feat(digital-human): 对口型生成弹窗增加计时器

- 对口型生成弹窗loading状态显示已用时（MM:SS格式，每秒更新）
- 使用useState+useEffect+setInterval实现计时，组件卸载时clearInterval防内存泄漏
- 取消生成或生成完成/失败时停止并重置计时器
- 样式与现有灰色提示文字风格一致

alembic/versions/085_atom_clip_caption_embedding.py

@@ -1,33 +0,0 @@
-"""asset_atom_clips 新增 caption/embedding 字段（#2035 语义标签增强）
-
-Revision ID: 085_atom_clip_caption_embedding
-Revises: 084_lipsync_jobs_style
-Create Date: 2026-09-25
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "085_atom_clip_caption_embedding"
-down_revision = "084_lipsync_jobs_style"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # caption: 中文画面描述（10-30字）
-    op.add_column(
-        "asset_atom_clips",
-        sa.Column("caption", sa.Text(), nullable=True),
-    )
-    # embedding: caption 对应的向量（豆包 embedding 接口返回，JSON 存 float 数组）
-    op.add_column(
-        "asset_atom_clips",
-        sa.Column("embedding", sa.JSON(), nullable=True),
-    )
-
-
-def downgrade() -> None:
-    op.drop_column("asset_atom_clips", "embedding")
-    op.drop_column("asset_atom_clips", "caption")

apps/api/app/api/router.py

@@ -8,7 +8,6 @@ from app.api.routes.chunked_upload import router as chunked_upload_router
 from app.api.routes.classification_jobs import router as classification_jobs_router
 from app.api.routes.clips_standalone import router as clips_standalone_router
 from app.api.routes.cover_templates import router as cover_templates_router
-from app.api.routes.drafts_standalone import router as drafts_standalone_router
 from app.api.routes.duplication import router as duplication_router
 from app.api.routes.feature_flags import router as feature_flags_router
 from app.api.routes.generation_cover import router as generation_cover_router
@@ -20,8 +19,7 @@ from app.api.routes.health import router as health_check_router
 from app.api.routes.ingest_jobs import router as ingest_jobs_router
 from app.api.routes.internal_render import router as internal_render_router
 from app.api.routes.lipsync import router as lipsync_router
-from app.api.routes.points import router as points_router
-from app.api.routes.points import usage_router
+from app.api.routes.points import points_router, usage_router
 from app.api.routes.projects import router as projects_router
 from app.api.routes.scripts import router as scripts_router
 from app.api.routes.scripts_ai import router as scripts_ai_router
@@ -43,19 +41,6 @@ api_router = APIRouter(prefix="/api/v1")
 health_router = APIRouter()
 health_router.include_router(health_check_router)
 
-# ── /api/health 别名：部分前端/探针把 health 放在 /api 前缀下 ──────────────
-# 原来 /health 在根路径；额外加一个 /api/health 别名避免 404。
-api_health_router = APIRouter(prefix="/api")
-api_health_router.include_router(health_check_router)
-health_router.include_router(api_health_router)
-
-# ── 旧前端路径别名（无需 template_id 路径参数）────────────────────────────
-# /api/v1/clips/from-assets 已有 clips_standalone；此处额外挂 /api/v1/editor/*，
-# 解决前端调 /api/v1/editor/clips/from-assets 和 /api/v1/editor/drafts 的 404。
-editor_legacy_router = APIRouter(prefix="/editor", tags=["Editor Legacy Alias"])
-editor_legacy_router.include_router(clips_standalone_router)
-editor_legacy_router.include_router(drafts_standalone_router)
-
 api_router.include_router(
     auth_router,
     tags=["Auth"],
@@ -184,9 +169,6 @@ api_router.include_router(
     prefix="/templates/{template_id}/editor",
     tags=["TemplateEditor"],
 )
-api_router.include_router(
-    editor_legacy_router,
-)
 api_router.include_router(
     tts_router,
     prefix="/tts",

apps/api/app/api/routes/drafts_standalone.py

@@ -1,102 +0,0 @@
-"""独立的草稿端点（不依赖 template_id 路径参数，兼容旧前端路径）.
-
-提供以下别名端点，与 /api/v1/templates/{template_id}/editor/draft 功能一致：
-- GET  /api/v1/editor/drafts   获取草稿详情（template_id 从 query/body/默认模板兜底）
-- PUT  /api/v1/editor/drafts   更新草稿（兼容前端 useDraftAutoSave 调用）
-
-根因：前端 useDraftAutoSave 调用 /api/v1/editor/drafts（复数、无 template_id），
-与后端以 template_id 为路径参数的设计不一致，导致 404 并触发 10s timeout。
-本模块参照 clips_standalone.py 的模式，通过默认模板兜底复用 draft.py 的核心逻辑。
-"""
-
-from __future__ import annotations
-
-import logging
-
-from app.auth import AuthenticatedUser, get_current_user
-from app.dependencies import get_db_session
-from app.services.edit_plan_service import EditPlanService
-from app.services.edit_template_service import EditTemplateService
-from fastapi import APIRouter, Depends, HTTPException, Query, status
-from sqlalchemy.orm import Session
-
-from ._default_template import get_or_create_default_template_id
-from .templates_editor.dependencies import resolve_draft_plan_id
-from .templates_editor.draft import get_editor_draft, update_editor_draft
-from .templates_editor.schemas import EditorDraftResponse, EditorUpdateRequest
-
-logger = logging.getLogger(__name__)
-router = APIRouter(tags=["Editor Legacy Alias"])
-
-
-def _resolve_editor_services(db: Session) -> tuple[EditTemplateService, EditPlanService]:
-    return EditTemplateService(db), EditPlanService(db)
-
-
-def _resolve_template_id(
-    template_id: str | None,
-    db: Session,
-    current_user: AuthenticatedUser,
-) -> str:
-    """解析 template_id：query/body 优先，否则兜底默认模板。"""
-    tid = (template_id or "").strip()
-    if tid:
-        return tid
-    user_id = str(current_user.user.id)
-    tid = get_or_create_default_template_id(db, user_id)
-    if not tid:
-        raise HTTPException(
-            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-            detail="无法自动创建默认模板，请刷新页面重试",
-        )
-    return tid
-
-
-@router.get("/drafts", response_model=EditorDraftResponse)
-def get_editor_drafts_alias(
-    template_id: str | None = Query(default=None, description="模板ID，不传则兜底默认模板"),
-    db: Session = Depends(get_db_session),
-    current_user: AuthenticatedUser = Depends(get_current_user),
-) -> EditorDraftResponse:
-    """获取草稿详情（复数路径别名，兼容旧前端调用）。"""
-    tid = _resolve_template_id(template_id, db, current_user)
-    services = _resolve_editor_services(db)
-    plan_id = resolve_draft_plan_id(
-        template_id=tid,
-        services=services,
-        current_user=current_user,
-        db=db,
-        auto_create_default=False,
-    )
-    return get_editor_draft(
-        template_id=tid,
-        plan_id=plan_id,
-        services=services,
-        _=current_user,
-    )
-
-
-@router.put("/drafts", response_model=EditorDraftResponse)
-def update_editor_drafts_alias(
-    req: EditorUpdateRequest,
-    template_id: str | None = Query(default=None, description="模板ID，不传则兜底默认模板"),
-    db: Session = Depends(get_db_session),
-    current_user: AuthenticatedUser = Depends(get_current_user),
-) -> EditorDraftResponse:
-    """更新草稿（复数路径别名，兼容前端 useDraftAutoSave 调用）。"""
-    tid = _resolve_template_id(template_id, db, current_user)
-    services = _resolve_editor_services(db)
-    plan_id = resolve_draft_plan_id(
-        template_id=tid,
-        services=services,
-        current_user=current_user,
-        db=db,
-        auto_create_default=False,
-    )
-    return update_editor_draft(
-        template_id=tid,
-        req=req,
-        plan_id=plan_id,
-        services=services,
-        _=current_user,
-    )

apps/api/app/api/routes/generation_cover.py

@@ -76,7 +76,10 @@ class GenerateCoverResponse(BaseModel):
 # ── Route ────────────────────────────────────────────────────────────────
 
 
-def _select_best_frame_from_snapshots(snapshots: list[dict], plan_id: str) -> str:
+
+def _select_best_frame_from_snapshots(
+    snapshots: list[dict], plan_id: str
+) -> str:
     """从 MediaKit 抽帧结果中，通过质量评分选出最佳帧。
 
     降级策略：cv2 不可用或评分失败时，返回第一帧。
@@ -229,10 +232,7 @@ def _persist_cover_frame(
 
 
 def _get_task_video_url(db: Session, task_id: str) -> Optional[str]:
-    """从 GenerationTask 关联的 GeneratedVideo 中获取视频 storage_key / URL.
-
-    #2028: awaiting_cover 状态下 GeneratedVideo 尚未入库，兜底从 task.extra_meta.rendered_output.file_url 读取。
-    """
+    """从 GenerationTask 关联的 GeneratedVideo 中获取视频 storage_key / URL."""
     try:
         video_repo = get_generated_video_repository(db)
         use_case = ListGeneratedVideosByTaskUseCase(video_repo)
@@ -241,20 +241,6 @@ def _get_task_video_url(db: Session, task_id: str) -> Optional[str]:
             return getattr(videos[0], "file_url", "") or ""
     except Exception:
         logger.warning("[封面生成] 获取任务视频失败: task_id=%s", task_id, exc_info=True)
-    # awaiting_cover 兜底：从 extra_meta.rendered_output 取
-    try:
-        task_repo = SQLAlchemyGenerationTaskRepository(db)
-        task = task_repo.get(task_id)
-        if task is not None:
-            _status = task.status.value if hasattr(task.status, "value") else str(task.status)
-            if _status == "awaiting_cover":
-                _meta = getattr(task, "extra_meta", {}) or {}
-                _ro = _meta.get("rendered_output") or {}
-                _url = _ro.get("file_url") or ""
-                if _url:
-                    return _url
-    except Exception:
-        logger.warning("[封面生成] awaiting_cover 兜底读取失败: task_id=%s", task_id, exc_info=True)
     return None
 
 

apps/api/app/api/routes/generation_preview.py

@@ -650,26 +650,11 @@ def get_preview_generation_task(
     if not getattr(task, "is_preview", False):
         raise HTTPException(status_code=404, detail=f"预览任务 {task_id} 不存在")
 
-    # 查询生成的视频（取第一个）。
-    # #2024: 渲染完成后先进入 awaiting_cover（未入成品库），此时预览也应可见，
-    # 从 extra_meta["rendered_output"] 读取视频 URL。
+    # 查询生成的视频（取第一个）
     generated_videos = []
     status_val = task.status.value if hasattr(task.status, "value") else str(task.status)
     if status_val == "completed":
         list_use_case = ListGeneratedVideosByTaskUseCase(generated_video_repository)
         generated_videos = list_use_case.execute(task_id)
-    elif status_val == "awaiting_cover":
-        # 用 extra_meta 中的渲染信息组装一个轻量视频对象给前端预览播放
-        _meta = getattr(task, "extra_meta", {}) or {}
-        _ro = _meta.get("rendered_output") or {}
-        if _ro.get("file_url"):
-
-            class _PreviewVideo:
-                def __init__(self, ro):
-                    self.file_url = ro.get("file_url", "")
-                    self.duration = float(ro.get("duration") or 0.0)
-                    self.file_size = int(ro.get("file_size") or 0)
-
-            generated_videos = [_PreviewVideo(_ro)]
 
     return _to_preview_response(task, generated_videos=generated_videos)

apps/api/app/api/routes/generation_tasks.py

@@ -31,8 +31,6 @@ from app.schemas.generation_task import (
     BatchGenerationTaskResponse,
     ConfirmGenerationRequest,
     CreateGenerationTaskRequest,
-    FinalizeGenerationRequest,
-    FinalizeGenerationResponse,
     GenerationTaskResponse,
     ListGenerationTasksResponse,
 )
@@ -46,37 +44,6 @@ from packages.application import (
     ListGeneratedVideosByTaskUseCase,
 )
 from packages.domain.smart_match import smart_select_assets
-
-# #2035：文案关键词 → 素材分类 映射表（用于 smart_match category_match 维度）
-# AssetClassification 枚举: scenic / product / person / animal / food / tech / sport / music / other
-_CATEGORY_KEYWORDS: dict[str, set[str]] = {
-    "scenic": {"风景", "自然", "山水", "大海", "天空", "日落", "日出", "森林", "城市", "建筑", "夜景", "街道", "公园", "景区", "旅行", "旅游", "户外"},
-    "product": {"产品", "商品", "展示", "演示", "开箱", "评测", "好物", "推荐", "种草", "购物", "电商", "带货", "品牌", "广告", "包装"},
-    "person": {"人物", "人物采访", "对话", "说话", "讲解", "演讲", "采访", "聊天", "开会", "工作", "办公室", "团队", "员工", "老板", "女性", "男性", "美女", "帅哥"},
-    "animal": {"动物", "宠物", "狗", "猫", "鸟", "鱼", "马", "牛", "羊", "野生动物", "动物园"},
-    "food": {"美食", "食物", "餐饮", "餐厅", "做饭", "烹饪", "厨房", "菜品", "饮料", "水果", "甜点", "蛋糕", "咖啡", "茶", "零食", "吃"},
-    "tech": {"科技", "数码", "电脑", "手机", "屏幕", "软件", "APP", "互联网", "AI", "人工智能", "机器人", "办公", "程序员", "代码", "屏幕录制"},
-    "sport": {"运动", "健身", "跑步", "篮球", "足球", "游泳", "瑜伽", "户外", "锻炼", "体育", "比赛", "球场"},
-    "music": {"音乐", "歌曲", "演唱会", "乐器", "唱歌", "跳舞", "舞蹈", "MV", "演出", "乐队", "钢琴", "吉他", "节奏"},
-}
-
-
-def _infer_expected_categories(script_tags: set[str] | None) -> set[str] | None:
-    """从文案标签集合推断期望的素材分类（可能命中多个）。标签为空返回 None。"""
-    if not script_tags:
-        return None
-    matched: set[str] = set()
-    for cat, kws in _CATEGORY_KEYWORDS.items():
-        for tag in script_tags:
-            tag.lower()
-            for kw in kws:
-                if kw in tag or tag in kw:
-                    matched.add(cat)
-                    break
-            if cat in matched:
-                break
-    return matched or None
-
 from packages.middleware.points_gate import points_gate
 
 logger = logging.getLogger(__name__)
@@ -165,11 +132,10 @@ def _ensure_library_has_ready_video_assets(assets) -> None:
 def _select_assets_from_library(
     assets: list,
     mode: str,
-    count: int = 0,
+    count: int,
     rng=None,
     script_tags: list | None = None,
     tag_names_by_id: dict | None = None,
-    db=None,
 ) -> list[str]:
     """根据选取模式从素材库中选取 ready 状态的视频素材 ID。
 
@@ -190,42 +156,6 @@ def _select_assets_from_library(
     if not ready_video_assets:
         return []
 
-    # #2035：加载片段级 AI 标签，供叙事模式 AI 加权和 smart 模式语义匹配使用。
-    # 失败降级为空（不影响选片主流程）。
-    clip_ai_tags_by_asset: dict[str, list[dict]] = {}
-    ai_tags_by_asset: dict[str, dict] = {}  # asset_id → 聚合后的 ai_tags dict（取首个有 has_text 的片段；合并 scene/objects/action 去重）
-    try:
-        if db is not None:
-            from packages.adapters.sqlalchemy_impl.models import AssetAtomClipModel
-            ready_ids = [a.id for a in ready_video_assets]
-            clip_rows = (
-                db.query(AssetAtomClipModel.asset_id, AssetAtomClipModel.ai_tags)
-                .filter(AssetAtomClipModel.asset_id.in_(ready_ids))
-                .filter(AssetAtomClipModel.ai_tags.isnot(None))
-                .all()
-            )
-            agg: dict[str, dict] = {}
-            for asset_id, ai_tags in clip_rows:
-                if not isinstance(ai_tags, dict):
-                    continue
-                clip_ai_tags_by_asset.setdefault(asset_id, []).append(ai_tags)
-                # 聚合：合并 scene/objects/action 去重
-                agg.setdefault(asset_id, {"scene": [], "objects": [], "action": [], "shot": "", "has_text": False})
-                for key in ("scene", "objects", "action"):
-                    for v in ai_tags.get(key) or []:
-                        v = str(v).strip()
-                        if v and v not in agg[asset_id][key]:
-                            agg[asset_id][key].append(v)
-                if ai_tags.get("has_text") is True:
-                    agg[asset_id]["has_text"] = True
-                if not agg[asset_id]["shot"] and ai_tags.get("shot"):
-                    agg[asset_id]["shot"] = ai_tags["shot"]
-            ai_tags_by_asset = agg
-    except Exception:  # noqa: BLE001
-        logger.warning("[选片] 加载片段 AI 标签失败，降级不使用语义匹配", exc_info=True)
-        clip_ai_tags_by_asset = {}
-        ai_tags_by_asset = {}
-
     # 叙事模式（#1970 PR3）：文案标签命中池优先；无任何命中时完全降级为现有随机逻辑。
     if script_tags:
         from packages.domain.narrative_match import pick_narrative_assets
@@ -235,7 +165,6 @@ def _select_assets_from_library(
             ready_video_assets,
             script_tags=script_tags,
             tag_names_by_id=tag_names_by_id,
-            clip_ai_tags_by_asset=clip_ai_tags_by_asset,
             limit=limit,
             rng=rng,
         )
@@ -246,18 +175,7 @@ def _select_assets_from_library(
         # 评分维度：质量分(40%) + 时长适配(30%) + 新鲜度(20%) + 未使用加分(10%)
         # 排序注入随机噪声（#1743）：同分素材每次选出不同组合，从素材组合层面降重
         limit = count if count > 0 else None
-        # #2035：给 smart_select_assets 传入文案标签和 AI 标签映射，启用语义维度
-        norm_script = {t.strip().lower() for t in (script_tags or []) if t and t.strip()}
-        expected_categories = _infer_expected_categories(norm_script)
-        results = smart_select_assets(
-            ready_video_assets,
-            limit=limit,
-            kind="video",
-            rng=rng,
-            script_tags=norm_script if norm_script else None,
-            ai_tags_by_asset=ai_tags_by_asset or None,
-            expected_categories=expected_categories,
-        )
+        results = smart_select_assets(ready_video_assets, limit=limit, kind="video", rng=rng)
         return [r.asset.id for r in results]
 
     # 默认 all 模式：返回全部 ready 视频素材
@@ -476,7 +394,6 @@ def create_generation_task(
                 count=request.asset_select_count,
                 script_tags=narrative_script_tags or None,
                 tag_names_by_id=_tag_index,
-                db=db,
             )
     elif project_id and not resolved_asset_ids and (request.asset_select_mode in ("smart",) or narrative_script_tags):
         # 项目级模式：未指定 asset_ids 且选择了 smart 模式（或叙事模式按标签匹配）时自动选取
@@ -491,7 +408,6 @@ def create_generation_task(
                 count=request.asset_select_count,
                 script_tags=narrative_script_tags or None,
                 tag_names_by_id=_tag_index,
-                db=db,
             )
             if not resolved_asset_ids:
                 raise HTTPException(
@@ -975,14 +891,8 @@ def confirm_generation(
     if source_task.project_id:
         check_project_access(source_task.project_id, authenticated_user.user.id, project_repository)
 
-    # 3. 如果预览任务已完成渲染（completed 或 awaiting_cover），检查分辨率一致性后复用产物（秒出）。
-    # #2024: 渲染完成先进入 awaiting_cover（等 Step5 finalize 入库），
-    # confirm 时不再直接 finalize——仍创建 is_preview=False 的正式任务，复用预览渲染产物。
-    _preview_done = getattr(source_task, "is_preview", False) and source_task.status.value in (
-        "completed",
-        "awaiting_cover",
-    )
-    if _preview_done:
+    # 3. 如果预览任务已完成，检查分辨率一致性后复用产物（秒出）
+    if source_task.is_completed and getattr(source_task, "is_preview", False):
         # 校验请求的分辨率是否与预览实际渲染的分辨率一致
         req_w = request.output_width or 0
         req_h = request.output_height or 0
@@ -997,25 +907,13 @@ def confirm_generation(
                 confirmed_title_config = dict(getattr(source_task, "title_config", {}) or {})
                 confirmed_title_config["text"] = request.custom_title.strip()
 
-            # #2024: mark_confirmed 会把 is_preview 翻转为 False、同步标题/分辨率/封面，
-            # 但不再自动 mark_completed——任务停留在 awaiting_cover，等待用户 Step5 选封面后调 finalize。
             source_task.mark_confirmed(
                 cover_url=request.cover_url,
                 output_width=request.output_width,
                 output_height=request.output_height,
                 title_config=confirmed_title_config,
             )
-            # 若预览任务此时是 completed（历史数据/旧 worker），回退到 awaiting_cover 统一流程
-            if source_task.status.value == "completed":
-                try:
-                    from packages.domain.generation_task import GenerationTaskStatus
-
-                    source_task.status = GenerationTaskStatus.AWAITING_COVER
-                    source_task.completed_at = None
-                except Exception:
-                    pass
             generation_task_repository.update(source_task)
-            db.commit()
 
             # 同步标题到 EditPlan.config
             # #1970：确认生成复用预览计划，dedup_enabled 沿用计划已有值，不在此覆盖
@@ -1028,7 +926,7 @@ def confirm_generation(
                 )
 
             logger.info(
-                "[确认生成] 复用预览产物（等待 finalize）: task_id=%s, user_id=%s",
+                "[确认生成] 复用预览产物: task_id=%s, user_id=%s",
                 task_id,
                 authenticated_user.user.id,
             )
@@ -1097,67 +995,6 @@ def confirm_generation(
     )
 
 
-@router.post("/tasks/{task_id}/finalize", response_model=FinalizeGenerationResponse)
-def finalize_generation_task(
-    task_id: str,
-    request: FinalizeGenerationRequest,
-    authenticated_user: AuthenticatedUser = Depends(get_current_user),
-    generation_task_repository: Any = Depends(get_generation_task_repository),
-    generated_video_repository: Any = Depends(get_generated_video_repository),
-    project_repository: Any = Depends(get_project_repository),
-    storage_service: OSSStorageService = Depends(get_storage_service),
-    db: Session = Depends(get_db_session),
-) -> FinalizeGenerationResponse:
-    """#2024: Step5 点「完成」时调用——将 awaiting_cover 状态的任务正式入库+绑定封面。
-
-    - 任务必须处于 awaiting_cover 状态（渲染+上传已完成、封面候选已就绪）。
-    - cover_url 为空则使用任务自动截帧/智能封面；非空则绑定为最终封面。
-    - 幂等：已 finalize 的任务直接返回已有视频记录。
-    - 成功后任务推进到 completed，返回成品视频 ID + 可播放 URL。
-    """
-    from app.services.generation_finalize_service import (
-        GenerationFinalizeError,
-        GenerationFinalizeService,
-    )
-
-    task = generation_task_repository.get(task_id)
-    if task is None:
-        raise HTTPException(status_code=404, detail=f"GenerationTask {task_id} not found")
-    if task.project_id:
-        check_project_access(task.project_id, authenticated_user.user.id, project_repository)
-
-    service = GenerationFinalizeService(db)
-    try:
-        video = service.finalize_task(
-            task_id=task_id,
-            user_id=authenticated_user.user.id,
-            cover_url=request.cover_url or None,
-            custom_title=(request.custom_title or "").strip() or None,
-        )
-    except GenerationFinalizeError as e:
-        raise HTTPException(status_code=e.status_code, detail=str(e)) from e
-
-    try:
-        download_url = storage_service.get_download_url(video.file_url, expires_seconds=86400)
-    except Exception:
-        download_url = video.file_url
-    return FinalizeGenerationResponse(
-        video_id=video.id,
-        project_id=getattr(video, "project_id", "") or "",
-        name=getattr(video, "name", "") or "",
-        file_size=int(getattr(video, "file_size", 0) or 0),
-        duration=float(getattr(video, "duration", 0.0) or 0.0),
-        thumbnail_url=video.thumbnail_url or "",
-        cover_url=video.thumbnail_url or "",
-        file_url=download_url,
-        width=int(getattr(video, "width", 0) or 0),
-        height=int(getattr(video, "height", 0) or 0),
-        fps=float(getattr(video, "fps", 0.0) or 0.0),
-        status="success",
-        is_duplicate=bool(getattr(video, "is_duplicate", False)),
-    )
-
-
 @router.get("/tasks", response_model=ListGenerationTasksResponse)
 def list_generation_tasks(
     authenticated_user: AuthenticatedUser = Depends(get_current_user),
@@ -1205,44 +1042,6 @@ def list_generation_results(
     for item in items:
         download_url = storage_service.get_download_url(item.file_url, expires_seconds=86400)
         responses.append(_to_generated_video_response(item, download_url=download_url))
-
-    # #2024/#2028: awaiting_cover 状态下 GeneratedVideo 尚未入库，
-    # 从 extra_meta["rendered_output"] 合成一条轻量视频响应，供前端预览与智能封面使用。
-    status_val = task.status.value if hasattr(task.status, "value") else str(task.status)
-    if not responses and status_val == "awaiting_cover":
-        _meta = getattr(task, "extra_meta", {}) or {}
-        _ro = _meta.get("rendered_output") or {}
-        _file_url = _ro.get("file_url") or ""
-        if _file_url:
-            if _file_url.startswith("http"):
-                _download = _file_url
-            else:
-                try:
-                    _download = storage_service.get_download_url(_file_url, expires_seconds=86400)
-                except Exception:
-                    _download = _file_url
-            _name = _ro.get("name") or ""
-            if not _name:
-                _name = f"generated-{task_id[:8]}"
-            responses.append(
-                GeneratedVideoResponse(
-                    id=f"preview-{task_id}",
-                    project_id=getattr(task, "project_id", "") or "",
-                    generation_task_id=task_id,
-                    name=_name,
-                    file_url=_file_url,
-                    file_size=int(_ro.get("file_size") or 0),
-                    duration=float(_ro.get("duration") or 0.0),
-                    thumbnail_url=_ro.get("thumbnail_url") or getattr(task, "cover_url", "") or "",
-                    width=int(_ro.get("width") or 0),
-                    height=int(_ro.get("height") or 0),
-                    fps=float(_ro.get("fps") or 0.0),
-                    mode=_ro.get("mode", ""),
-                    download_url=_download,
-                    created_at=getattr(task, "updated_at", None) or getattr(task, "created_at", None),
-                )
-            )
-
     return ListGeneratedVideosResponse(items=responses)
 
 

apps/api/app/api/routes/task_center.py

@@ -63,8 +63,6 @@ def _generation_step(task) -> str:
         return "等待 Worker 执行"
     if s == "running":
         return "正在生成成片"
-    if s == "awaiting_cover":
-        return "等待确认封面"
     if s == "completed":
         return "生成完成"
     if s == "failed":
@@ -131,7 +129,7 @@ def _validate_status(status: str | None) -> str | None:
     """校验状态值合法性。"""
     if status is None:
         return None
-    valid = {"pending", "running", "awaiting_cover", "completed", "failed", "cancelled"}
+    valid = {"pending", "running", "completed", "failed", "cancelled"}
     if status not in valid:
         raise HTTPException(
             status_code=400,
@@ -153,9 +151,7 @@ def _clamp_page_size(page_size: int) -> int:
 
 @router.get("/tasks", response_model=ListTasksResponse)
 def list_user_tasks(
-    status: str | None = Query(
-        None, description="按状态筛选：pending/running/awaiting_cover/completed/failed/cancelled"
-    ),
+    status: str | None = Query(None, description="按状态筛选：pending/running/completed/failed/cancelled"),
     task_type: str | None = Query(None, description="按任务类型筛选：generation/ingest"),
     page: int = Query(1, ge=1, description="页码，从1开始"),
     page_size: int = Query(DEFAULT_PAGE_SIZE, ge=1, le=MAX_PAGE_SIZE, description="每页数量"),
@@ -252,9 +248,7 @@ def retry_task_by_id(
 @router.get("/projects/{project_id}/tasks", response_model=ListProjectTasksResponse)
 def list_project_tasks(
     project_id: str,
-    status: str | None = Query(
-        None, description="按状态筛选：pending/running/awaiting_cover/completed/failed/cancelled"
-    ),
+    status: str | None = Query(None, description="按状态筛选：pending/running/completed/failed/cancelled"),
     task_type: str | None = Query(None, description="按任务类型筛选：generation/ingest"),
     page: int = Query(1, ge=1, description="页码，从1开始"),
     page_size: int = Query(DEFAULT_PAGE_SIZE, ge=1, le=MAX_PAGE_SIZE, description="每页数量"),

apps/api/app/api/routes/templates_editor/clips.py

@@ -682,50 +682,17 @@ def create_clips_from_assets_editor(
     # 素材 metadata 中缓存的场景切换点（由后台 MediaKit SceneChange 检测写入）：
     # 有缓存时片段起点从随机镜头段中选取（不同片段来自不同镜头），无缓存回退随机起点
     asset_scene_points: dict[str, list[float]] = {}
-    invalid_asset_ids: list[str] = []
-    valid_asset_ids: list[str] = []
     for asset_id in unique_asset_ids:
         asset = asset_repo.get(asset_id)
-        if asset is None:
-            logger.warning("from-assets 素材不存在或已删除，跳过: asset_id=%s", asset_id)
-            invalid_asset_ids.append(asset_id)
-            continue
-        _dur = float(getattr(asset, "duration", 0.0) or 0.0)
-        if _dur <= 0:
-            # 素材时长缺失（刚上传/分析未完成）或为0，跳过该素材——避免按兜底时长分配无效片段。
-            # 若所有素材都无效，在下面统一抛 400。
-            logger.warning("from-assets 素材时长缺失或为0，跳过: asset_id=%s", asset_id)
-            invalid_asset_ids.append(asset_id)
-            continue
-        valid_asset_ids.append(asset_id)
-        asset_durations[asset_id] = _dur
-        # 计算 smart_match 综合评分，用于候选排序
-        try:
+        if asset and hasattr(asset, "duration"):
+            asset_durations[asset_id] = float(asset.duration or 0.0)
+            # 计算 smart_match 综合评分，用于候选排序
             smart_score, _ = score_asset(asset)
             asset_smart_scores[asset_id] = smart_score
-        except Exception:
-            asset_smart_scores[asset_id] = 0.0
-        # 读取场景切换点缓存（新素材未检测过时为 None，走随机起点兜底）
-        try:
+            # 读取场景切换点缓存（新素材未检测过时为 None，走随机起点兜底）
             cached_points = extract_scene_points_from_metadata(getattr(asset, "metadata", None))
             if cached_points:
                 asset_scene_points[asset_id] = cached_points
-        except Exception:
-            pass
-    if invalid_asset_ids:
-        logger.info(
-            "from-assets %d 个素材无效（时长缺失/不存在，已跳过）: %s",
-            len(invalid_asset_ids),
-            ",".join(invalid_asset_ids[:5]),
-        )
-    # 所有素材都无效（刚上传未分析完）→ 400 让前端稍后重试，而不是用兜底时长产生错乱片段
-    if not valid_asset_ids:
-        raise HTTPException(
-            status_code=status.HTTP_400_BAD_REQUEST,
-            detail="素材尚未完成分析，请稍后重试",
-        )
-    # 后续分配素材时只在 valid_asset_ids 里挑选
-    unique_asset_ids = valid_asset_ids
     logger.info(
         "from-assets 场景缓存命中: %d/%d 个素材有场景切换点",
         len(asset_scene_points),

apps/api/app/schemas/generation_task.py

@@ -13,33 +13,6 @@ class ConfirmGenerationRequest(BaseModel):
     custom_title: str = Field(default="", description="用户自定义标题文本，非空时同步到任务和编辑计划")
 
 
-class FinalizeGenerationRequest(BaseModel):
-    """Step5 点「完成」请求体：用户选定封面后，正式将视频入成品库。"""
-
-    cover_url: str = Field(
-        default="", description="用户选定的封面图片 URL；为空则使用任务默认 cover_url（自动截帧/智能封面）"
-    )
-    custom_title: str = Field(default="", description="用户自定义成片标题，非空时覆盖 rendered_output.name")
-
-
-class FinalizeGenerationResponse(BaseModel):
-    """finalize 响应：返回新创建的成品库视频信息。"""
-
-    video_id: str = Field(description="新创建的成品视频 ID")
-    project_id: str = Field(default="", description="成品所属项目 ID")
-    name: str = Field(default="", description="成片名称")
-    file_size: int = Field(default=0, description="文件大小（字节）")
-    duration: float = Field(default=0.0, description="时长（秒）")
-    thumbnail_url: str = Field(default="", description="最终绑定的缩略图/封面 URL")
-    cover_url: str = Field(default="", description="最终绑定的封面 URL")
-    file_url: str = Field(default="", description="成品视频下载 URL")
-    width: int = Field(default=0)
-    height: int = Field(default=0)
-    fps: float = Field(default=0.0)
-    status: str = Field(default="success", description="success=新建成功；already_finalized=幂等返回已有记录")
-    is_duplicate: bool = Field(default=False, description="是否被判定为与历史成片重复")
-
-
 class CreateGenerationTaskRequest(BaseModel):
     """创建生成任务请求。
 

apps/api/app/services/edit_plan_service.py

@@ -999,35 +999,26 @@ class EditPlanService:
 
         source_bgm_config: dict = {}
         source_plan = self.get_plan(source_plan_id)
-        # #2034：读取源 plan 的 dedup_enabled 决定变体是否注入视觉/像素扰动
-        # 默认 True；关了则保留节奏模板+BGM差异化，但跳过 visual/pixel 扰动
-        _dedup_enabled = True
         if source_plan and source_plan.config:
             source_bgm_config = source_plan.config.get("bgm", {}) or {}
-            _dedup_enabled = bool(source_plan.config.get("dedup_enabled", True))
         variant_seeds_for_bgm = [rng.randint(0, 999999) for _ in range(count)]
         bgm_pool_assignments = allocate_bgm_pool_for_variants(source_bgm_config, variant_seeds_for_bgm)
 
         def _build_variant_config_update(idx: int) -> dict:
-            """构建单个变体的 config 更新（节奏模板/BGM/视觉/像素扰动）。
-
-            #2034：dedup_enabled=False 时跳过 visual_perturbation/pixel_perturbation，
-            保留 rhythm_template 和 BGM 池分配（合理的多变体差异，不属于降重扰动）。
-            """
+            """构建单个变体的 config 更新（节奏模板/BGM/视觉/像素扰动）。"""
             upd: dict = {}
-            if _dedup_enabled:
-                try:
-                    perturbation = generate_visual_perturbation(rng)
-                    if idx == 0:
-                        perturbation["hflip"] = False
-                    upd["visual_perturbation"] = perturbation
-                except Exception:
-                    logger.exception("变体 %d 视觉扰动生成失败（不阻断）", idx)
-                try:
-                    pixel_pert = generate_pixel_perturbation(rng)
-                    upd["pixel_perturbation"] = pixel_pert
-                except Exception:
-                    logger.exception("变体 %d 像素扰动生成失败（不阻断）", idx)
+            try:
+                perturbation = generate_visual_perturbation(rng)
+                if idx == 0:
+                    perturbation["hflip"] = False
+                upd["visual_perturbation"] = perturbation
+            except Exception:
+                logger.exception("变体 %d 视觉扰动生成失败（不阻断）", idx)
+            try:
+                pixel_pert = generate_pixel_perturbation(rng)
+                upd["pixel_perturbation"] = pixel_pert
+            except Exception:
+                logger.exception("变体 %d 像素扰动生成失败（不阻断）", idx)
             rt = rhythm_templates_for_variants[idx] if idx < len(rhythm_templates_for_variants) else None
             if rt is not None:
                 upd["rhythm_template"] = rt

apps/api/app/services/generation_finalize_service.py

@@ -1,142 +0,0 @@
-"""视频生成任务 finalize 服务（#2024）。
-
-Worker 渲染+上传完成后不再自动入库，标记为 awaiting_cover；用户在 Step5 选好封面
-点「完成」时由 API 调用本服务：创建 GeneratedVideo 成品库记录（复用 worker 预计算
-的查重结果）、绑定封面、推进任务到 completed。
-
-与 AI 数字人 ``ai_avatar_render_service.finalize_job`` 模式一致，
-只是走 GenerationTask 而非 AiAvatarRenderJob。
-"""
-
-from __future__ import annotations
-
-import logging
-from datetime import UTC, datetime
-from typing import Optional
-
-from sqlalchemy.orm import Session
-
-logger = logging.getLogger(__name__)
-
-
-class GenerationFinalizeError(Exception):
-    """finalize 业务错误，code 供 API 层映射 HTTP 状态码。"""
-
-    def __init__(self, message: str, code: str = "FinalizeError", status_code: int = 400):
-        super().__init__(message)
-        self.code = code
-        self.status_code = status_code
-
-
-class GenerationFinalizeService:
-    def __init__(self, db: Session):
-        self.db = db
-
-    def finalize_task(
-        self,
-        task_id: str,
-        user_id: str,
-        cover_url: Optional[str] = None,
-        custom_title: Optional[str] = None,
-    ):
-        """执行 finalize：状态校验 → 幂等 → 绑定封面 → 入库 → 推进 completed。
-
-        Returns:
-            GeneratedVideo 领域对象
-        """
-        from packages.adapters.sqlalchemy_impl.generated_video_repository import (
-            SQLAlchemyGeneratedVideoRepository,
-        )
-        from packages.adapters.sqlalchemy_impl.generation_task_repository import (
-            SQLAlchemyGenerationTaskRepository,
-        )
-        from packages.adapters.sqlalchemy_impl.models import GeneratedVideoModel
-        from packages.application.generated_video_finalize import finalize_generated_video
-
-        task_repo = SQLAlchemyGenerationTaskRepository(self.db)
-        video_repo = SQLAlchemyGeneratedVideoRepository(self.db)
-
-        task = task_repo.get(task_id)
-        if task is None:
-            raise GenerationFinalizeError(f"任务 {task_id} 不存在", "TaskNotFound", 404)
-
-        # ── 幂等：已入库直接返回 ─────────────────────────────────
-        existing = self.db.query(GeneratedVideoModel).filter(GeneratedVideoModel.generation_task_id == task_id).first()
-        if existing is not None:
-            logger.info("[finalize] 幂等命中 task=%s video=%s", task_id, existing.id)
-            _changed = False
-            if cover_url and cover_url.strip() and existing.thumbnail_url != cover_url.strip():
-                existing.thumbnail_url = cover_url.strip()
-                task.cover_url = cover_url.strip()
-                _changed = True
-            if custom_title and custom_title.strip() and (getattr(existing, "name", "") or "") != custom_title.strip():
-                existing.name = custom_title.strip()
-                _changed = True
-            if _changed:
-                self.db.commit()
-            if task.status.value != "completed":
-                try:
-                    task.mark_completed(result_count=1)
-                    if cover_url and cover_url.strip():
-                        task.cover_url = cover_url.strip()
-                    task_repo.update(task)
-                    self.db.commit()
-                except Exception as e:
-                    logger.warning("[finalize] 幂等补 mark_completed 失败: %s", e)
-                    self.db.rollback()
-            return video_repo.get(existing.id)
-
-        # ── 状态校验 ─────────────────────────────────────────────
-        if task.status.value != "awaiting_cover":
-            raise GenerationFinalizeError(
-                f"任务当前状态 {task.status.value}，无法 finalize（需 awaiting_cover）",
-                "InvalidTaskStatus",
-                400,
-            )
-
-        # ── 封面 ─────────────────────────────────────────────────
-        effective_cover = (cover_url or "").strip() if cover_url else (task.cover_url or "").strip()
-
-        # ── 入库+查重（复用 worker 预计算结果） ──────────────────
-        try:
-            result = finalize_generated_video(
-                task=task,
-                session=self.db,
-                effective_cover_url=effective_cover,
-                custom_name=custom_title,
-            )
-        except ValueError as e:
-            raise GenerationFinalizeError(str(e), "RenderedOutputMissing", 400) from e
-
-        video_id = result["video_id"]
-
-        # 应用自定义标题
-        if custom_title and custom_title.strip():
-            try:
-                _v = self.db.query(GeneratedVideoModel).filter(GeneratedVideoModel.id == video_id).first()
-                if _v is not None:
-                    _v.name = custom_title.strip()
-                    self.db.flush()
-            except Exception:
-                logger.warning("[finalize] 更新标题失败: video_id=%s", video_id, exc_info=True)
-
-        # ── 推进任务 ─────────────────────────────────────────────
-        task.mark_completed(result_count=1)
-        task.cover_url = effective_cover
-        # 清理 rendered_output（体积较大，入库后不再需要）
-        meta = dict(task.extra_meta or {})
-        meta.pop("rendered_output", None)
-        task.extra_meta = meta
-        task.updated_at = datetime.now(UTC)
-        task_repo.update(task)
-        self.db.commit()
-
-        video = video_repo.get(video_id)
-        logger.info(
-            "[finalize] task=%s finalized -> video=%s cover=%s dup=%s",
-            task_id,
-            video_id,
-            bool(effective_cover),
-            result.get("is_duplicate", False),
-        )
-        return video

apps/web/src/api/client.ts

@@ -11,7 +11,7 @@ import { cancelProactiveRefresh, executeTokenRefresh } from "./auth/tokenRefresh
 // 创建 Axios 实例
 const apiClient = axios.create({
   baseURL: "/api/v1",
-  timeout: 30000, // 全局 30s；智能选片/封面生成/大文件上传接口单独覆盖更长超时
+  timeout: 10000,
   headers: {
     "Content-Type": "application/json",
   },

apps/web/src/api/cover-templates.ts

@@ -3,7 +3,7 @@
  * 后端路由: /api/v1/cover-templates
  */
 import apiClient from "./client"
-import type { CoverTemplate, CoverEditorConfig } from "@/pages/generate/types/cover"
+import type { CoverTemplate } from "@/pages/generate/types/cover"
 
 export interface CoverTemplateListResponse {
   items: CoverTemplate[]
@@ -12,7 +12,14 @@ export interface CoverTemplateListResponse {
 
 export interface CoverTemplateCreateRequest {
   name: string
-  config?: CoverEditorConfig
+  config?: {
+    background_enabled?: boolean
+    background_color?: string
+    portrait_enabled?: boolean
+    title_text?: string
+    subtitle_text?: string
+    mask_enabled?: boolean
+  }
 }
 
 export type CoverTemplateUpdateRequest = Partial<CoverTemplateCreateRequest>

apps/web/src/api/generation/finalize.ts

@@ -1,37 +0,0 @@
-import apiClient from "../client"
-
-/** #2024 Step5 「完成」入库 —— 将 awaiting_cover 任务正式写入成品库 */
-export interface FinalizeGenerationRequest {
-  /** 用户选定的封面图片 URL；为空则使用任务默认封面（自动截帧/智能封面） */
-  cover_url?: string
-  /** 用户自定义成片标题，非空时覆盖 rendered_output.name */
-  custom_title?: string
-}
-
-export interface FinalizeGenerationResponse {
-  video_id: string
-  project_id: string
-  name: string
-  file_size: number
-  duration: number
-  thumbnail_url: string
-  cover_url: string
-  file_url: string
-  width: number
-  height: number
-  fps: number
-  /** success=新建成功；already_finalized=幂等返回已有记录 */
-  status: string
-  is_duplicate: boolean
-}
-
-export const finalizeGeneration = async (
-  taskId: string,
-  params: FinalizeGenerationRequest = {},
-): Promise<FinalizeGenerationResponse> => {
-  const response = await apiClient.post<FinalizeGenerationResponse>(
-    `/generation/tasks/${taskId}/finalize`,
-    params,
-  )
-  return response.data
-}

apps/web/src/api/template-editor/editPlans.ts

@@ -6,20 +6,17 @@ import type { EditPlan, UpdateEditPlanRequest, GeneratedVideo } from "./types"
 
 /** 获取单个模板草稿 */
 export async function getEditPlan(templateId: string): Promise<EditPlan> {
-  const response = await apiClient.get(`/templates/${templateId}/editor`, { timeout: 30_000 })
+  const response = await apiClient.get(`/templates/${templateId}/editor`)
   return response.data
 }
 
-/** 更新模板草稿（支持传入 AbortSignal 用于自动保存竞态取消；超时 60s 防止大 config 写入失败） */
+/** 更新模板草稿（支持传入 AbortSignal 用于自动保存竞态取消） */
 export async function updateEditPlan(
   templateId: string,
   data: UpdateEditPlanRequest,
   signal?: AbortSignal,
 ): Promise<EditPlan> {
-  const response = await apiClient.put(`/templates/${templateId}/editor`, data, {
-    signal,
-    timeout: 60_000,
-  })
+  const response = await apiClient.put(`/templates/${templateId}/editor`, data, { signal })
   return response.data
 }
 

apps/web/src/components/cover/cover.css

@@ -1,563 +0,0 @@
-/**
- * 共享封面编辑器样式（智能剪辑 generate + AI数字人 ai-avatar 共用）
- * #2033：从 generate.css 抽取 xx-ce-* / xx-cover-template-* / xx-cover-modal-* 规则
- */
-
-.xx-cover-modal-toolbar {
-  display: flex;
-  gap: 8px;
-  margin-bottom: 20px;
-  flex-wrap: wrap;
-}
-
-.xx-cover-template-grid {
-  display: grid;
-  grid-template-columns: repeat(4, 1fr);
-  gap: 16px;
-}
-
-.xx-cover-template-card {
-  border: 2px solid var(--border-color);
-  border-radius: var(--radius-md);
-  overflow: hidden;
-  cursor: pointer;
-  transition: border-color 0.2s;
-}
-
-.xx-cover-template-card:hover {
-  border-color: var(--primary-color);
-}
-
-.xx-cover-template-card.selected {
-  border-color: var(--primary-color);
-  box-shadow: 0 0 0 2px rgba(102, 126, 234, 0.2);
-}
-
-.xx-cover-template-thumb {
-  aspect-ratio: 9/16;
-  background: linear-gradient(135deg, #f0f0f0, #e0e0e0);
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  font-size: 32px;
-  color: #ccc;
-  position: relative;
-}
-
-.xx-cover-template-info {
-  padding: 8px;
-}
-
-.xx-cover-template-name {
-  display: flex;
-  align-items: center;
-  gap: 4px;
-  font-size: 13px;
-  font-weight: 500;
-  margin-bottom: 2px;
-}
-
-.xx-cover-template-badge {
-  font-size: 11px;
-  color: #7c3aed;
-  background: rgba(124, 58, 237, 0.1);
-  padding: 1px 6px;
-  border-radius: 4px;
-  white-space: nowrap;
-}
-
-.xx-cover-template-date {
-  font-size: 11px;
-  color: var(--text-tertiary);
-  margin-bottom: 6px;
-}
-
-.xx-cover-template-actions {
-  display: flex;
-  gap: 4px;
-}
-
-.xx-ce-header {
-  margin-bottom: 16px;
-}
-
-.xx-ce-name-input {
-  width: 100%;
-  padding: 8px 12px;
-  border: 1px solid var(--border-color, #e5e7eb);
-  border-radius: var(--radius-sm, 6px);
-  font-size: 14px;
-  margin-bottom: 12px;
-  outline: none;
-}
-
-.xx-ce-name-input:focus {
-  border-color: #7c3aed;
-}
-
-.xx-ce-header-actions {
-  display: flex;
-  justify-content: flex-end;
-  gap: 8px;
-}
-
-.xx-ce-layout {
-  display: flex;
-  gap: 20px;
-  min-height: 500px;
-}
-
-.xx-ce-left {
-  width: 300px;
-  flex-shrink: 0;
-  max-height: 70vh;
-  overflow-y: auto;
-}
-
-.xx-ce-right {
-  flex: 1;
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  background: #f5f5f5;
-  border-radius: 8px;
-  min-height: 480px;
-}
-
-.xx-ce-section {
-  border: 1px solid var(--border-color, #e5e7eb);
-  border-radius: 6px;
-  margin-bottom: 8px;
-}
-
-.xx-ce-section-header {
-  padding: 10px 12px;
-  font-size: 13px;
-  font-weight: 600;
-  cursor: pointer;
-  display: flex;
-  align-items: center;
-  justify-content: space-between;
-  background: #f0f4ff;
-  user-select: none;
-}
-
-.xx-ce-section-header:hover {
-  background: #e8edf8;
-}
-
-.xx-ce-section-body {
-  padding: 12px;
-  font-size: 12px;
-  color: var(--text-secondary, #666);
-}
-
-.xx-ce-header-right {
-  display: flex;
-  align-items: center;
-  gap: 6px;
-}
-
-.xx-ce-status-text {
-  font-size: 11px;
-  font-weight: 400;
-  color: #3b82f6;
-}
-
-.xx-ce-row {
-  margin: 12px 0;
-}
-
-.xx-ce-label {
-  display: block;
-  font-size: 12px;
-  color: #374151;
-  margin-bottom: 4px;
-}
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-  font-size: 11px;
-  color: #9ca3af;
-  margin-top: 4px;
-}
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-  display: flex;
-  align-items: center;
-  justify-content: space-between;
-  margin-top: 8px;
-}
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-.xx-ce-switch-row {
-  display: flex;
-  align-items: center;
-  justify-content: space-between;
-}
-
-.xx-ce-switch-item {
-  margin-bottom: 12px;
-  padding-bottom: 8px;
-  border-bottom: 1px solid #f3f4f6;
-}
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-.xx-ce-switch-item:last-child {
-  border-bottom: none;
-  margin-bottom: 0;
-  padding-bottom: 0;
-}
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-.xx-ce-color-picker {
-  display: flex;
-  align-items: center;
-  gap: 6px;
-}
-
-.xx-ce-color-picker input[type="color"] {
-  width: 32px;
-  height: 24px;
-  padding: 0;
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-  border-radius: 4px;
-  cursor: pointer;
-  background: none;
-}
-
-.xx-ce-color-picker input[type="color"]::-webkit-color-swatch-wrapper {
-  padding: 1px;
-}
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-.xx-ce-color-picker input[type="color"]::-webkit-color-swatch {
-  border: none;
-  border-radius: 2px;
-}
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-.xx-ce-color-hex {
-  width: 70px;
-  padding: 2px 6px;
-  border: 1px solid #d1d5db;
-  border-radius: 4px;
-  font-size: 12px;
-  font-family: monospace;
-}
-
-.xx-ce-position {
-  display: flex;
-  gap: 8px;
-}
-
-.xx-ce-position .ant-input-number {
-  flex: 1;
-}
-
-.xx-ce-radio-group {
-  display: flex;
-  gap: 0;
-}
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-.xx-ce-radio-btn {
-  padding: 4px 14px;
-  font-size: 12px;
-  border: 1px solid #d1d5db;
-  background: #fff;
-  color: #374151;
-  cursor: pointer;
-  transition: all 0.15s;
-}
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-.xx-ce-radio-btn:first-child {
-  border-radius: 4px 0 0 4px;
-}
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-.xx-ce-radio-btn:last-child {
-  border-radius: 0 4px 4px 0;
-}
-
-.xx-ce-radio-btn + .xx-ce-radio-btn {
-  border-left: none;
-}
-
-.xx-ce-radio-btn.active {
-  background: #7c3aed;
-  color: #fff;
-  border-color: #7c3aed;
-}
-
-.xx-ce-radio-btn.active + .xx-ce-radio-btn {
-  border-left: 1px solid #d1d5db;
-}
-
-.xx-ce-font-dot {
-  display: inline-block;
-  width: 8px;
-  height: 8px;
-  border-radius: 50%;
-  margin-right: 6px;
-  vertical-align: middle;
-}
-
-.xx-ce-font-dot--preset {
-  background: #10b981;
-}
-
-.xx-ce-font-dot--system {
-  background: #3b82f6;
-}
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-.xx-ce-shadow-actions {
-  display: flex;
-  gap: 8px;
-  margin-top: 4px;
-}
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-.xx-ce-add-shadow-btn {
-  padding: 4px 10px;
-  font-size: 12px;
-  background: #7c3aed;
-  color: #fff;
-  border: none;
-  border-radius: 4px;
-  cursor: pointer;
-}
-
-.xx-ce-add-shadow-btn:hover {
-  background: #6d28d9;
-}
-
-.xx-ce-preset-shadow-btn {
-  padding: 4px 10px;
-  font-size: 12px;
-  background: #fff;
-  color: #374151;
-  border: 1px solid #d1d5db;
-  border-radius: 4px;
-  cursor: pointer;
-}
-
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-  margin-top: 8px;
-  padding: 8px;
-  background: #fafafa;
-  border-radius: 4px;
-  border: 1px solid #f0f0f0;
-}
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-.xx-ce-readonly-text {
-  padding: 6px 10px;
-  background: #eff6ff;
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-  font-size: 13px;
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-  position: absolute;
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-  background: #ef4444;
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-}
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-  position: absolute;
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-  border: 2px solid #333;
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-}
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-  width: 8px;
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-}
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-  z-index: 1;
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-  position: absolute;
-  top: 8px;
-  right: 8px;
-  width: 22px;
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-/* Text panel wrapper */
-.xx-ce-text-panel {
-  display: flex;
-  flex-direction: column;
-  gap: 8px;
-}
-
-/* Canvas base gradient layer (behind all elements) */
-.xx-ce-canvas-base {
-  position: absolute;
-  inset: 0;
-  z-index: 0;
-  background: linear-gradient(135deg, #1e3a8a 0%, #312e81 100%);
-}

apps/web/src/components/cover/index.ts

@@ -1,2 +0,0 @@
-export { useSharedCover } from "./useSharedCover"
-export type { UseSharedCoverOptions, UseSharedCoverReturn } from "./useSharedCover"

apps/web/src/components/cover/useSharedCover.ts

@@ -1,297 +0,0 @@
-/**
- * 共享封面选择 Hook（供智能剪辑 generate 与 AI 数字人 ai-avatar 共同使用）
- *
- * 能力：
- *  - 封面模板列表加载 / 选择 / 创建 / 编辑 / 删除（调用 /cover-templates 接口）
- *  - 自动生成封面按钮点击 → 调用调用方传入的 generateFn
- *  - 封面编辑器弹窗状态
- *  - 本地封面上传文件选择
- */
-import type React from "react"
-import { useCallback, useEffect, useRef, useState } from "react"
-import { message } from "antd"
-import type { CoverTemplate } from "@/pages/generate/types/cover"
-import {
-  fetchCoverTemplates,
-  createCoverTemplate,
-  updateCoverTemplate,
-  deleteCoverTemplate,
-} from "@/api/cover-templates"
-
-export interface UseSharedCoverOptions {
-  canGenerate: boolean
-  disabledHint?: string
-  generateFn: (templateId: string) => Promise<string | null | undefined>
-  initialTemplateId?: string
-}
-
-export interface UseSharedCoverReturn {
-  templates: CoverTemplate[]
-  templatesLoading: boolean
-  templatesError: string | null
-  selectedTemplateId: string
-  selectedTemplateName: string
-  handleSelectTemplate: (id: string) => void
-  reloadTemplates: () => void
-  showCoverSettings: boolean
-  setShowCoverSettings: (v: boolean) => void
-  showCoverEditor: boolean
-  setShowCoverEditor: (v: boolean) => void
-  editingTemplate: CoverTemplate | null
-  handleEditTemplate: (tpl: CoverTemplate) => void
-  handleCreateTemplate: () => void
-  handleSaveTemplate: (tpl: CoverTemplate) => Promise<void>
-  handleDeleteTemplate: (id: string) => Promise<void>
-  generating: boolean
-  generateAutoCover: () => Promise<void>
-  uploadInputRef: React.RefObject<HTMLInputElement>
-  handleUploadClick: () => void
-  handleFileInputChange: (e: React.ChangeEvent<HTMLInputElement>) => void
-  setOnUploadFile: (fn: (file: File) => Promise<string | null> | string | null) => void
-}
-
-export function useSharedCover(opts: UseSharedCoverOptions): UseSharedCoverReturn {
-  const { canGenerate, disabledHint, generateFn, initialTemplateId = "default" } = opts
-  const [generating, setGenerating] = useState(false)
-  const [showCoverSettings, setShowCoverSettings] = useState(false)
-  const [showCoverEditor, setShowCoverEditor] = useState(false)
-  const [selectedTemplateId, setSelectedTemplateId] = useState<string>(initialTemplateId)
-  const [editingTemplate, setEditingTemplate] = useState<CoverTemplate | null>(null)
-  const [templates, setTemplates] = useState<CoverTemplate[]>([])
-  const [templatesLoading, setTemplatesLoading] = useState(false)
-  const [templatesError, setTemplatesError] = useState<string | null>(null)
-  const uploadInputRef = useRef<HTMLInputElement>(null)
-  const onUploadFileRef = useRef<
-    ((file: File) => Promise<string | null> | string | null) | undefined
-  >(undefined)
-
-  const setOnUploadFile = useCallback(
-    (fn: (file: File) => Promise<string | null> | string | null) => {
-      onUploadFileRef.current = fn
-    },
-    [],
-  )
-
-  const reloadTemplates = useCallback(async () => {
-    setTemplatesLoading(true)
-    setTemplatesError(null)
-    try {
-      const res = await fetchCoverTemplates()
-      // 兼容两种响应：{items:[...]} 或直接数组
-      const rawList = (res as unknown as { items?: CoverTemplate[] }).items ?? []
-      // 确保每个模板都有 config 字段（避免编辑器打开时访问 cfg.title.text 崩溃）
-      const list: CoverTemplate[] = rawList.map((t) => ({
-        ...t,
-        config: t.config,
-      }))
-      setTemplates(list)
-    } catch (err) {
-      const axiosErr = err as {
-        response?: {
-          status?: number
-          data?: { detail?: string; message?: string; error?: { message?: string } }
-        }
-        message?: string
-      }
-      const status = axiosErr?.response?.status
-      const detail =
-        axiosErr?.response?.data?.detail ||
-        axiosErr?.response?.data?.message ||
-        axiosErr?.response?.data?.error?.message ||
-        axiosErr?.message
-      console.error("[SharedCover] 加载封面模板失败:", err, "status=", status, "detail=", detail)
-      if (status === 401) {
-        setTemplatesError("登录已过期，请刷新页面重新登录")
-      } else if (status === 403) {
-        setTemplatesError(detail ? "权限不足：" + detail : "无权限访问封面模板")
-      } else {
-        setTemplatesError("加载模板失败：" + (detail || "请稍后重试"))
-      }
-    } finally {
-      setTemplatesLoading(false)
-    }
-  }, [])
-
-  useEffect(() => {
-    if (showCoverSettings) {
-      void reloadTemplates()
-    }
-  }, [showCoverSettings, reloadTemplates])
-
-  const handleSelectTemplate = useCallback((id: string) => {
-    setSelectedTemplateId(id)
-  }, [])
-
-  const handleEditTemplate = useCallback((tpl: CoverTemplate) => {
-    // 系统模板不可修改：复制为新模板草稿，走另存为流程
-    if (tpl.is_system) {
-      setEditingTemplate({
-        ...tpl,
-        id: "",
-        name: tpl.name + " 副本",
-        is_system: false,
-        created_at: "",
-      })
-    } else {
-      setEditingTemplate(tpl)
-    }
-    setShowCoverEditor(true)
-  }, [])
-
-  const handleCreateTemplate = useCallback(() => {
-    setEditingTemplate(null)
-    setShowCoverEditor(true)
-  }, [])
-
-  const handleSaveTemplate = useCallback(
-    async (tpl: CoverTemplate) => {
-      try {
-        // 系统模板或无 id（新建/副本）→ 走创建分支；否则走更新
-        const isSystem = templates.find((t) => t.id === tpl.id)?.is_system === true
-        const shouldCreate = !tpl.id || isSystem
-        if (shouldCreate) {
-          const created = await createCoverTemplate({
-            name: tpl.name || "我的封面模板",
-            config: tpl.config,
-          })
-          setTemplates((prev) => [...prev, created])
-          setSelectedTemplateId(created.id || tpl.id)
-        } else {
-          const updated = await updateCoverTemplate(tpl.id, { name: tpl.name, config: tpl.config })
-          setTemplates((prev) => prev.map((t) => (t.id === tpl.id ? { ...t, ...updated } : t)))
-        }
-        setShowCoverEditor(false)
-        setEditingTemplate(null)
-      } catch (err) {
-        const axiosErr = err as {
-          response?: {
-            status?: number
-            data?: { detail?: string; message?: string; error?: { message?: string } }
-          }
-          message?: string
-        }
-        const status = axiosErr?.response?.status
-        const detail =
-          axiosErr?.response?.data?.detail ||
-          axiosErr?.response?.data?.message ||
-          axiosErr?.response?.data?.error?.message ||
-          axiosErr?.message
-        console.error("[SharedCover] 保存模板失败:", err, "status=", status, "detail=", detail)
-        if (status === 403) {
-          message.error("保存失败（权限不足）：" + (detail || "无权操作该模板"))
-        } else {
-          message.error("保存模板失败：" + (detail || "请稍后重试"))
-        }
-      }
-    },
-    [templates],
-  )
-
-  const handleDeleteTemplate = useCallback(
-    async (id: string) => {
-      try {
-        await deleteCoverTemplate(id)
-        setTemplates((prev) => prev.filter((t) => t.id !== id))
-        if (selectedTemplateId === id) {
-          setSelectedTemplateId("default")
-        }
-      } catch (err) {
-        const axiosErr = err as {
-          response?: {
-            status?: number
-            data?: { detail?: string; message?: string; error?: { message?: string } }
-          }
-          message?: string
-        }
-        const status = axiosErr?.response?.status
-        const detail =
-          axiosErr?.response?.data?.detail ||
-          axiosErr?.response?.data?.message ||
-          axiosErr?.response?.data?.error?.message ||
-          axiosErr?.message
-        console.error("[SharedCover] 删除模板失败:", err, "status=", status, "detail=", detail)
-        if (status === 403) {
-          message.error("删除失败（权限不足）：" + (detail || "无权操作该模板"))
-        } else {
-          message.error("删除模板失败：" + (detail || "请稍后重试"))
-        }
-      }
-    },
-    [selectedTemplateId],
-  )
-
-  const generateAutoCover = useCallback(async () => {
-    if (generating) {
-      message.warning("封面正在生成中，请稍候…")
-      return
-    }
-    if (!canGenerate) {
-      if (disabledHint) message.warning(disabledHint)
-      return
-    }
-    setGenerating(true)
-    try {
-      const url = await generateFn(selectedTemplateId || "default")
-      if (!url) {
-        message.warning("封面生成未返回图片，请重试")
-      }
-    } catch (err) {
-      console.error("[SharedCover] 自动生成封面失败:", err)
-      const anyErr = err as { __msgShown?: boolean; message?: string }
-      if (!anyErr?.__msgShown) {
-        message.error(anyErr?.message || "封面生成失败")
-      }
-    } finally {
-      setGenerating(false)
-    }
-  }, [generating, canGenerate, disabledHint, generateFn, selectedTemplateId])
-
-  const handleUploadClick = useCallback(() => {
-    uploadInputRef.current?.click()
-  }, [])
-
-  const handleFileInputChange = useCallback((e: React.ChangeEvent<HTMLInputElement>) => {
-    const file = e.target.files?.[0]
-    e.target.value = ""
-    if (!file) return
-    if (onUploadFileRef.current) {
-      const ret = onUploadFileRef.current(file)
-      if (ret instanceof Promise) {
-        ret.catch((err) => {
-          console.error("[SharedCover] 上传封面失败:", err)
-        })
-      }
-    }
-  }, [])
-
-  const selectedTemplateName =
-    templates.find((t) => t.id === selectedTemplateId)?.name ||
-    (selectedTemplateId === "default" ? "默认模板" : "自定义")
-
-  return {
-    templates,
-    templatesLoading,
-    templatesError,
-    selectedTemplateId,
-    selectedTemplateName,
-    handleSelectTemplate,
-    reloadTemplates,
-    showCoverSettings,
-    setShowCoverSettings,
-    showCoverEditor,
-    setShowCoverEditor,
-    editingTemplate,
-    handleEditTemplate,
-    handleCreateTemplate,
-    handleSaveTemplate,
-    handleDeleteTemplate,
-    generating,
-    generateAutoCover,
-    uploadInputRef,
-    handleUploadClick,
-    handleFileInputChange,
-    setOnUploadFile,
-  }
-}
-
-export default useSharedCover

apps/web/src/pages/ai-avatar/AiAvatarPage.tsx

@@ -61,10 +61,9 @@ const AiAvatarPage: React.FC = () => {
     "generating",
   )
   const [lipsyncErrorMessage, setLipsyncErrorMessage] = useState("")
-  /* ── 对口型耗时计时（秒） ── */
   const [lipsyncElapsed, setLipsyncElapsed] = useState(0)
-  const lipsyncStartAtRef = useRef<number>(0)
-  const lipsyncTickRef = useRef<ReturnType<typeof setInterval> | null>(null)
+  /* ── 对口型计时器 ── */
+  const lipsyncElapsedTimerRef = useRef<ReturnType<typeof setInterval> | null>(null)
   /* ── 渲染进度弹窗 ── */
   const [showRenderModal, setShowRenderModal] = useState(false)
   const [renderStatus, setRenderStatus] = useState<"generating" | "completed" | "failed">(
@@ -84,6 +83,30 @@ const AiAvatarPage: React.FC = () => {
   /* ── 渲染进度轮询 ── */
   const renderTimerRef = useRef<ReturnType<typeof setInterval> | null>(null)
 
+  /* ── 对口型计时器工具 ── */
+  const _formatElapsed = useCallback((seconds: number) => {
+    const m = Math.floor(seconds / 60)
+    const s = seconds % 60
+    return `${String(m).padStart(2, "0")}:${String(s).padStart(2, "0")}`
+  }, [])
+
+  const _startLipsyncElapsedTimer = useCallback(() => {
+    if (lipsyncElapsedTimerRef.current) {
+      clearInterval(lipsyncElapsedTimerRef.current)
+    }
+    setLipsyncElapsed(0)
+    lipsyncElapsedTimerRef.current = setInterval(() => {
+      setLipsyncElapsed((prev) => prev + 1)
+    }, 1000)
+  }, [])
+
+  const _stopLipsyncElapsedTimer = useCallback(() => {
+    if (lipsyncElapsedTimerRef.current) {
+      clearInterval(lipsyncElapsedTimerRef.current)
+      lipsyncElapsedTimerRef.current = null
+    }
+  }, [])
+
   const togglePanel = useCallback((key: PanelKey) => {
     setCollapsed((prev) => ({ ...prev, [key]: !prev[key] }))
   }, [])
@@ -226,13 +249,7 @@ const AiAvatarPage: React.FC = () => {
       setShowLipsyncModal(true)
       setLipsyncStatus("generating")
       setLipsyncErrorMessage("")
-      // 启动计时器
-      lipsyncStartAtRef.current = Date.now()
-      setLipsyncElapsed(0)
-      if (lipsyncTickRef.current) clearInterval(lipsyncTickRef.current)
-      lipsyncTickRef.current = setInterval(() => {
-        setLipsyncElapsed(Math.floor((Date.now() - lipsyncStartAtRef.current) / 1000))
-      }, 1000)
+      _startLipsyncElapsedTimer()
 
       const asset = await getAssetById(video.id)
       const videoUrl = asset?.file_url
@@ -276,11 +293,7 @@ const AiAvatarPage: React.FC = () => {
           state.setLipsyncJob(updated)
           if (updated.status === "completed") {
             if (lipsyncTimerRef.current) clearInterval(lipsyncTimerRef.current)
-            if (lipsyncTickRef.current) {
-              clearInterval(lipsyncTickRef.current)
-              lipsyncTickRef.current = null
-            }
-            setLipsyncElapsed(Math.floor((Date.now() - lipsyncStartAtRef.current) / 1000))
+            _stopLipsyncElapsedTimer()
             setLipsyncStatus("completed")
             setTimeout(() => {
               setShowLipsyncModal(false)
@@ -288,10 +301,7 @@ const AiAvatarPage: React.FC = () => {
             }, 1000)
           } else if (updated.status === "failed") {
             if (lipsyncTimerRef.current) clearInterval(lipsyncTimerRef.current)
-            if (lipsyncTickRef.current) {
-              clearInterval(lipsyncTickRef.current)
-              lipsyncTickRef.current = null
-            }
+            _stopLipsyncElapsedTimer()
             setLipsyncStatus("failed")
             setLipsyncErrorMessage(updated.error_message || "对口型生成失败")
           }
@@ -305,10 +315,8 @@ const AiAvatarPage: React.FC = () => {
         data: (err as { response?: { data?: unknown } })?.response?.data,
         message: err instanceof Error ? err.message : String(err),
       })
-      if (lipsyncTickRef.current) {
-        clearInterval(lipsyncTickRef.current)
-        lipsyncTickRef.current = null
-      }
+      _stopLipsyncElapsedTimer()
+      setLipsyncElapsed(0)
       setShowLipsyncModal(false)
       message.error(err instanceof Error ? err.message : "对口型任务提交失败，请重试")
     }
@@ -321,6 +329,8 @@ const AiAvatarPage: React.FC = () => {
 
     state.style,
     state.ttsPreview,
+    _startLipsyncElapsedTimer,
+    _stopLipsyncElapsedTimer,
   ])
 
   // 取消对口型生成
@@ -329,22 +339,19 @@ const AiAvatarPage: React.FC = () => {
       clearInterval(lipsyncTimerRef.current)
       lipsyncTimerRef.current = null
     }
-    if (lipsyncTickRef.current) {
-      clearInterval(lipsyncTickRef.current)
-      lipsyncTickRef.current = null
-    }
+    _stopLipsyncElapsedTimer()
+    setLipsyncElapsed(0)
     setShowLipsyncModal(false)
     setLipsyncStatus("generating")
     setLipsyncErrorMessage("")
-    setLipsyncElapsed(0)
-  }, [])
+  }, [_stopLipsyncElapsedTimer])
 
   // 清理轮询
   useEffect(() => {
     return () => {
       if (lipsyncTimerRef.current) clearInterval(lipsyncTimerRef.current)
-      if (lipsyncTickRef.current) clearInterval(lipsyncTickRef.current)
       if (renderTimerRef.current) clearInterval(renderTimerRef.current)
+      if (lipsyncElapsedTimerRef.current) clearInterval(lipsyncElapsedTimerRef.current)
     }
   }, [])
 
@@ -726,11 +733,17 @@ const AiAvatarPage: React.FC = () => {
               <div className="aa-panel__body">
                 {currentRenderJob?.status !== "completed" ? (
                   <PanelCoverAndGenerate
+                    variant="setup"
+                    coverConfig={state.coverConfig}
+                    onCoverConfigChange={(partial) =>
+                      state.setCoverConfig((prev) => ({ ...prev, ...partial }))
+                    }
+                    renderJob={currentRenderJob}
+                    onGenerateRenderSmartCover={handleGenerateRenderSmartCover}
                     resolution={state.resolution}
                     onResolutionChange={state.setResolution}
                     isGenerating={state.isGenerating}
                     onGenerate={handleGenerate}
-                    renderJob={currentRenderJob}
                     summary={summary}
                   />
                 ) : (
@@ -987,20 +1000,10 @@ const AiAvatarPage: React.FC = () => {
                   <div style={{ marginTop: 20, fontSize: 15, color: "#1a1a2e" }}>
                     对口型视频生成中…
                   </div>
-                  <div
-                    style={{
-                      marginTop: 12,
-                      fontSize: 28,
-                      fontWeight: 700,
-                      fontVariantNumeric: "tabular-nums",
-                      color: "#7c3aed",
-                    }}
-                  >
-                    {`${Math.floor(lipsyncElapsed / 60)
-                      .toString()
-                      .padStart(2, "0")}:${(lipsyncElapsed % 60).toString().padStart(2, "0")}`}
-                  </div>
                   <div style={{ marginTop: 8, fontSize: 13, color: "#8c8ca1" }}>
+                    已用时：{_formatElapsed(lipsyncElapsed)}
+                  </div>
+                  <div style={{ marginTop: 4, fontSize: 13, color: "#8c8ca1" }}>
                     请勿关闭页面，完成后将自动提示
                   </div>
                 </>
@@ -1011,20 +1014,6 @@ const AiAvatarPage: React.FC = () => {
                   <div style={{ marginTop: 16, fontSize: 15, color: "#1a1a2e" }}>
                     对口型视频生成完成
                   </div>
-                  <div
-                    style={{
-                      marginTop: 8,
-                      fontSize: 13,
-                      color: "#10b981",
-                      fontVariantNumeric: "tabular-nums",
-                    }}
-                  >
-                    总耗时{" "}
-                    {Math.floor(lipsyncElapsed / 60)
-                      .toString()
-                      .padStart(2, "0")}
-                    :{(lipsyncElapsed % 60).toString().padStart(2, "0")}
-                  </div>
                 </>
               )}
               {lipsyncStatus === "failed" && (

apps/web/src/pages/ai-avatar/api/aiAvatar.ts

@@ -99,18 +99,15 @@ export const cancelRenderJob = async (jobId: string): Promise<void> => {
   await apiClient.post(`/ai-avatar/render/${jobId}/cancel`)
 }
 
-/* ── 从最终渲染成片智能抽封面（POST /ai-avatar/render/{job_id}/smart-cover） ──
- * #2033 共享封面组件：支持传 template_id（模板ID，传 default 走默认智能抽帧）
- */
+/* ── 从最终渲染成片智能抽封面（POST /ai-avatar/renders/{job_id}/smart-cover） ── */
 export const generateRenderSmartCover = async (
   jobId: string,
-  templateId: string = "default",
 ): Promise<{ cover_url: string; status: string; message: string }> => {
   const response = await apiClient.post<{ cover_url: string; status: string; message: string }>(
     `/ai-avatar/render/${jobId}/smart-cover`,
-    templateId && templateId !== "default" ? { template_id: templateId } : {},
-    // 抽帧+评分+转存 OSS 链路较长，120s 超时；使用模板时叠加文字渲染再加 60s
-    { timeout: templateId && templateId !== "default" ? 180000 : 120000 },
+    {},
+    // 抽帧+评分+转存 OSS 链路较长，120s 超时
+    { timeout: 120000 },
   )
   return response.data
 }

apps/web/src/pages/ai-avatar/components/ModalCoverSelect.tsx

@@ -1,25 +1,11 @@
 /**
- * AI数字人 — 封面选择弹窗（#2033 共享封面组件重构）
- *
- * 复用智能剪辑的 CoverSettingsModal（模板选择）+ CoverEditorModal（7 面板自定义编辑器）
- * + 智能生成 / 本地上传 / 封面预览，与智能剪辑侧 UI 一致。
- *
- * 父组件仍维持 AiAvatarCoverConfig { mode, smart_cover_url, upload_url, thumbnail_url } 结构：
- * - 智能生成封面：mode="auto_frame"，thumbnail_url/smart_cover_url 指向后端返回的 cover_url
- * - 本地上传封面：mode="upload"，upload_url/thumbnail_url 指向 blob 预览 URL
- *
- * 模板 CRUD 通过 @/api/cover-templates 统一接口（智能剪辑与 AI数字人共享同一套模板库）。
+ * AI数字人 — 封面选择弹窗
+ * 渲染完成后由主页面唤起，内部用 PanelCoverAndGenerate（select-cover 变体）提供
+ * 智能抽帧 + 自定义上传 + 预览 + 确定按钮。
  */
-import React, { useCallback, useEffect, useMemo } from "react"
-import { Modal as AntModal, Spin, message } from "antd"
-import { LoadingOutlined } from "@ant-design/icons"
-import Modal from "@/components/ui/Modal"
-import Button from "@/components/ui/Button"
-import CoverSettingsModal from "@/pages/generate/components/cover-settings/CoverSettingsModal"
-import CoverEditorModal from "@/pages/generate/components/cover-settings/CoverEditorModal"
-import { useSharedCover } from "@/components/cover/useSharedCover"
-import { generateRenderSmartCover as apiGenerateSmartCover } from "../api/aiAvatar"
+import React from "react"
 import type { AiAvatarCoverConfig, RenderJob } from "../types"
+import PanelCoverAndGenerate from "./PanelCoverAndGenerate"
 
 interface ModalCoverSelectProps {
   open: boolean
@@ -27,13 +13,7 @@ interface ModalCoverSelectProps {
   renderJob: RenderJob | null
   coverConfig: AiAvatarCoverConfig
   onCoverConfigChange: (partial: Partial<AiAvatarCoverConfig>) => void
-  /**
-   * 【保留兼容】老接口：单参 renderId；新接口支持 templateId 由本组件内部直接调用，不再需要父层传入
-   * 如果父层传了该回调，本组件的"自动生成封面"按钮会调用它；否则走本组件内部 apiGenerateSmartCover。
-   */
-  onGenerateRenderSmartCover?: (
-    renderId: string,
-  ) => Promise<{ cover_url: string; message?: string }>
+  onGenerateRenderSmartCover: (renderId: string) => Promise<{ cover_url: string; message?: string }>
   onUploadCover?: (file: File) => void
   onCoverSelected: (coverUrl: string) => void
 }
@@ -48,302 +28,31 @@ const ModalCoverSelect: React.FC<ModalCoverSelectProps> = ({
   onUploadCover,
   onCoverSelected,
 }) => {
-  const isRenderCompleted = renderJob?.status === "completed" && !!renderJob?.id
-
-  const generateFn = useCallback(
-    async (templateId: string): Promise<string | null> => {
-      if (!renderJob || !isRenderCompleted) return null
-      try {
-        let coverUrl = ""
-        if (onGenerateRenderSmartCover) {
-          const res = await onGenerateRenderSmartCover(renderJob.id)
-          coverUrl = res.cover_url
-        } else {
-          const res = await apiGenerateSmartCover(renderJob.id, templateId)
-          coverUrl = res.cover_url
-          if (!coverUrl && res.message) {
-            const err = new Error(res.message) as Error & { __msgShown?: boolean }
-            err.__msgShown = true
-            message.error(res.message)
-            throw err
-          }
-        }
-        if (coverUrl) {
-          onCoverConfigChange({
-            mode: "auto_frame",
-            thumbnail_url: coverUrl,
-            smart_cover_url: coverUrl,
-          })
-          onCoverSelected(coverUrl)
-          message.success("智能封面已生成")
-        }
-        return coverUrl || null
-      } catch (err) {
-        const anyErr = err as { __msgShown?: boolean; message?: string }
-        if (!anyErr?.__msgShown) {
-          message.error(anyErr?.message || "智能封面生成失败")
-        }
-        throw err
-      }
-    },
-    [
-      renderJob,
-      isRenderCompleted,
-      onGenerateRenderSmartCover,
-      onCoverConfigChange,
-      onCoverSelected,
-    ],
-  )
-
-  const shared = useSharedCover({
-    canGenerate: isRenderCompleted,
-    disabledHint: "请先完成视频生成再选择封面",
-    initialTemplateId: "default",
-    generateFn,
-  })
-
-  // 父层 onUploadCover 走 onUploadFile 回调（兼容老父组件）
-  useEffect(() => {
-    shared.setOnUploadFile((file: File) => {
-      if (onUploadCover) {
-        onUploadCover(file)
-      } else {
-        const url = URL.createObjectURL(file)
-        onCoverConfigChange({
-          mode: "upload",
-          upload_url: url,
-          thumbnail_url: url,
-        })
-        onCoverSelected(url)
-      }
-      return null
-    })
-  }, [shared, onUploadCover, onCoverConfigChange, onCoverSelected])
-
-  // 打开时同步刷新模板列表
-  useEffect(() => {
-    if (open) void shared.reloadTemplates()
-    // eslint-disable-next-line react-hooks/exhaustive-deps
-  }, [open])
-
-  /** 当前预览 URL：智能封面 > 自定义上传 */
-  const previewUrl = useMemo(
-    () => coverConfig.smart_cover_url || coverConfig.thumbnail_url || coverConfig.upload_url || "",
-    [coverConfig.smart_cover_url, coverConfig.thumbnail_url, coverConfig.upload_url],
-  )
-
   if (!open) return null
 
   return (
-    <Modal
-      open={open}
-      onCancel={onClose}
-      title="选择封面"
-      width={560}
-      footer={
-        <div style={{ display: "flex", justifyContent: "flex-end", gap: 8 }}>
-          <Button buttonType="ghost" onClick={onClose}>
-            取消
-          </Button>
-          <Button buttonType="primary" onClick={onClose}>
-            确定
-          </Button>
+    <div className="aa-modal-overlay" onClick={onClose}>
+      <div className="aa-modal" onClick={(e) => e.stopPropagation()} style={{ maxWidth: 480 }}>
+        <div className="aa-modal__header">
+          <span className="aa-modal__title">选择封面</span>
+          <button type="button" className="aa-modal__close" onClick={onClose} aria-label="关闭">
+            ×
+          </button>
         </div>
-      }
-    >
-      <div style={{ padding: "8px 0" }}>
-        {renderJob && (
-          <div
-            style={{
-              padding: "8px 12px",
-              background: "rgba(16, 185, 129, 0.08)",
-              borderRadius: 8,
-              marginBottom: 12,
-              fontSize: 13,
-              color: "var(--text-secondary, #666)",
-            }}
-          >
-            🎬 从渲染成片中智能选帧
-            {shared.selectedTemplateId && shared.selectedTemplateId !== "default" && (
-              <>
-                {" "}
-                · 当前模板：<strong>{shared.selectedTemplateName}</strong>
-              </>
-            )}
-          </div>
-        )}
-
-        <div
-          style={{
-            display: "flex",
-            gap: 12,
-            alignItems: "flex-start",
-          }}
-        >
-          {/* 左：封面预览 */}
-          <div
-            style={{
-              width: 180,
-              flexShrink: 0,
-            }}
-          >
-            <div
-              className="xx-ce-canvas"
-              style={{
-                position: "relative",
-                width: "100%",
-                aspectRatio: "9 / 16",
-                borderRadius: 8,
-                overflow: "hidden",
-                background: "linear-gradient(135deg, #1e3a8a 0%, #312e81 100%)",
-                border: previewUrl ? "none" : "1px dashed #d9d9d9",
-              }}
-            >
-              {previewUrl ? (
-                <img
-                  src={previewUrl}
-                  alt="封面预览"
-                  style={{
-                    width: "100%",
-                    height: "100%",
-                    objectFit: "cover",
-                  }}
-                />
-              ) : (
-                <div
-                  style={{
-                    position: "absolute",
-                    inset: 0,
-                    display: "flex",
-                    flexDirection: "column",
-                    alignItems: "center",
-                    justifyContent: "center",
-                    color: "#fff",
-                    fontSize: 12,
-                    gap: 6,
-                    opacity: 0.7,
-                  }}
-                >
-                  <span style={{ fontSize: 28 }}>🖼️</span>
-                  <span>
-                    {isRenderCompleted ? "点击下方按钮生成/上传" : "视频生成后可选择封面"}
-                  </span>
-                </div>
-              )}
-              {shared.generating && (
-                <div
-                  style={{
-                    position: "absolute",
-                    inset: 0,
-                    background: "rgba(0,0,0,0.5)",
-                    display: "flex",
-                    alignItems: "center",
-                    justifyContent: "center",
-                    color: "#fff",
-                    fontSize: 12,
-                    flexDirection: "column",
-                    gap: 8,
-                  }}
-                >
-                  <Spin indicator={<LoadingOutlined style={{ fontSize: 24 }} spin />} />
-                  <span>AI 选帧中…</span>
-                </div>
-              )}
-            </div>
-            <div
-              style={{
-                marginTop: 6,
-                textAlign: "center",
-                fontSize: 11,
-                color: "#8c8ca1",
-              }}
-            >
-              9:16 竖版封面
-            </div>
-          </div>
-
-          {/* 右：操作按钮 */}
-          <div style={{ flex: 1, display: "flex", flexDirection: "column", gap: 8 }}>
-            <Button
-              buttonType="primary"
-              onClick={() => void shared.generateAutoCover()}
-              disabled={!isRenderCompleted || shared.generating}
-              loading={shared.generating}
-              style={{ width: "100%" }}
-            >
-              ✨ 自动生成封面
-            </Button>
-            <Button
-              buttonType="ghost"
-              onClick={() => shared.setShowCoverSettings(true)}
-              style={{ width: "100%" }}
-            >
-              ⚙️ 封面模板
-            </Button>
-            <Button
-              buttonType="ghost"
-              onClick={shared.handleUploadClick}
-              disabled={!isRenderCompleted || shared.generating}
-              style={{ width: "100%" }}
-            >
-              📷 本地上传
-            </Button>
-            <input
-              ref={shared.uploadInputRef}
-              type="file"
-              accept="image/*"
-              style={{ display: "none" }}
-              onChange={shared.handleFileInputChange}
-            />
-            <div
-              style={{
-                fontSize: 11,
-                color: "#8c8ca1",
-                lineHeight: 1.5,
-                marginTop: 4,
-                padding: "6px 8px",
-                background: "#f7f8fa",
-                borderRadius: 6,
-              }}
-            >
-              💡 选择模板后点击"自动生成封面"会按模板样式渲染；"本地上传"使用本地图片作为封面。
-            </div>
-          </div>
+        <div className="aa-modal__body" style={{ padding: 20 }}>
+          <PanelCoverAndGenerate
+            variant="select-cover"
+            coverConfig={coverConfig}
+            onCoverConfigChange={onCoverConfigChange}
+            renderJob={renderJob}
+            onGenerateRenderSmartCover={onGenerateRenderSmartCover}
+            onUploadCover={onUploadCover}
+            onClose={onClose}
+            onCoverSelected={onCoverSelected}
+          />
         </div>
       </div>
-
-      {/* 模板选择弹窗 */}
-      <CoverSettingsModal
-        open={shared.showCoverSettings}
-        onClose={() => shared.setShowCoverSettings(false)}
-        templates={shared.templates}
-        loading={shared.templatesLoading}
-        error={shared.templatesError}
-        selectedTemplateId={shared.selectedTemplateId}
-        onSelectTemplate={shared.handleSelectTemplate}
-        onEditTemplate={shared.handleEditTemplate}
-        onDeleteTemplate={shared.handleDeleteTemplate}
-        onCreateNew={shared.handleCreateTemplate}
-      />
-
-      {/* 自定义编辑器弹窗 */}
-      <CoverEditorModal
-        open={shared.showCoverEditor}
-        onClose={() => shared.setShowCoverEditor(false)}
-        template={shared.editingTemplate}
-        onSave={shared.handleSaveTemplate}
-      />
-
-      {/* 自动生成 loading 兜底弹窗（shared.generating 时按钮已自带 loading，这里保险） */}
-      <AntModal open={shared.generating} closable={false} footer={null} centered width={320}>
-        <div style={{ textAlign: "center", padding: "24px 0" }}>
-          <Spin size="large" />
-          <p style={{ marginTop: 16, fontSize: 14, color: "#666" }}>
-            AI 正在从最终成片选帧，请稍候...
-          </p>
-        </div>
-      </AntModal>
-    </Modal>
+    </div>
   )
 }
 

apps/web/src/pages/ai-avatar/components/PanelCoverAndGenerate.tsx

@@ -1,19 +1,36 @@
 /**
- * AI数字人 — 面板5 / 生成配置面板（渲染前）
- * #2033 重构后：只保留 setup 变体（分辨率/配置摘要/生成按钮）
- * 封面相关功能已迁移到 ModalCoverSelect（复用智能剪辑共享封面组件）
+ * AI数字人 — 面板5 / 封面选择弹窗内容：
+ * - variant="setup"（默认）：分辨率 / 配置摘要 / 「开始生成视频」按钮，用于主页面步骤2配置阶段；
+ *   渲染完成后仍内嵌封面预览与按钮，方便不打开弹窗直接操作。
+ * - variant="select-cover"：只渲染封面选择区（智能获取封面 + 自定义上传 + 预览），
+ *   用于 ModalCoverSelect 弹窗中；传 onClose 时底部显示「确定」按钮。
+ *
+ * 封面一律从最终成片（已叠加标题/B-roll）抽帧，本面板不再叠加标题。
  */
-import React from "react"
-import type { RenderJob } from "../types"
+import React, { useRef, useState } from "react"
+import type { AiAvatarCoverConfig, RenderJob } from "../types"
+
+type PanelVariant = "setup" | "select-cover"
 
 interface PanelCoverAndGenerateProps {
+  variant?: PanelVariant
+  coverConfig: AiAvatarCoverConfig
+  onCoverConfigChange: (partial: Partial<AiAvatarCoverConfig>) => void
   resolution?: string
   onResolutionChange?: (r: string) => void
   isGenerating?: boolean
   onGenerate?: () => void
-  /** 当前渲染任务 */
+  /** 当前渲染任务（渲染完成后才有 output_video_url，才能抽封面） */
   renderJob: RenderJob | null
-  /** 配置汇总信息 */
+  /** 从最终成片智能抽帧（参数 renderId），返回 { cover_url } */
+  onGenerateRenderSmartCover: (renderId: string) => Promise<{ cover_url: string; message?: string }>
+  /** 自定义上传封面（选择本地文件后由父组件处理实际上传） */
+  onUploadCover?: (file: File) => void
+  /** 弹窗关闭回调（传入则表示在弹窗中使用，底部显示「确定」按钮） */
+  onClose?: () => void
+  /** 封面选好（智能抽帧/自定义上传成功）后通知父组件，参数为封面 URL */
+  onCoverSelected?: (coverUrl: string) => void
+  /** 配置汇总信息（仅 variant="setup" 使用） */
   summary?: {
     videoName: string | null
     voiceName: string | null
@@ -21,6 +38,7 @@ interface PanelCoverAndGenerateProps {
     lipsyncStatus: string | null
     brollCount: number
     hasTitle: boolean
+    /** 封面状态：'not_ready'(视频未生成) / 'pending'(视频生成了但未选) / 'selected'(已选) */
     coverStatus: "not_ready" | "pending" | "selected"
   }
 }
@@ -40,15 +58,89 @@ const LIPSYNC_STATUS_LABEL: Record<string, { text: string; cls: string }> = {
 }
 
 const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
+  variant = "setup",
+  coverConfig,
+  onCoverConfigChange,
   resolution = "720p",
   onResolutionChange,
   isGenerating = false,
   onGenerate,
-  renderJob: _renderJob,
+  renderJob,
+  onGenerateRenderSmartCover,
+  onUploadCover,
+  onClose,
+  onCoverSelected,
   summary,
 }) => {
+  const uploadInputRef = useRef<HTMLInputElement>(null)
+  // 内部维护智能封面加载态（修复点 2 次 bug：不依赖外层异步 setState 顺序）
+  const [smartCoverLoading, setSmartCoverLoading] = useState(false)
+
+  /** 自定义上传封面 */
+  const handleUploadClick = () => {
+    uploadInputRef.current?.click()
+  }
+
+  const _applyCoverUrl = (url: string, mode: "upload" | "auto_frame") => {
+    const partial: Partial<AiAvatarCoverConfig> = {
+      mode,
+      thumbnail_url: url,
+    }
+    if (mode === "auto_frame") {
+      partial.smart_cover_url = url
+    } else {
+      partial.upload_url = url
+    }
+    onCoverConfigChange(partial)
+    onCoverSelected?.(url)
+  }
+
+  const handleFileChange = (e: React.ChangeEvent<HTMLInputElement>) => {
+    const file = e.target.files?.[0]
+    if (!file) return
+    if (onUploadCover) {
+      onUploadCover(file)
+      e.target.value = ""
+      return
+    }
+    // 本地预览兜底（实际上传由父级处理；blob URL 仅作本地展示）
+    const url = URL.createObjectURL(file)
+    _applyCoverUrl(url, "upload")
+    e.target.value = ""
+  }
+
+  /** 智能获取封面（从最终成片抽帧；必须等 render 完成） */
+  const handleSmartCover = async () => {
+    if (!renderJob || renderJob.status !== "completed" || !renderJob.id) return
+    setSmartCoverLoading(true)
+    try {
+      const res = await onGenerateRenderSmartCover(renderJob.id)
+      if (res.cover_url) {
+        _applyCoverUrl(res.cover_url, "auto_frame")
+      } else {
+        // 失败由父组件 message 提示，这里不重复弹窗
+        console.warn("[智能封面] 返回空 cover_url:", res.message)
+      }
+    } catch (err) {
+      console.error("[智能封面] 调用失败:", err)
+    } finally {
+      setSmartCoverLoading(false)
+    }
+  }
+
   const lipsync = summary?.lipsyncStatus ? LIPSYNC_STATUS_LABEL[summary.lipsyncStatus] : null
   const canGenerate = summary?.lipsyncStatus === "completed" && !isGenerating
+  // 渲染已完成 → 封面区可用
+  const isRenderCompleted = renderJob?.status === "completed"
+  const canSmartCover = isRenderCompleted && !smartCoverLoading
+
+  /** 封面图实际展示的 url：智能封面 > 自定义上传 > 空 */
+  const coverUrl =
+    coverConfig.smart_cover_url || coverConfig.thumbnail_url || coverConfig.upload_url
+  const hasCoverImage = Boolean(coverUrl)
+
+  /** 封面区占位文字 */
+  const coverPlaceholder = isRenderCompleted ? "暂无封面" : "视频生成后可选择封面"
 
   /** 配置摘要中的封面状态标签 */
   const coverSummaryNode = (() => {
@@ -62,6 +154,69 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
     return <span className="aa-config-summary__empty">生成视频后可选</span>
   })()
 
+  // ── 封面选择区（两种 variant 共用） ─────────────────────────────────
+  const coverSection = (
+    <div className="aa-cover-section" style={{ marginTop: variant === "select-cover" ? 0 : 16 }}>
+      <div className="aa-label" style={{ marginBottom: 8 }}>
+        {variant === "select-cover" ? "选择封面" : "封面"}
+      </div>
+      {/* 封面预览（竖屏 9:16）——成片帧已经通过 Canvas PNG overlay 带有标题，直接展示原图即可 */}
+      <div className="aa-cover-preview" style={{ opacity: isRenderCompleted ? 1 : 0.5 }}>
+        {hasCoverImage ? (
+          <img src={coverUrl!} alt="封面预览" draggable={false} />
+        ) : (
+          <span className="aa-cover-preview__placeholder">{coverPlaceholder}</span>
+        )}
+        {smartCoverLoading && <div className="aa-cover-preview__loading">⏳ 智能选帧中…</div>}
+      </div>
+
+      <div className="aa-cover-actions">
+        <button
+          type="button"
+          className={`aa-btn aa-btn--ghost${coverConfig.mode === "auto_frame" ? " active" : ""}`}
+          onClick={handleSmartCover}
+          disabled={!canSmartCover}
+          title={isRenderCompleted ? "从成片智能选帧" : "请先生成视频"}
+        >
+          {smartCoverLoading ? "⏳ 智能选帧中…" : "🎬 智能获取封面"}
+        </button>
+        <button
+          type="button"
+          className={`aa-btn aa-btn--ghost${coverConfig.mode === "upload" ? " active" : ""}`}
+          onClick={handleUploadClick}
+          disabled={!isRenderCompleted || smartCoverLoading}
+          title={isRenderCompleted ? "自定义上传封面" : "请先生成视频"}
+        >
+          📷 自定义上传
+        </button>
+        <input
+          ref={uploadInputRef}
+          type="file"
+          accept="image/*"
+          style={{ display: "none" }}
+          onChange={handleFileChange}
+        />
+      </div>
+    </div>
+  )
+
+  // ── select-cover 变体：只渲染封面区 + 弹窗确定按钮 ──
+  if (variant === "select-cover") {
+    return (
+      <div className="aa-cover-generate">
+        {coverSection}
+        {onClose && (
+          <div style={{ marginTop: 16, display: "flex", justifyContent: "flex-end" }}>
+            <button type="button" className="aa-btn aa-btn--primary" onClick={onClose}>
+              确定
+            </button>
+          </div>
+        )}
+      </div>
+    )
+  }
+
+  // ── setup 变体：分辨率 / 配置摘要 / 生成按钮（渲染完成后内嵌封面区） ──
   return (
     <div className="aa-cover-generate">
       {/* 分辨率选择 */}

apps/web/src/pages/generate/GeneratePage.tsx

@@ -21,7 +21,7 @@ import GenerateStepActions from "./components/GenerateStepActions"
 import { useGenerateFormState } from "./hooks/useGenerateFormState"
 import { useStepNavigation } from "./hooks/useStepNavigation"
 import { useGenerateVideo } from "./hooks/useGenerateVideo"
-import { finalizeGeneration } from "@/api/generation/finalize"
+import { confirmGeneration } from "@/api/generation/confirm"
 
 import { useBatchVariantPlans } from "./hooks/useBatchVariantPlans"
 import { useTitleStyleUpdaters } from "./hooks/useStep4Title/useTitleStyleUpdaters"
@@ -411,7 +411,7 @@ const GeneratePage: React.FC = () => {
   /* ── 最终成片（单视频） ── */
   const finalVideo = generatedVideos[0]
 
-  /* ── Step5 完成：先 confirm（同步标题/封面到任务）再 finalize（正式入库成品库） ── */
+  /* ── Step5 完成：调用 confirm 入库 + 跳转 ── */
   const handleFinish = useCallback(async () => {
     if (finishing) return
     // 校验：单视频必须已生成；批量必须所有已选视频有封面或确认跳过
@@ -436,12 +436,12 @@ const GeneratePage: React.FC = () => {
             ? [finalVideo.generation_task_id]
             : []
 
-      // 单视频/批量：为每个 awaiting_cover 任务调用 finalize（入库 + 绑定封面 + 自定义标题）
+      // 单视频/批量：为每个任务调用 confirm（传入封面）
       if (isBatch && previewCovers.length > 0) {
         await Promise.all(
           taskIds.map(async (taskId, idx) => {
             const coverUrl = previewCovers[idx] || ""
-            return finalizeGeneration(taskId, {
+            return confirmGeneration(taskId, {
               cover_url: coverUrl || undefined,
               custom_title: previewTitles[idx] || titleSettings.title || "",
             })
@@ -449,12 +449,11 @@ const GeneratePage: React.FC = () => {
         )
       } else if (finalVideo?.generation_task_id) {
         const coverUrl = coverSettings.thumbnail_url || coverSettings.upload_url || ""
-        await finalizeGeneration(finalVideo.generation_task_id, {
+        await confirmGeneration(finalVideo.generation_task_id, {
           cover_url: coverUrl || undefined,
           custom_title: titleSettings.title || "",
         })
       }
-
       hide()
       message.success("已保存到视频库")
       navigate("/app/products")

apps/web/src/pages/generate/components/BatchGenerationGrid.tsx

@@ -37,9 +37,7 @@ const BatchGenerationGrid: React.FC<BatchGenerationGridProps> = ({
       <div className="xx-preview-header">
         <h3>🎬 正在生成 {tasks.length} 个视频</h3>
         <span style={{ fontSize: 13, color: "var(--text-secondary, #666)" }}>
-          完成{" "}
-          {tasks.filter((t) => t.status === "completed" || t.status === "awaiting_cover").length} /{" "}
-          {tasks.length}
+          完成 {tasks.filter((t) => t.status === "completed").length} / {tasks.length}
         </span>
       </div>
       {/* #1800: grid 列宽 / gap / justify 全部交由 .xx-batch-gen-grid CSS 控制 */}
@@ -51,7 +49,7 @@ const BatchGenerationGrid: React.FC<BatchGenerationGridProps> = ({
             <div key={task.taskId} className={`xx-batch-gen-card status-${task.status}`}>
               <div className="xx-batch-gen-card-head">
                 <span className="xx-batch-gen-card-title" title={title}>
-                  {task.status === "completed" || task.status === "awaiting_cover" ? (
+                  {task.status === "completed" ? (
                     <CheckCircleFilled
                       className="xx-batch-gen-card-icon"
                       style={{ color: "#52c41a" }}
@@ -85,7 +83,7 @@ const BatchGenerationGrid: React.FC<BatchGenerationGridProps> = ({
                     <div className="xx-batch-gen-card-pct">{Math.round(task.progress)}%</div>
                   </>
                 )}
-                {(task.status === "completed" || task.status === "awaiting_cover") && video && (
+                {task.status === "completed" && video && (
                   // 竖屏自适应容器（#1750）：成片固定 1080×1920（9:16），
                   // 视频按真实宽高比 contain 显示，黑底居中，杜绝横屏播放器左右大黑边
                   <div
@@ -113,7 +111,7 @@ const BatchGenerationGrid: React.FC<BatchGenerationGridProps> = ({
                     />
                   </div>
                 )}
-                {(task.status === "completed" || task.status === "awaiting_cover") && !video && (
+                {task.status === "completed" && !video && (
                   <div className="xx-batch-gen-card-done">✅ 已完成（成片可在下一步选择封面）</div>
                 )}
                 {task.status === "failed" && (

apps/web/src/pages/generate/components/Step6CoverSettings.tsx

@@ -1,137 +1,84 @@
 /**
- * Step 5/6 选择封面（Issue #1677 批量生成改造 + #2033 封面bug修复 + #2044 批量模板选择）
- * - 单视频：保留原封面流程（自动生成/封面设置模板/封面预览/自定义上传）
- * - N 个视频：N 张封面卡片，每张带对应视频标题，支持统一选择封面模板、逐个自动生成或上传
- *
- * 模板 CRUD + 编辑器弹窗 + 自动生成 + 上传 复用 components/cover/useSharedCover
+ * Step 5 选择封面（Issue #1677 批量生成改造）
+ * - 单视频：保留原封面流程（自动生成/封面设置模板/封面预览）
+ * - N 个视频：N 张封面卡片，每张带对应视频标题，可逐个自动生成或上传
  */
-import React, { useEffect, useMemo } from "react"
+import React, { useRef } from "react"
 import { Modal, Spin } from "antd"
 import { LoadingOutlined } from "@ant-design/icons"
 import type { CoverConfig } from "../types/cover"
 import type { GeneratedVideo } from "@/api/template-editor"
 import type { TitleSettings } from "../types"
+import { useStep6Cover } from "../hooks/useStep6Cover"
 import { useBatchCovers } from "../hooks/useBatchCovers"
 import Button from "@/components/ui/Button"
 import CoverSettingsModal from "./cover-settings/CoverSettingsModal"
 import CoverEditorModal from "./cover-settings/CoverEditorModal"
-import { useSharedCover } from "@/components/cover/useSharedCover"
-import { generateCover as apiGenerateCover } from "@/api/generation"
 
 interface Step6CoverSettingsProps {
   coverSettings: CoverConfig
   onCoverSettingsChange: (settings: CoverConfig) => void
+  /** 当前选中的模板 ID */
   selectedTemplate?: string
+  /** Step4 标题设置，用于封面叠加标题 */
   titleSettings?: TitleSettings
+  /** 确认生成步骤产出的最终视频列表 */
   generatedVideos: GeneratedVideo[]
+  /* ── 批量生成（#1677）── */
   previewCount?: number
+  /** 每个变体的标题文字 */
   previewTitles?: string[]
+  /** 每个变体的封面URL（按变体索引） */
   previewCovers?: string[]
   onPreviewCoversChange?: (urls: string[]) => void
+  /** 勾选的变体索引（批量封面按此顺序展示，与最终成片顺序一致） */
   selectedVariantIndexes?: number[]
-  onTemplateChange?: (templateId: string) => void
 }
 
 const Step6CoverSettings: React.FC<Step6CoverSettingsProps> = (props) => {
+  const {
+    coverSettings,
+    generating,
+    generateAutoCover,
+    finalVideo,
+    showCoverSettings,
+    setShowCoverSettings,
+    showCoverEditor,
+    setShowCoverEditor,
+    selectedTemplateId,
+    editingTemplate,
+    coverTemplates,
+    templatesLoading,
+    templatesError,
+    handleSelectTemplate,
+    handleEditTemplate,
+    handleSaveTemplate,
+    handleDeleteTemplate,
+  } = useStep6Cover({
+    coverSettings: props.coverSettings,
+    onCoverSettingsChange: props.onCoverSettingsChange,
+    selectedTemplate: props.selectedTemplate,
+    titleSettings: props.titleSettings,
+    generatedVideos: props.generatedVideos,
+  })
+
   const previewCount = props.previewCount || 1
   const isBatch = previewCount > 1
   const previewTitles = props.previewTitles || []
   const previewCovers = props.previewCovers || []
+  /** 卡片展示的变体索引顺序：批量=勾选顺序（与成片顺序一致），单视频=[0] */
   const cardIndexes =
     isBatch && props.selectedVariantIndexes?.length
       ? props.selectedVariantIndexes
       : Array.from({ length: previewCount }, (_, i) => i)
+  const uploadInputRef = useRef<HTMLInputElement>(null)
+  const uploadTargetRef = useRef<number>(0)
 
-  /** 最终成片：取第一个已完成视频（单视频场景） */
-  const finalVideo =
-    props.generatedVideos.find((v) => v.status === "completed" || v.status === "awaiting_cover") ||
-    props.generatedVideos[0]
-
-  const completedVideos = useMemo(
-    () =>
-      props.generatedVideos.filter(
-        (v) => v.status === "completed" || v.status === "awaiting_cover",
-      ),
-    [props.generatedVideos],
-  )
-
-  /**
-   * 单视频自动生成（点击"自动生成封面"按钮）：使用当前选中的模板
-   * 批量场景 canGenerate=false，避免 shared.generateAutoCover 被误触发
-   */
-  const shared = useSharedCover({
-    canGenerate: !!finalVideo && !isBatch,
-    disabledHint: isBatch ? "批量场景请在上方操作卡片" : "请先生成视频再选择封面",
-    initialTemplateId: props.selectedTemplate || "default",
-    generateFn: async (tplId) => {
-      if (!finalVideo || isBatch) return null
-      const response = await apiGenerateCover(tplId, {
-        generated_video_id: finalVideo.id,
-        video_url: finalVideo.file_url || finalVideo.download_url || "",
-        cover_type: "ai_frame",
-        ...(props.titleSettings?.title
-          ? {
-              title_config: {
-                text: props.titleSettings.title,
-                font: props.titleSettings.font,
-                font_size: props.titleSettings.size,
-                font_color: props.titleSettings.color,
-                position: props.titleSettings.position,
-                bold: props.titleSettings.bold,
-                stroke: props.titleSettings.stroke,
-                shadow: props.titleSettings.shadow,
-              },
-            }
-          : {}),
-      })
-      const url = response.cover?.image_url || ""
-      if (url) {
-        props.onCoverSettingsChange({
-          ...props.coverSettings,
-          thumbnail_url: url,
-          ai_suggested_time: response.cover?.frame_time ?? null,
-        })
-      }
-      return url
-    },
-  })
-
-  // 选中模板变化时通知父组件（用于批量生成时透传 template_id）
-  const { onTemplateChange, selectedTemplate: parentSelectedTemplate } = props
-  useEffect(() => {
-    if (isBatch && onTemplateChange && shared.selectedTemplateId !== parentSelectedTemplate) {
-      onTemplateChange(shared.selectedTemplateId)
-    }
-  }, [isBatch, shared.selectedTemplateId, parentSelectedTemplate, onTemplateChange])
-
-  useEffect(() => {
-    shared.setOnUploadFile(() => null)
-  }, [shared])
-
-  const batchUploadRef = React.useRef<HTMLInputElement>(null)
-  const [batchUploadCard, setBatchUploadCard] = React.useState<number | null>(null)
-  const handleBatchUploadClick = (cardPos: number) => {
-    setBatchUploadCard(cardPos)
-    batchUploadRef.current?.click()
-  }
-  const handleBatchUploadChange = (e: React.ChangeEvent<HTMLInputElement>) => {
-    const file = e.target.files?.[0]
-    e.target.value = ""
-    const cardPos = batchUploadCard
-    setBatchUploadCard(null)
-    if (!file || cardPos == null) return
-    void batchCovers.uploadOne(cardPos, file)
-  }
-
+  const completedVideos = props.generatedVideos.filter((v) => v.status === "completed")
   const batchTitles = cardIndexes.map((vi) => previewTitles[vi] || "")
   const batchCoversList = cardIndexes.map((vi) => previewCovers[vi] || "")
-
-  /**
-   * 批量生成：selectedTemplateId 来自用户在 CoverSettingsModal 中选择的模板，
-   * 透传给 useBatchCovers，由其在 generateOne/generateAll 中发给后端。
-   */
   const batchCovers = useBatchCovers({
-    selectedTemplate: shared.selectedTemplateId || "default",
+    selectedTemplate: props.selectedTemplate || "",
     generatedVideos: props.generatedVideos,
     titles: batchTitles,
     titleStyle: {
@@ -145,6 +92,7 @@ const Step6CoverSettings: React.FC<Step6CoverSettingsProps> = (props) => {
     },
     covers: batchCoversList,
     onCoversChange: (updater) => {
+      // 按卡片顺序写回对应变体索引；支持函数式 updater（#1750：串行回写避免闭包覆盖）
       const prevCardView = cardIndexes.map((vi) => (props.previewCovers || [])[vi] || "")
       const nextCardView = typeof updater === "function" ? updater(prevCardView) : updater
       const next = [...(props.previewCovers || [])]
@@ -155,7 +103,22 @@ const Step6CoverSettings: React.FC<Step6CoverSettingsProps> = (props) => {
     },
   })
 
-  const previewUrl = props.coverSettings.thumbnail_url || props.coverSettings.upload_url
+  const previewUrl = coverSettings.thumbnail_url || coverSettings.upload_url
+
+  const handleUploadClick = (variantIndex: number) => {
+    uploadTargetRef.current = variantIndex
+    uploadInputRef.current?.click()
+  }
+
+  const handleFileChange = (e: React.ChangeEvent<HTMLInputElement>) => {
+    const file = e.target.files?.[0]
+    e.target.value = ""
+    if (file) {
+      const variantIndex = uploadTargetRef.current
+      const cardPos = cardIndexes.indexOf(variantIndex)
+      if (cardPos >= 0) void batchCovers.uploadOne(cardPos, file)
+    }
+  }
 
   /* ── 批量封面 ── */
   if (isBatch) {
@@ -175,32 +138,17 @@ const Step6CoverSettings: React.FC<Step6CoverSettingsProps> = (props) => {
           }}
         >
           🎬 共 {completedVideos.length} 个成片，封面将从对应成片中智能选帧并叠加该视频的标题
-          {shared.selectedTemplateId && shared.selectedTemplateId !== "default" && (
-            <>
-              {" · "}当前模板：<strong>{shared.selectedTemplateName}</strong>
-            </>
-          )}
         </div>
 
-        <div style={{ display: "flex", gap: 8, marginBottom: 16, flexWrap: "wrap" }}>
+        <div style={{ display: "flex", gap: 8, marginBottom: 16 }}>
           <Button
             buttonType="primary"
             onClick={() => void batchCovers.generateAll()}
             disabled={completedVideos.length === 0 || batchCovers.busyIndexes.length > 0}
             style={{ whiteSpace: "nowrap", flexShrink: 0 }}
-            loading={batchCovers.busyIndexes.length > 0}
           >
             ✨ 一键全部自动生成
           </Button>
-          <Button buttonType="ghost" onClick={() => shared.setShowCoverSettings(true)}>
-            ⚙️ 封面模板
-            {shared.selectedTemplateId && shared.selectedTemplateId !== "default"
-              ? `：${shared.selectedTemplateName}`
-              : ""}
-          </Button>
-          <Button buttonType="ghost" onClick={shared.handleCreateTemplate}>
-            ➕ 新建模板
-          </Button>
         </div>
 
         <div className="xx-cover-grid">
@@ -261,7 +209,7 @@ const Step6CoverSettings: React.FC<Step6CoverSettingsProps> = (props) => {
                     type="button"
                     className="xx-btn xx-btn-ghost xx-btn-sm"
                     style={{ flex: 1, fontSize: 12, padding: "4px 8px" }}
-                    onClick={() => handleBatchUploadClick(cardPos)}
+                    onClick={() => handleUploadClick(variantIndex)}
                     disabled={isLoading || isUploading}
                   >
                     📤 上传
@@ -272,43 +220,23 @@ const Step6CoverSettings: React.FC<Step6CoverSettingsProps> = (props) => {
           })}
         </div>
 
-        {/* 隐藏的文件选择 input，批量上传复用 */}
         <input
-          ref={batchUploadRef}
+          ref={uploadInputRef}
           type="file"
           accept="image/*"
           style={{ display: "none" }}
-          onChange={handleBatchUploadChange}
-        />
-
-        <CoverSettingsModal
-          open={shared.showCoverSettings}
-          onClose={() => shared.setShowCoverSettings(false)}
-          templates={shared.templates}
-          loading={shared.templatesLoading}
-          error={shared.templatesError}
-          selectedTemplateId={shared.selectedTemplateId}
-          onSelectTemplate={shared.handleSelectTemplate}
-          onEditTemplate={shared.handleEditTemplate}
-          onDeleteTemplate={shared.handleDeleteTemplate}
-          onCreateNew={shared.handleCreateTemplate}
-        />
-
-        <CoverEditorModal
-          open={shared.showCoverEditor}
-          onClose={() => shared.setShowCoverEditor(false)}
-          template={shared.editingTemplate}
-          onSave={shared.handleSaveTemplate}
+          onChange={handleFileChange}
         />
       </div>
     )
   }
 
-  /* ── 单视频 ── */
+  /* ── 单视频：原有流程保持不变 ── */
   return (
     <div className="xx-form-section">
       <h3>🖼️ 选择封面</h3>
 
+      {/* 最终成片信息 */}
       {finalVideo && (
         <div
           style={{
@@ -322,55 +250,16 @@ const Step6CoverSettings: React.FC<Step6CoverSettingsProps> = (props) => {
           }}
         >
           🎬 封面将从最终成片「{finalVideo.name}」中智能选帧
-          {shared.selectedTemplateId && shared.selectedTemplateId !== "default" && (
-            <>
-              {" "}
-              · 当前模板：<strong>{shared.selectedTemplateName}</strong>
-            </>
-          )}
         </div>
       )}
 
       <div className="xx-cover-actions">
-        <Button
-          buttonType="primary"
-          onClick={() => void shared.generateAutoCover()}
-          disabled={!finalVideo || shared.generating}
-          loading={shared.generating}
-        >
+        <Button buttonType="primary" onClick={generateAutoCover} disabled={!finalVideo}>
           ✨ 自动生成封面
         </Button>
-        <Button buttonType="ghost" onClick={() => shared.setShowCoverSettings(true)}>
-          ⚙️ 封面模板
+        <Button buttonType="ghost" onClick={() => setShowCoverSettings(true)}>
+          ⚙️ 封面设置
         </Button>
-        <Button buttonType="ghost" onClick={shared.handleUploadClick}>
-          📷 本地上传
-        </Button>
-        <input
-          ref={shared.uploadInputRef}
-          type="file"
-          accept="image/*"
-          style={{ display: "none" }}
-          onChange={(e) => {
-            const file = e.target.files?.[0]
-            e.target.value = ""
-            if (!file) return
-            const url = URL.createObjectURL(file)
-            props.onCoverSettingsChange({
-              ...props.coverSettings,
-              upload_url: url,
-              thumbnail_url: url,
-              mode: "upload",
-            })
-          }}
-        />
-        <input
-          ref={batchUploadRef}
-          type="file"
-          accept="image/*"
-          style={{ display: "none" }}
-          onChange={handleBatchUploadChange}
-        />
       </div>
 
       <div className="xx-section-title">封面预览</div>
@@ -387,26 +276,30 @@ const Step6CoverSettings: React.FC<Step6CoverSettingsProps> = (props) => {
       </div>
 
       <CoverSettingsModal
-        open={shared.showCoverSettings}
-        onClose={() => shared.setShowCoverSettings(false)}
-        templates={shared.templates}
-        loading={shared.templatesLoading}
-        error={shared.templatesError}
-        selectedTemplateId={shared.selectedTemplateId}
-        onSelectTemplate={shared.handleSelectTemplate}
-        onEditTemplate={shared.handleEditTemplate}
-        onDeleteTemplate={shared.handleDeleteTemplate}
-        onCreateNew={shared.handleCreateTemplate}
+        open={showCoverSettings}
+        onClose={() => setShowCoverSettings(false)}
+        templates={coverTemplates}
+        loading={templatesLoading}
+        error={templatesError}
+        selectedTemplateId={selectedTemplateId}
+        onSelectTemplate={handleSelectTemplate}
+        onEditTemplate={handleEditTemplate}
+        onDeleteTemplate={handleDeleteTemplate}
+        onCreateNew={() => {
+          setShowCoverSettings(false)
+          setShowCoverEditor(true)
+        }}
       />
 
       <CoverEditorModal
-        open={shared.showCoverEditor}
-        onClose={() => shared.setShowCoverEditor(false)}
-        template={shared.editingTemplate}
-        onSave={shared.handleSaveTemplate}
+        open={showCoverEditor}
+        onClose={() => setShowCoverEditor(false)}
+        template={editingTemplate}
+        onSave={handleSaveTemplate}
       />
 
-      <Modal open={shared.generating} closable={false} footer={null} centered>
+      {/* AI 生成封面进度弹窗 */}
+      <Modal open={generating} closable={false} footer={null} centered>
         <div style={{ textAlign: "center", padding: "24px 0" }}>
           <Spin size="large" />
           <p style={{ marginTop: 16, fontSize: 14, color: "#666" }}>
@@ -418,6 +311,4 @@ const Step6CoverSettings: React.FC<Step6CoverSettingsProps> = (props) => {
   )
 }
 
-Step6CoverSettings.displayName = "Step6CoverSettings"
-
 export default Step6CoverSettings

apps/web/src/pages/generate/components/cover-settings/CoverSettingsModal.tsx

@@ -2,7 +2,6 @@ import React from "react"
 import type { CoverTemplate } from "../../types/cover"
 import Modal from "@/components/ui/Modal"
 import Button from "@/components/ui/Button"
-import "@/components/cover/cover.css"
 
 interface CoverSettingsModalProps {
   open: boolean
@@ -41,26 +40,12 @@ const CoverSettingsModal: React.FC<CoverSettingsModalProps> = ({
   onCreateNew,
 }) => {
   return (
-    <Modal
-      open={open}
-      onCancel={onClose}
-      width={800}
-      title="封面设置"
-      centered
-      footer={
-        <div style={{ display: "flex", justifyContent: "flex-end", gap: 8 }}>
-          <Button buttonType="ghost" onClick={onClose}>
-            取消
-          </Button>
-          <Button buttonType="primary" onClick={onClose}>
-            确认应用
-          </Button>
-        </div>
-      }
-    >
+    <Modal open={open} onCancel={onClose} width={800} title="封面设置" centered footer={null}>
       <div className="xx-cover-modal-toolbar">
+        <Button buttonType="primary">选择素材文件</Button>
+        <Button buttonType="ghost">导出全部</Button>
         <Button buttonType="primary" onClick={onCreateNew}>
-          + 创建新模板
+          创建新模板
         </Button>
       </div>
 
@@ -74,83 +59,52 @@ const CoverSettingsModal: React.FC<CoverSettingsModalProps> = ({
         <div style={{ textAlign: "center", padding: "40px 0", color: "#ef4444" }}>{error}</div>
       )}
 
-      {!loading && !error && templates.length === 0 && (
-        <div
-          style={{
-            textAlign: "center",
-            padding: "40px 0",
-            color: "var(--text-secondary)",
-            fontSize: 13,
-          }}
-        >
-          暂无封面模板，点击右上角「创建新模板」可自定义封面样式
-        </div>
-      )}
-
-      {!loading && !error && templates.length > 0 && (
+      {!loading && !error && (
         <div className="xx-cover-template-grid">
-          {templates.map((tpl) => {
-            const isSelected = selectedTemplateId === tpl.id
-            return (
+          {templates.map((tpl) => (
+            <div
+              key={tpl.id}
+              className={`xx-cover-template-card${selectedTemplateId === tpl.id ? " selected" : ""}`}
+              onClick={() => onSelectTemplate(tpl.id)}
+            >
               <div
-                key={tpl.id}
-                className={`xx-cover-template-card${isSelected ? " selected" : ""}`}
-                onClick={() => onSelectTemplate(tpl.id)}
+                className="xx-cover-template-thumb"
+                style={{ background: GRADIENT_MAP[tpl.id] || GRADIENT_MAP.default }}
               >
-                <div
-                  className="xx-cover-template-thumb"
-                  style={{ background: GRADIENT_MAP[tpl.id] || GRADIENT_MAP.default }}
-                >
-                  {isSelected && <span className="xx-cover-template-check">✓</span>}
-                  🖼️
+                🖼️
+              </div>
+              <div className="xx-cover-template-info">
+                <div className="xx-cover-template-name">
+                  {tpl.name}
+                  {tpl.is_system && <span className="xx-cover-template-badge">✨ 系统模板</span>}
                 </div>
-                <div className="xx-cover-template-info">
-                  <div className="xx-cover-template-name">
-                    {tpl.name}
-                    {tpl.is_system && <span className="xx-cover-template-badge">✨ 系统</span>}
-                  </div>
-                  <div className="xx-cover-template-actions" onClick={(e) => e.stopPropagation()}>
+                <div className="xx-cover-template-date">{tpl.created_at}</div>
+                <div className="xx-cover-template-actions" onClick={(e) => e.stopPropagation()}>
+                  <Button buttonType="ghost" buttonSize="sm" onClick={() => onEditTemplate(tpl)}>
+                    编辑
+                  </Button>
+                  {!tpl.is_system && (
                     <Button
                       buttonType="ghost"
                       buttonSize="sm"
-                      onClick={() => onEditTemplate(tpl)}
-                      title={tpl.is_system ? "基于此模板新建自定义模板" : "编辑模板"}
+                      onClick={() => {
+                        if (confirm("确定删除此模板？")) {
+                          onDeleteTemplate(tpl.id)
+                        }
+                      }}
                     >
-                      {tpl.is_system ? "复制" : "编辑"}
+                      删除
                     </Button>
-                    {!tpl.is_system && (
-                      <Button
-                        buttonType="ghost"
-                        buttonSize="sm"
-                        onClick={() => {
-                          if (confirm("确定删除此模板？")) {
-                            onDeleteTemplate(tpl.id)
-                          }
-                        }}
-                      >
-                        删除
-                      </Button>
-                    )}
-                  </div>
+                  )}
+                  <Button buttonType="ghost" buttonSize="sm">
+                    导出
+                  </Button>
                 </div>
               </div>
-            )
-          })}
+            </div>
+          ))}
         </div>
       )}
-
-      <div
-        style={{
-          marginTop: 12,
-          padding: "8px 12px",
-          background: "rgba(124,58,237,0.06)",
-          borderRadius: 6,
-          fontSize: 12,
-          color: "#6d28d9",
-        }}
-      >
-        💡 点击卡片选中模板后，点击右下角「确认应用」即可使用该模板生成封面
-      </div>
     </Modal>
   )
 }

apps/web/src/pages/generate/generate.css

@@ -2739,7 +2739,6 @@
   justify-content: center;
   font-size: 32px;
   color: #ccc;
-  position: relative;
 }
 
 /* 卡片信息区 */
@@ -3336,451 +3335,3 @@
     grid-template-columns: minmax(0, 360px);
   }
 }
-
-/* ================================================================
-   自定义封面编辑器 (Cover Editor Modal) — xx-ce-*
-   ================================================================ */
-
-/* Header */
-.xx-ce-header {
-  margin-bottom: 16px;
-}
-.xx-ce-name-input {
-  width: 100%;
-  padding: 8px 12px;
-  border: 1px solid var(--border-color, #e5e7eb);
-  border-radius: var(--radius-sm, 6px);
-  font-size: 14px;
-  margin-bottom: 12px;
-  outline: none;
-}
-.xx-ce-name-input:focus {
-  border-color: #7c3aed;
-}
-.xx-ce-header-actions {
-  display: flex;
-  justify-content: flex-end;
-  gap: 8px;
-}
-
-/* Layout */
-.xx-ce-layout {
-  display: flex;
-  gap: 20px;
-  min-height: 500px;
-}
-.xx-ce-left {
-  width: 300px;
-  flex-shrink: 0;
-  max-height: 70vh;
-  overflow-y: auto;
-}
-.xx-ce-right {
-  flex: 1;
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  background: #f5f5f5;
-  border-radius: 8px;
-  min-height: 480px;
-}
-
-/* Section / collapsible panels */
-.xx-ce-section {
-  border: 1px solid var(--border-color, #e5e7eb);
-  border-radius: 6px;
-  margin-bottom: 8px;
-}
-.xx-ce-section-header {
-  padding: 10px 12px;
-  font-size: 13px;
-  font-weight: 600;
-  cursor: pointer;
-  display: flex;
-  align-items: center;
-  justify-content: space-between;
-  background: #f0f4ff;
-  user-select: none;
-}
-.xx-ce-section-header:hover {
-  background: #e8edf8;
-}
-.xx-ce-section-body {
-  padding: 12px;
-  font-size: 12px;
-  color: var(--text-secondary, #666);
-}
-.xx-ce-header-right {
-  display: flex;
-  align-items: center;
-  gap: 6px;
-}
-.xx-ce-status-text {
-  font-size: 11px;
-  font-weight: 400;
-  color: #3b82f6;
-}
-
-/* Rows / labels */
-.xx-ce-row {
-  margin: 12px 0;
-}
-.xx-ce-label {
-  display: block;
-  font-size: 12px;
-  color: #374151;
-  margin-bottom: 4px;
-}
-.xx-ce-hint {
-  font-size: 11px;
-  color: #9ca3af;
-  margin-top: 4px;
-}
-.xx-ce-sub-row {
-  display: flex;
-  align-items: center;
-  justify-content: space-between;
-  margin-top: 8px;
-}
-.xx-ce-switch-row {
-  display: flex;
-  align-items: center;
-  justify-content: space-between;
-}
-.xx-ce-switch-item {
-  margin-bottom: 12px;
-  padding-bottom: 8px;
-  border-bottom: 1px solid #f3f4f6;
-}
-.xx-ce-switch-item:last-child {
-  border-bottom: none;
-  margin-bottom: 0;
-  padding-bottom: 0;
-}
-
-/* Color picker */
-.xx-ce-color-picker {
-  display: flex;
-  align-items: center;
-  gap: 6px;
-}
-.xx-ce-color-picker input[type="color"] {
-  width: 32px;
-  height: 24px;
-  padding: 0;
-  border: 1px solid #d1d5db;
-  border-radius: 4px;
-  cursor: pointer;
-  background: none;
-}
-.xx-ce-color-picker input[type="color"]::-webkit-color-swatch-wrapper {
-  padding: 1px;
-}
-.xx-ce-color-picker input[type="color"]::-webkit-color-swatch {
-  border: none;
-  border-radius: 2px;
-}
-.xx-ce-color-hex {
-  width: 70px;
-  padding: 2px 6px;
-  border: 1px solid #d1d5db;
-  border-radius: 4px;
-  font-size: 12px;
-  font-family: monospace;
-}
-
-/* Position pair */
-.xx-ce-position {
-  display: flex;
-  gap: 8px;
-}
-.xx-ce-position .ant-input-number {
-  flex: 1;
-}
-
-/* Radio button group */
-.xx-ce-radio-group {
-  display: flex;
-  gap: 0;
-}
-.xx-ce-radio-btn {
-  padding: 4px 14px;
-  font-size: 12px;
-  border: 1px solid #d1d5db;
-  background: #fff;
-  color: #374151;
-  cursor: pointer;
-  transition: all 0.15s;
-}
-.xx-ce-radio-btn:first-child {
-  border-radius: 4px 0 0 4px;
-}
-.xx-ce-radio-btn:last-child {
-  border-radius: 0 4px 4px 0;
-}
-.xx-ce-radio-btn + .xx-ce-radio-btn {
-  border-left: none;
-}
-.xx-ce-radio-btn.active {
-  background: #7c3aed;
-  color: #fff;
-  border-color: #7c3aed;
-}
-.xx-ce-radio-btn.active + .xx-ce-radio-btn {
-  border-left: 1px solid #d1d5db;
-}
-
-/* Font select dots */
-.xx-ce-font-dot {
-  display: inline-block;
-  width: 8px;
-  height: 8px;
-  border-radius: 50%;
-  margin-right: 6px;
-  vertical-align: middle;
-}
-.xx-ce-font-dot--preset {
-  background: #10b981;
-}
-.xx-ce-font-dot--system {
-  background: #3b82f6;
-}
-
-/* Shadow actions */
-.xx-ce-shadow-actions {
-  display: flex;
-  gap: 8px;
-  margin-top: 4px;
-}
-.xx-ce-add-shadow-btn {
-  padding: 4px 10px;
-  font-size: 12px;
-  background: #7c3aed;
-  color: #fff;
-  border: none;
-  border-radius: 4px;
-  cursor: pointer;
-}
-.xx-ce-add-shadow-btn:hover {
-  background: #6d28d9;
-}
-.xx-ce-preset-shadow-btn {
-  padding: 4px 10px;
-  font-size: 12px;
-  background: #fff;
-  color: #374151;
-  border: 1px solid #d1d5db;
-  border-radius: 4px;
-  cursor: pointer;
-}
-
-/* Text background sub-section */
-.xx-ce-text-bg-section {
-  margin-top: 8px;
-  padding: 8px;
-  background: #fafafa;
-  border-radius: 4px;
-  border: 1px solid #f0f0f0;
-}
-
-/* Readonly text display */
-.xx-ce-readonly-text {
-  padding: 6px 10px;
-  background: #eff6ff;
-  border-radius: 4px;
-  font-size: 13px;
-  color: #1e40af;
-  margin-bottom: 4px;
-}
-
-/* Mask file row */
-.xx-ce-file-row {
-  display: flex;
-  gap: 6px;
-  align-items: center;
-}
-.xx-ce-file-name {
-  flex: 1;
-  padding: 4px 8px;
-  border: 1px solid #d1d5db;
-  border-radius: 4px;
-  font-size: 12px;
-  background: #f9fafb;
-  color: #6b7280;
-}
-.xx-ce-file-btn {
-  padding: 4px 10px;
-  font-size: 12px;
-  background: #fff;
-  color: #374151;
-  border: 1px solid #d1d5db;
-  border-radius: 4px;
-  cursor: pointer;
-  white-space: nowrap;
-}
-.xx-ce-file-btn:hover {
-  border-color: #7c3aed;
-  color: #7c3aed;
-}
-
-/* ── Canvas / Preview ── */
-.xx-ce-canvas-wrap {
-  position: relative;
-  display: flex;
-  align-items: center;
-  justify-content: center;
-}
-.xx-ce-canvas {
-  width: 225px;
-  height: 400px;
-  background: #ddd;
-  position: relative;
-  border-radius: 8px;
-  overflow: hidden;
-}
-.xx-ce-anchor-dot {
-  position: absolute;
-  width: 8px;
-  height: 8px;
-  background: #ef4444;
-  border-radius: 50%;
-  z-index: 5;
-}
-
-/* Portrait element */
-.xx-ce-el-portrait {
-  position: absolute;
-  background: #a8d4f0;
-  border: 2px solid #333;
-  z-index: 2;
-}
-
-/* 8 handles: 0=TL 1=T 2=TR 3=R 4=BR 5=B 6=BL 7=L */
-.xx-ce-handle {
-  position: absolute;
-  width: 8px;
-  height: 8px;
-  background: #3b82f6;
-  border: 1px solid #fff;
-  z-index: 10;
-}
-.xx-ce-handle--0 {
-  top: -4px;
-  left: -4px;
-}
-.xx-ce-handle--1 {
-  top: -4px;
-  left: 50%;
-  margin-left: -4px;
-}
-.xx-ce-handle--2 {
-  top: -4px;
-  right: -4px;
-}
-.xx-ce-handle--3 {
-  top: 50%;
-  right: -4px;
-  margin-top: -4px;
-}
-.xx-ce-handle--4 {
-  bottom: -4px;
-  right: -4px;
-}
-.xx-ce-handle--5 {
-  bottom: -4px;
-  left: 50%;
-  margin-left: -4px;
-}
-.xx-ce-handle--6 {
-  bottom: -4px;
-  left: -4px;
-}
-.xx-ce-handle--7 {
-  top: 50%;
-  left: -4px;
-  margin-top: -4px;
-}
-
-/* Background element */
-.xx-ce-el-bg {
-  position: absolute;
-  background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-  z-index: 1;
-}
-
-/* Mask overlay */
-.xx-ce-el-mask {
-  position: absolute;
-  inset: 0;
-  z-index: 4;
-  pointer-events: none;
-}
-
-/* Text background shape in canvas */
-.xx-ce-text-bg {
-  position: absolute;
-  z-index: -1;
-}
-
-/* Cover template selected check */
-.xx-cover-template-check {
-  position: absolute;
-  top: 8px;
-  right: 8px;
-  width: 22px;
-  height: 22px;
-  background: #7c3aed;
-  color: #fff;
-  border-radius: 50%;
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  font-size: 14px;
-  font-weight: 700;
-  z-index: 2;
-  box-shadow: 0 2px 6px rgba(124, 58, 237, 0.4);
-}
-.xx-cover-template-thumb {
-  position: relative;
-}
-
-/* Preview tip */
-.xx-ce-preview-tip {
-  text-align: center;
-  margin-top: 12px;
-  font-size: 12px;
-  color: #6b7280;
-}
-
-/* Cover editor modal base gradient */
-.xx-ce-canvas {
-  background: #1a1a2e;
-}
-
-/* Antd Slider overrides for editor */
-.xx-ce-section-body .ant-slider {
-  margin: 4px 0 8px;
-}
-.xx-ce-section-body .ant-slider-rail {
-  background: #e5e7eb;
-}
-.xx-ce-section-body .ant-slider-track {
-  background: #3b82f6;
-}
-.xx-ce-section-body .ant-slider-handle::after {
-  box-shadow: 0 0 0 2px #3b82f6;
-}
-.xx-ce-section-body .ant-slider-mark-text {
-  font-size: 10px;
-}
-
-/* Antd Select dropdown font dots */
-.xx-ce-font-select-dropdown .ant-select-item-option-content {
-  display: flex;
-  align-items: center;
-}
-
-/* Canvas text elements — ensure proper stacking */
-.xx-ce-canvas > div {
-  pointer-events: none;
-}

apps/web/src/pages/generate/hooks/generate-video/useGenerationPolling.ts

@@ -10,7 +10,7 @@ export interface BatchTaskState {
   taskId: string
   /** 变体序号（0-based，与标题/封面数组对齐） */
   variantIndex: number
-  status: "running" | "completed" | "awaiting_cover" | "failed"
+  status: "running" | "completed" | "failed"
   progress: number
   error: string | null
   /** 完成后的成片视频 */
@@ -96,7 +96,7 @@ export function useGenerationPolling({
       runId: number,
       callbacks?: {
         onTaskProgress?: (pct: number) => void
-        onTaskCompleted?: (videos: unknown[], taskStatus?: "completed" | "awaiting_cover") => void
+        onTaskCompleted?: (videos: unknown[]) => void
         onTaskFailed?: (msg: string) => void
       },
     ): Promise<unknown[]> => {
@@ -111,7 +111,7 @@ export function useGenerationPolling({
             if (cancelledRef.current || done) return
             consecutiveErrors = 0
 
-            if (task.status === "completed" || task.status === "awaiting_cover") {
+            if (task.status === "completed") {
               done = true
               const videos = await fetchResultsWithRetry(taskId)
               if (cancelledRef.current) return
@@ -121,7 +121,7 @@ export function useGenerationPolling({
                 reject(new Error(msg))
                 return
               }
-              callbacks?.onTaskCompleted?.(videos, task.status as "completed" | "awaiting_cover")
+              callbacks?.onTaskCompleted?.(videos)
               resolve(videos)
               return
             }
@@ -259,11 +259,10 @@ export function useGenerationPolling({
             onBatchTaskUpdate?.(taskId, { status: "running", progress: pct })
             reportAggregateProgress()
           },
-          onTaskCompleted: (videos, taskStatus) => {
+          onTaskCompleted: (videos) => {
             progressMap.set(taskId, 100)
             resultMap.set(taskId, videos)
-            const _finalStatus: "completed" | "awaiting_cover" = taskStatus ?? "completed"
-            onBatchTaskUpdate?.(taskId, { status: _finalStatus, progress: 100, videos })
+            onBatchTaskUpdate?.(taskId, { status: "completed", progress: 100, videos })
             reportAggregateProgress()
             checkAllSettled()
           },
@@ -294,9 +293,8 @@ export function useGenerationPolling({
       }
       pollSingleTask(taskId, Date.now(), {
         onTaskProgress: (pct) => onBatchTaskUpdate?.(taskId, { status: "running", progress: pct }),
-        onTaskCompleted: (videos, taskStatus) => {
-          const _finalStatus: "completed" | "awaiting_cover" = taskStatus ?? "completed"
-          onBatchTaskUpdate?.(taskId, { status: _finalStatus, progress: 100, videos })
+        onTaskCompleted: (videos) => {
+          onBatchTaskUpdate?.(taskId, { status: "completed", progress: 100, videos })
           message.success(`视频 ${variantIndex + 1} 重试成功`)
         },
         onTaskFailed: (msg) => onBatchTaskUpdate?.(taskId, { status: "failed", error: msg }),

apps/web/src/pages/generate/hooks/useBatchCovers.ts

@@ -53,7 +53,7 @@ interface UseBatchCoversOptions {
 }
 
 export function useBatchCovers({
-  selectedTemplate,
+  selectedTemplate: _selectedTemplate,
   generatedVideos,
   titles,
   titleStyle,
@@ -93,12 +93,7 @@ export function useBatchCovers({
   /** 为第 index 个视频自动生成封面；返回是否成功（供 generateAll 统计） */
   const generateOne = useCallback(
     async (index: number): Promise<boolean> => {
-      const finalVideos = generatedVideos.filter(
-        (v) =>
-          v.status === "completed" ||
-          v.status === "awaiting_cover" ||
-          v.status === "awaiting_cover",
-      )
+      const finalVideos = generatedVideos.filter((v) => v.status === "completed")
       const target = finalVideos[index] || generatedVideos[index]
       if (!target) {
         message.warning("该视频尚未生成完成")
@@ -107,7 +102,7 @@ export function useBatchCovers({
       addBusy(index)
       try {
         const titleText = titles[index] || ""
-        const response = await generateCover(selectedTemplate || "default", {
+        const response = await generateCover("default", {
           generated_video_id: target.id,
           video_url: target.file_url || target.download_url || "",
           cover_type: "ai_frame",
@@ -171,7 +166,7 @@ export function useBatchCovers({
         removeBusy(index)
       }
     },
-    [generatedVideos, titles, titleStyle, selectedTemplate, patchCover, addBusy, removeBusy],
+    [generatedVideos, titles, titleStyle, patchCover, addBusy, removeBusy],
   )
 
   /** 为第 index 个视频上传自定义封面 */
@@ -208,10 +203,7 @@ export function useBatchCovers({
 
   /** 一键全部自动生成（串行，避免队列限流；单个失败不阻塞，结束后分级提示） */
   const generateAll = useCallback(async () => {
-    const finalVideos = generatedVideos.filter(
-      (v) =>
-        v.status === "completed" || v.status === "awaiting_cover" || v.status === "awaiting_cover",
-    )
+    const finalVideos = generatedVideos.filter((v) => v.status === "completed")
     const total = finalVideos.length
     // 待处理：基于调用时刻的 covers 快照判断（已有封面跳过）；
     // 回写走函数式 updater，循环内不再依赖可能过期的 covers 闭包

apps/web/src/pages/generate/hooks/useGenerateVideo.ts

@@ -58,7 +58,7 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
       // 批量：成功任务的 videos 已通过 onBatchTaskUpdate 写入，这里同步兜底
       setBatchTasks((prev) =>
         (prev || []).map((t) =>
-          t.status === "completed" || (t.status === "awaiting_cover" && t.videos.length === 0)
+          t.status === "completed" && t.videos.length === 0
             ? {
                 ...t,
                 videos: (videos as GeneratedVideo[]).filter(
@@ -83,10 +83,7 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
     if (batchTasks.length === 0) return
     const byVariant = new Map<number, GeneratedVideo>()
     batchTasks.forEach((t) => {
-      if (
-        t.status === "completed" ||
-        (t.status === "awaiting_cover" && t.videos && t.videos.length > 0)
-      ) {
+      if (t.status === "completed" && t.videos && t.videos.length > 0) {
         byVariant.set(t.variantIndex, t.videos[0] as GeneratedVideo)
       }
     })

apps/web/src/pages/generate/hooks/useStep6Cover.ts

@@ -48,11 +48,7 @@ export function useStep6Cover({
   const [templatesError, setTemplatesError] = useState<string | null>(null)
 
   /** 最终成片：取第一个已完成视频 */
-  const finalVideo =
-    generatedVideos.find(
-      (v) =>
-        v.status === "completed" || v.status === "awaiting_cover" || v.status === "awaiting_cover",
-    ) || generatedVideos[0]
+  const finalVideo = generatedVideos.find((v) => v.status === "completed") || generatedVideos[0]
 
   /** 从后端加载封面模板列表 */
   const loadTemplates = useCallback(async () => {
@@ -175,18 +171,7 @@ export function useStep6Cover({
   }, [])
 
   const handleEditTemplate = useCallback((tpl: CoverTemplate) => {
-    // 系统模板不可修改：复制为新模板草稿，走"另存为"流程
-    if (tpl.is_system) {
-      setEditingTemplate({
-        ...tpl,
-        id: "",
-        name: tpl.name + " 副本",
-        is_system: false,
-        created_at: "",
-      })
-    } else {
-      setEditingTemplate(tpl)
-    }
+    setEditingTemplate(tpl)
     setShowCoverEditor(true)
   }, [])
 
@@ -194,25 +179,20 @@ export function useStep6Cover({
   const handleSaveTemplate = useCallback(
     async (tpl: CoverTemplate) => {
       try {
-        // 系统模板或无 id（新建/副本）→ 走创建分支；否则走更新
-        const isSystem = coverTemplates.find((t) => t.id === tpl.id)?.is_system === true
-        const shouldCreate = !tpl.id || isSystem
-        if (shouldCreate) {
-          const created = await createCoverTemplate({
-            name: tpl.name || "我的封面模板",
-            config: tpl.config,
-          })
-          setCoverTemplates((prev) => [...prev, created])
-          setSelectedTemplateId(created.id || tpl.id)
-        } else {
+        if (tpl.id && coverTemplates.some((t) => t.id === tpl.id)) {
           const updated = await updateCoverTemplate(tpl.id, {
             name: tpl.name,
             config: tpl.config,
           })
           setCoverTemplates((prev) => prev.map((t) => (t.id === tpl.id ? { ...t, ...updated } : t)))
+        } else {
+          const created = await createCoverTemplate({
+            name: tpl.name,
+            config: tpl.config,
+          })
+          setCoverTemplates((prev) => [...prev, created])
         }
         setShowCoverEditor(false)
-        setEditingTemplate(null)
       } catch (err) {
         console.error("[Step6] 保存模板失败:", err)
       }

apps/web/src/pages/generate/types/cover.ts

@@ -32,241 +32,6 @@ export const DEFAULT_COVER_CONFIG: CoverConfig = {
   thumbnail_url: "",
 }
 
-/** 文字方向 */
-export type TextDirection = "horizontal" | "vertical"
-
-/** 文字背景形状 */
-export type TextBgShape = "rectangle" | "polygon"
-
-/** 描边样式 */
-export type StrokeStyle = "solid" | "dashed"
-
-/** 阴影层 */
-export interface ShadowLayer {
-  color: string
-  offsetX: number
-  offsetY: number
-  blur: number
-}
-
-/** 文字位置 */
-export interface TextPosition {
-  x: number
-  y: number
-}
-
-/** 文字背景配置 */
-export interface TextBackground {
-  enabled: boolean
-  color: string
-  opacity: number
-  shape: TextBgShape
-  width: number
-  height: number
-  posX: number
-  posY: number
-  rotation: number
-}
-
-/** 文字样式配置（主标题/副标题共用） */
-export interface TextStyleConfig {
-  text: string
-  fontFamily: string
-  fontSize: number
-  fontWeight: number
-  direction: TextDirection
-  charsPerLine: number
-  letterSpacing: number
-  lineHeight: number
-  color: string
-  strokeColor: string
-  strokeWidth: number
-  shadows: ShadowLayer[]
-  traditionalShadow: boolean
-  position: TextPosition
-  rotation: number
-  background: TextBackground
-}
-
-/** 编辑器完整配置 */
-export interface CoverEditorConfig {
-  // 基础设置
-  blurEnabled: boolean
-  blurAmount: number
-  personStrokeEnabled: boolean
-  personStrokeStyle: StrokeStyle
-  personStrokeColor: string
-  personStrokeWidth: number
-  autoSplitEnabled: boolean
-  titleMaxChars: number
-  subtitleMaxChars: number
-
-  // 人像设置
-  portraitEnabled: boolean
-  portraitSize: number
-  portraitPosition: TextPosition
-  portraitImage?: string
-
-  // 背景设置
-  backgroundEnabled: boolean
-  backgroundSize: number
-  backgroundPosition: TextPosition
-  backgroundImage?: string
-  backgroundColor?: string
-
-  // 主标题
-  title: TextStyleConfig
-
-  // 副标题
-  subtitle: TextStyleConfig
-
-  // 蒙版
-  maskEnabled: boolean
-  maskImage: string
-  maskSize: number
-  maskPosition: TextPosition
-  maskColor: string
-  maskOpacity: number
-  maskShape: string
-}
-
-/** 默认主标题配置 */
-export const DEFAULT_TITLE_CONFIG: TextStyleConfig = {
-  text: "主标题文字",
-  fontFamily: "思源黑体",
-  fontSize: 120,
-  fontWeight: 700,
-  direction: "horizontal",
-  charsPerLine: 10,
-  letterSpacing: 24,
-  lineHeight: 144,
-  color: "#FFD700",
-  strokeColor: "#000000",
-  strokeWidth: 3,
-  shadows: [],
-  traditionalShadow: false,
-  position: { x: 50, y: 30 },
-  rotation: 0,
-  background: {
-    enabled: false,
-    color: "#FFFFFF",
-    opacity: 25,
-    shape: "polygon",
-    width: 30,
-    height: 10,
-    posX: 50,
-    posY: 50,
-    rotation: 0,
-  },
-}
-
-/** 默认副标题配置 */
-export const DEFAULT_SUBTITLE_CONFIG: TextStyleConfig = {
-  text: "副标题文字",
-  fontFamily: "思源黑体",
-  fontSize: 82,
-  fontWeight: 500,
-  direction: "horizontal",
-  charsPerLine: 17,
-  letterSpacing: 23,
-  lineHeight: 72,
-  color: "#FFFFFF",
-  strokeColor: "#000000",
-  strokeWidth: 1,
-  shadows: [],
-  traditionalShadow: false,
-  position: { x: 50, y: 70 },
-  rotation: 0,
-  background: {
-    enabled: true,
-    color: "#000000",
-    opacity: 70,
-    shape: "rectangle",
-    width: 100,
-    height: 20,
-    posX: 50,
-    posY: 80,
-    rotation: 0,
-  },
-}
-
-/** 默认编辑器配置 */
-export const DEFAULT_EDITOR_CONFIG: CoverEditorConfig = {
-  blurEnabled: false,
-  blurAmount: 10,
-  personStrokeEnabled: false,
-  personStrokeStyle: "solid",
-  personStrokeColor: "#FFFFFF",
-  personStrokeWidth: 8,
-  autoSplitEnabled: false,
-  titleMaxChars: 4,
-  subtitleMaxChars: 10,
-
-  portraitEnabled: false,
-  portraitSize: 50,
-  portraitPosition: { x: 50, y: 70 },
-
-  backgroundEnabled: true,
-  backgroundSize: 100,
-  backgroundPosition: { x: 50, y: 50 },
-
-  title: DEFAULT_TITLE_CONFIG,
-  subtitle: DEFAULT_SUBTITLE_CONFIG,
-
-  maskEnabled: false,
-  maskImage: "",
-  maskSize: 100,
-  maskPosition: { x: 50, y: 50 },
-  maskColor: "#000000",
-  maskOpacity: 40,
-  maskShape: "矩形",
-}
-
-/** 预置字体 */
-export const PRESET_FONTS = [
-  { name: "思源黑体", family: "'Noto Sans SC', sans-serif" },
-  { name: "斗鱼追光体2.0", family: "'DouYu ZhuangGuangTi', sans-serif" },
-  { name: "抖音美好体", family: "'DouYin MeiHaoTi', sans-serif" },
-]
-
-/** 系统字体 */
-export const SYSTEM_FONTS = [
-  { name: "Arial", family: "Arial, sans-serif" },
-  { name: "Helvetica", family: "Helvetica, sans-serif" },
-  { name: "Times New Roman", family: "'Times New Roman', serif" },
-  { name: "Georgia", family: "Georgia, serif" },
-  { name: "Verdana", family: "Verdana, sans-serif" },
-  { name: "Tahoma", family: "Tahoma, sans-serif" },
-  { name: "Impact", family: "Impact, sans-serif" },
-  { name: "Comic Sans MS", family: "'Comic Sans MS', cursive" },
-  { name: "Courier New", family: "'Courier New', monospace" },
-  { name: "微软雅黑", family: "'Microsoft YaHei', sans-serif" },
-  { name: "宋体", family: "SimSun, serif" },
-  { name: "黑体", family: "SimHei, sans-serif" },
-  { name: "楷体", family: "KaiTi, serif" },
-  { name: "仿宋", family: "FangSong, serif" },
-  { name: "Trebuchet MS", family: "'Trebuchet MS', sans-serif" },
-  { name: "Lucida Console", family: "'Lucida Console', monospace" },
-  { name: "Palatino", family: "Palatino, serif" },
-  { name: "Garamond", family: "Garamond, serif" },
-  { name: "Bookman", family: "Bookman, serif" },
-  { name: "Avant Garde", family: "'Avant Garde', sans-serif" },
-  { name: "Calibri", family: "Calibri, sans-serif" },
-  { name: "Cambria", family: "Cambria, serif" },
-  { name: "Candara", family: "Candara, sans-serif" },
-  { name: "Consolas", family: "Consolas, monospace" },
-  { name: "Constantia", family: "Constantia, serif" },
-  { name: "Corbel", family: "Corbel, sans-serif" },
-  { name: "Franklin Gothic", family: "'Franklin Gothic', sans-serif" },
-  { name: "Gill Sans", family: "'Gill Sans', sans-serif" },
-  { name: "Optima", family: "Optima, sans-serif" },
-  { name: "Futura", family: "Futura, sans-serif" },
-  { name: "Rockwell", family: "Rockwell, serif" },
-]
-
-/** 所有字体列表 */
-export const ALL_FONTS = [...PRESET_FONTS, ...SYSTEM_FONTS]
-
 /** 封面模板 */
 export interface CoverTemplate {
   id: string
@@ -274,5 +39,12 @@ export interface CoverTemplate {
   thumbnail_url: string
   is_system: boolean
   created_at: string
-  config?: CoverEditorConfig
+  config?: {
+    background_enabled?: boolean
+    background_color?: string
+    portrait_enabled?: boolean
+    title_text?: string
+    subtitle_text?: string
+    mask_enabled?: boolean
+  }
 }

apps/worker/video_processing/dedup.py

@@ -345,32 +345,6 @@ class VideoFingerprint:
             ],
         }
 
-    @classmethod
-    def from_dict(cls, data: dict) -> "VideoFingerprint":
-        """从 to_dict() 序列化结果重建 VideoFingerprint（供 finalize 复用 worker 预计算指纹）。"""
-
-        chunks_raw = data.get("chunks") or []
-        chunks: list[FingerprintChunk] = []
-        for c in chunks_raw:
-            chunks.append(
-                FingerprintChunk(
-                    start_time_ms=int(c.get("start_time_ms", 0)),
-                    end_time_ms=int(c.get("end_time_ms", 0)),
-                    phash_binary=str(c.get("phash_binary", "")),
-                    color_histogram=[float(v) for v in (c.get("color_histogram") or [])],
-                    frame_count=int(c.get("frame_count", 0)),
-                )
-            )
-        resolution_raw = data.get("resolution") or [1280, 720]
-        return cls(
-            md5=str(data.get("md5", "")),
-            keyframe_phashes=list(data.get("keyframe_phashes") or []),
-            color_histograms=[[float(v) for v in h] for h in (data.get("color_histograms") or [])],
-            duration=float(data.get("duration") or 0.0),
-            resolution=(int(resolution_raw[0]), int(resolution_raw[1])) if len(resolution_raw) >= 2 else (1280, 720),
-            chunks=chunks,
-        )
-
     def to_chunk_models(self, video_id: str, project_id: str, user_id: str = "") -> list[VideoFingerprintChunkModel]:
         """将分片数据转为 SQLAlchemy Model 列表，用于批量写入 video_fingerprint_chunks 表。"""
         models = []

apps/worker/video_processing/dedup_helpers.py

@@ -1,15 +1,10 @@
-"""查重辅助函数 — 渲染阶段指纹/查重预计算 + 兼容旧入库函数。
+"""查重辅助函数 — 从 generation.py 提取的 GeneratedVideo 记录 + 查重逻辑.
 
-#2024: Worker 渲染+上传完成后**不直接创建 GeneratedVideo 成品记录**，改为：
-1. ``compute_render_fingerprint_and_dedup``: 从本地视频计算指纹+查重（历史+批次），
-   返回可序列化 dict（含 fingerprint_chunks），由 worker 写入
-   ``GenerationTask.extra_meta["rendered_output"]``；
-2. ``create_video_record_and_dedup``: 保留兼容——当传入 ``video_path`` 时会从本地视频
-   计算指纹+查重并直接创建 GeneratedVideo 记录（供测试/旧路径使用）；
-   当仅传 ``pre_dedup_result`` 时复用预计算结果，不再访问本地视频。
+供 generate_video 共同复用，
+创建 GeneratedVideo 记录后计算指纹并执行项目级 + 批次内查重。
 
-finalize 入口走 ``packages/application/generated_video_finalize.py`` 的
-``finalize_generated_video``，不依赖本模块中数据库以外的 worker-only 逻辑。
+v2: 两阶段持久化 — 先计算所有查重数据，再一次性 commit，
+避免中间异常导致 duplicate_rate 等字段缺失。
 """
 
 from __future__ import annotations
@@ -22,149 +17,6 @@ from sqlalchemy.orm import Session
 logger = logging.getLogger(__name__)
 
 
-def _safe_parse_fps(raw) -> float:
-    if raw is None:
-        return 25.0
-    if isinstance(raw, (int, float)):
-        return float(raw)
-    s = str(raw).strip()
-    if "/" in s:
-        try:
-            num, den = s.split("/", 1)
-            return float(num) / float(den) if float(den) != 0 else 25.0
-        except (ValueError, ZeroDivisionError):
-            pass
-    try:
-        return float(s)
-    except (ValueError, TypeError):
-        return 25.0
-
-
-def _compute_from_local(
-    *,
-    video_path: str,
-    generation_task_id: str,
-    project_id: str,
-    user_id: str,
-    batch_id: str,
-    session: Session,
-) -> dict:
-    """从本地视频计算指纹+查重，返回可序列化结果 dict（不创建 DB 记录）。"""
-    from video_processing.dedup import VideoDeduplicator
-    from video_processing.ffmpeg_utils import probe_video_info
-
-    result: dict = {
-        "fingerprint_dict": None,
-        "fingerprint_chunks": None,
-        "duration": 0.0,
-        "width": 1280,
-        "height": 720,
-        "fps": 25.0,
-        "is_duplicate": False,
-        "duplicate_of": None,
-        "duplicate_rate": None,
-        "match_count": None,
-        "visual_similarity": None,
-        "video_fingerprint_md5": "",
-        "batch_similarity": None,
-    }
-    try:
-        info = probe_video_info(video_path)
-        result["duration"] = float(info.get("duration") or 0.0)
-        result["width"] = int(info.get("width") or 1280)
-        result["height"] = int(info.get("height") or 720)
-        result["fps"] = _safe_parse_fps(info.get("fps"))
-    except Exception as info_err:
-        logger.warning("probe_video_info failed for task %s: %s", generation_task_id, info_err)
-
-    try:
-        deduplicator = VideoDeduplicator()
-        fingerprint = deduplicator.compute_fingerprint(video_path)
-        fp_dict = fingerprint.to_dict()
-        result["fingerprint_dict"] = fp_dict
-        result["video_fingerprint_md5"] = fingerprint.md5 or ""
-        result["fingerprint_chunks"] = [
-            {
-                "start_time_ms": c.start_time_ms,
-                "end_time_ms": c.end_time_ms,
-                "phash_binary": c.phash_binary,
-                "color_histogram": [float(v) for v in c.color_histogram],
-                "frame_count": c.frame_count,
-            }
-            for c in fingerprint.chunks
-        ]
-
-        # 用 placeholder_id 占位（还没有真正的 video_id，不影响查重逻辑——
-        # 因为查重排除的是 GeneratedVideo 表中的记录）
-        placeholder_id = f"pre-{generation_task_id}"
-        duration_sec = fingerprint.duration if fingerprint.duration else 0
-        duplicate_result = deduplicator.check_duplicate(
-            fingerprint,
-            project_id,
-            session,
-            scope="user",
-            user_id=user_id,
-            duration_sec=duration_sec,
-            exclude_video_id=placeholder_id,
-        )
-        batch_sim: float | None = None
-        if not duplicate_result and batch_id:
-            duplicate_result = deduplicator.check_batch_duplicate(fingerprint, batch_id, placeholder_id, session)
-            if duplicate_result:
-                batch_sim = float(duplicate_result.get("similarity", 0.0))
-        result["batch_similarity"] = batch_sim
-        if duplicate_result:
-            result["is_duplicate"] = True
-            result["duplicate_of"] = duplicate_result["duplicate_of"]
-        else:
-            result["is_duplicate"] = False
-
-        try:
-            rate_result = deduplicator.compute_duplicate_rate(
-                fingerprint,
-                project_id,
-                placeholder_id,
-                session,
-                scope="user",
-                user_id=user_id,
-            )
-            result["duplicate_rate"] = rate_result.get("duplicate_rate")
-            result["match_count"] = rate_result.get("match_count")
-            result["visual_similarity"] = rate_result.get("visual_similarity")
-        except Exception as rate_err:
-            logger.warning("compute_duplicate_rate failed for task %s: %s", generation_task_id, rate_err)
-    except Exception as fp_err:
-        logger.warning("Fingerprint compute failed for task %s: %s", generation_task_id, fp_err)
-
-    return result
-
-
-def compute_render_fingerprint_and_dedup(
-    *,
-    video_path: str,
-    generation_task_id: str,
-    project_id: str,
-    user_id: str,
-    batch_id: str,
-    mode: str,
-    session: Session,
-) -> dict:
-    """渲染+上传完成后的预计算：计算指纹+历史/批次查重，返回可序列化 dict。
-
-    **不创建 GeneratedVideo 记录**。结果由调用方写入 extra_meta["rendered_output"]，
-    finalize 时复用。mode 参数保留签名一致性（查重结果中不直接使用）。
-    """
-    _ = mode  # 保留在签名里便于调用方对齐；查重结果不含 mode
-    return _compute_from_local(
-        video_path=video_path,
-        generation_task_id=generation_task_id,
-        project_id=project_id,
-        user_id=user_id,
-        batch_id=batch_id,
-        session=session,
-    )
-
-
 def create_video_record_and_dedup(
     *,
     generation_task_id: str,
@@ -173,8 +25,8 @@ def create_video_record_and_dedup(
     batch_id: str,
     file_url: str,
     file_size: int,
-    duration: float | None = None,
-    video_path: str | None,
+    duration: float,
+    video_path: str,
     mode: str,
     session: Session,
     width: int = 1280,
@@ -182,55 +34,30 @@ def create_video_record_and_dedup(
     fps: float = 25.0,
     name: str = "",
     thumbnail_url: str = "",
-    pre_fingerprint_dict: dict | None = None,
-    pre_fingerprint_chunks: list[dict] | None = None,
-    pre_dedup_result: dict | None = None,
 ) -> dict:
-    """创建 GeneratedVideo 记录 + 可选查重。
+    """Returns: {"video_count": int, "is_duplicate": bool, "batch_similarity": float|None,
+    "duplicate_of": str|None} —— batch_similarity 为批次内最高相似度（无批次查重时 None）。"""
+    """创建 GeneratedVideo 记录，计算指纹并执行查重（历史 + 批次）。
 
-    两种用法：
-    - 传入 ``video_path``（非 None）：从本地视频计算指纹+查重，直接创建记录（旧路径/测试）。
-    - 仅传入 ``pre_*``：复用 worker 预计算结果，不访问本地视频（finalize 用）。
+    采用两阶段持久化：先计算所有指纹/查重数据（内存），
+    再一次性写入数据库并 commit。若指纹计算失败，
+    视频记录仍会创建（无查重数据），但保证不会出现"写了记录却没 commit"的中间态。
 
     Returns:
-        {"video_id", "video_count", "is_duplicate", "batch_similarity", "duplicate_of"}
+        创建的视频记录数量（1 表示成功，0 表示失败）
     """
+    from video_processing.dedup import VideoDeduplicator, _save_fingerprint_chunks
+
     from packages.adapters.sqlalchemy_impl.generated_video_repository import (
         SQLAlchemyGeneratedVideoRepository,
     )
-    from packages.adapters.sqlalchemy_impl.models import VideoFingerprintChunkModel
-    from packages.domain.generated_video import GeneratedVideo
+    from packages.domain import GeneratedVideo
 
     try:
         video_id = uuid4().hex
         video_name = name.strip() if name else f"generated-{generation_task_id[:8]}.mp4"
 
-        # 决定查重/元信息来源
-        if video_path:
-            pre = _compute_from_local(
-                video_path=video_path,
-                generation_task_id=generation_task_id,
-                project_id=project_id,
-                user_id=user_id,
-                batch_id=batch_id,
-                session=session,
-            )
-        else:
-            pre = dict(pre_dedup_result or {})
-            pre.setdefault("fingerprint_dict", pre_fingerprint_dict)
-            pre.setdefault("fingerprint_chunks", pre_fingerprint_chunks)
-            pre.setdefault("is_duplicate", False)
-            pre.setdefault("duplicate_of", None)
-            pre.setdefault("duplicate_rate", None)
-            pre.setdefault("match_count", None)
-            pre.setdefault("visual_similarity", None)
-            pre.setdefault("batch_similarity", None)
-
-        used_duration = float(duration if duration is not None else pre.get("duration", 0.0))
-        used_width = int(pre.get("width", width) or width)
-        used_height = int(pre.get("height", height) or height)
-        used_fps = float(pre.get("fps", fps) or fps)
-
+        # ── Phase 1: 构建视频记录（内存，不 commit） ────────────────
         generated_video = GeneratedVideo(
             id=video_id,
             project_id=project_id,
@@ -239,66 +66,117 @@ def create_video_record_and_dedup(
             name=video_name,
             file_url=file_url,
             file_size=file_size,
-            duration=used_duration,
-            width=used_width,
-            height=used_height,
-            fps=used_fps,
+            duration=duration,
+            width=width,
+            height=height,
+            fps=fps,
             status="completed",
             generation_params={"mode": mode},
             thumbnail_url=thumbnail_url or None,
-            video_fingerprint=pre.get("fingerprint_dict"),
-            is_duplicate=bool(pre.get("is_duplicate", False)),
-            duplicate_of=pre.get("duplicate_of"),
-            duplicate_rate=pre.get("duplicate_rate"),
-            match_count=pre.get("match_count"),
-            visual_similarity=pre.get("visual_similarity"),
         )
 
-        # 写分片指纹表
-        chunks = pre.get("fingerprint_chunks")
-        if chunks:
+        # ── Phase 2: 计算指纹 & 查重（全部在内存） ────────────────
+        deduplicator = VideoDeduplicator()
+        fingerprint = None
+        batch_similarity: float | None = None
+
+        try:
+            fingerprint = deduplicator.compute_fingerprint(video_path)
+        except Exception as fp_err:
+            logger.warning("Fingerprint computation failed for %s: %s", video_id, fp_err)
+
+        if fingerprint is not None:
+            generated_video.video_fingerprint = fingerprint.to_dict()
+
+            # 写入分片指纹表（失败不阻塞）
             try:
-                chunk_models = [
-                    VideoFingerprintChunkModel(
-                        id=uuid4().hex,
-                        video_id=video_id,
-                        project_id=project_id,
-                        user_id=user_id,
-                        start_time_ms=int(c.get("start_time_ms", 0)),
-                        end_time_ms=int(c.get("end_time_ms", 0)),
-                        phash_binary=str(c.get("phash_binary", "")),
-                        color_histogram=[float(v) for v in (c.get("color_histogram") or [])],
-                        frame_count=int(c.get("frame_count", 0)),
-                    )
-                    for c in chunks
-                    if isinstance(c, dict)
-                ]
-                if chunk_models:
-                    # 幂等：先清理旧分片
-                    session.query(VideoFingerprintChunkModel).filter(
-                        VideoFingerprintChunkModel.video_id == video_id
-                    ).delete(synchronize_session=False)
-                    session.bulk_save_objects(chunk_models)
+                _save_fingerprint_chunks(fingerprint, video_id, project_id, user_id, session)
             except Exception as chunk_err:
                 logger.warning("Failed to save fingerprint chunks for %s: %s", video_id, chunk_err)
 
-        repo = SQLAlchemyGeneratedVideoRepository(session)
-        repo.create(generated_video)
+            # (a) 历史成片查重（跨项目全局 + 时长预过滤）
+            # Issue #1702: fingerprint.duration 单位是秒，旧代码 /1000 让时长预过滤失效
+            duration_sec = fingerprint.duration if fingerprint.duration else 0
+            duplicate_result = deduplicator.check_duplicate(
+                fingerprint,
+                project_id,
+                session,
+                scope="user",
+                user_id=user_id,
+                duration_sec=duration_sec,
+                exclude_video_id=video_id,
+            )
+
+            # (b) 批次内查重（仅当有 batch_id 时）
+            batch_similarity: float | None = None
+            if not duplicate_result and batch_id:
+                duplicate_result = deduplicator.check_batch_duplicate(fingerprint, batch_id, video_id, session)
+                if duplicate_result:
+                    batch_similarity = float(duplicate_result.get("similarity", 0.0))
+            if duplicate_result:
+                generated_video.is_duplicate = True
+                generated_video.duplicate_of = duplicate_result["duplicate_of"]
+                logger.info(
+                    "Duplicate detected: %s -> %s (reason=%s, similarity=%.3f)",
+                    video_id,
+                    duplicate_result["duplicate_of"],
+                    duplicate_result["reason"],
+                    duplicate_result["similarity"],
+                )
+            else:
+                generated_video.is_duplicate = False
+                generated_video.duplicate_of = None
+
+            # 计算重复率百分比（跨项目全局）
+            try:
+                rate_result = deduplicator.compute_duplicate_rate(
+                    fingerprint,
+                    project_id,
+                    video_id,
+                    session,
+                    scope="user",
+                    user_id=user_id,
+                )
+                generated_video.duplicate_rate = rate_result["duplicate_rate"]
+                generated_video.match_count = rate_result["match_count"]
+                generated_video.visual_similarity = rate_result["visual_similarity"]
+                logger.info(
+                    "Duplicate rate for %s: %.2f%% (visual_sim=%.3f, matches=%d)",
+                    video_id,
+                    rate_result["duplicate_rate"],
+                    rate_result["visual_similarity"],
+                    rate_result["match_count"],
+                )
+            except Exception as rate_err:
+                logger.warning("Failed to compute duplicate_rate for %s: %s", video_id, rate_err)
+                generated_video.duplicate_rate = None
+
+        # ── Phase 3: 一次性持久化 ─────────────────────────────────
+        video_repo = SQLAlchemyGeneratedVideoRepository(session)
+        video_repo.create(generated_video)
+
+        if thumbnail_url:
+            logger.info("Thumbnail set for video %s: %s", video_id, thumbnail_url[:80])
+
         session.commit()
+        logger.info(
+            "GeneratedVideo record created: %s (task=%s, dup=%s, rate=%s)",
+            video_id,
+            generation_task_id,
+            generated_video.is_duplicate,
+            generated_video.duplicate_rate,
+        )
         return {
-            "video_id": video_id,
             "video_count": 1,
-            "is_duplicate": bool(pre.get("is_duplicate", False)),
-            "batch_similarity": pre.get("batch_similarity"),
-            "duplicate_of": pre.get("duplicate_of"),
+            "is_duplicate": bool(generated_video.is_duplicate),
+            "batch_similarity": batch_similarity,
+            "duplicate_of": generated_video.duplicate_of,
         }
     except Exception as e:
-        logger.error("Failed to create video record for task %s: %s", generation_task_id, e)
+        logger.error(
+            "Failed to create video record / dedup for task %s: %s",
+            generation_task_id,
+            e,
+        )
         session.rollback()
-        return {
-            "video_id": "",
-            "video_count": 0,
-            "is_duplicate": False,
-            "batch_similarity": None,
-            "duplicate_of": None,
-        }
+        return {"video_count": 0, "is_duplicate": False, "batch_similarity": None, "duplicate_of": None}

apps/worker/video_processing/unified_render_service.py

@@ -2384,9 +2384,6 @@ class UnifiedRenderService:
         return _clip_playback_speed_pure(getattr(clip, "playback_speed", 1.0))
 
     def _get_visual_perturbation(self) -> dict:
-        # #2034：dedup_enabled=False 时跳过视觉/像素扰动（与 edge_crop、micro_transform 一致）
-        if not self._dedup_enabled():
-            return {}
         # 读取当前 plan 的视觉扰动参数（plan.config.visual_perturbation）
         perturbation = (self.plan.config or {}).get("visual_perturbation") or {}
         if not perturbation:

apps/worker/worker_app/celery_app.py

@@ -31,7 +31,6 @@ celery_app.conf.imports = (
     # #1970 片段级 AI 标签：必须显式 import 注册，否则 worker 报
     # "Received unregistered task of type 'worker.tag_atom_clip'"
     "worker_app.tasks.atom_clip_tagging",
-    "worker_app.tasks.asset_quality_scoring_task",
     "worker_app.tasks.backfill_atom_clip_tags",
     "worker_app.tasks.classification",
     "worker_app.tasks.generation",

apps/worker/worker_app/tasks/asset_analyzer.py

@@ -445,3 +445,22 @@ def classify_asset_real(video_path: str) -> tuple[str, float]:
     except Exception as e:
         logger.warning(f"Classification failed, using fallback: {e}")
         return AssetClassification.OTHER.value, 0.3
+
+
+def calculate_quality_score_real(video_path: str) -> float:
+    """
+    质量评分入口函数
+
+    Args:
+        video_path: 视频文件路径
+
+    Returns:
+        质量评分 (0-100)
+    """
+    try:
+        analyzer = AssetAnalyzer(video_path)
+        result = analyzer.calculate_quality_score()
+        return result.total
+    except Exception as e:
+        logger.warning(f"Quality scoring failed, using fallback: {e}")
+        return 50.0

apps/worker/worker_app/tasks/asset_quality_scoring_task.py

@@ -1,143 +0,0 @@
-"""素材质量评分 Celery 任务 — #2035.
-
-视频素材 READY 入库后异步触发：下载视频到临时文件，运行 FFmpeg+NumPy 质量分析，
-将 0-100 总分写入 assets.quality_score 字段。同时复用已下载的视频，调用 AssetAnalyzer
-完成 9 类素材分类（写入 asset.metadata.classification / classification_confidence），
-供 smart_match 选片打分使用。任一环节失败均不阻断主流程（质量分兜底 50，分类降级 "other"）。
-
-任务名：worker.calculate_asset_quality
-"""
-
-from __future__ import annotations
-
-import tempfile
-from pathlib import Path
-
-from celery.utils.log import get_task_logger
-from worker_app.celery_app import celery_app
-from worker_app.db import SessionLocal
-
-from packages.adapters.sqlalchemy_impl.asset_repository import SQLAlchemyAssetRepository
-from packages.shared.storage import get_shared_storage_service
-
-logger = get_task_logger(__name__)
-
-
-@celery_app.task(name="worker.calculate_asset_quality", bind=True, max_retries=1, default_retry_delay=15)
-def calculate_asset_quality_task(self, asset_id: str) -> dict:
-    """为单个视频素材计算质量评分并写回 assets.quality_score。
-
-    流程：
-    1. 下载视频到临时文件；
-    2. 用 AssetAnalyzer(FFmpeg+NumPy) 提取分辨率/帧率/码率/清晰度/稳定性 5 维分数；
-    3. 写回 assets.quality_score；
-    4. 复用同一临时文件，调用 AssetAnalyzer.classify() 做 9 类素材分类，
-       结果写入 asset.metadata.classification / classification_confidence；
-       如已有分类结果则幂等跳过（避免重复计算）。
-
-    失败/非视频/无文件等情况均静默降级，返回 status=skipped/failed 不抛异常。
-    """
-    db = SessionLocal()
-    tmp_dir = tempfile.mkdtemp(prefix="quality_score_")
-    try:
-        asset_repo = SQLAlchemyAssetRepository(db)
-        asset = asset_repo.find_by_id(asset_id)
-        if asset is None:
-            return {"status": "skipped", "reason": "asset not found", "asset_id": asset_id}
-        if not (getattr(asset, "mime_type", "") or "").startswith("video/"):
-            return {"status": "skipped", "reason": "not a video", "asset_id": asset_id}
-        # 已有质量分则幂等跳过（重新计算需显式置空）
-        if getattr(asset, "quality_score", None) is not None:
-            return {"status": "skipped", "reason": "already scored", "asset_id": asset_id}
-
-        storage = get_shared_storage_service()
-        storage_key = getattr(asset, "storage_key", "") or ""
-        if not storage_key:
-            return {"status": "skipped", "reason": "no storage_key", "asset_id": asset_id}
-
-        # 下载到临时文件
-        safe_suffix = ".mp4"
-        local_path = Path(tmp_dir) / f"asset_{asset_id[:8]}{safe_suffix}"
-        ok = storage.download_asset(storage_key, local_path)
-        if not ok or not local_path.exists() or local_path.stat().st_size == 0:
-            return {"status": "failed", "reason": "download failed", "asset_id": asset_id}
-
-        # 调用 AssetAnalyzer
-        from worker_app.tasks.asset_analyzer import AssetAnalyzer
-
-        try:
-            analyzer = AssetAnalyzer(str(local_path), temp_dir=tmp_dir)
-            result = analyzer.calculate_quality_score()
-            total = float(result.total) if result and 0 <= result.total <= 100 else 50.0
-        except Exception as analyze_err:  # noqa: BLE001
-            logger.warning("[quality_score] 分析失败，使用默认50分: asset=%s err=%s", asset_id, analyze_err)
-            total = 50.0
-
-        # 写回数据库（质量分）
-        asset.quality_score = total
-
-        # #2035：自动触发 9 类分类（复用已下载的临时文件，避免重复下载）
-        existing_meta = dict(asset.metadata or {})
-        existing_classification = existing_meta.get("classification")
-        classification = None
-        confidence = None
-        if not existing_classification or existing_classification == "other":
-            try:
-                from worker_app.tasks.asset_analyzer import AssetAnalyzer as _AA
-
-                # 重新构造analyzer可能会重复抽帧，但classify()会复用临时帧
-                _analyzer = _AA(str(local_path), temp_dir=tmp_dir)
-                _cls_result = _analyzer.classify()
-                classification = getattr(_cls_result, "category", None) or "other"
-                confidence = float(getattr(_cls_result, "confidence", 0.0) or 0.0)
-                if confidence < 0:
-                    confidence = 0.0
-                if confidence > 1:
-                    confidence = 1.0
-                existing_meta["classification"] = classification
-                existing_meta["classification_confidence"] = confidence
-                asset.classification_status = "completed"
-                asset.metadata = existing_meta
-                logger.info(
-                    "[quality_score] asset=%s 自动分类完成: category=%s confidence=%.2f",
-                    asset_id,
-                    classification,
-                    confidence,
-                )
-            except Exception as cls_err:  # noqa: BLE001
-                logger.warning(
-                    "[quality_score] asset=%s 自动分类失败（不影响质量分）: %s",
-                    asset_id,
-                    cls_err,
-                )
-
-        asset_repo.update(asset)
-        db.commit()
-
-        logger.info(
-            "[quality_score] asset=%s score=%.1f classification=%s",
-            asset_id,
-            total,
-            classification or existing_classification,
-        )
-        return {
-            "status": "completed",
-            "asset_id": asset_id,
-            "quality_score": total,
-            "classification": classification or existing_classification or "other",
-        }
-    except Exception as exc:  # noqa: BLE001
-        db.rollback()
-        logger.exception("[quality_score] asset=%s 失败: %s", asset_id, exc)
-        if self.request.retries < self.max_retries:
-            raise self.retry(exc=exc) from None
-        return {"status": "failed", "asset_id": asset_id, "error": str(exc)}
-    finally:
-        db.close()
-        # 清理临时文件
-        try:
-            import shutil
-
-            shutil.rmtree(tmp_dir, ignore_errors=True)
-        except Exception:
-            pass

apps/worker/worker_app/tasks/atom_clip_tagging.py

@@ -1,8 +1,7 @@
 """片段级 AI 标签 Celery 任务 — #1970 智能剪辑流程重构 P2.
 
-为单个 atom_clip 调用视觉 AI 生成结构化标签（含 caption），再调用
-豆包 embedding 接口为 caption 生成向量，一并写入数据库。
-失败不阻断流程（降级为仅继承素材标签 / caption 留空 / embedding 留空）。
+为单个 atom_clip 调用视觉 AI 生成结构化标签，并更新到 ai_tags 字段。
+失败不阻断流程（降级为仅继承素材标签）。
 
 任务名：worker.tag_atom_clip
 """
@@ -27,16 +26,16 @@ logger = get_task_logger(__name__)
 
 @celery_app.task(name="worker.tag_atom_clip", bind=True, max_retries=2, default_retry_delay=10)
 def tag_atom_clip_task(self, atom_clip_id: str, force: bool = False) -> dict:
-    """为单个原子片段生成 AI 标签 + caption + embedding.
+    """为单个原子片段生成 AI 标签.
 
     Args:
         atom_clip_id: 原子片段 ID。
         force: True 时允许覆盖只有 inherited_tags 的降级记录
             （视觉 API 曾失败写入的占位标签，#1970）。
-            已有完整标签且有 caption 始终跳过，保证幂等。
+            已有完整标签（含 has_text）始终跳过，保证幂等。
 
     Returns:
-        任务结果 dict：status / clip_id / has_ai_tags / caption / embedding_dim。
+        任务结果 dict：status / clip_id / ai_tags（部分字段）。
     """
     db = SessionLocal()
     try:
@@ -47,27 +46,11 @@ def tag_atom_clip_task(self, atom_clip_id: str, force: bool = False) -> dict:
         if clip is None:
             return {"status": "skipped", "reason": "clip not found", "clip_id": atom_clip_id}
 
-        # 幂等：已有任意 ai_tags（含降级占位）则按 force 策略跳过；person_count/text_content 为附加字段不单独触发重跑
-        #   - 无 force：只要 ai_tags 非 None 就跳过（与旧逻辑一致）
-        #   - force=True 且 ai_tags 是完整标签（含 has_text）且 caption 已存在才跳过
-        existing_tags = clip.ai_tags
-        has_real_tags = isinstance(existing_tags, dict) and "has_text" in existing_tags
-        bool(getattr(clip, "caption", None))
-        if existing_tags is not None:
-            if not force:
-                return {
-                    "status": "skipped",
-                    "reason": "already tagged",
-                    "clip_id": atom_clip_id,
-                }
-            # force=True：有完整标签（has_text）就跳过；caption 是 #2035 新增的
-            # 字段，对已有完整标签的历史数据不强制重跑
-            if has_real_tags:
-                return {
-                    "status": "skipped",
-                    "reason": "already tagged",
-                    "clip_id": atom_clip_id,
-                }
+        # 已有完整标签则跳过（幂等）；force 仅放行缺失 has_text 的降级记录
+        if clip.ai_tags is not None:
+            has_real_tags = isinstance(clip.ai_tags, dict) and "has_text" in clip.ai_tags
+            if has_real_tags or not force:
+                return {"status": "skipped", "reason": "already tagged", "clip_id": atom_clip_id}
 
         # 获取素材信息
         asset = asset_repo.find_by_id(clip.asset_id)
@@ -82,7 +65,7 @@ def tag_atom_clip_task(self, atom_clip_id: str, force: bool = False) -> dict:
         doubao_client = get_doubao_client()
         mediakit_client = get_mediakit_client()
 
-        # 调用 tagger（视觉 API → ai_tags + caption）
+        # 调用 tagger
         ai_tags = tag_atom_clip(
             clip=clip,
             video_url=video_url,
@@ -91,54 +74,18 @@ def tag_atom_clip_task(self, atom_clip_id: str, force: bool = False) -> dict:
             storage=storage,
         )
 
-        # 先写入 AI 标签（含 caption 字段在 ai_tags 字典里）
+        # 更新数据库
         atom_repo.update_ai_tags(atom_clip_id, ai_tags)
 
-        # 提取 caption 并生成 embedding（失败降级，不阻断主流程）
-        caption = (ai_tags or {}).get("caption", "") or ""
-        embedding = None
-        try:
-            if caption.strip() and doubao_client.is_available:
-                embedding = doubao_client.embed_text(caption)
-        except Exception as exc:  # noqa: BLE001
-            logger.warning(
-                "[atom_clip_tagging] clip_id=%s embedding 生成失败，降级为空: %s",
-                atom_clip_id,
-                exc,
-            )
-            embedding = None
-
-        # 写入 caption + embedding（caption 冗余写一次到独立列，便于查询）
-        try:
-            atom_repo.update_caption_embedding(atom_clip_id, caption, embedding)
-        except Exception as exc:  # noqa: BLE001
-            logger.warning(
-                "[atom_clip_tagging] clip_id=%s caption/embedding 写入失败: %s",
-                atom_clip_id,
-                exc,
-            )
-
-        person_count = (ai_tags or {}).get("person_count", 0)
-        (ai_tags or {}).get("text_content", "") or ""
         logger.info(
-            "[atom_clip_tagging] clip_id=%s ai_tags=%s caption=%r person_count=%s has_text=%s embedding_dim=%s",
+            "[atom_clip_tagging] clip_id=%s ai_tags=%s",
             atom_clip_id,
-            {k: v for k, v in ai_tags.items() if k not in ("inherited_tags", "caption", "text_content")},
-            caption,
-            person_count,
-            bool((ai_tags or {}).get("has_text")),
-            len(embedding) if embedding else 0,
+            {k: v for k, v in ai_tags.items() if k != "inherited_tags"},
         )
         return {
             "status": "completed",
             "clip_id": atom_clip_id,
-            "has_ai_tags": any(
-                v for k, v in ai_tags.items() if k not in ("inherited_tags", "caption", "text_content") and v
-            ),
-            "caption": caption,
-            "person_count": (ai_tags or {}).get("person_count", 0),
-            "text_content": (ai_tags or {}).get("text_content", "") or "",
-            "embedding_dim": len(embedding) if embedding else 0,
+            "has_ai_tags": any(v for k, v in ai_tags.items() if k != "inherited_tags" and v),
         }
     except Exception as exc:
         db.rollback()

apps/worker/worker_app/tasks/atom_clips.py

@@ -19,7 +19,6 @@ from packages.adapters.sqlalchemy_impl.asset_atom_clip_repository import (
 from packages.adapters.sqlalchemy_impl.asset_repository import SQLAlchemyAssetRepository
 from packages.domain.atom_clip_service import compute_atom_clips
 from packages.domain.plan_generator_utils import extract_scene_points_from_metadata
-from packages.shared.mediakit_client import get_mediakit_client
 
 logger = get_task_logger(__name__)
 
@@ -57,35 +56,6 @@ def generate_atom_clips(asset_id: str) -> dict:
             }
 
         scene_points = extract_scene_points_from_metadata(asset.metadata)
-        # #2035：metadata 中没有 scene_change_points 时，按需调用 MediaKit 检测
-        # （templates_editor 路由会主动写 metadata，ingest 流程此前未触发检测导致切点无法对齐）
-        if not scene_points:
-            try:
-                mk = get_mediakit_client()
-                video_url = getattr(asset, "file_url", "") or ""
-                if mk.is_available and video_url:
-                    timestamps = mk.detect_scene_changes(video_url)
-                    if timestamps:
-                        scene_points = timestamps
-                        # 持久化到 metadata，避免下次重复检测
-                        new_meta = dict(asset.metadata or {})
-                        new_meta["scene_change_points"] = list(timestamps)
-                        asset.metadata = new_meta
-                        asset_repo.update(asset)
-                        db.commit()
-                        logger.info(
-                            "[atom_clips] asset_id=%s 自动检测到 %d 个场景切换点并写回metadata",
-                            asset_id,
-                            len(timestamps),
-                        )
-            except Exception as detect_err:  # noqa: BLE001
-                logger.warning(
-                    "[atom_clips] asset_id=%s scene_change自动检测失败，降级为均匀切片: %s",
-                    asset_id,
-                    detect_err,
-                )
-                db.rollback()  # 回滚metadata写失败，不影响后续切片
-
         # P1 阶段继承素材的标签 ID；片段级语义标签是 P2 功能
         tags = list(getattr(asset, "tag_ids", []) or [])
 

apps/worker/worker_app/tasks/generation.py

@@ -17,6 +17,7 @@ import logging
 import time
 from pathlib import Path
 
+from video_processing.ffmpeg_utils import probe_duration
 from worker_app.celery_app import celery_app
 from worker_app.db import SessionLocal
 from worker_app.tasks.generation_plan_builder import build_error_info as _build_error_info
@@ -141,7 +142,7 @@ def _flush_logs(task_id: str, gen_task) -> None:
 
 # ── 共享工具模块导入 ──────────────────────────────────────────────────────────
 
-from video_processing.dedup_helpers import compute_render_fingerprint_and_dedup
+from video_processing.dedup_helpers import create_video_record_and_dedup
 from video_processing.oss_helpers import (
     download_asset,
     get_signed_download_url,
@@ -554,7 +555,7 @@ def _reselect_plan_for_batch_retry(task_id: str, plan_id: str, task_info: dict)
         return None
 
 
-def _precompute_render_metadata(
+def _record_video_and_dedup(
     *,
     task_id: str,
     project_id: str,
@@ -567,48 +568,28 @@ def _precompute_render_metadata(
     video_name: str = "",
     thumbnail_url: str = "",
 ) -> dict:
-    """渲染+上传完成后的预处理：计算指纹/查重（不落 GeneratedVideo 库）。
-
-    #2024: 视频生成后不再自动入成品库。本函数计算视频元信息、指纹、历史+批次查重，
-    结果以 dict 返回，由调用方写入 GenerationTask.extra_meta["rendered_output"]，
-    等用户 Step5 调 finalize 时复用，避免 finalize 时从 OSS 下载视频重算。
-    """
-    pre_session = SessionLocal()
+    """成片落库 + 指纹查重（含批次内）。返回查重信息 dict。"""
+    duration = probe_duration(Path(video_path))
+    dedup_session = SessionLocal()
     try:
-        fp_result = compute_render_fingerprint_and_dedup(
-            video_path=video_path,
+        result = create_video_record_and_dedup(
             generation_task_id=task_id,
             project_id=project_id,
             user_id=user_id,
             batch_id=batch_id,
+            file_url=file_url,
+            file_size=file_size,
+            duration=duration,
+            video_path=video_path,
             mode=editing_mode.value,
-            session=pre_session,
+            session=dedup_session,
+            name=video_name,
+            thumbnail_url=thumbnail_url,
         )
     finally:
-        pre_session.close()
-    return {
-        "file_url": file_url,
-        "file_size": file_size,
-        "duration": fp_result.get("duration", 0.0),
-        "width": fp_result.get("width", 1280),
-        "height": fp_result.get("height", 720),
-        "fps": fp_result.get("fps", 25.0),
-        "name": video_name,
-        "thumbnail_url": thumbnail_url,
-        "mode": editing_mode.value,
-        "batch_id": batch_id,
-        "project_id": project_id,
-        "user_id": user_id,
-        # 查重结果（finalize 时直接写入 GeneratedVideo 字段，无需重算）
-        "fingerprint_dict": fp_result.get("fingerprint_dict"),
-        "fingerprint_chunks": fp_result.get("fingerprint_chunks"),
-        "is_duplicate": bool(fp_result.get("is_duplicate", False)),
-        "duplicate_of": fp_result.get("duplicate_of"),
-        "duplicate_rate": fp_result.get("duplicate_rate"),
-        "match_count": fp_result.get("match_count"),
-        "visual_similarity": fp_result.get("visual_similarity"),
-        "video_fingerprint_md5": fp_result.get("video_fingerprint_md5", ""),
-    }
+        dedup_session.close()
+    result["duration"] = duration
+    return result
 
 
 # ── Celery Task ──────────────────────────────────────────────────────────────
@@ -964,8 +945,8 @@ def generate_video(self, task_id: str) -> dict:
                     )
                     file_size = output_path.stat().st_size
 
-                    # ── 4.5 预计算指纹/元信息（#2024: 不自动入成品库，finalize 时再落库+查重） ──
-                    rendered_output = _precompute_render_metadata(
+                    # ── 4.5 落库 + 查重（批次任务检查批次内相似度） ───────────
+                    dedup_info = _record_video_and_dedup(
                         task_id=task_id,
                         project_id=project_id,
                         batch_id=batch_id,
@@ -977,23 +958,68 @@ def generate_video(self, task_id: str) -> dict:
                         video_name=task_info.get("video_title", ""),
                         thumbnail_url=thumbnail_url,
                     )
-                    duration = rendered_output.get("duration", render_duration)
-                    # #2024: 批次内重渲依赖已 finalize 的同批次视频。渲染阶段暂不做批次查重决策，
-                    # 统一在 finalize 阶段查重；首版即视为最终渲染结果。
-                    file_size_final = file_size
+                    duration = dedup_info.get("duration", render_duration)
+                    video_count = dedup_info.get("video_count", 1)
+                    batch_sim = dedup_info.get("batch_similarity")
 
                     if gen_task:
                         gen_task.append_log(
                             "OSS上传",
-                            f"第{render_attempt + 1}版上传成功, 大小={file_size}，等待用户确认封面",
+                            f"第{render_attempt + 1}版上传成功, 大小={file_size}"
+                            + (f", 批次相似度={batch_sim:.0%}" if batch_sim is not None else ""),
                             file_size=file_size,
                             file_url=file_url,
                         )
                         _flush_logs(task_id, gen_task)
 
-                    # #2024: 不再因批次内相似度过高而重渲（finalize 阶段统一查重），
-                    # 首版即视为最终渲染结果，直接结束循环。
-                    break
+                    # 非批次 / 相似度达标 / 已是最后一次 → 结束循环
+                    if not should_rerender_for_batch_dedup(
+                        batch_id=batch_id,
+                        render_attempt=render_attempt,
+                        batch_similarity=batch_sim,
+                    ):
+                        file_size_final = file_size
+                        break
+
+                    # 批次内相似度过高：重选独立 plan 后重渲一次
+                    logger.warning(
+                        "[task_id=%s] 批次内查重相似度 %.2f 超阈值 %.2f，重选 plan 重渲",
+                        task_id,
+                        batch_sim,
+                        BATCH_RENDER_SIMILARITY_LIMIT,
+                    )
+                    if gen_task:
+                        gen_task.append_log("批次查重", f"与批次内成片相似度过高({batch_sim:.0%})，重新选片渲染")
+                        _flush_logs(task_id, gen_task)
+                    new_plan_id = _reselect_plan_for_batch_retry(task_id, current_plan_id, task_info)
+                    if not new_plan_id:
+                        logger.warning("[task_id=%s] 重选 plan 失败，保留首版", task_id)
+                        file_size_final = file_size
+                        break
+                    # 回写任务关联的 plan（重渲版以新 plan 渲染）
+                    try:
+                        _ps = SessionLocal()
+                        try:
+                            from packages.adapters.sqlalchemy_impl.generation_task_repository import (
+                                SQLAlchemyGenerationTaskRepository,
+                            )
+
+                            _pr = SQLAlchemyGenerationTaskRepository(_ps)
+                            _gt = _pr.get(task_id)
+                            if _gt:
+                                _gt.source_edit_plan_id = new_plan_id
+                                _pr.update(_gt)
+                        finally:
+                            _ps.close()
+                    except Exception:
+                        logger.warning("[task_id=%s] 回写重渲 plan_id 失败", task_id, exc_info=True)
+                    current_plan_id = new_plan_id
+                    # 清理本轮临时目录，下一轮重新渲染
+                    if render_temp_dir:
+                        import shutil
+
+                        shutil.rmtree(render_temp_dir, ignore_errors=True)
+                        render_temp_dir = None
 
                 file_size = file_size_final or file_size
                 _update_task_progress(task_id, 95, "上传完成")
@@ -1036,47 +1062,8 @@ def generate_video(self, task_id: str) -> dict:
                 except Exception:
                     logger.warning("[task_id=%s] 封面帧持久化失败", task_id, exc_info=True)
 
-                # ── 5. 保存渲染产物到 extra_meta 并标记为等待封面确认（#2024: 不自动入成品库） ──
-                try:
-                    _finalize_meta_session = SessionLocal()
-                    try:
-                        from packages.adapters.sqlalchemy_impl.models import (
-                            GenerationTaskModel,
-                        )
-
-                        _meta_model = (
-                            _finalize_meta_session.query(GenerationTaskModel)
-                            .filter(GenerationTaskModel.id == task_id)
-                            .first()
-                        )
-                        if _meta_model:
-                            meta = dict(_meta_model.extra_meta or {})
-                            meta["rendered_output"] = {
-                                "file_url": file_url,
-                                "file_size": file_size,
-                                "duration": duration,
-                                "width": rendered_output.get("width", 1280),
-                                "height": rendered_output.get("height", 720),
-                                "fps": rendered_output.get("fps", 25.0),
-                                "name": rendered_output.get("name", ""),
-                                "thumbnail_url": rendered_output.get("thumbnail_url", ""),
-                                "mode": rendered_output.get("mode", editing_mode.value),
-                                "fingerprint_dict": rendered_output.get("fingerprint_dict"),
-                                "batch_id": batch_id,
-                                "project_id": project_id,
-                                "user_id": user_id,
-                            }
-                            _meta_model.extra_meta = meta
-                            _finalize_meta_session.commit()
-                    finally:
-                        _finalize_meta_session.close()
-                except Exception as meta_err:
-                    logger.warning(
-                        "[task_id=%s] 保存 rendered_output 到 extra_meta 失败: %s", task_id, meta_err, exc_info=True
-                    )
-
-                # #2024: 标记为「等待用户确认封面」，不自动入成品库；等用户调 finalize 接口才真正 mark_completed
-                _update_task_status(task_id, "mark_awaiting_cover")
+                # ── 5. 标记完成 ──────────────────────────────────────────────────
+                _update_task_status(task_id, "mark_completed", result_count=video_count)
 
                 # 5.1 更新标题使用次数
                 try:

apps/worker/worker_app/tasks/ingest.py

@@ -808,23 +808,17 @@ def ingest_asset(job_id: str) -> dict:
 
         db.commit()
 
-        # ── #1970 素材原子切片 + #2035 质量评分：视频 READY 后异步触发，失败不阻断入库 ──
+        # ── #1970 素材原子切片：视频 READY 后异步触发，失败不阻断入库 ──
         # atom_clips 未就绪时选片逻辑有内存兜底（compute_fallback_clips）。
-        # quality_score 未计算时选片按 50 分兜底。
         try:
             if media_type == "video" and float(asset.duration or 0) > 0:
                 celery_app.send_task(
                     "worker.generate_atom_clips",
                     args=[asset.id],
                 )
-                # #2035: 异步质量评分（不与 atom_clips 链式耦合，独立任务）
-                celery_app.send_task(
-                    "worker.calculate_asset_quality",
-                    args=[asset.id],
-                )
         except Exception as atom_err:  # noqa: BLE001
             logger.warning(
-                "触发原子切片/质量评分任务失败（不影响入库）: asset_id=%s err=%s",
+                "触发原子切片任务失败（不影响入库）: asset_id=%s err=%s",
                 asset.id,
                 atom_err,
             )

deploy/configs/nginx-production.conf

@@ -12,12 +12,6 @@ server {
     client_max_body_size 800m;
 
     # SPA routing - index.html 禁止缓存，确保每次获取最新版本
-    location = /index.html {
-        add_header Cache-Control "no-cache, no-store, must-revalidate";
-        add_header Pragma "no-cache";
-        expires 0;
-    }
-
     location / {
         try_files $uri /index.html;
         # HTML 文档（含 try_files 回退的 SPA 路由，如 /login /app/dashboard）一律 no-cache，

infra/docker/nginx-production.conf

@@ -12,13 +12,6 @@ server {
 
     client_max_body_size 800m;
 
-    # SPA routing - index.html 禁止缓存，确保每次获取最新版本
-    location = /index.html {
-        add_header Cache-Control "no-cache, no-store, must-revalidate";
-        add_header Pragma "no-cache";
-        expires 0;
-    }
-
     # SPA routing - all routes to index.html
     # 注意：不能加 $uri/，否则 /assets 等与构建产物目录同名的路由会被当成目录访问，返回 403
     location / {

packages/adapters/sqlalchemy_impl/asset_atom_clip_repository.py

@@ -83,19 +83,6 @@ class SQLAlchemyAssetAtomClipRepository:
         models = query.all()
         return [self._to_domain(m) for m in models]
 
-    def update_caption_embedding(self, clip_id: str, caption: str | None, embedding: list[float] | None = None) -> bool:
-        """更新片段的 caption 和 embedding 字段。"""
-        upd: dict = {}
-        if caption is not None:
-            upd["caption"] = caption
-        if embedding is not None:
-            upd["embedding"] = embedding
-        if not upd:
-            return False
-        count = self.session.query(AssetAtomClipModel).filter(AssetAtomClipModel.id == clip_id).update(upd)
-        self.session.commit()
-        return count > 0
-
     def update_ai_tags(self, clip_id: str, ai_tags: dict) -> bool:
         """更新指定片段的 ai_tags 字段."""
         count = (
@@ -131,8 +118,6 @@ class SQLAlchemyAssetAtomClipRepository:
             clip_index=clip.clip_index,
             tags=clip.tags,
             ai_tags=clip.ai_tags,
-            caption=clip.caption,
-            embedding=clip.embedding,
             scene_change_at=clip.scene_change_at,
             is_fallback=clip.is_fallback,
             created_at=clip.created_at or datetime.now(UTC),
@@ -147,9 +132,6 @@ class SQLAlchemyAssetAtomClipRepository:
             duration=model.duration,
             clip_index=model.clip_index,
             tags=model.tags or [],
-            ai_tags=getattr(model, "ai_tags", None),
-            caption=getattr(model, "caption", None),
-            embedding=getattr(model, "embedding", None),
             scene_change_at=model.scene_change_at,
             is_fallback=model.is_fallback,
             created_at=model.created_at,

packages/adapters/sqlalchemy_impl/models.py

@@ -841,8 +841,6 @@ class AssetAtomClipModel(Base):
     clip_index = Column(Integer, nullable=False)
     tags = Column(JSON, nullable=False, default=list)
     ai_tags = Column(JSON, nullable=True, default=None)
-    caption = Column(Text, nullable=True, default=None)
-    embedding = Column(JSON, nullable=True, default=None)
     scene_change_at = Column(Float, nullable=True)
     is_fallback = Column(Boolean, nullable=False, default=False)
     created_at = Column(DateTime, nullable=False, default=lambda: datetime.now(UTC))

packages/application/generated_video_finalize.py

@@ -1,193 +0,0 @@
-"""#2024: 视频生成 finalize 入库用例。
-
-Worker 渲染+上传完成后不自动入库，只把渲染产物与查重结果保存到
-GenerationTask.extra_meta["rendered_output"]，并标记为 awaiting_cover。
-用户点「完成」时由 API 调用本用例：创建 GeneratedVideo 记录（复用预计算查重结果）、
-推进任务到 completed，返回新记录 id。
-
-设计原则：finalize 必须快速（仅 DB 写入，不下载视频、不重算指纹）——
-所有耗时操作（指纹计算、历史/批次查重）都在 worker 渲染阶段预完成。
-"""
-
-from __future__ import annotations
-
-import logging
-from dataclasses import dataclass
-from datetime import UTC, datetime
-from typing import Any
-from uuid import uuid4
-
-from sqlalchemy.orm import Session
-
-logger = logging.getLogger(__name__)
-
-
-@dataclass(slots=True)
-class RenderedOutput:
-    """Worker 预计算并写入 extra_meta 的渲染产物+查重结果。"""
-
-    file_url: str
-    file_size: int = 0
-    duration: float = 0.0
-    width: int = 1280
-    height: int = 720
-    fps: float = 25.0
-    name: str = ""
-    thumbnail_url: str = ""
-    mode: str = "narrative"
-    batch_id: str = ""
-    project_id: str = ""
-    user_id: str = ""
-    # 查重结果（worker 预计算）
-    fingerprint_dict: dict[str, Any] | None = None
-    fingerprint_chunks: list[dict[str, Any]] | None = None
-    is_duplicate: bool = False
-    duplicate_of: str | None = None
-    duplicate_rate: float | None = None
-    match_count: int | None = None
-    visual_similarity: float | None = None
-    video_fingerprint_md5: str = ""
-
-    @classmethod
-    def from_dict(cls, data: dict[str, Any]) -> "RenderedOutput":
-        if not isinstance(data, dict):
-            raise ValueError("rendered_output must be a dict")
-        return cls(
-            file_url=str(data.get("file_url") or ""),
-            file_size=int(data.get("file_size") or 0),
-            duration=float(data.get("duration") or 0.0),
-            width=int(data.get("width") or 1280),
-            height=int(data.get("height") or 720),
-            fps=float(data.get("fps") or 25.0),
-            name=str(data.get("name") or ""),
-            thumbnail_url=str(data.get("thumbnail_url") or ""),
-            mode=str(data.get("mode") or "narrative"),
-            batch_id=str(data.get("batch_id") or ""),
-            project_id=str(data.get("project_id") or ""),
-            user_id=str(data.get("user_id") or ""),
-            fingerprint_dict=data.get("fingerprint_dict"),
-            fingerprint_chunks=data.get("fingerprint_chunks"),
-            is_duplicate=bool(data.get("is_duplicate", False)),
-            duplicate_of=data.get("duplicate_of"),
-            duplicate_rate=_safe_float(data.get("duplicate_rate")),
-            match_count=_safe_int(data.get("match_count")),
-            visual_similarity=_safe_float(data.get("visual_similarity")),
-            video_fingerprint_md5=str(data.get("video_fingerprint_md5") or ""),
-        )
-
-
-def _safe_float(v) -> float | None:
-    if v is None:
-        return None
-    try:
-        return float(v)
-    except (TypeError, ValueError):
-        return None
-
-
-def _safe_int(v) -> int | None:
-    if v is None:
-        return None
-    try:
-        return int(v)
-    except (TypeError, ValueError):
-        return None
-
-
-def finalize_generated_video(
-    *,
-    task,
-    session: Session,
-    effective_cover_url: str = "",
-    custom_name: str | None = None,
-) -> dict:
-    """将 awaiting_cover 的任务正式入库。
-
-    从 ``task.extra_meta["rendered_output"]`` 读取 worker 预存的渲染结果与查重数据，
-    创建 GeneratedVideo 记录并 commit；调用方负责将 task 推进到 completed 并 update。
-
-    Returns:
-        {"video_id": str, "is_duplicate": bool, "duplicate_of": str|None}
-    """
-    from packages.adapters.sqlalchemy_impl.generated_video_repository import (
-        SQLAlchemyGeneratedVideoRepository,
-    )
-    from packages.adapters.sqlalchemy_impl.models import VideoFingerprintChunkModel
-    from packages.domain.generated_video import GeneratedVideo
-
-    meta = dict(task.extra_meta or {})
-    rendered_dict = meta.get("rendered_output") or {}
-    rendered = RenderedOutput.from_dict(rendered_dict)
-
-    if not rendered.file_url.strip():
-        raise ValueError(f"task {task.id} rendered_output.file_url 为空，无法 finalize")
-
-    video_id = uuid4().hex
-    _custom = (custom_name or "").strip() if custom_name else ""
-    video_name = _custom or (rendered.name.strip() or f"generated-{task.id[:8]}.mp4")
-
-    generated_video = GeneratedVideo(
-        id=video_id,
-        project_id=(rendered.project_id or task.project_id or "").strip(),
-        user_id=(rendered.user_id or task.created_by_user_id or "").strip(),
-        generation_task_id=task.id,
-        name=video_name,
-        file_url=rendered.file_url.strip(),
-        file_size=rendered.file_size,
-        duration=rendered.duration,
-        width=rendered.width,
-        height=rendered.height,
-        fps=rendered.fps,
-        status="completed",
-        generation_params={"mode": rendered.mode},
-        thumbnail_url=effective_cover_url or rendered.thumbnail_url or None,
-        video_fingerprint=rendered.fingerprint_dict,
-        is_duplicate=rendered.is_duplicate,
-        duplicate_of=rendered.duplicate_of,
-        duplicate_rate=rendered.duplicate_rate,
-        match_count=rendered.match_count,
-        visual_similarity=rendered.visual_similarity,
-        created_at=datetime.now(UTC),
-        generated_at=datetime.now(UTC),
-    )
-
-    # 写入分片指纹（worker 预序列化的 chunk 列表）
-    if rendered.fingerprint_chunks:
-        try:
-            chunk_models = []
-            for c in rendered.fingerprint_chunks:
-                if not isinstance(c, dict):
-                    continue
-                chunk_models.append(
-                    VideoFingerprintChunkModel(
-                        id=uuid4().hex,
-                        video_id=video_id,
-                        project_id=generated_video.project_id,
-                        user_id=generated_video.user_id,
-                        start_time_ms=int(c.get("start_time_ms", 0)),
-                        end_time_ms=int(c.get("end_time_ms", 0)),
-                        phash_binary=str(c.get("phash_binary", "")),
-                        color_histogram=[float(v) for v in (c.get("color_histogram") or [])],
-                        frame_count=int(c.get("frame_count", 0)),
-                    )
-                )
-            if chunk_models:
-                session.bulk_save_objects(chunk_models)
-        except Exception as chunk_err:
-            logger.warning("Failed to persist fingerprint chunks for video %s: %s", video_id, chunk_err)
-
-    video_repo = SQLAlchemyGeneratedVideoRepository(session)
-    video_repo.create(generated_video)
-    session.commit()
-    logger.info(
-        "[finalize] GeneratedVideo created: %s (task=%s, dup=%s, cover=%s)",
-        video_id,
-        task.id,
-        rendered.is_duplicate,
-        bool(effective_cover_url),
-    )
-    return {
-        "video_id": video_id,
-        "is_duplicate": rendered.is_duplicate,
-        "duplicate_of": rendered.duplicate_of,
-    }

packages/config/base.py

@@ -70,7 +70,6 @@ class SharedSettings(BaseSettings):
     doubao_timeout: int = 30
     doubao_max_retries: int = 2
     doubao_vision_model: str = "doubao-1-5-vision-pro-250915"
-    doubao_embedding_model: str = "doubao-embedding-large-text-240915"
 
     # ── MediaKit (火山引擎 AI 媒体工具) ──────────────────────────────────
     mediakit_api_key: str = ""

packages/domain/asset_atom_clip.py

@@ -37,8 +37,6 @@ class AssetAtomClip:
     clip_index: int
     tags: list[str] = field(default_factory=list)
     ai_tags: dict | None = None
-    caption: str | None = None
-    embedding: list[float] | None = None
     scene_change_at: float | None = None
     is_fallback: bool = False
     created_at: datetime | None = None
@@ -69,8 +67,6 @@ class AssetAtomClip:
         tags: list[str] | None = None,
         scene_change_at: float | None = None,
         is_fallback: bool = False,
-        caption: str | None = None,
-        embedding: list[float] | None = None,
     ) -> AssetAtomClip:
         """工厂方法：创建一个新的原子片段。"""
         return cls(
@@ -83,6 +79,4 @@ class AssetAtomClip:
             tags=tags or [],
             scene_change_at=scene_change_at,
             is_fallback=is_fallback,
-            caption=caption,
-            embedding=embedding,
         )

packages/domain/atom_clip_tagger.py

@@ -23,53 +23,36 @@ from typing import Any, Optional
 logger = logging.getLogger(__name__)
 
 # AI 标签结构的键
-AI_TAG_KEYS = ("scene", "objects", "action", "shot", "has_text", "person_count", "text_content", "caption")
+AI_TAG_KEYS = ("scene", "objects", "action", "shot", "has_text")
 
 
 def build_vision_prompt() -> str:
     """返回结构化标签提取 prompt.
 
     要求 AI 以 JSON 格式返回片段内容标签，包含：
-    - scene: 场景类型列表（如 "工厂", "办公室", "户外", "家庭", "商店"）
-    - objects: 画面中出现的主要物体/人物/动物类别，详细列出，常见类别包括：
-        人物类："人物"/"男性"/"女性"/"儿童"
-        食物类："食物"/"水果"/"饮料"/"菜肴"
-        电子设备类："手机"/"电脑"/"笔记本"/"平板"/"电视"/"相机"
-        交通类："汽车"/"自行车"/"公交车"/"飞机"
-        建筑类："建筑"/"房屋"/"桥梁"/"道路"
-        动物类："狗"/"猫"/"鸟"/"马"
-        其他常见："桌子"/"椅子"/"书本"/"花草"/"产品"等
-        尽可能列出所有可识别的主要物体，3-8个
-    - action: 动作类型列表（如 "演示", "说话", "操作", "行走", "奔跑", "进食"）
+    - scene: 场景类型列表（如 "工厂", "办公室", "户外"）
+    - objects: 出现的物体列表（如 "产品", "手机", "电脑"）
+    - action: 动作类型列表（如 "演示", "说话", "操作"）
     - shot: 景别（"特写" / "中景" / "远景" 之一）
-    - has_text: 画面中是否有显著文字（标题/字幕/标语/海报文字）
-    - person_count: 画面中可见的人数，0/1/2/3（3代表3人及以上）
-    - text_content: 若 has_text=true，提取画面中最显著的文字内容（不超过30字，概括即可）；否则为空字符串
-    - caption: 一句中文画面描述（15-30字），简洁概括这段视频的人物、动作、场景和主体内容
+    - has_text: 画面中是否有显著文字（true/false）
     """
     return """请分析这段视频片段的关键帧，识别内容并返回 JSON 格式标签。
 
 要求返回以下 JSON 结构（严格 JSON，不要添加其他文字）：
 {
   "scene": ["场景1", "场景2"],
-  "objects": ["物体1", "物体2", "物体3"],
+  "objects": ["物体1", "物体2"],
   "action": ["动作1"],
   "shot": "特写|中景|远景",
-  "has_text": true/false,
-  "person_count": 0,
-  "text_content": "",
-  "caption": "一句中文描述"
+  "has_text": true/false
 }
 
 规则：
-- scene: 场景类型，如"工厂"、"办公室"、"户外"、"商店"、"家庭"、"街道"等，1-3个
-- objects: 画面中可见的所有主要物体/人物/动物/食物/设备等，详细列出（3-8个）。人物算作"人物"，不要写具体人名。
-- action: 人物或物体正在进行的动作，如"演示"、"说话"、"操作"、"展示"、"行走"等，1-3个
+- scene: 场景类型，如"工厂"、"办公室"、"户外"、"商店"、"家庭"等，1-3个
+- objects: 画面中可见的主要物体，如"产品"、"手机"、"电脑"、"食品"等，1-5个
+- action: 人物或物体正在进行的动作，如"演示"、"说话"、"操作"、"展示"等，1-3个
 - shot: 景别判断，只能是"特写"、"中景"或"远景"之一
-- has_text: 画面中是否有显著可读文字（标题、字幕、标语、海报文字等）
-- person_count: 画面中可见的清晰人物数量，0=无人/远景人物不计数，1=1人，2=2人，3=3人及以上
-- text_content: 仅当 has_text=true 时填写，提取画面中最显眼的文字内容（不要超过30字）；has_text=false 时填空字符串
-- caption: 一句简洁的中文画面描述（15-30字），概括主体人物、动作、场景和物体，例如"一名女性在办公室中讲解产品展示，桌上放有笔记本电脑"
+- has_text: 画面中是否有显著可读文字（标题、字幕、标语等）
 
 请只返回 JSON，不要有其他说明文字。"""
 
@@ -82,7 +65,7 @@ def parse_vision_response(text: str) -> dict:
 
     Returns:
         结构化标签 dict，格式如：
-        {"scene": [...], "objects": [...], "action": [...], "shot": "...", "has_text": bool, "person_count": int, "text_content": str, "caption": "..."}
+        {"scene": [...], "objects": [...], "action": [...], "shot": "...", "has_text": bool}
 
     解析失败时返回空 dict。
     """
@@ -144,33 +127,6 @@ def parse_vision_response(text: str) -> dict:
     else:
         result["has_text"] = False
 
-    cap_val = data.get("caption", "")
-    if isinstance(cap_val, str):
-        cap_val = cap_val.strip()
-        if len(cap_val) > 80:
-            cap_val = cap_val[:80]
-    else:
-        cap_val = ""
-    result["caption"] = cap_val
-
-    # person_count: 0/1/2/3
-    pc_val = data.get("person_count", 0)
-    try:
-        pc = int(pc_val)
-        result["person_count"] = max(0, min(3, pc))
-    except (TypeError, ValueError):
-        result["person_count"] = 0
-
-    # text_content: OCR 文字
-    tc_val = data.get("text_content", "")
-    if isinstance(tc_val, str):
-        tc_val = tc_val.strip()
-        if len(tc_val) > 100:
-            tc_val = tc_val[:100]
-    else:
-        tc_val = ""
-    result["text_content"] = tc_val
-
     return result
 
 
@@ -281,24 +237,14 @@ def tag_atom_clip(
     Returns:
         结构化标签 dict，格式如：
         {"scene": [...], "objects": [...], "action": [...], "shot": "...",
-         "has_text": bool, "caption": "...", "inherited_tags": [...]}
+         "has_text": bool, "inherited_tags": [...]}
     """
     inherited = list(getattr(clip, "tags", []) or [])
 
     # 检查 DoubaoClient 是否可用
     if not getattr(doubao_client, "is_available", False):
         logger.info("DoubaoClient 不可用，跳过 AI 标签: clip_id=%s", getattr(clip, "id", ""))
-        return {
-            "scene": [],
-            "objects": [],
-            "action": [],
-            "shot": "",
-            "has_text": False,
-            "person_count": 0,
-            "text_content": "",
-            "caption": "",
-            "inherited_tags": inherited,
-        }
+        return {"inherited_tags": inherited}
 
     # 提取帧图片
     frame_urls: Optional[list[str]] = None
@@ -315,17 +261,7 @@ def tag_atom_clip(
 
     if not frame_urls:
         logger.warning("帧提取失败，跳过 AI 标签: clip_id=%s", getattr(clip, "id", ""))
-        return {
-            "scene": [],
-            "objects": [],
-            "action": [],
-            "shot": "",
-            "has_text": False,
-            "person_count": 0,
-            "text_content": "",
-            "caption": "",
-            "inherited_tags": inherited,
-        }
+        return {"inherited_tags": inherited}
 
     # 调用视觉 API
     prompt = build_vision_prompt()
@@ -339,47 +275,17 @@ def tag_atom_clip(
         )
     except Exception as e:
         logger.warning("视觉 API 调用异常: clip_id=%s error=%s", getattr(clip, "id", ""), e)
-        return {
-            "scene": [],
-            "objects": [],
-            "action": [],
-            "shot": "",
-            "has_text": False,
-            "person_count": 0,
-            "text_content": "",
-            "caption": "",
-            "inherited_tags": inherited,
-        }
+        return {"inherited_tags": inherited}
 
     if not response_text:
         logger.warning("视觉 API 返回空: clip_id=%s", getattr(clip, "id", ""))
-        return {
-            "scene": [],
-            "objects": [],
-            "action": [],
-            "shot": "",
-            "has_text": False,
-            "person_count": 0,
-            "text_content": "",
-            "caption": "",
-            "inherited_tags": inherited,
-        }
+        return {"inherited_tags": inherited}
 
     # 解析标签
     ai_tags = parse_vision_response(response_text)
     if not ai_tags:
         logger.warning("标签解析失败: clip_id=%s response=%s", getattr(clip, "id", ""), response_text[:200])
-        return {
-            "scene": [],
-            "objects": [],
-            "action": [],
-            "shot": "",
-            "has_text": False,
-            "person_count": 0,
-            "text_content": "",
-            "caption": "",
-            "inherited_tags": inherited,
-        }
+        return {"inherited_tags": inherited}
 
     # 合并 inherited_tags
     ai_tags["inherited_tags"] = inherited

packages/domain/generation_task.py

@@ -1,13 +1,9 @@
 """GenerationTask 领域模型 — 视频生成任务.
 
 状态机：
-  pending → running → awaiting_cover → completed
+  pending → running → completed
               ↘ failed → pending (重试)
        ↘ cancelled
-
-``awaiting_cover`` 表示渲染已完成、视频文件已上传、封面候选已就绪，
-但用户尚未在 Step5 确认封面并点击「完成」，此时不创建 GeneratedVideo 成品记录。
-用户调用 finalize 接口后才进入 ``completed`` 并正式入库。
 """
 
 from __future__ import annotations
@@ -38,11 +34,8 @@ class GenerationTaskStatus(StrEnum):
     RUNNING = "running"
     """运行中（正在生成视频）"""
 
-    AWAITING_COVER = "awaiting_cover"
-    """视频已渲染上传、封面候选已就绪，等待用户在 Step5 确认封面（finalize 前的中间态）"""
-
     COMPLETED = "completed"
-    """已完成（用户已确认封面，视频已正式入库）"""
+    """已完成（视频生成成功）"""
 
     FAILED = "failed"
     """失败（生成失败）"""
@@ -68,8 +61,6 @@ class GenerationTaskStatus(StrEnum):
                 return cls.FAILED
             if normalized in ("process", "processing", "run", "running", "in_progress"):
                 return cls.RUNNING
-            if normalized in ("awaiting_cover", "waiting_cover", "video_ready", "rendered", "pending_cover"):
-                return cls.AWAITING_COVER
             if normalized in ("cancel", "cancelled", "canceled"):
                 return cls.CANCELLED
         return cls.PENDING
@@ -88,12 +79,6 @@ _VALID_TRANSITIONS: dict[GenerationTaskStatus, set[GenerationTaskStatus]] = {
         GenerationTaskStatus.CANCELLED,
     },
     GenerationTaskStatus.RUNNING: {
-        GenerationTaskStatus.AWAITING_COVER,
-        GenerationTaskStatus.COMPLETED,  # 兜底/测试兼容：允许直接完成；主路径走 awaiting_cover
-        GenerationTaskStatus.FAILED,
-        GenerationTaskStatus.CANCELLED,
-    },
-    GenerationTaskStatus.AWAITING_COVER: {
         GenerationTaskStatus.COMPLETED,
         GenerationTaskStatus.FAILED,
         GenerationTaskStatus.CANCELLED,
@@ -225,11 +210,6 @@ class GenerationTask:
         """是否运行中。"""
         return self.status == GenerationTaskStatus.RUNNING
 
-    @property
-    def is_awaiting_cover(self) -> bool:
-        """是否等待用户确认封面（渲染已完成、视频已上传、尚未 finalize 入库）。"""
-        return self.status == GenerationTaskStatus.AWAITING_COVER
-
     # ── 状态转换 ────────────────────────────────────────────────────────────
 
     def transition_to(self, new_status: GenerationTaskStatus | str) -> None:
@@ -268,27 +248,13 @@ class GenerationTask:
         self.started_at = datetime.now(UTC)
         self.error_message = ""
 
-    def mark_awaiting_cover(self) -> None:
-        """标记为等待确认封面（running → awaiting_cover）。
-
-        渲染与上传已完成、封面候选已就绪，等待用户在 Step5 选封面并点「完成」。
-        此时不创建 GeneratedVideo 成品记录；progress 置 100，completed_at 暂不设置
-        （finalize 完成入库时才真正结束任务）。
-
-        Raises:
-            ValueError: 当前状态不允许转换到 awaiting_cover
-        """
-        self.transition_to(GenerationTaskStatus.AWAITING_COVER)
-        self.progress = 100.0
-        self.error_message = ""
-
     def mark_completed(self, result_count: int = 1) -> None:
-        """标记为已完成（awaiting_cover → completed，由 finalize 调用）。
+        """标记为已完成（running → completed）。
 
         设置 completed_at、progress=100.0、result_count，清除 error_message。
 
         Args:
-            result_count: 入库的视频数量，默认为 1
+            result_count: 生成的视频数量，默认为 1
 
         Raises:
             ValueError: 当前状态不允许转换到 completed

packages/domain/narrative_match.py

@@ -245,39 +245,16 @@ def pick_narrative_assets(
         clip_ai_tags_by_asset=clip_ai_tags_by_asset,
     )
 
-    # #2035：把文案标签与聚合的素材级 ai_tags 透传给 smart_select_assets，
-    # 让 smart 评分维度（ai_semantic）在叙事模式内部兜底/补位时同样生效。
-    wanted_norm = _normalize_tags(script_tags)
-    asset_ai_tags: dict[str, dict] = {}
-    if clip_ai_tags_by_asset:
-        for aid, clips in clip_ai_tags_by_asset.items():
-            agg: dict = {"scene": [], "objects": [], "action": []}
-            for clip_tags in clips or []:
-                if not isinstance(clip_tags, dict):
-                    continue
-                for key in ("scene", "objects", "action"):
-                    for v in clip_tags.get(key) or []:
-                        v = str(v).strip()
-                        if v and v not in agg[key]:
-                            agg[key].append(v)
-            asset_ai_tags[aid] = agg
-
-    smart_kwargs = dict(
-        kind="video",
-        rng=rng,
-        script_tags=wanted_norm if wanted_norm else None,
-        ai_tags_by_asset=asset_ai_tags if asset_ai_tags else None,
-    )
-
     need = limit if (limit is not None and limit > 0) else None
 
     if not matched:
-        return [r.asset for r in smart_select_assets(assets, limit=need, **smart_kwargs)]
+        # 完全降级：与改造前随机混剪同一逻辑
+        return [r.asset for r in smart_select_assets(assets, kind="video", limit=need, rng=rng)]
 
-    picked = [r.asset for r in smart_select_assets(matched, limit=need, **smart_kwargs)]
+    picked = [r.asset for r in smart_select_assets(matched, kind="video", limit=need, rng=rng)]
     if need is not None and len(picked) < need and unmatched:
         rest_need = need - len(picked)
-        picked.extend(r.asset for r in smart_select_assets(unmatched, limit=rest_need, **smart_kwargs))
+        picked.extend(r.asset for r in smart_select_assets(unmatched, kind="video", limit=rest_need, rng=rng))
     elif need is None:
-        picked.extend(r.asset for r in smart_select_assets(unmatched, **smart_kwargs))
+        picked.extend(r.asset for r in smart_select_assets(unmatched, kind="video", rng=rng))
     return picked

packages/domain/smart_match.py

@@ -40,14 +40,6 @@ def _get_enum_value(obj: Any, attr: str) -> str:
     return val.value if hasattr(val, "value") else str(val)
 
 
-def normalize_tag(tag) -> str:
-    """标准化标签：去两端空白、小写；非 str 转 str。返回空串表示应丢弃。"""
-    if tag is None:
-        return ""
-    s = str(tag).strip().lower()
-    return s
-
-
 def _duration_bucket(duration: float | None) -> str:
     """将素材时长分为 3 档：short(<10s) / medium(10-30s) / long(>30s)。"""
     if duration is None or duration <= 0:
@@ -62,24 +54,14 @@ def _duration_bucket(duration: float | None) -> str:
 def score_asset(
     asset: Any,
     now: datetime | None = None,
-    script_tags: set | None = None,
-    ai_tags_by_asset: dict | None = None,
-    expected_categories: set[str] | None = None,
 ) -> tuple[float, dict[str, float]]:
     """为单个素材计算综合得分（0-100）。
 
-    维度权重（#2035 加入 AI 语义匹配 + 素材分类维度）：
-    - quality_score (28%)：素材质量分（0-100），无质量分按 50 计
-    - duration_fitness (22%)：时长适配度，5-30s 为最优区间
-    - recency (12%)：新鲜度，30 天内衰减
-    - unused (8%)：未被/少被使用过的素材加分
-    - ai_semantic (20%)：AI 标签（scene/objects/action）与文案标签重合度；无数据给 50 中性分
-    - category_match (10%)：FFmpeg 自动分类结果（scenic/product/person/animal/food/tech/sport/music）
-      与期望类别重合度；无分类或无期望类别时给 60 中性分
-
-    Args:
-        script_tags: 标准化后的文案标签集合，用于 AI 语义匹配维度打分。
-        ai_tags_by_asset: asset_id → ai_tags dict 映射，ai_tags 含 scene/objects/action 字段。
+    维度权重：
+    - quality_score (40%)：素材质量分（0-100），无质量分按 50 计
+    - duration_fitness (30%)：时长适配度，5-30s 为最优区间
+    - recency (20%)：新鲜度，30 天内衰减
+    - unused_bonus (10%)：未被使用过的素材加分
 
     Returns:
         (total_score, breakdown_dict)
@@ -91,7 +73,7 @@ def score_asset(
 
     # 1. 质量分 (0-100) → 权重 40%
     raw_quality = asset.quality_score if asset.quality_score is not None else 50.0
-    quality_component = raw_quality * 0.28
+    quality_component = raw_quality * 0.4
     breakdown["quality"] = round(quality_component, 2)
 
     # 2. 时长适配度 (0-100) → 权重 30%
@@ -108,7 +90,7 @@ def score_asset(
         # >30s: 指数衰减，60s 时约 50 分
         duration_fitness = 100.0 * math.exp(-0.02 * (duration - 30))
         duration_fitness = max(duration_fitness, 10.0)
-    duration_component = duration_fitness * 0.22
+    duration_component = duration_fitness * 0.3
     breakdown["duration"] = round(duration_component, 2)
 
     # 3. 新鲜度 (0-100) → 权重 20%
@@ -121,7 +103,7 @@ def score_asset(
             created_at = created_at.replace(tzinfo=UTC)
         age_days = max(0, (now - created_at).total_seconds() / 86400)
         recency = 100.0 * math.exp(-0.05 * age_days)  # ~14天半衰期
-    recency_component = recency * 0.12
+    recency_component = recency * 0.2
     breakdown["recency"] = round(recency_component, 2)
 
     # 4. 未使用偏好 (0-100) → 权重 10%
@@ -136,55 +118,10 @@ def score_asset(
         unused_score = 70.0
     else:
         unused_score = 30.0
-    unused_component = unused_score * 0.08
+    unused_component = unused_score * 0.1
     breakdown["unused"] = round(unused_component, 2)
 
-    # 5. AI 语义匹配 (0-100) → 权重 20%
-    if script_tags and ai_tags_by_asset:
-        asset_ai = ai_tags_by_asset.get(getattr(asset, "id", "")) or {}
-        ai_terms: set = set()
-        for key in ("scene", "objects", "action"):
-            vals = asset_ai.get(key) or []
-            if isinstance(vals, list):
-                for v in vals:
-                    norm = normalize_tag(v)
-                    if norm:
-                        ai_terms.add(norm)
-        if ai_terms:
-            norm_script = {normalize_tag(t) for t in script_tags if normalize_tag(t)}
-            overlap = ai_terms & norm_script
-            union = ai_terms | norm_script
-            ratio = (len(overlap) / len(union)) if union else 0.0
-            if overlap:
-                ai_score = 50.0 + 50.0 * ratio
-            else:
-                ai_score = 20.0
-        else:
-            ai_score = 50.0
-    else:
-        ai_score = 50.0
-    ai_component = ai_score * 0.20
-    breakdown["ai_semantic"] = round(ai_component, 2)
-
-    # 6. 分类匹配 (0-100) → 权重 10%
-    asset_meta = getattr(asset, "metadata", None) or {}
-    asset_cat = (asset_meta.get("classification") or "").strip().lower()
-    if expected_categories and asset_cat:
-        norm_expected = {c.strip().lower() for c in expected_categories if c and c.strip()}
-        if asset_cat == "other":
-            cat_score = 50.0  # other 类不给额外加分也不扣分
-        elif asset_cat in norm_expected:
-            cat_score = 100.0
-        else:
-            cat_score = 30.0  # 分类明确但不匹配，略扣分
-    elif expected_categories:
-        cat_score = 60.0  # 无分类结果，中性
-    else:
-        cat_score = 60.0  # 无期望类别，中性
-    cat_component = cat_score * 0.10
-    breakdown["category_match"] = round(cat_component, 2)
-
-    total = quality_component + duration_component + recency_component + unused_component + ai_component + cat_component
+    total = quality_component + duration_component + recency_component + unused_component
     return round(total, 2), breakdown
 
 
@@ -195,9 +132,6 @@ def smart_select_assets(
     kind: str | None = None,
     now: datetime | None = None,
     rng: random.Random | None = None,
-    script_tags: set | None = None,
-    ai_tags_by_asset: dict | None = None,
-    expected_categories: set[str] | None = None,
 ) -> list[SmartMatchResult]:
     """从素材列表中智能选取素材。
 
@@ -225,13 +159,7 @@ def smart_select_assets(
     # Step 3: 评分
     scored: list[SmartMatchResult] = []
     for a in ready_assets:
-        total, breakdown = score_asset(
-            a,
-            now=now,
-            script_tags=script_tags,
-            ai_tags_by_asset=ai_tags_by_asset,
-            expected_categories=expected_categories,
-        )
+        total, breakdown = score_asset(a, now=now)
         scored.append(SmartMatchResult(asset=a, score=total, breakdown=breakdown))
 
     # Step 4: 按「得分 + 随机噪声」降序排序

packages/shared/ai_client.py

@@ -39,47 +39,6 @@ class DoubaoClient:
         self.max_retries: int = settings.doubao_max_retries
         self.vision_model: str = settings.doubao_vision_model
 
-    def embed_text(self, text: str, timeout: int | None = None) -> list[float] | None:
-        """调用豆包文本 Embedding API，返回浮点向量；失败返回 None。"""
-        if not self.is_available or not text or not text.strip():
-            return None
-
-        url = f"{self.base_url}/embeddings"
-        headers = {
-            "Authorization": f"Bearer {self.api_key}",
-            "Content-Type": "application/json",
-        }
-        payload: dict[str, Any] = {
-            "model": getattr(self, "embedding_model", None) or "doubao-embedding-large-text-240915",
-            "input": text.strip(),
-            "encoding_format": "float",
-        }
-
-        req_timeout = timeout or self.timeout
-        last_error: Exception | None = None
-        for attempt in range(self.max_retries + 1):
-            try:
-                resp = httpx.post(url, headers=headers, json=payload, timeout=req_timeout)
-                resp.raise_for_status()
-                data = resp.json()
-                emb_list = data.get("data") or []
-                if emb_list and isinstance(emb_list, list):
-                    vec = emb_list[0].get("embedding")
-                    if isinstance(vec, list) and vec:
-                        return [float(x) for x in vec]
-                logger.warning("embedding 返回结构异常: %s", str(data)[:200])
-                return None
-            except Exception as e:
-                last_error = e
-                if attempt < self.max_retries:
-                    wait = 0.5 * (2**attempt)
-                    logger.warning(
-                        "豆包 Embedding 调用失败，%.1fs 后重试 (%d/%d): %s", wait, attempt + 1, self.max_retries + 1, e
-                    )
-                    time.sleep(wait)
-        logger.error("豆包 Embedding 调用最终失败: %s", last_error)
-        return None
-
     @property
     def is_available(self) -> bool:
         """是否可用（配置了 API Key）."""

tests/unit/domain/test_generation_task.py

@@ -13,9 +13,8 @@ class TestGenerationTaskStatus:
     """GenerationTaskStatus 枚举测试."""
 
     def test_five_statuses(self):
-        """六种状态（#2024 新增 awaiting_cover）."""
-        assert len(GenerationTaskStatus) == 6
-        assert GenerationTaskStatus.AWAITING_COVER == "awaiting_cover"
+        """五种状态."""
+        assert len(GenerationTaskStatus) == 5
 
     def test_pending(self):
         assert GenerationTaskStatus.PENDING == "pending"

tests/unit/test_1970_atom_clip_tagger.py

@@ -210,12 +210,7 @@ class TestTagAtomClip:
             doubao_client=fake_doubao,
         )
 
-        assert result["inherited_tags"] == ["tag1", "tag2"]
-        assert result.get("caption", "") == ""
-        assert result.get("scene", []) == []
-        assert result.get("objects", []) == []
-        assert result.get("action", []) == []
-        assert "inherited_tags" in result
+        assert result == {"inherited_tags": ["tag1", "tag2"]}
         assert len(fake_doubao.vision_calls) == 0
 
     def test_mediakit_unavailable_no_ffmpeg(self):
@@ -232,12 +227,7 @@ class TestTagAtomClip:
         )
 
         # 没有 ffmpeg 的情况下，帧提取失败
-        assert result["inherited_tags"] == ["tag1", "tag2"]
-        assert result.get("caption", "") == ""
-        assert result.get("scene", []) == []
-        assert result.get("objects", []) == []
-        assert result.get("action", []) == []
-        assert "inherited_tags" in result
+        assert result == {"inherited_tags": ["tag1", "tag2"]}
 
     def test_vision_api_error_returns_inherited(self):
         """视觉 API 抛异常 → 降级 inherited_tags."""
@@ -252,12 +242,7 @@ class TestTagAtomClip:
             mediakit_client=fake_mediakit,
         )
 
-        assert result["inherited_tags"] == ["tag1", "tag2"]
-        assert result.get("caption", "") == ""
-        assert result.get("scene", []) == []
-        assert result.get("objects", []) == []
-        assert result.get("action", []) == []
-        assert "inherited_tags" in result
+        assert result == {"inherited_tags": ["tag1", "tag2"]}
 
     def test_vision_api_empty_response(self):
         """视觉 API 返回空 → 降级 inherited_tags."""
@@ -272,12 +257,7 @@ class TestTagAtomClip:
             mediakit_client=fake_mediakit,
         )
 
-        assert result["inherited_tags"] == ["tag1", "tag2"]
-        assert result.get("caption", "") == ""
-        assert result.get("scene", []) == []
-        assert result.get("objects", []) == []
-        assert result.get("action", []) == []
-        assert "inherited_tags" in result
+        assert result == {"inherited_tags": ["tag1", "tag2"]}
 
     def test_vision_api_invalid_json_response(self):
         """视觉 API 返回无效 JSON → 降级 inherited_tags."""
@@ -292,12 +272,7 @@ class TestTagAtomClip:
             mediakit_client=fake_mediakit,
         )
 
-        assert result["inherited_tags"] == ["tag1", "tag2"]
-        assert result.get("caption", "") == ""
-        assert result.get("scene", []) == []
-        assert result.get("objects", []) == []
-        assert result.get("action", []) == []
-        assert "inherited_tags" in result
+        assert result == {"inherited_tags": ["tag1", "tag2"]}
 
     def test_clip_with_empty_tags(self):
         """空素材标签 → inherited_tags 为空列表."""
@@ -310,8 +285,7 @@ class TestTagAtomClip:
             doubao_client=fake_doubao,
         )
 
-        assert result["inherited_tags"] == []
-        assert result.get("caption", "") == ""
+        assert result == {"inherited_tags": []}
 
 
 if __name__ == "__main__":

tests/unit/test_2035_coverage.py

@@ -1,262 +0,0 @@
-"""Additional unit tests to hit uncovered lines for diff-coverage >=60%."""
-from __future__ import annotations
-
-import json
-from dataclasses import dataclass
-from pathlib import Path
-from unittest.mock import MagicMock, patch
-
-import pytest
-
-from packages.shared.ai_client import DoubaoClient
-
-
-class _FakeSettings:
-    doubao_api_key = "test-key"
-    doubao_model = "test-model"
-    doubao_base_url = "https://ark.cn-beijing.volces.com/api/v3"
-    doubao_timeout = 10
-    doubao_max_retries = 0
-    doubao_vision_model = "test-vision"
-    doubao_embedding_model = "test-embedding"
-
-
-def _make_client(api_key: str = "test-key") -> DoubaoClient:
-    with patch("packages.shared.ai_client.get_shared_settings", return_value=_FakeSettings()):
-        c = DoubaoClient()
-    c.api_key = api_key
-    c.max_retries = 0
-    return c
-
-
-class TestDoubaoClientEmbedText:
-    def test_no_api_key_returns_none(self):
-        c = _make_client(api_key="")
-        assert c.embed_text("hello") is None
-
-    def test_empty_text_returns_none(self):
-        c = _make_client()
-        assert c.embed_text("") is None
-        assert c.embed_text("   ") is None
-
-    def test_none_text_returns_none(self):
-        c = _make_client()
-        assert c.embed_text(None) is None
-
-    @patch("packages.shared.ai_client.httpx.post")
-    def test_successful_embedding(self, mock_post):
-        mock_resp = MagicMock()
-        mock_resp.json.return_value = {"data": [{"embedding": [0.1, 0.2, 0.3]}]}
-        mock_resp.raise_for_status = MagicMock()
-        mock_post.return_value = mock_resp
-        c = _make_client()
-        result = c.embed_text("hello world")
-        assert result == [0.1, 0.2, 0.3]
-        mock_post.assert_called_once()
-
-    @patch("packages.shared.ai_client.httpx.post")
-    def test_malformed_response_returns_none(self, mock_post):
-        mock_resp = MagicMock()
-        mock_resp.json.return_value = {"data": []}
-        mock_resp.raise_for_status = MagicMock()
-        mock_post.return_value = mock_resp
-        c = _make_client()
-        assert c.embed_text("hello") is None
-
-    @patch("packages.shared.ai_client.httpx.post", side_effect=Exception("network error"))
-    def test_network_error_returns_none(self, mock_post):
-        c = _make_client()
-        assert c.embed_text("hello") is None
-
-    def test_is_available_with_key(self):
-        c = _make_client(api_key="sk-xxx")
-        assert c.is_available is True
-
-    def test_is_available_without_key(self):
-        c = _make_client(api_key="")
-        assert c.is_available is False
-
-
-# --- 2. _infer_expected_categories ---
-_GEN_TASKS_PATH = Path(__file__).resolve().parents[2] / "apps/api/app/api/routes/generation_tasks.py"
-
-
-def _load_infer_func():
-    src = _GEN_TASKS_PATH.read_text()
-    start = src.index("# #2035：文案关键词")
-    end = src.index("from packages.middleware")
-    code = src[start:end]
-    ns: dict = {}
-    exec(code, ns)
-    return ns["_infer_expected_categories"]
-
-
-_infer_expected_categories = _load_infer_func()
-
-
-class TestInferExpectedCategories:
-    def test_none_returns_none(self):
-        assert _infer_expected_categories(None) is None
-        assert _infer_expected_categories(set()) is None
-
-    def test_product_keyword_matches(self):
-        cats = _infer_expected_categories({"产品展示"})
-        assert cats is not None
-        assert "product" in cats
-
-    def test_scenic_keyword_matches(self):
-        cats = _infer_expected_categories({"户外风景"})
-        assert cats is not None
-        assert "scenic" in cats
-
-    def test_food_keyword_matches(self):
-        cats = _infer_expected_categories({"美食制作"})
-        assert cats is not None
-        assert "food" in cats
-
-    def test_no_match_returns_none(self):
-        assert _infer_expected_categories({"抽象概念xyz"}) is None
-
-
-# --- 3. parse_vision_response edge cases ---
-from packages.domain.atom_clip_tagger import parse_vision_response
-
-
-class TestParseVisionResponseEdgeCases:
-    def test_person_count_type_error_defaults_zero(self):
-        text = json.dumps({
-            "scene": [], "objects": [], "action": [], "shot": "", "has_text": False,
-            "person_count": "not-an-int", "text_content": "", "caption": "x",
-        })
-        r = parse_vision_response(text)
-        assert r["person_count"] == 0
-
-    def test_person_count_out_of_range_clamped(self):
-        text = json.dumps({
-            "scene": [], "objects": [], "action": [], "shot": "", "has_text": False,
-            "person_count": 10, "text_content": "", "caption": "x",
-        })
-        r = parse_vision_response(text)
-        assert r["person_count"] == 3
-
-    def test_person_count_negative_clamped(self):
-        text = json.dumps({
-            "scene": [], "objects": [], "action": [], "shot": "", "has_text": False,
-            "person_count": -5, "text_content": "", "caption": "x",
-        })
-        r = parse_vision_response(text)
-        assert r["person_count"] == 0
-
-    def test_text_content_non_string_defaults_empty(self):
-        text = '{"scene":[],"objects":[],"action":[],"shot":"","has_text":true,"person_count":0,"text_content":123,"caption":"x"}'
-        r = parse_vision_response(text)
-        assert r["text_content"] == ""
-
-    def test_caption_truncation_at_80(self):
-        long_caption = "描" * 100
-        text = json.dumps({
-            "scene": [], "objects": [], "action": [], "shot": "", "has_text": False,
-            "person_count": 0, "text_content": "", "caption": long_caption,
-        })
-        r = parse_vision_response(text)
-        assert len(r["caption"]) == 80
-
-
-# --- 4. smart_match normalize_tag ---
-from packages.domain.smart_match import normalize_tag
-
-
-class TestNormalizeTagEdge:
-    def test_none_returns_empty(self):
-        assert normalize_tag(None) == ""
-
-    def test_non_string_converted(self):
-        assert normalize_tag(123) == "123"
-
-    def test_strip_and_lower(self):
-        assert normalize_tag("  FOO Bar  ") == "foo bar"
-
-
-# --- 5. narrative_match non-dict clip_tags skip ---
-from packages.domain.narrative_match import match_assets_by_script_tags
-
-
-@dataclass
-class _FA:
-    id: str
-    tags: list
-
-
-class TestNarrativeMatchNonDictClipTags:
-    def test_non_dict_clip_tags_are_skipped(self):
-        a1 = _FA("a1", tags=[])
-        clip_map = {"a1": [None, "bad", {"scene": ["工厂"], "objects": [], "action": []}, 123]}
-        matched, unmatched = match_assets_by_script_tags(
-            [a1], script_tags=["工厂"], clip_ai_tags_by_asset=clip_map
-        )
-        assert [a.id for a in matched] == ["a1"]
-
-
-# --- 6. update_caption_embedding ---
-class _FakeSession:
-    def __init__(self, rows_found: int = 1):
-        self.rows_found = rows_found
-        self.commits = 0
-        self.updates = []
-
-    def query(self, model):
-        return _FQuery(self)
-
-    def commit(self):
-        self.commits += 1
-
-
-class _FQuery:
-    def __init__(self, session):
-        self.session = session
-
-    def filter(self, *a, **kw):
-        return self
-
-    def update(self, upd):
-        self.session.updates.append(upd)
-        return self.session.rows_found
-
-
-class TestUpdateCaptionEmbedding:
-    def _make_repo(self, session):
-        from packages.adapters.sqlalchemy_impl.asset_atom_clip_repository import SQLAlchemyAssetAtomClipRepository
-        repo = SQLAlchemyAssetAtomClipRepository.__new__(SQLAlchemyAssetAtomClipRepository)
-        repo.session = session
-        return repo
-
-    def test_updates_both_caption_and_embedding(self):
-        s = _FakeSession(rows_found=1)
-        repo = self._make_repo(s)
-        ok = repo.update_caption_embedding("c1", "new caption", [0.1, 0.2])
-        assert ok is True
-        assert s.commits == 1
-        assert s.updates[0]["caption"] == "new caption"
-        assert s.updates[0]["embedding"] == [0.1, 0.2]
-
-    def test_only_caption_update(self):
-        s = _FakeSession(rows_found=1)
-        repo = self._make_repo(s)
-        ok = repo.update_caption_embedding("c1", "cap", None)
-        assert ok is True
-        assert "embedding" not in s.updates[0]
-        assert s.updates[0]["caption"] == "cap"
-
-    def test_no_update_when_both_none(self):
-        s = _FakeSession()
-        repo = self._make_repo(s)
-        ok = repo.update_caption_embedding("c1", None, None)
-        assert ok is False
-        assert s.commits == 0
-        assert s.updates == []
-
-    def test_returns_false_when_row_not_found(self):
-        s = _FakeSession(rows_found=0)
-        repo = self._make_repo(s)
-        ok = repo.update_caption_embedding("c1", "x", [0.1])
-        assert ok is False

tests/unit/test_2035_semantic_tags.py

@@ -1,352 +0,0 @@
-"""#2035 语义标签增强 / 质量评分 / AI选片 单测。"""
-
-from __future__ import annotations
-
-import random
-from dataclasses import dataclass, field
-from datetime import UTC, datetime, timedelta
-
-import pytest
-
-from packages.domain.asset_atom_clip import AssetAtomClip
-from packages.domain.atom_clip_tagger import parse_vision_response
-from packages.domain.narrative_match import (
-    _compute_ai_score,
-    _extract_ai_tag_names,
-    match_assets_by_script_tags,
-    pick_narrative_assets,
-)
-from packages.domain.smart_match import score_asset, smart_select_assets
-
-# ── helpers ──────────────────────────────────────────────────────
-
-
-@dataclass
-class FakeAsset:
-    id: str
-    tag_ids: list[str] = field(default_factory=list)
-    tags: list[str] = field(default_factory=list)
-    status: object = None
-    file_type: str = "video"
-    duration: float = 10.0
-    quality_score: float | None = 50.0
-    created_at: datetime | None = None
-    metadata: dict = field(default_factory=dict)
-    usage_count: int = 0
-
-    def __post_init__(self):
-        if self.status is None:
-
-            class _S:
-                value = "ready"
-
-            self.status = _S()
-        if self.created_at is None:
-            self.created_at = datetime.now(UTC) - timedelta(days=1)
-
-
-# ── parse_vision_response: caption 提取 ─────────────────────────
-
-
-class TestParseVisionResponseCaption:
-    def test_extracts_caption(self):
-        text = '{"scene":["办公室"],"objects":["电脑","人"],"action":["说话"],"shot":"中景","has_text":false,"caption":"职场女性在办公室讲解产品功能"}'
-        result = parse_vision_response(text)
-        assert result["caption"] == "职场女性在办公室讲解产品功能"
-        assert result["has_text"] is False
-        assert result["scene"] == ["办公室"]
-
-    def test_caption_truncated_at_80(self):
-        long = "A" * 100
-        text = '{"scene":[],"objects":[],"action":[],"shot":"中景","has_text":false,"caption":"' + long + '"}'
-        result = parse_vision_response(text)
-        assert len(result["caption"]) == 80
-
-    def test_missing_caption_defaults_empty(self):
-        text = '{"scene":[],"objects":[],"action":[],"shot":"特写","has_text":true}'
-        result = parse_vision_response(text)
-        assert result["caption"] == ""
-
-    def test_empty_input_returns_empty_dict(self):
-        assert parse_vision_response("") == {}
-        assert parse_vision_response(None) == {}
-
-
-# ── AI 标签提取 ──────────────────────────────────────────────────
-
-
-class TestExtractAiTagNames:
-    def test_extracts_scene_objects_action(self):
-        tags = {"scene": ["办公室"], "objects": ["电脑", "杯子"], "action": ["说话"], "shot": "中景", "has_text": False}
-        names = _extract_ai_tag_names(tags)
-        assert "办公室" in names
-        assert "电脑" in names
-        assert "杯子" in names
-        assert "说话" in names
-        assert "中景" not in names  # shot 不参与匹配
-
-    def test_empty_tags(self):
-        assert _extract_ai_tag_names({}) == set()
-        assert _extract_ai_tag_names({"scene": []}) == set()
-
-
-# ── _compute_ai_score ───────────────────────────────────────────
-
-
-class TestComputeAiScore:
-    def test_basic_hit(self):
-        clip_map = {"a1": [{"scene": ["工厂"], "objects": ["产品"], "action": ["演示"]}]}
-        score = _compute_ai_score("a1", {"工厂", "演示"}, clip_map)
-        # 2 hits * weight 2.0 = 4.0
-        assert score == 4.0
-
-    def test_no_hit(self):
-        clip_map = {"a1": [{"scene": ["户外"], "objects": [], "action": []}]}
-        assert _compute_ai_score("a1", {"办公室"}, clip_map) == 0.0
-
-    def test_no_clip_map(self):
-        assert _compute_ai_score("a1", {"工厂"}, None) == 0.0
-        assert _compute_ai_score("a1", set(), {"a1": [{"scene": ["x"]}]}) == 0.0
-
-    def test_best_clip_score_not_sum(self):
-        """多片段取最高得分，不是累加。"""
-        clip_map = {
-            "a1": [
-                {"scene": ["工厂"], "objects": [], "action": []},  # 1 hit
-                {"scene": ["工厂"], "objects": ["产品"], "action": ["演示"]},  # 3 hits
-                {"scene": ["户外"], "objects": [], "action": []},  # 0
-            ]
-        }
-        score = _compute_ai_score("a1", {"工厂", "产品", "演示"}, clip_map)
-        assert score == 3 * 2.0  # best = 6.0, not (1+3+0)*2 = 8.0
-
-
-# ── match_assets_by_script_tags 接受 clip_ai_tags_by_asset ──────
-
-
-class TestMatchSplitAiTags:
-    def test_ai_hit_only_puts_in_matched(self):
-        """素材无人工标签，但 AI 标签命中 → 命中池。"""
-        assets = [FakeAsset("a1", tags=[]), FakeAsset("a2", tags=["旅游"])]
-        clip_map = {"a1": [{"scene": ["工厂"], "objects": [], "action": []}]}
-        matched, unmatched = match_assets_by_script_tags(assets, script_tags=["工厂"], clip_ai_tags_by_asset=clip_map)
-        assert [a.id for a in matched] == ["a1"]
-        assert [a.id for a in unmatched] == ["a2"]
-
-    def test_ai_and_manual_both_hit(self):
-        assets = [FakeAsset("a1", tags=["工厂"]), FakeAsset("a2", tags=[])]
-        clip_map = {"a1": [{"objects": ["产品"]}]}
-        matched, unmatched = match_assets_by_script_tags(
-            assets, script_tags=["工厂", "产品"], clip_ai_tags_by_asset=clip_map
-        )
-        assert [a.id for a in matched] == ["a1"]
-        # a2 无人标签也无AI命中 → unmatched
-        assert [a.id for a in unmatched] == ["a2"]
-
-
-# ── score_asset AI 语义维度 ────────────────────────────────────
-
-
-class TestScoreAssetAiSemantic:
-    def test_no_ai_data_gives_neutral_ai_component(self):
-        a = FakeAsset("a1", quality_score=80)
-        total, breakdown = score_asset(a, now=datetime.now(UTC))
-        # ai_semantic 中性分 50 * 0.20 = 10；category 中性分 60 * 0.10 = 6
-        assert breakdown["ai_semantic"] == 10.0
-        assert breakdown["category_match"] == 6.0
-
-    def test_ai_hit_boosts_score(self):
-        a = FakeAsset("a1", quality_score=50)
-        ai_map = {"a1": {"scene": ["工厂"], "objects": ["产品"], "action": ["演示"]}}
-        total_hit, _ = score_asset(a, now=datetime.now(UTC), script_tags={"工厂", "产品"}, ai_tags_by_asset=ai_map)
-        total_miss, _ = score_asset(a, now=datetime.now(UTC), script_tags={"旅游"}, ai_tags_by_asset=ai_map)
-        total_neutral, _ = score_asset(a, now=datetime.now(UTC))
-        assert total_hit > total_neutral
-        assert total_neutral > total_miss
-
-    def test_weights_sum_to_100(self):
-        a = FakeAsset("a1", quality_score=100, duration=15)
-        a.created_at = datetime.now(UTC)
-        a.metadata = {"generation_use_count": 0}
-        _, bd = score_asset(a, now=datetime.now(UTC))
-        # 满分素材：quality=28, duration=22, recency=~12 (new), unused=8, ai=10(neutral), cat=6(neutral)
-        # 总和应该 ~86
-        assert 80 <= sum(bd.values()) <= 100.5
-
-
-# ── smart_select_assets 接受 script_tags/ai_tags_by_asset ──────
-
-
-class TestSmartSelectAi:
-    def test_ai_hit_ranks_higher(self):
-        a1 = FakeAsset("a1", quality_score=50, duration=15)
-        a2 = FakeAsset("a2", quality_score=50, duration=15)
-        a3 = FakeAsset("a3", quality_score=50, duration=15)
-        ai_map = {
-            "a1": {"scene": ["工厂"], "objects": ["产品"], "action": ["演示"]},
-            "a2": {"scene": ["户外"], "objects": [], "action": []},
-            "a3": {},
-        }
-        rng = random.Random(42)
-        results = smart_select_assets(
-            [a1, a2, a3],
-            kind="video",
-            rng=rng,
-            script_tags={"工厂", "产品", "演示"},
-            ai_tags_by_asset=ai_map,
-        )
-        assert results[0].asset.id == "a1"  # AI 命中应排第一
-
-    def test_without_ai_params_works_as_before(self):
-        a1 = FakeAsset("a1", quality_score=80, duration=15)
-        a2 = FakeAsset("a2", quality_score=40, duration=15)
-        rng = random.Random(0)
-        results = smart_select_assets([a1, a2], kind="video", rng=rng)
-        assert results[0].asset.id == "a1"
-
-
-# ── pick_narrative_assets 接受 clip_ai_tags_by_asset ────────────
-
-
-class TestPickNarrativeAi:
-    def test_ai_tagged_assets_selected_first(self):
-        a1 = FakeAsset("a1", tags=[])
-        a2 = FakeAsset("a2", tags=[])
-        a3 = FakeAsset("a3", tags=["无关"])
-        clip_map = {
-            "a1": [{"scene": ["工厂"], "objects": ["产品"], "action": ["演示"]}],
-            "a2": [{"scene": ["户外"], "objects": [], "action": []}],
-        }
-        rng = random.Random(0)
-        picked = pick_narrative_assets(
-            [a1, a2, a3],
-            script_tags=["工厂", "产品"],
-            tag_names_by_id={},
-            clip_ai_tags_by_asset=clip_map,
-            rng=rng,
-            limit=2,
-        )
-        assert picked[0].id == "a1"  # a1 命中 AI 标签应在首位
-        assert {a.id for a in picked} == {"a1", "a3"} or {a.id for a in picked} == {"a1", "a2"}
-
-
-# ── AssetAtomClip 字段扩展 ─────────────────────────────────────
-
-
-class TestAssetAtomClipNewFields:
-    def test_caption_embedding_fields(self):
-        clip = AssetAtomClip.create(
-            asset_id="a1",
-            start_time=0,
-            end_time=5,
-            clip_index=0,
-            tags=[],
-            caption="测试画面描述",
-            embedding=[0.1, 0.2, 0.3],
-        )
-        assert clip.caption == "测试画面描述"
-        assert clip.embedding == [0.1, 0.2, 0.3]
-        assert clip.ai_tags is None
-
-    def test_default_fields_none(self):
-        clip = AssetAtomClip.create("a1", 0, 5, 0)
-        assert clip.caption is None
-        assert clip.embedding is None
-
-
-# ── parse_vision_response: person_count / text_content ───────────
-
-
-class TestParseVisionResponseEnhanced:
-    def test_person_count_parsed(self):
-        text = '{"scene":["办公室"],"objects":["人物","电脑"],"action":["说话"],"shot":"中景","has_text":false,"person_count":1,"text_content":"","caption":"职场女性在办公室讲解产品功能，桌上有笔记本电脑"}'
-        result = parse_vision_response(text)
-        assert result["person_count"] == 1
-        assert result["text_content"] == ""
-
-    def test_person_count_multi_people(self):
-        text = '{"scene":["会议室"],"objects":["人物","桌子","椅子"],"action":["开会"],"shot":"中景","has_text":false,"person_count":3,"text_content":"","caption":"多人在会议室开会讨论项目方案"}'
-        result = parse_vision_response(text)
-        assert result["person_count"] == 3  # 3人及以上
-
-    def test_person_count_non_int_defaults_zero(self):
-        text = '{"scene":[],"objects":[],"action":[],"shot":"特写","has_text":false,"person_count":"abc","text_content":"","caption":""}'
-        result = parse_vision_response(text)
-        assert result["person_count"] == 0
-
-    def test_text_content_extracted_when_has_text(self):
-        text = '{"scene":["街道"],"objects":["招牌","建筑"],"action":[],"shot":"远景","has_text":true,"person_count":0,"text_content":"欢迎光临","caption":"街道上有一家店铺招牌写着欢迎光临"}'
-        result = parse_vision_response(text)
-        assert result["text_content"] == "欢迎光临"
-        assert result["has_text"] is True
-
-    def test_text_content_truncated_at_100(self):
-        long_text = "X" * 200
-        text = (
-            '{"scene":[],"objects":[],"action":[],"shot":"特写","has_text":true,"person_count":0,"text_content":"'
-            + long_text
-            + '","caption":""}'
-        )
-        result = parse_vision_response(text)
-        assert len(result["text_content"]) == 100
-
-    def test_missing_person_count_defaults_zero(self):
-        text = '{"scene":[],"objects":[],"action":[],"shot":"特写","has_text":false,"caption":"一个苹果"}'
-        result = parse_vision_response(text)
-        assert result["person_count"] == 0
-        assert result["text_content"] == ""
-
-    def test_fallback_returns_person_count_zero(self):
-        """非 JSON 输入应返回空 dict（不是 fallback tags）。"""
-        result = parse_vision_response("not json at all")
-        assert result == {}
-
-    def test_objects_list_merged(self):
-        """objects 应该被保留并转为列表。"""
-        text = '{"scene":["厨房"],"objects":["食物","锅","蔬菜","刀具"],"action":["烹饪"],"shot":"中景","has_text":false,"person_count":1,"text_content":"","caption":"厨师在厨房烹饪食物，食材摆放整齐"}'
-        result = parse_vision_response(text)
-        assert "食物" in result["objects"]
-        assert "锅" in result["objects"]
-        assert "蔬菜" in result["objects"]
-        assert len(result["objects"]) >= 3
-
-
-# ── score_asset category_match 维度 ────────────────────────────
-
-
-class TestScoreAssetCategoryMatch:
-    def test_no_category_gives_neutral(self):
-        a = FakeAsset("a1", quality_score=50, metadata={})
-        _, bd = score_asset(a, now=datetime.now(UTC))
-        assert bd["category_match"] == 6.0  # 60 * 0.10 = 6
-
-    def test_category_hit_gives_10(self):
-        a = FakeAsset("a1", quality_score=50, metadata={"classification": "product"})
-        _, bd = score_asset(a, now=datetime.now(UTC), expected_categories={"product", "person"})
-        assert bd["category_match"] == 10.0  # 100 * 0.10 = 10
-
-    def test_category_miss_gives_low(self):
-        a = FakeAsset("a1", quality_score=50, metadata={"classification": "scenic"})
-        _, bd_hit = score_asset(a, now=datetime.now(UTC), expected_categories={"product"})
-        _, bd_neutral = score_asset(a, now=datetime.now(UTC))
-        assert bd_hit["category_match"] == 3.0  # 30 * 0.10 = 3
-        assert bd_neutral["category_match"] == 6.0
-
-    def test_other_category_neutral(self):
-        """other 类不给额外加分。"""
-        a = FakeAsset("a1", quality_score=50, metadata={"classification": "other"})
-        _, bd = score_asset(a, now=datetime.now(UTC), expected_categories={"product"})
-        assert bd["category_match"] == 5.0  # 50 * 0.10 = 5
-
-    def test_category_affects_ranking(self):
-        a_product = FakeAsset("a_product", quality_score=50, duration=15, metadata={"classification": "product"})
-        a_scenic = FakeAsset("a_scenic", quality_score=50, duration=15, metadata={"classification": "scenic"})
-        a_none = FakeAsset("a_none", quality_score=50, duration=15, metadata={})
-        rng = random.Random(42)
-        results = smart_select_assets(
-            [a_product, a_scenic, a_none],
-            kind="video",
-            rng=rng,
-            expected_categories={"product"},
-        )
-        assert results[0].asset.id == "a_product"

tests/unit/test_cover_awaiting_fallback.py

@@ -1,167 +0,0 @@
-"""#2028: generation_cover._get_task_video_url 兜底逻辑测试。"""
-
-from __future__ import annotations
-
-import os
-import sys
-from pathlib import Path
-from unittest.mock import MagicMock, patch
-
-os.environ.setdefault("JWT_SECRET_KEY", "unit-test-secret-key-for-testing")
-os.environ.setdefault("DATABASE_URL", "sqlite:///test.db")
-
-sys.path.insert(0, str(Path(__file__).resolve().parents[2] / "apps" / "api"))
-
-import pytest
-
-
-class TestGetTaskVideoUrlAwaitingCoverFallback:
-    def test_returns_url_from_rendered_output_when_awaiting_cover(self):
-        from app.api.routes import generation_cover as cover_mod
-
-        mock_usecase = MagicMock()
-        mock_usecase.execute.return_value = []
-
-        mock_task = MagicMock()
-        mock_task.status.value = "awaiting_cover"
-        mock_task.extra_meta = {"rendered_output": {"file_url": "oss://generated/awaiting.mp4"}}
-
-        mock_task_repo_instance = MagicMock()
-        mock_task_repo_instance.get.return_value = mock_task
-        mock_db = MagicMock()
-
-        with (
-            patch.object(cover_mod, "ListGeneratedVideosByTaskUseCase", return_value=mock_usecase),
-            patch.object(cover_mod, "SQLAlchemyGenerationTaskRepository", return_value=mock_task_repo_instance),
-        ):
-            url = cover_mod._get_task_video_url("task-aw1", mock_db)
-        assert url == "oss://generated/awaiting.mp4"
-
-    def test_returns_none_when_status_not_awaiting_cover(self):
-        from app.api.routes import generation_cover as cover_mod
-
-        mock_usecase = MagicMock()
-        mock_usecase.execute.return_value = []
-        mock_task = MagicMock()
-        mock_task.status.value = "running"
-        mock_task.extra_meta = {"rendered_output": {"file_url": "oss://x.mp4"}}
-        mock_task_repo_instance = MagicMock()
-        mock_task_repo_instance.get.return_value = mock_task
-        mock_db = MagicMock()
-        with (
-            patch.object(cover_mod, "ListGeneratedVideosByTaskUseCase", return_value=mock_usecase),
-            patch.object(cover_mod, "SQLAlchemyGenerationTaskRepository", return_value=mock_task_repo_instance),
-        ):
-            url = cover_mod._get_task_video_url("task-run", mock_db)
-        assert url is None
-
-    def test_returns_none_when_rendered_output_missing(self):
-        from app.api.routes import generation_cover as cover_mod
-
-        mock_usecase = MagicMock()
-        mock_usecase.execute.return_value = []
-        mock_task = MagicMock()
-        mock_task.status.value = "awaiting_cover"
-        mock_task.extra_meta = {}
-        mock_task_repo_instance = MagicMock()
-        mock_task_repo_instance.get.return_value = mock_task
-        mock_db = MagicMock()
-        with (
-            patch.object(cover_mod, "ListGeneratedVideosByTaskUseCase", return_value=mock_usecase),
-            patch.object(cover_mod, "SQLAlchemyGenerationTaskRepository", return_value=mock_task_repo_instance),
-        ):
-            url = cover_mod._get_task_video_url("task-empty", mock_db)
-        assert url is None
-
-
-class TestAwaitingCoverResultsSynthesis:
-    """list_generation_results 在 awaiting_cover + 无 GeneratedVideo 时合成预览响应。"""
-
-    def _invoke(self, task, storage_service):
-        from app.api.routes import generation_tasks as gt_mod
-
-        mock_auth = MagicMock()
-        mock_auth.user.id = "u1"
-        mock_task_repo = MagicMock()
-        mock_task_repo.get.return_value = task
-        mock_video_repo = MagicMock()
-        mock_usecase = MagicMock()
-        mock_usecase.execute.return_value = []
-        mock_project_repo = MagicMock()
-
-        with (
-            patch.object(gt_mod, "check_project_access", return_value=None),
-            patch.object(gt_mod, "ListGeneratedVideosByTaskUseCase", return_value=mock_usecase),
-        ):
-            return gt_mod.list_generation_results(
-                task_id=task.id,
-                authenticated_user=mock_auth,
-                generation_task_repository=mock_task_repo,
-                generated_video_repository=mock_video_repo,
-                project_repository=mock_project_repo,
-                storage_service=storage_service,
-            )
-
-    def test_synthesizes_preview_response_when_awaiting_cover(self):
-        task = MagicMock()
-        task.id = "task-syn-1"
-        task.project_id = "proj1"
-        task.status.value = "awaiting_cover"
-        task.cover_url = ""
-        task.extra_meta = {
-            "rendered_output": {
-                "file_url": "oss://bucket/v.mp4",
-                "file_size": 2048,
-                "duration": 10.5,
-                "width": 1080,
-                "height": 1920,
-                "fps": 30.0,
-                "name": "合成预览",
-                "mode": "random",
-                "thumbnail_url": "https://cdn/t.jpg",
-            }
-        }
-        task.updated_at = None
-        task.created_at = None
-        storage = MagicMock()
-        storage.get_download_url.return_value = "https://signed/v.mp4"
-        resp = self._invoke(task, storage)
-        assert len(resp.items) == 1
-        item = resp.items[0]
-        assert item.id == "preview-task-syn-1"
-        assert item.name == "合成预览"
-        assert item.file_size == 2048
-        assert item.duration == 10.5
-        assert item.width == 1080
-        assert item.height == 1920
-        assert item.fps == 30.0
-        assert item.download_url == "https://signed/v.mp4"
-
-    def test_http_file_url_used_directly(self):
-        task = MagicMock()
-        task.id = "task-httpx"
-        task.project_id = "p"
-        task.status.value = "awaiting_cover"
-        task.cover_url = ""
-        task.extra_meta = {"rendered_output": {"file_url": "https://cdn.example.com/v.mp4", "name": ""}}
-        task.updated_at = None
-        task.created_at = None
-        storage = MagicMock()
-        resp = self._invoke(task, storage)
-        assert resp.items[0].download_url == "https://cdn.example.com/v.mp4"
-        storage.get_download_url.assert_not_called()
-        assert resp.items[0].name.startswith("generated-task-htt")
-
-    def test_no_items_when_status_completed_without_videos(self):
-        task = MagicMock()
-        task.id = "task-done"
-        task.project_id = "p"
-        task.status.value = "completed"
-        task.extra_meta = {"rendered_output": {"file_url": "oss://x.mp4"}}
-        storage = MagicMock()
-        resp = self._invoke(task, storage)
-        assert resp.items == []
-
-
-if __name__ == "__main__":
-    sys.exit(pytest.main([__file__, "-v"]))

tests/unit/test_editor_clips_random_start.py

@@ -367,13 +367,7 @@ class TestEditorClipsDurationAndStartTime:
                 )
 
         assert exc_info.value.status_code == 400
-        # 时长为0的素材被跳过，全部无效时返回「素材尚未完成分析，请稍后重试」
-        assert "素材" in exc_info.value.detail and (
-            "未完成" in exc_info.value.detail
-            or "无效" in exc_info.value.detail
-            or "分析" in exc_info.value.detail
-            or "稍后" in exc_info.value.detail
-        )
+        assert "素材可切区间不足" in exc_info.value.detail
 
     @patch("app.api.routes.templates_editor.clips.get_storage_service")
     def test_zero_duration_asset_skipped_in_mixed_pool(self, mock_storage):
@@ -902,75 +896,3 @@ class TestClipsFromAssetsInvalidIds:
                 )
         assert exc_info.value.status_code == 400
         mock_plan_svc.replace_all_clips_transactional.assert_not_called()
-
-
-class TestClipsFromAssetsExceptionTolerance:
-    """#2028: score_asset / scene_points 抛异常时不应阻断整个请求，应兜底跳过。"""
-
-    @patch("app.api.routes.templates_editor.clips.get_storage_service")
-    def test_score_asset_exception_sets_score_zero(self, mock_storage):
-        from app.api.routes.templates_editor.clips import (
-            create_clips_from_assets_editor,
-        )
-        from app.api.routes.templates_editor.schemas import ClipsFromAssetsRequest
-
-        mock_plan_svc = _make_plan_svc(replace_return_count=2)
-        mock_asset_repo = MagicMock()
-        mock_asset_repo.get = MagicMock(return_value=_make_mock_asset("a1", 30.0))
-        body = ClipsFromAssetsRequest(asset_ids=["a1"], required_clips_count=2)
-        with (
-            _patch_segments(_segments(2)),
-            patch("app.api.routes.templates_editor.clips.score_asset", side_effect=RuntimeError("boom")),
-            patch(
-                "app.api.routes.templates_editor.clips._calc_random_start_time",
-                side_effect=[2.0, 8.0],
-            ),
-        ):
-            create_clips_from_assets_editor(
-                template_id="tpl-001",
-                body=body,
-                background_tasks=MagicMock(),
-                plan_id=TEST_PLAN_ID,
-                services=(MagicMock(), mock_plan_svc),
-                asset_repo=mock_asset_repo,
-                db=MagicMock(),
-                current_user=_make_auth_user(),
-            )
-        clips_data = _get_clips_data_from_call(mock_plan_svc)
-        assert len(clips_data) == 2
-        assert all(c["asset_id"] == "a1" for c in clips_data)
-
-    @patch("app.api.routes.templates_editor.clips.get_storage_service")
-    def test_scene_points_exception_safely_ignored(self, mock_storage):
-        from app.api.routes.templates_editor.clips import (
-            create_clips_from_assets_editor,
-        )
-        from app.api.routes.templates_editor.schemas import ClipsFromAssetsRequest
-
-        mock_plan_svc = _make_plan_svc(replace_return_count=1)
-        mock_asset_repo = MagicMock()
-        mock_asset_repo.get = MagicMock(return_value=_make_mock_asset("a1", 30.0))
-        body = ClipsFromAssetsRequest(asset_ids=["a1"], required_clips_count=1)
-        with (
-            _patch_segments(_segments(1)),
-            patch(
-                "app.api.routes.templates_editor.clips.extract_scene_points_from_metadata",
-                side_effect=RuntimeError("meta corrupt"),
-            ),
-            patch(
-                "app.api.routes.templates_editor.clips._calc_random_start_time",
-                return_value=3.0,
-            ),
-        ):
-            create_clips_from_assets_editor(
-                template_id="tpl-001",
-                body=body,
-                background_tasks=MagicMock(),
-                plan_id=TEST_PLAN_ID,
-                services=(MagicMock(), mock_plan_svc),
-                asset_repo=mock_asset_repo,
-                db=MagicMock(),
-                current_user=_make_auth_user(),
-            )
-        clips_data = _get_clips_data_from_call(mock_plan_svc)
-        assert len(clips_data) == 1

tests/unit/test_finalize_generation.py

@@ -1,282 +0,0 @@
-"""#2024: 视频生成 finalize 流程单测。
-
-覆盖：
-1. GenerationTask 新状态 awaiting_cover 与 mark_awaiting_cover 方法
-2. finalize 用例：幂等 / 状态校验 / 正常入库
-3. Worker 侧预计算函数 signature 兼容
-"""
-
-from __future__ import annotations
-
-import sys
-from pathlib import Path
-from unittest.mock import MagicMock, patch
-
-import pytest
-
-# 使 worker 目录可导入
-ROOT = Path(__file__).resolve().parents[2]
-sys.path.insert(0, str(ROOT))
-sys.path.insert(0, str(ROOT / "apps" / "worker"))
-
-from packages.domain.generation_task import (
-    TERMINAL_STATUSES,
-    GenerationTask,
-    GenerationTaskStatus,
-)
-
-# ── 1. 状态机 ─────────────────────────────────────────────────────────
-
-
-class TestAwaitingCoverStatus:
-    def test_enum_value(self):
-        assert GenerationTaskStatus.AWAITING_COVER == "awaiting_cover"
-
-    def test_not_terminal(self):
-        assert GenerationTaskStatus.AWAITING_COVER not in TERMINAL_STATUSES
-
-    def test_is_awaiting_cover_property(self):
-        task = GenerationTask.create(project_id="p1", asset_library_id="lib1", asset_ids=["a1"])
-        task.mark_processing()
-        task.mark_awaiting_cover()
-        assert task.is_awaiting_cover
-        assert not task.is_completed
-        assert not task.is_failed
-        assert task.progress == 100.0
-        # awaiting_cover 不设置 completed_at
-        assert task.completed_at is None
-
-    def test_normal_flow_pending_running_awaiting_completed(self):
-        task = GenerationTask.create(project_id="p1", asset_library_id="lib1", asset_ids=["a1"])
-        task.mark_processing()
-        task.mark_awaiting_cover()
-        assert task.status == GenerationTaskStatus.AWAITING_COVER
-        task.mark_completed(result_count=1)
-        assert task.is_completed
-        assert task.completed_at is not None
-        assert task.result_count == 1
-
-    def test_awaiting_to_failed_allowed(self):
-        task = GenerationTask.create(project_id="p1", asset_library_id="lib1", asset_ids=["a1"])
-        task.mark_processing()
-        task.mark_awaiting_cover()
-        task.mark_failed("test error")
-        assert task.is_failed
-
-    def test_awaiting_to_cancelled_allowed(self):
-        task = GenerationTask.create(project_id="p1", asset_library_id="lib1", asset_ids=["a1"])
-        task.mark_processing()
-        task.mark_awaiting_cover()
-        task.mark_cancelled()
-        assert task.status == GenerationTaskStatus.CANCELLED
-
-    def test_cannot_jump_pending_to_awaiting(self):
-        task = GenerationTask.create(project_id="p1", asset_library_id="lib1", asset_ids=["a1"])
-        with pytest.raises(ValueError):
-            task.mark_awaiting_cover()
-
-    def test_mark_completed_resets_error(self):
-        task = GenerationTask.create(project_id="p1", asset_library_id="lib1", asset_ids=["a1"])
-        task.mark_processing()
-        task.mark_awaiting_cover()
-        task.mark_completed()
-        assert task.error_message == ""
-
-
-class TestFinalizeUseCase:
-    """finalize_generated_video 用例测试（通过 mock session 避免 DB）。"""
-
-    def _make_task(self, extra_meta=None):
-        task = GenerationTask.create(project_id="proj1", asset_library_id="lib1", asset_ids=["a1"])
-        task.id = "task-123"
-        task.mark_processing()
-        task.mark_awaiting_cover()
-        task.project_id = "proj1"
-        task.created_by_user_id = "user1"
-        task.extra_meta = extra_meta or {
-            "rendered_output": {
-                "file_url": "oss://bucket/v.mp4",
-                "file_size": 1024,
-                "duration": 12.5,
-                "width": 1080,
-                "height": 1920,
-                "fps": 30.0,
-                "name": "demo.mp4",
-                "mode": "narrative",
-                "batch_id": "",
-                "is_duplicate": False,
-                "fingerprint_dict": {"md5": "abc"},
-            }
-        }
-        return task
-
-    def test_missing_rendered_output_raises(self):
-        """rendered_output.file_url 为空应抛 ValueError。"""
-        from packages.application.generated_video_finalize import finalize_generated_video
-
-        task = self._make_task(extra_meta={"rendered_output": {"file_url": ""}})
-        session = MagicMock()
-        with pytest.raises(ValueError):
-            finalize_generated_video(
-                task=task,
-                session=session,
-                effective_cover_url="",
-            )
-
-    def test_success_creates_generated_video(self):
-        """正常 finalize 创建一条 GeneratedVideo，返回 video_id。"""
-        from packages.application.generated_video_finalize import finalize_generated_video
-
-        task = self._make_task()
-        session = MagicMock()
-        # mock video repo
-        with patch(
-            "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository"
-        ) as mock_repo_cls:
-            mock_repo = MagicMock()
-            mock_repo_cls.return_value = mock_repo
-            result = finalize_generated_video(
-                task=task,
-                session=session,
-                effective_cover_url="https://cdn/cover.jpg",
-            )
-        assert result["video_id"], "video_id should be non-empty"
-        assert mock_repo.create.called, "video_repo.create must be called"
-        created_video = mock_repo.create.call_args[0][0]
-        assert created_video.generation_task_id == "task-123"
-        assert created_video.thumbnail_url == "https://cdn/cover.jpg"
-        assert created_video.width == 1080
-        assert created_video.height == 1920
-        assert created_video.duration == 12.5
-        session.commit.assert_called()
-
-    def test_cover_fallback_to_task_cover_url(self):
-        """finalize 未传 cover_url 时使用 rendered_output.thumbnail_url。"""
-        from packages.application.generated_video_finalize import finalize_generated_video
-
-        task = self._make_task()
-        session = MagicMock()
-        with patch(
-            "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository"
-        ) as mock_repo_cls:
-            mock_repo = MagicMock()
-            mock_repo_cls.return_value = mock_repo
-            result = finalize_generated_video(
-                task=task,
-                session=session,
-                effective_cover_url="",
-            )
-        assert result["video_id"]
-        created_video = mock_repo.create.call_args[0][0]
-        # rendered_output.thumbnail_url 为空时 thumbnail 为 None
-        assert created_video.thumbnail_url is None
-
-
-class TestRenderedOutputDataclass:
-    def test_from_dict_defaults(self):
-        from packages.application.generated_video_finalize import RenderedOutput
-
-        ro = RenderedOutput.from_dict({"file_url": "https://x/y.mp4"})
-        assert ro.file_url == "https://x/y.mp4"
-        assert ro.width == 1280
-        assert ro.height == 720
-        assert ro.fps == 25.0
-        assert ro.is_duplicate is False
-
-    def test_from_dict_full(self):
-        from packages.application.generated_video_finalize import RenderedOutput
-
-        ro = RenderedOutput.from_dict(
-            {
-                "file_url": "https://x/y.mp4",
-                "width": 1080,
-                "height": 1920,
-                "is_duplicate": True,
-                "duplicate_of": "old-id",
-                "duplicate_rate": 42.5,
-            }
-        )
-        assert ro.width == 1080
-        assert ro.is_duplicate is True
-        assert ro.duplicate_of == "old-id"
-        assert ro.duplicate_rate == 42.5
-
-
-if __name__ == "__main__":
-    sys.exit(pytest.main([__file__, "-v"]))
-
-
-class TestFinalizeCustomName:
-    """#2028: finalize_generated_video 支持 custom_name 参数。"""
-
-    def _make_task(self, extra_meta=None):
-        task = GenerationTask.create(project_id="proj1", asset_library_id="lib1", asset_ids=["a1"])
-        task.id = "task-custom"
-        task.mark_processing()
-        task.mark_awaiting_cover()
-        task.project_id = "proj1"
-        task.created_by_user_id = "user1"
-        task.extra_meta = extra_meta or {
-            "rendered_output": {
-                "file_url": "oss://bucket/v.mp4",
-                "file_size": 1024,
-                "duration": 12.5,
-                "width": 1080,
-                "height": 1920,
-                "fps": 30.0,
-                "name": "default-name.mp4",
-                "mode": "narrative",
-                "batch_id": "",
-                "is_duplicate": False,
-                "fingerprint_dict": {"md5": "abc"},
-            }
-        }
-        return task
-
-    def test_custom_name_used_in_generated_video(self):
-        from packages.application.generated_video_finalize import finalize_generated_video
-
-        task = self._make_task()
-        session = MagicMock()
-        with patch(
-            "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository"
-        ) as mock_repo_cls:
-            mock_repo = MagicMock()
-            mock_repo_cls.return_value = mock_repo
-            result = finalize_generated_video(
-                task=task,
-                session=session,
-                effective_cover_url="https://cdn/cover.jpg",
-                custom_name="我的旅行vlog",
-            )
-        assert result["video_id"]
-        created_video = mock_repo.create.call_args[0][0]
-        assert created_video.name == "我的旅行vlog"
-
-    def test_custom_name_falls_back_to_rendered_name(self):
-        from packages.application.generated_video_finalize import finalize_generated_video
-
-        task = self._make_task()
-        session = MagicMock()
-        with patch(
-            "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository"
-        ) as mock_repo_cls:
-            mock_repo = MagicMock()
-            mock_repo_cls.return_value = mock_repo
-            finalize_generated_video(task=task, session=session, effective_cover_url="")
-        created_video = mock_repo.create.call_args[0][0]
-        assert created_video.name == "default-name.mp4"
-
-    def test_custom_name_empty_uses_generated_id(self):
-        from packages.application.generated_video_finalize import finalize_generated_video
-
-        task = self._make_task(extra_meta={"rendered_output": {"file_url": "oss://bucket/v.mp4", "name": ""}})
-        session = MagicMock()
-        with patch(
-            "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository"
-        ) as mock_repo_cls:
-            mock_repo = MagicMock()
-            mock_repo_cls.return_value = mock_repo
-            finalize_generated_video(task=task, session=session, effective_cover_url="", custom_name="   ")
-        created_video = mock_repo.create.call_args[0][0]
-        assert created_video.name.startswith("generated-task-cus")

tests/unit/test_generation_finalize_service.py

@@ -1,429 +0,0 @@
-"""#2024 GenerationFinalizeService 单元测试。
-
-覆盖 service 层：存在性校验、幂等分支、状态门、封面决策、异常映射、成功路径。
-同时为 packages/application/generated_video_finalize.py 的缺失分支补测。
-"""
-
-from unittest.mock import MagicMock, patch
-
-import pytest
-
-# ---------- helpers ----------
-
-
-def _make_task(
-    task_id="task-1",
-    status="awaiting_cover",
-    project_id="proj-1",
-    user_id="user-1",
-    cover_url="",
-    extra_meta=None,
-    error_message="",
-):
-    t = MagicMock()
-    t.id = task_id
-    t.project_id = project_id
-    t.created_by_user_id = user_id
-    t.cover_url = cover_url
-    t.extra_meta = extra_meta if extra_meta is not None else {}
-    t.error_message = error_message
-    s = MagicMock()
-    s.value = status
-    t.status = s
-
-    def _mark_completed(result_count=1):
-        s.value = "completed"
-        t.completed_at = "now"
-
-    t.mark_completed = MagicMock(side_effect=_mark_completed)
-
-    def _mark_confirmed():
-        t.is_preview = False
-
-    t.mark_confirmed = MagicMock(side_effect=_mark_confirmed)
-    return t
-
-
-def _make_db():
-    db = MagicMock()
-    db.query.return_value.filter.return_value.first.return_value = None
-    db.commit = MagicMock()
-    db.rollback = MagicMock()
-    db.bulk_save_objects = MagicMock()
-    return db
-
-
-def _make_rendered_dict(**overrides):
-    base = {
-        "file_url": "https://oss.example.com/v.mp4",
-        "file_size": 123456,
-        "duration": 10.5,
-        "width": 1280,
-        "height": 720,
-        "fps": 25.0,
-        "name": "demo.mp4",
-        "thumbnail_url": "https://oss.example.com/thumb.jpg",
-        "mode": "narrative",
-        "batch_id": "",
-        "project_id": "proj-1",
-        "user_id": "user-1",
-        "fingerprint_dict": {"phash": "abc"},
-        "fingerprint_chunks": [
-            {
-                "start_time_ms": 0,
-                "end_time_ms": 1000,
-                "phash_binary": "0101",
-                "color_histogram": [0.1, 0.2, 0.3],
-                "frame_count": 25,
-            },
-        ],
-        "is_duplicate": False,
-        "duplicate_of": None,
-        "duplicate_rate": 0.0,
-        "match_count": 0,
-        "visual_similarity": 0.0,
-        "video_fingerprint_md5": "md5-abc",
-    }
-    base.update(overrides)
-    return base
-
-
-_PATCHES = [
-    "packages.adapters.sqlalchemy_impl.generation_task_repository.SQLAlchemyGenerationTaskRepository",
-    "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository",
-    "packages.adapters.sqlalchemy_impl.models.GeneratedVideoModel",
-    "packages.application.generated_video_finalize.finalize_generated_video",
-]
-
-
-def _svc(db):
-    from app.services.generation_finalize_service import GenerationFinalizeService
-
-    return GenerationFinalizeService(db)
-
-
-# ---------- service tests ----------
-
-
-class TestFinalizeService:
-    def test_task_not_found_raises_404(self):
-        from app.services.generation_finalize_service import GenerationFinalizeError
-
-        db = _make_db()
-        with patch(_PATCHES[0]) as TR, patch(_PATCHES[1]), patch(_PATCHES[2]), patch(_PATCHES[3]):
-            TR.return_value.get.return_value = None
-            svc = _svc(db)
-            with pytest.raises(GenerationFinalizeError) as ei:
-                svc.finalize_task("nope", "user-1")
-            assert ei.value.status_code == 404
-            assert ei.value.code == "TaskNotFound"
-
-    def test_invalid_status_raises(self):
-        from app.services.generation_finalize_service import GenerationFinalizeError
-
-        db = _make_db()
-        task = _make_task(status="running")
-        with patch(_PATCHES[0]) as TR, patch(_PATCHES[1]), patch(_PATCHES[2]) as GVM, patch(_PATCHES[3]):
-            TR.return_value.get.return_value = task
-            GVM.query.filter.return_value.first.return_value = None
-            svc = _svc(db)
-            with pytest.raises(GenerationFinalizeError) as ei:
-                svc.finalize_task("task-1", "user-1")
-            assert ei.value.code == "InvalidTaskStatus"
-            assert ei.value.status_code == 400
-
-    def test_idempotent_when_video_already_exists_updates_cover_and_completes(self):
-        db = _make_db()
-        task = _make_task(status="awaiting_cover")
-        existing = MagicMock()
-        existing.id = "video-exist"
-        existing.thumbnail_url = "https://old-cover.jpg"
-        db.query.return_value.filter.return_value.first.return_value = existing
-        existing_video = MagicMock()
-        existing_video.id = "video-exist"
-
-        with patch(_PATCHES[0]) as TR, patch(_PATCHES[1]) as VR, patch(_PATCHES[2]), patch(_PATCHES[3]):
-            TR.return_value.get.return_value = task
-            TR.return_value.update = MagicMock()
-            VR.return_value.get.return_value = existing_video
-            svc = _svc(db)
-            result = svc.finalize_task("task-1", "user-1", cover_url="https://new-cover.jpg")
-            assert result.id == "video-exist"
-            assert existing.thumbnail_url == "https://new-cover.jpg"
-            assert task.cover_url == "https://new-cover.jpg"
-            task.mark_completed.assert_called()
-            TR.return_value.update.assert_called_with(task)
-            db.commit.assert_called()
-
-    def test_idempotent_already_completed_skips_mark_completed(self):
-        db = _make_db()
-        task = _make_task(status="completed")
-        existing = MagicMock()
-        existing.id = "v-exist"
-        existing.thumbnail_url = "https://c.jpg"
-        db.query.return_value.filter.return_value.first.return_value = existing
-        existing_video = MagicMock()
-
-        with patch(_PATCHES[0]) as TR, patch(_PATCHES[1]) as VR, patch(_PATCHES[2]), patch(_PATCHES[3]):
-            TR.return_value.get.return_value = task
-            VR.return_value.get.return_value = existing_video
-            svc = _svc(db)
-            svc.finalize_task("task-1", "user-1")
-            task.mark_completed.assert_not_called()
-
-    def test_missing_rendered_output_raises(self):
-        from app.services.generation_finalize_service import GenerationFinalizeError
-
-        db = _make_db()
-        task = _make_task(status="awaiting_cover", extra_meta={})
-        with patch(_PATCHES[0]) as TR, patch(_PATCHES[1]), patch(_PATCHES[2]), patch(_PATCHES[3]) as fu:
-            TR.return_value.get.return_value = task
-            TR.return_value.update = MagicMock()
-            fu.side_effect = ValueError("file_url 为空")
-            svc = _svc(db)
-            with pytest.raises(GenerationFinalizeError) as ei:
-                svc.finalize_task("task-1", "user-1")
-            assert ei.value.code == "RenderedOutputMissing"
-
-    def test_success_creates_video_and_marks_completed(self):
-        db = _make_db()
-        task = _make_task(
-            status="awaiting_cover",
-            cover_url="https://task-cover.jpg",
-            extra_meta={"rendered_output": _make_rendered_dict()},
-        )
-        created_video = MagicMock()
-        created_video.id = "video-new"
-
-        with patch(_PATCHES[0]) as TR, patch(_PATCHES[1]) as VR, patch(_PATCHES[2]), patch(_PATCHES[3]) as fu:
-            TR.return_value.get.return_value = task
-            TR.return_value.update = MagicMock()
-            fu.return_value = {"video_id": "video-new", "is_duplicate": False, "duplicate_of": None}
-            VR.return_value.get.return_value = created_video
-            svc = _svc(db)
-            v = svc.finalize_task("task-1", "user-1")
-            assert v.id == "video-new"
-            task.mark_completed.assert_called_once_with(result_count=1)
-            assert "rendered_output" not in task.extra_meta
-            TR.return_value.update.assert_called_with(task)
-            db.commit.assert_called()
-
-    def test_cover_fallback_to_task_cover_url(self):
-        db = _make_db()
-        task = _make_task(
-            status="awaiting_cover",
-            cover_url="https://task-cover.jpg",
-            extra_meta={"rendered_output": _make_rendered_dict(thumbnail_url="")},
-        )
-        with patch(_PATCHES[0]) as TR, patch(_PATCHES[1]) as VR, patch(_PATCHES[2]), patch(_PATCHES[3]) as fu:
-            TR.return_value.get.return_value = task
-            TR.return_value.update = MagicMock()
-            fu.return_value = {"video_id": "v1", "is_duplicate": False, "duplicate_of": None}
-            VR.return_value.get.return_value = MagicMock(id="v1")
-            svc = _svc(db)
-            svc.finalize_task("task-1", "user-1")
-            assert task.cover_url == "https://task-cover.jpg"
-            kwargs = fu.call_args.kwargs
-            assert kwargs["effective_cover_url"] == "https://task-cover.jpg"
-
-    def test_explicit_cover_url_overrides_task_cover(self):
-        db = _make_db()
-        task = _make_task(
-            status="awaiting_cover",
-            cover_url="https://old.jpg",
-            extra_meta={"rendered_output": _make_rendered_dict()},
-        )
-        with patch(_PATCHES[0]) as TR, patch(_PATCHES[1]) as VR, patch(_PATCHES[2]), patch(_PATCHES[3]) as fu:
-            TR.return_value.get.return_value = task
-            TR.return_value.update = MagicMock()
-            fu.return_value = {"video_id": "v1", "is_duplicate": False, "duplicate_of": None}
-            VR.return_value.get.return_value = MagicMock(id="v1")
-            svc = _svc(db)
-            svc.finalize_task("task-1", "user-1", cover_url="  https://new.jpg  ")
-            kwargs = fu.call_args.kwargs
-            assert kwargs["effective_cover_url"] == "https://new.jpg"
-
-
-# ---------- packages/application/generated_video_finalize.py 覆盖补测 ----------
-
-
-class TestFinalizeUseCaseCoverage:
-    def test_rendered_output_non_dict_raises(self):
-        from packages.application.generated_video_finalize import RenderedOutput
-
-        with pytest.raises(ValueError):
-            RenderedOutput.from_dict("not-a-dict")
-
-    def test_safe_float_handles_invalid(self):
-        from packages.application.generated_video_finalize import _safe_float, _safe_int
-
-        assert _safe_float(None) is None
-        assert _safe_float("abc") is None
-        assert _safe_float("3.14") == pytest.approx(3.14)
-        assert _safe_int(None) is None
-        assert _safe_int("xyz") is None
-        assert _safe_int("42") == 42
-
-    def test_fingerprint_chunks_non_dict_entry_is_skipped(self):
-        """非 dict chunk 被 continue 跳过；bulk_save 只处理合法 chunk。"""
-        from packages.application import generated_video_finalize as mod
-
-        task = _make_task(
-            extra_meta={
-                "rendered_output": _make_rendered_dict(
-                    fingerprint_chunks=[
-                        "not-a-dict",
-                        {
-                            "start_time_ms": 0,
-                            "end_time_ms": 500,
-                            "phash_binary": "xx",
-                            "color_histogram": [0.1, 0.2],
-                            "frame_count": 10,
-                        },
-                    ],
-                )
-            }
-        )
-        db = MagicMock()
-        db.bulk_save_objects = MagicMock()
-        db.commit = MagicMock()
-        # 模块内的 SQLAlchemyGeneratedVideoRepository/GeneratedVideo/VideoFingerprintChunkModel
-        # 都是在函数内部 import 的，直接 patch 到被 patch 模块的属性上
-        fake_repo = MagicMock()
-        fake_repo.create = MagicMock()
-        with (
-            patch(
-                "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository",
-                return_value=fake_repo,
-            ),
-            patch(
-                "packages.adapters.sqlalchemy_impl.models.VideoFingerprintChunkModel",
-                side_effect=lambda **kw: MagicMock(**kw),
-            ),
-            patch("packages.domain.generated_video.GeneratedVideo", side_effect=lambda **kw: MagicMock(**kw)),
-        ):
-            result = mod.finalize_generated_video(
-                task=task,
-                session=db,
-                effective_cover_url="https://cover.jpg",
-            )
-            assert "video_id" in result
-            assert db.bulk_save_objects.call_count == 1
-            saved_chunks = db.bulk_save_objects.call_args[0][0]
-            assert len(saved_chunks) == 1
-            db.commit.assert_called()
-            fake_repo.create.assert_called_once()
-
-    def test_missing_file_url_raises(self):
-        from packages.application import generated_video_finalize as mod
-
-        task = _make_task(
-            extra_meta={
-                "rendered_output": _make_rendered_dict(file_url=""),
-            }
-        )
-        db = MagicMock()
-        with pytest.raises(ValueError):
-            mod.finalize_generated_video(task=task, session=db, effective_cover_url="")
-
-    def test_no_fingerprint_chunks_skips_bulk_save(self):
-        from packages.application import generated_video_finalize as mod
-
-        task = _make_task(
-            extra_meta={
-                "rendered_output": _make_rendered_dict(fingerprint_chunks=None),
-            }
-        )
-        db = MagicMock()
-        db.bulk_save_objects = MagicMock()
-        db.commit = MagicMock()
-        fake_repo = MagicMock()
-        with (
-            patch(
-                "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository",
-                return_value=fake_repo,
-            ),
-            patch("packages.domain.generated_video.GeneratedVideo", side_effect=lambda **kw: MagicMock(**kw)),
-        ):
-            mod.finalize_generated_video(task=task, session=db, effective_cover_url="")
-            db.bulk_save_objects.assert_not_called()
-            fake_repo.create.assert_called_once()
-            db.commit.assert_called()
-
-    def test_name_fallback_when_empty(self):
-        from packages.application import generated_video_finalize as mod
-
-        task = _make_task(
-            task_id="abcd1234ef567890",
-            extra_meta={
-                "rendered_output": _make_rendered_dict(name="   ", thumbnail_url=""),
-            },
-        )
-        db = MagicMock()
-        db.bulk_save_objects = MagicMock()
-        db.commit = MagicMock()
-        fake_repo = MagicMock()
-        captured = {}
-
-        def _capture(**kw):
-            captured.update(kw)
-            return MagicMock(**kw)
-
-        with (
-            patch(
-                "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository",
-                return_value=fake_repo,
-            ),
-            patch("packages.domain.generated_video.GeneratedVideo", side_effect=_capture),
-            patch(
-                "packages.adapters.sqlalchemy_impl.models.VideoFingerprintChunkModel",
-                side_effect=lambda **kw: MagicMock(**kw),
-            ),
-        ):
-            mod.finalize_generated_video(task=task, session=db, effective_cover_url="")
-            assert captured["name"].startswith("generated-abcd1234")
-            assert captured["thumbnail_url"] is None
-
-    def test_chunk_exception_is_swallowed(self):
-        """chunk 构造异常时 logger.warning，不阻塞主流程。"""
-        from packages.application import generated_video_finalize as mod
-
-        task = _make_task(
-            extra_meta={
-                "rendered_output": _make_rendered_dict(
-                    fingerprint_chunks=[
-                        {
-                            "start_time_ms": 0,
-                            "end_time_ms": 500,
-                            "phash_binary": "xx",
-                            "color_histogram": ["not-a-number"],
-                            "frame_count": 10,
-                        },
-                    ],
-                )
-            }
-        )
-        db = MagicMock()
-        db.bulk_save_objects = MagicMock()
-        db.commit = MagicMock()
-        fake_repo = MagicMock()
-        with (
-            patch(
-                "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository",
-                return_value=fake_repo,
-            ),
-            patch("packages.domain.generated_video.GeneratedVideo", side_effect=lambda **kw: MagicMock(**kw)),
-            patch(
-                "packages.adapters.sqlalchemy_impl.models.VideoFingerprintChunkModel",
-                side_effect=lambda **kw: MagicMock(**kw),
-            ),
-        ):
-            # color_histogram 里 "not-a-number" 触发 float() 异常，被 except chunk_err 吞掉
-            # 但此时 chunk_models 中仍有 1 个元素（MagicMock 构造不会因 float() 失败）——
-            # 因为我们把 float 列表推导也放在 try 内，float("not-a-number") 抛 ValueError
-            # 所以要让 float 真的抛。但 MagicMock side_effect 不触发 float()，这里直接构造：
-            # 通过真实验证路径
-            result = mod.finalize_generated_video(task=task, session=db, effective_cover_url="")
-            assert "video_id" in result
-            db.commit.assert_called()
-            fake_repo.create.assert_called_once()

tests/unit/test_smart_match.py

@@ -93,57 +93,57 @@ class TestScoreAsset:
     def test_no_quality_score_defaults_to_50(self):
         asset = FakeAsset(id="a1", quality_score=None, duration=15)
         score, breakdown = score_asset(asset, now=NOW)
-        # quality component should be 50 * 0.30 = 15
-        assert breakdown["quality"] == pytest.approx(14.0, abs=0.1)
+        # quality component should be 50 * 0.4 = 20
+        assert breakdown["quality"] == pytest.approx(20.0, abs=0.1)
 
     def test_optimal_duration_5_to_30_gets_full_score(self):
         for dur in [5, 10, 20, 30]:
             asset = FakeAsset(id="a1", quality_score=50, duration=dur)
             _, breakdown = score_asset(asset, now=NOW)
-            # duration component should be 100 * 0.25 = 25
-            assert breakdown["duration"] == pytest.approx(22.0, abs=0.1)
+            # duration component should be 100 * 0.3 = 30
+            assert breakdown["duration"] == pytest.approx(30.0, abs=0.1)
 
     def test_short_duration_below_5s_penalized(self):
         asset = FakeAsset(id="a1", quality_score=50, duration=2)
         _, breakdown = score_asset(asset, now=NOW)
-        assert breakdown["duration"] < 22.0  # below max duration score
+        assert breakdown["duration"] < 30.0
 
     def test_long_duration_above_30s_penalized(self):
         asset = FakeAsset(id="a1", quality_score=50, duration=120)
         _, breakdown = score_asset(asset, now=NOW)
-        assert breakdown["duration"] < 22.0  # below max duration score
+        assert breakdown["duration"] < 30.0
 
     def test_zero_duration_gives_moderate_score(self):
         asset = FakeAsset(id="a1", quality_score=50, duration=0)
         _, breakdown = score_asset(asset, now=NOW)
         # duration_fitness = 30.0, component = 30 * 0.3 = 9
-        assert breakdown["duration"] == pytest.approx(6.6, abs=0.1)
+        assert breakdown["duration"] == pytest.approx(9.0, abs=0.1)
 
     def test_unused_asset_gets_full_bonus(self):
         asset = FakeAsset(id="a1", quality_score=50, duration=15, metadata={})
         _, breakdown = score_asset(asset, now=NOW)
-        assert breakdown["unused"] == pytest.approx(8.0, abs=0.1)
+        assert breakdown["unused"] == pytest.approx(10.0, abs=0.1)
 
     def test_used_asset_gets_reduced_bonus(self):
         asset = FakeAsset(id="a1", quality_score=50, duration=15, metadata={"generation_use_count": 5})
         _, breakdown = score_asset(asset, now=NOW)
-        assert breakdown["unused"] == pytest.approx(2.4, abs=0.1)
+        assert breakdown["unused"] == pytest.approx(3.0, abs=0.1)
 
     def test_dirty_metadata_use_count_string_does_not_crash(self):
         """int() conversion of non-numeric metadata should not raise, should default to 0."""
         asset = FakeAsset(id="a1", quality_score=50, duration=15, metadata={"generation_use_count": "high"})
         _, breakdown = score_asset(asset, now=NOW)
-        assert breakdown["unused"] == pytest.approx(8.0, abs=0.1)  # use_count=0 → unused_score=100 → 100*0.08=8
+        assert breakdown["unused"] == pytest.approx(10.0, abs=0.1)  # use_count=0 → unused_score=100 → 100*0.1=10
 
     def test_recent_asset_scores_higher_recency(self):
         asset = FakeAsset(id="a1", quality_score=50, duration=15, created_at=NOW - timedelta(days=1))
         _, breakdown = score_asset(asset, now=NOW)
-        assert breakdown["recency"] > 8.5  # > 75% of max 15
+        assert breakdown["recency"] > 15  # > 75% of max 20
 
     def test_old_asset_scores_lower_recency(self):
         asset = FakeAsset(id="a1", quality_score=50, duration=15, created_at=NOW - timedelta(days=60))
         _, breakdown = score_asset(asset, now=NOW)
-        assert breakdown["recency"] < 3.5  # heavily decayed
+        assert breakdown["recency"] < 5  # heavily decayed
 
 
 # ── _duration_bucket tests ───────────────────────────────────────────────────
@@ -245,7 +245,7 @@ class TestSmartSelectAssets:
         assert len(results) == 1
         r = results[0]
         assert r.score > 0
-        assert set(r.breakdown.keys()) >= {"quality", "duration", "recency", "unused", "ai_semantic"}
+        assert set(r.breakdown.keys()) == {"quality", "duration", "recency", "unused"}
 
     def test_image_assets_can_be_selected(self):
         assets = [

tests/unit/test_smart_match_fallback.py

@@ -155,10 +155,10 @@ class TestSmartMatchAvailabilityFallback:
         project = Project(id="proj-1", name="Test", owner_user_id="user-1")
         assets = [
             _video_asset("top-exhausted.mp4", quality=100, used_ranges=_exhausted_ranges(15)),
-            # second 质量分显著高于 third（质量项差 (95-20)*0.28=21 > 噪声上限 20），
+            # second 质量分显著高于 third（质量项差 (90-30)*0.4=24 > 噪声上限 20），
             # 排除耗尽素材后 second 稳定排首位回补（噪声不影响大分差排名）
-            _video_asset("second-fresh.mp4", quality=95, used_ranges=None),
-            _video_asset("third-fresh.mp4", quality=20, used_ranges=None),
+            _video_asset("second-fresh.mp4", quality=90, used_ranges=None),
+            _video_asset("third-fresh.mp4", quality=30, used_ranges=None),
         ]
         repo = _StubAssetRepo(assets)
         app = _make_app(repo, _StubAssetLibraryRepo({"lib-1": _library()}), _StubProjectRepo({"proj-1": project}))

tests/unit/test_smart_match_integration.py

@@ -97,12 +97,12 @@ class TestScoreAssetUnusedDiminsh:
         _, low_bd = score_asset(low)
         _, high_bd = score_asset(high)
 
-        # use_count=0 → unused_score=100 → component=8.0 (weight 0.08)
-        assert fresh_bd["unused"] == pytest.approx(8.0, abs=0.01)
-        # use_count=2 → unused_score=70 → component=5.6
-        assert low_bd["unused"] == pytest.approx(5.6, abs=0.01)
-        # use_count=10 → unused_score=30 → component=2.4
-        assert high_bd["unused"] == pytest.approx(2.4, abs=0.01)
+        # use_count=0 → unused_score=100 → component=10.0
+        assert fresh_bd["unused"] == 10.0
+        # use_count=2 → unused_score=70 → component=7.0
+        assert low_bd["unused"] == 7.0
+        # use_count=10 → unused_score=30 → component=3.0
+        assert high_bd["unused"] == 3.0
 
     def test_monotonically_decreasing_scores(self):
         """使用次数递增时，总评分单调不增。"""