fix(title): 预设卡片间距调整-1px+列宽52px自适应

perf(deploy): 健康检查轮询间隔从 5s 降至 3s
- 更快检测到服务就绪状态 - 减少约 10-20s 的等待时间
2026-09-01 21:15:38 +08:00 · 2026-09-01 20:49:55 +08:00 · 2026-09-01 20:49:54 +08:00 · 2026-09-01 20:49:54 +08:00 · 2026-09-01 20:40:35 +08:00 · 2026-09-01 20:37:25 +08:00
31 changed files with 1476 additions and 233 deletions
@@ -23,6 +23,10 @@ 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,
@@ -44,6 +48,7 @@ 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
@@ -582,6 +587,47 @@ 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,
@@ -626,10 +672,14 @@ 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），
@@ -662,19 +712,46 @@ 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
+
    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

-        # 轮询分配素材：跳过时长缺失、复用占比已超 15% 阈值的素材；
+        # 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；
        # 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），
-        # 继续轮询下一个素材
+        # 继续尝试下一个素材
        asset_id = ""
        clip_duration = 0.0
        start_time: float | None = None
-        n_assets = len(asset_ids)
-        for offset in range(n_assets):
-            candidate = asset_ids[(i + offset) % n_assets]
+        # 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:
            candidate_total = asset_durations.get(candidate, 0.0)
            if candidate_total <= 0:
                continue
@@ -690,7 +767,7 @@ 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 15% 则拒绝并返回 None）
+            # 预判复用后占比超 10% 则拒绝并返回 None）
            candidate_start = _calc_random_start_time(
                candidate,
                candidate_duration,
@@ -712,6 +789,7 @@ 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",
@@ -754,11 +832,31 @@ def create_clips_from_assets_editor(
        unique_asset_ids,
    )

-    # 6. 立即返回响应
+    # 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
    return ClipsFromAssetsResponse(
        created_count=created_count,
        plan_id=plan_id,
        clip_ids=[],
+        duplicate_warning=duplicate_warning,
+        exhaustion_warning=exhaustion_warning,
    )


@@ -189,6 +189,8 @@ 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 = 15%），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 = 10%），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 = 3
+MAX_RANGE_USE_COUNT = 2
 """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 = 0.15
-"""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%）。
+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%）。
 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 = 0.3
+SEGMENT_EDGE_GAP = 1.5
 """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（15% 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（10% 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 15%。
+        ratio_limit: 单条成片复用时长占比上限，默认 10%。

    Returns:
        回调函数 ``(asset_id, clip_duration) -> (start, end) | None``。
@@ -32,6 +32,7 @@ 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__)
@@ -218,8 +219,13 @@ class PlanGeneratorService:
    ) -> None:
        """按 editing_mode 将素材分配到 clips（就地修改，未持久化）.

-        委托给 plan_generator_utils.distribute_assets 纯函数。
+        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。
        """
+        # 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,
@@ -228,6 +234,23 @@ 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.

@@ -1848,10 +1848,9 @@
    },
    "node_modules/@testing-library/dom": {
      "version": "10.4.1",
-      "resolved": "https://registry.npmmirror.com/@testing-library/dom/-/dom-10.4.1.tgz",
+      "resolved": "https://registry.npmjs.org/@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",
@@ -1938,10 +1937,9 @@
    },
    "node_modules/@types/aria-query": {
      "version": "5.0.4",
-      "resolved": "https://registry.npmmirror.com/@types/aria-query/-/aria-query-5.0.4.tgz",
+      "resolved": "https://registry.npmjs.org/@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": {
@@ -3113,10 +3111,9 @@
    },
    "node_modules/dom-accessibility-api": {
      "version": "0.5.16",
-      "resolved": "https://registry.npmmirror.com/dom-accessibility-api/-/dom-accessibility-api-0.5.16.tgz",
+      "resolved": "https://registry.npmjs.org/dom-accessibility-api/-/dom-accessibility-api-0.5.16.tgz",
      "integrity": "sha512-X7BJ2yElsnOJ30pZF4uIIDfBEVgF4XEBxL9Bxhy6dnrm5hkzqmsWHGTiHqRiITNhMyFLyAiWndIJP7Z1NTteDg==",
      "dev": true,
-      "license": "MIT",
      "peer": true
    },
    "node_modules/dunder-proto": {
@@ -4457,10 +4454,9 @@
    },
    "node_modules/lz-string": {
      "version": "1.5.0",
-      "resolved": "https://registry.npmmirror.com/lz-string/-/lz-string-1.5.0.tgz",
+      "resolved": "https://registry.npmjs.org/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"
@@ -5008,10 +5004,9 @@
    },
    "node_modules/pretty-format": {
      "version": "27.5.1",
-      "resolved": "https://registry.npmmirror.com/pretty-format/-/pretty-format-27.5.1.tgz",
+      "resolved": "https://registry.npmjs.org/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",
@@ -5024,10 +5019,9 @@
    },
    "node_modules/pretty-format/node_modules/ansi-styles": {
      "version": "5.2.0",
-      "resolved": "https://registry.npmmirror.com/ansi-styles/-/ansi-styles-5.2.0.tgz",
+      "resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-5.2.0.tgz",
      "integrity": "sha512-Cxwpt2SfTzTtXcfOlzGEee8O+c+MmUgGrNiBcXnuWxuFJHe6a5Hz7qwhwe5OgaSYI0IJvkLqWX1ASG+cJOkEiA==",
      "dev": true,
-      "license": "MIT",
      "peer": true,
      "engines": {
        "node": ">=10"
@@ -5735,10 +5729,9 @@
    },
    "node_modules/react-is": {
      "version": "17.0.2",
-      "resolved": "https://registry.npmmirror.com/react-is/-/react-is-17.0.2.tgz",
+      "resolved": "https://registry.npmjs.org/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": {
@@ -71,4 +71,5 @@ export interface VideoItem {
  generation_params: Record<string, unknown>
  download_url: string
  generated_at: string
+  duplicate_rate?: number
 }
@@ -29,7 +29,6 @@ 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,
-    // 后端 /videos 接口暂无 duplicate_rate 字段
-    duplicate_rate: undefined,
+    duplicate_rate: video.duplicate_rate,
  }
 }
@@ -141,6 +141,7 @@ 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
@@ -152,32 +153,45 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
    },
    [onTitlePositionChange],
  )
-  const handleTitlePointerMove = useCallback(
-    (e: React.PointerEvent<HTMLDivElement>) => {
-      if (!draggingTitleRef.current || !onTitlePositionChange || !playerContainerRef.current) return
-      e.preventDefault()
-      e.stopPropagation()
+  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 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)
+      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 */
+      }
    },
    [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)
@@ -594,6 +608,7 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
                        ? { top: "50%", transform: "translateY(-50%)" }
                        : { bottom: `${titleBottomPct}%` }),
                  }),
+              pointerEvents: "auto",
              cursor: onTitlePositionChange ? "grab" : "default",
              touchAction: "none",
              userSelect: "none",
@@ -601,6 +616,7 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
              padding: "8px 12px",
              boxShadow: "inset 0 0 0 16px transparent",
            }}
+            ref={titleDragRef}
            onPointerDown={handleTitlePointerDown}
            onPointerMove={handleTitlePointerMove}
            onPointerUp={handleTitlePointerUp}
@@ -1,5 +1,7 @@
 /**
 * 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"
@@ -7,7 +9,10 @@ import { getFontFamily } from "../../constants"
 interface TitlePresetItem {
  key: string
  label: string
-  previewStyle: React.CSSProperties
+  previewStyle: React.CSSProperties & {
+    _strokeColor?: string
+    _strokeWidth?: number
+  }
 }

 interface TitlePresetsGridProps {
@@ -17,6 +22,32 @@ 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 ${color}`)
+  return parts.join(", ")
+}
+
 const TitlePresetsGrid: React.FC<TitlePresetsGridProps> = ({
  presets,
  activePreset,
@@ -27,18 +58,52 @@ const TitlePresetsGrid: React.FC<TitlePresetsGridProps> = ({
    <div className="xx-title-presets-grid">
      {presets.map((p) => {
        const isActive = activePreset === p.key
+        const { _strokeColor, _strokeWidth, ...fillStyle } = p.previewStyle
+        const ff = getFontFamily(fontFamily || "思源黑体")
+
+        // 底层：描边轮廓（用 text-shadow 模拟粗描边）
+        const strokeStyle: React.CSSProperties = {
+          color: _strokeColor || "transparent",
+          textShadow:
+            _strokeColor && _strokeWidth
+              ? buildStrokeShadow(_strokeColor, _strokeWidth)
+              : undefined,
+          fontWeight: fillStyle.fontWeight,
+          fontSize: fillStyle.fontSize,
+          lineHeight: 1,
+        }
+
+        // 上层：仅填充色 + 可选 textShadow（发光/投影效果）
+        const topStyle: React.CSSProperties = {
+          color: fillStyle.color,
+          textShadow: fillStyle.textShadow,
+          fontWeight: fillStyle.fontWeight,
+          fontSize: fillStyle.fontSize,
+          lineHeight: 1,
+        }
+
        return (
          <button
            key={p.key}
            className={`xx-title-preset-card${isActive ? " active" : ""}`}
            onClick={() => onApply(p.key)}
-            title={p.label}
          >
-            <span
-              className="xx-title-preset-preview-text"
-              style={{ ...p.previewStyle, fontFamily: getFontFamily(fontFamily || "思源黑体") }}
-            >
-              T
+            <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>
          </button>
        )
@@ -78,10 +78,11 @@ export const TITLE_PRESETS = [
    label: "经典白字",
    style: { size: 28, color: "#ffffff", bold: true, italic: false, stroke: true, shadow: false },
    previewStyle: {
-      fontWeight: 700,
      color: "#ffffff",
-      WebkitTextStroke: "1px #000000",
-      fontSize: "20px",
+      _strokeColor: "#000000",
+      _strokeWidth: 2,
+      fontWeight: 700,
+      fontSize: "32px",
    },
  },
  {
@@ -89,45 +90,54 @@ export const TITLE_PRESETS = [
    label: "黑金质感",
    style: { size: 32, color: "#d4a843", bold: true, italic: false, stroke: false, shadow: true },
    previewStyle: {
-      fontWeight: 700,
      color: "#d4a843",
+      fontWeight: 700,
+      fontSize: "32px",
      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: { fontWeight: 400, color: "#333333", fontSize: "18px" },
+    previewStyle: {
+      color: "#e8e8e8",
+      fontWeight: 400,
+      fontSize: "32px",
+    },
  },
  {
    key: "variety_show",
    label: "综艺花字",
    style: { size: 36, color: "#ff4081", bold: true, italic: false, stroke: true, shadow: true },
    previewStyle: {
-      fontWeight: 900,
      color: "#ff4081",
-      WebkitTextStroke: "1.5px #ffffff",
+      _strokeColor: "#ffffff",
+      _strokeWidth: 2,
+      fontWeight: 900,
+      fontSize: "32px",
      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: { fontWeight: 400, color: "#1a1a1a", fontSize: "17px" },
+    previewStyle: {
+      color: "#e0e0e0",
+      fontWeight: 400,
+      fontSize: "32px",
+    },
  },
  {
    key: "retro_film",
    label: "复古胶片",
    style: { size: 28, color: "#e8d5b7", bold: false, italic: false, stroke: false, shadow: true },
    previewStyle: {
-      fontWeight: 400,
      color: "#e8d5b7",
+      fontWeight: 400,
+      fontSize: "32px",
      textShadow: "2px 2px 6px rgba(0,0,0,0.7)",
-      fontSize: "18px",
    },
  },
  {
@@ -135,10 +145,10 @@ export const TITLE_PRESETS = [
    label: "霓虹发光",
    style: { size: 32, color: "#00e5ff", bold: true, italic: false, stroke: false, shadow: true },
    previewStyle: {
-      fontWeight: 700,
      color: "#00e5ff",
+      fontWeight: 700,
+      fontSize: "32px",
      textShadow: "0 0 4px #00e5ff, 0 0 8px #00e5ff, 0 0 16px rgba(0,229,255,0.5)",
-      fontSize: "20px",
    },
  },
  {
@@ -146,10 +156,202 @@ 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,
-      color: "#333333",
+      fontSize: "32px",
      textShadow: "1px 1px 2px rgba(0,0,0,0.3)",
-      fontSize: "20px",
+    },
+  },
+  {
+    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)",
    },
  },
 ]
@@ -1733,36 +1733,36 @@
 /* 标题预设卡片网格 */
 .xx-title-presets-grid {
  display: grid;
-  grid-template-columns: repeat(6, 1fr);
-  gap: 8px;
+  grid-template-columns: repeat(6, 52px);
+  gap: 1px;
 }

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

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

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

 .xx-title-preset-preview-text {
+  font-size: 32px;
  line-height: 1;
  user-select: none;
 }
@@ -20,13 +20,14 @@ const SECONDS_PER_ASSET = 15
 /**
 * 根据模板 segments 计算所需素材数量上限。
 * 取每个 segment 的 duration_min 之和作为目标视频总时长，
- * 再按 15 秒/素材估算需要多少个素材；结果钳制到 [1, 200] 区间（后端 limit 上限 200）。
+ * 再按 15 秒/素材估算需要多少个素材，且保证不少于片段数（每个片段至少 1 个素材）；
+ * 结果钳制到 [1, 200] 区间（后端 limit 上限 200）。
 */
 function computeLimitFromSegments(segments?: TemplateSegment[]): number {
  if (!segments || segments.length === 0) return DEFAULT_LIMIT
  const totalSeconds = segments.reduce((sum, seg) => sum + (seg.duration_min || 0), 0)
  if (totalSeconds <= 0) return DEFAULT_LIMIT
-  const limit = Math.ceil(totalSeconds / SECONDS_PER_ASSET)
+  const limit = Math.max(segments.length, Math.ceil(totalSeconds / SECONDS_PER_ASSET))
  return Math.max(1, Math.min(limit, 200))
 }

@@ -91,8 +91,6 @@
  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;
@@ -137,7 +135,7 @@
   ============================================================ */
 .xx-products-grid {
  display: grid;
-  grid-template-columns: repeat(4, 1fr);
+  grid-template-columns: repeat(auto-fill, minmax(220px, 1fr));
  gap: var(--space-md);
 }

@@ -187,8 +185,6 @@
  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;
@@ -262,11 +258,8 @@
 .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 {
@@ -289,22 +282,28 @@
 }

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

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

 /* 时长标签 */
@@ -324,7 +323,7 @@

 /* 卡片信息区 */
 .xx-product-info {
-  padding: 14px;
+  padding: 8px 10px;
  display: flex;
  flex-direction: column;
  gap: var(--space-sm);
@@ -506,8 +505,6 @@
  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;
 }

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

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

-        遍历项目内所有其他有指纹的视频，对每个计算相似度：
+        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：
        - 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）。
@@ -325,23 +328,34 @@ class VideoDeduplicator:

        Args:
            fingerprint: 当前视频的指纹
-            project_id: 项目 ID
+            project_id: 项目 ID（user_id 为空时的回退范围）
            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 100 个视频，避免大项目内存溢出
+        # 限制查询最近 200 个视频，避免大库内存溢出
        from packages.adapters.sqlalchemy_impl.models import GeneratedVideoModel

-        recent_models = (
-            session.query(GeneratedVideoModel)
-            .filter(GeneratedVideoModel.project_id == project_id)
-            .order_by(GeneratedVideoModel.generated_at.desc())
-            .limit(100)
-            .all()
-        )
+        # 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()
        video_repo = SQLAlchemyGeneratedVideoRepository(session)
        existing_videos = [video_repo._to_domain(m) for m in recent_models]

@@ -123,7 +123,13 @@ 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)
+            dup_rate = deduplicator.compute_duplicate_rate(
+                fingerprint,
+                project_id,
+                video_id,
+                session,
+                user_id=user_id,
+            )
            generated_video.duplicate_rate = dup_rate
            logger.info("Duplicate rate for %s: %.2f%%", video_id, dup_rate)
        except Exception as rate_err:
@@ -200,6 +200,22 @@ 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)
@@ -1422,6 +1438,7 @@ 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}"
@@ -1429,6 +1446,19 @@ 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,
@@ -1439,7 +1469,7 @@ 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=getattr(clip, "playback_speed", 1.0) or 1.0,
+                        playback_speed=seg_speed,
                        config={**clip_config, "_segment_id": seg.segment_id},
                        actual_duration=actual_duration,
                        trim_config=seg.trim,
@@ -1461,6 +1491,7 @@ 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)
@@ -1474,6 +1505,25 @@ 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,
@@ -1484,13 +1534,25 @@ 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=getattr(clip, "playback_speed", 1.0) or 1.0,
+                playback_speed=final_speed,
                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
@@ -1683,7 +1745,7 @@ class UnifiedRenderService:
                        if d > 0:
                            layer_dur = d
                            break
-                    xfade_filter, _ = self._transition_engine.build_xfade_chain(
+                    xfade_filter, xfade_estimated_dur = self._transition_engine.build_xfade_chain(
                        clip_durations=layer_durations,
                        clip_video_labels=layer_labels,
                        transitions=layer_transitions,
@@ -1692,6 +1754,13 @@ 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
@@ -1915,8 +1984,14 @@ 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 ──────────────────────────────────────────────────
@@ -150,8 +150,11 @@ def build_xfade_filter_chain(
        else:
            first_input_dur = cumulative - total_transition

-        # 原始 offset 计算
-        offset = max(0.0, cumulative - transition_duration * i)
+        # 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)

        # 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)
@@ -4,6 +4,7 @@
 # - 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

@@ -34,3 +35,26 @@ 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
+
@@ -1,77 +1,136 @@
 #!/bin/bash
 # CI Unit Tests Job 主脚本
-# 包含：依赖安装、增量测试选择、覆盖率测试、diff覆盖率门禁
+# 包含：依赖缓存、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 ---
-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..."
-  [ $i -eq 3 ] && exit 1
-  sleep 5
-done
+if [ "$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
 pytest --version

 # 双保险：确保numpy已安装
 echo "=== 验证 numpy 安装 ==="
 SKIP_NUMPY_TESTS=0
-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
+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
+    }
  }
-}
+fi
 if [ "$SKIP_NUMPY_TESTS" = "0" ]; then
-  python3 -c "import numpy; print(f'✅ numpy {numpy.__version__} 安装成功')" || {
+  python3 -c "import numpy; print(f'✅ numpy {numpy.__version__} 就绪')" || {
    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（仅PR） ---
+# --- 增量测试选择（PR + push 均支持） ---
 UNIT_TEST_MODE="full"
 SELECTED_TEST_FILES="tests/unit"

-if [ "${GITHUB_EVENT_NAME:-}" = "pull_request" ] && [ -n "${GITHUB_TOKEN:-}" ]; then
+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
  echo ""
  echo "=== 增量测试选择 ==="
-  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']")
+
+  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
+
  echo "改动文件数: $(echo "$CHANGED_FILES" | grep -c . || echo 0)"
-  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: $(cat /tmp/selected_tests.txt | wc -l) 个测试文件"
+
+  if [ -n "$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
  else
-    echo "全量模式"
+    echo "无法获取改动文件列表，使用全量模式"
  fi
 fi

@@ -116,7 +175,7 @@ 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 300 xiaoxia-worker-staging 2>/dev/null || true
+docker stop -t 120 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 5
+        sleep 3
    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 [0,2.3]，[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
+        # [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
        info = compute_asset_availability(
            _make_asset(
                duration=10.0,
                ranges=[
                    _range(0.0, 2.0, use_count=MAX_RANGE_USE_COUNT),
-                    _range(6.0, 10.0, use_count=MAX_RANGE_USE_COUNT),
+                    _range(9.0, 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 0.3s（与 MediaKit 冲突检测同口径）。"""
-        assert SEGMENT_EDGE_GAP == 0.3
+        """边缘间隙常量为 1.5s（与 MediaKit 冲突检测同口径）。"""
+        assert SEGMENT_EDGE_GAP == 1.5

    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 == 3
-    assert REUSE_RATIO_LIMIT == 0.15
-    assert SEGMENT_EDGE_GAP == 0.3
+    assert MAX_RANGE_USE_COUNT == 2
+    assert REUSE_RATIO_LIMIT == 0.10
+    assert SEGMENT_EDGE_GAP == 1.5


 # ── 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（3）的区间不再参与复用；全部达上限返回 None。"""
+    """use_count 达到上限（2）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": 3, "last_used_at": "2026-01-01T00:00:00"},
+                    {"start": 0.0, "end": 10.0, "use_count": 2, "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_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。"""
+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。"""
    models = {
        "a1": FakeModel(
            "a1",
            {
                "used_time_ranges": [
-                    {"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"},
+                    {"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"},
                ]
            },
        )
    }
    db = _db(models)
    result = find_reusable_range(db, "a1", 5.0, 30.0)
-    # 只能选 use_count=2 的区间（start=0），不能选 use_count=3 的（虽然它更老）
+    # 只能选 use_count=1 的区间（start=0），不能选 use_count=2 的（虽然它更老）
    assert result is not None and result[0] == 0.0


@@ -0,0 +1,152 @@
+"""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
@@ -56,9 +56,10 @@ class TestComputeDuplicateRate:

        with patch("video_processing.dedup.SQLAlchemyGeneratedVideoRepository") as MockRepo:
            mock_repo = MockRepo.return_value
-            session.query.return_value.filter.return_value.order_by.return_value.limit.return_value.all.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)

        assert rate == 0.0
@@ -73,7 +74,6 @@ 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
@@ -83,10 +83,12 @@ class TestComputeDuplicateRate:
        with patch("video_processing.dedup.SQLAlchemyGeneratedVideoRepository") as MockRepo:
            mock_repo = MockRepo.return_value
            mock_repo._to_domain.return_value = existing
-            # Mock the session.query chain
-            session.query.return_value.filter.return_value.order_by.return_value.limit.return_value.all.return_value = [
-                mock_model
-            ]
+            # 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
            rate = deduplicator.compute_duplicate_rate(fingerprint, "proj1", "vid1", session)

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

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

        assert rate == 0.0
@@ -172,15 +176,89 @@ class TestComputeDuplicateRate:
        with patch("video_processing.dedup.SQLAlchemyGeneratedVideoRepository") as MockRepo:
            mock_repo = MockRepo.return_value
            mock_repo._to_domain.side_effect = [existing1, existing2]
-            session.query.return_value.filter.return_value.order_by.return_value.limit.return_value.all.return_value = [
+            query_mock = MagicMock()
+            query_mock.filter.return_value = query_mock
+            query_mock.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."""
@@ -0,0 +1,97 @@
+"""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
@@ -58,6 +58,10 @@ 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


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

-        # 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"
+        # 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

    @patch("app.api.routes.templates_editor.clips.get_storage_service")
    def test_orders_start_at_zero(self, mock_storage):
@@ -631,7 +636,8 @@ 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%
-        assert reused.get("a1", 0.0) == 5.0
+        # 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

    @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]）：0.3s 扩边内 → 冲突。"""
+        """首尾紧贴（推荐 15 开始，已用 [10,15]）：1.5s 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（< 0.3s 边缘间隙）→ 冲突。"""
+        """间隔 0.2s（< 1.5s 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 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
+        """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

    def test_far_apart_no_conflict(self):
        """相隔很远 → 不冲突。"""
@@ -54,7 +54,9 @@ 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(6.0, 2.0, used) is False
+        assert (
+            _recommended_time_conflicts(6.5, 2.0, used) is False
+        )  # range [6.5,8.5], just outside all expanded used ranges

    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）。"""
@@ -64,5 +66,5 @@ 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 0.3s（配置常量）。"""
-        assert SEGMENT_EDGE_GAP == 0.3
+        """默认边缘间隙常量为 1.5s（配置常量）。"""
+        assert SEGMENT_EDGE_GAP == 1.5
@@ -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 0.3s 边缘间隙扩边，推荐 [10, 15] 与已用 [0, 10] 首尾相接
+        # 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
        # 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（0.5 > 0.3）→ 不冲突
-        assert _recommended_time_conflicts(10.5, 5.0, [(0.0, 10.0)]) 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

    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：0.3s 扩边内 → 冲突
+        # 推荐 [15, 20] 与 [10, 15] 首尾相接：1.5s 扩边内 → 冲突
        assert _recommended_time_conflicts(15.0, 5.0, used) is True
-        # 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
+        # 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


 # ── _get_mediakit_recommendations 单元测试 ──────────────────────────────────
@@ -347,6 +347,10 @@ 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


@@ -445,8 +449,8 @@ class TestFromAssetsByTemplateSegments:
        assert 3.0 <= clips_data[0]["duration"] <= 5.0
        assert 4.0 <= clips_data[1]["duration"] <= 8.0

-    def test_assets_round_robin_assignment(self):
-        """素材按片段顺序轮询分配。"""
+    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。"""
        from app.api.routes.templates_editor.clips import create_clips_from_assets_editor
        from app.api.routes.templates_editor.schemas import ClipsFromAssetsRequest

@@ -475,7 +479,11 @@ class TestFromAssetsByTemplateSegments:

        clips_data = _get_clips_data(mock_plan_svc)
        asset_ids = [c["asset_id"] for c in clips_data]
-        assert asset_ids == ["a1", "a2", "a1", "a2"]
+        # 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

    def test_orders_start_from_zero(self):
        """片段 order 从 0 开始递增。"""
@@ -908,6 +908,10 @@ 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)
@@ -0,0 +1,324 @@
+"""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()