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WIP: resume

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QuantumGhost
2025-11-21 10:13:20 +08:00
parent c0e15b9e1b
commit c0f1aeddbe
49 changed files with 2160 additions and 1445 deletions
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71
api/core/app/apps/advanced_chat/app_generator.py
View File

@ -2,7 +2,7 @@ import contextvars
import logging
import threading
import uuid
from collections.abc import Generator, Mapping
from collections.abc import Generator, Mapping, Sequence
from typing import Any, Literal, TypeVar, Union, overload
from flask import Flask, current_app
@ -24,16 +24,19 @@ 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
from core.app.entities.task_entities import ChatbotAppBlockingResponse, ChatbotAppStreamResponse
from core.app.layers.pause_state_persist_layer import PauseStateLayerConfig, PauseStatePersistenceLayer
from core.helper.trace_id_helper import extract_external_trace_id_from_args
from core.model_runtime.errors.invoke import InvokeAuthorizationError
from core.ops.ops_trace_manager import TraceQueueManager
from core.prompt.utils.get_thread_messages_length import get_thread_messages_length
from core.repositories import DifyCoreRepositoryFactory
from core.workflow.graph_engine.layers.base import GraphEngineLayer
from core.workflow.repositories.draft_variable_repository import (
DraftVariableSaverFactory,
)
from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
from core.workflow.runtime import GraphRuntimeState
from core.workflow.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader
from extensions.ext_database import db
from factories import file_factory
@ -63,6 +66,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
invoke_from: InvokeFrom,
workflow_run_id: uuid.UUID,
streaming: Literal[False],
pause_state_config: PauseStateLayerConfig | None = None,
) -> Mapping[str, Any]: ...
@overload
@ -75,6 +79,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
invoke_from: InvokeFrom,
workflow_run_id: uuid.UUID,
streaming: Literal[True],
pause_state_config: PauseStateLayerConfig | None = None,
) -> Generator[Mapping | str, None, None]: ...
@overload
@ -87,6 +92,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
invoke_from: InvokeFrom,
workflow_run_id: uuid.UUID,
streaming: bool,
pause_state_config: PauseStateLayerConfig | None = None,
) -> Mapping[str, Any] | Generator[str | Mapping, None, None]: ...
def generate(
@ -98,6 +104,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
invoke_from: InvokeFrom,
workflow_run_id: uuid.UUID,
streaming: bool = True,
pause_state_config: PauseStateLayerConfig | None = None,
) -> Mapping[str, Any] | Generator[str | Mapping, None, None]:
"""
Generate App response.
@ -215,6 +222,38 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
workflow_node_execution_repository=workflow_node_execution_repository,
conversation=conversation,
stream=streaming,
pause_state_config=pause_state_config,
)
def resume(
self,
*,
app_model: App,
workflow: Workflow,
user: Union[Account, EndUser],
conversation: Conversation,
message: Message,
application_generate_entity: AdvancedChatAppGenerateEntity,
workflow_execution_repository: WorkflowExecutionRepository,
workflow_node_execution_repository: WorkflowNodeExecutionRepository,
graph_runtime_state: GraphRuntimeState,
pause_state_config: PauseStateLayerConfig | None = None,
):
"""
Resume a paused advanced chat execution.
"""
return self._generate(
workflow=workflow,
user=user,
invoke_from=application_generate_entity.invoke_from,
application_generate_entity=application_generate_entity,
workflow_execution_repository=workflow_execution_repository,
workflow_node_execution_repository=workflow_node_execution_repository,
conversation=conversation,
message=message,
stream=application_generate_entity.stream,
pause_state_config=pause_state_config,
graph_runtime_state=graph_runtime_state,
)
def single_iteration_generate(
@ -395,8 +434,12 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
workflow_execution_repository: WorkflowExecutionRepository,
workflow_node_execution_repository: WorkflowNodeExecutionRepository,
conversation: Conversation | None = None,
message: Message | None = None,
stream: bool = True,
variable_loader: VariableLoader = DUMMY_VARIABLE_LOADER,
pause_state_config: PauseStateLayerConfig | None = None,
graph_runtime_state: GraphRuntimeState | None = None,
graph_engine_layers: Sequence[GraphEngineLayer] = (),
) -> Mapping[str, Any] | Generator[str | Mapping[str, Any], Any, None]:
"""
Generate App response.
@ -410,12 +453,12 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
:param conversation: conversation
:param stream: is stream
"""
is_first_conversation = False
if not conversation:
is_first_conversation = True
is_first_conversation = conversation is None
# init generate records
(conversation, message) = self._init_generate_records(application_generate_entity, conversation)
if conversation is not None and message is not None:
pass
else:
conversation, message = self._init_generate_records(application_generate_entity, conversation)
if is_first_conversation:
# update conversation features
@ -438,6 +481,16 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
message_id=message.id,
)
graph_layers: list[GraphEngineLayer] = list(graph_engine_layers)
if pause_state_config is not None:
graph_layers.append(
PauseStatePersistenceLayer(
session_factory=pause_state_config.session_factory,
generate_entity=application_generate_entity,
state_owner_user_id=pause_state_config.state_owner_user_id,
)
)
# new thread with request context and contextvars
context = contextvars.copy_context()
@ -453,6 +506,8 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
"variable_loader": variable_loader,
"workflow_execution_repository": workflow_execution_repository,
"workflow_node_execution_repository": workflow_node_execution_repository,
"graph_engine_layers": tuple(graph_layers),
"graph_runtime_state": graph_runtime_state,
},
)
@ -498,6 +553,8 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
variable_loader: VariableLoader,
workflow_execution_repository: WorkflowExecutionRepository,
workflow_node_execution_repository: WorkflowNodeExecutionRepository,
graph_engine_layers: Sequence[GraphEngineLayer] = (),
graph_runtime_state: GraphRuntimeState | None = None,
):
"""
Generate worker in a new thread.
@ -555,6 +612,8 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
app=app,
workflow_execution_repository=workflow_execution_repository,
workflow_node_execution_repository=workflow_node_execution_repository,
graph_engine_layers=graph_engine_layers,
graph_runtime_state=graph_runtime_state,
)
try:

16
api/core/app/apps/advanced_chat/app_runner.py
View File

@ -64,6 +64,7 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
workflow_execution_repository: WorkflowExecutionRepository,
workflow_node_execution_repository: WorkflowNodeExecutionRepository,
graph_engine_layers: Sequence[GraphEngineLayer] = (),
graph_runtime_state: GraphRuntimeState | None = None,
):
super().__init__(
queue_manager=queue_manager,
@ -80,6 +81,7 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
self._app = app
self._workflow_execution_repository = workflow_execution_repository
self._workflow_node_execution_repository = workflow_node_execution_repository
self._resume_graph_runtime_state = graph_runtime_state
@trace_span(WorkflowAppRunnerHandler)
def run(self):
@ -103,7 +105,19 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
if not app_record:
raise ValueError("App not found")
if self.application_generate_entity.single_iteration_run or self.application_generate_entity.single_loop_run:
resume_state = self._resume_graph_runtime_state
if resume_state is not None:
graph_runtime_state = resume_state
variable_pool = graph_runtime_state.variable_pool
graph = self._init_graph(
graph_config=self._workflow.graph_dict,
graph_runtime_state=graph_runtime_state,
workflow_id=self._workflow.id,
tenant_id=self._workflow.tenant_id,
user_id=self.application_generate_entity.user_id,
)
elif self.application_generate_entity.single_iteration_run or self.application_generate_entity.single_loop_run:
# Handle single iteration or single loop run
graph, variable_pool, graph_runtime_state = self._prepare_single_node_execution(
workflow=self._workflow,

63
api/core/app/apps/workflow/app_generator.py
View File

@ -23,6 +23,7 @@ from core.app.apps.workflow.generate_response_converter import WorkflowAppGenera
from core.app.apps.workflow.generate_task_pipeline import WorkflowAppGenerateTaskPipeline
from core.app.entities.app_invoke_entities import InvokeFrom, WorkflowAppGenerateEntity
from core.app.entities.task_entities import WorkflowAppBlockingResponse, WorkflowAppStreamResponse
from core.app.layers.pause_state_persist_layer import PauseStateLayerConfig, PauseStatePersistenceLayer
from core.helper.trace_id_helper import extract_external_trace_id_from_args
from core.model_runtime.errors.invoke import InvokeAuthorizationError
from core.ops.ops_trace_manager import TraceQueueManager
@ -31,12 +32,15 @@ from core.workflow.graph_engine.layers.base import GraphEngineLayer
from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory
from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
from core.workflow.runtime import GraphRuntimeState
from core.workflow.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader
from extensions.ext_database import db
from factories import file_factory
from libs.flask_utils import preserve_flask_contexts
from models import Account, App, EndUser, Workflow, WorkflowNodeExecutionTriggeredFrom
from models.account import Account
from models.enums import WorkflowRunTriggeredFrom
from models.model import App, EndUser
from models.workflow import Workflow, WorkflowNodeExecutionTriggeredFrom
from services.workflow_draft_variable_service import DraftVarLoader, WorkflowDraftVariableService
SKIP_PREPARE_USER_INPUTS_KEY = "_skip_prepare_user_inputs"
@ -63,6 +67,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
triggered_from: WorkflowRunTriggeredFrom | None = None,
root_node_id: str | None = None,
graph_engine_layers: Sequence[GraphEngineLayer] = (),
pause_state_config: PauseStateLayerConfig | None = None,
) -> Generator[Mapping[str, Any] | str, None, None]: ...
@overload
@ -79,6 +84,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
triggered_from: WorkflowRunTriggeredFrom | None = None,
root_node_id: str | None = None,
graph_engine_layers: Sequence[GraphEngineLayer] = (),
pause_state_config: PauseStateLayerConfig | None = None,
) -> Mapping[str, Any]: ...
@overload
@ -95,6 +101,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
triggered_from: WorkflowRunTriggeredFrom | None = None,
root_node_id: str | None = None,
graph_engine_layers: Sequence[GraphEngineLayer] = (),
pause_state_config: PauseStateLayerConfig | None = None,
) -> Union[Mapping[str, Any], Generator[Mapping[str, Any] | str, None, None]]: ...
def generate(
@ -110,6 +117,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
triggered_from: WorkflowRunTriggeredFrom | None = None,
root_node_id: str | None = None,
graph_engine_layers: Sequence[GraphEngineLayer] = (),
pause_state_config: PauseStateLayerConfig | None = None,
) -> Union[Mapping[str, Any], Generator[Mapping[str, Any] | str, None, None]]:
files: Sequence[Mapping[str, Any]] = args.get("files") or []
@ -210,13 +218,40 @@ class WorkflowAppGenerator(BaseAppGenerator):
streaming=streaming,
root_node_id=root_node_id,
graph_engine_layers=graph_engine_layers,
pause_state_config=pause_state_config,
)
def resume(self, *, workflow_run_id: str) -> None:
def resume(
self,
*,
app_model: App,
workflow: Workflow,
user: Union[Account, EndUser],
application_generate_entity: WorkflowAppGenerateEntity,
graph_runtime_state: GraphRuntimeState,
workflow_execution_repository: WorkflowExecutionRepository,
workflow_node_execution_repository: WorkflowNodeExecutionRepository,
graph_engine_layers: Sequence[GraphEngineLayer] = (),
pause_state_config: PauseStateLayerConfig | None = None,
variable_loader: VariableLoader = DUMMY_VARIABLE_LOADER,
) -> Union[Mapping[str, Any], Generator[str | Mapping[str, Any], None, None]]:
"""
@TBD
Resume a paused workflow execution using the persisted runtime state.
"""
pass
return self._generate(
app_model=app_model,
workflow=workflow,
user=user,
application_generate_entity=application_generate_entity,
invoke_from=application_generate_entity.invoke_from,
workflow_execution_repository=workflow_execution_repository,
workflow_node_execution_repository=workflow_node_execution_repository,
streaming=application_generate_entity.stream,
variable_loader=variable_loader,
graph_engine_layers=graph_engine_layers,
graph_runtime_state=graph_runtime_state,
pause_state_config=pause_state_config,
)
def _generate(
self,
@ -232,6 +267,8 @@ class WorkflowAppGenerator(BaseAppGenerator):
variable_loader: VariableLoader = DUMMY_VARIABLE_LOADER,
root_node_id: str | None = None,
graph_engine_layers: Sequence[GraphEngineLayer] = (),
graph_runtime_state: GraphRuntimeState | None = None,
pause_state_config: PauseStateLayerConfig | None = None,
) -> Union[Mapping[str, Any], Generator[str | Mapping[str, Any], None, None]]:
"""
Generate App response.
@ -245,6 +282,8 @@ class WorkflowAppGenerator(BaseAppGenerator):
:param workflow_node_execution_repository: repository for workflow node execution
:param streaming: is stream
"""
graph_layers: list[GraphEngineLayer] = list(graph_engine_layers)
# init queue manager
queue_manager = WorkflowAppQueueManager(
task_id=application_generate_entity.task_id,
@ -253,6 +292,15 @@ class WorkflowAppGenerator(BaseAppGenerator):
app_mode=app_model.mode,
)
if pause_state_config is not None:
graph_layers.append(
PauseStatePersistenceLayer(
session_factory=pause_state_config.session_factory,
generate_entity=application_generate_entity,
state_owner_user_id=pause_state_config.state_owner_user_id,
)
)
# new thread with request context and contextvars
context = contextvars.copy_context()
@ -270,7 +318,8 @@ class WorkflowAppGenerator(BaseAppGenerator):
"root_node_id": root_node_id,
"workflow_execution_repository": workflow_execution_repository,
"workflow_node_execution_repository": workflow_node_execution_repository,
"graph_engine_layers": graph_engine_layers,
"graph_engine_layers": tuple(graph_layers),
"graph_runtime_state": graph_runtime_state,
},
)
@ -372,6 +421,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
workflow_node_execution_repository=workflow_node_execution_repository,
streaming=streaming,
variable_loader=var_loader,
pause_state_config=None,
)
def single_loop_generate(
@ -453,6 +503,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
workflow_node_execution_repository=workflow_node_execution_repository,
streaming=streaming,
variable_loader=var_loader,
pause_state_config=None,
)
def _generate_worker(
@ -466,6 +517,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
workflow_node_execution_repository: WorkflowNodeExecutionRepository,
root_node_id: str | None = None,
graph_engine_layers: Sequence[GraphEngineLayer] = (),
graph_runtime_state: GraphRuntimeState | None = None,
) -> None:
"""
Generate worker in a new thread.
@ -511,6 +563,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
workflow_node_execution_repository=workflow_node_execution_repository,
root_node_id=root_node_id,
graph_engine_layers=graph_engine_layers,
graph_runtime_state=graph_runtime_state,
)
try:

31
api/core/app/apps/workflow/app_runner.py
View File

@ -43,6 +43,7 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
workflow_execution_repository: WorkflowExecutionRepository,
workflow_node_execution_repository: WorkflowNodeExecutionRepository,
graph_engine_layers: Sequence[GraphEngineLayer] = (),
graph_runtime_state: GraphRuntimeState | None = None,
):
super().__init__(
queue_manager=queue_manager,
@ -56,6 +57,7 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
self._root_node_id = root_node_id
self._workflow_execution_repository = workflow_execution_repository
self._workflow_node_execution_repository = workflow_node_execution_repository
self._resume_graph_runtime_state = graph_runtime_state
@trace_span(WorkflowAppRunnerHandler)
def run(self):
@ -65,17 +67,12 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
app_config = self.application_generate_entity.app_config
app_config = cast(WorkflowAppConfig, app_config)
system_inputs = SystemVariable(
files=self.application_generate_entity.files,
user_id=self._sys_user_id,
app_id=app_config.app_id,
timestamp=int(naive_utc_now().timestamp()),
workflow_id=app_config.workflow_id,
workflow_execution_id=self.application_generate_entity.workflow_execution_id,
)
resume_state = self._resume_graph_runtime_state
# if only single iteration or single loop run is requested
if self.application_generate_entity.single_iteration_run or self.application_generate_entity.single_loop_run:
if resume_state is not None:
graph_runtime_state = resume_state
variable_pool = graph_runtime_state.variable_pool
elif self.application_generate_entity.single_iteration_run or self.application_generate_entity.single_loop_run:
graph, variable_pool, graph_runtime_state = self._prepare_single_node_execution(
workflow=self._workflow,
single_iteration_run=self.application_generate_entity.single_iteration_run,
@ -85,7 +82,14 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
inputs = self.application_generate_entity.inputs
# Create a variable pool.
system_inputs = SystemVariable(
files=self.application_generate_entity.files,
user_id=self._sys_user_id,
app_id=app_config.app_id,
timestamp=int(naive_utc_now().timestamp()),
workflow_id=app_config.workflow_id,
workflow_execution_id=self.application_generate_entity.workflow_execution_id,
)
variable_pool = VariablePool(
system_variables=system_inputs,
user_inputs=inputs,
@ -95,7 +99,10 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter())
# init graph
# init graph (for both resumed and fresh runs when not single-step)
if resume_state is not None or not (
self.application_generate_entity.single_iteration_run or self.application_generate_entity.single_loop_run
):
graph = self._init_graph(
graph_config=self._workflow.graph_dict,
graph_runtime_state=graph_runtime_state,

9
api/core/app/layers/pause_state_persist_layer.py
View File

@ -1,3 +1,4 @@
from dataclasses import dataclass
from typing import Annotated, Literal, Self, TypeAlias
from pydantic import BaseModel, Field
@ -52,6 +53,14 @@ class WorkflowResumptionContext(BaseModel):
return self.generate_entity.entity
@dataclass(frozen=True)
class PauseStateLayerConfig:
"""Configuration container for instantiating pause persistence layers."""
session_factory: Engine | sessionmaker[Session]
state_owner_user_id: str
class PauseStatePersistenceLayer(GraphEngineLayer):
def __init__(
self,

2
api/core/entities/provider_configuration.py
View File

@ -28,8 +28,8 @@ from core.model_runtime.entities.provider_entities import (
)
from core.model_runtime.model_providers.__base.ai_model import AIModel
from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory
from extensions.ext_database import db
from libs.datetime_utils import naive_utc_now
from models.engine import db
from models.provider import (
LoadBalancingModelConfig,
Provider,

10
api/core/ops/ops_trace_manager.py
View File

@ -15,10 +15,7 @@ from sqlalchemy import select
from sqlalchemy.orm import Session, sessionmaker
from core.helper.encrypter import batch_decrypt_token, encrypt_token, obfuscated_token
from core.ops.entities.config_entity import (
OPS_FILE_PATH,
TracingProviderEnum,
)
from core.ops.entities.config_entity import OPS_FILE_PATH, TracingProviderEnum
from core.ops.entities.trace_entity import (
DatasetRetrievalTraceInfo,
GenerateNameTraceInfo,
@ -31,11 +28,10 @@ from core.ops.entities.trace_entity import (
WorkflowTraceInfo,
)
from core.ops.utils import get_message_data
from extensions.ext_database import db
from extensions.ext_storage import storage
from models.engine import db
from models.model import App, AppModelConfig, Conversation, Message, MessageFile, TraceAppConfig
from models.workflow import WorkflowAppLog
from repositories.factory import DifyAPIRepositoryFactory
from tasks.ops_trace_task import process_trace_tasks
if TYPE_CHECKING:
@ -470,6 +466,8 @@ class TraceTask:
@classmethod
def _get_workflow_run_repo(cls):
from repositories.factory import DifyAPIRepositoryFactory
if cls._workflow_run_repo is None:
with cls._repo_lock:
if cls._workflow_run_repo is None:

2
api/core/ops/utils.py
View File

@ -5,7 +5,7 @@ from urllib.parse import urlparse
from sqlalchemy import select
from extensions.ext_database import db
from models.engine import db
from models.model import Message

36
api/core/repositories/__init__.py
View File

@ -2,27 +2,17 @@
from __future__ import annotations
from importlib import import_module
from typing import Any
from .celery_workflow_execution_repository import CeleryWorkflowExecutionRepository
from .celery_workflow_node_execution_repository import CeleryWorkflowNodeExecutionRepository
from .factory import DifyCoreRepositoryFactory, RepositoryImportError
from .sqlalchemy_workflow_execution_repository import SQLAlchemyWorkflowExecutionRepository
from .sqlalchemy_workflow_node_execution_repository import SQLAlchemyWorkflowNodeExecutionRepository
_ATTRIBUTE_MODULE_MAP = {
"CeleryWorkflowExecutionRepository": "core.repositories.celery_workflow_execution_repository",
"CeleryWorkflowNodeExecutionRepository": "core.repositories.celery_workflow_node_execution_repository",
"DifyCoreRepositoryFactory": "core.repositories.factory",
"RepositoryImportError": "core.repositories.factory",
"SQLAlchemyWorkflowNodeExecutionRepository": "core.repositories.sqlalchemy_workflow_node_execution_repository",
}
__all__ = list(_ATTRIBUTE_MODULE_MAP.keys())
def __getattr__(name: str) -> Any:
module_path = _ATTRIBUTE_MODULE_MAP.get(name)
if module_path is None:
raise AttributeError(f"module 'core.repositories' has no attribute '{name}'")
module = import_module(module_path)
return getattr(module, name)
def __dir__() -> list[str]: # pragma: no cover - simple helper
return sorted(__all__)
__all__ = [
"CeleryWorkflowExecutionRepository",
"CeleryWorkflowNodeExecutionRepository",
"DifyCoreRepositoryFactory",
"RepositoryImportError",
"SQLAlchemyWorkflowExecutionRepository",
"SQLAlchemyWorkflowNodeExecutionRepository",
]

121
api/core/repositories/human_input_reposotiry.py
View File

@ -1,10 +1,11 @@
import dataclasses
import json
from collections.abc import Mapping, Sequence
from datetime import datetime
from typing import Any
from sqlalchemy import Engine, select
from sqlalchemy.orm import Session, sessionmaker, selectinload
from sqlalchemy.orm import Session, selectinload, sessionmaker
from core.workflow.nodes.human_input.entities import (
DeliveryChannelConfig,
@ -85,6 +86,53 @@ class _FormSubmissionImpl(FormSubmission):
return json.loads(submitted_data)
@dataclasses.dataclass(frozen=True)
class HumanInputFormRecord:
form_id: str
workflow_run_id: str
node_id: str
tenant_id: str
definition: FormDefinition
rendered_content: str
expiration_time: datetime
selected_action_id: str | None
submitted_data: Mapping[str, Any] | None
submitted_at: datetime | None
submission_user_id: str | None
submission_end_user_id: str | None
completed_by_recipient_id: str | None
recipient_id: str | None
recipient_type: RecipientType | None
access_token: str | None
@property
def submitted(self) -> bool:
return self.submitted_at is not None
@classmethod
def from_models(
cls, form_model: HumanInputForm, recipient_model: HumanInputFormRecipient | None
) -> "HumanInputFormRecord":
return cls(
form_id=form_model.id,
workflow_run_id=form_model.workflow_run_id,
node_id=form_model.node_id,
tenant_id=form_model.tenant_id,
definition=FormDefinition.model_validate_json(form_model.form_definition),
rendered_content=form_model.rendered_content,
expiration_time=form_model.expiration_time,
selected_action_id=form_model.selected_action_id,
submitted_data=json.loads(form_model.submitted_data) if form_model.submitted_data else None,
submitted_at=form_model.submitted_at,
submission_user_id=form_model.submission_user_id,
submission_end_user_id=form_model.submission_end_user_id,
completed_by_recipient_id=form_model.completed_by_recipient_id,
recipient_id=recipient_model.id if recipient_model else None,
recipient_type=recipient_model.recipient_type if recipient_model else None,
access_token=recipient_model.access_token if recipient_model else None,
)
class HumanInputFormRepositoryImpl:
def __init__(
self,
@ -275,11 +323,74 @@ class HumanInputFormRepositoryImpl:
return _FormSubmissionImpl(form_model=form_model)
def get_form_by_token(self, token: str, recipient_type: RecipientType | None = None):
class HumanInputFormReadRepository:
"""Read/write repository for fetching and submitting human input forms."""
def __init__(self, session_factory: sessionmaker | Engine):
if isinstance(session_factory, Engine):
session_factory = sessionmaker(bind=session_factory)
self._session_factory = session_factory
def get_by_token(self, form_token: str) -> HumanInputFormRecord | None:
query = (
select(HumanInputFormRecipient)
.options(selectinload(HumanInputFormRecipient.form))
.where()
.where(HumanInputFormRecipient.access_token == form_token)
)
with self._session_factory(expire_on_commit=False) as session:
form_recipient = session.qu
recipient_model = session.scalars(query).first()
if recipient_model is None or recipient_model.form is None:
return None
return HumanInputFormRecord.from_models(recipient_model.form, recipient_model)
def get_by_form_id_and_recipient_type(
self,
form_id: str,
recipient_type: RecipientType,
) -> HumanInputFormRecord | None:
query = (
select(HumanInputFormRecipient)
.options(selectinload(HumanInputFormRecipient.form))
.where(
HumanInputFormRecipient.form_id == form_id,
HumanInputFormRecipient.recipient_type == recipient_type,
)
)
with self._session_factory(expire_on_commit=False) as session:
recipient_model = session.scalars(query).first()
if recipient_model is None or recipient_model.form is None:
return None
return HumanInputFormRecord.from_models(recipient_model.form, recipient_model)
def mark_submitted(
self,
*,
form_id: str,
recipient_id: str | None,
selected_action_id: str,
form_data: Mapping[str, Any],
submission_user_id: str | None,
submission_end_user_id: str | None,
) -> HumanInputFormRecord:
with self._session_factory(expire_on_commit=False) as session, session.begin():
form_model = session.get(HumanInputForm, form_id)
if form_model is None:
raise FormNotFoundError(f"form not found, id={form_id}")
recipient_model = session.get(HumanInputFormRecipient, recipient_id) if recipient_id else None
form_model.selected_action_id = selected_action_id
form_model.submitted_data = json.dumps(form_data)
form_model.submitted_at = naive_utc_now()
form_model.submission_user_id = submission_user_id
form_model.submission_end_user_id = submission_end_user_id
form_model.completed_by_recipient_id = recipient_id
session.add(form_model)
session.flush()
session.refresh(form_model)
if recipient_model is not None:
session.refresh(recipient_model)
return HumanInputFormRecord.from_models(form_model, recipient_model)

71
api/core/workflow/graph_engine/command_source.py
View File

@ -1,71 +0,0 @@
import abc
from collections.abc import Callable
from dataclasses import dataclass
from enum import StrEnum
from typing import Annotated, TypeAlias, final
from pydantic import BaseModel, ConfigDict, Discriminator, Tag, field_validator
from core.workflow.nodes.base import BaseNode
@dataclass(frozen=True)
class CommandParams:
# `next_node_instance` is the instance of the next node to run.
next_node: BaseNode
class _CommandTag(StrEnum):
SUSPEND = "suspend"
STOP = "stop"
CONTINUE = "continue"
# Note: Avoid using the `_Command` class directly.
# Instead, use `CommandTypes` for type annotations.
class _Command(BaseModel, abc.ABC):
model_config = ConfigDict(frozen=True)
tag: _CommandTag
@field_validator("tag")
@classmethod
def validate_value_type(cls, value):
if value != cls.model_fields["tag"].default:
raise ValueError("Cannot modify 'tag'")
return value
@final
class StopCommand(_Command):
tag: _CommandTag = _CommandTag.STOP
@final
class SuspendCommand(_Command):
tag: _CommandTag = _CommandTag.SUSPEND
@final
class ContinueCommand(_Command):
tag: _CommandTag = _CommandTag.CONTINUE
def _get_command_tag(command: _Command):
return command.tag
CommandTypes: TypeAlias = Annotated[
(
Annotated[StopCommand, Tag(_CommandTag.STOP)]
| Annotated[SuspendCommand, Tag(_CommandTag.SUSPEND)]
| Annotated[ContinueCommand, Tag(_CommandTag.CONTINUE)]
),
Discriminator(_get_command_tag),
]
# `CommandSource` is a callable that takes a single argument of type `CommandParams` and
# returns a `Command` object to the engine, indicating whether the graph engine should suspend, continue, or stop.
#
# It must not modify the data inside `CommandParams`, including any attributes within its fields.
CommandSource: TypeAlias = Callable[[CommandParams], CommandTypes]

5
api/core/workflow/nodes/human_input/__init__.py
View File

@ -1,8 +1,3 @@
"""
Human Input node implementation.
"""
from .entities import HumanInputNodeData
from .human_input_node import HumanInputNode
__all__ = ["HumanInputNode", "HumanInputNodeData"]

10
api/core/workflow/nodes/human_input/entities.py
View File

@ -269,16 +269,6 @@ class HumanInputNodeData(BaseNodeData):
return variable_mappings
class HumanInputRequired(BaseModel):
"""Event data for human input required."""
form_id: str
node_id: str
form_content: str
inputs: list[FormInput]
web_app_form_token: Optional[str] = None
class FormDefinition(BaseModel):
form_content: str
inputs: list[FormInput] = Field(default_factory=list)

6
api/core/workflow/nodes/human_input/human_input_node.py
View File

@ -1,4 +1,3 @@
import dataclasses
import logging
from collections.abc import Generator, Mapping, Sequence
from typing import Any
@ -18,11 +17,6 @@ _SELECTED_BRANCH_KEY = "selected_branch"
logger = logging.getLogger(__name__)
@dataclasses.dataclass
class _FormSubmissionResult:
action_id: str
class HumanInputNode(Node[HumanInputNodeData]):
node_type = NodeType.HUMAN_INPUT
execution_type = NodeExecutionType.BRANCH

7
api/core/workflow/runtime/graph_runtime_state.py
View File

@ -5,7 +5,7 @@ import json
from collections.abc import Mapping, Sequence
from copy import deepcopy
from dataclasses import dataclass
from typing import Any, Protocol
from typing import TYPE_CHECKING, Any, Protocol
from pydantic.json import pydantic_encoder
@ -13,6 +13,9 @@ from core.model_runtime.entities.llm_entities import LLMUsage
from core.workflow.entities.pause_reason import PauseReason
from core.workflow.runtime.variable_pool import VariablePool
if TYPE_CHECKING:
from core.workflow.entities.pause_reason import PauseReason
class ReadyQueueProtocol(Protocol):
"""Structural interface required from ready queue implementations."""
@ -59,7 +62,7 @@ class GraphExecutionProtocol(Protocol):
aborted: bool
error: Exception | None
exceptions_count: int
pause_reasons: list[PauseReason]
pause_reasons: Sequence[PauseReason]
def start(self) -> None:
"""Transition execution into the running state."""