842 lines
33 KiB
Python
842 lines
33 KiB
Python
from __future__ import annotations
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import uuid
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from datetime import datetime, timezone
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from typing import Any
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from fastapi import HTTPException
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from app.config import settings
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from sqlalchemy import String, cast, func, or_, select
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.enums.shot_replicate import (
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ModuleCodeEnum,
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ShotAnalysisStatusEnum,
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ShotSegmentAnalysisStatusEnum,
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ShotSegmentReplicateStatusEnum,
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ShotReplicateLogEventEnum,
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ShotSegmentSourceModeEnum,
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ShotSplitStatusEnum,
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ShotTaskSetStatusEnum,
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)
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from app.models.module_generation_project import ModuleGenerationProject
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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.models.user import User
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from app.schemas.shot_replicate import (
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ShotAISuggestionOut,
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ShotSegmentDeleteOut,
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ShotSegmentDetailOut,
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ShotSegmentListOut,
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ShotReanalyzeOut,
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ShotSegmentOut,
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ShotSplitByAIOut,
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ShotSplitByAIRequest,
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ShotSplitCustomOut,
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ShotSplitCustomRequest,
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ShotTaskSetCreate,
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ShotTaskSetDetailOut,
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ShotTaskSetListOut,
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ShotTaskSetOut,
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)
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from app.services.module_generation_log_service import log_module_event_file
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from app.services.resource_accounting_service import SOURCE_MODEL_SHOT_SEGMENT, soft_delete_resources_by_source
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from app.services.upload_video_asset_service import (
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build_time_node,
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validate_split_range,
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validate_upload_video_asset,
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)
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from app.tasks.celery_app import celery_app
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from app.utils.id_gen import generate_id
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MODULE = ModuleCodeEnum.SHOT_REPLICATE.value
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def _now() -> datetime:
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return datetime.now(timezone.utc)
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def _normalize_suggestions(value: Any) -> list[dict[str, Any]]:
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if not isinstance(value, list):
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return []
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normalized: list[dict[str, Any]] = []
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for idx, item in enumerate(value, start=1):
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if not isinstance(item, dict):
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continue
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start = item.get("拆镜开始秒")
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end = item.get("拆镜结束秒")
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try:
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start_f = float(start)
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end_f = float(end)
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except Exception:
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continue
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if start_f < 0 or end_f <= start_f:
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continue
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normalized.append(
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{
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"index": idx,
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"start_second": start_f,
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"end_second": end_f,
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"duration_seconds": round(end_f - start_f, 3),
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"time_node": str(item.get("拆镜时间节点") or build_time_node(start_f, end_f)),
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"content": str(item.get("对应时间节点内的内容") or "无"),
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"category": str(item.get("分类") or "无"),
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"audience": str(item.get("受众人群") or "无"),
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"raw": item,
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}
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)
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return normalized
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def _task_set_to_out(task_set: ShotReplicateTaskSet, user_name: str | None = None) -> ShotTaskSetOut:
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data = ShotTaskSetOut.model_validate(task_set)
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data.user_name = user_name
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return data
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def _task_set_to_detail_out(task_set: ShotReplicateTaskSet, user_name: str | None = None) -> ShotTaskSetDetailOut:
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suggestions = [ShotAISuggestionOut(**{k: v for k, v in item.items() if k != "raw"}) for item in _normalize_suggestions(task_set.ai_suggestion_json)]
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base = ShotTaskSetDetailOut.model_validate(task_set)
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base.user_name = user_name
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base.ai_suggestions = suggestions
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return base
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def _segment_to_out(segment: ShotReplicateSegment, project: ModuleGenerationProject | None = None) -> ShotSegmentOut:
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data = ShotSegmentOut.model_validate(segment)
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data.segment_name = f"片段{segment.segment_index}"
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if project:
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data.module_project_title = project.title
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data.module_project_status = project.status
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data.module_project_current_step_code = project.current_step_code
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return data
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def _segment_to_detail_out(segment: ShotReplicateSegment, project: ModuleGenerationProject | None = None) -> ShotSegmentDetailOut:
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data = ShotSegmentDetailOut.model_validate(segment)
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data.segment_name = f"片段{segment.segment_index}"
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if project:
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data.module_project_title = project.title
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data.module_project_status = project.status
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data.module_project_current_step_code = project.current_step_code
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return data
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async def get_task_set_for_user(
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db: AsyncSession,
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*,
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task_set_id: str,
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user: User,
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for_update: bool = False,
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) -> ShotReplicateTaskSet:
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query = select(ShotReplicateTaskSet).where(
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ShotReplicateTaskSet.id == task_set_id,
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ShotReplicateTaskSet.deleted_at.is_(None),
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)
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if not user.is_admin:
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query = query.where(ShotReplicateTaskSet.user_id == user.id)
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if for_update:
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query = query.with_for_update()
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result = await db.execute(query.limit(1))
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task_set = result.scalar_one_or_none()
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if not task_set:
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raise HTTPException(status_code=404, detail="拆镜总任务集不存在")
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return task_set
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async def get_segment_for_user(
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db: AsyncSession,
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*,
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segment_id: str,
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user: User,
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for_update: bool = False,
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) -> ShotReplicateSegment:
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query = select(ShotReplicateSegment).where(
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ShotReplicateSegment.id == segment_id,
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ShotReplicateSegment.deleted_at.is_(None),
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)
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if not user.is_admin:
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query = query.where(ShotReplicateSegment.user_id == user.id)
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if for_update:
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query = query.with_for_update()
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result = await db.execute(query.limit(1))
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segment = result.scalar_one_or_none()
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if not segment:
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raise HTTPException(status_code=404, detail="拆镜片段不存在")
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return segment
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async def create_task_set(db: AsyncSession, *, current_user: User, req: ShotTaskSetCreate) -> ShotReplicateTaskSet:
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if req.idempotency_key:
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existing_result = await db.execute(
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select(ShotReplicateTaskSet).where(
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ShotReplicateTaskSet.user_id == current_user.id,
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ShotReplicateTaskSet.idempotency_key == req.idempotency_key,
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ShotReplicateTaskSet.deleted_at.is_(None),
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).limit(1)
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)
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existing = existing_result.scalar_one_or_none()
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if existing:
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return existing
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asset = validate_upload_video_asset(req.video_url, req.video_duration_seconds)
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task_set = ShotReplicateTaskSet(
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id=generate_id(),
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user_id=current_user.id,
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title=req.title or "拆镜复刻任务",
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video_url=asset.url,
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video_path=str(asset.path),
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video_duration_seconds=asset.duration_seconds,
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status=ShotTaskSetStatusEnum.PENDING_ANALYSIS.value,
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analysis_status=ShotAnalysisStatusEnum.PENDING.value,
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split_status=ShotSplitStatusEnum.NONE.value,
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segment_count=0,
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completed_segment_count=0,
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failed_segment_count=0,
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idempotency_key=req.idempotency_key,
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)
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db.add(task_set)
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await db.flush()
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log_module_event_file(
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module=MODULE,
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event_type="SHOT_TASK_SET_CREATED",
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project_id=task_set.id,
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user_id=task_set.user_id,
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message="创建拆镜总任务集",
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detail={
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"task_set_id": task_set.id,
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"title": task_set.title,
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"video_url": task_set.video_url,
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"video_path": task_set.video_path,
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"video_duration_seconds": task_set.video_duration_seconds,
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"idempotency_key": task_set.idempotency_key,
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},
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)
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return task_set
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def _user_name_filter_subquery(value: str):
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"""后台按用户名筛选时使用的子查询。
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只在传入 user_name 时查询 users 表；keyword 不再关联 users，避免后台关键词搜索扩大查询范围。
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"""
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like = f"%{value.strip()}%"
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return select(User.id).where(User.username.ilike(like))
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async def _user_name_map_by_ids(db: AsyncSession, user_ids: set[str]) -> dict[str, str | None]:
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"""一次性查询当前页涉及的用户，避免列表逐条查询用户表。"""
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if not user_ids:
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return {}
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result = await db.execute(select(User.id, User.username).where(User.id.in_(list(user_ids))))
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return {user_id: username for user_id, username in result.all()}
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async def list_task_sets(
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db: AsyncSession,
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*,
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current_user: User,
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status: str | None = None,
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analysis_status: str | None = None,
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split_status: str | None = None,
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keyword: str | None = None,
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user_id: str | None = None,
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user_name: str | None = None,
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created_start: datetime | None = None,
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created_end: datetime | None = None,
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page: int = 1,
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page_size: int = 20,
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) -> ShotTaskSetListOut:
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"""
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拆镜总任务集列表查询。
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性能策略：
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1. 主列表不 join User，避免 count/list 复杂化。
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2. 管理员按 user_name 搜索时使用 IN (SELECT users.id ...) 子查询；keyword 不查询 users 表。
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3. 当前页数据取出后，再按 user_id 去重批量查 user_name，用于后台渲染。
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"""
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query = select(ShotReplicateTaskSet).where(ShotReplicateTaskSet.deleted_at.is_(None))
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if not current_user.is_admin:
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query = query.where(ShotReplicateTaskSet.user_id == current_user.id)
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else:
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if user_id and user_id.strip():
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query = query.where(ShotReplicateTaskSet.user_id == user_id.strip())
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if user_name and user_name.strip():
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query = query.where(ShotReplicateTaskSet.user_id.in_(_user_name_filter_subquery(user_name)))
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if created_start:
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query = query.where(ShotReplicateTaskSet.created_at >= created_start)
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if created_end:
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query = query.where(ShotReplicateTaskSet.created_at <= created_end)
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if status:
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query = query.where(ShotReplicateTaskSet.status == status)
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if analysis_status:
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query = query.where(ShotReplicateTaskSet.analysis_status == analysis_status)
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if split_status:
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query = query.where(ShotReplicateTaskSet.split_status == split_status)
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if keyword and keyword.strip():
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like = f"%{keyword.strip()}%"
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conditions = [
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ShotReplicateTaskSet.id.ilike(like),
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ShotReplicateTaskSet.title.ilike(like),
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ShotReplicateTaskSet.original_video_content.ilike(like),
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ShotReplicateTaskSet.original_video_category.ilike(like),
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ShotReplicateTaskSet.original_video_audience.ilike(like),
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cast(ShotReplicateTaskSet.ai_suggestion_json, String).ilike(like),
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]
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query = query.where(or_(*conditions))
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total_result = await db.execute(select(func.count()).select_from(query.subquery()))
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total = int(total_result.scalar() or 0)
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result = await db.execute(
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query.order_by(ShotReplicateTaskSet.created_at.desc())
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.offset((page - 1) * page_size)
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.limit(page_size)
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)
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task_sets = list(result.scalars().unique().all())
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user_name_map: dict[str, str | None] = {}
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if current_user.is_admin:
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user_ids = {task_set.user_id for task_set in task_sets if task_set.user_id}
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user_name_map = await _user_name_map_by_ids(db, user_ids)
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return ShotTaskSetListOut(
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total=total,
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page=page,
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page_size=page_size,
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items=[
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_task_set_to_out(
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task_set,
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user_name_map.get(task_set.user_id) if current_user.is_admin and task_set.user_id else None,
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)
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for task_set in task_sets
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],
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)
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async def task_set_detail(db: AsyncSession, *, current_user: User, task_set_id: str) -> ShotTaskSetDetailOut:
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task_set = await get_task_set_for_user(db, task_set_id=task_set_id, user=current_user)
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user_result = await db.execute(select(User.username).where(User.id == task_set.user_id).limit(1))
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return _task_set_to_detail_out(task_set, user_result.scalar_one_or_none())
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async def _next_segment_index(db: AsyncSession, task_set_id: str) -> int:
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result = await db.execute(
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select(func.max(ShotReplicateSegment.segment_index)).where(
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ShotReplicateSegment.task_set_id == task_set_id,
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ShotReplicateSegment.deleted_at.is_(None),
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)
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)
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return int(result.scalar() or 0) + 1
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async def refresh_task_set_split_summary(db: AsyncSession, task_set_id: str) -> None:
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task_set_result = await db.execute(select(ShotReplicateTaskSet).where(ShotReplicateTaskSet.id == task_set_id).with_for_update().limit(1))
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task_set = task_set_result.scalar_one_or_none()
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if not task_set:
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return
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result = await db.execute(
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select(ShotReplicateSegment).where(
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ShotReplicateSegment.task_set_id == task_set_id,
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ShotReplicateSegment.deleted_at.is_(None),
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)
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)
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segments = list(result.scalars().all())
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total = len(segments)
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completed = len([s for s in segments if s.split_status == ShotSplitStatusEnum.COMPLETED.value])
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failed = len([s for s in segments if s.split_status == ShotSplitStatusEnum.FAILED.value])
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task_set.segment_count = total
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task_set.completed_segment_count = completed
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task_set.failed_segment_count = failed
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if total <= 0:
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task_set.split_status = ShotSplitStatusEnum.NONE.value
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if task_set.analysis_status == ShotAnalysisStatusEnum.COMPLETED.value:
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task_set.status = ShotTaskSetStatusEnum.ANALYSIS_COMPLETED.value
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return
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old_status = task_set.status
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old_split_status = task_set.split_status
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if completed == total:
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task_set.split_status = ShotSplitStatusEnum.COMPLETED.value
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task_set.status = ShotTaskSetStatusEnum.SPLIT_COMPLETED.value
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elif failed == total:
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task_set.split_status = ShotSplitStatusEnum.FAILED.value
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task_set.status = ShotTaskSetStatusEnum.FAILED.value
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elif failed > 0:
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task_set.split_status = ShotSplitStatusEnum.FAILED.value
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task_set.status = ShotTaskSetStatusEnum.PARTIAL_FAILED.value
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else:
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task_set.split_status = ShotSplitStatusEnum.PROCESSING.value
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task_set.status = ShotTaskSetStatusEnum.SPLITTING.value
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if old_status != task_set.status or old_split_status != task_set.split_status:
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log_module_event_file(
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module=MODULE,
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event_type="SHOT_SPLIT_STATUS_CHANGED",
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project_id=task_set.id,
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user_id=task_set.user_id,
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message="拆镜总任务集拆分状态变更",
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detail={
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"task_set_id": task_set.id,
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"from_status": old_status,
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"to_status": task_set.status,
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"from_split_status": old_split_status,
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"to_split_status": task_set.split_status,
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"segment_count": total,
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"completed_segment_count": completed,
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"failed_segment_count": failed,
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},
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)
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async def create_segments_by_ai(
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db: AsyncSession,
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*,
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current_user: User,
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task_set_id: str,
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req: ShotSplitByAIRequest,
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) -> ShotSplitByAIOut:
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task_set = await get_task_set_for_user(db, task_set_id=task_set_id, user=current_user, for_update=True)
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if task_set.analysis_status != ShotAnalysisStatusEnum.COMPLETED.value:
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raise HTTPException(status_code=400, detail="原视频分析未完成，不能按 AI 建议拆镜")
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suggestions = _normalize_suggestions(task_set.ai_suggestion_json)
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if not suggestions:
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raise HTTPException(status_code=400, detail="当前没有可用 AI 建议拆镜方案，请使用自定义拆镜")
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if req.selected_indices:
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selected_set = {int(x) for x in req.selected_indices}
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suggestions = [item for item in suggestions if int(item["index"]) in selected_set]
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if not suggestions:
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raise HTTPException(status_code=400, detail="selected_indices 没有匹配到可用 AI 建议")
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old_result = await db.execute(
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select(ShotReplicateSegment).where(
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ShotReplicateSegment.task_set_id == task_set.id,
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ShotReplicateSegment.source_mode == ShotSegmentSourceModeEnum.AI_SUGGESTION.value,
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ShotReplicateSegment.deleted_at.is_(None),
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)
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)
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old_segments = list(old_result.scalars().all())
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if old_segments and not req.replace_existing:
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raise HTTPException(status_code=409, detail="已存在 AI 建议拆镜片段，如需重拆请传 replace_existing=true")
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if old_segments and req.replace_existing:
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now = _now()
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for segment in old_segments:
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segment.deleted_at = now
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created: list[ShotReplicateSegment] = []
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next_index = await _next_segment_index(db, task_set.id)
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for item in suggestions:
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start, end, duration = validate_split_range(
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start_second=item["start_second"],
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end_second=item["end_second"],
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video_duration_seconds=task_set.video_duration_seconds,
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)
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segment = ShotReplicateSegment(
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id=generate_id(),
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task_set_id=task_set.id,
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user_id=task_set.user_id,
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segment_index=next_index,
|
|
source_mode=ShotSegmentSourceModeEnum.AI_SUGGESTION.value,
|
|
start_second=start,
|
|
end_second=end,
|
|
duration_seconds=duration,
|
|
time_node=build_time_node(start, end),
|
|
split_status=ShotSplitStatusEnum.PENDING.value,
|
|
analysis_status=ShotSegmentAnalysisStatusEnum.NOT_REQUIRED.value,
|
|
replicate_status=ShotSegmentReplicateStatusEnum.NOT_STARTED.value,
|
|
original_video_content=task_set.original_video_content,
|
|
original_video_category=task_set.original_video_category,
|
|
original_video_audience=task_set.original_video_audience,
|
|
segment_content=item.get("content"),
|
|
segment_category=item.get("category"),
|
|
segment_audience=item.get("audience"),
|
|
ai_suggestion_json=item.get("raw") or item,
|
|
split_enqueued_at=_now(),
|
|
split_celery_task_id=f"shot-split:{uuid.uuid4().hex}",
|
|
)
|
|
db.add(segment)
|
|
created.append(segment)
|
|
next_index += 1
|
|
|
|
task_set.status = ShotTaskSetStatusEnum.SPLITTING.value
|
|
task_set.split_status = ShotSplitStatusEnum.PROCESSING.value
|
|
await db.flush()
|
|
await refresh_task_set_split_summary(db, task_set.id)
|
|
await db.flush()
|
|
|
|
log_module_event_file(
|
|
module=MODULE,
|
|
event_type="SHOT_SPLIT_BY_AI_SUBMITTED",
|
|
project_id=task_set.id,
|
|
user_id=task_set.user_id,
|
|
message="按 AI 建议创建拆镜片段",
|
|
detail={
|
|
"task_set_id": task_set.id,
|
|
"selected_indices": req.selected_indices,
|
|
"replace_existing": req.replace_existing,
|
|
"created_segment_count": len(created),
|
|
"segment_ids": [segment.id for segment in created],
|
|
},
|
|
)
|
|
|
|
return ShotSplitByAIOut(
|
|
task_set_id=task_set.id,
|
|
status=task_set.status,
|
|
split_status=task_set.split_status,
|
|
created_segment_count=len(created),
|
|
segments=[_segment_to_out(segment) for segment in created],
|
|
)
|
|
|
|
|
|
async def create_custom_segment(
|
|
db: AsyncSession,
|
|
*,
|
|
current_user: User,
|
|
task_set_id: str,
|
|
req: ShotSplitCustomRequest,
|
|
) -> ShotSplitCustomOut:
|
|
task_set = await get_task_set_for_user(db, task_set_id=task_set_id, user=current_user, for_update=True)
|
|
start, end, duration = validate_split_range(
|
|
start_second=req.start_second,
|
|
end_second=req.end_second,
|
|
video_duration_seconds=task_set.video_duration_seconds,
|
|
)
|
|
next_index = await _next_segment_index(db, task_set.id)
|
|
segment = ShotReplicateSegment(
|
|
id=generate_id(),
|
|
task_set_id=task_set.id,
|
|
user_id=task_set.user_id,
|
|
segment_index=next_index,
|
|
source_mode=ShotSegmentSourceModeEnum.CUSTOM.value,
|
|
start_second=start,
|
|
end_second=end,
|
|
duration_seconds=duration,
|
|
time_node=build_time_node(start, end),
|
|
split_status=ShotSplitStatusEnum.PENDING.value,
|
|
analysis_status=ShotSegmentAnalysisStatusEnum.PENDING.value,
|
|
replicate_status=ShotSegmentReplicateStatusEnum.NOT_STARTED.value,
|
|
split_enqueued_at=_now(),
|
|
split_celery_task_id=f"shot-split:{uuid.uuid4().hex}",
|
|
)
|
|
db.add(segment)
|
|
task_set.status = ShotTaskSetStatusEnum.SPLITTING.value
|
|
task_set.split_status = ShotSplitStatusEnum.PROCESSING.value
|
|
await db.flush()
|
|
await refresh_task_set_split_summary(db, task_set.id)
|
|
await db.flush()
|
|
log_module_event_file(
|
|
module=MODULE,
|
|
event_type="SHOT_SPLIT_CUSTOM_SUBMITTED",
|
|
project_id=task_set.id,
|
|
step_id=segment.id,
|
|
user_id=task_set.user_id,
|
|
message="按用户自定义时间创建拆镜片段",
|
|
detail={
|
|
"task_set_id": task_set.id,
|
|
"segment_id": segment.id,
|
|
"start_second": start,
|
|
"end_second": end,
|
|
"duration_seconds": duration,
|
|
"time_node": segment.time_node,
|
|
},
|
|
)
|
|
return ShotSplitCustomOut(task_set_id=task_set.id, segment=_segment_to_out(segment))
|
|
|
|
|
|
async def enqueue_segment_split(segment_id: str, *, countdown: int | None = None, recover: bool = False) -> None:
|
|
if not celery_app:
|
|
return
|
|
from app.tasks.shot_replicate_tasks import split_one_segment
|
|
|
|
split_one_segment.apply_async(
|
|
args=[segment_id],
|
|
queue="gen_result_download",
|
|
countdown=countdown,
|
|
priority=settings.DOWNLOAD_TASK_PRIORITY_RECOVER if recover else settings.DOWNLOAD_TASK_PRIORITY_NORMAL,
|
|
)
|
|
|
|
|
|
async def list_segments(
|
|
db: AsyncSession,
|
|
*,
|
|
current_user: User,
|
|
task_set_id: str,
|
|
source_mode: str | None = None,
|
|
split_status: str | None = None,
|
|
analysis_status: str | None = None,
|
|
replicate_status: str | None = None,
|
|
page: int = 1,
|
|
page_size: int = 20,
|
|
) -> ShotSegmentListOut:
|
|
await get_task_set_for_user(db, task_set_id=task_set_id, user=current_user)
|
|
query = (
|
|
select(ShotReplicateSegment, ModuleGenerationProject)
|
|
.outerjoin(ModuleGenerationProject, ModuleGenerationProject.id == ShotReplicateSegment.module_project_id)
|
|
.where(
|
|
ShotReplicateSegment.task_set_id == task_set_id,
|
|
ShotReplicateSegment.deleted_at.is_(None),
|
|
)
|
|
)
|
|
if not current_user.is_admin:
|
|
query = query.where(ShotReplicateSegment.user_id == current_user.id)
|
|
if source_mode:
|
|
query = query.where(ShotReplicateSegment.source_mode == source_mode)
|
|
if split_status:
|
|
query = query.where(ShotReplicateSegment.split_status == split_status)
|
|
if analysis_status:
|
|
query = query.where(ShotReplicateSegment.analysis_status == analysis_status)
|
|
if replicate_status:
|
|
query = query.where(ShotReplicateSegment.replicate_status == replicate_status)
|
|
|
|
total_result = await db.execute(select(func.count()).select_from(query.subquery()))
|
|
total = int(total_result.scalar() or 0)
|
|
rows = await db.execute(
|
|
query.order_by(ShotReplicateSegment.segment_index.asc())
|
|
.offset((page - 1) * page_size)
|
|
.limit(page_size)
|
|
)
|
|
return ShotSegmentListOut(
|
|
total=total,
|
|
page=page,
|
|
page_size=page_size,
|
|
items=[_segment_to_out(segment, project) for segment, project in rows.all()],
|
|
)
|
|
|
|
|
|
async def segment_detail(db: AsyncSession, *, current_user: User, segment_id: str) -> ShotSegmentDetailOut:
|
|
segment = await get_segment_for_user(db, segment_id=segment_id, user=current_user)
|
|
project: ModuleGenerationProject | None = None
|
|
if segment.module_project_id:
|
|
project_result = await db.execute(select(ModuleGenerationProject).where(ModuleGenerationProject.id == segment.module_project_id).limit(1))
|
|
project = project_result.scalar_one_or_none()
|
|
return _segment_to_detail_out(segment, project)
|
|
|
|
async def delete_segment(
|
|
db: AsyncSession,
|
|
*,
|
|
current_user: User,
|
|
segment_id: str,
|
|
) -> ShotSegmentDeleteOut:
|
|
"""软删除拆镜片段。
|
|
|
|
只释放用户容量账本记录，不删除 segment_video_path 指向的物理文件。
|
|
如果片段已创建复刻项目，则联动调用项目删除逻辑，但用户主动删除不退款；
|
|
项目仍有生成中任务时会拒绝删除，避免异步任务继续写回软删数据。
|
|
"""
|
|
query = select(ShotReplicateSegment).where(ShotReplicateSegment.id == segment_id)
|
|
if not current_user.is_admin:
|
|
query = query.where(ShotReplicateSegment.user_id == current_user.id)
|
|
result = await db.execute(query.with_for_update().limit(1))
|
|
segment = result.scalar_one_or_none()
|
|
if not segment:
|
|
raise HTTPException(status_code=404, detail="拆镜片段不存在")
|
|
|
|
task_set_id = segment.task_set_id
|
|
module_project_id = segment.module_project_id
|
|
|
|
if segment.deleted_at is not None:
|
|
return ShotSegmentDeleteOut(
|
|
message="拆镜片段已删除",
|
|
segment_id=segment.id,
|
|
task_set_id=task_set_id,
|
|
deleted=True,
|
|
deleted_module_project_id=module_project_id,
|
|
released_size_bytes=0,
|
|
)
|
|
|
|
if segment.split_status == ShotSplitStatusEnum.PROCESSING.value:
|
|
raise HTTPException(status_code=400, detail="当前拆镜片段正在切割处理中，暂不能删除")
|
|
if segment.analysis_status == ShotSegmentAnalysisStatusEnum.PROCESSING.value:
|
|
raise HTTPException(status_code=400, detail="当前拆镜片段正在分析处理中，暂不能删除")
|
|
if segment.replicate_status == ShotSegmentReplicateStatusEnum.PROCESSING.value:
|
|
raise HTTPException(status_code=400, detail="当前拆镜片段关联的复刻流程正在处理中，暂不能删除")
|
|
|
|
deleted_at = _now()
|
|
released_size_bytes = await soft_delete_resources_by_source(
|
|
db,
|
|
source_model=SOURCE_MODEL_SHOT_SEGMENT,
|
|
source_ids=[segment.id],
|
|
deleted_at=deleted_at,
|
|
)
|
|
|
|
deleted_module_project_id: str | None = None
|
|
if module_project_id:
|
|
from app.services.shot_replicate_flow_service import delete_shot_replicate_project
|
|
|
|
project_delete_out = await delete_shot_replicate_project(
|
|
db,
|
|
current_user=current_user,
|
|
project_id=module_project_id,
|
|
refund_unfinished=False,
|
|
)
|
|
deleted_module_project_id = project_delete_out.project_id
|
|
released_size_bytes += int(project_delete_out.released_size_bytes or 0)
|
|
|
|
segment.deleted_at = deleted_at
|
|
segment.replicate_status = (
|
|
ShotSegmentReplicateStatusEnum.NOT_STARTED.value
|
|
if not deleted_module_project_id
|
|
else ShotSegmentReplicateStatusEnum.FAILED.value
|
|
)
|
|
|
|
await refresh_task_set_split_summary(db, task_set_id)
|
|
await db.flush()
|
|
|
|
log_module_event_file(
|
|
module=MODULE,
|
|
event_type="SHOT_SEGMENT_DELETED",
|
|
project_id=task_set_id,
|
|
step_id=segment.id,
|
|
user_id=segment.user_id,
|
|
message="软删除拆镜片段并释放用户容量账本记录",
|
|
detail={
|
|
"segment_id": segment.id,
|
|
"task_set_id": task_set_id,
|
|
"module_project_id": module_project_id,
|
|
"deleted_module_project_id": deleted_module_project_id,
|
|
"released_size_bytes": released_size_bytes,
|
|
"physical_file_deleted": False,
|
|
"refund": False,
|
|
},
|
|
)
|
|
|
|
return ShotSegmentDeleteOut(
|
|
message="拆镜片段已删除",
|
|
segment_id=segment.id,
|
|
task_set_id=task_set_id,
|
|
deleted=True,
|
|
deleted_module_project_id=deleted_module_project_id,
|
|
released_size_bytes=int(released_size_bytes or 0),
|
|
)
|
|
|
|
|
|
|
|
async def prepare_reanalyze_task_set(
|
|
db: AsyncSession,
|
|
*,
|
|
current_user: User,
|
|
task_set_id: str,
|
|
force: bool = False,
|
|
reason: str | None = None,
|
|
) -> ShotReanalyzeOut:
|
|
"""重置原视频分析状态，供 API 重新投递 Celery。"""
|
|
task_set = await get_task_set_for_user(db, task_set_id=task_set_id, user=current_user, for_update=True)
|
|
if task_set.analysis_status == ShotAnalysisStatusEnum.PROCESSING.value:
|
|
log_module_event_file(
|
|
module=MODULE,
|
|
event_type=ShotReplicateLogEventEnum.TASK_SET_REANALYZE_REJECTED.value,
|
|
project_id=task_set.id,
|
|
user_id=task_set.user_id,
|
|
message="原视频分析正在处理中，拒绝再次分析",
|
|
detail={"task_set_id": task_set.id, "analysis_status": task_set.analysis_status, "reason": reason},
|
|
event_status="rejected",
|
|
)
|
|
raise HTTPException(status_code=409, detail="原视频分析正在处理中，不能重复投递")
|
|
if task_set.analysis_status == ShotAnalysisStatusEnum.COMPLETED.value and not force:
|
|
raise HTTPException(status_code=409, detail="原视频分析已完成，如确需重跑请传 force=true")
|
|
if force:
|
|
active_segments_result = await db.execute(
|
|
select(func.count())
|
|
.select_from(ShotReplicateSegment)
|
|
.where(
|
|
ShotReplicateSegment.task_set_id == task_set.id,
|
|
ShotReplicateSegment.deleted_at.is_(None),
|
|
)
|
|
)
|
|
if int(active_segments_result.scalar() or 0) > 0:
|
|
raise HTTPException(status_code=409, detail="当前总任务集已存在拆镜片段，不能强制重跑原视频分析")
|
|
|
|
task_set.status = ShotTaskSetStatusEnum.PENDING_ANALYSIS.value
|
|
task_set.analysis_status = ShotAnalysisStatusEnum.PENDING.value
|
|
task_set.analysis_error_message = None
|
|
task_set.original_video_content = None
|
|
task_set.original_video_category = None
|
|
task_set.original_video_audience = None
|
|
task_set.ai_suggestion_json = None
|
|
task_set.analysis_raw_json = None
|
|
task_set.analysis_result_json = None
|
|
await db.flush()
|
|
log_module_event_file(
|
|
module=MODULE,
|
|
event_type=ShotReplicateLogEventEnum.TASK_SET_REANALYZE_RECEIVED.value,
|
|
project_id=task_set.id,
|
|
user_id=task_set.user_id,
|
|
message="原视频再次分析已重置状态",
|
|
detail={"task_set_id": task_set.id, "force": force, "reason": reason, "video_url": task_set.video_url},
|
|
)
|
|
return ShotReanalyzeOut(
|
|
message="原视频再次分析任务已准备投递",
|
|
task_set_id=task_set.id,
|
|
segment_id=None,
|
|
analysis_status=task_set.analysis_status,
|
|
celery_task_name="shot_replicate.analyze_original_video",
|
|
)
|
|
|
|
|
|
async def prepare_reanalyze_segment(
|
|
db: AsyncSession,
|
|
*,
|
|
current_user: User,
|
|
segment_id: str,
|
|
force: bool = False,
|
|
reason: str | None = None,
|
|
) -> ShotReanalyzeOut:
|
|
"""重置自定义切片视频分析状态，供 API 重新投递 Celery。"""
|
|
segment = await get_segment_for_user(db, segment_id=segment_id, user=current_user, for_update=True)
|
|
if segment.split_status != ShotSplitStatusEnum.COMPLETED.value:
|
|
raise HTTPException(status_code=409, detail="当前片段还未切割完成，不能再次分析")
|
|
if not segment.segment_video_url:
|
|
raise HTTPException(status_code=409, detail="当前片段缺少 segment_video_url，不能再次分析")
|
|
if segment.analysis_status == ShotSegmentAnalysisStatusEnum.PROCESSING.value:
|
|
log_module_event_file(
|
|
module=MODULE,
|
|
event_type=ShotReplicateLogEventEnum.SEGMENT_REANALYZE_REJECTED.value,
|
|
project_id=segment.task_set_id,
|
|
step_id=segment.id,
|
|
user_id=segment.user_id,
|
|
message="切片视频分析正在处理中，拒绝再次分析",
|
|
detail={"segment_id": segment.id, "analysis_status": segment.analysis_status, "reason": reason},
|
|
event_status="rejected",
|
|
)
|
|
raise HTTPException(status_code=409, detail="切片视频分析正在处理中，不能重复投递")
|
|
if segment.analysis_status == ShotSegmentAnalysisStatusEnum.COMPLETED.value and not force:
|
|
raise HTTPException(status_code=409, detail="切片视频分析已完成，如确需重跑请传 force=true")
|
|
if segment.source_mode != ShotSegmentSourceModeEnum.CUSTOM.value and not force:
|
|
raise HTTPException(status_code=409, detail="AI 建议片段默认无需单独分析，如确需重跑请传 force=true")
|
|
|
|
segment.analysis_status = ShotSegmentAnalysisStatusEnum.PENDING.value
|
|
segment.analysis_error_message = None
|
|
segment.analysis_json = None
|
|
segment.original_video_content = None
|
|
segment.original_video_category = None
|
|
segment.original_video_audience = None
|
|
segment.segment_content = None
|
|
segment.segment_category = None
|
|
segment.segment_audience = None
|
|
await db.flush()
|
|
log_module_event_file(
|
|
module=MODULE,
|
|
event_type=ShotReplicateLogEventEnum.SEGMENT_REANALYZE_RECEIVED.value,
|
|
project_id=segment.task_set_id,
|
|
step_id=segment.id,
|
|
user_id=segment.user_id,
|
|
message="切片视频再次分析已重置状态",
|
|
detail={"segment_id": segment.id, "task_set_id": segment.task_set_id, "force": force, "reason": reason, "video_url": segment.segment_video_url},
|
|
)
|
|
return ShotReanalyzeOut(
|
|
message="切片视频再次分析任务已准备投递",
|
|
task_set_id=segment.task_set_id,
|
|
segment_id=segment.id,
|
|
analysis_status=segment.analysis_status,
|
|
celery_task_name="shot_replicate.analyze_custom_segment_video",
|
|
)
|