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refactor(api): continue decoupling dify_graph from API concerns (#33580)
Signed-off-by: -LAN- <laipz8200@outlook.com> Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> Co-authored-by: WH-2099 <wh2099@pm.me>
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GitHub
@ -1,15 +1,14 @@
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import json
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from collections.abc import Mapping, MutableMapping, Sequence
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from typing import TYPE_CHECKING, Any
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from collections.abc import Generator, Mapping, MutableMapping, Sequence
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from typing import TYPE_CHECKING, Any, cast
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from dify_graph.constants import CONVERSATION_VARIABLE_NODE_ID
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from dify_graph.entities.graph_config import NodeConfigDict
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from dify_graph.enums import BuiltinNodeTypes, WorkflowNodeExecutionStatus
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from dify_graph.node_events import NodeRunResult
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from dify_graph.node_events import NodeEventBase, NodeRunResult, StreamCompletedEvent, VariableUpdatedEvent
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from dify_graph.nodes.base.node import Node
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from dify_graph.nodes.variable_assigner.common import helpers as common_helpers
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from dify_graph.nodes.variable_assigner.common.exc import VariableOperatorNodeError
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from dify_graph.variables import SegmentType, VariableBase
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from dify_graph.variables import SegmentType, Variable, VariableBase
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from dify_graph.variables.consts import SELECTORS_LENGTH
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from . import helpers
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@ -29,9 +28,6 @@ if TYPE_CHECKING:
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def _target_mapping_from_item(mapping: MutableMapping[str, Sequence[str]], node_id: str, item: VariableOperationItem):
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selector_node_id = item.variable_selector[0]
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if selector_node_id != CONVERSATION_VARIABLE_NODE_ID:
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return
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selector_str = ".".join(item.variable_selector)
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key = f"{node_id}.#{selector_str}#"
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mapping[key] = item.variable_selector
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@ -103,15 +99,18 @@ class VariableAssignerNode(Node[VariableAssignerNodeData]):
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_source_mapping_from_item(var_mapping, node_id, item)
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return var_mapping
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def _run(self) -> NodeRunResult:
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def _run(self) -> Generator[NodeEventBase, None, None]:
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inputs = self.node_data.model_dump()
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process_data: dict[str, Any] = {}
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# NOTE: This node has no outputs
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updated_variable_selectors: list[Sequence[str]] = []
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# Preserve intra-node read-after-write behavior without mutating the shared pool
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# until the engine processes the emitted VariableUpdatedEvent instances.
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working_variable_pool = self.graph_runtime_state.variable_pool.model_copy(deep=True)
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try:
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for item in self.node_data.items:
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variable = self.graph_runtime_state.variable_pool.get(item.variable_selector)
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variable = working_variable_pool.get(item.variable_selector)
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# ==================== Validation Part
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@ -136,60 +135,64 @@ class VariableAssignerNode(Node[VariableAssignerNodeData]):
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raise InputTypeNotSupportedError(input_type=InputType.CONSTANT, operation=item.operation)
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# Get value from variable pool
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input_value = item.value
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if (
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item.input_type == InputType.VARIABLE
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and item.operation not in {Operation.CLEAR, Operation.REMOVE_FIRST, Operation.REMOVE_LAST}
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and item.value is not None
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):
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value = self.graph_runtime_state.variable_pool.get(item.value)
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value = working_variable_pool.get(item.value)
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if value is None:
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raise VariableNotFoundError(variable_selector=item.value)
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# Skip if value is NoneSegment
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if value.value_type == SegmentType.NONE:
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continue
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item.value = value.value
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input_value = value.value
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# If set string / bytes / bytearray to object, try convert string to object.
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if (
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item.operation == Operation.SET
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and variable.value_type == SegmentType.OBJECT
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and isinstance(item.value, str | bytes | bytearray)
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and isinstance(input_value, str | bytes | bytearray)
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):
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try:
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item.value = json.loads(item.value)
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input_value = json.loads(input_value)
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except json.JSONDecodeError:
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raise InvalidInputValueError(value=item.value)
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raise InvalidInputValueError(value=input_value)
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# Check if input value is valid
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if not helpers.is_input_value_valid(
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variable_type=variable.value_type, operation=item.operation, value=item.value
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variable_type=variable.value_type, operation=item.operation, value=input_value
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):
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raise InvalidInputValueError(value=item.value)
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raise InvalidInputValueError(value=input_value)
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# ==================== Execution Part
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updated_value = self._handle_item(
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variable=variable,
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operation=item.operation,
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value=item.value,
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value=input_value,
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)
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variable = variable.model_copy(update={"value": updated_value})
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self.graph_runtime_state.variable_pool.add(variable.selector, variable)
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updated_variable_selectors.append(variable.selector)
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updated_variable = variable.model_copy(update={"value": updated_value})
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working_variable_pool.add(updated_variable.selector, updated_variable)
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updated_variable_selectors.append(updated_variable.selector)
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except VariableOperatorNodeError as e:
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return NodeRunResult(
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status=WorkflowNodeExecutionStatus.FAILED,
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inputs=inputs,
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process_data=process_data,
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error=str(e),
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yield StreamCompletedEvent(
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node_run_result=NodeRunResult(
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status=WorkflowNodeExecutionStatus.FAILED,
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inputs=inputs,
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process_data=process_data,
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error=str(e),
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)
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)
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return
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# The `updated_variable_selectors` is a list contains list[str] which not hashable,
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# remove the duplicated items first.
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updated_variable_selectors = list(set(map(tuple, updated_variable_selectors)))
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# remove duplicated items while preserving the first update order.
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updated_variable_selectors = list(dict.fromkeys(map(tuple, updated_variable_selectors)))
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for selector in updated_variable_selectors:
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variable = self.graph_runtime_state.variable_pool.get(selector)
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variable = working_variable_pool.get(selector)
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if not isinstance(variable, VariableBase):
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raise VariableNotFoundError(variable_selector=selector)
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process_data[variable.name] = variable.value
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@ -197,15 +200,23 @@ class VariableAssignerNode(Node[VariableAssignerNodeData]):
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updated_variables = [
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common_helpers.variable_to_processed_data(selector, seg)
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for selector in updated_variable_selectors
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if (seg := self.graph_runtime_state.variable_pool.get(selector)) is not None
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if (seg := working_variable_pool.get(selector)) is not None
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]
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process_data = common_helpers.set_updated_variables(process_data, updated_variables)
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return NodeRunResult(
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status=WorkflowNodeExecutionStatus.SUCCEEDED,
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inputs=inputs,
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process_data=process_data,
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outputs={},
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for selector in updated_variable_selectors:
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variable = working_variable_pool.get(selector)
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if not isinstance(variable, VariableBase):
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raise VariableNotFoundError(variable_selector=selector)
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yield VariableUpdatedEvent(variable=cast(Variable, variable))
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yield StreamCompletedEvent(
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node_run_result=NodeRunResult(
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status=WorkflowNodeExecutionStatus.SUCCEEDED,
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inputs=inputs,
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process_data=process_data,
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outputs={},
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)
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)
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def _handle_item(
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