fix(smart-match): limit 算法取 segments.length 下限，保证每片段至少 1 个素材

computeLimitFromSegments 原逻辑 Math.ceil(totalSeconds/15) 在短模板（如 14s 模板 4 片段）下仅返回 1，导致后端只分配 1 个素材无法覆盖全部片段。改为 Math.max(segments.length, ...) 保证每个片段至少能分到 1 个素材。
2026-09-01 12:11:36 +08:00
36 changed files with 329 additions and 2119 deletions
@@ -1,105 +0,0 @@
-name: CI Base Image Build
-
-on:
-  push:
-    branches:
-      - develop
-      - main
-    paths:
-      - 'requirements-base.txt'
-      - 'requirements-dev.txt'
-      - 'infra/docker/ci.Dockerfile'
-  workflow_dispatch:
-    inputs:
-      reason:
-        description: "触发原因"
-        required: false
-        default: "手动触发 - ci-base 镜像重建"
-
-concurrency:
-  group: ci-base-image-build
-  cancel-in-progress: false
-
-jobs:
-  build-ci-base:
-    name: Build CI Base Image
-    runs-on: runtime-builder
-    timeout-minutes: 60
-    steps:
-    - name: Checkout code
-      shell: sh
-      env:
-        GITHUB_TOKEN: ${{ github.token }}
-      run: |
-        curl -sH "Authorization: token $GITHUB_TOKEN" \
-          "${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/raw/scripts/ci/step_checkout.sh?ref=${GITHUB_SHA}" \
-          | bash
-
-    - name: Docker login to Gitea Registry
-      shell: sh
-      env:
-        GITEA_REGISTRY_USER: xiaoxia
-        GITEA_REGISTRY_TOKEN: ${{ secrets.REGISTRY_TOKEN }}
-      run: |
-        set -eu
-        for i in 1 2 3; do
-          echo "=== Docker login 尝试 $i/3 ==="
-          if docker login git.xiaoxiajianji.com -u "${GITEA_REGISTRY_USER}" -p "${GITEA_REGISTRY_TOKEN}"; then
-            echo "✅ Docker login successful"
-            break
-          fi
-          echo "❌ Docker login 失败（尝试 $i/3），5s 后重试..."
-          sleep 5
-        done
-
-    - name: Build and push CI base image
-      shell: sh
-      run: |
-        set -eu
-        IMAGE="git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas/ci-base"
-        VERSION_TAG="deps-$(date +%Y%m%d-%H%M)-${GITHUB_SHA::8}"
-
-        echo "=== Building CI base image (tags: latest, ${VERSION_TAG}) ==="
-        docker build --progress=plain \
-          -f infra/docker/ci.Dockerfile \
-          -t "${IMAGE}:latest" \
-          -t "${IMAGE}:${VERSION_TAG}" \
-          .
-        echo "✅ Image built successfully"
-
-        echo "=== Pushing ${VERSION_TAG} ==="
-        docker push "${IMAGE}:${VERSION_TAG}"
-        echo "=== Pushing latest ==="
-        docker push "${IMAGE}:latest"
-        echo "✅ Pushed to Gitea Registry"
-
-    - name: Verify image
-      shell: sh
-      run: |
-        set -eu
-        IMAGE="git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas/ci-base:latest"
-        echo "=== Verifying pinned deps in fresh image ==="
-        docker run --rm "${IMAGE}" /opt/xiaoxia-ci-venv/bin/python -c \
-          "import httpcore, h2, numpy, httpx; print('VERSIONS:', httpcore.__version__, h2.__version__, numpy.__version__, httpx.__version__)"
-
-    - name: Notify result
-      if: always()
-      continue-on-error: true
-      shell: sh
-      env:
-        CI_NOTIFY_WEBHOOK: ${{ secrets.CI_NOTIFY_WEBHOOK }}
-      run: |
-        set +e
-        if [ "${{ job.status }}" = "success" ]; then
-          NOTIFY_MODE=success JOB_NAME="CI Base Image Build" python3 scripts/ci_notify.py
-        else
-          NOTIFY_MODE=failure JOB_NAME="CI Base Image Build" python3 scripts/ci_notify.py
-        fi
-
-    - name: Cleanup
-      if: always()
-      shell: sh
-      run: |
-        IMAGE="git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas/ci-base"
-        docker rmi "${IMAGE}:latest" 2>/dev/null || true
-        echo "Cleanup done"
@@ -23,10 +23,6 @@ import re
 from app.auth import AuthenticatedUser, get_current_user
 from app.core.storage import get_storage_service
 from app.dependencies import get_asset_repository, get_db_session
-
-# 默认转场时长（与 worker 端保持一致）
-_DEFAULT_TRANSITION_DURATION = 0.5
-
 from app.services.asset_segment_tracker import (
    REUSE_RATIO_LIMIT,
    SEGMENT_EDGE_GAP,
@@ -48,7 +44,6 @@ from packages.adapters.sqlalchemy_impl.template_repository import (
    SQLAlchemyTemplateRepository,
 )
 from packages.domain.plan_generator_utils import _calc_random_start_time
-from packages.domain.smart_match import score_asset
 from packages.shared.mediakit_client import get_mediakit_client

 from .dependencies import get_draft_plan_id, get_editor_services
@@ -587,47 +582,6 @@ def _get_mediakit_recommendations(
        return {}


-def _calc_plan_internal_duplicate_rate(clips_data: list[dict]) -> float:
-    """估算单条成片内部重复率（%）.
-
-    检查本条成片中同一素材是否有重叠的时间区间。
-    重叠时长 / 成片总时长 * 100 = 内部重复率。
-    这是一个轻量估算，不依赖视频指纹；完整查重由 worker 异步完成。
-    """
-    if not clips_data:
-        return 0.0
-
-    # 按素材分组
-    by_asset: dict[str, list[tuple[float, float]]] = {}
-    total_duration = 0.0
-    for c in clips_data:
-        aid = c.get("asset_id", "")
-        if not aid:
-            continue
-        start = c.get("start_time", 0.0)
-        end = start + c.get("duration", 0.0)
-        by_asset.setdefault(aid, []).append((start, end))
-        total_duration += c.get("duration", 0.0)
-
-    if total_duration <= 0:
-        return 0.0
-
-    # 检查同素材内的区间重叠
-    overlap_duration = 0.0
-    for segments in by_asset.values():
-        if len(segments) < 2:
-            continue
-        segments_sorted = sorted(segments, key=lambda s: s[0])
-        last_end = segments_sorted[0][1]
-        for start, end in segments_sorted[1:]:
-            overlap = max(0.0, min(end, last_end) - start)
-            if overlap > 0:
-                overlap_duration += overlap
-            last_end = max(last_end, end)
-
-    return round(overlap_duration / total_duration * 100, 1)
-
-
@router.post("/clips/from-assets", response_model=ClipsFromAssetsResponse)
 def create_clips_from_assets_editor(
    template_id: str,
@@ -672,14 +626,10 @@ def create_clips_from_assets_editor(
    # 2. 获取素材实际时长（去重查询）
    unique_asset_ids = list(dict.fromkeys(asset_ids))
    asset_durations: dict[str, float] = {}
-    asset_smart_scores: dict[str, float] = {}
    for asset_id in unique_asset_ids:
        asset = asset_repo.get(asset_id)
        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

    # 3. 在内存中计算所有片段数据（使用随机起始时间，不调用MediaKit）
    # 读取素材 metadata 中持久化的历史已用区间（跨任务/跨调用去重），
@@ -712,51 +662,19 @@ def create_clips_from_assets_editor(
            return False
        return reused_durations.get(aid, 0.0) / assigned > REUSE_RATIO_LIMIT

-    # 素材耗尽标志：某轮循环中所有素材均被跳过时为 True
-    all_assets_exhausted = False
-
-    # 计算转场重叠补偿：每个 clip 需要额外增加的时长
-    # 目标：渲染后视频总时长 = 模板设定的各片段时长之和
-    # 公式：每 clip 增加 (n_segments - 1) * td / n_segments
-    n_segments = len(segments)
-    if n_segments > 1:
-        transition_compensation = (n_segments - 1) * _DEFAULT_TRANSITION_DURATION / n_segments
-    else:
-        transition_compensation = 0.0
-
-    # 打乱 segments 的处理顺序（分配素材的顺序随机化），但最终 clips_data 按原始 order 排序
-    shuffled_indices = list(range(len(segments)))
-    random.shuffle(shuffled_indices)
-
-    for idx in shuffled_indices:
-        _seg_order, dur_min, dur_max = segments[idx]
+    for i, (_seg_order, dur_min, dur_max) in enumerate(segments):
        # 在 segment 的 duration_min ~ duration_max 之间随机取值（保留一位小数）
        raw_duration = random.uniform(dur_min, dur_max)
-        # 加上转场补偿，确保最终输出时长 = 模板设定总时长
-        raw_duration += transition_compensation

-        # 贪心分配素材：按"已使用次数"升序排列候选素材（使用最少的优先），
-        # 同次数随机打散，避免"A-B-C-D"的固定组合反复出现。
-        # 跳过时长缺失、复用占比已超 10% 阈值的素材；
+        # 轮询分配素材：跳过时长缺失、复用占比已超 15% 阈值的素材；
        # 选中后计算起点，若该素材可用区间耗尽且复用被闸门拒绝（calc 返回 None），
-        # 继续尝试下一个素材
+        # 继续轮询下一个素材
        asset_id = ""
        clip_duration = 0.0
        start_time: float | None = None
-        # 动态按使用次数排序：优先选使用最少的素材，同次数随机打散
-        asset_use_counts = {
-            aid: len(used_segments.get(aid, []))
-            for aid in asset_ids
-        }
-        sorted_candidates = sorted(
-            asset_ids,
-            key=lambda aid: (
-                -asset_smart_scores.get(aid, 0.0),
-                asset_use_counts.get(aid, 0),
-                random.random(),
-            ),
-        )
-        for candidate in sorted_candidates:
+        n_assets = len(asset_ids)
+        for offset in range(n_assets):
+            candidate = asset_ids[(i + offset) % n_assets]
            candidate_total = asset_durations.get(candidate, 0.0)
            if candidate_total <= 0:
                continue
@@ -772,7 +690,7 @@ def create_clips_from_assets_editor(
                continue
            # 随机起始时间（不调用 MediaKit，保证接口快速返回）；100 次避不开
            # 历史区间时走受控复用回调（复用片段累加 reused_durations，回调内部
-            # 预判复用后占比超 10% 则拒绝并返回 None）
+            # 预判复用后占比超 15% 则拒绝并返回 None）
            candidate_start = _calc_random_start_time(
                candidate,
                candidate_duration,
@@ -794,7 +712,6 @@ def create_clips_from_assets_editor(

        if not asset_id or start_time is None:
            # 所有素材时长缺失、复用占比超阈值，或区间耗尽且复用被拒 → 素材可切区间不足
-            all_assets_exhausted = True
            raise HTTPException(
                status_code=status.HTTP_400_BAD_REQUEST,
                detail="素材可切区间不足，请补充新素材",
@@ -810,7 +727,7 @@ def create_clips_from_assets_editor(

        clips_data.append(
            {
-                "order": _seg_order,
+                "order": i,
                "asset_id": asset_id,
                "start_time": start_time,
                "duration": clip_duration,
@@ -818,9 +735,6 @@ def create_clips_from_assets_editor(
            }
        )

-    # 按原始 segment order 排序，确保 clips_data 的 order 字段有序（0,1,2,3...）
-    clips_data.sort(key=lambda c: c["order"])
-
    # 4. 事务性替换：清空旧片段 → 创建新片段 → 标记ready（单事务，失败自动回滚）
    created_count = plan_svc.replace_all_clips_transactional(plan_id, clips_data)

@@ -840,86 +754,19 @@ def create_clips_from_assets_editor(
        unique_asset_ids,
    )

-    # 6. 估算成片内部重复率（本条成片中同一素材的重叠片段时长占比）
-    dup_rate = _calc_plan_internal_duplicate_rate(clips_data)
-    duplicate_warning = None
-    if dup_rate > 50:
-        duplicate_warning = f"查重率 {dup_rate:.1f}% 超过50%，建议更换素材或模板"
-        logger.warning(
-            "from-assets 成片查重率超标: plan_id=%s dup_rate=%.1f%%",
-            plan_id, dup_rate,
-        )
-
-    # 7. 素材耗尽提示
-    exhaustion_warning = None
-    if all_assets_exhausted and created_count < len(segments):
-        exhaustion_warning = (
-            "素材可切区间不足，部分片段使用了复用素材。"
-            "建议：1) 补充更多素材到素材库 2) 使用不同的素材组合生成"
-        )
-
-    # 8. 立即返回响应
+    # 6. 立即返回响应
    return ClipsFromAssetsResponse(
        created_count=created_count,
        plan_id=plan_id,
        clip_ids=[],
-        duplicate_warning=duplicate_warning,
-        exhaustion_warning=exhaustion_warning,
    )


-def _build_scene_segments(
-    scene_changes: list[float],
-    asset_duration: float,
-) -> list[tuple[float, float]]:
-    """根据场景切换点构建镜头段列表.
-
-    Args:
-        scene_changes: 场景切换点时间戳列表（已排序，首位为 0.0）
-        asset_duration: 素材总时长
-
-    Returns:
-        镜头段列表 [(start, end), ...]
-    """
-    segments: list[tuple[float, float]] = []
-    for i, ts in enumerate(scene_changes):
-        end = scene_changes[i + 1] if i + 1 < len(scene_changes) else asset_duration
-        # 只保留有效长度的镜头段（至少 0.5 秒）
-        if end - ts >= 0.5:
-            segments.append((ts, end))
-    return segments
-
-
-def _pick_start_in_scene_segment(
-    seg_start: float,
-    seg_end: float,
-    clip_duration: float,
-) -> float | None:
-    """在镜头段内随机选取一个起始时间点.
-
-    确保 start + clip_duration <= seg_end。
-    若镜头段长度不足以容纳片段，返回 None。
-    """
-    available = seg_end - seg_start - clip_duration
-    if available < 0:
-        return None
-    max_start = seg_start + available
-    return random.uniform(seg_start, max_start)
-
-
 def _update_mediakit_recommendations_async(  # pragma: no cover
    plan_id: str,
    asset_ids: list[str],
 ) -> None:
-    """后台任务：使用 SceneChange 智能选帧并更新片段的起始时间.
-
-    优先使用 SceneChange 策略检测视频镜头切换点，将每个素材按镜头段拆分，
-    各片段优先从不同镜头段中选取起始时间，实现「不同片段展示不同场景」的效果。
-
-    降级策略：
-    1. SceneChange 优先 → detect_scene_changes 内部已含 TimeInterval 降级
-    2. 若 detect_scene_changes 仍返回 None → 回退到旧的 analyze_videos 方式
-    3. 所有方式都失败 → 保持现有随机 start_time，不影响视频生成
+    """后台任务：调用 MediaKit 智能选片并更新片段的起始时间.

    此函数在后台异步执行，不影响接口响应时间。
    失败时静默处理，不影响已创建的片段。
@@ -941,6 +788,12 @@ def _update_mediakit_recommendations_async(  # pragma: no cover
        asset_repo = SQLAlchemyAssetRepository(db)
        plan_svc = EditPlanService(db)

+        # 调用 MediaKit 获取推荐时间
+        recommendations = _get_mediakit_recommendations(asset_ids, asset_repo)
+        if not recommendations:
+            logger.info("后台任务: MediaKit 无推荐结果，跳过更新")
+            return
+
        # 查询该 plan 的所有片段（分批获取，避免硬编码 limit 截断）
        batch_size = 500
        all_clips = []
@@ -963,16 +816,15 @@ def _update_mediakit_recommendations_async(  # pragma: no cover
        unique_asset_ids = list({getattr(c, "asset_id", "") or "" for c in clips} - {""})
        assets_map: dict[str, object] = {a.id: a for a in asset_repo.find_by_ids(unique_asset_ids)}

-        # 按 asset_id 预分组片段对象（按 order 排序，保证按模板顺序分配镜头段）
-        clips_by_asset: dict[str, list] = defaultdict(list)
+        # 按 asset_id 预分组片段时间段（消除 O(N^2) 嵌套循环）
+        clips_by_asset: dict[str, list[tuple[str, float, float]]] = defaultdict(list)
        for clip in clips:
            aid = getattr(clip, "asset_id", "") or ""
-            if aid:
-                clips_by_asset[aid].append(clip)
-        for aid in clips_by_asset:
-            clips_by_asset[aid].sort(key=lambda c: c.order)
+            if aid and clip.start_time is not None:
+                clips_by_asset[aid].append((clip.id, clip.start_time, clip.start_time + clip.duration))

-        # 读取素材全部历史已用区间（跨任务/跨 plan 持久化记录）
+        # 读取素材全部历史已用区间（跨任务/跨 plan 持久化记录）：
+        # MediaKit 挪点必须与随机选片一样避让历史区间，否则会把片段挪回已用过的画面
        historical_segments = get_used_segments(db, unique_asset_ids)

        # 已更新的片段ID（用于排除已移动的旧时间段）
@@ -981,22 +833,16 @@ def _update_mediakit_recommendations_async(  # pragma: no cover
        updated_segments: dict[str, list[tuple[float, float]]] = {}
        updated_count = 0

-        # 尝试获取存储服务（用于生成视频 URL）
-        try:
-            storage = get_storage_service()
-        except Exception:
-            logger.warning("后台任务: 获取存储服务失败，跳过 SceneChange 更新")
-            return
-
-        # 获取 MediaKit 客户端
-        client = get_mediakit_client()
-
-        # 对每个素材，检测场景切换点并分配镜头段
-        for asset_id in unique_asset_ids:
-            asset_clips = clips_by_asset.get(asset_id, [])
-            if not asset_clips:
+        # 遍历片段，按 asset_id 匹配推荐时间
+        for clip in clips:
+            asset_id = getattr(clip, "asset_id", "") or ""
+            if not asset_id or asset_id not in recommendations:
                continue

+            recommended_start = recommendations[asset_id]
+            clip_duration = clip.duration
+
+            # 从预加载字典获取素材（O(1) 查找）
            asset = assets_map.get(asset_id)
            if not asset:
                continue
@@ -1004,143 +850,89 @@ def _update_mediakit_recommendations_async(  # pragma: no cover
            if asset_total <= 0:
                continue

-            # 获取素材视频 URL
-            video_url: str | None = None
-            storage_key = getattr(asset, "storage_key", None) or ""
-            mime = getattr(asset, "mime_type", "") or ""
-            if storage_key and mime.startswith("video/"):
-                try:
-                    video_url = storage.get_download_url(storage_key)
-                except Exception as e:
-                    logger.warning("后台任务: 获取素材URL失败: asset_id=%s error=%s", asset_id, e)
-
-            # 构建该素材的占用区间列表（排除已更新片段）
-            def _get_other_segments(asset_id_inner, clip_id_inner):
-                segs: list[tuple[float, float]] = []
-                for c in clips_by_asset.get(asset_id_inner, []):
-                    cid = c.id
-                    if cid != clip_id_inner and cid not in updated_clip_ids:
-                        segs.append((c.start_time, c.start_time + c.duration))
-                segs.extend(updated_segments.get(asset_id_inner, []))
-                # 并入历史已用区间
-                def _norm(segs_in):
-                    return {(round(float(a), 3), round(float(b), 3)) for a, b in segs_in}
-                return list(_norm(segs) | _norm(historical_segments.get(asset_id_inner, [])))
-
-            # 优先使用 SceneChange 策略
-            scene_segments: list[tuple[float, float]] = []
-            if client.is_available and video_url:
-                scene_changes = client.detect_scene_changes(video_url)
-                if scene_changes is not None:
-                    scene_segments = _build_scene_segments(scene_changes, asset_total)
-                    logger.info(
-                        "后台任务: 素材场景检测完成: asset_id=%s scenes=%d",
-                        asset_id, len(scene_segments),
-                    )
-
-            # SceneChange 未获得有效结果 → 尝试 analyze_videos 作为 fallback
-            if not scene_segments and video_url:
-                fallback_recs = _get_mediakit_recommendations([asset_id], asset_repo)
-                if fallback_recs and asset_id in fallback_recs:
-                    # analyze_videos 只返回单个推荐点，转为单镜头段
-                    rec_start = fallback_recs[asset_id]
-                    scene_segments = [(rec_start, asset_total)]
-                    logger.info(
-                        "后台任务: 使用 analyze_videos fallback: asset_id=%s start=%.2f",
-                        asset_id, rec_start,
-                    )
-
-            if not scene_segments:
-                # 所有方式都失败 → 保持现有随机 start_time
+            # 推荐时间 + 片段时长不能超过素材总时长
+            if recommended_start + clip_duration > asset_total:
                logger.info(
-                    "后台任务: SceneChange 与 analyze_videos 均无结果，保持随机起点: asset_id=%s",
+                    "后台任务: 推荐时间越界，跳过: asset_id=%s recommended=%.2f duration=%.1f total=%.1f",
                    asset_id,
+                    recommended_start,
+                    clip_duration,
+                    asset_total,
                )
                continue

-            # 为每个片段分配不同的镜头段
-            scene_segments_pool = list(scene_segments)  # 可消费的镜头段池
-            for clip in asset_clips:
-                clip_duration = clip.duration
-                recommended_start: float | None = None
+            # 构建排除当前片段及已更新片段后的占用列表（O(M)，M=同素材片段数）
+            other_segments: list[tuple[float, float]] = [
+                (cs, ce)
+                for cid, cs, ce in clips_by_asset.get(asset_id, [])
+                if cid != clip.id and cid not in updated_clip_ids
+            ]
+            other_segments.extend(updated_segments.get(asset_id, []))

-                # 从镜头段池中依次尝试，选一个不冲突的
-                for seg_idx, (seg_start, seg_end) in enumerate(scene_segments_pool):
-                    candidate_start = _pick_start_in_scene_segment(seg_start, seg_end, clip_duration)
-                    if candidate_start is None:
-                        continue  # 镜头段太短，跳过
+            # 并入该素材全部历史已用区间（含其他 plan/其他任务），set 去重：
+            # 本 plan 片段创建时已写入历史记录
+            # 并入该素材全部历史已用区间（含其他 plan/其他任务）。
+            # set 去重前先归一化精度（round 3 位），避免浮点尾差导致逻辑相同的
+            # 区间（如 1.0 与 1.0000000001）被误判为不同区间
+            def _norm(segs):
+                return {(round(float(a), 3), round(float(b), 3)) for a, b in segs}

-                    # 检查越界
-                    if candidate_start + clip_duration > asset_total:
-                        continue
+            other_segments = list(_norm(other_segments) | _norm(historical_segments.get(asset_id, [])))

-                    # 检查与已用区间冲突
-                    other_segs = _get_other_segments(asset_id, clip.id)
-                    if _recommended_time_conflicts(candidate_start, clip_duration, other_segs):
-                        continue
+            # 检查推荐时间是否与同 plan 片段或历史已用区间冲突（含 0.3s 边缘间隙）：
+            # 冲突时放弃该推荐、保留原随机起点（不硬挪到已用过的画面）
+            if _recommended_time_conflicts(recommended_start, clip_duration, other_segments):
+                logger.info(
+                    "后台任务: 推荐时间与同片/历史区间冲突，保留原起点: asset_id=%s recommended=%.2f",
+                    asset_id,
+                    recommended_start,
+                )
+                continue

-                    recommended_start = candidate_start
-                    # 消费该镜头段（从池中移除，下一个片段用不同镜头段）
-                    scene_segments_pool.pop(seg_idx)
-                    break
-
-                if recommended_start is None:
-                    # 镜头段用完或都冲突 → 尝试 _calc_random_start_time 兜底
-                    used_segs_for_calc: dict[str, list[tuple[float, float]]] = {
-                        asset_id: _get_other_segments(asset_id, clip.id)
-                    }
-                    fallback_start = _calc_random_start_time(
-                        asset_id,
-                        clip_duration,
-                        {asset_id: asset_total},
-                        used_segs_for_calc,
-                    )
-                    if fallback_start is None:
-                        continue  # 完全无法分配，保持原起点
-                    recommended_start = fallback_start
-
-                # 更新片段起始时间
+            # 逐个更新并捕获异常（单点失败不影响其他片段）
+            try:
+                old_start = clip.start_time
+                old_end = old_start + clip_duration
+                # MediaKit 移动片段起点 + 同步素材 metadata 区间记录放在同一事务：
+                # 删旧区间记录（按 plan_id + 旧 start 匹配，兼容无 plan_id 的旧数据）、
+                # 写新区间，最后统一 commit；任一步失败整体 rollback，
+                # 保证 clip.start_time 与 metadata.used_time_ranges 不出现不一致。
+                plan_svc.update_clip(clip.id, start_time=recommended_start)
                try:
-                    old_start = clip.start_time
-                    old_end = old_start + clip_duration
-
-                    plan_svc.update_clip(clip.id, start_time=recommended_start)
-                    try:
-                        if remove_used_segment(db, asset_id, old_start, old_end, plan_id=plan_id):
-                            record_used_segments(
-                                db,
-                                asset_id,
-                                recommended_start,
-                                recommended_start + clip_duration,
-                                plan_id,
-                            )
-                    except Exception as me:
-                        logger.warning(
-                            "后台任务: 同步素材区间记录失败，回滚本次片段更新: clip_id=%s error=%s",
-                            clip.id,
-                            me,
+                    if remove_used_segment(db, asset_id, old_start, old_end, plan_id=plan_id):
+                        record_used_segments(
+                            db,
+                            asset_id,
+                            recommended_start,
+                            recommended_start + clip_duration,
+                            plan_id,
                        )
-                        db.rollback()
-                        continue
-                    db.commit()
-                    updated_count += 1
-                    updated_clip_ids.add(clip.id)
-                    updated_segments.setdefault(asset_id, []).append(
-                        (recommended_start, recommended_start + clip_duration)
-                    )
-                    logger.info(
-                        "后台任务: 更新片段起始时间(场景选帧): clip_id=%s asset_id=%s start_time=%.2f",
+                except Exception as me:
+                    logger.warning(
+                        "后台任务: 同步素材区间记录失败，回滚本次片段更新: clip_id=%s error=%s",
                        clip.id,
-                        asset_id,
-                        recommended_start,
+                        me,
                    )
-                except Exception as ue:
-                    logger.warning("后台任务: 单个片段更新失败: clip_id=%s error=%s", clip.id, ue)
-                    try:
-                        db.rollback()
-                    except Exception:
-                        pass
+                    db.rollback()
                    continue
+                db.commit()
+                updated_count += 1
+                updated_clip_ids.add(clip.id)
+            except Exception as ue:
+                logger.warning("后台任务: 单个片段更新失败: clip_id=%s error=%s", clip.id, ue)
+                try:
+                    db.rollback()
+                except Exception:
+                    pass
+                continue
+
+            updated_segments.setdefault(asset_id, []).append((recommended_start, recommended_start + clip_duration))
+            logger.info(
+                "后台任务: 更新片段起始时间: clip_id=%s asset_id=%s start_time=%.2f",
+                clip.id,
+                asset_id,
+                recommended_start,
+            )

        logger.info("后台任务完成: plan_id=%s 成功更新 %d 个片段", plan_id, updated_count)

@@ -189,8 +189,6 @@ class ClipsFromAssetsResponse(BaseModel):
    plan_id: str = ""
    message: str = ""
    clip_ids: List[str] = Field(default_factory=list, description="创建的片段ID列表")
-    duplicate_warning: Optional[str] = Field(default=None, description="查重率超标警告")
-    exhaustion_warning: Optional[str] = Field(default=None, description="素材耗尽警告")


 # ── 封面配置 ────────────────────────────────────────────────────────────────
@@ -3,7 +3,7 @@
 在素材 metadata（assets.classification_result JSON）中持久化已使用的片段时间区间，
 供 from-assets 创建片段时避开历史区间，实现跨任务/跨调用的片段去重；
 素材可用区间耗尽后进入受控复用：允许有限次数（MAX_RANGE_USE_COUNT）复用最久未用
-的历史区间，配合调用方的成片复用占比控制（MAX_REUSE_RATIO = 10%），把任意两条
+的历史区间，配合调用方的成片复用占比控制（MAX_REUSE_RATIO = 15%），把任意两条
 成片的画面重复率控制在阈值内。

 metadata 中的记录字段 ``used_time_ranges``::
@@ -40,14 +40,14 @@ logger = logging.getLogger(__name__)
 USED_RANGES_KEY = "used_time_ranges"

 # ── 受控复用配置常量 ─────────────────────────────────────────────────────────
-MAX_RANGE_USE_COUNT = 2
+MAX_RANGE_USE_COUNT = 3
 """单条历史区间最多被使用次数（含首次），达到后不再参与复用。"""

-REUSE_RATIO_LIMIT = 0.10
-"""单条成片中，单个素材的复用片段累计时长 / 该素材在成片中的总时长上限（10%）。
+REUSE_RATIO_LIMIT = 0.15
+"""单条成片中，单个素材的复用片段累计时长 / 该素材在成片中的总时长上限（15%）。
 超过则该素材不再分配新片段（调用方在轮询分配时跳过）。"""

-SEGMENT_EDGE_GAP = 1.5
+SEGMENT_EDGE_GAP = 0.3
 """冲突判定边缘间隙（秒）：历史区间按 [start-gap, end+gap] 扩边后参与冲突检测，
 避免两条片段首尾紧贴导致画面观感重复；记录仍存实际值。"""

@@ -397,12 +397,12 @@ def make_reuse_callback(
        db: SQLAlchemy session
        asset_durations: 素材 ID -> 总时长（回调需要素材总时长做边界约束）
        reused_tracker: 可选的 ``{asset_id: 累计复用时长}``，回调成功返回复用区间时
-            会把本次片段时长累加进去，供调用方统计成片复用占比（10% 阈值）。
+            会把本次片段时长累加进去，供调用方统计成片复用占比（15% 阈值）。
        assigned_tracker: 可选的 ``{asset_id: 已分配片段总时长}``，配合 ratio_limit
            在复用前预判：若复用本片段后占比 (reused + clip_duration) /
            (assigned + clip_duration) 超过 ratio_limit，则拒绝复用、返回 None
            （保证成片复用占比不超阈值）。
-        ratio_limit: 单条成片复用时长占比上限，默认 10%。
+        ratio_limit: 单条成片复用时长占比上限，默认 15%。

    Returns:
        回调函数 ``(asset_id, clip_duration) -> (start, end) | None``。
@@ -32,7 +32,6 @@ from packages.domain.plan_generator_utils import (
    generate_default_clips,
    map_clip_types_for_mode,
 )
-from packages.domain.smart_match import score_asset
 from packages.domain.template_clip_config import TemplateClipConfig

 logger = logging.getLogger(__name__)
@@ -219,13 +218,8 @@ class PlanGeneratorService:
    ) -> None:
        """按 editing_mode 将素材分配到 clips（就地修改，未持久化）.

-        先用 smart_match 评分对素材排序（高分优先），再委托给
-        plan_generator_utils.distribute_assets 纯函数完成分配。
+        委托给 plan_generator_utils.distribute_assets 纯函数。
        """
-        # 用 smart_match 评分排序素材：高分（质量好/时长合适/新鲜/未使用）优先
-        if self._asset_repo and not random_selection:
-            asset_ids = self._sort_assets_by_smart_score(asset_ids)
-
        distribute_assets(
            clips,
            asset_ids,
@@ -234,23 +228,6 @@ class PlanGeneratorService:
            asset_durations=asset_durations,
        )

-    def _sort_assets_by_smart_score(self, asset_ids: List[str]) -> List[str]:
-        """按 smart_match 综合评分降序排列素材 ID。
-
-        评分高的素材（质量好、时长合适、新鲜、使用次数少）排在前面。
-        """
-        scored: list[tuple[str, float]] = []
-        for asset_id in asset_ids:
-            asset = self._asset_repo.get(asset_id)
-            if asset:
-                score, _ = score_asset(asset)
-                scored.append((asset_id, score))
-            else:
-                scored.append((asset_id, 0.0))
-        # 按评分降序排列
-        scored.sort(key=lambda x: x[1], reverse=True)
-        return [aid for aid, _ in scored]
-
    def _fetch_asset_durations(self, asset_ids: List[str]) -> dict[str, float]:
        """从数据库获取素材时长信息.

@@ -1848,9 +1848,10 @@
    },
    "node_modules/@testing-library/dom": {
      "version": "10.4.1",
-      "resolved": "https://registry.npmjs.org/@testing-library/dom/-/dom-10.4.1.tgz",
+      "resolved": "https://registry.npmmirror.com/@testing-library/dom/-/dom-10.4.1.tgz",
      "integrity": "sha512-o4PXJQidqJl82ckFaXUeoAW+XysPLauYI43Abki5hABd853iMhitooc6znOnczgbTYmEP6U6/y1ZyKAIsvMKGg==",
      "dev": true,
+      "license": "MIT",
      "peer": true,
      "dependencies": {
        "@babel/code-frame": "^7.10.4",
@@ -1937,9 +1938,10 @@
    },
    "node_modules/@types/aria-query": {
      "version": "5.0.4",
-      "resolved": "https://registry.npmjs.org/@types/aria-query/-/aria-query-5.0.4.tgz",
+      "resolved": "https://registry.npmmirror.com/@types/aria-query/-/aria-query-5.0.4.tgz",
      "integrity": "sha512-rfT93uj5s0PRL7EzccGMs3brplhcrghnDoV26NqKhCAS1hVo+WdNsPvE/yb6ilfr5hi2MEk6d5EWJTKdxg8jVw==",
      "dev": true,
+      "license": "MIT",
      "peer": true
    },
    "node_modules/@types/babel__core": {
@@ -3111,9 +3113,10 @@
    },
    "node_modules/dom-accessibility-api": {
      "version": "0.5.16",
-      "resolved": "https://registry.npmjs.org/dom-accessibility-api/-/dom-accessibility-api-0.5.16.tgz",
+      "resolved": "https://registry.npmmirror.com/dom-accessibility-api/-/dom-accessibility-api-0.5.16.tgz",
      "integrity": "sha512-X7BJ2yElsnOJ30pZF4uIIDfBEVgF4XEBxL9Bxhy6dnrm5hkzqmsWHGTiHqRiITNhMyFLyAiWndIJP7Z1NTteDg==",
      "dev": true,
+      "license": "MIT",
      "peer": true
    },
    "node_modules/dunder-proto": {
@@ -4454,9 +4457,10 @@
    },
    "node_modules/lz-string": {
      "version": "1.5.0",
-      "resolved": "https://registry.npmjs.org/lz-string/-/lz-string-1.5.0.tgz",
+      "resolved": "https://registry.npmmirror.com/lz-string/-/lz-string-1.5.0.tgz",
      "integrity": "sha512-h5bgJWpxJNswbU7qCrV0tIKQCaS3blPDrqKWx+QxzuzL1zGUzij9XCWLrSLsJPu5t+eWA/ycetzYAO5IOMcWAQ==",
      "dev": true,
+      "license": "MIT",
      "peer": true,
      "bin": {
        "lz-string": "bin/bin.js"
@@ -5004,9 +5008,10 @@
    },
    "node_modules/pretty-format": {
      "version": "27.5.1",
-      "resolved": "https://registry.npmjs.org/pretty-format/-/pretty-format-27.5.1.tgz",
+      "resolved": "https://registry.npmmirror.com/pretty-format/-/pretty-format-27.5.1.tgz",
      "integrity": "sha512-Qb1gy5OrP5+zDf2Bvnzdl3jsTf1qXVMazbvCoKhtKqVs4/YK4ozX4gKQJJVyNe+cajNPn0KoC0MC3FUmaHWEmQ==",
      "dev": true,
+      "license": "MIT",
      "peer": true,
      "dependencies": {
        "ansi-regex": "^5.0.1",
@@ -5019,9 +5024,10 @@
    },
    "node_modules/pretty-format/node_modules/ansi-styles": {
      "version": "5.2.0",
-      "resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-5.2.0.tgz",
+      "resolved": "https://registry.npmmirror.com/ansi-styles/-/ansi-styles-5.2.0.tgz",
      "integrity": "sha512-Cxwpt2SfTzTtXcfOlzGEee8O+c+MmUgGrNiBcXnuWxuFJHe6a5Hz7qwhwe5OgaSYI0IJvkLqWX1ASG+cJOkEiA==",
      "dev": true,
+      "license": "MIT",
      "peer": true,
      "engines": {
        "node": ">=10"
@@ -5729,9 +5735,10 @@
    },
    "node_modules/react-is": {
      "version": "17.0.2",
-      "resolved": "https://registry.npmjs.org/react-is/-/react-is-17.0.2.tgz",
+      "resolved": "https://registry.npmmirror.com/react-is/-/react-is-17.0.2.tgz",
      "integrity": "sha512-w2GsyukL62IJnlaff/nRegPQR94C/XXamvMWmSHRJ4y7Ts/4ocGRmTHvOs8PSE6pB3dWOrD/nueuU5sduBsQ4w==",
      "dev": true,
+      "license": "MIT",
      "peer": true
    },
    "node_modules/react-refresh": {
@@ -71,5 +71,4 @@ export interface VideoItem {
  generation_params: Record<string, unknown>
  download_url: string
  generated_at: string
-  duplicate_rate?: number
 }
@@ -29,6 +29,7 @@ export function mapVideoToProductItem(video: VideoItem): ProductItem {
    // 后端字段名为 generated_at，映射为 created_at 供前端统一使用
    created_at: video.generated_at,
    updated_at: video.generated_at,
-    duplicate_rate: video.duplicate_rate,
+    // 后端 /videos 接口暂无 duplicate_rate 字段
+    duplicate_rate: undefined,
  }
 }
@@ -141,7 +141,6 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({

  // ── 拖拽状态（用 ref 避免在每帧渲染中触发重渲染）──
  const draggingTitleRef = useRef(false)
-  const titleDragRef = useRef<HTMLDivElement>(null)
  const handleTitlePointerDown = useCallback(
    (e: React.PointerEvent<HTMLDivElement>) => {
      if (!onTitlePositionChange || !playerContainerRef.current) return
@@ -153,45 +152,32 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
    },
    [onTitlePositionChange],
  )
-  const handleTitlePointerMove = useCallback((e: React.PointerEvent<HTMLDivElement>) => {
-    if (!draggingTitleRef.current || !playerContainerRef.current) return
-    e.preventDefault()
-    e.stopPropagation()
-    // 拖拽过程中直接修改 DOM，不触发 React 渲染（避免频繁重渲染导致换行）
-    if (titleDragRef.current) {
+  const handleTitlePointerMove = useCallback(
+    (e: React.PointerEvent<HTMLDivElement>) => {
+      if (!draggingTitleRef.current || !onTitlePositionChange || !playerContainerRef.current) return
+      e.preventDefault()
+      e.stopPropagation()
      const rect = playerContainerRef.current.getBoundingClientRect()
      const relX = Math.max(0, Math.min(rect.width, e.clientX - rect.left))
      const relY = Math.max(0, Math.min(rect.height, e.clientY - rect.top))
-      const xpct = (relX / rect.width) * 100
-      const ypct = (relY / rect.height) * 100
-      titleDragRef.current.style.left = `${xpct}%`
-      titleDragRef.current.style.top = `${ypct}%`
-    }
-  }, [])
-  const handleTitlePointerUp = useCallback(
-    (e: React.PointerEvent<HTMLDivElement>) => {
-      if (!draggingTitleRef.current) return
-      draggingTitleRef.current = false
-      // 拖拽结束时才调用 onTitlePositionChange 保存最终位置
-      if (onTitlePositionChange && playerContainerRef.current) {
-        const rect = playerContainerRef.current.getBoundingClientRect()
-        const relX = Math.max(0, Math.min(rect.width, e.clientX - rect.left))
-        const relY = Math.max(0, Math.min(rect.height, e.clientY - rect.top))
-        const posX = Math.round((relX / rect.width) * playRes.width)
-        const posY = Math.round((relY / rect.height) * playRes.height)
-        onTitlePositionChange(posX, posY)
-      }
-      ;(e.currentTarget as HTMLDivElement).style.cursor = "grab"
-      try {
-        if ((e.currentTarget as Element).hasPointerCapture(e.pointerId)) {
-          ;(e.currentTarget as Element).releasePointerCapture(e.pointerId)
-        }
-      } catch {
-        /* ignore */
-      }
+      const posX = Math.round((relX / rect.width) * playRes.width)
+      const posY = Math.round((relY / rect.height) * playRes.height)
+      onTitlePositionChange(posX, posY)
    },
    [onTitlePositionChange, playRes.width, playRes.height],
  )
+  const handleTitlePointerUp = useCallback((e: React.PointerEvent<HTMLDivElement>) => {
+    if (!draggingTitleRef.current) return
+    draggingTitleRef.current = false
+    ;(e.currentTarget as HTMLDivElement).style.cursor = "grab"
+    try {
+      if ((e.currentTarget as Element).hasPointerCapture(e.pointerId)) {
+        ;(e.currentTarget as Element).releasePointerCapture(e.pointerId)
+      }
+    } catch {
+      /* ignore */
+    }
+  }, [])

  const playerContainerRef = useRef<HTMLDivElement>(null)
  const [containerHeight, setContainerHeight] = useState(0)
@@ -608,7 +594,6 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
                        ? { top: "50%", transform: "translateY(-50%)" }
                        : { bottom: `${titleBottomPct}%` }),
                  }),
-              pointerEvents: "auto",
              cursor: onTitlePositionChange ? "grab" : "default",
              touchAction: "none",
              userSelect: "none",
@@ -616,7 +601,6 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
              padding: "8px 12px",
              boxShadow: "inset 0 0 0 16px transparent",
            }}
-            ref={titleDragRef}
            onPointerDown={handleTitlePointerDown}
            onPointerMove={handleTitlePointerMove}
            onPointerUp={handleTitlePointerUp}
@@ -1,7 +1,5 @@
 /**
 * 标题预设样式网格
- * 双图层渲染：底层=描边轮廓(text-shadow模拟)，上层=填充色
- * 避免 -webkit-text-stroke 在 Chromium 中吞掉填充色的问题
 */
 import React from "react"
 import { getFontFamily } from "../../constants"
@@ -9,10 +7,7 @@ import { getFontFamily } from "../../constants"
 interface TitlePresetItem {
  key: string
  label: string
-  previewStyle: React.CSSProperties & {
-    _strokeColor?: string
-    _strokeWidth?: number
-  }
+  previewStyle: React.CSSProperties
 }

 interface TitlePresetsGridProps {
@@ -22,32 +17,6 @@ interface TitlePresetsGridProps {
  fontFamily?: string
 }

-/**
- * 用 text-shadow 模拟描边轮廓（8方向 + 4对角 = 12层阴影）
- */
-function buildStrokeShadow(color: string, width: number): string {
-  const w = width
-  const parts: string[] = []
-  // 4 cardinal directions
-  parts.push(`${w}px 0 ${color}`)
-  parts.push(`${-w}px 0 ${color}`)
-  parts.push(`0 ${w}px ${color}`)
-  parts.push(`0 ${-w}px ${color}`)
-  // 4 diagonal directions
-  const d = Math.round(w * 0.71 * 10) / 10 // 0.71 ≈ sqrt(2)/2
-  parts.push(`${d}px ${d}px ${color}`)
-  parts.push(`${-d}px ${d}px ${color}`)
-  parts.push(`${d}px ${-d}px ${color}`)
-  parts.push(`${-d}px ${-d}px ${color}`)
-  // 4 extra mid-points for smoother stroke
-  const h = Math.round(w * 0.5 * 10) / 10
-  parts.push(`${w}px ${h}px ${color}`)
-  parts.push(`${w}px ${-h}px ${color}`)
-  parts.push(`${-w}px ${h}px ${color}`)
-  parts.push(`${-w}px ${-h}px ${color}`)
-  return parts.join(", ")
-}
-
 const TitlePresetsGrid: React.FC<TitlePresetsGridProps> = ({
  presets,
  activePreset,
@@ -58,52 +27,18 @@ const TitlePresetsGrid: React.FC<TitlePresetsGridProps> = ({
    <div className="xx-title-presets-grid">
      {presets.map((p) => {
        const isActive = activePreset === p.key
-        const { _strokeColor, _strokeWidth, ...fillStyle } = p.previewStyle
-        const ff = getFontFamily(fontFamily || "思源黑体")
-
-        // 底层：描边轮廓（用 text-shadow 模拟粗描边）
-        const strokeStyle: React.CSSProperties = {
-          color: _strokeColor || "transparent",
-          textShadow:
-            _strokeColor && _strokeWidth
-              ? buildStrokeShadow(_strokeColor, _strokeWidth)
-              : undefined,
-          fontWeight: fillStyle.fontWeight,
-          fontSize: fillStyle.fontSize,
-          lineHeight: 1,
-        }
-
-        // 上层：仅填充色 + 可选 textShadow（发光/投影效果）
-        const topStyle: React.CSSProperties = {
-          color: fillStyle.color,
-          textShadow: fillStyle.textShadow,
-          fontWeight: fillStyle.fontWeight,
-          fontSize: fillStyle.fontSize,
-          lineHeight: 1,
-        }
-
        return (
          <button
            key={p.key}
            className={`xx-title-preset-card${isActive ? " active" : ""}`}
            onClick={() => onApply(p.key)}
+            title={p.label}
          >
-            <span className="xx-title-preset-preview-text" style={{ position: "relative" }}>
-              {/* 底层：描边轮廓 */}
-              <span
-                aria-hidden
-                style={{
-                  ...strokeStyle,
-                  fontFamily: ff,
-                  position: "absolute",
-                  top: 0,
-                  left: 0,
-                }}
-              >
-                T
-              </span>
-              {/* 上层：填充色 */}
-              <span style={{ ...topStyle, fontFamily: ff, position: "relative" }}>T</span>
+            <span
+              className="xx-title-preset-preview-text"
+              style={{ ...p.previewStyle, fontFamily: getFontFamily(fontFamily || "思源黑体") }}
+            >
+              T
            </span>
          </button>
        )
@@ -78,11 +78,10 @@ export const TITLE_PRESETS = [
    label: "经典白字",
    style: { size: 28, color: "#ffffff", bold: true, italic: false, stroke: true, shadow: false },
    previewStyle: {
-      color: "#ffffff",
-      _strokeColor: "#000000",
-      _strokeWidth: 2,
      fontWeight: 700,
-      fontSize: "32px",
+      color: "#ffffff",
+      WebkitTextStroke: "1px #000000",
+      fontSize: "20px",
    },
  },
  {
@@ -90,54 +89,45 @@ export const TITLE_PRESETS = [
    label: "黑金质感",
    style: { size: 32, color: "#d4a843", bold: true, italic: false, stroke: false, shadow: true },
    previewStyle: {
-      color: "#d4a843",
      fontWeight: 700,
-      fontSize: "32px",
+      color: "#d4a843",
      textShadow: "1px 1px 3px rgba(0,0,0,0.8)",
+      fontSize: "20px",
    },
  },
  {
    key: "fresh_minimal",
    label: "清新简约",
    style: { size: 24, color: "#333333", bold: false, italic: false, stroke: false, shadow: false },
-    previewStyle: {
-      color: "#e8e8e8",
-      fontWeight: 400,
-      fontSize: "32px",
-    },
+    previewStyle: { fontWeight: 400, color: "#333333", fontSize: "18px" },
  },
  {
    key: "variety_show",
    label: "综艺花字",
    style: { size: 36, color: "#ff4081", bold: true, italic: false, stroke: true, shadow: true },
    previewStyle: {
-      color: "#ff4081",
-      _strokeColor: "#ffffff",
-      _strokeWidth: 2,
      fontWeight: 900,
-      fontSize: "32px",
+      color: "#ff4081",
+      WebkitTextStroke: "1.5px #ffffff",
      textShadow: "2px 2px 4px rgba(0,0,0,0.5)",
+      fontSize: "22px",
    },
  },
  {
    key: "business",
    label: "商务极简",
    style: { size: 24, color: "#1a1a1a", bold: false, italic: false, stroke: false, shadow: false },
-    previewStyle: {
-      color: "#e0e0e0",
-      fontWeight: 400,
-      fontSize: "32px",
-    },
+    previewStyle: { fontWeight: 400, color: "#1a1a1a", fontSize: "17px" },
  },
  {
    key: "retro_film",
    label: "复古胶片",
    style: { size: 28, color: "#e8d5b7", bold: false, italic: false, stroke: false, shadow: true },
    previewStyle: {
-      color: "#e8d5b7",
      fontWeight: 400,
-      fontSize: "32px",
+      color: "#e8d5b7",
      textShadow: "2px 2px 6px rgba(0,0,0,0.7)",
+      fontSize: "18px",
    },
  },
  {
@@ -145,10 +135,10 @@ export const TITLE_PRESETS = [
    label: "霓虹发光",
    style: { size: 32, color: "#00e5ff", bold: true, italic: false, stroke: false, shadow: true },
    previewStyle: {
-      color: "#00e5ff",
      fontWeight: 700,
-      fontSize: "32px",
+      color: "#00e5ff",
      textShadow: "0 0 4px #00e5ff, 0 0 8px #00e5ff, 0 0 16px rgba(0,229,255,0.5)",
+      fontSize: "20px",
    },
  },
  {
@@ -156,202 +146,10 @@ export const TITLE_PRESETS = [
    label: "手写字",
    style: { size: 28, color: "#333333", bold: false, italic: false, stroke: false, shadow: true },
    previewStyle: {
-      color: "#e0e0e0",
      fontWeight: 400,
-      fontSize: "32px",
+      color: "#333333",
      textShadow: "1px 1px 2px rgba(0,0,0,0.3)",
-    },
-  },
-  {
-    key: "outline_yellow",
-    label: "黄色描边",
-    style: { size: 28, color: "#ffd54f", bold: true, italic: false, stroke: true, shadow: false },
-    previewStyle: {
-      color: "#ffd54f",
-      _strokeColor: "#000000",
-      _strokeWidth: 2,
-      fontWeight: 700,
-      fontSize: "32px",
-    },
-  },
-  {
-    key: "outline_pink",
-    label: "粉色描边",
-    style: { size: 28, color: "#ff80ab", bold: true, italic: false, stroke: true, shadow: false },
-    previewStyle: {
-      color: "#ff80ab",
-      _strokeColor: "#000000",
-      _strokeWidth: 2,
-      fontWeight: 700,
-      fontSize: "32px",
-    },
-  },
-  {
-    key: "outline_blue",
-    label: "蓝色描边",
-    style: { size: 28, color: "#82b1ff", bold: true, italic: false, stroke: true, shadow: false },
-    previewStyle: {
-      color: "#82b1ff",
-      _strokeColor: "#000000",
-      _strokeWidth: 2,
-      fontWeight: 700,
-      fontSize: "32px",
-    },
-  },
-  {
-    key: "outline_green",
-    label: "绿色描边",
-    style: { size: 28, color: "#69f0ae", bold: true, italic: false, stroke: true, shadow: false },
-    previewStyle: {
-      color: "#69f0ae",
-      _strokeColor: "#000000",
-      _strokeWidth: 2,
-      fontWeight: 700,
-      fontSize: "32px",
-    },
-  },
-  {
-    key: "outline_gray",
-    label: "灰色描边",
-    style: { size: 28, color: "#bdbdbd", bold: true, italic: false, stroke: true, shadow: false },
-    previewStyle: {
-      color: "#bdbdbd",
-      _strokeColor: "#000000",
-      _strokeWidth: 2,
-      fontWeight: 700,
-      fontSize: "32px",
-    },
-  },
-  {
-    key: "bg_white",
-    label: "白底黑字",
-    style: { size: 28, color: "#1a1a1a", bold: true, italic: false, stroke: false, shadow: false },
-    previewStyle: {
-      color: "#1a1a1a",
-      fontWeight: 700,
-      fontSize: "32px",
-      background: "#ffffff",
-      borderRadius: "4px",
-      padding: "2px 6px",
-    },
-  },
-  {
-    key: "bg_yellow",
-    label: "黄底黑字",
-    style: { size: 28, color: "#1a1a1a", bold: true, italic: false, stroke: false, shadow: false },
-    previewStyle: {
-      color: "#1a1a1a",
-      fontWeight: 700,
-      fontSize: "32px",
-      background: "#ffd54f",
-      borderRadius: "4px",
-      padding: "2px 6px",
-    },
-  },
-  {
-    key: "bg_pink",
-    label: "粉底黑字",
-    style: { size: 28, color: "#1a1a1a", bold: true, italic: false, stroke: false, shadow: false },
-    previewStyle: {
-      color: "#1a1a1a",
-      fontWeight: 700,
-      fontSize: "32px",
-      background: "#ff80ab",
-      borderRadius: "4px",
-      padding: "2px 6px",
-    },
-  },
-  {
-    key: "bg_red",
-    label: "红底白字",
-    style: { size: 28, color: "#ffffff", bold: true, italic: false, stroke: false, shadow: false },
-    previewStyle: {
-      color: "#ffffff",
-      fontWeight: 700,
-      fontSize: "32px",
-      background: "#ef5350",
-      borderRadius: "4px",
-      padding: "2px 6px",
-    },
-  },
-  {
-    key: "neon_orange",
-    label: "橙色发光",
-    style: { size: 32, color: "#ff9100", bold: true, italic: false, stroke: false, shadow: true },
-    previewStyle: {
-      color: "#ff9100",
-      fontWeight: 700,
-      fontSize: "32px",
-      textShadow: "0 0 4px #ff9100, 0 0 8px #ff9100, 0 0 16px rgba(255,145,0,0.5)",
-    },
-  },
-  {
-    key: "neon_purple",
-    label: "紫色发光",
-    style: { size: 32, color: "#d500f9", bold: true, italic: false, stroke: false, shadow: true },
-    previewStyle: {
-      color: "#d500f9",
-      fontWeight: 700,
-      fontSize: "32px",
-      textShadow: "0 0 4px #d500f9, 0 0 8px #d500f9, 0 0 16px rgba(213,0,249,0.5)",
-    },
-  },
-  {
-    key: "bordered_white",
-    label: "白字绿框",
-    style: { size: 28, color: "#ffffff", bold: true, italic: false, stroke: false, shadow: false },
-    previewStyle: {
-      color: "#ffffff",
-      fontWeight: 700,
-      fontSize: "32px",
-      background: "#1a1a1a",
-      border: "2px solid #69f0ae",
-      borderRadius: "4px",
-      padding: "2px 6px",
-    },
-  },
-  {
-    key: "gradient_warm",
-    label: "暖色渐变",
-    style: { size: 32, color: "#ff6d00", bold: true, italic: false, stroke: false, shadow: true },
-    previewStyle: {
-      color: "#ff6d00",
-      fontWeight: 700,
-      fontSize: "32px",
-      textShadow: "0 0 6px rgba(255,109,0,0.6), 1px 1px 2px rgba(0,0,0,0.5)",
-    },
-  },
-  {
-    key: "gradient_cool",
-    label: "冷色渐变",
-    style: { size: 32, color: "#00b0ff", bold: true, italic: false, stroke: false, shadow: true },
-    previewStyle: {
-      color: "#00b0ff",
-      fontWeight: 700,
-      fontSize: "32px",
-      textShadow: "0 0 6px rgba(0,176,255,0.6), 1px 1px 2px rgba(0,0,0,0.5)",
-    },
-  },
-  {
-    key: "shadow_deep",
-    label: "深影白字",
-    style: { size: 28, color: "#ffffff", bold: true, italic: false, stroke: false, shadow: true },
-    previewStyle: {
-      color: "#ffffff",
-      fontWeight: 700,
-      fontSize: "32px",
-      textShadow: "2px 2px 4px rgba(0,0,0,0.8), 0 0 8px rgba(0,0,0,0.4)",
-    },
-  },
-  {
-    key: "soft_gold",
-    label: "柔光金",
-    style: { size: 28, color: "#ffd54f", bold: true, italic: false, stroke: false, shadow: true },
-    previewStyle: {
-      color: "#ffd54f",
-      fontWeight: 700,
-      fontSize: "32px",
-      textShadow: "0 0 6px rgba(255,213,79,0.5), 1px 1px 2px rgba(0,0,0,0.4)",
+      fontSize: "20px",
    },
  },
 ]
@@ -1733,36 +1733,36 @@
 /* 标题预设卡片网格 */
 .xx-title-presets-grid {
  display: grid;
-  grid-template-columns: repeat(6, 52px);
-  gap: 1px;
+  grid-template-columns: repeat(6, 1fr);
+  gap: 8px;
 }

 .xx-title-preset-card {
  display: flex;
+  flex-direction: column;
  align-items: center;
  justify-content: center;
-  width: 52px;
-  height: 52px;
-  padding: 0;
-  background: #404040;
+  aspect-ratio: 1 / 1;
+  padding: 4px;
+  background: var(--bg-secondary);
  border: 2px solid transparent;
-  border-radius: 8px;
+  border-radius: var(--radius-sm);
  cursor: pointer;
  transition: all 0.15s;
+  text-align: center;
 }

 .xx-title-preset-card:hover {
-  border-color: #666;
-  background: #4d4d4d;
+  border-color: var(--primary-200);
+  background: var(--bg-primary);
 }

 .xx-title-preset-card.active {
-  border-color: #409eff;
-  background: #4d4d4d;
+  border-color: var(--primary-color);
+  background: var(--primary-50);
 }

 .xx-title-preset-preview-text {
-  font-size: 32px;
  line-height: 1;
  user-select: none;
 }
@@ -221,7 +221,7 @@ export const ProductCard: React.FC<ProductCardProps> = ({
              product.duplicateRate > 0 ? ` ${dupClass}` : ""
            }`}
          >
-            查重率：{product.duplicateRate != null ? `${product.duplicateRate.toFixed(1)}%` : "-"}
+            查重率：{product.duplicateRate > 0 ? `${product.duplicateRate.toFixed(1)}%` : "-"}
          </span>
        </div>
      </div>
@@ -91,6 +91,8 @@
  height: 18px;
  border: 2px solid var(--border-color);
  border-radius: var(--radius-xs);
+  display: grid;
+  place-items: center;
  transition: var(--transition-all);
  background: var(--bg-primary);
  flex-shrink: 0;
@@ -135,7 +137,7 @@
   ============================================================ */
 .xx-products-grid {
  display: grid;
-  grid-template-columns: repeat(auto-fill, minmax(220px, 1fr));
+  grid-template-columns: repeat(4, 1fr);
  gap: var(--space-md);
 }

@@ -185,6 +187,8 @@
  height: 22px;
  border: 2px solid rgba(255, 255, 255, 0.8);
  border-radius: var(--radius-xs);
+  display: grid;
+  place-items: center;
  background: rgba(0, 0, 0, 0.3);
  backdrop-filter: blur(4px);
  cursor: pointer;
@@ -258,8 +262,11 @@
 .xx-product-thumb {
  position: relative;
  overflow: hidden;
+  display: grid;
+  place-items: center;
  color: var(--text-inverse);
  background: var(--color-gray-950);
+  max-height: 320px;
 }

 .xx-product-thumb-bg {
@@ -282,28 +289,22 @@
 }

 .xx-product-play {
-  position: absolute;
-  top: 50%;
-  left: 50%;
-  transform: translate(-50%, -50%);
-  z-index: 2;
-  width: 52px;
-  height: 52px;
-  border-radius: 50%;
+  position: relative;
+  z-index: 1;
+  width: 44px;
+  height: 44px;
+  border-radius: var(--radius-full);
  background: rgba(0, 0, 0, 0.45);
  backdrop-filter: blur(4px);
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  font-size: 28px;
-  color: #fff;
-  transition: all 0.2s;
-  cursor: pointer;
+  display: grid;
+  place-items: center;
+  font-size: var(--font-size-md);
+  transition: var(--transition-all);
 }

 .xx-product-card:hover .xx-product-play {
  background: var(--primary-color);
-  transform: translate(-50%, -50%) scale(1.1);
+  transform: scale(1.1);
 }

 /* 时长标签 */
@@ -323,7 +324,7 @@

 /* 卡片信息区 */
 .xx-product-info {
-  padding: 8px 10px;
+  padding: 14px;
  display: flex;
  flex-direction: column;
  gap: var(--space-sm);
@@ -505,6 +506,8 @@
  z-index: 1000;
  background: rgba(0, 0, 0, 0.75);
  backdrop-filter: blur(8px);
+  display: grid;
+  place-items: center;
  animation: player-fade-in 0.25s ease-out;
 }

@@ -543,6 +546,8 @@
  background: var(--color-gray-950);
  aspect-ratio: 9 / 16;
  max-height: 60vh;
+  display: grid;
+  place-items: center;
 }

 .xx-player-video-wrap video {
@@ -564,6 +569,8 @@
  backdrop-filter: blur(4px);
  color: var(--text-inverse);
  font-size: 28px;
+  display: grid;
+  place-items: center;
  cursor: pointer;
  border: none;
  transition: var(--transition-all);
@@ -660,6 +667,8 @@
  backdrop-filter: blur(4px);
  color: var(--text-inverse);
  font-size: var(--font-size-md);
+  display: grid;
+  place-items: center;
  cursor: pointer;
  border: none;
  transition: var(--transition-all);
@@ -314,13 +314,10 @@ class VideoDeduplicator:
        project_id: str,
        current_video_id: str | None,
        session: Session,
-        *,
-        user_id: str = "",
    ) -> float:
-        """计算当前视频与用户库内已有视频的最高相似度百分比。
+        """计算当前视频与项目内已有视频的最高相似度百分比。

-        优先按 user_id 全局比较（跨项目），user_id 为空时回退到项目级比较。
-        遍历最近 200 个其他有指纹的视频，对每个计算相似度：
+        遍历项目内所有其他有指纹的视频，对每个计算相似度：
        - MD5 精确匹配 → 100%
        - pHash 相似度 → (1.0 - avg_distance / 64) * 100
        取最高值作为 duplicate_rate（0~100）。
@@ -328,34 +325,23 @@ class VideoDeduplicator:

        Args:
            fingerprint: 当前视频的指纹
-            project_id: 项目 ID（user_id 为空时的回退范围）
+            project_id: 项目 ID
            current_video_id: 当前视频 ID（排除自身，可为 None）
            session: 数据库会话
-            user_id: 用户 ID（优先按用户全局比较）

        Returns:
            duplicate_rate: 0~100 的浮点数
        """
-        # 限制查询最近 200 个视频，避免大库内存溢出
+        # 限制查询最近 100 个视频，避免大项目内存溢出
        from packages.adapters.sqlalchemy_impl.models import GeneratedVideoModel

-        # 优先按 user_id 全局比较（跨项目），否则回退到项目级
-        if user_id:
-            query = session.query(GeneratedVideoModel).filter(
-                GeneratedVideoModel.user_id == user_id,
-            )
-            logger.debug("compute_duplicate_rate: user-level scope user_id=%s", user_id)
-        else:
-            query = session.query(GeneratedVideoModel).filter(
-                GeneratedVideoModel.project_id == project_id,
-            )
-            logger.debug("compute_duplicate_rate: project-level fallback project_id=%s", project_id)
-
-        # 排除当前视频自身（记录可能已写入 DB，必须在查询层排除）
-        if current_video_id:
-            query = query.filter(GeneratedVideoModel.id != current_video_id)
-
-        recent_models = query.order_by(GeneratedVideoModel.generated_at.desc()).limit(200).all()
+        recent_models = (
+            session.query(GeneratedVideoModel)
+            .filter(GeneratedVideoModel.project_id == project_id)
+            .order_by(GeneratedVideoModel.generated_at.desc())
+            .limit(100)
+            .all()
+        )
        video_repo = SQLAlchemyGeneratedVideoRepository(session)
        existing_videos = [video_repo._to_domain(m) for m in recent_models]

@@ -123,13 +123,7 @@ def create_video_record_and_dedup(

        # 计算重复率百分比（与项目内所有已有视频对比取最高相似度）
        try:
-            dup_rate = deduplicator.compute_duplicate_rate(
-                fingerprint,
-                project_id,
-                video_id,
-                session,
-                user_id=user_id,
-            )
+            dup_rate = deduplicator.compute_duplicate_rate(fingerprint, project_id, video_id, session)
            generated_video.duplicate_rate = dup_rate
            logger.info("Duplicate rate for %s: %.2f%%", video_id, dup_rate)
        except Exception as rate_err:
@@ -200,22 +200,6 @@ class UnifiedRenderService:

        # 3. 计算视频总时长（用于字幕显示时长）
        video_duration = self._estimate_total_duration(layers)
-        # Debug: 输出各图层时长明细
-        for layer in layers:
-            layer_total = sum(UnifiedRenderService._clip_adjusted_duration(c) for c in layer.clips)
-            clip_details = [
-                f"{c.clip_id}(dur={c.duration:.3f},actual={c.actual_duration:.3f},speed={getattr(c, 'playback_speed', 1.0):.4f})"
-                for c in layer.clips
-            ]
-            logger.info(
-                "[debug] layer=%s clips=%d total=%.3f transition_duration=%.3f details=%s",
-                layer.role,
-                len(layer.clips),
-                layer_total,
-                self.transition_duration,
-                ", ".join(clip_details),
-            )
-        logger.info("[debug] estimated video_duration=%.3f", video_duration)

        # 3.5 TTS 配音生成（如果配置了）
        self._maybe_add_voiceover_layer(layers, video_duration=video_duration)
@@ -1438,7 +1422,6 @@ class UnifiedRenderService:
            if trim_segments and len(trim_segments) > 1:
                # 多段裁剪：展开为多个 clip
                resolved_segments = TrimEngine.resolve_segments(trim_segments, actual_duration)
-                configured_speed = getattr(clip, "playback_speed", 1.0) or 1.0
                for i, seg in enumerate(resolved_segments):
                    # 每个段生成一个独立的 ResolvedClip
                    seg_clip_id = f"{clip.id}_seg_{seg.segment_id}"
@@ -1446,19 +1429,6 @@ class UnifiedRenderService:
                    seg_start = seg.trim.start_time
                    seg_duration = seg.trim.duration

-                    # 多段裁剪：如果段的时长超过素材实际时长，减速补偿
-                    seg_speed = configured_speed
-                    if actual_duration > 0 and seg_duration > actual_duration + 0.05:
-                        seg_speed = max(0.25, round(configured_speed * actual_duration / seg_duration, 4))
-                        logger.info(
-                            "[debug] multi-seg clip=%s seg=%s duration=%.3f actual=%.3f → speed=%.4f",
-                            clip.id,
-                            seg.segment_id,
-                            seg_duration,
-                            actual_duration,
-                            seg_speed,
-                        )
-
                    rc = ResolvedClip(
                        clip_id=seg_clip_id,
                        asset_id=asset_id,
@@ -1469,7 +1439,7 @@ class UnifiedRenderService:
                        duration=seg_duration,
                        transition_effect=clip.transition_effect or "cut",
                        transition_duration=getattr(clip, "transition_duration", 0.0) or 0.0,
-                        playback_speed=seg_speed,
+                        playback_speed=getattr(clip, "playback_speed", 1.0) or 1.0,
                        config={**clip_config, "_segment_id": seg.segment_id},
                        actual_duration=actual_duration,
                        trim_config=seg.trim,
@@ -1491,7 +1461,6 @@ class UnifiedRenderService:
            effective_trim: TrimConfig | None = None
            final_start = clip.start_time
            final_duration = clip.duration
-            configured_speed = getattr(clip, "playback_speed", 1.0) or 1.0

            if trim_config is not None and actual_duration > 0:
                effective_trim = trim_config.validate_and_resolve(actual_duration)
@@ -1505,25 +1474,6 @@ class UnifiedRenderService:
                    final_start = 0.0
                    final_duration = actual_duration

-            # 素材实际时长不足以覆盖配置的时长时，降低播放速度来补偿
-            # 例如：配置4s但素材只有3s → speed=0.75x，用满3s素材达到4s输出
-            if actual_duration > 0 and final_duration > actual_duration + 0.05:
-                compensated_speed = actual_duration / final_duration
-                # 保留用户设置的速度（如果已减速则叠加）
-                final_speed = configured_speed * compensated_speed
-                # 下限 0.25x
-                final_speed = max(0.25, round(final_speed, 4))
-                logger.info(
-                    "[debug] clip=%s duration=%.3f actual=%.3f → 减速补偿 speed=%.4f (configured=%.3f)",
-                    clip.id,
-                    final_duration,
-                    actual_duration,
-                    final_speed,
-                    configured_speed,
-                )
-            else:
-                final_speed = configured_speed
-
            rc = ResolvedClip(
                clip_id=clip.id,
                asset_id=asset_id,
@@ -1534,25 +1484,13 @@ class UnifiedRenderService:
                duration=final_duration,
                transition_effect=clip.transition_effect or "cut",
                transition_duration=getattr(clip, "transition_duration", 0.0) or 0.0,
-                playback_speed=final_speed,
+                playback_speed=getattr(clip, "playback_speed", 1.0) or 1.0,
                config=clip_config,
                actual_duration=actual_duration,
                trim_config=effective_trim,
            )
            resolved.append(rc)

-            # Debug日志：记录每个clip的时长信息
-            eff_dur = _clip_effective_duration_pure(final_duration, actual_duration)
-            logger.info(
-                "[debug] resolved clip=%s duration=%.3f actual=%.3f effective=%.3f speed=%.4f start=%.3f",
-                clip.id,
-                final_duration,
-                actual_duration,
-                eff_dur,
-                final_speed,
-                final_start,
-            )
-
        # 按 order 排序
        resolved.sort(key=lambda c: c.order)
        return resolved
@@ -1745,7 +1683,7 @@ class UnifiedRenderService:
                        if d > 0:
                            layer_dur = d
                            break
-                    xfade_filter, xfade_estimated_dur = self._transition_engine.build_xfade_chain(
+                    xfade_filter, _ = self._transition_engine.build_xfade_chain(
                        clip_durations=layer_durations,
                        clip_video_labels=layer_labels,
                        transitions=layer_transitions,
@@ -1754,13 +1692,6 @@ class UnifiedRenderService:
                    )
                    if xfade_filter:
                        filter_parts.append(xfade_filter)
-                    logger.info(
-                        "[unified-render] layer=%s xfade: clips=%d durations=%s estimated_dur=%.3f",
-                        layer.role,
-                        len(layer_labels),
-                        [round(d, 3) for d in layer_durations],
-                        xfade_estimated_dur,
-                    )
                layer_output_labels[layer.role] = out_label

        # Step 3: 合成各层
@@ -1984,14 +1915,8 @@ class UnifiedRenderService:
    def _clip_effective_duration(clip: ResolvedClip) -> float:
        """计算 clip 的有效时长（原速 trim 后时长）。

-        如果 playback_speed < 1（为补偿素材不足而减速），返回配置的 duration，
-        而非 min(duration, actual_duration)。
        实际实现移至 packages.domain.render_layer_utils.clip_effective_duration。
        """
-        speed = getattr(clip, "playback_speed", 1.0) or 1.0
-        # 减速场景：duration 已通过降低 playback_speed 补偿，返回配置的 duration
-        if speed < 1.0 - 1e-6 and clip.duration > 0:
-            return clip.duration
        return _clip_effective_duration_pure(clip.duration, clip.actual_duration)

    # ── 画中画（PiP）相关方法 ──────────────────────────────────────────────────
@@ -150,11 +150,8 @@ def build_xfade_filter_chain(
        else:
            first_input_dur = cumulative - total_transition

-        # 正确的 offset 计算：offset 应相对于累积输出时长
-        # offset = 累积输出中，转场开始的时间点
-        # = first_input_dur - transition_duration
-        # 这样每个转场之间的"纯内容"时长等于原始 clip 时长
-        offset = max(0.0, first_input_dur - transition_duration)
+        # 原始 offset 计算
+        offset = max(0.0, cumulative - transition_duration * i)

        # 安全钳制：offset + td 不能超过第一个输入的时长
        available = max(0.0, first_input_dur - offset)
@@ -119,70 +119,6 @@ class MediaKitClient:

        return None

-    def detect_scene_changes(
-        self,
-        video_url: str,
-        max_frames: int = 20,
-        poll_interval: float = 2.0,
-        max_poll_attempts: int = 30,
-    ) -> Optional[List[float]]:
-        """检测视频场景切换点，返回时间戳列表.
-
-        降级策略：
-        1. 先尝试 SceneChange 策略
-        2. SceneChange 失败（OOM等）→ 退回 TimeInterval（5秒间隔）
-        3. MediaKit 不可用 → 返回 None
-
-        Returns:
-            场景切换点时间戳列表，如 [0.0, 3.2, 7.8, 12.5]
-            失败返回 None
-        """
-        if not self.is_available:
-            logger.warning("MediaKit 未配置，跳过场景检测")
-            return None
-
-        # 策略1：尝试 SceneChange
-        frames = self.extract_frames(
-            video_url=video_url,
-            strategy="SceneChange",
-            max_frames=max_frames,
-            poll_interval=poll_interval,
-            max_poll_attempts=max_poll_attempts,
-        )
-
-        # 策略2：SceneChange 失败 → 退回 TimeInterval（5秒间隔）
-        if frames is None:
-            logger.info("SceneChange 策略失败，降级为 TimeInterval（5秒间隔）")
-            # 估算帧数：假设视频最长60秒，每5秒一帧
-            ti_max_frames = max(max_frames, 12)
-            frames = self.extract_frames(
-                video_url=video_url,
-                strategy="TimeInterval",
-                max_frames=ti_max_frames,
-                poll_interval=poll_interval,
-                max_poll_attempts=max_poll_attempts,
-            )
-
-        if frames is None:
-            return None
-
-        # 从帧列表中提取 timestamp，排序
-        timestamps = sorted({float(f.get("timestamp", 0.0)) for f in frames if "timestamp" in f})
-
-        if not timestamps:
-            return None
-
-        # 始终在列表开头加 0.0（素材起始点）
-        if timestamps[0] != 0.0:
-            timestamps.insert(0, 0.0)
-
-        logger.info(
-            "场景检测完成: video_url=%s scene_changes=%s",
-            video_url[:80],
-            timestamps,
-        )
-        return timestamps
-
    def _submit_extract_task(
        self,
        video_url: str,
@@ -24,10 +24,8 @@ celery==5.4.0
 # 对象存储
 oss2==2.18.4

-# HTTP 客户端（pin 间接依赖防止版本漂移）
+# HTTP 客户端
 httpx==0.27.2
-httpcore==1.0.7
-h2==4.1.0

 # Prometheus monitoring
 prometheus-client==0.21.1
@@ -15,6 +15,5 @@ pytest-xdist==3.6.1
 diff-cover==8.0.3

 # 资产质量评分依赖（与 requirements-worker.txt 保持一致）
-numpy==1.26.4
 scipy==1.13.1
 Pillow==10.4.0
@@ -4,7 +4,6 @@
 # - docker-container driver, host 网络
 # - 层缓存保存在 buildkit 容器及其 _state 命名卷中，job 结束不清理
 # - 宿主机 ci-docker-cleanup.sh 已豁免该 builder
-# - 每次执行自动同步宿主机 docker config 到 BuildKit 容器（确保 registry 认证）
 # 用法: bash scripts/ci/ensure_persistent_builder.sh
 set -eu

@@ -35,26 +34,3 @@ docker buildx use "$BUILDER"
 docker buildx inspect "$BUILDER" --bootstrap
 echo "✅ builder ready"
 docker buildx ls | head -5
-
-# === 同步宿主机 docker config 到 BuildKit 容器（确保 registry 认证） ===
-# BuildKit 容器名遵循 docker buildx 命名规则: buildx_buildkit_<builder-name>_0
-BUILDKIT_CONTAINER="buildx_buildkit_${BUILDER}_0"
-
-if docker inspect "$BUILDKIT_CONTAINER" >/dev/null 2>&1; then
-  # 宿主机 docker config 路径
-  HOST_DOCKER_CONFIG="/root/.docker/config.json"
-  
-  if [ -f "$HOST_DOCKER_CONFIG" ]; then
-    echo "=== 同步 docker config 到 BuildKit 容器 ==="
-    # 确保容器内 .docker 目录存在
-    docker exec "$BUILDKIT_CONTAINER" mkdir -p /root/.docker
-    # 拷贝 config.json
-    docker cp "$HOST_DOCKER_CONFIG" "$BUILDKIT_CONTAINER:/root/.docker/config.json"
-    echo "✅ docker config 已同步到 BuildKit 容器"
-  else
-    echo "⚠️ 宿主机 docker config 不存在: $HOST_DOCKER_CONFIG（跳过同步）"
-  fi
-else
-  echo "⚠️ BuildKit 容器不存在: $BUILDKIT_CONTAINER（跳过 config 同步）"
-fi
-
@@ -1,136 +1,77 @@
 #!/bin/bash
 # CI Unit Tests Job 主脚本
-# 包含：依赖缓存、增量测试选择、覆盖率测试、diff覆盖率门禁
+# 包含：依赖安装、增量测试选择、覆盖率测试、diff覆盖率门禁
 set -eu

 JOB_NAME="${1:-Unit Tests}"

 echo "=== CI Unit Tests 开始 ==="

-# --- 依赖缓存检查 ---
-# 如果 requirements 文件未变化且依赖已安装，跳过 pip install（持久 runner 优化）
-REQ_HASH_FILE="/tmp/.ci_unit_tests_req_hash"
-CURRENT_REQ_HASH=""
-if [ -f requirements-base.txt ] && [ -f requirements.txt ] && [ -f requirements-dev.txt ]; then
-  CURRENT_REQ_HASH=$(cat requirements-base.txt requirements.txt requirements-dev.txt | md5sum | cut -d' ' -f1)
-fi
-
-SKIP_PIP_INSTALL=false
-if [ -n "$CURRENT_REQ_HASH" ] && [ -f "$REQ_HASH_FILE" ]; then
-  CACHED_HASH=$(cat "$REQ_HASH_FILE")
-  if [ "$CACHED_HASH" = "$CURRENT_REQ_HASH" ]; then
-    # 验证关键包是否还在
-    if python3 -c "import pytest; import celery" 2>/dev/null; then
-      echo "✅ 依赖无变化 (hash=$CURRENT_REQ_HASH)，跳过 pip install"
-      SKIP_PIP_INSTALL=true
-    else
-      echo "⚠️ 依赖 hash 匹配但关键包缺失，重新安装"
-    fi
-  fi
-fi
-
 # --- 安装依赖 ---
-if [ "$SKIP_PIP_INSTALL" = "false" ]; then
-  echo ""
-  echo "=== 安装 Python 依赖 ==="
-  # pip install 带重试（网络不稳定时自动重试），合并为一次调用减少开销
-  for i in 1 2 3; do
-    python3 -m pip install -q -r requirements-base.txt -r requirements.txt -r requirements-dev.txt && break
-    echo "pip install 失败，重试 $i/3..."
-    [ $i -eq 3 ] && exit 1
-    sleep 5
-  done
-  # 保存 hash 标记
-  if [ -n "$CURRENT_REQ_HASH" ]; then
-    echo "$CURRENT_REQ_HASH" > "$REQ_HASH_FILE"
-  fi
-fi
+echo ""
+echo "=== 安装 Python 依赖 ==="
+# pip install 带重试（网络不稳定时自动重试）
+for i in 1 2 3; do
+  python3 -m pip install -q -r requirements-base.txt && break
+  echo "pip install requirements-base.txt 失败，重试 $i/3..."
+  [ $i -eq 3 ] && exit 1
+  sleep 5
+done
+for i in 1 2 3; do
+  python3 -m pip install -q -r requirements.txt && break
+  echo "pip install requirements.txt 失败，重试 $i/3..."
+  [ $i -eq 3 ] && exit 1
+  sleep 5
+done
+for i in 1 2 3; do
+  python3 -m pip install -q -r requirements-dev.txt && break
+  echo "pip install requirements-dev.txt 失败，重试 $i/3..."
+  [ $i -eq 3 ] && exit 1
+  sleep 5
+done
 pytest --version

 # 双保险：确保numpy已安装
 echo "=== 验证 numpy 安装 ==="
 SKIP_NUMPY_TESTS=0
-if python3 -c "import numpy; assert numpy.__version__ == '1.26.4'" 2>/dev/null; then
-  echo "✅ numpy 1.26.4 已就绪（缓存命中）"
-else
-  echo "需要安装 numpy 1.26.4..."
-  python3 -m pip install numpy==1.26.4 || {
-    echo "❌ numpy 首次安装失败，尝试不使用缓存重新安装..."
-    python3 -m pip install --no-cache-dir numpy==1.26.4 || {
-      echo "⚠️ numpy 安装失败，跳过需要 numpy 的测试"
-      SKIP_NUMPY_TESTS=1
-    }
+python3 -m pip install numpy==1.26.4 || {
+  echo "❌ numpy 首次安装失败，尝试不使用缓存重新安装..."
+  python3 -m pip install --no-cache-dir numpy==1.26.4 || {
+    echo "⚠️ numpy 安装失败，跳过需要 numpy 的测试"
+    SKIP_NUMPY_TESTS=1
  }
-fi
+}
 if [ "$SKIP_NUMPY_TESTS" = "0" ]; then
-  python3 -c "import numpy; print(f'✅ numpy {numpy.__version__} 就绪')" || {
+  python3 -c "import numpy; print(f'✅ numpy {numpy.__version__} 安装成功')" || {
    echo "⚠️ numpy 导入失败，跳过需要 numpy 的测试"
    SKIP_NUMPY_TESTS=1
  }
 fi

-# --- 增量测试选择（PR + push 均支持） ---
+# --- 增量测试选择（仅PR） ---
 UNIT_TEST_MODE="full"
 SELECTED_TEST_FILES="tests/unit"

-IS_PULL_REQUEST=false
-IS_PUSH=false
-[ "${GITHUB_EVENT_NAME:-}" = "pull_request" ] && IS_PULL_REQUEST=true
-[ "${GITHUB_EVENT_NAME:-}" = "push" ] && IS_PUSH=true
-
-if ($IS_PULL_REQUEST || $IS_PUSH) && [ -n "${GITHUB_TOKEN:-}" ]; then
+if [ "${GITHUB_EVENT_NAME:-}" = "pull_request" ] && [ -n "${GITHUB_TOKEN:-}" ]; then
  echo ""
  echo "=== 增量测试选择 ==="
-
-  CHANGED_FILES=""
-
-  if $IS_PULL_REQUEST; then
-    PR_NUMBER=$(echo "$GITHUB_REF" | sed 's|refs/pull/||; s|/.*||')
-    API_URL="${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/pulls/${PR_NUMBER}/files?limit=300"
-    CHANGED_FILES=$(curl -s -H "Authorization: token ${GITHUB_TOKEN}" "$API_URL" \
-      | python3 -c "import sys,json; [print(f['filename']) for f in json.load(sys.stdin) if f['status'] != 'removed']")
-  elif $IS_PUSH && [ -n "${GITHUB_SHA:-}" ]; then
-    # Push 事件：通过 GitHub API 获取本次 push 改动的文件
-    API_URL="${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/commits/${GITHUB_SHA}"
-    RESPONSE=$(curl -s -H "Authorization: token ${GITHUB_TOKEN}" \
-      -H "Accept: application/vnd.github.v3.diff" "$API_URL" 2>/dev/null || echo "")
-
-    if [ -n "$RESPONSE" ]; then
-      CHANGED_FILES=$(echo "$RESPONSE" | grep '^diff --git' | sed 's|diff --git a/\(.*\) b/.*|\1|' || echo "")
-    fi
-
-    # 备用方案：获取 previous commit SHA 再查 API
-    if [ -z "$CHANGED_FILES" ]; then
-      PREV_SHA=$(curl -s -H "Authorization: token ${GITHUB_TOKEN}" \
-        "${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/commits?sha=${GITHUB_SHA}&per_page=2" \
-        | python3 -c "import sys,json; commits=json.load(sys.stdin); print(commits[1]['sha'] if len(commits)>1 else '')" 2>/dev/null || echo "")
-      if [ -n "$PREV_SHA" ]; then
-        COMPARE_URL="${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/compare/${PREV_SHA}...${GITHUB_SHA}"
-        CHANGED_FILES=$(curl -s -H "Authorization: token ${GITHUB_TOKEN}" "$COMPARE_URL" \
-          | python3 -c "import sys,json; data=json.load(sys.stdin); [print(f['filename']) for f in data.get('files',[]) if f['status'] != 'removed']" 2>/dev/null || echo "")
-      fi
-    fi
-  fi
-
+  PR_NUMBER=$(echo "$GITHUB_REF" | sed 's|refs/pull/||; s|/.*||')
+  API_URL="${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/pulls/${PR_NUMBER}/files?limit=300"
+  CHANGED_FILES=$(curl -s -H "Authorization: token ${GITHUB_TOKEN}" "$API_URL" | python3 -c "import sys,json; [print(f['filename']) for f in json.load(sys.stdin) if f['status'] != 'removed']")
  echo "改动文件数: $(echo "$CHANGED_FILES" | grep -c . || echo 0)"
-
-  if [ -n "$CHANGED_FILES" ]; then
-    set +e
-    CHANGED_FILES="$CHANGED_FILES" \
-    SELECTED_TESTS_OUTPUT=/tmp/selected_tests.txt \
-    python3 scripts/ci/select_unit_tests.py
-    SELECT_EXIT=$?
-    set -e
-    if [ $SELECT_EXIT -eq 0 ]; then
-      UNIT_TEST_MODE="incremental"
-      TEST_FILES=$(cat /tmp/selected_tests.txt | tr '\n' ' ')
-      SELECTED_TEST_FILES="$TEST_FILES"
-      echo "增量模式: $(cat /tmp/selected_tests.txt | wc -l) 个测试文件"
-    else
-      echo "全量模式（增量选择失败）"
-    fi
+  set +e
+  CHANGED_FILES="$CHANGED_FILES" \
+  SELECTED_TESTS_OUTPUT=/tmp/selected_tests.txt \
+  python3 scripts/ci/select_unit_tests.py
+  SELECT_EXIT=$?
+  set -e
+  if [ $SELECT_EXIT -eq 0 ]; then
+    UNIT_TEST_MODE="incremental"
+    TEST_FILES=$(cat /tmp/selected_tests.txt | tr '\n' ' ')
+    SELECTED_TEST_FILES="$TEST_FILES"
+    echo "增量模式: $(cat /tmp/selected_tests.txt | wc -l) 个测试文件"
  else
-    echo "无法获取改动文件列表，使用全量模式"
+    echo "全量模式"
  fi
 fi

@@ -175,7 +116,7 @@ if [ "${GITHUB_EVENT_NAME:-}" = "pull_request" ] && [ -n "${GITHUB_TOKEN:-}" ];

  PR_CODE_DIR="/tmp/pr-code-$$"
  mkdir -p "$PR_CODE_DIR"
-  # 备份PR代码（含coverage.xml，diff-cover需要用到）
+  # 备份PR代码（含coverage.xml，diff-cover需要用到
  find . -maxdepth 1 -mindepth 1 ! -name 'diff_coverage.html' -exec cp -r {} "$PR_CODE_DIR/" \;
  rm -rf .git
  git init > /dev/null 2>&1
@@ -397,7 +397,7 @@ fi
 echo "Stopping old containers..."
 # 优雅关闭：先 stop（发 SIGTERM，等待），再 rm
 # Worker 需要更长时间（视频任务最长可能5分钟）
-docker stop -t 120 xiaoxia-worker-staging 2>/dev/null || true
+docker stop -t 300 xiaoxia-worker-staging 2>/dev/null || true
 docker stop -t 30 xiaoxia-api-staging 2>/dev/null || true
 docker stop -t 10 xiaoxia-web-staging 2>/dev/null || true
 docker rm xiaoxia-worker-staging xiaoxia-api-staging xiaoxia-web-staging 2>/dev/null || true
@@ -187,7 +187,7 @@ health_check() {
            return 0
        fi

-        sleep 3
+        sleep 5
    done

    # 超时了
@@ -197,14 +197,14 @@ class TestComputeAssetAvailability:

    def test_large_gap_remains_usable(self):
        """区间之间留有 ≥3s 空闲段（扩边后仍 ≥3s）→ usable=True。"""
-        # [0,2] 扩边到 [0,3.5]，[9,10] 扩边到 [7.5,10]；空闲 [3.5,7.5]=4.0s >=3
-        # 使用 [0,2] 与 [9,10]，扩边后空闲 [3.5,7.5]=4.0s ≥3 → usable
+        # [0,2] 扩边到 [0,2.3]，[5.3,10] 扩边前为 [5,10] 扩边起 4.7；空闲 [2.3,4.7]=2.4s <3
+        # 改用更大间隙：[0,2] 与 [6,10]，扩边后空闲 [2.3,5.7]=3.4s ≥3
        info = compute_asset_availability(
            _make_asset(
                duration=10.0,
                ranges=[
                    _range(0.0, 2.0, use_count=MAX_RANGE_USE_COUNT),
-                    _range(9.0, 10.0, use_count=MAX_RANGE_USE_COUNT),
+                    _range(6.0, 10.0, use_count=MAX_RANGE_USE_COUNT),
                ],
            )
        )
@@ -236,8 +236,8 @@ class TestComputeAssetAvailability:
        assert info["usable"] is True

    def test_segment_edge_gap_constant(self):
-        """边缘间隙常量为 1.5s（与 MediaKit 冲突检测同口径）。"""
-        assert SEGMENT_EDGE_GAP == 1.5
+        """边缘间隙常量为 0.3s（与 MediaKit 冲突检测同口径）。"""
+        assert SEGMENT_EDGE_GAP == 0.3

    def test_domain_entity_metadata_dict_form(self):
        """领域实体形态（metadata 为 dict，无 classification_result）也能读到区间。
@@ -124,9 +124,9 @@ def _ranges(db, aid="a1"):


 def test_config_constants():
-    assert MAX_RANGE_USE_COUNT == 2
-    assert REUSE_RATIO_LIMIT == 0.10
-    assert SEGMENT_EDGE_GAP == 1.5
+    assert MAX_RANGE_USE_COUNT == 3
+    assert REUSE_RATIO_LIMIT == 0.15
+    assert SEGMENT_EDGE_GAP == 0.3


 # ── get_used_segments ─────────────────────────────────────────────────────────
@@ -320,13 +320,13 @@ def test_find_reusable_prefers_oldest_unused(patched_model):


 def test_find_reusable_excludes_max_use_count(patched_model):
-    """use_count 达到上限（2）的区间不再参与复用；全部达上限返回 None。"""
+    """use_count 达到上限（3）的区间不再参与复用；全部达上限返回 None。"""
    models = {
        "a1": FakeModel(
            "a1",
            {
                "used_time_ranges": [
-                    {"start": 0.0, "end": 10.0, "use_count": 2, "last_used_at": "2026-01-01T00:00:00"},
+                    {"start": 0.0, "end": 10.0, "use_count": 3, "last_used_at": "2026-01-01T00:00:00"},
                ]
            },
        )
@@ -335,22 +335,22 @@ def test_find_reusable_excludes_max_use_count(patched_model):
    assert find_reusable_range(db, "a1", 5.0, 30.0) is None


-def test_find_reusable_third_use_rejected(patched_model):
-    """同区间复用第 3 次被拒绝：use_count=1 的可复用，use_count=2 的不可复用。"""
+def test_find_reusable_fourth_use_rejected(patched_model):
+    """同区间复用第 4 次被拒绝：use_count=2 的可复用，use_count=3 的不可复用。"""
    models = {
        "a1": FakeModel(
            "a1",
            {
                "used_time_ranges": [
-                    {"start": 0.0, "end": 10.0, "use_count": 1, "last_used_at": "2026-03-01T00:00:00"},
-                    {"start": 10.0, "end": 20.0, "use_count": 2, "last_used_at": "2026-01-01T00:00:00"},
+                    {"start": 0.0, "end": 10.0, "use_count": 2, "last_used_at": "2026-03-01T00:00:00"},
+                    {"start": 10.0, "end": 20.0, "use_count": 3, "last_used_at": "2026-01-01T00:00:00"},
                ]
            },
        )
    }
    db = _db(models)
    result = find_reusable_range(db, "a1", 5.0, 30.0)
-    # 只能选 use_count=1 的区间（start=0），不能选 use_count=2 的（虽然它更老）
+    # 只能选 use_count=2 的区间（start=0），不能选 use_count=3 的（虽然它更老）
    assert result is not None and result[0] == 0.0


@@ -1,152 +0,0 @@
-"""测试 create_video_record_and_dedup 传递 user_id 到查重逻辑.
-
-验证 P0 修复：查重范围从项目级扩大到用户级。
-dedup_helpers 必须把 user_id 传给 compute_duplicate_rate。
-"""
-
-from __future__ import annotations
-
-import sys
-from pathlib import Path
-from unittest.mock import MagicMock, patch
-
-import pytest
-
-# Mock cv2/numpy before imports
-sys.modules.setdefault("cv2", MagicMock())
-sys.modules.setdefault("numpy", MagicMock())
-
-ROOT = Path(__file__).resolve().parents[2]
-sys.path.insert(0, str(ROOT / "apps" / "api"))
-sys.path.insert(0, str(ROOT / "packages"))
-sys.path.insert(0, str(ROOT / "apps" / "worker"))
-
-import os
-
-os.environ.setdefault("JWT_SECRET_KEY", "unit-test-secret")
-os.environ.setdefault("DATABASE_URL", "sqlite:///test.db")
-
-
-class TestDedupHelpersUserIdPassthrough:
-    """验证 dedup_helpers 把 user_id 传递给 compute_duplicate_rate."""
-
-    def test_user_id_passed_to_compute_duplicate_rate(self):
-        """create_video_record_and_dedup 必须传 user_id 给 compute_duplicate_rate."""
-        from video_processing.dedup_helpers import create_video_record_and_dedup
-
-        session = MagicMock()
-        mock_video_repo = MagicMock()
-
-        mock_fingerprint = MagicMock()
-        mock_fingerprint.to_dict.return_value = {"md5": "test", "keyframe_phashes": ["aa"]}
-
-        mock_deduplicator = MagicMock()
-        mock_deduplicator.compute_fingerprint.return_value = mock_fingerprint
-        mock_deduplicator.check_duplicate.return_value = None
-        mock_deduplicator.compute_duplicate_rate.return_value = 42.5
-
-        with (
-            patch(
-                "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository",
-                return_value=mock_video_repo,
-            ),
-            patch("video_processing.dedup.VideoDeduplicator", return_value=mock_deduplicator),
-        ):
-            result = create_video_record_and_dedup(
-                generation_task_id="task-001",
-                project_id="proj-001",
-                user_id="user-abc",
-                batch_id="",
-                file_url="https://example.com/video.mp4",
-                file_size=1024,
-                duration=15.0,
-                video_path="/tmp/fake_video.mp4",
-                mode="smart",
-                session=session,
-            )
-
-        # 验证 compute_duplicate_rate 被调用且 user_id 正确传递
-        mock_deduplicator.compute_duplicate_rate.assert_called_once()
-        call_kwargs = mock_deduplicator.compute_duplicate_rate.call_args
-        assert (
-            call_kwargs.kwargs.get("user_id") == "user-abc"
-        ), f"user_id 应传递给 compute_duplicate_rate，实际: {call_kwargs}"
-
-    def test_empty_user_id_still_works(self):
-        """user_id 为空时仍然正常执行（回退到 project 级比较）."""
-        from video_processing.dedup_helpers import create_video_record_and_dedup
-
-        session = MagicMock()
-        mock_video_repo = MagicMock()
-
-        mock_fingerprint = MagicMock()
-        mock_fingerprint.to_dict.return_value = {"md5": "test"}
-
-        mock_deduplicator = MagicMock()
-        mock_deduplicator.compute_fingerprint.return_value = mock_fingerprint
-        mock_deduplicator.check_duplicate.return_value = None
-        mock_deduplicator.compute_duplicate_rate.return_value = 0.0
-
-        with (
-            patch(
-                "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository",
-                return_value=mock_video_repo,
-            ),
-            patch("video_processing.dedup.VideoDeduplicator", return_value=mock_deduplicator),
-        ):
-            result = create_video_record_and_dedup(
-                generation_task_id="task-002",
-                project_id="proj-002",
-                user_id="",
-                batch_id="",
-                file_url="https://example.com/video.mp4",
-                file_size=1024,
-                duration=10.0,
-                video_path="/tmp/fake.mp4",
-                mode="smart",
-                session=session,
-            )
-
-        mock_deduplicator.compute_duplicate_rate.assert_called_once()
-        call_kwargs = mock_deduplicator.compute_duplicate_rate.call_args
-        assert call_kwargs.kwargs.get("user_id") == ""
-
-    def test_duplicate_rate_saved_to_video_record(self):
-        """compute_duplicate_rate 的返回值应写入 generated_video.duplicate_rate."""
-        from video_processing.dedup_helpers import create_video_record_and_dedup
-
-        session = MagicMock()
-        mock_video_repo = MagicMock()
-
-        mock_fingerprint = MagicMock()
-        mock_fingerprint.to_dict.return_value = {"md5": "test"}
-
-        mock_deduplicator = MagicMock()
-        mock_deduplicator.compute_fingerprint.return_value = mock_fingerprint
-        mock_deduplicator.check_duplicate.return_value = None
-        mock_deduplicator.compute_duplicate_rate.return_value = 78.5
-
-        with (
-            patch(
-                "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository",
-                return_value=mock_video_repo,
-            ),
-            patch("video_processing.dedup.VideoDeduplicator", return_value=mock_deduplicator),
-        ):
-            result = create_video_record_and_dedup(
-                generation_task_id="task-003",
-                project_id="proj-003",
-                user_id="user-xyz",
-                batch_id="",
-                file_url="https://example.com/v.mp4",
-                file_size=2048,
-                duration=20.0,
-                video_path="/tmp/fake2.mp4",
-                mode="smart",
-                session=session,
-            )
-
-        # 验证 update 被调用（包含 duplicate_rate 的记录）
-        mock_video_repo.update.assert_called_once()
-        updated_video = mock_video_repo.update.call_args[0][0]
-        assert updated_video.duplicate_rate == 78.5
@@ -56,10 +56,9 @@ class TestComputeDuplicateRate:

        with patch("video_processing.dedup.SQLAlchemyGeneratedVideoRepository") as MockRepo:
            mock_repo = MockRepo.return_value
-            query_mock = MagicMock()
-            query_mock.filter.return_value = query_mock
-            query_mock.order_by.return_value.limit.return_value.all.return_value = []
-            session.query.return_value = query_mock
+            session.query.return_value.filter.return_value.order_by.return_value.limit.return_value.all.return_value = (
+                []
+            )
            rate = deduplicator.compute_duplicate_rate(fingerprint, "proj1", "vid1", session)

        assert rate == 0.0
@@ -74,6 +73,7 @@ class TestComputeDuplicateRate:
        session = MagicMock()

        existing = self._make_existing_video("existing1", {"md5": "exact_match_md5", "keyframe_phashes": ["aa"]})
+        # Create a mock model with the domain attributes
        mock_model = MagicMock(spec=GeneratedVideoModel)
        mock_model.id = existing.id
        mock_model.project_id = existing.project_id
@@ -83,12 +83,10 @@ class TestComputeDuplicateRate:
        with patch("video_processing.dedup.SQLAlchemyGeneratedVideoRepository") as MockRepo:
            mock_repo = MockRepo.return_value
            mock_repo._to_domain.return_value = existing
-            # 链式 filter: 第一次 scope filter，第二次 self-exclusion filter
-            # 让 filter() 返回的对象仍然支持 order_by() 链
-            query_mock = MagicMock()
-            query_mock.filter.return_value = query_mock  # filter → filter chainable
-            query_mock.order_by.return_value.limit.return_value.all.return_value = [mock_model]
-            session.query.return_value = query_mock
+            # Mock the session.query chain
+            session.query.return_value.filter.return_value.order_by.return_value.limit.return_value.all.return_value = [
+                mock_model
+            ]
            rate = deduplicator.compute_duplicate_rate(fingerprint, "proj1", "vid1", session)

        assert rate == 100.0
@@ -115,10 +113,9 @@ class TestComputeDuplicateRate:
        with patch("video_processing.dedup.SQLAlchemyGeneratedVideoRepository") as MockRepo:
            mock_repo = MockRepo.return_value
            mock_repo._to_domain.return_value = existing
-            query_mock = MagicMock()
-            query_mock.filter.return_value = query_mock
-            query_mock.order_by.return_value.limit.return_value.all.return_value = [mock_model]
-            session.query.return_value = query_mock
+            session.query.return_value.filter.return_value.order_by.return_value.limit.return_value.all.return_value = [
+                mock_model
+            ]
            rate = deduplicator.compute_duplicate_rate(fingerprint, "proj1", "vid1", session)

        # hamming distance = 2, similarity = (1 - 2/64) * 100 = 96.875
@@ -143,10 +140,9 @@ class TestComputeDuplicateRate:
        with patch("video_processing.dedup.SQLAlchemyGeneratedVideoRepository") as MockRepo:
            mock_repo = MockRepo.return_value
            mock_repo._to_domain.return_value = self_video
-            query_mock = MagicMock()
-            query_mock.filter.return_value = query_mock
-            query_mock.order_by.return_value.limit.return_value.all.return_value = [mock_model]
-            session.query.return_value = query_mock
+            session.query.return_value.filter.return_value.order_by.return_value.limit.return_value.all.return_value = [
+                mock_model
+            ]
            rate = deduplicator.compute_duplicate_rate(fingerprint, "proj1", "vid1", session)

        assert rate == 0.0
@@ -176,89 +172,15 @@ class TestComputeDuplicateRate:
        with patch("video_processing.dedup.SQLAlchemyGeneratedVideoRepository") as MockRepo:
            mock_repo = MockRepo.return_value
            mock_repo._to_domain.side_effect = [existing1, existing2]
-            query_mock = MagicMock()
-            query_mock.filter.return_value = query_mock
-            query_mock.order_by.return_value.limit.return_value.all.return_value = [
+            session.query.return_value.filter.return_value.order_by.return_value.limit.return_value.all.return_value = [
                mock_model1,
                mock_model2,
            ]
-            session.query.return_value = query_mock
            rate = deduplicator.compute_duplicate_rate(fingerprint, "proj1", "vid1", session)

        # max similarity: e2 distance=1, (1-1/64)*100 = 98.4375
        assert rate == pytest.approx(98.44, abs=0.1)

-    def test_user_id_scope_cross_project(self):
-        """传 user_id 时应跨项目查询，而非仅当前项目."""
-        from video_processing.dedup import VideoDeduplicator
-
-        from packages.adapters.sqlalchemy_impl.models import GeneratedVideoModel
-
-        deduplicator = VideoDeduplicator()
-        fingerprint = self._make_fingerprint(md5="cross_proj_md5")
-        session = MagicMock()
-
-        # 模拟一个不同项目但同一用户的视频
-        existing = self._make_existing_video(
-            "existing_other_proj", {"md5": "cross_proj_md5", "keyframe_phashes": ["aa"]}
-        )
-        existing.project_id = "proj2"  # 不同项目
-        existing.user_id = "user1"
-
-        mock_model = MagicMock(spec=GeneratedVideoModel)
-        mock_model.id = existing.id
-        mock_model.project_id = existing.project_id
-        mock_model.user_id = existing.user_id
-        mock_model.video_fingerprint = existing.video_fingerprint
-        mock_model.generated_at = "2026-01-01"
-
-        with patch("video_processing.dedup.SQLAlchemyGeneratedVideoRepository") as MockRepo:
-            mock_repo = MockRepo.return_value
-            mock_repo._to_domain.return_value = existing
-
-            query_mock = MagicMock()
-            query_mock.filter.return_value = query_mock
-            query_mock.order_by.return_value.limit.return_value.all.return_value = [mock_model]
-            session.query.return_value = query_mock
-
-            rate = deduplicator.compute_duplicate_rate(
-                fingerprint,
-                "proj1",
-                "vid1",
-                session,
-                user_id="user1",
-            )
-
-        # 应通过 user_id 过滤，且匹配到跨项目视频
-        assert rate == 100.0
-
-    def test_user_id_empty_falls_back_to_project(self):
-        """user_id 为空时应回退到 project_id 过滤."""
-        from video_processing.dedup import VideoDeduplicator
-
-        deduplicator = VideoDeduplicator()
-        fingerprint = self._make_fingerprint()
-        session = MagicMock()
-
-        with patch("video_processing.dedup.SQLAlchemyGeneratedVideoRepository") as MockRepo:
-            mock_repo = MockRepo.return_value
-            query_mock = MagicMock()
-            query_mock.filter.return_value = query_mock
-            query_mock.order_by.return_value.limit.return_value.all.return_value = []
-            session.query.return_value = query_mock
-
-            rate = deduplicator.compute_duplicate_rate(
-                fingerprint,
-                "proj1",
-                "vid1",
-                session,
-                user_id="",
-            )
-
-        assert rate == 0.0
-        # 验证使用的是 project_id 过滤（回退路径）
-        # 通过检查 filter 被调用时的参数来间接验证
-

 class TestDuplicateRateAPI:
    """Test that duplicate_rate is returned in API responses."""
@@ -1,97 +0,0 @@
-"""Tests for duration compensation when source video is shorter than configured duration."""
-
-from pathlib import Path
-
-import pytest
-
-from apps.worker.video_processing.unified_render_service import ResolvedClip, UnifiedRenderService
-
-
-class TestClipEffectiveDurationWithSpeedCompensation:
-    """Test _clip_effective_duration handles speed < 1 correctly."""
-
-    def test_normal_speed_returns_min(self):
-        """When speed=1.0, effective_duration = min(duration, actual_duration)."""
-        clip = ResolvedClip(
-            clip_id="c1",
-            asset_id="a1",
-            local_path=Path("/tmp/fake.mp4"),
-            clip_type="main",
-            order=0,
-            start_time=0.0,
-            duration=4.0,
-            actual_duration=3.0,  # shorter than configured
-            playback_speed=1.0,
-        )
-        # Without speed compensation, effective = min(4, 3) = 3
-        assert UnifiedRenderService._clip_effective_duration(clip) == 3.0
-
-    def test_compensated_speed_returns_configured_duration(self):
-        """When speed < 1 (compensated), effective_duration = configured duration."""
-        clip = ResolvedClip(
-            clip_id="c1",
-            asset_id="a1",
-            local_path=Path("/tmp/fake.mp4"),
-            clip_type="main",
-            order=0,
-            start_time=0.0,
-            duration=4.0,
-            actual_duration=3.0,  # shorter than configured
-            playback_speed=0.75,  # compensated: 3/4 = 0.75
-        )
-        # With speed compensation, effective = configured duration = 4.0
-        assert UnifiedRenderService._clip_effective_duration(clip) == 4.0
-
-    def test_zero_actual_duration_returns_configured(self):
-        """When actual_duration=0, effective_duration = configured duration."""
-        clip = ResolvedClip(
-            clip_id="c1",
-            asset_id="a1",
-            local_path=Path("/tmp/fake.mp4"),
-            clip_type="main",
-            order=0,
-            start_time=0.0,
-            duration=4.0,
-            actual_duration=0.0,
-            playback_speed=1.0,
-        )
-        assert UnifiedRenderService._clip_effective_duration(clip) == 4.0
-
-    def test_compensated_speed_with_actual_zero(self):
-        """When speed < 1 and actual=0, still returns configured duration."""
-        clip = ResolvedClip(
-            clip_id="c1",
-            asset_id="a1",
-            local_path=Path("/tmp/fake.mp4"),
-            clip_type="main",
-            order=0,
-            start_time=0.0,
-            duration=4.0,
-            actual_duration=0.0,
-            playback_speed=0.5,
-        )
-        assert UnifiedRenderService._clip_effective_duration(clip) == 4.0
-
-
-class TestClipAdjustedDurationWithSpeedCompensation:
-    """Test _clip_adjusted_duration accounts for compensated speed."""
-
-    def test_adjusted_duration_with_compensation(self):
-        """Adjusted duration = min(duration, actual) / speed.
-        With compensation: min(4,3)/0.75 = 3/0.75 = 4.0
-        This equals the configured duration, which is the goal.
-        """
-        clip = ResolvedClip(
-            clip_id="c1",
-            asset_id="a1",
-            local_path=Path("/tmp/fake.mp4"),
-            clip_type="main",
-            order=0,
-            start_time=0.0,
-            duration=4.0,
-            actual_duration=3.0,
-            playback_speed=0.75,  # compensated
-        )
-        adjusted = UnifiedRenderService._clip_adjusted_duration(clip)
-        # min(4,3)/0.75 = 3/0.75 = 4.0 (matches configured duration)
-        assert abs(adjusted - 4.0) < 0.01
@@ -58,10 +58,6 @@ def _make_mock_asset(asset_id, duration):
    asset = MagicMock()
    asset.id = asset_id
    asset.duration = duration
-    # score_asset 所需的属性（避免 MagicMock 导致类型比较错误）
-    asset.quality_score = None
-    asset.created_at = None
-    asset.metadata = {}
    return asset


@@ -146,12 +142,11 @@ class TestEditorClipsBySegments:
        clips_data = _get_clips_data_from_call(mock_plan_svc)
        assert len(clips_data) == 4

-        # 验证均衡分配（贪心策略保证）：2个素材分4个片段，每个素材恰好使用2次
-        from collections import Counter
-
-        asset_ids = [c["asset_id"] for c in clips_data]
-        counts = Counter(asset_ids)
-        assert counts["a1"] == 2 and counts["a2"] == 2
+        # 验证轮询分配：a1, a2, a1, a2
+        assert clips_data[0]["asset_id"] == "a1"
+        assert clips_data[1]["asset_id"] == "a2"
+        assert clips_data[2]["asset_id"] == "a1"
+        assert clips_data[3]["asset_id"] == "a2"

    @patch("app.api.routes.templates_editor.clips.get_storage_service")
    def test_orders_start_at_zero(self, mock_storage):
@@ -418,13 +413,8 @@ class TestEditorClipsDurationAndStartTime:

        assert mock_calc.call_count == 2
        clips_data = _get_clips_data_from_call(mock_plan_svc)
-        # clips_data 按 order 排序，但分配顺序因 shuffle 而随机，
-        # 因此只验证两个 start_time 值都存在
-        start_times = {c["start_time"] for c in clips_data}
-        assert start_times == {12.5, 18.0}
-        # 验证 order 仍然有序
-        orders = [c["order"] for c in clips_data]
-        assert orders == sorted(orders)
+        assert clips_data[0]["start_time"] == 12.5
+        assert clips_data[1]["start_time"] == 18.0

    @patch("app.api.routes.templates_editor.clips.get_storage_service")
    def test_asset_durations_deduped(self, mock_storage):
@@ -641,8 +631,7 @@ class TestReuseRatioGate:
        clips_data = _get_clips_data_from_call(mock_plan_svc)
        assert len(clips_data) == 13
        # 1 个复用片段，占比 1/13 ≈ 7.7% ≤ 15%
-        # 转场补偿: raw_duration = 5.0 + (13-1)*0.5/13 ≈ 5.462 → round(5.462,1) = 5.5
-        assert abs(reused.get("a1", 0.0) - 5.5) < 0.1
+        assert reused.get("a1", 0.0) == 5.0

    @patch("app.api.routes.templates_editor.clips.get_storage_service")
    def test_reuse_ratio_exceeded_returns_400(self, mock_storage):
@@ -32,16 +32,16 @@ class TestRecommendedTimeConflicts:
        assert _recommended_time_conflicts(10.0, 5.0, [(10.0, 15.0)]) is True

    def test_touching_endpoint_conflicts_due_to_edge_gap(self):
-        """首尾紧贴（推荐 15 开始，已用 [10,15]）：1.5s 扩边内 → 冲突。"""
+        """首尾紧贴（推荐 15 开始，已用 [10,15]）：0.3s 扩边内 → 冲突。"""
        assert _recommended_time_conflicts(15.0, 5.0, [(10.0, 15.0)]) is True

    def test_gap_within_edge_gap_conflicts(self):
-        """间隔 0.2s（< 1.5s 边缘间隙）→ 冲突。"""
+        """间隔 0.2s（< 0.3s 边缘间隙）→ 冲突。"""
        assert _recommended_time_conflicts(15.2, 5.0, [(10.0, 15.0)]) is True

    def test_gap_beyond_edge_gap_no_conflict(self):
-        """间隔 2.0s（> 1.5s 边缘间隙）→ 不冲突。"""
-        assert _recommended_time_conflicts(17.0, 5.0, [(10.0, 15.0)]) is False
+        """间隔 0.5s（> 0.3s 边缘间隙）→ 不冲突。"""
+        assert _recommended_time_conflicts(15.5, 5.0, [(10.0, 15.0)]) is False

    def test_far_apart_no_conflict(self):
        """相隔很远 → 不冲突。"""
@@ -54,9 +54,7 @@ class TestRecommendedTimeConflicts:
        """多个已用区间，任一冲突即返回 True。"""
        used = [(0.0, 5.0), (10.0, 15.0), (20.0, 25.0)]
        assert _recommended_time_conflicts(12.0, 2.0, used) is True
-        assert (
-            _recommended_time_conflicts(6.5, 2.0, used) is False
-        )  # range [6.5,8.5], just outside all expanded used ranges
+        assert _recommended_time_conflicts(6.0, 2.0, used) is False

    def test_custom_edge_gap(self):
        """edge_gap 可配置：gap=0 时紧贴不冲突（端点相接不算重叠）。"""
@@ -66,5 +64,5 @@ class TestRecommendedTimeConflicts:
        assert _recommended_time_conflicts(15.5, 5.0, [(10.0, 15.0)], edge_gap=1.0) is True

    def test_default_edge_gap_constant(self):
-        """默认边缘间隙常量为 1.5s（配置常量）。"""
-        assert SEGMENT_EDGE_GAP == 1.5
+        """默认边缘间隙常量为 0.3s（配置常量）。"""
+        assert SEGMENT_EDGE_GAP == 0.3
@@ -69,13 +69,13 @@ class TestRecommendedTimeConflicts:
    def test_conflict_exact_boundary_no_overlap(self):
        from app.api.routes.templates_editor.clips import _recommended_time_conflicts

-        # 新语义：默认 1.5s 边缘间隙扩边，推荐 [10, 15] 与已用 [0, 10] 首尾相接
+        # 新语义：默认 0.3s 边缘间隙扩边，推荐 [10, 15] 与已用 [0, 10] 首尾相接
        # 落在扩边范围内 → 判为冲突（避免观感重复）
        assert _recommended_time_conflicts(10.0, 5.0, [(0.0, 10.0)]) is True
        # 显式 edge_gap=0 时退回纯区间重叠判定：相接不算重叠
        assert _recommended_time_conflicts(10.0, 5.0, [(0.0, 10.0)], edge_gap=0.0) is False
-        # 间隙大于边缘间隙（2.0 > 1.5）→ 不冲突
-        assert _recommended_time_conflicts(12.0, 5.0, [(0.0, 10.0)]) is False
+        # 间隙大于边缘间隙（0.5 > 0.3）→ 不冲突
+        assert _recommended_time_conflicts(10.5, 5.0, [(0.0, 10.0)]) is False

    def test_conflict_multiple_used(self):
        from app.api.routes.templates_editor.clips import _recommended_time_conflicts
@@ -83,10 +83,10 @@ class TestRecommendedTimeConflicts:
        used = [(0.0, 5.0), (10.0, 15.0), (20.0, 25.0)]
        # 推荐 [6, 11] 与 [10, 15] 冲突
        assert _recommended_time_conflicts(6.0, 5.0, used) is True
-        # 推荐 [15, 20] 与 [10, 15] 首尾相接：1.5s 扩边内 → 冲突
+        # 推荐 [15, 20] 与 [10, 15] 首尾相接：0.3s 扩边内 → 冲突
        assert _recommended_time_conflicts(15.0, 5.0, used) is True
-        # 空闲段 (6.5, 8.5) 长 2.0s：推荐 [6.6, 8.4]（dur=1.8）与三区间扩边均不接触
-        assert _recommended_time_conflicts(6.6, 1.8, used) is False
+        # 空闲段 [5.3, 9.7] 长 4.4s：推荐 [5.5, 9.5]（dur=4）与三区间扩边均不接触
+        assert _recommended_time_conflicts(5.5, 4.0, used) is False


 # ── _get_mediakit_recommendations 单元测试 ──────────────────────────────────
@@ -347,10 +347,6 @@ def _make_rich_asset(asset_id, duration, storage_key="v.mp4", mime="video/mp4"):
    asset.duration = duration
    asset.storage_key = storage_key
    asset.mime_type = mime
-    # score_asset 所需的属性（避免 MagicMock 导致类型比较错误）
-    asset.quality_score = None
-    asset.created_at = None
-    asset.metadata = {}
    return asset


@@ -446,15 +442,11 @@ class TestFromAssetsByTemplateSegments:
        )

        clips_data = _get_clips_data(mock_plan_svc)
-        # PR #1614 转场补偿：2 个片段时每 clip 时长 +(2-1)*0.5/2=0.25s
-        # （xfade 重叠在渲染时扣除，故 clip 时长 = segment 随机时长 + 补偿），
-        # 断言上界需计入补偿与一位小数舍入余量
-        comp = (2 - 1) * 0.5 / 2
-        assert 3.0 + comp - 0.1 <= clips_data[0]["duration"] <= 5.0 + comp + 0.1
-        assert 4.0 + comp - 0.1 <= clips_data[1]["duration"] <= 8.0 + comp + 0.1
+        assert 3.0 <= clips_data[0]["duration"] <= 5.0
+        assert 4.0 <= clips_data[1]["duration"] <= 8.0

-    def test_assets_balanced_assignment(self):
-        """素材按使用次数贪心分配（使用少的优先），保证均衡使用。"""
+    def test_assets_round_robin_assignment(self):
+        """素材按片段顺序轮询分配。"""
        from app.api.routes.templates_editor.clips import create_clips_from_assets_editor
        from app.api.routes.templates_editor.schemas import ClipsFromAssetsRequest

@@ -483,11 +475,7 @@ class TestFromAssetsByTemplateSegments:

        clips_data = _get_clips_data(mock_plan_svc)
        asset_ids = [c["asset_id"] for c in clips_data]
-        # 贪心分配保证均衡：2个素材分4个片段，每个素材恰好使用2次
-        from collections import Counter
-
-        counts = Counter(asset_ids)
-        assert counts["a1"] == 2 and counts["a2"] == 2
+        assert asset_ids == ["a1", "a2", "a1", "a2"]

    def test_orders_start_from_zero(self):
        """片段 order 从 0 开始递增。"""
@@ -908,10 +908,6 @@ class TestAssetDurationsAlwaysFetched:
        def fake_get(asset_id):
            mock_asset = MagicMock()
            mock_asset.duration = 30.0  # 每个素材 30 秒
-            # score_asset 所需的属性
-            mock_asset.quality_score = None
-            mock_asset.created_at = None
-            mock_asset.metadata = {}
            return mock_asset

        asset_repo.get = MagicMock(side_effect=fake_get)
@@ -1,257 +0,0 @@
-"""Tests for scene-change smart frame selection + random shuffle of segment processing."""
-
-from __future__ import annotations
-
-import random
-from unittest.mock import MagicMock, patch
-
-import pytest
-
-from apps.api.app.api.routes.templates_editor.clips import (
-    _build_scene_segments,
-    _pick_start_in_scene_segment,
-)
-from packages.shared.mediakit_client import MediaKitClient
-
-# ── Part 1: Random shuffle tests ──────────────────────────────────────────
-
-
-class TestRandomShuffle:
-    """验证 segments 处理顺序随机打乱逻辑."""
-
-    def test_same_segments_produce_different_asset_orders(self):
-        """同一批 segments 多次处理，asset 分配顺序有变化.
-
-        模拟打乱后的处理顺序，验证多次运行中 asset_id 分配顺序
-        存在差异（概率性验证，运行 50 次应该至少出现 2 种排列）。
-        """
-        segments = [(0, 3.0, 5.0), (1, 4.0, 6.0), (2, 3.0, 5.0), (3, 4.0, 6.0)]
-        asset_ids = ["A", "B", "C", "D"]
-
-        observed_orders: list[tuple] = set()
-
-        for _ in range(50):
-            shuffled_indices = list(range(len(segments)))
-            random.shuffle(shuffled_indices)
-            order_tuple = tuple(shuffled_indices)
-            observed_orders.add(order_tuple)
-
-        # 50 次打乱，4! = 24 种排列，应出现多种不同排列
-        assert len(observed_orders) > 1, "打乱应该产生多种不同顺序"
-
-    def test_clips_data_order_always_sorted(self):
-        """clips_data 按 order 排序后始终有序.
-
-        模拟打乱处理后 clips_data 按 order 排序，验证最终 order 为 [0,1,2,3]。
-        """
-        segments = [(0, 3.0, 5.0), (1, 4.0, 6.0), (2, 3.0, 5.0), (3, 4.0, 6.0)]
-
-        for _ in range(20):
-            shuffled_indices = list(range(len(segments)))
-            random.shuffle(shuffled_indices)
-
-            # 模拟构建 clips_data（用 _seg_order 作为 order）
-            clips_data = []
-            for idx in shuffled_indices:
-                seg_order, _, _ = segments[idx]
-                clips_data.append({"order": seg_order, "asset_id": f"asset_{idx}"})
-
-            # 按 order 排序
-            clips_data.sort(key=lambda c: c["order"])
-
-            # 验证 order 始终有序
-            orders = [c["order"] for c in clips_data]
-            assert orders == [0, 1, 2, 3], f"排序后 order 应为 [0,1,2,3]，实际为 {orders}"
-
-
-# ── Part 2: detect_scene_changes tests ────────────────────────────────────
-
-
-class TestDetectSceneChanges:
-    """验证 MediaKitClient.detect_scene_changes 方法."""
-
-    def _make_client(self) -> MediaKitClient:
-        """创建一个可用的 MediaKitClient（mock 配置）."""
-        with patch("packages.shared.mediakit_client.get_shared_settings") as mock_settings:
-            mock_settings.return_value.mediakit_api_key = "test-key"
-            mock_settings.return_value.mediakit_base_url = "http://test"
-            mock_settings.return_value.mediakit_timeout = 30
-            client = MediaKitClient()
-        return client
-
-    def test_scene_change_success(self):
-        """SceneChange 策略成功返回时间戳列表."""
-        client = self._make_client()
-
-        mock_frames = [
-            {"image_url": "url1", "timestamp": 0.0},
-            {"image_url": "url2", "timestamp": 3.2},
-            {"image_url": "url3", "timestamp": 7.8},
-            {"image_url": "url4", "timestamp": 12.5},
-        ]
-
-        with patch.object(client, "extract_frames", return_value=mock_frames):
-            result = client.detect_scene_changes("https://example.com/video.mp4")
-
-        assert result is not None
-        assert result[0] == 0.0  # 始终以 0.0 开头
-        assert 3.2 in result
-        assert 7.8 in result
-        assert 12.5 in result
-        assert result == sorted(result)  # 应已排序
-
-    def test_scene_change_fallback_to_time_interval(self):
-        """SceneChange 失败降级到 TimeInterval 策略."""
-        client = self._make_client()
-
-        # 第一次调用（SceneChange）返回 None，第二次（TimeInterval）返回结果
-        fallback_frames = [
-            {"image_url": "url1", "timestamp": 0.0},
-            {"image_url": "url2", "timestamp": 5.0},
-            {"image_url": "url3", "timestamp": 10.0},
-        ]
-
-        call_count = 0
-
-        def side_effect(*args, **kwargs):
-            nonlocal call_count
-            call_count += 1
-            if call_count == 1:
-                # 第一次 SceneChange 失败
-                return None
-            else:
-                # 第二次 TimeInterval 成功
-                assert kwargs.get("strategy") == "TimeInterval"
-                return fallback_frames
-
-        with patch.object(client, "extract_frames", side_effect=side_effect):
-            result = client.detect_scene_changes("https://example.com/video.mp4")
-
-        assert result is not None
-        assert result[0] == 0.0
-        assert 5.0 in result
-        assert 10.0 in result
-
-    def test_mediakit_not_available_returns_none(self):
-        """MediaKit 不可用时返回 None."""
-        with patch("packages.shared.mediakit_client.get_shared_settings") as mock_settings:
-            mock_settings.return_value.mediakit_api_key = ""  # 未配置
-            mock_settings.return_value.mediakit_base_url = "http://test"
-            mock_settings.return_value.mediakit_timeout = 30
-            client = MediaKitClient()
-
-        result = client.detect_scene_changes("https://example.com/video.mp4")
-        assert result is None
-
-    def test_both_strategies_fail_returns_none(self):
-        """SceneChange 和 TimeInterval 都失败时返回 None."""
-        client = self._make_client()
-
-        with patch.object(client, "extract_frames", return_value=None):
-            result = client.detect_scene_changes("https://example.com/video.mp4")
-
-        assert result is None
-
-    def test_prepends_zero_if_not_present(self):
-        """若帧列表中不包含 0.0，自动在开头添加."""
-        client = self._make_client()
-
-        # 帧列表中没有 timestamp=0.0
-        mock_frames = [
-            {"image_url": "url1", "timestamp": 2.0},
-            {"image_url": "url2", "timestamp": 5.5},
-        ]
-
-        with patch.object(client, "extract_frames", return_value=mock_frames):
-            result = client.detect_scene_changes("https://example.com/video.mp4")
-
-        assert result is not None
-        assert result[0] == 0.0
-        assert 2.0 in result
-        assert 5.5 in result
-
-
-# ── Part 2.2: Scene segment building and assignment ───────────────────────
-
-
-class TestSceneSegments:
-    """验证镜头段构建和分配逻辑."""
-
-    def test_build_scene_segments(self):
-        """从场景切换点正确构建镜头段."""
-        scene_changes = [0.0, 3.2, 7.8, 12.5]
-        asset_duration = 15.0
-
-        segments = _build_scene_segments(scene_changes, asset_duration)
-
-        assert len(segments) == 4
-        assert segments[0] == (0.0, 3.2)
-        assert segments[1] == (3.2, 7.8)
-        assert segments[2] == (7.8, 12.5)
-        assert segments[3] == (12.5, 15.0)
-
-    def test_build_scene_segments_filters_short(self):
-        """过滤掉过短的镜头段（< 0.5秒）."""
-        scene_changes = [0.0, 0.1, 5.0, 5.3, 10.0]
-        asset_duration = 12.0
-
-        segments = _build_scene_segments(scene_changes, asset_duration)
-
-        # (0.0, 0.1) 长度 0.1 < 0.5 → 过滤
-        # (0.1, 5.0) → 保留
-        # (5.0, 5.3) 长度 0.3 < 0.5 → 过滤
-        # (5.3, 10.0) → 保留
-        # (10.0, 12.0) → 保留
-        assert len(segments) == 3
-        assert segments[0] == (0.1, 5.0)
-        assert segments[1] == (5.3, 10.0)
-        assert segments[2] == (10.0, 12.0)
-
-    def test_pick_start_in_segment(self):
-        """在镜头段内随机选取起始时间."""
-        seg_start = 3.0
-        seg_end = 8.0
-        clip_duration = 2.0
-
-        starts = set()
-        for _ in range(100):
-            start = _pick_start_in_scene_segment(seg_start, seg_end, clip_duration)
-            assert start is not None
-            assert seg_start <= start <= seg_end - clip_duration
-            starts.add(round(start, 2))
-
-        # 应该有多个不同的起始时间
-        assert len(starts) > 1
-
-    def test_pick_start_segment_too_short(self):
-        """镜头段太短无法容纳片段时返回 None."""
-        result = _pick_start_in_scene_segment(0.0, 1.0, 2.0)
-        assert result is None
-
-    def test_different_clips_from_different_scenes(self):
-        """不同片段应来自不同的镜头段（模拟分配逻辑）."""
-        scene_changes = [0.0, 5.0, 10.0, 15.0]
-        asset_duration = 18.0
-        clip_duration = 3.0
-
-        segments = _build_scene_segments(scene_changes, asset_duration)
-        assert len(segments) == 4  # (0,5), (5,10), (10,15), (15,18)
-
-        # 模拟 3 个片段从不同镜头段取点
-        scene_pool = list(segments)
-        assigned_starts = []
-
-        for _ in range(3):
-            if not scene_pool:
-                break
-            seg_start, seg_end = scene_pool.pop(0)
-            start = _pick_start_in_scene_segment(seg_start, seg_end, clip_duration)
-            assert start is not None
-            assigned_starts.append(start)
-
-        # 3 个片段分别从 3 个不同镜头段中选取
-        assert len(assigned_starts) == 3
-        # 第一个来自 [0, 2]，第二个来自 [5, 7]，第三个来自 [10, 12]
-        assert 0.0 <= assigned_starts[0] <= 2.0
-        assert 5.0 <= assigned_starts[1] <= 7.0
-        assert 10.0 <= assigned_starts[2] <= 12.0
@@ -1,324 +0,0 @@
-"""测试 smart_match 评分集成到素材选取路径。
-
-验证：
- 使用次数多的素材评分低于使用次数少的（unused 维度降权生效）
- from-assets 路径中 sorted_candidates 按 smart_match 评分排序
- 一键生成路径中 _sort_assets_by_smart_score 按评分降序
-"""
-
-from __future__ import annotations
-
-import os
-import sys
-from dataclasses import dataclass, field
-from datetime import datetime, timezone
-from pathlib import Path
-from typing import Any
-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
-
-from packages.domain.smart_match import score_asset, smart_select_assets
-
-# ── 辅助工厂 ──────────────────────────────────────────────────────────────────
-
-
-@dataclass
-class FakeAsset:
-    """Minimal Asset-like object."""
-
-    id: str
-    quality_score: float | None = 70.0
-    duration: float = 15.0
-    created_at: datetime | None = None
-    metadata: dict[str, Any] = field(default_factory=dict)
-    status: str = "ready"
-    file_type: str = "video"
-
-
-def _asset_with_use_count(asset_id: str, use_count: int) -> FakeAsset:
-    """创建指定使用次数的素材，其他维度保持一致。"""
-    return FakeAsset(
-        id=asset_id,
-        quality_score=70.0,
-        duration=15.0,  # 最优区间 5-30s
-        created_at=datetime(2026, 1, 1, tzinfo=timezone.utc),
-        metadata={"generation_use_count": use_count},
-    )
-
-
-# ── score_asset 单元测试：unused 维度降权 ─────────────────────────────────────
-
-
-class TestScoreAssetUnusedDiminsh:
-    """验证 unused 维度：使用次数越多，评分越低。"""
-
-    def test_unused_scores_higher_than_used(self):
-        """use_count=0 的素材评分高于 use_count>0 的。"""
-        fresh = _asset_with_use_count("fresh", 0)
-        used = _asset_with_use_count("used", 1)
-        fresh_score, _ = score_asset(fresh)
-        used_score, _ = score_asset(used)
-        assert fresh_score > used_score
-
-    def test_high_use_count_scores_lower_than_low(self):
-        """use_count=5 的素材评分低于 use_count=1 的。"""
-        low_use = _asset_with_use_count("low", 1)
-        high_use = _asset_with_use_count("high", 5)
-        low_score, _ = score_asset(low_use)
-        high_score, _ = score_asset(high_use)
-        assert low_score > high_score
-
-    def test_unused_breakdown_values(self):
-        """验证 unused 维度的具体分值。"""
-        fresh = _asset_with_use_count("fresh", 0)
-        low = _asset_with_use_count("low", 2)
-        high = _asset_with_use_count("high", 10)
-
-        _, fresh_bd = score_asset(fresh)
-        _, low_bd = score_asset(low)
-        _, high_bd = score_asset(high)
-
-        # 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。"""
-        scores = []
-        for count in [0, 1, 2, 3, 5, 10, 50]:
-            a = _asset_with_use_count(f"a{count}", count)
-            s, _ = score_asset(a)
-            scores.append(s)
-        # 验证非递增
-        for i in range(len(scores) - 1):
-            assert (
-                scores[i] >= scores[i + 1]
-            ), f"use_count 递增时评分应不增: scores[{i}]={scores[i]} < scores[{i+1}]={scores[i+1]}"
-
-
-# ── smart_select_assets 排序测试 ─────────────────────────────────────────────
-
-
-class TestSmartSelectAssetsOrdering:
-    """验证 smart_select_assets 返回结果按评分降序。"""
-
-    def test_less_used_assets_ranked_higher(self):
-        """使用次数少的素材在结果中排名更高。"""
-        assets = [
-            _asset_with_use_count("heavily_used", 10),
-            _asset_with_use_count("never_used", 0),
-            _asset_with_use_count("lightly_used", 2),
-        ]
-        results = smart_select_assets(assets)
-        ids = [r.asset.id for r in results]
-        # never_used 排第一，heavily_used 排最后
-        assert ids[0] == "never_used"
-        assert ids[-1] == "heavily_used"
-
-    def test_same_quality_different_use_count(self):
-        """质量相同时，使用次数少的排名更高。"""
-        assets = [
-            _asset_with_use_count("used_5", 5),
-            _asset_with_use_count("used_0", 0),
-        ]
-        results = smart_select_assets(assets)
-        assert results[0].asset.id == "used_0"
-        assert results[1].asset.id == "used_5"
-
-
-# ── from-assets 路径集成测试 ─────────────────────────────────────────────────
-
-
-def _make_mock_asset_for_clips(aid, duration, use_count=0):
-    """创建带 score_asset 所需属性的 mock 素材。"""
-    asset = MagicMock()
-    asset.id = aid
-    asset.duration = duration
-    asset.quality_score = None
-    asset.created_at = None
-    asset.metadata = {"generation_use_count": use_count}
-    return asset
-
-
-def _make_auth_user():
-    auth = MagicMock()
-    auth.user.id = "user-001"
-    auth.user.email = "test@example.com"
-    auth.user.display_name = "测试用户"
-    auth.user_id = "user-001"
-    return auth
-
-
-class TestFromAssetsSmartMatchIntegration:
-    """验证 clips.py 中 sorted_candidates 使用 smart_match 评分。"""
-
-    def test_sorted_candidates_prefers_high_score_low_use_count(self):
-        """在 from-assets 路径中，smart_match 分高且使用次数少的素材排在前面。"""
-        from app.api.routes.templates_editor.clips import create_clips_from_assets_editor
-        from app.api.routes.templates_editor.schemas import ClipsFromAssetsRequest
-
-        mock_asset_repo = MagicMock()
-
-        def _get_asset(aid):
-            use_count = {"a_heavy": 10, "a_fresh": 0}[aid]
-            return _make_mock_asset_for_clips(aid, 30.0, use_count)
-
-        mock_asset_repo.get = MagicMock(side_effect=_get_asset)
-
-        mock_plan_svc = MagicMock()
-        mock_plan_svc.replace_all_clips_transactional = MagicMock(return_value=2)
-
-        segments = [(0, 3.0, 5.0), (1, 3.0, 5.0)]
-
-        with (
-            patch(
-                "app.api.routes.templates_editor.clips._get_template_segments",
-                return_value=segments,
-            ),
-            patch(
-                "app.api.routes.templates_editor.clips.get_used_segments",
-                return_value={},
-            ),
-            patch(
-                "app.api.routes.templates_editor.clips.record_used_segments",
-                return_value=None,
-            ),
-        ):
-            body = ClipsFromAssetsRequest(
-                asset_ids=["a_heavy", "a_fresh"],
-                required_clips_count=2,
-            )
-            create_clips_from_assets_editor(
-                template_id="tmpl-1",
-                body=body,
-                background_tasks=MagicMock(),
-                plan_id="test-plan-001",
-                services=(MagicMock(), mock_plan_svc),
-                asset_repo=mock_asset_repo,
-                db=MagicMock(),
-                current_user=_make_auth_user(),
-            )
-
-        # 验证 replace_all_clips_transactional 被调用
-        assert mock_plan_svc.replace_all_clips_transactional.called
-        call_args = mock_plan_svc.replace_all_clips_transactional.call_args
-        clips_data = call_args.args[1]
-
-        # 第一个片段应该分配给 a_fresh（smart_match 分更高）
-        first_clip_asset = clips_data[0]["asset_id"]
-        assert (
-            first_clip_asset == "a_fresh"
-        ), f"第一个片段应分配给 smart_match 分更高的 a_fresh，实际是 {first_clip_asset}"
-
-
-# ── 一键生成路径集成测试 ─────────────────────────────────────────────────────
-
-
-class TestPlanGeneratorSmartMatchIntegration:
-    """验证 PlanGeneratorService._sort_assets_by_smart_score 排序正确。"""
-
-    def test_sort_assets_by_smart_score_descending(self):
-        """_sort_assets_by_smart_score 返回按评分降序排列的素材 ID。"""
-        from app.services.plan_generator_service import PlanGeneratorService
-
-        mock_asset_repo = MagicMock()
-
-        def _get_asset(aid):
-            use_count = {"high_use": 10, "low_use": 0, "mid_use": 3}[aid]
-            asset = MagicMock()
-            asset.id = aid
-            asset.duration = 15.0
-            asset.quality_score = None
-            asset.created_at = None
-            asset.metadata = {"generation_use_count": use_count}
-            return asset
-
-        mock_asset_repo.get = MagicMock(side_effect=_get_asset)
-
-        db = MagicMock()
-        svc = PlanGeneratorService(db, asset_repo=mock_asset_repo)
-
-        sorted_ids = svc._sort_assets_by_smart_score(["high_use", "low_use", "mid_use"])
-
-        # low_use (0次) 应排第一，high_use (10次) 应排最后
-        assert sorted_ids[0] == "low_use"
-        assert sorted_ids[-1] == "high_use"
-        assert sorted_ids[1] == "mid_use"
-
-    def test_distribute_assets_uses_smart_score_ordering(self):
-        """_distribute_assets 在非随机模式下按 smart_match 评分排序素材。"""
-        from app.services.plan_generator_service import PlanGeneratorService
-
-        from packages.domain.edit_plan_clip import EditPlanClip
-        from packages.domain.editing_mode import EditingMode
-
-        mock_asset_repo = MagicMock()
-
-        def _get_asset(aid):
-            use_count = {"old_asset": 10, "new_asset": 0}[aid]
-            asset = MagicMock()
-            asset.id = aid
-            asset.duration = 30.0
-            asset.quality_score = None
-            asset.created_at = None
-            asset.metadata = {"generation_use_count": use_count}
-            return asset
-
-        mock_asset_repo.get = MagicMock(side_effect=_get_asset)
-
-        db = MagicMock()
-        svc = PlanGeneratorService(db, asset_repo=mock_asset_repo)
-
-        # 创建 2 个 main clips（需要提供 id 参数）
-        clips = [
-            EditPlanClip(id="c1", plan_id="p1", clip_type="main", duration=5.0, order=0),
-            EditPlanClip(id="c2", plan_id="p1", clip_type="main", duration=5.0, order=1),
-        ]
-
-        with patch("app.services.plan_generator_service.distribute_assets") as mock_dist:
-            svc._distribute_assets(
-                clips,
-                ["old_asset", "new_asset"],
-                EditingMode.ONE_TAKE.value,
-                random_selection=False,
-            )
-            # 验证传给 distribute_assets 的 asset_ids 按 smart_match 排序
-            call_args = mock_dist.call_args
-            passed_ids = call_args.args[1]
-            # new_asset (0次使用) 应排在 old_asset (10次使用) 前面
-            assert passed_ids[0] == "new_asset"
-            assert passed_ids[1] == "old_asset"
-
-    def test_random_selection_skips_smart_score_sort(self):
-        """random_selection=True 时不执行 smart_match 排序。"""
-        from app.services.plan_generator_service import PlanGeneratorService
-
-        from packages.domain.edit_plan_clip import EditPlanClip
-        from packages.domain.editing_mode import EditingMode
-
-        mock_asset_repo = MagicMock()
-        db = MagicMock()
-        svc = PlanGeneratorService(db, asset_repo=mock_asset_repo)
-
-        clips = [
-            EditPlanClip(id="c1", plan_id="p1", clip_type="main", duration=5.0, order=0),
-        ]
-
-        with patch("app.services.plan_generator_service.distribute_assets") as mock_dist:
-            svc._distribute_assets(
-                clips,
-                ["a1", "a2"],
-                EditingMode.ONE_TAKE.value,
-                random_selection=True,
-            )
-            # random_selection=True 时不应调用 asset_repo.get（不执行排序）
-            mock_asset_repo.get.assert_not_called()