343 lines
15 KiB
Python
343 lines
15 KiB
Python
from __future__ import annotations
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from datetime import datetime, timedelta, timezone
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import logging
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from typing import Any
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from sqlalchemy import or_, select
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.config import settings
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from app.enums.celery_queue import CeleryQueue
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from app.enums.llm_billing import LlmBillingLedgerState
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from app.enums.shot_replicate import ShotSplitStatusEnum
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from app.models.shot_replicate_segment import ShotReplicateSegment
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from app.models.shot_replicate_task_set import ShotReplicateTaskSet
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from app.services.shot_replicate_taskset_service import (
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build_segment_analysis_billing_context,
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build_task_set_analysis_billing_context,
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refresh_task_set_split_summaries,
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)
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from app.services.llm_billing import get_llm_ledger_states
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from app.services.celery_runtime.runtime_service import runtime_lock_values
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from app.tasks.celery_app import celery_app
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logger = logging.getLogger("video_gen")
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def _now() -> datetime:
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return datetime.now(timezone.utc)
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def _ensure_aware(value: datetime | None) -> datetime | None:
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if value is None:
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return None
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if value.tzinfo is None:
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return value.replace(tzinfo=timezone.utc)
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return value.astimezone(timezone.utc)
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def _expired(value: datetime | None, now: datetime | None = None) -> bool:
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checked = _ensure_aware(value)
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if checked is None:
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return True
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return checked <= (now or _now())
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def _queue_timeout(segment: ShotReplicateSegment, now: datetime | None = None) -> bool:
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enqueued_at = _ensure_aware(segment.split_enqueued_at)
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if enqueued_at is None:
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return True
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return enqueued_at + timedelta(seconds=int(settings.SHOT_SPLIT_PENDING_TIMEOUT_SECONDS or 300)) <= (now or _now())
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async def recover_shot_split_tasks_once(db: AsyncSession) -> dict[str, Any]:
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"""批量恢复拆镜 ffmpeg 任务；只接管执行锁消失且业务租约到期的记录。"""
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from app.tasks.shot_replicate_tasks import split_one_segment
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batch_size = max(1, int(settings.SHOT_SPLIT_RECOVERY_BATCH_SIZE or 50))
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current_time = _now()
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result = await db.execute(
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select(ShotReplicateSegment)
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.where(
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ShotReplicateSegment.deleted_at.is_(None),
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ShotReplicateSegment.split_status.in_(
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[
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ShotSplitStatusEnum.PENDING.value,
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ShotSplitStatusEnum.PROCESSING.value,
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ShotSplitStatusEnum.RETRY_WAITING.value,
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]
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),
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)
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.order_by(ShotReplicateSegment.updated_at.asc(), ShotReplicateSegment.id.asc())
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.limit(batch_size)
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.with_for_update(skip_locked=True)
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)
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segments = list(result.scalars().all())
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due_segments: list[ShotReplicateSegment] = []
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results: dict[str, int] = {}
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for segment in segments:
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if segment.split_status == ShotSplitStatusEnum.PENDING.value:
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due = _queue_timeout(segment, current_time)
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elif segment.split_status == ShotSplitStatusEnum.PROCESSING.value:
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due = _expired(segment.split_lease_until, current_time)
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else:
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due = _expired(segment.split_next_retry_at, current_time)
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if not due:
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key = f"skip_{segment.split_status}_not_due"
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results[key] = results.get(key, 0) + 1
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continue
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due_segments.append(segment)
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lock_key_by_id: dict[str, str] = {}
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for segment in due_segments:
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current_attempt = max(0, int(segment.split_retry_count or 0))
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active_attempt = (
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max(1, current_attempt)
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if segment.split_status == ShotSplitStatusEnum.PROCESSING.value
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else current_attempt + 1
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)
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lock_key_by_id[str(segment.id)] = (
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f"{settings.SHOT_SPLIT_LOCK_KEY_PREFIX}:{segment.id}:attempt:{active_attempt}"
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)
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live_locks = await runtime_lock_values(list(lock_key_by_id.values()))
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dispatches: list[tuple[str, int]] = []
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touched_task_set_ids: set[str] = set()
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for segment in due_segments:
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lock_key = lock_key_by_id[str(segment.id)]
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if live_locks.get(lock_key):
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results["skip_live_runtime_lock"] = results.get("skip_live_runtime_lock", 0) + 1
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continue
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touched_task_set_ids.add(str(segment.task_set_id))
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if int(segment.split_retry_count or 0) >= int(settings.SHOT_SPLIT_MAX_RETRY_COUNT or 3):
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segment.split_status = ShotSplitStatusEnum.FAILED.value
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segment.split_last_error = segment.split_last_error or "恢复时超过最大重试次数"
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segment.split_claim_token = None
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segment.split_lease_until = None
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segment.split_next_retry_at = None
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results["mark_failed_max_retry"] = results.get("mark_failed_max_retry", 0) + 1
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continue
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segment.split_status = ShotSplitStatusEnum.PENDING.value
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segment.split_claim_token = None
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segment.split_enqueued_at = current_time
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segment.split_lease_until = None
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segment.split_next_retry_at = None
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next_attempt = int(segment.split_retry_count or 0) + 1
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dispatches.append((str(segment.id), next_attempt))
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results["recover_db"] = results.get("recover_db", 0) + 1
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await refresh_task_set_split_summaries(db, touched_task_set_ids)
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await db.commit()
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enqueue_failed = 0
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if celery_app:
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for segment_id, next_attempt in dispatches:
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try:
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split_one_segment.apply_async(
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args=[segment_id],
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queue=CeleryQueue.GEN_SHOT_SPLIT.value,
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priority=settings.DOWNLOAD_TASK_PRIORITY_RECOVER,
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countdown=0,
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task_id=f"shot-split:{segment_id}:attempt:{next_attempt}",
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)
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except Exception:
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enqueue_failed += 1
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if enqueue_failed:
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results["enqueue_failed"] = enqueue_failed
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return {"checked": len(segments), "results": results}
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async def recover_shot_analysis_tasks_once(db: AsyncSession) -> dict[str, Any]:
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"""恢复长视频分析；只接管执行锁消失且数据库租约已到期的记录。"""
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from app.enums.shot_replicate import (
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ShotAnalysisStatusEnum,
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ShotSegmentAnalysisStatusEnum,
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ShotTaskSetStatusEnum,
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)
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from app.services.celery_runtime.runtime_service import runtime_lock_values
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from app.tasks.shot_replicate_tasks import analyze_custom_segment_video, analyze_original_video
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now = _now()
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queue_cutoff = now - timedelta(seconds=max(60, int(settings.MODULE_ASYNC_QUEUE_TIMEOUT_SECONDS or 300)))
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batch_size = max(1, int(settings.MODULE_ASYNC_RECOVERY_BATCH_SIZE or 100))
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task_set_result = await db.execute(
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select(ShotReplicateTaskSet)
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.where(
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ShotReplicateTaskSet.deleted_at.is_(None),
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ShotReplicateTaskSet.analysis_status.in_([
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ShotAnalysisStatusEnum.PENDING.value,
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ShotAnalysisStatusEnum.PROCESSING.value,
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]),
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or_(
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(
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(ShotReplicateTaskSet.analysis_status == ShotAnalysisStatusEnum.PENDING.value)
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& (ShotReplicateTaskSet.updated_at <= queue_cutoff)
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),
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(
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(ShotReplicateTaskSet.analysis_status == ShotAnalysisStatusEnum.PROCESSING.value)
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& or_(
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ShotReplicateTaskSet.analysis_lease_until <= now,
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(
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ShotReplicateTaskSet.analysis_lease_until.is_(None)
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& (ShotReplicateTaskSet.updated_at <= queue_cutoff)
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),
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)
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),
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),
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)
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.order_by(ShotReplicateTaskSet.updated_at.asc(), ShotReplicateTaskSet.id.asc())
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.limit(batch_size)
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.with_for_update(skip_locked=True)
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)
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task_sets = list(task_set_result.scalars().all())
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remaining = max(0, batch_size - len(task_sets))
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segments: list[ShotReplicateSegment] = []
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if remaining:
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segment_result = await db.execute(
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select(ShotReplicateSegment)
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.where(
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ShotReplicateSegment.deleted_at.is_(None),
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ShotReplicateSegment.segment_video_url.is_not(None),
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ShotReplicateSegment.analysis_status.in_([
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ShotSegmentAnalysisStatusEnum.PENDING.value,
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ShotSegmentAnalysisStatusEnum.PROCESSING.value,
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]),
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or_(
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(
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(ShotReplicateSegment.analysis_status == ShotSegmentAnalysisStatusEnum.PENDING.value)
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& (ShotReplicateSegment.updated_at <= queue_cutoff)
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),
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(
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(ShotReplicateSegment.analysis_status == ShotSegmentAnalysisStatusEnum.PROCESSING.value)
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& or_(
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ShotReplicateSegment.analysis_lease_until <= now,
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(
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ShotReplicateSegment.analysis_lease_until.is_(None)
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& (ShotReplicateSegment.updated_at <= queue_cutoff)
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),
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)
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),
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),
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)
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.order_by(ShotReplicateSegment.updated_at.asc(), ShotReplicateSegment.id.asc())
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.limit(remaining)
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.with_for_update(skip_locked=True)
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)
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segments = list(segment_result.scalars().all())
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billing_contexts = [
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*(build_task_set_analysis_billing_context(item) for item in task_sets),
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*(build_segment_analysis_billing_context(item) for item in segments),
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]
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# 场景积分消费配置变更后仍需识别并继续处理已存在的有效消费；缺少消费记录时禁止恢复。
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billing_states = await get_llm_ledger_states(db, billing_contexts)
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lock_keys: list[str] = []
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task_set_lock_keys: dict[str, str] = {}
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segment_lock_keys: dict[str, str] = {}
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for item in task_sets:
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attempt = max(1, int(item.analysis_attempt_no or 1))
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key = f"{settings.SHOT_ANALYSIS_LOCK_KEY_PREFIX}:shot_task_set:{item.id}:attempt:{attempt}"
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task_set_lock_keys[str(item.id)] = key
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lock_keys.append(key)
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for item in segments:
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attempt = max(1, int(item.analysis_attempt_no or 1))
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key = f"{settings.SHOT_ANALYSIS_LOCK_KEY_PREFIX}:shot_segment:{item.id}:attempt:{attempt}"
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segment_lock_keys[str(item.id)] = key
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lock_keys.append(key)
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live_locks = await runtime_lock_values(lock_keys)
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dispatches: list[tuple[str, str, int]] = []
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results: dict[str, int] = {}
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for item in task_sets:
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key = task_set_lock_keys[str(item.id)]
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if live_locks.get(key):
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results["skip_live_task_set_lock"] = results.get("skip_live_task_set_lock", 0) + 1
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continue
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context = build_task_set_analysis_billing_context(item)
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validation = billing_states.get(context.charge_biz_key)
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can_execute = bool(validation and validation.can_execute)
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state = validation.state.value if validation else LlmBillingLedgerState.MISSING.value
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if validation and validation.state == LlmBillingLedgerState.MISSING:
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state = LlmBillingLedgerState.INVALID.value
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if not can_execute:
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item.analysis_status = ShotAnalysisStatusEnum.FAILED.value
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item.status = ShotTaskSetStatusEnum.ANALYSIS_FAILED.value
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item.analysis_claim_token = None
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item.analysis_started_at = None
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item.analysis_lease_until = None
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item.analysis_error_message = f"LLM账务状态异常（{state}），恢复任务已终止"
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result_key = f"task_set_billing_{state}"
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results[result_key] = results.get(result_key, 0) + 1
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continue
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attempt = max(1, int(item.analysis_attempt_no or 1))
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item.analysis_status = ShotAnalysisStatusEnum.PENDING.value
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item.status = ShotTaskSetStatusEnum.PENDING_ANALYSIS.value
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item.analysis_claim_token = None
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item.analysis_started_at = None
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item.analysis_lease_until = None
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dispatches.append(("task_set", str(item.id), attempt))
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results["task_set_recovered"] = results.get("task_set_recovered", 0) + 1
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for item in segments:
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key = segment_lock_keys[str(item.id)]
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if live_locks.get(key):
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results["skip_live_segment_lock"] = results.get("skip_live_segment_lock", 0) + 1
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continue
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context = build_segment_analysis_billing_context(item)
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validation = billing_states.get(context.charge_biz_key)
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can_execute = bool(validation and validation.can_execute)
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state = validation.state.value if validation else LlmBillingLedgerState.MISSING.value
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if validation and validation.state == LlmBillingLedgerState.MISSING:
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state = LlmBillingLedgerState.INVALID.value
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if not can_execute:
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item.analysis_status = ShotSegmentAnalysisStatusEnum.FAILED.value
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item.analysis_claim_token = None
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item.analysis_started_at = None
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item.analysis_lease_until = None
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item.analysis_error_message = f"LLM账务状态异常（{state}），恢复任务已终止"
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result_key = f"segment_billing_{state}"
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results[result_key] = results.get(result_key, 0) + 1
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continue
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attempt = max(1, int(item.analysis_attempt_no or 1))
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item.analysis_status = ShotSegmentAnalysisStatusEnum.PENDING.value
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item.analysis_claim_token = None
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item.analysis_started_at = None
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item.analysis_lease_until = None
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dispatches.append(("segment", str(item.id), attempt))
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results["segment_recovered"] = results.get("segment_recovered", 0) + 1
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await db.commit()
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for owner_type, owner_id, attempt in dispatches:
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try:
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if owner_type == "task_set":
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analyze_original_video.apply_async(
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args=[owner_id, attempt],
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queue=CeleryQueue.GEN_SHOT_ANALYSIS.value,
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countdown=0,
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priority=settings.DOWNLOAD_TASK_PRIORITY_RECOVER,
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task_id=f"shot-analysis:task-set:{owner_id}:attempt:{attempt}",
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)
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else:
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analyze_custom_segment_video.apply_async(
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args=[owner_id, attempt],
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queue=CeleryQueue.GEN_SHOT_ANALYSIS.value,
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countdown=0,
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priority=settings.DOWNLOAD_TASK_PRIORITY_RECOVER,
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task_id=f"shot-analysis:segment:{owner_id}:attempt:{attempt}",
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)
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results["enqueue_success"] = results.get("enqueue_success", 0) + 1
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except Exception:
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logger.exception(
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"恢复投递拆镜分析失败。owner_type=%s owner_id=%s attempt=%s",
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owner_type,
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owner_id,
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attempt,
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)
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results["enqueue_failed"] = results.get("enqueue_failed", 0) + 1
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return {"checked": len(task_sets) + len(segments), "results": results}
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