feat: 素材选取评分注入随机噪声，降低成片查重率 (#1620)

Co-authored-by: xiaoxia <dev@xiaoxiajianji.com>
Co-committed-by: xiaoxia <dev@xiaoxiajianji.com>

.gitea/workflows/ci-base-image.yml

@@ -0,0 +1,105 @@
+name: CI Base Image Build
+
+on:
+  push:
+    branches:
+      - develop
+      - main
+    paths:
+      - 'requirements-base.txt'
+      - 'requirements-dev.txt'
+      - 'infra/docker/ci.Dockerfile'
+  workflow_dispatch:
+    inputs:
+      reason:
+        description: "触发原因"
+        required: false
+        default: "手动触发 - ci-base 镜像重建"
+
+concurrency:
+  group: ci-base-image-build
+  cancel-in-progress: false
+
+jobs:
+  build-ci-base:
+    name: Build CI Base Image
+    runs-on: runtime-builder
+    timeout-minutes: 60
+    steps:
+    - name: Checkout code
+      shell: sh
+      env:
+        GITHUB_TOKEN: ${{ github.token }}
+      run: |
+        curl -sH "Authorization: token $GITHUB_TOKEN" \
+          "${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/raw/scripts/ci/step_checkout.sh?ref=${GITHUB_SHA}" \
+          | bash
+
+    - name: Docker login to Gitea Registry
+      shell: sh
+      env:
+        GITEA_REGISTRY_USER: xiaoxia
+        GITEA_REGISTRY_TOKEN: ${{ secrets.REGISTRY_TOKEN }}
+      run: |
+        set -eu
+        for i in 1 2 3; do
+          echo "=== Docker login 尝试 $i/3 ==="
+          if docker login git.xiaoxiajianji.com -u "${GITEA_REGISTRY_USER}" -p "${GITEA_REGISTRY_TOKEN}"; then
+            echo "✅ Docker login successful"
+            break
+          fi
+          echo "❌ Docker login 失败（尝试 $i/3），5s 后重试..."
+          sleep 5
+        done
+
+    - name: Build and push CI base image
+      shell: sh
+      run: |
+        set -eu
+        IMAGE="git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas/ci-base"
+        VERSION_TAG="deps-$(date +%Y%m%d-%H%M)-${GITHUB_SHA::8}"
+
+        echo "=== Building CI base image (tags: latest, ${VERSION_TAG}) ==="
+        docker build --progress=plain \
+          -f infra/docker/ci.Dockerfile \
+          -t "${IMAGE}:latest" \
+          -t "${IMAGE}:${VERSION_TAG}" \
+          .
+        echo "✅ Image built successfully"
+
+        echo "=== Pushing ${VERSION_TAG} ==="
+        docker push "${IMAGE}:${VERSION_TAG}"
+        echo "=== Pushing latest ==="
+        docker push "${IMAGE}:latest"
+        echo "✅ Pushed to Gitea Registry"
+
+    - name: Verify image
+      shell: sh
+      run: |
+        set -eu
+        IMAGE="git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas/ci-base:latest"
+        echo "=== Verifying pinned deps in fresh image ==="
+        docker run --rm "${IMAGE}" /opt/xiaoxia-ci-venv/bin/python -c \
+          "import httpcore, h2, numpy, httpx; print('VERSIONS:', httpcore.__version__, h2.__version__, numpy.__version__, httpx.__version__)"
+
+    - name: Notify result
+      if: always()
+      continue-on-error: true
+      shell: sh
+      env:
+        CI_NOTIFY_WEBHOOK: ${{ secrets.CI_NOTIFY_WEBHOOK }}
+      run: |
+        set +e
+        if [ "${{ job.status }}" = "success" ]; then
+          NOTIFY_MODE=success JOB_NAME="CI Base Image Build" python3 scripts/ci_notify.py
+        else
+          NOTIFY_MODE=failure JOB_NAME="CI Base Image Build" python3 scripts/ci_notify.py
+        fi
+
+    - name: Cleanup
+      if: always()
+      shell: sh
+      run: |
+        IMAGE="git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas/ci-base"
+        docker rmi "${IMAGE}:latest" 2>/dev/null || true
+        echo "Cleanup done"

.gitea/workflows/pr-auto-scan.yml

@@ -3,7 +3,7 @@ name: PR Auto Scan
 # 作为短作业模式的兜底，防止事件驱动遗漏
 on:
   schedule:
-    - cron: "*/10 * * * *"  # 每10分钟扫描一次（脚本自带240s墙钟上限，降频减负）
+    - cron: "*/15 * * * *"  # 每10分钟扫描一次（脚本自带240s墙钟上限，降频减负）
   workflow_dispatch:
 
 permissions:

README.md

@@ -263,4 +263,3 @@ pytest --cov=packages --cov-report=html
 ---
 
 **License**: MIT
-<!-- CI trigger: 1788229339 -->

alembic/versions/034_add_confirm_generation_fields.py

@@ -1,60 +0,0 @@
-"""Add confirm generation fields
-
-Revision ID: 034
-Revises: 033
-Create Date: 2026-07-08
-
-确认生成 API 改造：为 generation_tasks 表添加 is_preview、source_task_id、
-output_width、output_height、cover_url、custom_title 字段。
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "034"
-down_revision = "033"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.add_column(
-        "generation_tasks",
-        sa.Column("is_preview", sa.Boolean(), nullable=False, server_default=sa.true()),
-    )
-    op.add_column(
-        "generation_tasks",
-        sa.Column("source_task_id", sa.String(32), nullable=False, server_default=""),
-    )
-    op.add_column(
-        "generation_tasks",
-        sa.Column("output_width", sa.Integer(), nullable=False, server_default=sa.text("1280")),
-    )
-    op.add_column(
-        "generation_tasks",
-        sa.Column("output_height", sa.Integer(), nullable=False, server_default=sa.text("720")),
-    )
-    op.add_column(
-        "generation_tasks",
-        sa.Column("cover_url", sa.String(1000), nullable=False, server_default=""),
-    )
-    op.add_column(
-        "generation_tasks",
-        sa.Column("custom_title", sa.String(500), nullable=False, server_default=""),
-    )
-    op.create_index(
-        op.f("ix_generation_tasks_source_task_id"),
-        "generation_tasks",
-        ["source_task_id"],
-    )
-
-
-def downgrade() -> None:
-    op.drop_index(op.f("ix_generation_tasks_source_task_id"), table_name="generation_tasks")
-    op.drop_column("generation_tasks", "custom_title")
-    op.drop_column("generation_tasks", "cover_url")
-    op.drop_column("generation_tasks", "output_height")
-    op.drop_column("generation_tasks", "output_width")
-    op.drop_column("generation_tasks", "source_task_id")
-    op.drop_column("generation_tasks", "is_preview")

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

@@ -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_RANDOM_NOISE_MAX, 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 +712,52 @@ def create_clips_from_assets_editor(
             return False
         return reused_durations.get(aid, 0.0) / assigned > REUSE_RATIO_LIMIT
 
-    for i, (_seg_order, dur_min, dur_max) in enumerate(segments):
+    # 素材耗尽标志：某轮循环中所有素材均被跳过时为 True
+    all_assets_exhausted = False
+
+    # 计算转场重叠补偿：每个 clip 需要额外增加的时长
+    # 目标：渲染后视频总时长 = 模板设定的各片段时长之和
+    # 公式：每 clip 增加 (n_segments - 1) * td / n_segments
+    n_segments = len(segments)
+    if n_segments > 1:
+        transition_compensation = (n_segments - 1) * _DEFAULT_TRANSITION_DURATION / n_segments
+    else:
+        transition_compensation = 0.0
+
+    # 打乱 segments 的处理顺序（分配素材的顺序随机化），但最终 clips_data 按原始 order 排序
+    shuffled_indices = list(range(len(segments)))
+    random.shuffle(shuffled_indices)
+
+    for idx in shuffled_indices:
+        _seg_order, dur_min, dur_max = segments[idx]
         # 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}
+        # 排序键：smart_match 评分（注入随机噪声）→ 使用次数 → 纯随机。
+        # 噪声让得分接近的素材排名每次浮动，避免同一批素材反复选出相同组合，
+        # 从素材组合层面降低成片查重率；分差 > SCORE_RANDOM_NOISE_MAX 时排名稳定，
+        # 质量差距显著的素材仍保持优先级。
+        sorted_candidates = sorted(
+            asset_ids,
+            key=lambda aid: (
+                -(asset_smart_scores.get(aid, 0.0) + random.uniform(0.0, SCORE_RANDOM_NOISE_MAX)),
+                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 +773,7 @@ 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 +795,7 @@ 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",
@@ -727,7 +811,7 @@ def create_clips_from_assets_editor(
 
         clips_data.append(
             {
-                "order": i,
+                "order": _seg_order,
                 "asset_id": asset_id,
                 "start_time": start_time,
                 "duration": clip_duration,
@@ -735,6 +819,9 @@ def create_clips_from_assets_editor(
             }
         )
 
+    # 按原始 segment order 排序，确保 clips_data 的 order 字段有序（0,1,2,3...）
+    clips_data.sort(key=lambda c: c["order"])
+
     # 4. 事务性替换：清空旧片段 → 创建新片段 → 标记ready（单事务，失败自动回滚）
     created_count = plan_svc.replace_all_clips_transactional(plan_id, clips_data)
 
@@ -754,19 +841,86 @@ 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,
     )
 
 
+def _build_scene_segments(
+    scene_changes: list[float],
+    asset_duration: float,
+) -> list[tuple[float, float]]:
+    """根据场景切换点构建镜头段列表.
+
+    Args:
+        scene_changes: 场景切换点时间戳列表（已排序，首位为 0.0）
+        asset_duration: 素材总时长
+
+    Returns:
+        镜头段列表 [(start, end), ...]
+    """
+    segments: list[tuple[float, float]] = []
+    for i, ts in enumerate(scene_changes):
+        end = scene_changes[i + 1] if i + 1 < len(scene_changes) else asset_duration
+        # 只保留有效长度的镜头段（至少 0.5 秒）
+        if end - ts >= 0.5:
+            segments.append((ts, end))
+    return segments
+
+
+def _pick_start_in_scene_segment(
+    seg_start: float,
+    seg_end: float,
+    clip_duration: float,
+) -> float | None:
+    """在镜头段内随机选取一个起始时间点.
+
+    确保 start + clip_duration <= seg_end。
+    若镜头段长度不足以容纳片段，返回 None。
+    """
+    available = seg_end - seg_start - clip_duration
+    if available < 0:
+        return None
+    max_start = seg_start + available
+    return random.uniform(seg_start, max_start)
+
+
 def _update_mediakit_recommendations_async(  # pragma: no cover
     plan_id: str,
     asset_ids: list[str],
 ) -> None:
-    """后台任务：调用 MediaKit 智能选片并更新片段的起始时间.
+    """后台任务：使用 SceneChange 智能选帧并更新片段的起始时间.
+
+    优先使用 SceneChange 策略检测视频镜头切换点，将每个素材按镜头段拆分，
+    各片段优先从不同镜头段中选取起始时间，实现「不同片段展示不同场景」的效果。
+
+    降级策略：
+    1. SceneChange 优先 → detect_scene_changes 内部已含 TimeInterval 降级
+    2. 若 detect_scene_changes 仍返回 None → 回退到旧的 analyze_videos 方式
+    3. 所有方式都失败 → 保持现有随机 start_time，不影响视频生成
 
     此函数在后台异步执行，不影响接口响应时间。
     失败时静默处理，不影响已创建的片段。
@@ -788,12 +942,6 @@ def _update_mediakit_recommendations_async(  # pragma: no cover
         asset_repo = SQLAlchemyAssetRepository(db)
         plan_svc = EditPlanService(db)
 
-        # 调用 MediaKit 获取推荐时间
-        recommendations = _get_mediakit_recommendations(asset_ids, asset_repo)
-        if not recommendations:
-            logger.info("后台任务: MediaKit 无推荐结果，跳过更新")
-            return
-
         # 查询该 plan 的所有片段（分批获取，避免硬编码 limit 截断）
         batch_size = 500
         all_clips = []
@@ -816,15 +964,16 @@ def _update_mediakit_recommendations_async(  # pragma: no cover
         unique_asset_ids = list({getattr(c, "asset_id", "") or "" for c in clips} - {""})
         assets_map: dict[str, object] = {a.id: a for a in asset_repo.find_by_ids(unique_asset_ids)}
 
-        # 按 asset_id 预分组片段时间段（消除 O(N^2) 嵌套循环）
-        clips_by_asset: dict[str, list[tuple[str, float, float]]] = defaultdict(list)
+        # 按 asset_id 预分组片段对象（按 order 排序，保证按模板顺序分配镜头段）
+        clips_by_asset: dict[str, list] = defaultdict(list)
         for clip in clips:
             aid = getattr(clip, "asset_id", "") or ""
-            if aid and clip.start_time is not None:
-                clips_by_asset[aid].append((clip.id, clip.start_time, clip.start_time + clip.duration))
+            if aid:
+                clips_by_asset[aid].append(clip)
+        for aid in clips_by_asset:
+            clips_by_asset[aid].sort(key=lambda c: c.order)
 
-        # 读取素材全部历史已用区间（跨任务/跨 plan 持久化记录）：
-        # MediaKit 挪点必须与随机选片一样避让历史区间，否则会把片段挪回已用过的画面
+        # 读取素材全部历史已用区间（跨任务/跨 plan 持久化记录）
         historical_segments = get_used_segments(db, unique_asset_ids)
 
         # 已更新的片段ID（用于排除已移动的旧时间段）
@@ -833,16 +982,22 @@ def _update_mediakit_recommendations_async(  # pragma: no cover
         updated_segments: dict[str, list[tuple[float, float]]] = {}
         updated_count = 0
 
-        # 遍历片段，按 asset_id 匹配推荐时间
-        for clip in clips:
-            asset_id = getattr(clip, "asset_id", "") or ""
-            if not asset_id or asset_id not in recommendations:
+        # 尝试获取存储服务（用于生成视频 URL）
+        try:
+            storage = get_storage_service()
+        except Exception:
+            logger.warning("后台任务: 获取存储服务失败，跳过 SceneChange 更新")
+            return
+
+        # 获取 MediaKit 客户端
+        client = get_mediakit_client()
+
+        # 对每个素材，检测场景切换点并分配镜头段
+        for asset_id in unique_asset_ids:
+            asset_clips = clips_by_asset.get(asset_id, [])
+            if not asset_clips:
                 continue
 
-            recommended_start = recommendations[asset_id]
-            clip_duration = clip.duration
-
-            # 从预加载字典获取素材（O(1) 查找）
             asset = assets_map.get(asset_id)
             if not asset:
                 continue
@@ -850,89 +1005,147 @@ def _update_mediakit_recommendations_async(  # pragma: no cover
             if asset_total <= 0:
                 continue
 
-            # 推荐时间 + 片段时长不能超过素材总时长
-            if recommended_start + clip_duration > asset_total:
-                logger.info(
-                    "后台任务: 推荐时间越界，跳过: asset_id=%s recommended=%.2f duration=%.1f total=%.1f",
-                    asset_id,
-                    recommended_start,
-                    clip_duration,
-                    asset_total,
-                )
-                continue
-
-            # 构建排除当前片段及已更新片段后的占用列表（O(M)，M=同素材片段数）
-            other_segments: list[tuple[float, float]] = [
-                (cs, ce)
-                for cid, cs, ce in clips_by_asset.get(asset_id, [])
-                if cid != clip.id and cid not in updated_clip_ids
-            ]
-            other_segments.extend(updated_segments.get(asset_id, []))
-
-            # 并入该素材全部历史已用区间（含其他 plan/其他任务），set 去重：
-            # 本 plan 片段创建时已写入历史记录
-            # 并入该素材全部历史已用区间（含其他 plan/其他任务）。
-            # set 去重前先归一化精度（round 3 位），避免浮点尾差导致逻辑相同的
-            # 区间（如 1.0 与 1.0000000001）被误判为不同区间
-            def _norm(segs):
-                return {(round(float(a), 3), round(float(b), 3)) for a, b in segs}
-
-            other_segments = list(_norm(other_segments) | _norm(historical_segments.get(asset_id, [])))
-
-            # 检查推荐时间是否与同 plan 片段或历史已用区间冲突（含 0.3s 边缘间隙）：
-            # 冲突时放弃该推荐、保留原随机起点（不硬挪到已用过的画面）
-            if _recommended_time_conflicts(recommended_start, clip_duration, other_segments):
-                logger.info(
-                    "后台任务: 推荐时间与同片/历史区间冲突，保留原起点: asset_id=%s recommended=%.2f",
-                    asset_id,
-                    recommended_start,
-                )
-                continue
-
-            # 逐个更新并捕获异常（单点失败不影响其他片段）
-            try:
-                old_start = clip.start_time
-                old_end = old_start + clip_duration
-                # MediaKit 移动片段起点 + 同步素材 metadata 区间记录放在同一事务：
-                # 删旧区间记录（按 plan_id + 旧 start 匹配，兼容无 plan_id 的旧数据）、
-                # 写新区间，最后统一 commit；任一步失败整体 rollback，
-                # 保证 clip.start_time 与 metadata.used_time_ranges 不出现不一致。
-                plan_svc.update_clip(clip.id, start_time=recommended_start)
+            # 获取素材视频 URL
+            video_url: str | None = None
+            storage_key = getattr(asset, "storage_key", None) or ""
+            mime = getattr(asset, "mime_type", "") or ""
+            if storage_key and mime.startswith("video/"):
                 try:
-                    if remove_used_segment(db, asset_id, old_start, old_end, plan_id=plan_id):
-                        record_used_segments(
-                            db,
-                            asset_id,
-                            recommended_start,
-                            recommended_start + clip_duration,
-                            plan_id,
-                        )
-                except Exception as me:
-                    logger.warning(
-                        "后台任务: 同步素材区间记录失败，回滚本次片段更新: clip_id=%s error=%s",
-                        clip.id,
-                        me,
+                    video_url = storage.get_download_url(storage_key)
+                except Exception as e:
+                    logger.warning("后台任务: 获取素材URL失败: asset_id=%s error=%s", asset_id, e)
+
+            # 构建该素材的占用区间列表（排除已更新片段）
+            def _get_other_segments(asset_id_inner, clip_id_inner):
+                segs: list[tuple[float, float]] = []
+                for c in clips_by_asset.get(asset_id_inner, []):
+                    cid = c.id
+                    if cid != clip_id_inner and cid not in updated_clip_ids:
+                        segs.append((c.start_time, c.start_time + c.duration))
+                segs.extend(updated_segments.get(asset_id_inner, []))
+
+                # 并入历史已用区间
+                def _norm(segs_in):
+                    return {(round(float(a), 3), round(float(b), 3)) for a, b in segs_in}
+
+                return list(_norm(segs) | _norm(historical_segments.get(asset_id_inner, [])))
+
+            # 优先使用 SceneChange 策略
+            scene_segments: list[tuple[float, float]] = []
+            if client.is_available and video_url:
+                scene_changes = client.detect_scene_changes(video_url)
+                if scene_changes is not None:
+                    scene_segments = _build_scene_segments(scene_changes, asset_total)
+                    logger.info(
+                        "后台任务: 素材场景检测完成: asset_id=%s scenes=%d",
+                        asset_id,
+                        len(scene_segments),
                     )
-                    db.rollback()
-                    continue
-                db.commit()
-                updated_count += 1
-                updated_clip_ids.add(clip.id)
-            except Exception as ue:
-                logger.warning("后台任务: 单个片段更新失败: clip_id=%s error=%s", clip.id, ue)
-                try:
-                    db.rollback()
-                except Exception:
-                    pass
+
+            # SceneChange 未获得有效结果 → 尝试 analyze_videos 作为 fallback
+            if not scene_segments and video_url:
+                fallback_recs = _get_mediakit_recommendations([asset_id], asset_repo)
+                if fallback_recs and asset_id in fallback_recs:
+                    # analyze_videos 只返回单个推荐点，转为单镜头段
+                    rec_start = fallback_recs[asset_id]
+                    scene_segments = [(rec_start, asset_total)]
+                    logger.info(
+                        "后台任务: 使用 analyze_videos fallback: asset_id=%s start=%.2f",
+                        asset_id,
+                        rec_start,
+                    )
+
+            if not scene_segments:
+                # 所有方式都失败 → 保持现有随机 start_time
+                logger.info(
+                    "后台任务: SceneChange 与 analyze_videos 均无结果，保持随机起点: asset_id=%s",
+                    asset_id,
+                )
                 continue
 
-            updated_segments.setdefault(asset_id, []).append((recommended_start, recommended_start + clip_duration))
-            logger.info(
-                "后台任务: 更新片段起始时间: clip_id=%s asset_id=%s start_time=%.2f",
-                clip.id,
-                asset_id,
-                recommended_start,
-            )
+            # 为每个片段分配不同的镜头段
+            scene_segments_pool = list(scene_segments)  # 可消费的镜头段池
+            for clip in asset_clips:
+                clip_duration = clip.duration
+                recommended_start: float | None = None
+
+                # 从镜头段池中依次尝试，选一个不冲突的
+                for seg_idx, (seg_start, seg_end) in enumerate(scene_segments_pool):
+                    candidate_start = _pick_start_in_scene_segment(seg_start, seg_end, clip_duration)
+                    if candidate_start is None:
+                        continue  # 镜头段太短，跳过
+
+                    # 检查越界
+                    if candidate_start + clip_duration > asset_total:
+                        continue
+
+                    # 检查与已用区间冲突
+                    other_segs = _get_other_segments(asset_id, clip.id)
+                    if _recommended_time_conflicts(candidate_start, clip_duration, other_segs):
+                        continue
+
+                    recommended_start = candidate_start
+                    # 消费该镜头段（从池中移除，下一个片段用不同镜头段）
+                    scene_segments_pool.pop(seg_idx)
+                    break
+
+                if recommended_start is None:
+                    # 镜头段用完或都冲突 → 尝试 _calc_random_start_time 兜底
+                    used_segs_for_calc: dict[str, list[tuple[float, float]]] = {
+                        asset_id: _get_other_segments(asset_id, clip.id)
+                    }
+                    fallback_start = _calc_random_start_time(
+                        asset_id,
+                        clip_duration,
+                        {asset_id: asset_total},
+                        used_segs_for_calc,
+                    )
+                    if fallback_start is None:
+                        continue  # 完全无法分配，保持原起点
+                    recommended_start = fallback_start
+
+                # 更新片段起始时间
+                try:
+                    old_start = clip.start_time
+                    old_end = old_start + clip_duration
+
+                    plan_svc.update_clip(clip.id, start_time=recommended_start)
+                    try:
+                        if remove_used_segment(db, asset_id, old_start, old_end, plan_id=plan_id):
+                            record_used_segments(
+                                db,
+                                asset_id,
+                                recommended_start,
+                                recommended_start + clip_duration,
+                                plan_id,
+                            )
+                    except Exception as me:
+                        logger.warning(
+                            "后台任务: 同步素材区间记录失败，回滚本次片段更新: clip_id=%s error=%s",
+                            clip.id,
+                            me,
+                        )
+                        db.rollback()
+                        continue
+                    db.commit()
+                    updated_count += 1
+                    updated_clip_ids.add(clip.id)
+                    updated_segments.setdefault(asset_id, []).append(
+                        (recommended_start, recommended_start + clip_duration)
+                    )
+                    logger.info(
+                        "后台任务: 更新片段起始时间(场景选帧): clip_id=%s asset_id=%s start_time=%.2f",
+                        clip.id,
+                        asset_id,
+                        recommended_start,
+                    )
+                except Exception as ue:
+                    logger.warning("后台任务: 单个片段更新失败: clip_id=%s error=%s", clip.id, ue)
+                    try:
+                        db.rollback()
+                    except Exception:
+                        pass
+                    continue
 
         logger.info("后台任务完成: plan_id=%s 成功更新 %d 个片段", plan_id, updated_count)
 

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

@@ -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 ────────────────────────────────────────────────────────────────

apps/api/app/services/asset_segment_tracker.py

@@ -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``。

apps/api/app/services/plan_generator_service.py

@@ -13,6 +13,7 @@
 from __future__ import annotations
 
 import logging
+import random
 from typing import Any, List
 
 from sqlalchemy.orm import Session
@@ -32,6 +33,7 @@ from packages.domain.plan_generator_utils import (
     generate_default_clips,
     map_clip_types_for_mode,
 )
+from packages.domain.smart_match import SCORE_RANDOM_NOISE_MAX, score_asset
 from packages.domain.template_clip_config import TemplateClipConfig
 
 logger = logging.getLogger(__name__)
@@ -218,8 +220,13 @@ 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 +235,29 @@ 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（注入随机噪声）。
+
+        评分高的素材（质量好、时长合适、新鲜、使用次数少）倾向排在前面；
+        排序时给每个素材的得分注入 0~SCORE_RANDOM_NOISE_MAX 的随机噪声，
+        使得分接近的素材排名每次浮动，避免一键生成反复选出相同素材组合，
+        从素材组合层面降低成片查重率。分差大于噪声上限时排名保持稳定。
+        """
+        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))
+        # 评分 + 随机噪声后按降序排列
+        scored.sort(
+            key=lambda x: x[1] + random.uniform(0.0, SCORE_RANDOM_NOISE_MAX),
+            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.
 

apps/web/package-lock.json

@@ -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": {

apps/web/src/api/products/types.ts

@@ -71,4 +71,5 @@ export interface VideoItem {
   generation_params: Record<string, unknown>
   download_url: string
   generated_at: string
+  duplicate_rate?: number
 }

apps/web/src/api/products/utils.ts

@@ -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,
   }
 }

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

@@ -338,12 +338,15 @@ const GeneratePage: React.FC = () => {
                 size: titleSettings.size,
                 font: titleSettings.font,
                 color: titleSettings.color,
-                position: titleSettings.position as "top" | "center" | "bottom",
+                position: titleSettings.position as "top" | "center" | "bottom" | "custom",
                 bold: titleSettings.bold,
                 italic: titleSettings.italic,
                 stroke: titleSettings.stroke,
                 shadow: titleSettings.shadow,
+                posX: titleSettings.posX,
+                posY: titleSettings.posY,
               }}
+              onTitlePositionChange={styleUpdaters.updateTitlePosition}
             />
           )}
           {currentStep >= 5 && generated && finalVideo && (

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

@@ -32,12 +32,15 @@ interface FrontendPreviewPlayerProps {
     size: number
     font: string
     color: string
-    position: "top" | "center" | "bottom"
+    position: "top" | "center" | "bottom" | "custom"
     bold?: boolean
     italic?: boolean
     stroke?: boolean
     shadow?: boolean
+    posX?: number | null
+    posY?: number | null
   }
+  onTitlePositionChange?: (posX: number, posY: number) => void
 }
 
 function formatTime(seconds: number): string {
@@ -105,6 +108,7 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
   serverClips,
   voiceAudioUrl,
   titleSettings,
+  onTitlePositionChange,
 }) => {
   const segments = useMemo(
     () => buildPlaybackSegments(assets, template, serverClips),
@@ -126,6 +130,69 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
         return { width: 1080, height: 1920 }
     }
   })()
+  const customTitleXPct =
+    titleSettings?.posX != null && playRes.width > 0
+      ? (titleSettings.posX / playRes.width) * 100
+      : null
+  const customTitleYPct =
+    titleSettings?.posY != null && playRes.height > 0
+      ? (titleSettings.posY / playRes.height) * 100
+      : null
+
+  // ── 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
+      e.preventDefault()
+      e.stopPropagation()
+      ;(e.target as Element).setPointerCapture(e.pointerId)
+      draggingTitleRef.current = true
+      ;(e.currentTarget as HTMLDivElement).style.cursor = "grabbing"
+    },
+    [onTitlePositionChange],
+  )
+  const handleTitlePointerMove = useCallback((e: React.PointerEvent<HTMLDivElement>) => {
+    if (!draggingTitleRef.current || !playerContainerRef.current) return
+    e.preventDefault()
+    e.stopPropagation()
+    // 拖拽过程中直接修改 DOM，不触发 React 渲染（避免频繁重渲染导致换行）
+    if (titleDragRef.current) {
+      const rect = playerContainerRef.current.getBoundingClientRect()
+      const relX = Math.max(0, Math.min(rect.width, e.clientX - rect.left))
+      const relY = Math.max(0, Math.min(rect.height, e.clientY - rect.top))
+      const xpct = (relX / rect.width) * 100
+      const ypct = (relY / rect.height) * 100
+      titleDragRef.current.style.left = `${xpct}%`
+      titleDragRef.current.style.top = `${ypct}%`
+    }
+  }, [])
+  const handleTitlePointerUp = useCallback(
+    (e: React.PointerEvent<HTMLDivElement>) => {
+      if (!draggingTitleRef.current) return
+      draggingTitleRef.current = false
+      // 拖拽结束时才调用 onTitlePositionChange 保存最终位置
+      if (onTitlePositionChange && playerContainerRef.current) {
+        const rect = playerContainerRef.current.getBoundingClientRect()
+        const relX = Math.max(0, Math.min(rect.width, e.clientX - rect.left))
+        const relY = Math.max(0, Math.min(rect.height, e.clientY - rect.top))
+        const posX = Math.round((relX / rect.width) * playRes.width)
+        const posY = Math.round((relY / rect.height) * playRes.height)
+        onTitlePositionChange(posX, posY)
+      }
+      ;(e.currentTarget as HTMLDivElement).style.cursor = "grab"
+      try {
+        if ((e.currentTarget as Element).hasPointerCapture(e.pointerId)) {
+          ;(e.currentTarget as Element).releasePointerCapture(e.pointerId)
+        }
+      } catch {
+        /* ignore */
+      }
+    },
+    [onTitlePositionChange, playRes.width, playRes.height],
+  )
+
   const playerContainerRef = useRef<HTMLDivElement>(null)
   const [containerHeight, setContainerHeight] = useState(0)
   useEffect(() => {
@@ -524,15 +591,36 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
           <div
             style={{
               position: "absolute",
-              left: `${titleSidePct}%`,
-              right: `${titleSidePct}%`,
-              textAlign: "center",
-              ...(titleSettings.position === "top"
-                ? { top: `${titleTopPct}%` }
-                : titleSettings.position === "center"
-                  ? { top: "50%", transform: "translateY(-50%)" }
-                  : { bottom: `${titleBottomPct}%` }),
+              ...(customTitleXPct != null && customTitleYPct != null
+                ? {
+                    left: `${customTitleXPct}%`,
+                    top: `${customTitleYPct}%`,
+                    transform: "translate(-50%, -50%)",
+                    textAlign: "center" as const,
+                  }
+                : {
+                    left: `${titleSidePct}%`,
+                    right: `${titleSidePct}%`,
+                    textAlign: "center" as const,
+                    ...(titleSettings.position === "top"
+                      ? { top: `${titleTopPct}%` }
+                      : titleSettings.position === "center"
+                        ? { top: "50%", transform: "translateY(-50%)" }
+                        : { bottom: `${titleBottomPct}%` }),
+                  }),
+              pointerEvents: "auto",
+              cursor: onTitlePositionChange ? "grab" : "default",
+              touchAction: "none",
+              userSelect: "none",
+              WebkitUserSelect: "none",
+              padding: "8px 12px",
+              boxShadow: "inset 0 0 0 16px transparent",
             }}
+            ref={titleDragRef}
+            onPointerDown={handleTitlePointerDown}
+            onPointerMove={handleTitlePointerMove}
+            onPointerUp={handleTitlePointerUp}
+            onPointerCancel={handleTitlePointerUp}
           >
             <span
               style={{

apps/web/src/pages/generate/components/title/TitlePresetsGrid.tsx

@@ -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>
         )

apps/web/src/pages/generate/constants.ts

@@ -42,6 +42,7 @@ export const POSITION_OPTIONS = [
   { value: "top", label: "顶部" },
   { value: "center", label: "居中" },
   { value: "bottom", label: "底部" },
+  { value: "custom", label: "自定义" },
 ]
 
 /* ── 标题字体选项 ── */
@@ -77,10 +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",
     },
   },
   {
@@ -88,45 +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",
     },
   },
   {
@@ -134,10 +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",
     },
   },
   {
@@ -145,10 +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)",
     },
   },
 ]

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

@@ -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;
 }

apps/web/src/pages/generate/hooks/step2-materials/useSmartMatch.ts

@@ -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))
 }
 

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

@@ -233,7 +233,7 @@ export function useCanvasPlayer(
     fontSize: number
     fontFamily: string
     color: string
-    position: "top" | "center" | "bottom"
+    position: "top" | "center" | "bottom" | "custom"
     bold?: boolean
     stroke?: boolean
     shadow?: boolean

apps/web/src/pages/generate/hooks/useGenerateFormState/index.ts

@@ -27,6 +27,8 @@ const DEFAULT_TITLE_SETTINGS: TitleSettings = {
   stroke: true,
   shadow: false,
   color: "#ffffff",
+  posX: null,
+  posY: null,
 }
 
 export interface GenerateFormState {

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

@@ -117,6 +117,14 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
                   font_size: props.titleSettings.size,
                   font_color: props.titleSettings.color,
                   position: props.titleSettings.position,
+                  ...(props.titleSettings.position === "custom" &&
+                  props.titleSettings.posX != null &&
+                  props.titleSettings.posY != null
+                    ? {
+                        pos_x: Math.round(props.titleSettings.posX),
+                        pos_y: Math.round(props.titleSettings.posY),
+                      }
+                    : {}),
                   bold: props.titleSettings.bold,
                   stroke: props.titleSettings.stroke,
                   shadow: props.titleSettings.shadow,

apps/web/src/pages/generate/hooks/useStep4Title/useTitleStyleUpdaters.ts

@@ -46,7 +46,16 @@ export function useTitleStyleUpdaters({
 
   const updatePosition = useCallback(
     (position: string) => {
-      onTitleSettingsChange({ ...titleSettings, position })
+      // 切回三档预设时清掉自定义坐标
+      onTitleSettingsChange({ ...titleSettings, position, posX: null, posY: null })
+    },
+    [titleSettings, onTitleSettingsChange],
+  )
+
+  /** 拖拽更新自定义位置（由预览播放器调用） */
+  const updateTitlePosition = useCallback(
+    (posX: number, posY: number) => {
+      onTitleSettingsChange({ ...titleSettings, position: "custom", posX, posY })
     },
     [titleSettings, onTitleSettingsChange],
   )
@@ -111,6 +120,7 @@ export function useTitleStyleUpdaters({
     updateTitle,
     toggleAiAutoSelect,
     updatePosition,
+    updateTitlePosition,
     updateFont,
     updateSize,
     updateColor,

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

@@ -16,6 +16,9 @@ export interface TitleSettings {
   stroke: boolean
   shadow: boolean
   color: string
+  /** 自由位置坐标（PlayRes 像素），仅当 position="custom" 时有效 */
+  posX: number | null
+  posY: number | null
 }
 
 /* ── 智能匹配结果 ── */

apps/web/src/pages/products/components/ProductCard.tsx

@@ -221,7 +221,7 @@ export const ProductCard: React.FC<ProductCardProps> = ({
               product.duplicateRate > 0 ? ` ${dupClass}` : ""
             }`}
           >
-            查重率：{product.duplicateRate > 0 ? `${product.duplicateRate.toFixed(1)}%` : "-"}
+            查重率：{product.duplicateRate != null ? `${product.duplicateRate.toFixed(1)}%` : "-"}
           </span>
         </div>
       </div>

apps/web/src/pages/products/products.css

@@ -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);

apps/worker/video_processing/dedup.py

@@ -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]
 

apps/worker/video_processing/dedup_helpers.py

@@ -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:

apps/worker/video_processing/unified_render_service.py

@@ -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 ──────────────────────────────────────────────────

packages/domain/smart_match.py

@@ -14,6 +14,13 @@ from dataclasses import dataclass, field
 from datetime import datetime, timezone
 from typing import Any
 
+# 素材选取排序时注入的随机噪声上限（分）。
+# score_asset 综合得分范围为 0-100，噪声 0~20 意味着：
+# - 素材间得分差距 > 20 分时，排名不受影响（质量差异显著的素材保持稳定优先级）
+# - 得分接近（差距 <= 20 分）的素材排名会随机浮动，使每次生成选出的素材组合不同，
+#   从素材组合层面降低成片重复率；排名靠后的低分素材也有机会入选。
+SCORE_RANDOM_NOISE_MAX = 20.0
+
 
 @dataclass
 class SmartMatchResult:

packages/domain/xfade_builder.py

@@ -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)

packages/shared/mediakit_client.py

@@ -119,6 +119,70 @@ class MediaKitClient:
 
         return None
 
+    def detect_scene_changes(
+        self,
+        video_url: str,
+        max_frames: int = 20,
+        poll_interval: float = 2.0,
+        max_poll_attempts: int = 30,
+    ) -> Optional[List[float]]:
+        """检测视频场景切换点，返回时间戳列表.
+
+        降级策略：
+        1. 先尝试 SceneChange 策略
+        2. SceneChange 失败（OOM等）→ 退回 TimeInterval（5秒间隔）
+        3. MediaKit 不可用 → 返回 None
+
+        Returns:
+            场景切换点时间戳列表，如 [0.0, 3.2, 7.8, 12.5]
+            失败返回 None
+        """
+        if not self.is_available:
+            logger.warning("MediaKit 未配置，跳过场景检测")
+            return None
+
+        # 策略1：尝试 SceneChange
+        frames = self.extract_frames(
+            video_url=video_url,
+            strategy="SceneChange",
+            max_frames=max_frames,
+            poll_interval=poll_interval,
+            max_poll_attempts=max_poll_attempts,
+        )
+
+        # 策略2：SceneChange 失败 → 退回 TimeInterval（5秒间隔）
+        if frames is None:
+            logger.info("SceneChange 策略失败，降级为 TimeInterval（5秒间隔）")
+            # 估算帧数：假设视频最长60秒，每5秒一帧
+            ti_max_frames = max(max_frames, 12)
+            frames = self.extract_frames(
+                video_url=video_url,
+                strategy="TimeInterval",
+                max_frames=ti_max_frames,
+                poll_interval=poll_interval,
+                max_poll_attempts=max_poll_attempts,
+            )
+
+        if frames is None:
+            return None
+
+        # 从帧列表中提取 timestamp，排序
+        timestamps = sorted({float(f.get("timestamp", 0.0)) for f in frames if "timestamp" in f})
+
+        if not timestamps:
+            return None
+
+        # 始终在列表开头加 0.0（素材起始点）
+        if timestamps[0] != 0.0:
+            timestamps.insert(0, 0.0)
+
+        logger.info(
+            "场景检测完成: video_url=%s scene_changes=%s",
+            video_url[:80],
+            timestamps,
+        )
+        return timestamps
+
     def _submit_extract_task(
         self,
         video_url: str,

requirements-base.txt

@@ -24,8 +24,10 @@ celery==5.4.0
 # 对象存储
 oss2==2.18.4
 
-# HTTP 客户端
+# HTTP 客户端（pin 间接依赖防止版本漂移）
 httpx==0.27.2
+httpcore==1.0.7
+h2==4.1.0
 
 # Prometheus monitoring
 prometheus-client==0.21.1

requirements-dev.txt

@@ -15,5 +15,6 @@ pytest-xdist==3.6.1
 diff-cover==8.0.3
 
 # 资产质量评分依赖（与 requirements-worker.txt 保持一致）
+numpy==1.26.4
 scipy==1.13.1
 Pillow==10.4.0

scripts/ci/auto_approve.sh

@@ -28,15 +28,12 @@ if [ "$SKIP_BACKEND" = "true" ]; then
   CONTEXTS=("CI/CD Pipeline / Frontend Lint (pull_request)")
 else
   CONTEXTS=(
-    "CI/CD Pipeline / Validate - Code Quality (pull_request)"
-    "CI/CD Pipeline / Validate - Type Check (mypy) (pull_request)"
-    "CI/CD Pipeline / Validate - Migration (alembic) (pull_request)"
+    # CI 优化后 job 名称（2026-08）：Code Quality 拆分为 Style+Security，Type Check+Migration 合并为 Python
+    # 与 pr_auto_scan.py 的 REQUIRED_CONTEXTS_APPROVE 保持一致
+    "CI/CD Pipeline / Validate - Style (pull_request)"
+    "CI/CD Pipeline / Validate - Security (pull_request)"
+    "CI/CD Pipeline / Validate - Python (mypy + alembic) (pull_request)"
     "CI/CD Pipeline / Frontend Lint (pull_request)"
-    "CI/CD Pipeline / Unit Tests (pull_request)"
-    "CI/CD Pipeline / Frontend Unit Tests (pull_request)"
-    "CI/CD Pipeline / PR Build API Image (pull_request)"
-    "CI/CD Pipeline / PR Build Web Image (pull_request)"
-    "CI/CD Pipeline / PR Build Worker Image (pull_request)"
   )
 fi
 
@@ -153,4 +150,4 @@ done
 
 echo
 echo "⏰ 快速检查超时（2分钟），CI尚未完成，退出等待下次触发（workflow_run事件或5分钟定时扫描）"
-exit 0
+exit 0

scripts/ci/ensure_persistent_builder.sh

@@ -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
+

scripts/ci/pr_auto_scan.py

@@ -303,9 +303,10 @@ def main():
         "CI/CD Pipeline / CI Gate (pull_request)",
     ]
     REQUIRED_CONTEXTS_APPROVE = [
-        "CI/CD Pipeline / Validate - Code Quality (pull_request)",
-        "CI/CD Pipeline / Validate - Type Check (mypy) (pull_request)",
-        "CI/CD Pipeline / Validate - Migration (alembic) (pull_request)",
+        # CI 优化后 job 名称（2026-08）：Code Quality 拆分为 Style+Security，Type Check+Migration 合并为 Python
+        "CI/CD Pipeline / Validate - Style (pull_request)",
+        "CI/CD Pipeline / Validate - Security (pull_request)",
+        "CI/CD Pipeline / Validate - Python (mypy + alembic) (pull_request)",
         "CI/CD Pipeline / Frontend Lint (pull_request)",
     ]
     FRONTEND_ONLY_CONTEXT = [

scripts/ci/run_integration_tests.sh

@@ -197,8 +197,8 @@ if [ "$USE_SHARED_PG" = "true" ]; then
   # 创建主数据库（xdist 模式下各 worker 会创建自己的数据库，主库作为 fallback）
   echo "创建主测试数据库: $CI_DB_NAME"
   PGPASSWORD="$SHARED_PG_PASSWORD" python3 -c "
-import psycopg2
-conn = psycopg2.connect(host='$SHARED_PG_HOST', port=$SHARED_PG_PORT, user='$SHARED_PG_USER', password='$SHARED_PG_PASSWORD', dbname='postgres')
+import psycopg
+conn = psycopg.connect(host='$SHARED_PG_HOST', port=$SHARED_PG_PORT, user='$SHARED_PG_USER', password='$SHARED_PG_PASSWORD', dbname='postgres')
 conn.autocommit = True
 cur = conn.cursor()
 cur.execute(f'DROP DATABASE IF EXISTS \"$CI_DB_NAME\" WITH (FORCE)')
@@ -304,8 +304,8 @@ if [ "$USE_SHARED_PG" = "true" ]; then
 
   # 清理所有以 CI_DB_NAME 开头的数据库（主库 + worker 库）
   PGPASSWORD="${SHARED_PG_PASSWORD}" python3 -c "
-import psycopg2
-conn = psycopg2.connect(host='${SHARED_PG_HOST}', port=${SHARED_PG_PORT}, user='${SHARED_PG_USER}', password='${SHARED_PG_PASSWORD}', dbname='postgres')
+import psycopg
+conn = psycopg.connect(host='${SHARED_PG_HOST}', port=${SHARED_PG_PORT}, user='${SHARED_PG_USER}', password='${SHARED_PG_PASSWORD}', dbname='postgres')
 conn.autocommit = True
 cur = conn.cursor()
 
@@ -344,4 +344,4 @@ python3 scripts/ci_coverage_summary.py
 set -e
 
 echo ""
-echo "=== CI Integration Tests 全部通过 ✅ ==="
+echo "=== CI Integration Tests 全部通过 ✅ ==="

scripts/ci/run_unit_tests.sh

@@ -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

scripts/ci/run_validate.sh

@@ -409,8 +409,8 @@ except:
 
     echo "创建测试数据库: $CI_DB_NAME"
     PGPASSWORD="$SHARED_PG_PASSWORD" python3 -c "
-import psycopg2
-conn = psycopg2.connect(host='$SHARED_PG_HOST', port=$SHARED_PG_PORT, user='$SHARED_PG_USER', password='$SHARED_PG_PASSWORD', dbname='postgres')
+import psycopg
+conn = psycopg.connect(host='$SHARED_PG_HOST', port=$SHARED_PG_PORT, user='$SHARED_PG_USER', password='$SHARED_PG_PASSWORD', dbname='postgres')
 conn.autocommit = True
 cur = conn.cursor()
 cur.execute(f'DROP DATABASE IF EXISTS \"$CI_DB_NAME\" WITH (FORCE)')
@@ -431,8 +431,8 @@ conn.close()
       # 清理数据库
       echo "清理测试数据库: $CI_DB_NAME"
       PGPASSWORD="$SHARED_PG_PASSWORD" python3 -c "
-import psycopg2
-conn = psycopg2.connect(host='$SHARED_PG_HOST', port=$SHARED_PG_PORT, user='$SHARED_PG_USER', password='$SHARED_PG_PASSWORD', dbname='postgres')
+import psycopg
+conn = psycopg.connect(host='$SHARED_PG_HOST', port=$SHARED_PG_PORT, user='$SHARED_PG_USER', password='$SHARED_PG_PASSWORD', dbname='postgres')
 conn.autocommit = True
 cur = conn.cursor()
 cur.execute(f'DROP DATABASE IF EXISTS \"$CI_DB_NAME\" WITH (FORCE)')

scripts/ci/sync_base_images.sh

@@ -1,103 +0,0 @@
-#!/bin/bash
-# ============================================
-# 基础镜像同步脚本 - 从公共镜像源同步到私有ACR
-# 用法:
-#   ACR_USERNAME=xxx ACR_PASSWORD=yyy bash scripts/ci/sync_base_images.sh
-# ============================================
-
-set -euo pipefail
-
-ACR_REGISTRY="${ACR_REGISTRY:-xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com/xiaoxiakeji}"
-ACR_USERNAME="${ACR_USERNAME:-}"
-ACR_PASSWORD="${ACR_PASSWORD:-}"
-SOURCE_PREFIX="${SOURCE_PREFIX:-docker.m.daocloud.io/library}"
-
-# 需要同步的镜像列表 (源镜像名:tag => ACR目标名:tag)
-IMAGES=(
-    "python:3.12-slim-bookworm"
-    "python:3.12-slim"
-    "node:20"
-    "nginx:alpine"
-)
-
-echo "============================================"
-echo "  基础镜像同步到 ACR"
-echo "  ACR: $ACR_REGISTRY"
-echo "  源: $SOURCE_PREFIX"
-echo "============================================"
-echo ""
-
-# 登录 ACR
-if [ -n "$ACR_PASSWORD" ] && [ -n "$ACR_USERNAME" ]; then
-    echo "登录 ACR..."
-    ACR_HOST=$(echo "$ACR_REGISTRY" | cut -d/ -f1)
-    printf '%s' "$ACR_PASSWORD" | docker login "$ACR_HOST" -u "$ACR_USERNAME" --password-stdin
-    echo "ACR 登录成功"
-    echo ""
-fi
-
-success=0
-failed=0
-
-for image in "${IMAGES[@]}"; do
-    source_image="${SOURCE_PREFIX}/${image}"
-    target_image="${ACR_REGISTRY}/base/${image}"
-
-    echo "--- 同步: $image ---"
-    echo "  源: $source_image"
-    echo "  目标: $target_image"
-
-    # Pull 源镜像（带重试）
-    pulled=0
-    for attempt in 1 2 3; do
-        echo "  Pull 尝试 $attempt/3..."
-        if docker pull "$source_image"; then
-            pulled=1
-            break
-        fi
-        echo "  Pull 失败，5s 后重试..."
-        sleep 5
-    done
-
-    if [ "$pulled" -eq 0 ]; then
-        echo "  ❌ Pull 失败: $image"
-        failed=$((failed + 1))
-        continue
-    fi
-
-    # Tag
-    docker tag "$source_image" "$target_image"
-    echo "  Tag 完成"
-
-    # Push 到 ACR
-    pushed=0
-    for attempt in 1 2 3; do
-        echo "  Push 尝试 $attempt/3..."
-        if docker push "$target_image"; then
-            pushed=1
-            break
-        fi
-        echo "  Push 失败，5s 后重试..."
-        sleep 5
-    done
-
-    if [ "$pushed" -eq 1 ]; then
-        echo "  ✅ 同步成功: $image"
-        success=$((success + 1))
-    else
-        echo "  ❌ Push 失败: $image"
-        failed=$((failed + 1))
-    fi
-
-    echo ""
-done
-
-echo "============================================"
-echo "  同步完成"
-echo "  成功: $success"
-echo "  失败: $failed"
-echo "============================================"
-
-if [ "$failed" -gt 0 ]; then
-    exit 1
-fi

scripts/ci/validate_code_quality.sh

@@ -1,157 +0,0 @@
-#!/bin/bash
-# CI Validate: 代码质量与安全扫描（并行Job 1/3）
-# 包含：密钥扫描、格式检查、安全扫描、依赖漏洞、死代码检测、脚本语法校验
-set -eu
-
-echo "=== CI Validate: 代码质量与安全扫描 ==="
-
-# --- 密钥检测 ---
-echo ""
-echo "=== [1/6] Secret detection (detect-secrets) ==="
-python3 -m pip install -q detect-secrets
-detect-secrets --version
-
-detect-secrets scan \
-  --all-files \
-  --exclude-files '(^|/)(tests|test|e2e|__tests__|spec|docs|node_modules|site-packages|migrations|alembic|.gitea|.git|.pytest_cache|.next|dist|build)/' \
-  --exclude-files '\.(md|rst|txt|lock|example|sample|min\.js|min\.css|spec\.ts|test\.ts|test\.py)$' \
-  --exclude-files '(package-lock|yarn\.lock|poetry\.lock|Pipfile\.lock)$' \
-  --disable-plugin Base64HighEntropyString \
-  --disable-plugin HexHighEntropyString \
-  --disable-plugin BasicAuthDetector \
-  --disable-plugin KeywordDetector \
-  --disable-plugin IPPublicDetector \
-  > /tmp/secrets-scan.json 2>&1
-
-FOUND=$(python3 -c "
-import json
-try:
-    with open('/tmp/secrets-scan.json') as f:
-        data = json.load(f)
-    results = data.get('results', {})
-    total = sum(len(v) for v in results.values())
-    print(total)
-except Exception:
-    print('error')
-")
-
-echo "Secrets detected: $FOUND"
-if [ "$FOUND" != "0" ] && [ "$FOUND" != "error" ]; then
-  echo ""
-  echo "=== Secret details ==="
-  python3 -c "
-import json
-with open('/tmp/secrets-scan.json') as f:
-    data = json.load(f)
-for fpath, items in data.get('results', {}).items():
-    for item in items:
-        line = item.get('line_number', '?')
-        stype = item.get('type', '?')
-        hashed = item.get('hashed_secret', '')[:16]
-        print(f'  {fpath}:{line} [{stype}] {hashed}...')
-"
-  echo ""
-  echo "ERROR: Potential secrets detected in code!"
-  exit 1
-fi
-echo "✅ Secret scan passed"
-
-# --- 代码质量检查（全量，PR 和 push 统一标准）---
-# 历史：PR 侧用增量检查以加速，但会导致 push 侧全量检查失败时 PR 侧感知不到
-# 现在统一全量检查，确保 CI 真正保护主分支（black/isort/ruff 全量仅多几十秒）
-echo ""
-echo "=== [2/6] Code quality checks (full scan) ==="
-SCAN_MODE="full"
-echo "Full scan mode"
-python3 -m compileall -q alembic apps packages tests scripts
-python3 -m black --check --fast alembic apps packages tests scripts
-python3 -m isort --check-only alembic apps packages tests scripts
-python3 -m ruff check apps packages tests --statistics
-
-echo "✅ Code quality checks passed"
-
-# --- Bandit 安全扫描（仅告警） ---
-echo ""
-echo "=== [3/6] Security scan (bandit, advisory only) ==="
-set +e
-bandit -r apps packages -q -ll
-BANDIT_EXIT=$?
-set -e
-if [ "$BANDIT_EXIT" -ne 0 ]; then
-  echo "⚠️  Bandit found security issues (advisory mode - not blocking CI)"
-else
-  echo "✅ Bandit security scan passed"
-fi
-
-# --- Pip-audit 依赖漏洞扫描（仅告警） ---
-echo ""
-echo "=== [4/6] Python dependency vulnerability scan (pip-audit, advisory only) ==="
-python3 -m pip install -q pip-audit
-pip-audit --version
-EXIT_CODE=0
-for req_file in requirements.txt requirements-base.txt requirements-dev.txt; do
-  if [ -f "$req_file" ]; then
-    echo "--- Scanning $req_file ---"
-    pip-audit -r "$req_file" --desc on 2>&1 | head -40 || EXIT_CODE=$?
-    echo ""
-  fi
-done
-echo "pip-audit scan completed (advisory mode - warnings only, not blocking CI)"
-
-# --- Vulture 死代码检测（仅告警） ---
-echo ""
-echo "=== [5/6] Dead code detection (vulture, advisory only) ==="
-set +e
-python3 -m pip install -q vulture
-vulture --version
-echo "告警模式，不阻断CI。置信度>=90%建议尽快确认。"
-echo ""
-vulture apps packages scripts \
-  --exclude "tests,test,migrations,.gitea,docs,node_modules,site-packages,*/test_*.py,*/conftest.py" \
-  --min-confidence 70 \
-  2>&1 | sort -t'(' -k2 -rn | head -80
-echo ""
-echo "=== vulture scan summary ==="
-echo "发现潜在死代码（可能包含框架装饰器注册的函数，为误报）"
-echo "建议：定期人工审查高置信度（>=90%）条目"
-set -e
-
-# --- CI脚本语法校验 ---
-echo ""
-echo "=== [6/6] CI & shell scripts syntax validation ==="
-SYNTAX_ERROR=0
-# 检查所有 CI shell 脚本
-for script in scripts/ci/*.sh; do
-  if [ -f "$script" ]; then
-    if ! bash -n "$script" 2>&1; then
-      echo "❌ 语法错误: $script"
-      SYNTAX_ERROR=1
-    fi
-  fi
-done
-# 检查所有 CI Python 脚本语法
-for script in scripts/ci/*.py; do
-  if [ -f "$script" ]; then
-    if ! python3 -m py_compile "$script" 2>&1; then
-      echo "❌ Python语法错误: $script"
-      SYNTAX_ERROR=1
-    fi
-  fi
-done
-# 检查 .gitea/workflows 下的脚本（如果有）
-for script in .gitea/workflows/*.sh; do
-  if [ -f "$script" ]; then
-    if ! bash -n "$script" 2>&1; then
-      echo "❌ 语法错误: $script"
-      SYNTAX_ERROR=1
-    fi
-  fi
-done
-if [ "$SYNTAX_ERROR" -ne 0 ]; then
-  echo "❌ CI脚本语法校验失败，见上方错误"
-  exit 1
-fi
-echo "✅ All CI scripts syntax OK"
-
-echo ""
-echo "=== CI Validate: 代码质量与安全扫描 全部通过 ✅ ==="

scripts/ci/validate_migration.sh

@@ -169,8 +169,8 @@ if [ "$USE_SHARED_PG" = "true" ]; then
 
   echo "创建测试数据库: $CI_DB_NAME"
   PGPASSWORD="$SHARED_PG_PASSWORD" python3 -c "
-import psycopg2
-conn = psycopg2.connect(host='$SHARED_PG_HOST', port=$SHARED_PG_PORT, user='$SHARED_PG_USER', password='$SHARED_PG_PASSWORD', dbname='postgres')
+import psycopg
+conn = psycopg.connect(host='$SHARED_PG_HOST', port=$SHARED_PG_PORT, user='$SHARED_PG_USER', password='$SHARED_PG_PASSWORD', dbname='postgres')
 conn.autocommit = True
 cur = conn.cursor()
 cur.execute(f'DROP DATABASE IF EXISTS \"$CI_DB_NAME\" WITH (FORCE)')
@@ -185,8 +185,8 @@ conn.close()
     echo ""
     echo "清理测试数据库: $CI_DB_NAME"
     PGPASSWORD="$SHARED_PG_PASSWORD" python3 -c "
-import psycopg2
-conn = psycopg2.connect(host='$SHARED_PG_HOST', port=$SHARED_PG_PORT, user='$SHARED_PG_USER', password='$SHARED_PG_PASSWORD', dbname='postgres')
+import psycopg
+conn = psycopg.connect(host='$SHARED_PG_HOST', port=$SHARED_PG_PORT, user='$SHARED_PG_USER', password='$SHARED_PG_PASSWORD', dbname='postgres')
 conn.autocommit = True
 cur = conn.cursor()
 cur.execute(f'DROP DATABASE IF EXISTS \"$CI_DB_NAME\" WITH (FORCE)')

scripts/ci_staging_deploy.sh

@@ -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

scripts/ci_staging_healthcheck.sh

@@ -187,7 +187,7 @@ health_check() {
             return 0
         fi
 
-        sleep 5
+        sleep 3
     done
 
     # 超时了

tests/unit/test_asset_availability.py

@@ -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。

tests/unit/test_asset_segment_tracker.py

@@ -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
 
 

tests/unit/test_dedup_helpers_user_id.py

@@ -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

tests/unit/test_duplicate_rate.py

@@ -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."""

tests/unit/test_duration_compensation.py

@@ -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

tests/unit/test_editor_clips_random_start.py

@@ -38,6 +38,28 @@ def _segments(count: int, dur_min: float = 3.0, dur_max: float = 5.0):
     return [(i, dur_min, dur_max) for i in range(count)]
 
 
+def _patch_zero_noise():
+    """消除 clips.py 排序随机噪声，用于确定性断言（如均衡分配）。
+
+    排序噪声（random.uniform(0, SCORE_RANDOM_NOISE_MAX)）返回 0；
+    其他 uniform 调用（片段时长随机）委托给独立 Random 实例，行为不变。
+    """
+    import random as _stdlib_random
+
+    from app.api.routes.templates_editor import clips as clips_module
+
+    from packages.domain.smart_match import SCORE_RANDOM_NOISE_MAX
+
+    _fallback = _stdlib_random.Random()
+
+    def _fake_uniform(a, b):
+        if b == SCORE_RANDOM_NOISE_MAX:
+            return 0.0
+        return _fallback.uniform(a, b)
+
+    return patch.object(clips_module.random, "uniform", _fake_uniform)
+
+
 def _patch_segments(segments=None):
     return patch(
         "app.api.routes.templates_editor.clips._get_template_segments",
@@ -58,6 +80,10 @@ 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
 
 
@@ -126,7 +152,8 @@ class TestEditorClipsBySegments:
 
         body = ClipsFromAssetsRequest(asset_ids=["a1", "a2"], required_clips_count=2)
 
-        with _patch_segments(DEFAULT_SEGMENTS):
+        # 均衡分配由 use_count 贪心保证，消除排序噪声后确定性断言
+        with _patch_zero_noise(), _patch_segments(DEFAULT_SEGMENTS):
             result = create_clips_from_assets_editor(
                 template_id="tpl-001",
                 body=body,
@@ -142,11 +169,12 @@ 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):
@@ -413,8 +441,13 @@ class TestEditorClipsDurationAndStartTime:
 
         assert mock_calc.call_count == 2
         clips_data = _get_clips_data_from_call(mock_plan_svc)
-        assert clips_data[0]["start_time"] == 12.5
-        assert clips_data[1]["start_time"] == 18.0
+        # clips_data 按 order 排序，但分配顺序因 shuffle 而随机，
+        # 因此只验证两个 start_time 值都存在
+        start_times = {c["start_time"] for c in clips_data}
+        assert start_times == {12.5, 18.0}
+        # 验证 order 仍然有序
+        orders = [c["order"] for c in clips_data]
+        assert orders == sorted(orders)
 
     @patch("app.api.routes.templates_editor.clips.get_storage_service")
     def test_asset_durations_deduped(self, mock_storage):
@@ -631,7 +664,8 @@ 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):
@@ -784,7 +818,8 @@ class TestClipsFromAssetsInvalidIds:
 
         body = ClipsFromAssetsRequest(asset_ids=["a1", None, "", "a2"])  # type: ignore[list-item]
 
-        with _patch_segments(_segments(2, dur_min=3.0, dur_max=5.0)):
+        # 消除排序噪声，确定性断言两条合法素材各被使用
+        with _patch_zero_noise(), _patch_segments(_segments(2, dur_min=3.0, dur_max=5.0)):
             result = create_clips_from_assets_editor(
                 template_id="tpl-001",
                 body=body,

tests/unit/test_mediakit_conflicts.py

@@ -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

tests/unit/test_mediakit_smart_clips.py

@@ -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 ──────────────────────────────────
@@ -306,6 +306,27 @@ class TestGetTemplateSegments:
 # ── from-assets 端点集成测试 ────────────────────────────────────────────────
 
 
+def _patch_zero_noise():
+    """消除 clips.py 排序随机噪声（SCORE_RANDOM_NOISE_MAX 噪声返回 0）。
+
+    用于均衡分配等确定性断言；其他 uniform 调用（片段时长随机）行为不变。
+    """
+    import random as _stdlib_random
+
+    from app.api.routes.templates_editor import clips as clips_module
+
+    from packages.domain.smart_match import SCORE_RANDOM_NOISE_MAX
+
+    _fallback = _stdlib_random.Random()
+
+    def _fake_uniform(a, b):
+        if b == SCORE_RANDOM_NOISE_MAX:
+            return 0.0
+        return _fallback.uniform(a, b)
+
+    return patch.object(clips_module.random, "uniform", _fake_uniform)
+
+
 def _make_auth_user():
     auth = MagicMock()
     auth.user.id = "user-001"
@@ -347,6 +368,10 @@ 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
 
 
@@ -442,11 +467,15 @@ class TestFromAssetsByTemplateSegments:
         )
 
         clips_data = _get_clips_data(mock_plan_svc)
-        assert 3.0 <= clips_data[0]["duration"] <= 5.0
-        assert 4.0 <= clips_data[1]["duration"] <= 8.0
+        # PR #1614 转场补偿：2 个片段时每 clip 时长 +(2-1)*0.5/2=0.25s
+        # （xfade 重叠在渲染时扣除，故 clip 时长 = segment 随机时长 + 补偿），
+        # 断言上界需计入补偿与一位小数舍入余量
+        comp = (2 - 1) * 0.5 / 2
+        assert 3.0 + comp - 0.1 <= clips_data[0]["duration"] <= 5.0 + comp + 0.1
+        assert 4.0 + comp - 0.1 <= clips_data[1]["duration"] <= 8.0 + comp + 0.1
 
-    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
 
@@ -462,20 +491,26 @@ class TestFromAssetsByTemplateSegments:
         mock_asset_repo.get.side_effect = get_asset
 
         body = ClipsFromAssetsRequest(asset_ids=["a1", "a2"])
-        create_clips_from_assets_editor(
-            template_id="tmpl-1",
-            body=body,
-            background_tasks=MagicMock(),
-            plan_id="plan-1",
-            services=(mock_tpl_svc, mock_plan_svc),
-            asset_repo=mock_asset_repo,
-            db=MagicMock(),
-            current_user=_make_auth_user(),
-        )
+        # 消除排序噪声，确定性断言贪心均衡分配
+        with _patch_zero_noise():
+            create_clips_from_assets_editor(
+                template_id="tmpl-1",
+                body=body,
+                background_tasks=MagicMock(),
+                plan_id="plan-1",
+                services=(mock_tpl_svc, mock_plan_svc),
+                asset_repo=mock_asset_repo,
+                db=MagicMock(),
+                current_user=_make_auth_user(),
+            )
 
         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。"""

tests/unit/test_plan_generator.py

@@ -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)

tests/unit/test_scene_change_shuffle.py

@@ -0,0 +1,257 @@
+"""Tests for scene-change smart frame selection + random shuffle of segment processing."""
+
+from __future__ import annotations
+
+import random
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from apps.api.app.api.routes.templates_editor.clips import (
+    _build_scene_segments,
+    _pick_start_in_scene_segment,
+)
+from packages.shared.mediakit_client import MediaKitClient
+
+# ── Part 1: Random shuffle tests ──────────────────────────────────────────
+
+
+class TestRandomShuffle:
+    """验证 segments 处理顺序随机打乱逻辑."""
+
+    def test_same_segments_produce_different_asset_orders(self):
+        """同一批 segments 多次处理，asset 分配顺序有变化.
+
+        模拟打乱后的处理顺序，验证多次运行中 asset_id 分配顺序
+        存在差异（概率性验证，运行 50 次应该至少出现 2 种排列）。
+        """
+        segments = [(0, 3.0, 5.0), (1, 4.0, 6.0), (2, 3.0, 5.0), (3, 4.0, 6.0)]
+        asset_ids = ["A", "B", "C", "D"]
+
+        observed_orders: list[tuple] = set()
+
+        for _ in range(50):
+            shuffled_indices = list(range(len(segments)))
+            random.shuffle(shuffled_indices)
+            order_tuple = tuple(shuffled_indices)
+            observed_orders.add(order_tuple)
+
+        # 50 次打乱，4! = 24 种排列，应出现多种不同排列
+        assert len(observed_orders) > 1, "打乱应该产生多种不同顺序"
+
+    def test_clips_data_order_always_sorted(self):
+        """clips_data 按 order 排序后始终有序.
+
+        模拟打乱处理后 clips_data 按 order 排序，验证最终 order 为 [0,1,2,3]。
+        """
+        segments = [(0, 3.0, 5.0), (1, 4.0, 6.0), (2, 3.0, 5.0), (3, 4.0, 6.0)]
+
+        for _ in range(20):
+            shuffled_indices = list(range(len(segments)))
+            random.shuffle(shuffled_indices)
+
+            # 模拟构建 clips_data（用 _seg_order 作为 order）
+            clips_data = []
+            for idx in shuffled_indices:
+                seg_order, _, _ = segments[idx]
+                clips_data.append({"order": seg_order, "asset_id": f"asset_{idx}"})
+
+            # 按 order 排序
+            clips_data.sort(key=lambda c: c["order"])
+
+            # 验证 order 始终有序
+            orders = [c["order"] for c in clips_data]
+            assert orders == [0, 1, 2, 3], f"排序后 order 应为 [0,1,2,3]，实际为 {orders}"
+
+
+# ── Part 2: detect_scene_changes tests ────────────────────────────────────
+
+
+class TestDetectSceneChanges:
+    """验证 MediaKitClient.detect_scene_changes 方法."""
+
+    def _make_client(self) -> MediaKitClient:
+        """创建一个可用的 MediaKitClient（mock 配置）."""
+        with patch("packages.shared.mediakit_client.get_shared_settings") as mock_settings:
+            mock_settings.return_value.mediakit_api_key = "test-key"
+            mock_settings.return_value.mediakit_base_url = "http://test"
+            mock_settings.return_value.mediakit_timeout = 30
+            client = MediaKitClient()
+        return client
+
+    def test_scene_change_success(self):
+        """SceneChange 策略成功返回时间戳列表."""
+        client = self._make_client()
+
+        mock_frames = [
+            {"image_url": "url1", "timestamp": 0.0},
+            {"image_url": "url2", "timestamp": 3.2},
+            {"image_url": "url3", "timestamp": 7.8},
+            {"image_url": "url4", "timestamp": 12.5},
+        ]
+
+        with patch.object(client, "extract_frames", return_value=mock_frames):
+            result = client.detect_scene_changes("https://example.com/video.mp4")
+
+        assert result is not None
+        assert result[0] == 0.0  # 始终以 0.0 开头
+        assert 3.2 in result
+        assert 7.8 in result
+        assert 12.5 in result
+        assert result == sorted(result)  # 应已排序
+
+    def test_scene_change_fallback_to_time_interval(self):
+        """SceneChange 失败降级到 TimeInterval 策略."""
+        client = self._make_client()
+
+        # 第一次调用（SceneChange）返回 None，第二次（TimeInterval）返回结果
+        fallback_frames = [
+            {"image_url": "url1", "timestamp": 0.0},
+            {"image_url": "url2", "timestamp": 5.0},
+            {"image_url": "url3", "timestamp": 10.0},
+        ]
+
+        call_count = 0
+
+        def side_effect(*args, **kwargs):
+            nonlocal call_count
+            call_count += 1
+            if call_count == 1:
+                # 第一次 SceneChange 失败
+                return None
+            else:
+                # 第二次 TimeInterval 成功
+                assert kwargs.get("strategy") == "TimeInterval"
+                return fallback_frames
+
+        with patch.object(client, "extract_frames", side_effect=side_effect):
+            result = client.detect_scene_changes("https://example.com/video.mp4")
+
+        assert result is not None
+        assert result[0] == 0.0
+        assert 5.0 in result
+        assert 10.0 in result
+
+    def test_mediakit_not_available_returns_none(self):
+        """MediaKit 不可用时返回 None."""
+        with patch("packages.shared.mediakit_client.get_shared_settings") as mock_settings:
+            mock_settings.return_value.mediakit_api_key = ""  # 未配置
+            mock_settings.return_value.mediakit_base_url = "http://test"
+            mock_settings.return_value.mediakit_timeout = 30
+            client = MediaKitClient()
+
+        result = client.detect_scene_changes("https://example.com/video.mp4")
+        assert result is None
+
+    def test_both_strategies_fail_returns_none(self):
+        """SceneChange 和 TimeInterval 都失败时返回 None."""
+        client = self._make_client()
+
+        with patch.object(client, "extract_frames", return_value=None):
+            result = client.detect_scene_changes("https://example.com/video.mp4")
+
+        assert result is None
+
+    def test_prepends_zero_if_not_present(self):
+        """若帧列表中不包含 0.0，自动在开头添加."""
+        client = self._make_client()
+
+        # 帧列表中没有 timestamp=0.0
+        mock_frames = [
+            {"image_url": "url1", "timestamp": 2.0},
+            {"image_url": "url2", "timestamp": 5.5},
+        ]
+
+        with patch.object(client, "extract_frames", return_value=mock_frames):
+            result = client.detect_scene_changes("https://example.com/video.mp4")
+
+        assert result is not None
+        assert result[0] == 0.0
+        assert 2.0 in result
+        assert 5.5 in result
+
+
+# ── Part 2.2: Scene segment building and assignment ───────────────────────
+
+
+class TestSceneSegments:
+    """验证镜头段构建和分配逻辑."""
+
+    def test_build_scene_segments(self):
+        """从场景切换点正确构建镜头段."""
+        scene_changes = [0.0, 3.2, 7.8, 12.5]
+        asset_duration = 15.0
+
+        segments = _build_scene_segments(scene_changes, asset_duration)
+
+        assert len(segments) == 4
+        assert segments[0] == (0.0, 3.2)
+        assert segments[1] == (3.2, 7.8)
+        assert segments[2] == (7.8, 12.5)
+        assert segments[3] == (12.5, 15.0)
+
+    def test_build_scene_segments_filters_short(self):
+        """过滤掉过短的镜头段（< 0.5秒）."""
+        scene_changes = [0.0, 0.1, 5.0, 5.3, 10.0]
+        asset_duration = 12.0
+
+        segments = _build_scene_segments(scene_changes, asset_duration)
+
+        # (0.0, 0.1) 长度 0.1 < 0.5 → 过滤
+        # (0.1, 5.0) → 保留
+        # (5.0, 5.3) 长度 0.3 < 0.5 → 过滤
+        # (5.3, 10.0) → 保留
+        # (10.0, 12.0) → 保留
+        assert len(segments) == 3
+        assert segments[0] == (0.1, 5.0)
+        assert segments[1] == (5.3, 10.0)
+        assert segments[2] == (10.0, 12.0)
+
+    def test_pick_start_in_segment(self):
+        """在镜头段内随机选取起始时间."""
+        seg_start = 3.0
+        seg_end = 8.0
+        clip_duration = 2.0
+
+        starts = set()
+        for _ in range(100):
+            start = _pick_start_in_scene_segment(seg_start, seg_end, clip_duration)
+            assert start is not None
+            assert seg_start <= start <= seg_end - clip_duration
+            starts.add(round(start, 2))
+
+        # 应该有多个不同的起始时间
+        assert len(starts) > 1
+
+    def test_pick_start_segment_too_short(self):
+        """镜头段太短无法容纳片段时返回 None."""
+        result = _pick_start_in_scene_segment(0.0, 1.0, 2.0)
+        assert result is None
+
+    def test_different_clips_from_different_scenes(self):
+        """不同片段应来自不同的镜头段（模拟分配逻辑）."""
+        scene_changes = [0.0, 5.0, 10.0, 15.0]
+        asset_duration = 18.0
+        clip_duration = 3.0
+
+        segments = _build_scene_segments(scene_changes, asset_duration)
+        assert len(segments) == 4  # (0,5), (5,10), (10,15), (15,18)
+
+        # 模拟 3 个片段从不同镜头段取点
+        scene_pool = list(segments)
+        assigned_starts = []
+
+        for _ in range(3):
+            if not scene_pool:
+                break
+            seg_start, seg_end = scene_pool.pop(0)
+            start = _pick_start_in_scene_segment(seg_start, seg_end, clip_duration)
+            assert start is not None
+            assigned_starts.append(start)
+
+        # 3 个片段分别从 3 个不同镜头段中选取
+        assert len(assigned_starts) == 3
+        # 第一个来自 [0, 2]，第二个来自 [5, 7]，第三个来自 [10, 12]
+        assert 0.0 <= assigned_starts[0] <= 2.0
+        assert 5.0 <= assigned_starts[1] <= 7.0
+        assert 10.0 <= assigned_starts[2] <= 12.0

tests/unit/test_smart_match_integration.py

@@ -0,0 +1,475 @@
+"""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_RANDOM_NOISE_MAX, 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
+
+
+def _make_zero_noise_patcher(module):
+    """构造 patch(module.random.uniform)：噪声调用(上界=SCORE_RANDOM_NOISE_MAX)返回 0。
+
+    其他 uniform 调用（如片段时长随机）委托给一个独立的 Random 实例，
+    避免递归回已 patch 的全局函数。
+    """
+    import random as _stdlib_random
+
+    _fallback = _stdlib_random.Random()
+
+    def _fake_uniform(a, b):
+        if b == SCORE_RANDOM_NOISE_MAX:
+            return 0.0
+        return _fallback.uniform(a, b)
+
+    return patch.object(module.random, "uniform", _fake_uniform)
+
+
+def _patch_zero_noise_clips():
+    """消除 clips.py 排序噪声，其他 uniform 调用不受影响。"""
+    from app.api.routes.templates_editor import clips as clips_module
+
+    return _make_zero_noise_patcher(clips_module)
+
+
+def _patch_zero_noise_plan_service():
+    """消除 plan_generator_service.py 排序噪声，其他 uniform 调用不受影响。"""
+    from app.services import plan_generator_service as svc_module
+
+    return _make_zero_noise_patcher(svc_module)
+
+
+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_zero_noise_clips(),
+            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}"
+
+    def test_score_noise_causes_varied_selection(self):
+        """得分接近（差距 < SCORE_RANDOM_NOISE_MAX）的素材，多次生成的素材组合应有变化。
+
+        两条同等质量/时长/新鲜度的素材（use_count 相同），smart_match 得分一致，
+        噪声让两者的相对排名随机浮动，多次调用首个片段的素材分布应两者都出现。
+        """
+        from app.api.routes.templates_editor.clips import create_clips_from_assets_editor
+        from app.api.routes.templates_editor.schemas import ClipsFromAssetsRequest
+
+        def _get_asset(aid):
+            return _make_mock_asset_for_clips(aid, 30.0, 0)
+
+        mock_asset_repo = MagicMock()
+        mock_asset_repo.get = MagicMock(side_effect=_get_asset)
+
+        segments = [(0, 3.0, 5.0), (1, 3.0, 5.0)]
+
+        first_assets: set[str] = set()
+        for _ in range(30):
+            mock_plan_svc = MagicMock()
+            mock_plan_svc.replace_all_clips_transactional = MagicMock(return_value=2)
+            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_x", "a_y"],
+                    required_clips_count=2,
+                )
+                create_clips_from_assets_editor(
+                    template_id="tmpl-1",
+                    body=body,
+                    background_tasks=MagicMock(),
+                    plan_id=f"plan-noise-{len(first_assets)}-{_}",
+                    services=(MagicMock(), mock_plan_svc),
+                    asset_repo=mock_asset_repo,
+                    db=MagicMock(),
+                    current_user=_make_auth_user(),
+                )
+            clips_data = mock_plan_svc.replace_all_clips_transactional.call_args.args[1]
+            first_assets.add(clips_data[0]["asset_id"])
+
+        assert first_assets == {
+            "a_x",
+            "a_y",
+        }, f"噪声应使两条等分素材的排名浮动，30 次调用首个片段应覆盖两者，实际 {first_assets}"
+
+
+# ── 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)
+
+        with _patch_zero_noise_plan_service():
+            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_zero_noise_plan_service(),
+            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()
+
+
+class TestPlanGeneratorScoreNoise:
+    """验证一键生成路径的评分排序注入了随机噪声。"""
+
+    def test_equal_scores_produce_varied_order(self):
+        """两条 smart_match 得分相同的素材，多次排序的首位应覆盖两者。"""
+        from app.services.plan_generator_service import PlanGeneratorService
+
+        def _get_asset(aid):
+            asset = MagicMock()
+            asset.id = aid
+            asset.duration = 15.0
+            asset.quality_score = None
+            asset.created_at = None
+            asset.metadata = {"generation_use_count": 0}
+            return asset
+
+        mock_asset_repo = MagicMock()
+        mock_asset_repo.get = MagicMock(side_effect=_get_asset)
+        svc = PlanGeneratorService(MagicMock(), asset_repo=mock_asset_repo)
+
+        first_ids: set[str] = set()
+        for _ in range(30):
+            order = svc._sort_assets_by_smart_score(["equal_a", "equal_b"])
+            first_ids.add(order[0])
+
+        assert first_ids == {
+            "equal_a",
+            "equal_b",
+        }, f"噪声应使等分素材排名浮动，30 次排序首位应覆盖两者，实际 {first_ids}"
+
+    def test_large_score_gap_not_flipped(self):
+        """得分差距远大于噪声上限时，低分素材不会因噪声超过高分素材。
+
+        quality 100 vs 0 → quality 维度差距 40 分 > 噪声上限 20，
+        其余维度完全一致，50 次排序高质量素材必须始终排第一。
+        """
+        from app.services.plan_generator_service import PlanGeneratorService
+
+        def _get_asset(aid):
+            quality = {"top": 100.0, "bad": 0.0}[aid]
+            asset = MagicMock()
+            asset.id = aid
+            asset.duration = 15.0
+            asset.quality_score = quality
+            asset.created_at = None
+            asset.metadata = {"generation_use_count": 0}
+            return asset
+
+        mock_asset_repo = MagicMock()
+        mock_asset_repo.get = MagicMock(side_effect=_get_asset)
+        svc = PlanGeneratorService(MagicMock(), asset_repo=mock_asset_repo)
+
+        for _ in range(50):
+            order = svc._sort_assets_by_smart_score(["top", "bad"])
+            assert order[0] == "top", f"质量差距 40 分 > 噪声上限，top 应始终排第一，实际 {order}"