Implement FastAPI Temporal MVP pipeline
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315
app/workers/workflows/mid_end_pipeline.py
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315
app/workers/workflows/mid_end_pipeline.py
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"""Mid-end image pipeline workflow with review signal support."""
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from datetime import timedelta
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from temporalio import workflow
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from temporalio.common import RetryPolicy
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with workflow.unsafe.imports_passed_through():
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from app.domain.enums import OrderStatus, ReviewDecision, WorkflowStepName
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from app.infra.temporal.task_queues import (
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IMAGE_PIPELINE_CONTROL_TASK_QUEUE,
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IMAGE_PIPELINE_EXPORT_TASK_QUEUE,
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IMAGE_PIPELINE_IMAGE_GEN_TASK_QUEUE,
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IMAGE_PIPELINE_POST_PROCESS_TASK_QUEUE,
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IMAGE_PIPELINE_QC_TASK_QUEUE,
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)
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from app.workers.activities.export_activities import run_export_activity
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from app.workers.activities.face_activities import run_face_activity
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from app.workers.activities.fusion_activities import run_fusion_activity
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from app.workers.activities.qc_activities import run_qc_activity
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from app.workers.activities.review_activities import (
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complete_review_wait_activity,
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mark_waiting_for_review_activity,
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mark_workflow_failed_activity,
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)
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from app.workers.activities.scene_activities import run_scene_activity
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from app.workers.activities.texture_activities import run_texture_activity
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from app.workers.activities.tryon_activities import prepare_model_activity, run_tryon_activity
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from app.workers.workflows.types import (
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MockActivityResult,
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PipelineWorkflowInput,
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ReviewResolutionActivityInput,
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ReviewSignalPayload,
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ReviewWaitActivityInput,
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StepActivityInput,
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WorkflowFailureActivityInput,
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)
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ACTIVITY_TIMEOUT = timedelta(seconds=30)
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ACTIVITY_RETRY_POLICY = RetryPolicy(
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initial_interval=timedelta(seconds=1),
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backoff_coefficient=2.0,
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maximum_attempts=3,
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)
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@workflow.defn
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class MidEndPipelineWorkflow:
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"""Mid-end workflow that pauses for human review and supports reruns."""
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def __init__(self) -> None:
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self._review_payload: ReviewSignalPayload | None = None
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@workflow.signal
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def submit_review(self, payload: ReviewSignalPayload) -> None:
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"""Receive a review decision from the API layer."""
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self._review_payload = payload
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@workflow.run
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async def run(self, payload: PipelineWorkflowInput) -> dict[str, int | str | None]:
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"""Execute the mid-end workflow with a human review loop."""
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current_step = WorkflowStepName.PREPARE_MODEL
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try:
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prepared = await workflow.execute_activity(
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prepare_model_activity,
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StepActivityInput(
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order_id=payload.order_id,
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workflow_run_id=payload.workflow_run_id,
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step_name=WorkflowStepName.PREPARE_MODEL,
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model_id=payload.model_id,
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pose_id=payload.pose_id,
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garment_asset_id=payload.garment_asset_id,
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scene_ref_asset_id=payload.scene_ref_asset_id,
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),
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task_queue=IMAGE_PIPELINE_CONTROL_TASK_QUEUE,
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start_to_close_timeout=ACTIVITY_TIMEOUT,
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retry_policy=ACTIVITY_RETRY_POLICY,
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)
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current_step = WorkflowStepName.TRYON
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tryon_result = await workflow.execute_activity(
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run_tryon_activity,
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StepActivityInput(
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order_id=payload.order_id,
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workflow_run_id=payload.workflow_run_id,
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step_name=WorkflowStepName.TRYON,
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source_asset_id=prepared.asset_id,
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garment_asset_id=payload.garment_asset_id,
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),
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task_queue=IMAGE_PIPELINE_IMAGE_GEN_TASK_QUEUE,
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start_to_close_timeout=ACTIVITY_TIMEOUT,
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retry_policy=ACTIVITY_RETRY_POLICY,
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)
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current_step = WorkflowStepName.SCENE
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scene_result = await self._run_scene(payload, tryon_result.asset_id)
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current_step = WorkflowStepName.TEXTURE
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texture_result = await self._run_texture(payload, scene_result.asset_id)
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current_step = WorkflowStepName.FACE
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face_result = await self._run_face(payload, texture_result.asset_id)
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current_step = WorkflowStepName.FUSION
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fusion_result = await self._run_fusion(payload, scene_result.asset_id, face_result.asset_id)
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current_step = WorkflowStepName.QC
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qc_result = await self._run_qc(payload, fusion_result.asset_id)
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if not qc_result.passed:
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await self._mark_failed(payload, current_step, qc_result.message)
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return {"order_id": payload.order_id, "status": OrderStatus.FAILED.value, "final_asset_id": None}
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while True:
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current_step = WorkflowStepName.REVIEW
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await workflow.execute_activity(
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mark_waiting_for_review_activity,
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ReviewWaitActivityInput(
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order_id=payload.order_id,
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workflow_run_id=payload.workflow_run_id,
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candidate_asset_ids=qc_result.candidate_asset_ids,
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),
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task_queue=IMAGE_PIPELINE_CONTROL_TASK_QUEUE,
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start_to_close_timeout=ACTIVITY_TIMEOUT,
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retry_policy=ACTIVITY_RETRY_POLICY,
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)
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review_payload = await self._wait_for_review()
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await workflow.execute_activity(
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complete_review_wait_activity,
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ReviewResolutionActivityInput(
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order_id=payload.order_id,
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workflow_run_id=payload.workflow_run_id,
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decision=review_payload.decision,
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reviewer_id=review_payload.reviewer_id,
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selected_asset_id=review_payload.selected_asset_id,
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comment=review_payload.comment,
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),
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task_queue=IMAGE_PIPELINE_CONTROL_TASK_QUEUE,
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start_to_close_timeout=ACTIVITY_TIMEOUT,
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retry_policy=ACTIVITY_RETRY_POLICY,
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)
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if review_payload.decision == ReviewDecision.APPROVE:
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current_step = WorkflowStepName.EXPORT
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export_source_id = review_payload.selected_asset_id
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if export_source_id is None:
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export_source_id = (qc_result.candidate_asset_ids or [fusion_result.asset_id])[0]
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final_result = await workflow.execute_activity(
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run_export_activity,
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StepActivityInput(
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order_id=payload.order_id,
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workflow_run_id=payload.workflow_run_id,
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step_name=WorkflowStepName.EXPORT,
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source_asset_id=export_source_id,
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),
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task_queue=IMAGE_PIPELINE_EXPORT_TASK_QUEUE,
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start_to_close_timeout=ACTIVITY_TIMEOUT,
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retry_policy=ACTIVITY_RETRY_POLICY,
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)
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return {
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"order_id": payload.order_id,
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"status": OrderStatus.SUCCEEDED.value,
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"final_asset_id": final_result.asset_id,
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}
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if review_payload.decision == ReviewDecision.REJECT:
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return {"order_id": payload.order_id, "status": OrderStatus.FAILED.value, "final_asset_id": None}
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if review_payload.decision == ReviewDecision.RERUN_SCENE:
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current_step = WorkflowStepName.SCENE
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scene_result = await self._run_scene(payload, tryon_result.asset_id)
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current_step = WorkflowStepName.TEXTURE
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texture_result = await self._run_texture(payload, scene_result.asset_id)
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current_step = WorkflowStepName.FACE
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face_result = await self._run_face(payload, texture_result.asset_id)
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current_step = WorkflowStepName.FUSION
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fusion_result = await self._run_fusion(payload, scene_result.asset_id, face_result.asset_id)
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elif review_payload.decision == ReviewDecision.RERUN_FACE:
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current_step = WorkflowStepName.FACE
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face_result = await self._run_face(payload, texture_result.asset_id)
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current_step = WorkflowStepName.FUSION
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fusion_result = await self._run_fusion(payload, scene_result.asset_id, face_result.asset_id)
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elif review_payload.decision == ReviewDecision.RERUN_FUSION:
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current_step = WorkflowStepName.FUSION
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fusion_result = await self._run_fusion(payload, scene_result.asset_id, face_result.asset_id)
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current_step = WorkflowStepName.QC
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qc_result = await self._run_qc(payload, fusion_result.asset_id)
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if not qc_result.passed:
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await self._mark_failed(payload, current_step, qc_result.message)
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return {"order_id": payload.order_id, "status": OrderStatus.FAILED.value, "final_asset_id": None}
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except Exception as exc:
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await self._mark_failed(payload, current_step, str(exc))
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raise
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async def _wait_for_review(self) -> ReviewSignalPayload:
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"""Suspend the workflow until a review signal arrives."""
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if self._review_payload is None:
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await workflow.wait_condition(lambda: self._review_payload is not None)
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assert self._review_payload is not None
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review_payload = self._review_payload
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self._review_payload = None
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return review_payload
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async def _run_scene(self, payload: PipelineWorkflowInput, source_asset_id: int | None) -> MockActivityResult:
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"""Execute the scene activity."""
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return await workflow.execute_activity(
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run_scene_activity,
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StepActivityInput(
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order_id=payload.order_id,
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workflow_run_id=payload.workflow_run_id,
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step_name=WorkflowStepName.SCENE,
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source_asset_id=source_asset_id,
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scene_ref_asset_id=payload.scene_ref_asset_id,
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),
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task_queue=IMAGE_PIPELINE_IMAGE_GEN_TASK_QUEUE,
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start_to_close_timeout=ACTIVITY_TIMEOUT,
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retry_policy=ACTIVITY_RETRY_POLICY,
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)
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async def _run_texture(self, payload: PipelineWorkflowInput, source_asset_id: int | None) -> MockActivityResult:
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"""Execute the texture activity."""
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return await workflow.execute_activity(
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run_texture_activity,
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StepActivityInput(
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order_id=payload.order_id,
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workflow_run_id=payload.workflow_run_id,
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step_name=WorkflowStepName.TEXTURE,
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source_asset_id=source_asset_id,
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),
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task_queue=IMAGE_PIPELINE_POST_PROCESS_TASK_QUEUE,
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start_to_close_timeout=ACTIVITY_TIMEOUT,
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retry_policy=ACTIVITY_RETRY_POLICY,
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)
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async def _run_face(self, payload: PipelineWorkflowInput, source_asset_id: int | None) -> MockActivityResult:
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"""Execute the face activity."""
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return await workflow.execute_activity(
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run_face_activity,
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StepActivityInput(
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order_id=payload.order_id,
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workflow_run_id=payload.workflow_run_id,
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step_name=WorkflowStepName.FACE,
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source_asset_id=source_asset_id,
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),
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task_queue=IMAGE_PIPELINE_POST_PROCESS_TASK_QUEUE,
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start_to_close_timeout=ACTIVITY_TIMEOUT,
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retry_policy=ACTIVITY_RETRY_POLICY,
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)
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async def _run_fusion(
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self,
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payload: PipelineWorkflowInput,
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source_asset_id: int | None,
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face_asset_id: int | None,
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) -> MockActivityResult:
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"""Execute the fusion activity."""
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return await workflow.execute_activity(
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run_fusion_activity,
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StepActivityInput(
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order_id=payload.order_id,
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workflow_run_id=payload.workflow_run_id,
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step_name=WorkflowStepName.FUSION,
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source_asset_id=source_asset_id,
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selected_asset_id=face_asset_id,
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),
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task_queue=IMAGE_PIPELINE_POST_PROCESS_TASK_QUEUE,
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start_to_close_timeout=ACTIVITY_TIMEOUT,
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retry_policy=ACTIVITY_RETRY_POLICY,
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)
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async def _run_qc(self, payload: PipelineWorkflowInput, source_asset_id: int | None) -> MockActivityResult:
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"""Execute the QC activity."""
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return await workflow.execute_activity(
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run_qc_activity,
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StepActivityInput(
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order_id=payload.order_id,
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workflow_run_id=payload.workflow_run_id,
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step_name=WorkflowStepName.QC,
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source_asset_id=source_asset_id,
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),
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task_queue=IMAGE_PIPELINE_QC_TASK_QUEUE,
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start_to_close_timeout=ACTIVITY_TIMEOUT,
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retry_policy=ACTIVITY_RETRY_POLICY,
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)
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async def _mark_failed(
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self,
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payload: PipelineWorkflowInput,
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current_step: WorkflowStepName,
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message: str,
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) -> None:
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"""Persist workflow failure state."""
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await workflow.execute_activity(
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mark_workflow_failed_activity,
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WorkflowFailureActivityInput(
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order_id=payload.order_id,
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workflow_run_id=payload.workflow_run_id,
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current_step=current_step,
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message=message,
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),
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task_queue=IMAGE_PIPELINE_CONTROL_TASK_QUEUE,
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start_to_close_timeout=ACTIVITY_TIMEOUT,
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retry_policy=ACTIVITY_RETRY_POLICY,
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)
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