVariable.FILES: files,
SystemVariable.USER_ID: user_id,
}
variable_pool = VariablePool(
system_variables=system_inputs,
user_inputs=inputs,
environment_variables=workflow.environment_variables,
conversation_variables=[],
)
# init graph
graph = self._init_graph(graph_config=workflow.graph_dict)
# RUN WORKFLOW
workflow_entry = WorkflowEntry(
workflow=workflow,
tenant_id=workflow.tenant_id,
app_id=workflow.app_id,
workflow_id=workflow.id,
workflow_type=workflow.type,
graph=graph,
graph_config=workflow.graph_dict,
user_id=self.application_generate_entity.user_id,
user_from=(
UserFrom.ACCOUNT

15
api/core/app/apps/workflow/generate_task_pipeline.py
View File

@ -249,25 +249,34 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
event=event
)
yield self._workflow_node_start_to_stream_response(
response = self._workflow_node_start_to_stream_response(
event=event,
task_id=self._application_generate_entity.task_id,
workflow_node_execution=workflow_node_execution
)
if response:
yield response
elif isinstance(event, QueueNodeSucceededEvent):
workflow_node_execution = self._handle_workflow_node_execution_success(event)
yield self._workflow_node_finish_to_stream_response(
response = self._workflow_node_finish_to_stream_response(
task_id=self._application_generate_entity.task_id,
workflow_node_execution=workflow_node_execution
)
if response:
yield response
elif isinstance(event, QueueNodeFailedEvent):
workflow_node_execution = self._handle_workflow_node_execution_failed(event)
yield self._workflow_node_finish_to_stream_response(
response = self._workflow_node_finish_to_stream_response(
task_id=self._application_generate_entity.task_id,
workflow_node_execution=workflow_node_execution
)
if response:
yield response
elif isinstance(event, QueueIterationStartEvent):
if not workflow_run:
raise Exception('Workflow run not initialized.')

124
api/core/app/apps/workflow_app_runner.py
View File

@ -1,4 +1,4 @@
from typing import Optional
from typing import Any, Mapping, Optional, cast
from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
from core.app.apps.base_app_runner import AppRunner
@ -18,6 +18,8 @@ from core.app.entities.queue_entities import (
QueueWorkflowStartedEvent,
QueueWorkflowSucceededEvent,
)
from core.workflow.entities.node_entities import NodeType
from core.workflow.entities.variable_pool import VariablePool
from core.workflow.graph_engine.entities.event import (
GraphEngineEvent,
GraphRunFailedEvent,
@ -36,6 +38,10 @@ from core.workflow.graph_engine.entities.event import (
ParallelBranchRunStartedEvent,
ParallelBranchRunSucceededEvent,
)
from core.workflow.graph_engine.entities.graph import Graph
from core.workflow.nodes.base_node import BaseNode
from core.workflow.nodes.iteration.entities import IterationNodeData
from core.workflow.nodes.node_mapping import node_classes
from core.workflow.workflow_entry import WorkflowEntry
from extensions.ext_database import db
from models.model import App
@ -46,6 +52,122 @@ class WorkflowBasedAppRunner(AppRunner):
def __init__(self, queue_manager: AppQueueManager):
self.queue_manager = queue_manager
def _init_graph(self, graph_config: Mapping[str, Any]) -> Graph:
"""
Init graph
"""
if 'nodes' not in graph_config or 'edges' not in graph_config:
raise ValueError('nodes or edges not found in workflow graph')
if not isinstance(graph_config.get('nodes'), list):
raise ValueError('nodes in workflow graph must be a list')
if not isinstance(graph_config.get('edges'), list):
raise ValueError('edges in workflow graph must be a list')
# init graph
graph = Graph.init(
graph_config=graph_config
)
if not graph:
raise ValueError('graph not found in workflow')
return graph
def _get_graph_and_variable_pool_of_single_iteration(
self,
workflow: Workflow,
node_id: str,
user_inputs: dict,
) -> tuple[Graph, VariablePool]:
"""
Get variable pool of single iteration
"""
# fetch workflow graph
graph_config = workflow.graph_dict
if not graph_config:
raise ValueError('workflow graph not found')
graph_config = cast(dict[str, Any], graph_config)
if 'nodes' not in graph_config or 'edges' not in graph_config:
raise ValueError('nodes or edges not found in workflow graph')
if not isinstance(graph_config.get('nodes'), list):
raise ValueError('nodes in workflow graph must be a list')
if not isinstance(graph_config.get('edges'), list):
raise ValueError('edges in workflow graph must be a list')
# filter nodes only in iteration
node_configs = [
node for node in graph_config.get('nodes', [])
if node.get('id') == node_id or node.get('data', {}).get('iteration_id', '') == node_id
]
graph_config['nodes'] = node_configs
node_ids = [node.get('id') for node in node_configs]
# filter edges only in iteration
edge_configs = [
edge for edge in graph_config.get('edges', [])
if (edge.get('source') is None or edge.get('source') in node_ids)
and (edge.get('target') is None or edge.get('target') in node_ids)
]
graph_config['edges'] = edge_configs
# init graph
graph = Graph.init(
graph_config=graph_config,
root_node_id=node_id
)
if not graph:
raise ValueError('graph not found in workflow')
# fetch node config from node id
iteration_node_config = None
for node in node_configs:
if node.get('id') == node_id:
iteration_node_config = node
break
if not iteration_node_config:
raise ValueError('iteration node id not found in workflow graph')
# Get node class
node_type = NodeType.value_of(iteration_node_config.get('data', {}).get('type'))
node_cls = node_classes.get(node_type)
node_cls = cast(type[BaseNode], node_cls)
# init variable pool
variable_pool = VariablePool(
system_variables={},
user_inputs={},
environment_variables=workflow.environment_variables,
)
try:
variable_mapping = node_cls.extract_variable_selector_to_variable_mapping(
graph_config=workflow.graph_dict,
config=iteration_node_config
)
except NotImplementedError:
variable_mapping = {}
WorkflowEntry.mapping_user_inputs_to_variable_pool(
variable_mapping=variable_mapping,
user_inputs=user_inputs,
variable_pool=variable_pool,
tenant_id=workflow.tenant_id,
node_type=node_type,
node_data=IterationNodeData(**iteration_node_config.get('data', {}))
)
return graph, variable_pool
def _handle_event(self, workflow_entry: WorkflowEntry, event: GraphEngineEvent) -> None:
"""
Handle event

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

@ -231,7 +231,6 @@ class WorkflowCycleManage:
outputs = WorkflowEntry.handle_special_values(event.outputs)
workflow_node_execution.status = WorkflowNodeExecutionStatus.SUCCEEDED.value
workflow_node_execution.elapsed_time = time.perf_counter() - event.start_at.timestamp()
workflow_node_execution.inputs = json.dumps(inputs) if inputs 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
@ -239,6 +238,7 @@ class WorkflowCycleManage:
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)
@ -259,11 +259,11 @@ class WorkflowCycleManage:
workflow_node_execution.status = WorkflowNodeExecutionStatus.FAILED.value
workflow_node_execution.error = event.error
workflow_node_execution.elapsed_time = time.perf_counter() - event.start_at.timestamp()
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(event.process_data) if event.process_data else None
workflow_node_execution.outputs = json.dumps(outputs) if outputs 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)
@ -344,7 +344,7 @@ class WorkflowCycleManage:
def _workflow_node_start_to_stream_response(
self, event: QueueNodeStartedEvent, task_id: str, workflow_node_execution: WorkflowNodeExecution
) -> NodeStartStreamResponse:
) -> Optional[NodeStartStreamResponse]:
"""
Workflow node start to stream response.
:param event: queue node started event
@ -352,6 +352,9 @@ class WorkflowCycleManage:
: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,
@ -380,13 +383,16 @@ class WorkflowCycleManage:
def _workflow_node_finish_to_stream_response(
self, task_id: str, workflow_node_execution: WorkflowNodeExecution
) -> NodeFinishStreamResponse:
) -> Optional[NodeFinishStreamResponse]:
"""
Workflow node finish to stream response.
: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,
@ -483,7 +489,7 @@ class WorkflowCycleManage:
inputs=event.inputs or {},
status=WorkflowNodeExecutionStatus.SUCCEEDED,
error=None,
elapsed_time=time.perf_counter() - event.start_at.timestamp(),
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()),

1
api/core/workflow/errors.py
View File

@ -1,4 +1,3 @@
from core.workflow.entities.node_entities import NodeType
from core.workflow.nodes.base_node import BaseNode

134
api/core/workflow/graph_engine/graph_engine.py
View File

@ -39,7 +39,7 @@ from core.workflow.graph_engine.entities.runtime_route_state import RouteNodeSta
from core.workflow.nodes.answer.answer_stream_processor import AnswerStreamProcessor
from core.workflow.nodes.base_node import BaseNode
from core.workflow.nodes.end.end_stream_processor import EndStreamProcessor
from core.workflow.nodes.event import RunCompletedEvent, RunRetrieverResourceEvent, RunStreamChunkEvent
from core.workflow.nodes.event import RunCompletedEvent, RunEvent, RunRetrieverResourceEvent, RunStreamChunkEvent
from core.workflow.nodes.node_mapping import node_classes
from extensions.ext_database import db
from models.workflow import WorkflowNodeExecutionStatus, WorkflowType
@ -400,81 +400,85 @@ class GraphEngine:
# run node
generator = node_instance.run()
for item in generator:
if isinstance(item, RunCompletedEvent):
run_result = item.run_result
route_node_state.set_finished(run_result=run_result)
if isinstance(item, GraphEngineEvent):
if isinstance(item, BaseIterationEvent):
# add parallel info to iteration event
item.parallel_id = parallel_id
item.parallel_start_node_id = parallel_start_node_id
if run_result.status == WorkflowNodeExecutionStatus.FAILED:
yield NodeRunFailedEvent(
error=route_node_state.failed_reason or 'Unknown error.',
id=node_instance.id,
node_id=node_instance.node_id,
node_type=node_instance.node_type,
node_data=node_instance.node_data,
route_node_state=route_node_state,
parallel_id=parallel_id,
parallel_start_node_id=parallel_start_node_id
)
elif run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED:
if run_result.metadata and run_result.metadata.get(NodeRunMetadataKey.TOTAL_TOKENS):
# plus state total_tokens
self.graph_runtime_state.total_tokens += int(
run_result.metadata.get(NodeRunMetadataKey.TOTAL_TOKENS) # type: ignore[arg-type]
yield item
else:
if isinstance(item, RunCompletedEvent):
run_result = item.run_result
route_node_state.set_finished(run_result=run_result)
if run_result.status == WorkflowNodeExecutionStatus.FAILED:
yield NodeRunFailedEvent(
error=route_node_state.failed_reason or 'Unknown error.',
id=node_instance.id,
node_id=node_instance.node_id,
node_type=node_instance.node_type,
node_data=node_instance.node_data,
route_node_state=route_node_state,
parallel_id=parallel_id,
parallel_start_node_id=parallel_start_node_id
)
if run_result.llm_usage:
# use the latest usage
self.graph_runtime_state.llm_usage += run_result.llm_usage
# append node output variables to variable pool
if run_result.outputs:
for variable_key, variable_value in run_result.outputs.items():
# append variables to variable pool recursively
self._append_variables_recursively(
node_id=node_instance.node_id,
variable_key_list=[variable_key],
variable_value=variable_value
elif run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED:
if run_result.metadata and run_result.metadata.get(NodeRunMetadataKey.TOTAL_TOKENS):
# plus state total_tokens
self.graph_runtime_state.total_tokens += int(
run_result.metadata.get(NodeRunMetadataKey.TOTAL_TOKENS) # type: ignore[arg-type]
)
yield NodeRunSucceededEvent(
if run_result.llm_usage:
# use the latest usage
self.graph_runtime_state.llm_usage += run_result.llm_usage
# append node output variables to variable pool
if run_result.outputs:
for variable_key, variable_value in run_result.outputs.items():
# append variables to variable pool recursively
self._append_variables_recursively(
node_id=node_instance.node_id,
variable_key_list=[variable_key],
variable_value=variable_value
)
yield NodeRunSucceededEvent(
id=node_instance.id,
node_id=node_instance.node_id,
node_type=node_instance.node_type,
node_data=node_instance.node_data,
route_node_state=route_node_state,
parallel_id=parallel_id,
parallel_start_node_id=parallel_start_node_id
)
break
elif isinstance(item, RunStreamChunkEvent):
yield NodeRunStreamChunkEvent(
id=node_instance.id,
node_id=node_instance.node_id,
node_type=node_instance.node_type,
node_data=node_instance.node_data,
chunk_content=item.chunk_content,
from_variable_selector=item.from_variable_selector,
route_node_state=route_node_state,
parallel_id=parallel_id,
parallel_start_node_id=parallel_start_node_id
parallel_start_node_id=parallel_start_node_id,
)
elif isinstance(item, RunRetrieverResourceEvent):
yield NodeRunRetrieverResourceEvent(
id=node_instance.id,
node_id=node_instance.node_id,
node_type=node_instance.node_type,
node_data=node_instance.node_data,
retriever_resources=item.retriever_resources,
context=item.context,
route_node_state=route_node_state,
parallel_id=parallel_id,
parallel_start_node_id=parallel_start_node_id,
)
break
elif isinstance(item, RunStreamChunkEvent):
yield NodeRunStreamChunkEvent(
id=node_instance.id,
node_id=node_instance.node_id,
node_type=node_instance.node_type,
node_data=node_instance.node_data,
chunk_content=item.chunk_content,
from_variable_selector=item.from_variable_selector,
route_node_state=route_node_state,
parallel_id=parallel_id,
parallel_start_node_id=parallel_start_node_id,
)
elif isinstance(item, RunRetrieverResourceEvent):
yield NodeRunRetrieverResourceEvent(
id=node_instance.id,
node_id=node_instance.node_id,
node_type=node_instance.node_type,
node_data=node_instance.node_data,
retriever_resources=item.retriever_resources,
context=item.context,
route_node_state=route_node_state,
parallel_id=parallel_id,
parallel_start_node_id=parallel_start_node_id,
)
elif isinstance(item, BaseIterationEvent):
# add parallel info to iteration event
item.parallel_id = parallel_id
item.parallel_start_node_id = parallel_start_node_id
except GenerateTaskStoppedException:
# trigger node run failed event
route_node_state.status = RouteNodeState.Status.FAILED

5
api/core/workflow/nodes/answer/answer_node.py
View File

@ -1,8 +1,7 @@
from typing import Any, Mapping, Sequence, cast
from collections.abc import Mapping, Sequence
from typing import Any, cast
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeRunResult, NodeType
from core.workflow.graph_engine.entities.graph import Graph
from core.workflow.nodes.answer.answer_stream_generate_router import AnswerStreamGeneratorRouter
from core.workflow.nodes.answer.entities import (
AnswerNodeData,

3
api/core/workflow/nodes/code/code_node.py
View File

@ -1,4 +1,5 @@
from typing import Any, Mapping, Optional, Sequence, Union, cast
from collections.abc import Mapping, Sequence
from typing import Any, Optional, Union, cast
from configs import dify_config
from core.helper.code_executor.code_executor import CodeExecutionException, CodeExecutor, CodeLanguage

4
api/core/workflow/nodes/end/end_node.py
View File

@ -1,6 +1,6 @@
from typing import Any, Mapping, Sequence, cast
from collections.abc import Mapping, Sequence
from typing import Any, cast
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeRunResult, NodeType
from core.workflow.nodes.base_node import BaseNode
from core.workflow.nodes.end.entities import EndNodeData

4
api/core/workflow/nodes/http_request/http_request_node.py
View File

@ -1,12 +1,12 @@
import logging
from collections.abc import Mapping, Sequence
from mimetypes import guess_extension
from os import path
from typing import Any, Mapping, Sequence, cast
from typing import Any, cast
from core.app.segments import parser
from core.file.file_obj import FileTransferMethod, FileType, FileVar
from core.tools.tool_file_manager import ToolFileManager
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeRunResult, NodeType
from core.workflow.nodes.base_node import BaseNode
from core.workflow.nodes.http_request.entities import (

4
api/core/workflow/nodes/if_else/if_else_node.py
View File

@ -1,6 +1,6 @@
from typing import Any, Mapping, Sequence, cast
from collections.abc import Mapping, Sequence
from typing import Any, cast
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeRunResult, NodeType
from core.workflow.nodes.base_node import BaseNode
from core.workflow.nodes.if_else.entities import IfElseNodeData

1
api/core/workflow/nodes/iteration/iteration_node.py
View File

@ -5,7 +5,6 @@ from typing import Any, cast
from configs import dify_config
from core.model_runtime.utils.encoders import jsonable_encoder
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType
from core.workflow.graph_engine.entities.event import (
BaseGraphEvent,

4
api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py
View File

@ -1,5 +1,6 @@
import logging
from typing import Any, Mapping, Sequence, cast
from collections.abc import Mapping, Sequence
from typing import Any, cast
from sqlalchemy import func
@ -13,7 +14,6 @@ from core.model_runtime.entities.model_entities import ModelFeature, ModelType
from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
from core.rag.retrieval.retrival_methods import RetrievalMethod
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeRunResult, NodeType
from core.workflow.nodes.base_node import BaseNode
from core.workflow.nodes.knowledge_retrieval.entities import KnowledgeRetrievalNodeData

5
api/core/workflow/nodes/llm/llm_node.py
View File

@ -1,7 +1,7 @@
import json
from collections.abc import Generator
from collections.abc import Generator, Mapping, Sequence
from copy import deepcopy
from typing import Any, Mapping, Optional, Sequence, cast
from typing import Any, Optional, cast
from pydantic import BaseModel
@ -24,7 +24,6 @@ from core.model_runtime.utils.encoders import jsonable_encoder
from core.prompt.advanced_prompt_transform import AdvancedPromptTransform
from core.prompt.entities.advanced_prompt_entities import CompletionModelPromptTemplate, MemoryConfig
from core.prompt.utils.prompt_message_util import PromptMessageUtil
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType, SystemVariable
from core.workflow.entities.variable_pool import VariablePool
from core.workflow.graph_engine.entities.event import InNodeEvent

3
api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py
View File

@ -1,6 +1,7 @@
import json
import uuid
from typing import Any, Mapping, Optional, Sequence, cast
from collections.abc import Mapping, Sequence
from typing import Any, Optional, cast
from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
from core.memory.token_buffer_memory import TokenBufferMemory

4
api/core/workflow/nodes/question_classifier/question_classifier_node.py
View File

@ -1,6 +1,7 @@
import json
import logging
from typing import Any, Mapping, Optional, Sequence, Union, cast
from collections.abc import Mapping, Sequence
from typing import Any, Optional, Union, cast
from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
from core.memory.token_buffer_memory import TokenBufferMemory
@ -14,7 +15,6 @@ from core.prompt.entities.advanced_prompt_entities import ChatModelMessage, Comp
from core.prompt.simple_prompt_transform import ModelMode
from core.prompt.utils.prompt_message_util import PromptMessageUtil
from core.prompt.utils.prompt_template_parser import PromptTemplateParser
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType
from core.workflow.entities.variable_pool import VariablePool
from core.workflow.nodes.llm.llm_node import LLMNode, ModelInvokeCompleted

5
api/core/workflow/nodes/start/start_node.py
View File

@ -1,6 +1,7 @@
from typing import Any, Mapping, Sequence
from core.workflow.entities.base_node_data_entities import BaseNodeData
from collections.abc import Mapping, Sequence
from typing import Any
from core.workflow.entities.node_entities import NodeRunResult, NodeType
from core.workflow.nodes.base_node import BaseNode
from core.workflow.nodes.start.entities import StartNodeData

3
api/core/workflow/nodes/template_transform/template_transform_node.py
View File

@ -1,5 +1,6 @@
import os
from typing import Any, Mapping, Optional, Sequence, cast
from collections.abc import Mapping, Sequence
from typing import Any, Optional, cast
from core.helper.code_executor.code_executor import CodeExecutionException, CodeExecutor, CodeLanguage
from core.workflow.entities.node_entities import NodeRunResult, NodeType

4
api/core/workflow/nodes/variable_aggregator/variable_aggregator_node.py
View File

@ -1,6 +1,6 @@
from typing import Any, Mapping, Sequence, cast
from collections.abc import Mapping, Sequence
from typing import Any, cast
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeRunResult, NodeType
from core.workflow.nodes.base_node import BaseNode
from core.workflow.nodes.variable_aggregator.entities import VariableAssignerNodeData

209
api/core/workflow/workflow_entry.py
View File

@ -2,7 +2,7 @@ import logging
import time
import uuid
from collections.abc import Generator, Mapping, Sequence
from typing import Any, Optional, Type, cast
from typing import Any, Optional, cast
from configs import dify_config
from core.app.app_config.entities import FileExtraConfig
@ -11,7 +11,7 @@ from core.app.entities.app_invoke_entities import InvokeFrom
from core.file.file_obj import FileTransferMethod, FileType, FileVar
from core.workflow.callbacks.base_workflow_callback import WorkflowCallback
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeRunResult, NodeType, UserFrom
from core.workflow.entities.node_entities import NodeType, UserFrom
from core.workflow.entities.variable_pool import VariablePool
from core.workflow.errors import WorkflowNodeRunFailedError
from core.workflow.graph_engine.entities.event import GraphEngineEvent, GraphRunFailedEvent, InNodeEvent
@ -20,8 +20,7 @@ from core.workflow.graph_engine.entities.graph_init_params import GraphInitParam
from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState
from core.workflow.graph_engine.graph_engine import GraphEngine
from core.workflow.nodes.base_node import BaseNode
from core.workflow.nodes.event import RunCompletedEvent, RunEvent
from core.workflow.nodes.iteration.entities import IterationNodeData
from core.workflow.nodes.event import RunEvent
from core.workflow.nodes.llm.entities import LLMNodeData
from core.workflow.nodes.node_mapping import node_classes
from models.workflow import (
@ -35,7 +34,12 @@ logger = logging.getLogger(__name__)
class WorkflowEntry:
def __init__(
self,
workflow: Workflow,
tenant_id: str,
app_id: str,
workflow_id: str,
workflow_type: WorkflowType,
graph_config: Mapping[str, Any],
graph: Graph,
user_id: str,
user_from: UserFrom,
invoke_from: InvokeFrom,
@ -43,46 +47,29 @@ class WorkflowEntry:
variable_pool: VariablePool
) -> None:
"""
:param workflow: Workflow instance
Init workflow entry
:param tenant_id: tenant id
:param app_id: app id
:param workflow_id: workflow id
:param workflow_type: workflow type
:param graph_config: workflow graph config
:param graph: workflow graph
:param user_id: user id
:param user_from: user from
:param invoke_from: invoke from service-api, web-app, debugger, explore
:param invoke_from: invoke from
:param call_depth: call depth
:param variable_pool: variable pool
:param single_step_run_iteration_id: single step run iteration id
"""
# fetch workflow graph
graph_config = workflow.graph_dict
if not graph_config:
raise ValueError('workflow graph not found')
if 'nodes' not in graph_config or 'edges' not in graph_config:
raise ValueError('nodes or edges not found in workflow graph')
if not isinstance(graph_config.get('nodes'), list):
raise ValueError('nodes in workflow graph must be a list')
if not isinstance(graph_config.get('edges'), list):
raise ValueError('edges in workflow graph must be a list')
workflow_call_max_depth = dify_config.WORKFLOW_CALL_MAX_DEPTH
if call_depth > workflow_call_max_depth:
raise ValueError('Max workflow call depth {} reached.'.format(workflow_call_max_depth))
# init graph
graph = Graph.init(
graph_config=graph_config
)
if not graph:
raise ValueError('graph not found in workflow')
# init workflow run state
self.graph_engine = GraphEngine(
tenant_id=workflow.tenant_id,
app_id=workflow.app_id,
workflow_type=WorkflowType.value_of(workflow.type),
workflow_id=workflow.id,
tenant_id=tenant_id,
app_id=app_id,
workflow_type=workflow_type,
workflow_id=workflow_id,
user_id=user_id,
user_from=user_from,
invoke_from=invoke_from,
@ -133,152 +120,6 @@ class WorkflowEntry:
)
return
@classmethod
def single_step_run_iteration(
cls,
workflow: Workflow,
node_id: str,
user_id: str,
user_inputs: dict,
callbacks: Sequence[WorkflowCallback],
) -> Generator[GraphEngineEvent, None, None]:
"""
Single step run workflow node iteration
:param workflow: Workflow instance
:param node_id: node id
:param user_id: user id
:param user_inputs: user inputs
:return:
"""
# fetch workflow graph
graph_config = workflow.graph_dict
if not graph_config:
raise ValueError('workflow graph not found')
graph_config = cast(dict[str, Any], graph_config)
if 'nodes' not in graph_config or 'edges' not in graph_config:
raise ValueError('nodes or edges not found in workflow graph')
if not isinstance(graph_config.get('nodes'), list):
raise ValueError('nodes in workflow graph must be a list')
if not isinstance(graph_config.get('edges'), list):
raise ValueError('edges in workflow graph must be a list')
# filter nodes only in iteration
node_configs = [
node for node in graph_config.get('nodes', [])
if node.get('id') == node_id or node.get('data', {}).get('iteration_id', '') == node_id
]
graph_config['nodes'] = node_configs
node_ids = [node.get('id') for node in node_configs]
# filter edges only in iteration
edge_configs = [
edge for edge in graph_config.get('edges', [])
if (edge.get('source') is None or edge.get('source') in node_ids)
and (edge.get('target') is None or edge.get('target') in node_ids)
]
graph_config['edges'] = edge_configs
# init graph
graph = Graph.init(
graph_config=graph_config,
root_node_id=node_id
)
if not graph:
raise ValueError('graph not found in workflow')
# fetch node config from node id
iteration_node_config = None
for node in node_configs:
if node.get('id') == node_id:
iteration_node_config = node
break
if not iteration_node_config:
raise ValueError('iteration node id not found in workflow graph')
# Get node class
node_type = NodeType.value_of(iteration_node_config.get('data', {}).get('type'))
node_cls = node_classes.get(node_type)
node_cls = cast(type[BaseNode], node_cls)
# init variable pool
variable_pool = VariablePool(
system_variables={},
user_inputs={},
environment_variables=workflow.environment_variables,
)
try:
variable_mapping = node_cls.extract_variable_selector_to_variable_mapping(
graph_config=workflow.graph_dict,
config=iteration_node_config
)
except NotImplementedError:
variable_mapping = {}
cls._mapping_user_inputs_to_variable_pool(
variable_mapping=variable_mapping,
user_inputs=user_inputs,
variable_pool=variable_pool,
tenant_id=workflow.tenant_id,
node_type=node_type,
node_data=IterationNodeData(**iteration_node_config.get('data', {}))
)
# init workflow run state
graph_engine = GraphEngine(
tenant_id=workflow.tenant_id,
app_id=workflow.app_id,
workflow_type=WorkflowType.value_of(workflow.type),
workflow_id=workflow.id,
user_id=user_id,
user_from=UserFrom.ACCOUNT,
invoke_from=InvokeFrom.DEBUGGER,
call_depth=1,
graph=graph,
graph_config=graph_config,
variable_pool=variable_pool,
max_execution_steps=dify_config.WORKFLOW_MAX_EXECUTION_STEPS,
max_execution_time=dify_config.WORKFLOW_MAX_EXECUTION_TIME
)
try:
# run workflow
generator = graph_engine.run()
for event in generator:
if callbacks:
for callback in callbacks:
callback.on_event(
graph=graph_engine.graph,
graph_init_params=graph_engine.init_params,
graph_runtime_state=graph_engine.graph_runtime_state,
event=event
)
yield event
except GenerateTaskStoppedException:
pass
except Exception as e:
logger.exception("Unknown Error when workflow entry running")
if callbacks:
for callback in callbacks:
callback.on_event(
graph=graph_engine.graph,
graph_init_params=graph_engine.init_params,
graph_runtime_state=graph_engine.graph_runtime_state,
event=GraphRunFailedEvent(
error=str(e)
)
)
return
@classmethod
def single_step_run(
cls,
@ -366,7 +207,7 @@ class WorkflowEntry:
except NotImplementedError:
variable_mapping = {}
cls._mapping_user_inputs_to_variable_pool(
cls.mapping_user_inputs_to_variable_pool(
variable_mapping=variable_mapping,
user_inputs=user_inputs,
variable_pool=variable_pool,
@ -413,7 +254,7 @@ class WorkflowEntry:
return new_value
@classmethod
def _mapping_user_inputs_to_variable_pool(
def mapping_user_inputs_to_variable_pool(
cls,
variable_mapping: Mapping[str, Sequence[str]],
user_inputs: dict,
@ -428,11 +269,11 @@ class WorkflowEntry:
if len(node_variable_list) < 1:
raise ValueError(f'Invalid node variable {node_variable}')
node_variable_key = node_variable_list[1:]
node_variable_key = '.'.join(node_variable_list[1:])
if (
node_variable_key not in user_inputs
or node_variable not in user_inputs
and node_variable not in user_inputs
) and not variable_pool.get(variable_selector):
raise ValueError(f'Variable key {node_variable} not found in user inputs.')