WIP: resume

api/core/workflow/graph_engine/command_source.py

@@ -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]

api/core/workflow/nodes/human_input/__init__.py

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

api/core/workflow/nodes/human_input/entities.py

@@ -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)

api/core/workflow/nodes/human_input/human_input_node.py

@@ -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

api/core/workflow/runtime/graph_runtime_state.py

@@ -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."""