Signed-off-by: yihong0618 <zouzou0208@gmail.com> Signed-off-by: -LAN- <laipz8200@outlook.com> Co-authored-by: -LAN- <laipz8200@outlook.com>
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@ -2,7 +2,7 @@ from datetime import datetime
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from enum import Enum, StrEnum
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from typing import Any, Optional
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from pydantic import BaseModel, field_validator
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from pydantic import BaseModel
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from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk
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from core.workflow.entities.node_entities import NodeRunMetadataKey
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@ -113,18 +113,6 @@ class QueueIterationNextEvent(AppQueueEvent):
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output: Optional[Any] = None # output for the current iteration
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duration: Optional[float] = None
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@field_validator("output", mode="before")
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@classmethod
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def set_output(cls, v):
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"""
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Set output
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"""
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if v is None:
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return None
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if isinstance(v, int | float | str | bool | dict | list):
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return v
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raise ValueError("output must be a valid type")
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class QueueIterationCompletedEvent(AppQueueEvent):
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"""
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@ -9,7 +9,7 @@ from typing import TYPE_CHECKING, Any, Optional, cast
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from flask import Flask, current_app
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from configs import dify_config
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from core.model_runtime.utils.encoders import jsonable_encoder
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from core.variables import IntegerVariable
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from core.workflow.entities.node_entities import (
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NodeRunMetadataKey,
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NodeRunResult,
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@ -155,18 +155,19 @@ class IterationNode(BaseNode[IterationNodeData]):
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iteration_node_data=self.node_data,
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index=0,
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pre_iteration_output=None,
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duration=None,
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)
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iter_run_map: dict[str, float] = {}
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outputs: list[Any] = [None] * len(iterator_list_value)
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try:
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if self.node_data.is_parallel:
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futures: list[Future] = []
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q = Queue()
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q: Queue = Queue()
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thread_pool = GraphEngineThreadPool(max_workers=self.node_data.parallel_nums, max_submit_count=100)
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for index, item in enumerate(iterator_list_value):
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future: Future = thread_pool.submit(
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self._run_single_iter_parallel,
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current_app._get_current_object(),
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current_app._get_current_object(), # type: ignore
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q,
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iterator_list_value,
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inputs,
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@ -181,6 +182,7 @@ class IterationNode(BaseNode[IterationNodeData]):
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future.add_done_callback(thread_pool.task_done_callback)
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futures.append(future)
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succeeded_count = 0
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empty_count = 0
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while True:
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try:
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event = q.get(timeout=1)
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@ -208,17 +210,22 @@ class IterationNode(BaseNode[IterationNodeData]):
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else:
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for _ in range(len(iterator_list_value)):
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yield from self._run_single_iter(
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iterator_list_value,
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variable_pool,
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inputs,
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outputs,
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start_at,
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graph_engine,
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iteration_graph,
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iter_run_map,
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iterator_list_value=iterator_list_value,
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variable_pool=variable_pool,
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inputs=inputs,
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outputs=outputs,
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start_at=start_at,
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graph_engine=graph_engine,
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iteration_graph=iteration_graph,
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iter_run_map=iter_run_map,
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)
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if self.node_data.error_handle_mode == ErrorHandleMode.REMOVE_ABNORMAL_OUTPUT:
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outputs = [output for output in outputs if output is not None]
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# Flatten the list of lists
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if isinstance(outputs, list) and all(isinstance(output, list) for output in outputs):
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outputs = [item for sublist in outputs for item in sublist]
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yield IterationRunSucceededEvent(
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iteration_id=self.id,
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iteration_node_id=self.node_id,
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@ -226,7 +233,7 @@ class IterationNode(BaseNode[IterationNodeData]):
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iteration_node_data=self.node_data,
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start_at=start_at,
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inputs=inputs,
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outputs={"output": jsonable_encoder(outputs)},
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outputs={"output": outputs},
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steps=len(iterator_list_value),
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metadata={"total_tokens": graph_engine.graph_runtime_state.total_tokens},
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)
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@ -234,7 +241,7 @@ class IterationNode(BaseNode[IterationNodeData]):
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yield RunCompletedEvent(
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run_result=NodeRunResult(
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status=WorkflowNodeExecutionStatus.SUCCEEDED,
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outputs={"output": jsonable_encoder(outputs)},
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outputs={"output": outputs},
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metadata={NodeRunMetadataKey.ITERATION_DURATION_MAP: iter_run_map},
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)
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)
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@ -248,7 +255,7 @@ class IterationNode(BaseNode[IterationNodeData]):
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iteration_node_data=self.node_data,
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start_at=start_at,
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inputs=inputs,
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outputs={"output": jsonable_encoder(outputs)},
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outputs={"output": outputs},
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steps=len(iterator_list_value),
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metadata={"total_tokens": graph_engine.graph_runtime_state.total_tokens},
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error=str(e),
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@ -280,7 +287,7 @@ class IterationNode(BaseNode[IterationNodeData]):
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:param node_data: node data
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:return:
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"""
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variable_mapping = {
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variable_mapping: dict[str, Sequence[str]] = {
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f"{node_id}.input_selector": node_data.iterator_selector,
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}
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@ -308,7 +315,7 @@ class IterationNode(BaseNode[IterationNodeData]):
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sub_node_variable_mapping = node_cls.extract_variable_selector_to_variable_mapping(
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graph_config=graph_config, config=sub_node_config
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)
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sub_node_variable_mapping = cast(dict[str, list[str]], sub_node_variable_mapping)
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sub_node_variable_mapping = cast(dict[str, Sequence[str]], sub_node_variable_mapping)
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except NotImplementedError:
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sub_node_variable_mapping = {}
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@ -329,8 +336,12 @@ class IterationNode(BaseNode[IterationNodeData]):
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return variable_mapping
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def _handle_event_metadata(
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self, event: BaseNodeEvent, iter_run_index: str, parallel_mode_run_id: str
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) -> NodeRunStartedEvent | BaseNodeEvent:
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self,
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*,
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event: BaseNodeEvent | InNodeEvent,
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iter_run_index: int,
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parallel_mode_run_id: str | None,
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) -> NodeRunStartedEvent | BaseNodeEvent | InNodeEvent:
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"""
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add iteration metadata to event.
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"""
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@ -355,6 +366,7 @@ class IterationNode(BaseNode[IterationNodeData]):
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def _run_single_iter(
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self,
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*,
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iterator_list_value: list[str],
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variable_pool: VariablePool,
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inputs: dict[str, list],
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@ -373,12 +385,12 @@ class IterationNode(BaseNode[IterationNodeData]):
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try:
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rst = graph_engine.run()
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# get current iteration index
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current_index = variable_pool.get([self.node_id, "index"]).value
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index_variable = variable_pool.get([self.node_id, "index"])
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if not isinstance(index_variable, IntegerVariable):
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raise IterationIndexNotFoundError(f"iteration {self.node_id} current index not found")
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current_index = index_variable.value
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iteration_run_id = parallel_mode_run_id if parallel_mode_run_id is not None else f"{current_index}"
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next_index = int(current_index) + 1
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if current_index is None:
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raise IterationIndexNotFoundError(f"iteration {self.node_id} current index not found")
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for event in rst:
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if isinstance(event, (BaseNodeEvent | BaseParallelBranchEvent)) and not event.in_iteration_id:
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event.in_iteration_id = self.node_id
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@ -391,7 +403,9 @@ class IterationNode(BaseNode[IterationNodeData]):
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continue
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if isinstance(event, NodeRunSucceededEvent):
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yield self._handle_event_metadata(event, current_index, parallel_mode_run_id)
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yield self._handle_event_metadata(
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event=event, iter_run_index=current_index, parallel_mode_run_id=parallel_mode_run_id
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)
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elif isinstance(event, BaseGraphEvent):
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if isinstance(event, GraphRunFailedEvent):
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# iteration run failed
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@ -404,7 +418,7 @@ class IterationNode(BaseNode[IterationNodeData]):
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parallel_mode_run_id=parallel_mode_run_id,
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start_at=start_at,
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inputs=inputs,
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outputs={"output": jsonable_encoder(outputs)},
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outputs={"output": outputs},
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steps=len(iterator_list_value),
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metadata={"total_tokens": graph_engine.graph_runtime_state.total_tokens},
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error=event.error,
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@ -417,7 +431,7 @@ class IterationNode(BaseNode[IterationNodeData]):
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iteration_node_data=self.node_data,
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start_at=start_at,
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inputs=inputs,
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outputs={"output": jsonable_encoder(outputs)},
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outputs={"output": outputs},
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steps=len(iterator_list_value),
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metadata={"total_tokens": graph_engine.graph_runtime_state.total_tokens},
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error=event.error,
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@ -429,9 +443,11 @@ class IterationNode(BaseNode[IterationNodeData]):
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)
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)
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return
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else:
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event = cast(InNodeEvent, event)
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metadata_event = self._handle_event_metadata(event, current_index, parallel_mode_run_id)
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elif isinstance(event, InNodeEvent):
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# event = cast(InNodeEvent, event)
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metadata_event = self._handle_event_metadata(
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event=event, iter_run_index=current_index, parallel_mode_run_id=parallel_mode_run_id
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)
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if isinstance(event, NodeRunFailedEvent):
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if self.node_data.error_handle_mode == ErrorHandleMode.CONTINUE_ON_ERROR:
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yield NodeInIterationFailedEvent(
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@ -513,7 +529,7 @@ class IterationNode(BaseNode[IterationNodeData]):
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iteration_node_data=self.node_data,
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index=next_index,
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parallel_mode_run_id=parallel_mode_run_id,
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pre_iteration_output=jsonable_encoder(current_iteration_output) if current_iteration_output else None,
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pre_iteration_output=current_iteration_output or None,
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duration=duration,
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)
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@ -551,7 +567,7 @@ class IterationNode(BaseNode[IterationNodeData]):
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index: int,
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item: Any,
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iter_run_map: dict[str, float],
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) -> Generator[NodeEvent | InNodeEvent, None, None]:
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):
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"""
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run single iteration in parallel mode
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"""
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