chore: use from __future__ import annotations (#30254)

Co-authored-by: Dev <dev@Devs-MacBook-Pro-4.local>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: Asuka Minato <i@asukaminato.eu.org>
Co-authored-by: crazywoola <100913391+crazywoola@users.noreply.github.com>

api/core/workflow/entities/workflow_execution.py

@@ -5,6 +5,8 @@ Models are independent of the storage mechanism and don't contain
 implementation details like tenant_id, app_id, etc.
 """
 
+from __future__ import annotations
+
 from collections.abc import Mapping
 from datetime import datetime
 from typing import Any
@@ -59,7 +61,7 @@ class WorkflowExecution(BaseModel):
         graph: Mapping[str, Any],
         inputs: Mapping[str, Any],
         started_at: datetime,
-    ) -> "WorkflowExecution":
+    ) -> WorkflowExecution:
         return WorkflowExecution(
             id_=id_,
             workflow_id=workflow_id,

api/core/workflow/graph/graph.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import logging
 from collections import defaultdict
 from collections.abc import Mapping, Sequence
@@ -175,7 +177,7 @@ class Graph:
     def _create_node_instances(
         cls,
         node_configs_map: dict[str, dict[str, object]],
-        node_factory: "NodeFactory",
+        node_factory: NodeFactory,
     ) -> dict[str, Node]:
         """
         Create node instances from configurations using the node factory.
@@ -197,7 +199,7 @@ class Graph:
         return nodes
 
     @classmethod
-    def new(cls) -> "GraphBuilder":
+    def new(cls) -> GraphBuilder:
         """Create a fluent builder for assembling a graph programmatically."""
 
         return GraphBuilder(graph_cls=cls)
@@ -284,9 +286,9 @@ class Graph:
         cls,
         *,
         graph_config: Mapping[str, object],
-        node_factory: "NodeFactory",
+        node_factory: NodeFactory,
         root_node_id: str | None = None,
-    ) -> "Graph":
+    ) -> Graph:
         """
         Initialize graph
 
@@ -383,7 +385,7 @@ class GraphBuilder:
         self._edges: list[Edge] = []
         self._edge_counter = 0
 
-    def add_root(self, node: Node) -> "GraphBuilder":
+    def add_root(self, node: Node) -> GraphBuilder:
         """Register the root node. Must be called exactly once."""
 
         if self._nodes:
@@ -398,7 +400,7 @@ class GraphBuilder:
         *,
         from_node_id: str | None = None,
         source_handle: str = "source",
-    ) -> "GraphBuilder":
+    ) -> GraphBuilder:
         """Append a node and connect it from the specified predecessor."""
 
         if not self._nodes:
@@ -419,7 +421,7 @@ class GraphBuilder:
 
         return self
 
-    def connect(self, *, tail: str, head: str, source_handle: str = "source") -> "GraphBuilder":
+    def connect(self, *, tail: str, head: str, source_handle: str = "source") -> GraphBuilder:
         """Connect two existing nodes without adding a new node."""
 
         if tail not in self._nodes_by_id:

api/core/workflow/graph_engine/graph_engine.py

@@ -5,6 +5,8 @@ This engine uses a modular architecture with separated packages following
 Domain-Driven Design principles for improved maintainability and testability.
 """
 
+from __future__ import annotations
+
 import contextvars
 import logging
 import queue
@@ -232,7 +234,7 @@ class GraphEngine:
     ) -> None:
         layer.initialize(ReadOnlyGraphRuntimeStateWrapper(self._graph_runtime_state), self._command_channel)
 
-    def layer(self, layer: GraphEngineLayer) -> "GraphEngine":
+    def layer(self, layer: GraphEngineLayer) -> GraphEngine:
         """Add a layer for extending functionality."""
         self._layers.append(layer)
         self._bind_layer_context(layer)

api/core/workflow/graph_engine/ready_queue/factory.py

@@ -2,6 +2,8 @@
 Factory for creating ReadyQueue instances from serialized state.
 """
 
+from __future__ import annotations
+
 from typing import TYPE_CHECKING
 
 from .in_memory import InMemoryReadyQueue
@@ -11,7 +13,7 @@ if TYPE_CHECKING:
     from .protocol import ReadyQueue
 
 
-def create_ready_queue_from_state(state: ReadyQueueState) -> "ReadyQueue":
+def create_ready_queue_from_state(state: ReadyQueueState) -> ReadyQueue:
     """
     Create a ReadyQueue instance from a serialized state.
 

api/core/workflow/graph_engine/response_coordinator/session.py

@@ -5,6 +5,8 @@ This module contains the private ResponseSession class used internally
 by ResponseStreamCoordinator to manage streaming sessions.
 """
 
+from __future__ import annotations
+
 from dataclasses import dataclass
 
 from core.workflow.nodes.answer.answer_node import AnswerNode
@@ -27,7 +29,7 @@ class ResponseSession:
     index: int = 0  # Current position in the template segments
 
     @classmethod
-    def from_node(cls, node: Node) -> "ResponseSession":
+    def from_node(cls, node: Node) -> ResponseSession:
         """
         Create a ResponseSession from an AnswerNode or EndNode.
 

api/core/workflow/nodes/agent/agent_node.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import json
 from collections.abc import Generator, Mapping, Sequence
 from typing import TYPE_CHECKING, Any, cast
@@ -167,7 +169,7 @@ class AgentNode(Node[AgentNodeData]):
         variable_pool: VariablePool,
         node_data: AgentNodeData,
         for_log: bool = False,
-        strategy: "PluginAgentStrategy",
+        strategy: PluginAgentStrategy,
     ) -> dict[str, Any]:
         """
         Generate parameters based on the given tool parameters, variable pool, and node data.
@@ -328,7 +330,7 @@ class AgentNode(Node[AgentNodeData]):
     def _generate_credentials(
         self,
         parameters: dict[str, Any],
-    ) -> "InvokeCredentials":
+    ) -> InvokeCredentials:
         """
         Generate credentials based on the given agent parameters.
         """
@@ -442,9 +444,7 @@ class AgentNode(Node[AgentNodeData]):
                     model_schema.features.remove(feature)
         return model_schema
 
-    def _filter_mcp_type_tool(
-        self, strategy: "PluginAgentStrategy", tools: list[dict[str, Any]]
-    ) -> list[dict[str, Any]]:
+    def _filter_mcp_type_tool(self, strategy: PluginAgentStrategy, tools: list[dict[str, Any]]) -> list[dict[str, Any]]:
         """
         Filter MCP type tool
         :param strategy: plugin agent strategy

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

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import json
 from abc import ABC
 from builtins import type as type_
@@ -111,7 +113,7 @@ class DefaultValue(BaseModel):
             raise DefaultValueTypeError(f"Cannot convert to number: {value}")
 
     @model_validator(mode="after")
-    def validate_value_type(self) -> "DefaultValue":
+    def validate_value_type(self) -> DefaultValue:
         # Type validation configuration
         type_validators = {
             DefaultValueType.STRING: {

api/core/workflow/nodes/base/node.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import importlib
 import logging
 import operator
@@ -59,7 +61,7 @@ logger = logging.getLogger(__name__)
 
 
 class Node(Generic[NodeDataT]):
-    node_type: ClassVar["NodeType"]
+    node_type: ClassVar[NodeType]
     execution_type: NodeExecutionType = NodeExecutionType.EXECUTABLE
     _node_data_type: ClassVar[type[BaseNodeData]] = BaseNodeData
 
@@ -198,14 +200,14 @@ class Node(Generic[NodeDataT]):
         return None
 
     # Global registry populated via __init_subclass__
-    _registry: ClassVar[dict["NodeType", dict[str, type["Node"]]]] = {}
+    _registry: ClassVar[dict[NodeType, dict[str, type[Node]]]] = {}
 
     def __init__(
         self,
         id: str,
         config: Mapping[str, Any],
-        graph_init_params: "GraphInitParams",
-        graph_runtime_state: "GraphRuntimeState",
+        graph_init_params: GraphInitParams,
+        graph_runtime_state: GraphRuntimeState,
     ) -> None:
         self._graph_init_params = graph_init_params
         self.id = id
@@ -241,7 +243,7 @@ class Node(Generic[NodeDataT]):
         return
 
     @property
-    def graph_init_params(self) -> "GraphInitParams":
+    def graph_init_params(self) -> GraphInitParams:
         return self._graph_init_params
 
     @property
@@ -457,7 +459,7 @@ class Node(Generic[NodeDataT]):
         raise NotImplementedError("subclasses of BaseNode must implement `version` method.")
 
     @classmethod
-    def get_node_type_classes_mapping(cls) -> Mapping["NodeType", Mapping[str, type["Node"]]]:
+    def get_node_type_classes_mapping(cls) -> Mapping[NodeType, Mapping[str, type[Node]]]:
         """Return mapping of NodeType -> {version -> Node subclass} using __init_subclass__ registry.
 
         Import all modules under core.workflow.nodes so subclasses register themselves on import.

api/core/workflow/nodes/base/template.py

@@ -4,6 +4,8 @@ This module provides a unified template structure for both Answer and End nodes,
 similar to SegmentGroup but focused on template representation without values.
 """
 
+from __future__ import annotations
+
 from abc import ABC, abstractmethod
 from collections.abc import Sequence
 from dataclasses import dataclass
@@ -58,7 +60,7 @@ class Template:
     segments: list[TemplateSegmentUnion]
 
     @classmethod
-    def from_answer_template(cls, template_str: str) -> "Template":
+    def from_answer_template(cls, template_str: str) -> Template:
         """Create a Template from an Answer node template string.
 
         Example:
@@ -107,7 +109,7 @@ class Template:
         return cls(segments=segments)
 
     @classmethod
-    def from_end_outputs(cls, outputs_config: list[dict[str, Any]]) -> "Template":
+    def from_end_outputs(cls, outputs_config: list[dict[str, Any]]) -> Template:
         """Create a Template from an End node outputs configuration.
 
         End nodes are treated as templates of concatenated variables with newlines.

api/core/workflow/nodes/llm/node.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import base64
 import io
 import json
@@ -113,7 +115,7 @@ class LLMNode(Node[LLMNodeData]):
 
     # Instance attributes specific to LLMNode.
     # Output variable for file
-    _file_outputs: list["File"]
+    _file_outputs: list[File]
 
     _llm_file_saver: LLMFileSaver
 
@@ -121,8 +123,8 @@ class LLMNode(Node[LLMNodeData]):
         self,
         id: str,
         config: Mapping[str, Any],
-        graph_init_params: "GraphInitParams",
-        graph_runtime_state: "GraphRuntimeState",
+        graph_init_params: GraphInitParams,
+        graph_runtime_state: GraphRuntimeState,
         *,
         llm_file_saver: LLMFileSaver | None = None,
     ):
@@ -361,7 +363,7 @@ class LLMNode(Node[LLMNodeData]):
         structured_output_enabled: bool,
         structured_output: Mapping[str, Any] | None = None,
         file_saver: LLMFileSaver,
-        file_outputs: list["File"],
+        file_outputs: list[File],
         node_id: str,
         node_type: NodeType,
         reasoning_format: Literal["separated", "tagged"] = "tagged",
@@ -415,7 +417,7 @@ class LLMNode(Node[LLMNodeData]):
         *,
         invoke_result: LLMResult | Generator[LLMResultChunk | LLMStructuredOutput, None, None],
         file_saver: LLMFileSaver,
-        file_outputs: list["File"],
+        file_outputs: list[File],
         node_id: str,
         node_type: NodeType,
         reasoning_format: Literal["separated", "tagged"] = "tagged",
@@ -525,7 +527,7 @@ class LLMNode(Node[LLMNodeData]):
         )
 
     @staticmethod
-    def _image_file_to_markdown(file: "File", /):
+    def _image_file_to_markdown(file: File, /):
         text_chunk = f"![]({file.generate_url()})"
         return text_chunk
 
@@ -774,7 +776,7 @@ class LLMNode(Node[LLMNodeData]):
     def fetch_prompt_messages(
         *,
         sys_query: str | None = None,
-        sys_files: Sequence["File"],
+        sys_files: Sequence[File],
         context: str | None = None,
         memory: TokenBufferMemory | None = None,
         model_config: ModelConfigWithCredentialsEntity,
@@ -785,7 +787,7 @@ class LLMNode(Node[LLMNodeData]):
         variable_pool: VariablePool,
         jinja2_variables: Sequence[VariableSelector],
         tenant_id: str,
-        context_files: list["File"] | None = None,
+        context_files: list[File] | None = None,
     ) -> tuple[Sequence[PromptMessage], Sequence[str] | None]:
         prompt_messages: list[PromptMessage] = []
 
@@ -1137,7 +1139,7 @@ class LLMNode(Node[LLMNodeData]):
         *,
         invoke_result: LLMResult | LLMResultWithStructuredOutput,
         saver: LLMFileSaver,
-        file_outputs: list["File"],
+        file_outputs: list[File],
         reasoning_format: Literal["separated", "tagged"] = "tagged",
         request_latency: float | None = None,
     ) -> ModelInvokeCompletedEvent:
@@ -1179,7 +1181,7 @@ class LLMNode(Node[LLMNodeData]):
         *,
         content: ImagePromptMessageContent,
         file_saver: LLMFileSaver,
-    ) -> "File":
+    ) -> File:
         """_save_multimodal_output saves multi-modal contents generated by LLM plugins.
 
         There are two kinds of multimodal outputs:
@@ -1229,7 +1231,7 @@ class LLMNode(Node[LLMNodeData]):
         *,
         contents: str | list[PromptMessageContentUnionTypes] | None,
         file_saver: LLMFileSaver,
-        file_outputs: list["File"],
+        file_outputs: list[File],
     ) -> Generator[str, None, None]:
         """Convert intermediate prompt messages into strings and yield them to the caller.
 

api/core/workflow/repositories/draft_variable_repository.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import abc
 from collections.abc import Mapping
 from typing import Any, Protocol
@@ -23,7 +25,7 @@ class DraftVariableSaverFactory(Protocol):
         node_type: NodeType,
         node_execution_id: str,
         enclosing_node_id: str | None = None,
-    ) -> "DraftVariableSaver":
+    ) -> DraftVariableSaver:
         pass
 
 

api/core/workflow/runtime/variable_pool.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import re
 from collections import defaultdict
 from collections.abc import Mapping, Sequence
@@ -267,6 +269,6 @@ class VariablePool(BaseModel):
             self.add(selector, value)
 
     @classmethod
-    def empty(cls) -> "VariablePool":
+    def empty(cls) -> VariablePool:
         """Create an empty variable pool."""
         return cls(system_variables=SystemVariable.empty())

api/core/workflow/system_variable.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from collections.abc import Mapping, Sequence
 from types import MappingProxyType
 from typing import Any
@@ -70,7 +72,7 @@ class SystemVariable(BaseModel):
         return data
 
     @classmethod
-    def empty(cls) -> "SystemVariable":
+    def empty(cls) -> SystemVariable:
         return cls()
 
     def to_dict(self) -> dict[SystemVariableKey, Any]:
@@ -114,7 +116,7 @@ class SystemVariable(BaseModel):
             d[SystemVariableKey.TIMESTAMP] = self.timestamp
         return d
 
-    def as_view(self) -> "SystemVariableReadOnlyView":
+    def as_view(self) -> SystemVariableReadOnlyView:
         return SystemVariableReadOnlyView(self)