diff --git a/.gitea/workflows/ci-base-image.yml b/.gitea/workflows/ci-base-image.yml new file mode 100644 index 000000000..fe3c443e9 --- /dev/null +++ b/.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" diff --git a/.gitea/workflows/pr-auto-scan.yml b/.gitea/workflows/pr-auto-scan.yml index f362e74de..684258415 100644 --- a/.gitea/workflows/pr-auto-scan.yml +++ b/.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: diff --git a/apps/api/app/api/routes/templates_editor/clips.py b/apps/api/app/api/routes/templates_editor/clips.py index 59ce092e6..98dcee836 100755 --- a/apps/api/app/api/routes/templates_editor/clips.py +++ b/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, @@ -43,7 +47,14 @@ from packages.adapters.sqlalchemy_impl.template_clip_config_repository import ( from packages.adapters.sqlalchemy_impl.template_repository import ( SQLAlchemyTemplateRepository, ) -from packages.domain.plan_generator_utils import _calc_random_start_time +from packages.domain.plan_generator_utils import ( + _calc_random_start_time, + build_scene_segments, + extract_scene_points_from_metadata, + pick_scene_aware_start, + pick_start_in_scene_segment, +) +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 @@ -470,6 +481,12 @@ def _recommended_time_conflicts( return False +# 向后兼容别名：镜头段构建/段内取点逻辑已下沉到 packages.domain.plan_generator_utils， +# 旧测试与历史代码仍按 clips._build_scene_segments / _pick_start_in_scene_segment 导入 +_build_scene_segments = build_scene_segments +_pick_start_in_scene_segment = pick_start_in_scene_segment + + def _get_mediakit_recommendations( asset_ids: list[str], asset_repo, @@ -582,6 +599,47 @@ 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 +684,26 @@ 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] = {} + # 素材 metadata 中缓存的场景切换点（由后台 MediaKit SceneChange 检测写入）： + # 有缓存时片段起点从随机镜头段中选取（不同片段来自不同镜头），无缓存回退随机起点 + asset_scene_points: dict[str, list[float]] = {} 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 + # 读取场景切换点缓存（新素材未检测过时为 None，走随机起点兜底） + cached_points = extract_scene_points_from_metadata(getattr(asset, "metadata", None)) + if cached_points: + asset_scene_points[asset_id] = cached_points + logger.info( + "from-assets 场景缓存命中: %d/%d 个素材有场景切换点", + len(asset_scene_points), + len(unique_asset_ids), + ) # 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 +736,52 @@ 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 @@ -688,16 +795,30 @@ def create_clips_from_assets_editor( candidate, ) 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） - candidate_start = _calc_random_start_time( - candidate, - candidate_duration, - asset_durations, - used_segments, - on_exhausted=reuse_cb, - ) + # 起始时间选取（不调用 MediaKit，保证接口快速返回）： + # 1) 素材有场景切换点缓存时，优先从随机镜头段中选起点（不同片段来自不同镜头， + # 画面内容本质不同），与 used_segments 做冲突避让（含 1.5s 边缘间隙） + # 2) 无缓存 / 镜头段全冲突 → _calc_random_start_time 随机起点兜底； + # 100 次避不开历史区间时走受控复用回调（复用片段累加 reused_durations， + # 回调内部预判复用后占比超 10% 则拒绝并返回 None） + candidate_start = None + if candidate in asset_scene_points: + candidate_start = pick_scene_aware_start( + candidate, + candidate_duration, + asset_durations, + asset_scene_points, + used_segments, + edge_gap=SEGMENT_EDGE_GAP, + ) + if candidate_start is None: + candidate_start = _calc_random_start_time( + candidate, + candidate_duration, + asset_durations, + used_segments, + on_exhausted=reuse_cb, + ) if candidate_start is None: # 该素材可用区间耗尽且复用被闸门/use_count 上限拒绝 → 尝试下一素材 logger.info( @@ -712,6 +833,7 @@ 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 +849,7 @@ 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 +857,9 @@ 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) @@ -754,11 +879,31 @@ def create_clips_from_assets_editor( unique_asset_ids, ) - # 6. 立即返回响应 + # 6. 估算成片内部重复率（本条成片中同一素材的重叠片段时长占比） + dup_rate = _calc_plan_internal_duplicate_rate(clips_data) + duplicate_warning = None + if dup_rate > 50: + duplicate_warning = f"查重率 {dup_rate:.1f}% 超过50%，建议更换素材或模板" + logger.warning( + "from-assets 成片查重率超标: plan_id=%s dup_rate=%.1f%%", + plan_id, + dup_rate, + ) + + # 7. 素材耗尽提示 + exhaustion_warning = None + if all_assets_exhausted and created_count < len(segments): + exhaustion_warning = ( + "素材可切区间不足，部分片段使用了复用素材。" "建议：1) 补充更多素材到素材库 2) 使用不同的素材组合生成" + ) + + # 8. 立即返回响应 return ClipsFromAssetsResponse( created_count=created_count, plan_id=plan_id, clip_ids=[], + duplicate_warning=duplicate_warning, + exhaustion_warning=exhaustion_warning, ) @@ -766,7 +911,15 @@ 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 +941,6 @@ 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 +963,16 @@ 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 +981,22 @@ 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 +1004,177 @@ 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]] = [] + # 先查素材 metadata 中的场景点缓存：命中则直接复用，跳过 MediaKit 检测 + # （缓存由本任务首次检测后写入，跨任务/跨 plan 复用） + cached_points = extract_scene_points_from_metadata(getattr(asset, "metadata", None)) + if cached_points: + scene_segments = build_scene_segments(cached_points, asset_total) + logger.info( + "后台任务: 命中场景点缓存: asset_id=%s scenes=%d", + asset_id, + len(scene_segments), + ) + + if not scene_segments and 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 + # 检测结果写入素材 metadata 缓存：首次生成用随机起点， + # 检测完成后后续生成的渲染前同步路径即可读缓存选镜头段 + try: + existing_meta = dict(getattr(asset, "metadata", None) or {}) + existing_meta["scene_change_points"] = scene_changes + asset.metadata = existing_meta + asset_repo.update(asset) + logger.info( + "后台任务: 场景点已写入素材缓存: asset_id=%s points=%d", + asset_id, + len(scene_changes), + ) + except Exception as cache_err: + # 缓存写入失败不影响本次片段更新 + logger.warning( + "后台任务: 场景点缓存写入失败: asset_id=%s error=%s", + asset_id, + cache_err, + ) + + # 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) diff --git a/apps/api/app/api/routes/templates_editor/schemas.py b/apps/api/app/api/routes/templates_editor/schemas.py index 8d4f036b9..5757c8866 100755 --- a/apps/api/app/api/routes/templates_editor/schemas.py +++ b/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 ──────────────────────────────────────────────────────────────── diff --git a/apps/api/app/services/asset_segment_tracker.py b/apps/api/app/services/asset_segment_tracker.py index 06b7273c6..c9122bb02 100644 --- a/apps/api/app/services/asset_segment_tracker.py +++ b/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``。 diff --git a/apps/api/app/services/plan_generator_service.py b/apps/api/app/services/plan_generator_service.py index 12b1c0015..de0b9b938 100755 --- a/apps/api/app/services/plan_generator_service.py +++ b/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 @@ -29,9 +30,11 @@ from packages.domain.editing_mode import EditingMode from packages.domain.plan_generator_utils import ( create_clips_from_configs, distribute_assets, + extract_scene_points_from_metadata, 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__) @@ -218,16 +221,64 @@ 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。 """ + # 预览随机模式：素材顺序已 shuffle，纯随机起点即可，不读 DB 评分/缓存 + asset_scene_points: dict[str, list[float]] = {} + if not random_selection: + # 正式生成：smart_match 评分排序（高分优先）+ 场景切换点缓存 + if self._asset_repo: + asset_ids = self._sort_assets_by_smart_score(asset_ids) + # 读取素材 metadata 中的场景切换点缓存（后台 SceneChange 检测写入）： + # 有缓存的素材片段起点从随机镜头段选取，无缓存走随机起点兜底 + asset_scene_points = self._fetch_asset_scene_points(asset_ids) + distribute_assets( clips, asset_ids, editing_mode, random_selection=random_selection, asset_durations=asset_durations, + asset_scene_points=asset_scene_points, ) + def _fetch_asset_scene_points(self, asset_ids: List[str]) -> dict[str, list[float]]: + """从素材 metadata 读取场景切换点缓存（无缓存的素材不包含在结果中）。""" + points_map: dict[str, list[float]] = {} + if not self._asset_repo: + return points_map + for asset_id in asset_ids: + asset = self._asset_repo.get(asset_id) + if asset: + points = extract_scene_points_from_metadata(getattr(asset, "metadata", None)) + if points: + points_map[asset_id] = points + return points_map + + 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. diff --git a/apps/web/.tscache/tsconfig.tsbuildinfo b/apps/web/.tscache/tsconfig.tsbuildinfo new file mode 100644 index 000000000..4f4e339f1 --- /dev/null +++ b/apps/web/.tscache/tsconfig.tsbuildinfo @@ -0,0 +1 @@ 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"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": { diff --git a/apps/web/src/api/products/types.ts b/apps/web/src/api/products/types.ts index 83a8af804..9b4fa758d 100644 --- a/apps/web/src/api/products/types.ts +++ b/apps/web/src/api/products/types.ts @@ -71,4 +71,5 @@ export interface VideoItem { generation_params: Record download_url: string generated_at: string + duplicate_rate?: number } diff --git a/apps/web/src/api/products/utils.ts b/apps/web/src/api/products/utils.ts index 00fd89ef3..1293a6cd2 100644 --- a/apps/web/src/api/products/utils.ts +++ b/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, } } diff --git a/apps/web/src/pages/generate/GeneratePage.tsx b/apps/web/src/pages/generate/GeneratePage.tsx index ffd783cd5..f03f84d7a 100644 --- a/apps/web/src/pages/generate/GeneratePage.tsx +++ b/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 && ( diff --git a/apps/web/src/pages/generate/components/FrontendPreviewPlayer.tsx b/apps/web/src/pages/generate/components/FrontendPreviewPlayer.tsx index d72a689d1..61ce703f9 100644 --- a/apps/web/src/pages/generate/components/FrontendPreviewPlayer.tsx +++ b/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 = ({ serverClips, voiceAudioUrl, titleSettings, + onTitlePositionChange, }) => { const segments = useMemo( () => buildPlaybackSegments(assets, template, serverClips), @@ -126,6 +130,69 @@ const FrontendPreviewPlayer: React.FC = ({ 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(null) + const handleTitlePointerDown = useCallback( + (e: React.PointerEvent) => { + 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) => { + 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) => { + 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(null) const [containerHeight, setContainerHeight] = useState(0) useEffect(() => { @@ -524,15 +591,36 @@ const FrontendPreviewPlayer: React.FC = ({
= ({ presets, activePreset, @@ -27,18 +58,52 @@ const TitlePresetsGrid: React.FC = ({
{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 ( ) diff --git a/apps/web/src/pages/generate/constants.ts b/apps/web/src/pages/generate/constants.ts index e13061fdd..6dbce4752 100644 --- a/apps/web/src/pages/generate/constants.ts +++ b/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)", }, }, ] diff --git a/apps/web/src/pages/generate/generate.css b/apps/web/src/pages/generate/generate.css index 5675cf8f1..d55572b93 100644 --- a/apps/web/src/pages/generate/generate.css +++ b/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; } diff --git a/apps/web/src/pages/generate/hooks/step2-materials/useSmartMatch.ts b/apps/web/src/pages/generate/hooks/step2-materials/useSmartMatch.ts index e297b4626..3be6c288e 100755 --- a/apps/web/src/pages/generate/hooks/step2-materials/useSmartMatch.ts +++ b/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)) } diff --git a/apps/web/src/pages/generate/hooks/useCanvasPlayer.ts b/apps/web/src/pages/generate/hooks/useCanvasPlayer.ts index 10d14df0b..2bb6c1f71 100644 --- a/apps/web/src/pages/generate/hooks/useCanvasPlayer.ts +++ b/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 diff --git a/apps/web/src/pages/generate/hooks/useGenerateFormState/index.ts b/apps/web/src/pages/generate/hooks/useGenerateFormState/index.ts index 255825343..feac0db50 100755 --- a/apps/web/src/pages/generate/hooks/useGenerateFormState/index.ts +++ b/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 { diff --git a/apps/web/src/pages/generate/hooks/useGenerateVideo.ts b/apps/web/src/pages/generate/hooks/useGenerateVideo.ts index 6ed60aefc..e131d0f63 100755 --- a/apps/web/src/pages/generate/hooks/useGenerateVideo.ts +++ b/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, diff --git a/apps/web/src/pages/generate/hooks/useStep4Title/useTitleStyleUpdaters.ts b/apps/web/src/pages/generate/hooks/useStep4Title/useTitleStyleUpdaters.ts index 49ef2685d..5a7934c87 100644 --- a/apps/web/src/pages/generate/hooks/useStep4Title/useTitleStyleUpdaters.ts +++ b/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, diff --git a/apps/web/src/pages/generate/types.ts b/apps/web/src/pages/generate/types.ts index 88be13f77..b279973aa 100644 --- a/apps/web/src/pages/generate/types.ts +++ b/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 ── */ diff --git a/apps/web/src/pages/products/components/ProductCard.tsx b/apps/web/src/pages/products/components/ProductCard.tsx index 8f1ff35ad..5a447ab5e 100644 --- a/apps/web/src/pages/products/components/ProductCard.tsx +++ b/apps/web/src/pages/products/components/ProductCard.tsx @@ -221,7 +221,7 @@ export const ProductCard: React.FC = ({ product.duplicateRate > 0 ? ` ${dupClass}` : "" }`} > - 查重率：{product.duplicateRate > 0 ? `${product.duplicateRate.toFixed(1)}%` : "-"} + 查重率：{product.duplicateRate != null ? `${product.duplicateRate.toFixed(1)}%` : "-"}
diff --git a/apps/web/src/pages/products/products.css b/apps/web/src/pages/products/products.css index 1df3cdc38..58bae02de 100644 --- a/apps/web/src/pages/products/products.css +++ b/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); diff --git a/apps/worker/video_processing/dedup.py b/apps/worker/video_processing/dedup.py index 16992ab30..ecbeec613 100755 --- a/apps/worker/video_processing/dedup.py +++ b/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] diff --git a/apps/worker/video_processing/dedup_helpers.py b/apps/worker/video_processing/dedup_helpers.py index 8f17d7ac3..efcc2072f 100755 --- a/apps/worker/video_processing/dedup_helpers.py +++ b/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: diff --git a/apps/worker/video_processing/unified_render_service.py b/apps/worker/video_processing/unified_render_service.py index 3906869b0..4dd3323a4 100755 --- a/apps/worker/video_processing/unified_render_service.py +++ b/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 ────────────────────────────────────────────────── diff --git a/packages/domain/plan_generator_utils.py b/packages/domain/plan_generator_utils.py index 3e57596ac..446f6da21 100755 --- a/packages/domain/plan_generator_utils.py +++ b/packages/domain/plan_generator_utils.py @@ -27,6 +27,137 @@ DEFAULT_INTRO_DURATION = 3.0 DEFAULT_OUTRO_DURATION = 3.0 +# ── SceneChange 镜头段工具 ──────────────────────────────────────────────────── + + +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), ...]，仅保留长度 >= 0.5s 的段 + """ + 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 _segments_overlap( + start: float, + duration: float, + used: list[tuple[float, float]], + edge_gap: float = 0.0, +) -> bool: + """候选区间 [start, start+duration] 是否与已用区间冲突（含边缘间隙扩边）。""" + end = start + duration + for used_start, used_end in used: + if start < used_end + edge_gap and end > used_start - edge_gap: + return True + return False + + +def pick_scene_aware_start( + asset_id: str, + clip_duration: float, + asset_durations: dict[str, float], + asset_scene_points: dict[str, list[float]] | None, + used_segments: dict[str, list[tuple[float, float]]], + *, + edge_gap: float = 0.0, +) -> float | None: + """基于缓存的场景切换点，从随机镜头段中选取不冲突的起始时间. + + 流程： + 1. 读取 asset_scene_points 中该素材的场景切换点缓存 → 构建镜头段 + 2. random.shuffle 镜头段（保证同一素材多次生成选不同镜头，而非固定第N段） + 3. 依次尝试：段内随机取点 → 越界检查 → 与 used_segments 冲突检查 + 4. 全部冲突/无缓存 → 返回 None，由调用方回退 _calc_random_start_time + + Args: + asset_id: 素材 ID + clip_duration: 片段时长（秒） + asset_durations: 素材 ID -> 总时长 + asset_scene_points: 素材 ID -> 场景切换点列表（metadata 缓存） + used_segments: 素材 ID -> 已用区间列表（冲突避让） + edge_gap: 冲突判定的边缘间隙（秒），已用区间按 [s-gap, e+gap] 扩边 + """ + asset_total = (asset_durations or {}).get(asset_id) + if not asset_total or asset_total <= 0: + return None + scene_points = (asset_scene_points or {}).get(asset_id) + if not scene_points: + return None + used = used_segments.get(asset_id, []) if used_segments else [] + + scene_segments = build_scene_segments(scene_points, asset_total) + if not scene_segments: + return None + random.shuffle(scene_segments) + + for seg_start, seg_end in scene_segments: + candidate = pick_start_in_scene_segment(seg_start, seg_end, clip_duration) + if candidate is None: + continue + # 越界检查（防御：场景点末尾段理论上不越界，metadata 脏数据兜底） + if candidate + clip_duration > asset_total: + continue + # 与已用区间冲突检查 + if _segments_overlap(candidate, clip_duration, used, edge_gap): + continue + return candidate + + return None + + +def extract_scene_points_from_metadata(metadata: object) -> list[float] | None: + """从素材 metadata 中提取并校验场景切换点缓存. + + 合法缓存：list 类型、至少 2 个数值点、单调非负；否则返回 None（按未缓存处理）。 + """ + if not isinstance(metadata, dict): + return None + points = metadata.get("scene_change_points") + if not isinstance(points, list) or len(points) < 2: + return None + try: + cleaned = [float(p) for p in points] + except (TypeError, ValueError): + return None + if any(p < 0 for p in cleaned): + return None + cleaned = sorted(cleaned) + if cleaned[0] != 0.0: + cleaned.insert(0, 0.0) + return cleaned + + # ── 素材分配 ──────────────────────────────────────────────────────────────── @@ -37,6 +168,7 @@ def distribute_assets( *, random_selection: bool = False, asset_durations: dict[str, float] | None = None, + asset_scene_points: dict[str, list[float]] | None = None, ) -> None: """按 editing_mode 将素材分配到 clips（就地修改）. @@ -46,12 +178,16 @@ def distribute_assets( - VOICE_OVER: 素材→main clips (B-roll) - VOICE_PIP: 第1个→background, 第2个→corner_voice, 其余→b_roll + start_time 选取：素材 metadata 中有场景切换点缓存时，优先从随机镜头段 + 取起点（不同片段来自不同镜头）；无缓存或镜头段都冲突时回退随机起点。 + Args: clips: 剪辑片段列表（就地修改 asset_id） asset_ids: 素材 ID 列表 editing_mode: 剪辑模式字符串 random_selection: 是否随机选择素材（用于预览生成） - asset_durations: 素材 ID -> 时长（秒）映射，用于设置随机 start_time + asset_durations: 素材 ID -> 时长（秒）映射，用于设置 start_time + asset_scene_points: 素材 ID -> 场景切换点列表（metadata 缓存） """ if not asset_ids or not clips: return @@ -62,22 +198,56 @@ def distribute_assets( random.shuffle(asset_ids) if editing_mode == EditingMode.ONE_TAKE.value: - _distribute_one_take(clips, asset_ids, asset_durations) + _distribute_one_take(clips, asset_ids, asset_durations, asset_scene_points) elif editing_mode == EditingMode.PIP.value: - _distribute_pip(clips, asset_ids, asset_durations) + _distribute_pip(clips, asset_ids, asset_durations, asset_scene_points) elif editing_mode == EditingMode.VOICE_OVER.value: - _distribute_voice_over(clips, asset_ids, asset_durations) + _distribute_voice_over(clips, asset_ids, asset_durations, asset_scene_points) elif editing_mode == EditingMode.VOICE_PIP.value: - _distribute_voice_pip(clips, asset_ids, asset_durations) + _distribute_voice_pip(clips, asset_ids, asset_durations, asset_scene_points) else: # 未知模式，退化为 one_take - _distribute_one_take(clips, asset_ids, asset_durations) + _distribute_one_take(clips, asset_ids, asset_durations, asset_scene_points) + + +def _resolve_start_time( + asset_id: str, + clip_duration: float, + asset_durations: dict[str, float] | None, + used_segments: dict[str, list[tuple[float, float]]], + asset_scene_points: dict[str, list[float]] | None = None, + on_exhausted: Callable[[str, float], tuple[float, float] | None] | None = None, +) -> float | None: + """选取片段起点：场景缓存优先（随机镜头段），无缓存/全冲突回退随机起点. + + 场景路径与随机路径共享 used_segments 冲突避让；场景路径返回 None 时 + （无缓存、镜头段全冲突）回退 _calc_random_start_time，其受控复用逻辑 + （on_exhausted）不受影响。 + """ + if asset_scene_points and asset_scene_points.get(asset_id): + scene_start = pick_scene_aware_start( + asset_id, + clip_duration, + asset_durations or {}, + asset_scene_points, + used_segments, + ) + if scene_start is not None: + return scene_start + return _calc_random_start_time( + asset_id, + clip_duration, + asset_durations, + used_segments, + on_exhausted=on_exhausted, + ) def _distribute_one_take( clips: List[EditPlanClip], asset_ids: List[str], asset_durations: dict[str, float] | None = None, + asset_scene_points: dict[str, list[float]] | None = None, ) -> None: """ONE_TAKE: 素材按顺序依次分配给 main 类型 clips.""" used_segments: dict[str, list[tuple[float, float]]] = {} @@ -85,7 +255,9 @@ def _distribute_one_take( for i, clip in enumerate(main_clips): if i < len(asset_ids): asset_id = asset_ids[i] - start_time = _calc_random_start_time(asset_id, clip.duration, asset_durations, used_segments) + start_time = _resolve_start_time( + asset_id, clip.duration, asset_durations, used_segments, asset_scene_points + ) clip.assign_asset(asset_id, start_time=start_time) # Record used segment if start_time is not None and asset_durations is not None: @@ -98,6 +270,7 @@ def _distribute_pip( clips: List[EditPlanClip], asset_ids: List[str], asset_durations: dict[str, float] | None = None, + asset_scene_points: dict[str, list[float]] | None = None, ) -> None: """PIP: 第1个素材→main(全屏背景)，其余→overlay clips.""" used_segments: dict[str, list[tuple[float, float]]] = {} @@ -105,7 +278,9 @@ def _distribute_pip( main_clips = [c for c in clips if c.clip_type == ClipType.MAIN.value] if main_clips and asset_ids: asset_id = asset_ids[0] - start_time = _calc_random_start_time(asset_id, main_clips[0].duration, asset_durations, used_segments) + start_time = _resolve_start_time( + asset_id, main_clips[0].duration, asset_durations, used_segments, asset_scene_points + ) main_clips[0].assign_asset(asset_id, start_time=start_time) # Record used segment if start_time is not None and asset_durations is not None: @@ -119,7 +294,9 @@ def _distribute_pip( for i, clip in enumerate(overlay_clips): if i < len(remaining): asset_id = remaining[i] - start_time = _calc_random_start_time(asset_id, clip.duration, asset_durations, used_segments) + start_time = _resolve_start_time( + asset_id, clip.duration, asset_durations, used_segments, asset_scene_points + ) clip.assign_asset(asset_id, start_time=start_time) # Record used segment if start_time is not None and asset_durations is not None: @@ -132,6 +309,7 @@ def _distribute_voice_over( clips: List[EditPlanClip], asset_ids: List[str], asset_durations: dict[str, float] | None = None, + asset_scene_points: dict[str, list[float]] | None = None, ) -> None: """VOICE_OVER: 素材→main clips (B-roll).""" used_segments: dict[str, list[tuple[float, float]]] = {} @@ -139,7 +317,9 @@ def _distribute_voice_over( for i, clip in enumerate(main_clips): if i < len(asset_ids): asset_id = asset_ids[i] - start_time = _calc_random_start_time(asset_id, clip.duration, asset_durations, used_segments) + start_time = _resolve_start_time( + asset_id, clip.duration, asset_durations, used_segments, asset_scene_points + ) clip.assign_asset(asset_id, start_time=start_time) # Record used segment if start_time is not None and asset_durations is not None: @@ -152,6 +332,7 @@ def _distribute_voice_pip( clips: List[EditPlanClip], asset_ids: List[str], asset_durations: dict[str, float] | None = None, + asset_scene_points: dict[str, list[float]] | None = None, ) -> None: """VOICE_PIP: 第1个→background, 第2个→corner_voice, 其余→b_roll.""" used_segments: dict[str, list[tuple[float, float]]] = {} @@ -164,7 +345,9 @@ def _distribute_voice_pip( # 第1个 → background if idx < len(asset_ids) and bg_clips: asset_id = asset_ids[idx] - start_time = _calc_random_start_time(asset_id, bg_clips[0].duration, asset_durations, used_segments) + start_time = _resolve_start_time( + asset_id, bg_clips[0].duration, asset_durations, used_segments, asset_scene_points + ) bg_clips[0].assign_asset(asset_id, start_time=start_time) # Record used segment if start_time is not None and asset_durations is not None: @@ -176,7 +359,9 @@ def _distribute_voice_pip( # 第2个 → corner_voice if idx < len(asset_ids) and voice_clips: asset_id = asset_ids[idx] - start_time = _calc_random_start_time(asset_id, voice_clips[0].duration, asset_durations, used_segments) + start_time = _resolve_start_time( + asset_id, voice_clips[0].duration, asset_durations, used_segments, asset_scene_points + ) voice_clips[0].assign_asset(asset_id, start_time=start_time) # Record used segment if start_time is not None and asset_durations is not None: @@ -190,7 +375,9 @@ def _distribute_voice_pip( for i, clip in enumerate(broll_clips): if i < len(remaining): asset_id = remaining[i] - start_time = _calc_random_start_time(asset_id, clip.duration, asset_durations, used_segments) + start_time = _resolve_start_time( + asset_id, clip.duration, asset_durations, used_segments, asset_scene_points + ) clip.assign_asset(asset_id, start_time=start_time) # Record used segment if start_time is not None and asset_durations is not None: diff --git a/packages/domain/smart_match.py b/packages/domain/smart_match.py index a678265b9..b639a91f0 100755 --- a/packages/domain/smart_match.py +++ b/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: diff --git a/packages/domain/xfade_builder.py b/packages/domain/xfade_builder.py index c5ec2a505..a4345e7c3 100755 --- a/packages/domain/xfade_builder.py +++ b/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) diff --git a/packages/shared/mediakit_client.py b/packages/shared/mediakit_client.py index 94557cbe5..80c63f1ae 100755 --- a/packages/shared/mediakit_client.py +++ b/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, diff --git a/requirements-base.txt b/requirements-base.txt index d29b06545..1eb77c820 100644 --- a/requirements-base.txt +++ b/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 diff --git a/requirements-dev.txt b/requirements-dev.txt index 1f7dbf57b..dd88dd618 100755 --- a/requirements-dev.txt +++ b/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 diff --git a/scripts/ci/auto_approve.sh b/scripts/ci/auto_approve.sh index 5736898f1..c94988901 100644 --- a/scripts/ci/auto_approve.sh +++ b/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 \ No newline at end of file diff --git a/scripts/ci/ensure_persistent_builder.sh b/scripts/ci/ensure_persistent_builder.sh index 0f3c45bdc..3e37f2203 100755 --- a/scripts/ci/ensure_persistent_builder.sh +++ b/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__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: $BUILDKIT_CONTAINER（跳过 config 同步）" +fi + diff --git a/scripts/ci/pr_auto_scan.py b/scripts/ci/pr_auto_scan.py index fc422893e..37626c916 100644 --- a/scripts/ci/pr_auto_scan.py +++ b/scripts/ci/pr_auto_scan.py @@ -303,9 +303,10 @@ def main(): "CI/CD Pipeline / CI Gate (pull_request)", ] REQUIRED_CONTEXTS_APPROVE = [ - "CI/CD Pipeline / Validate - Code Quality (pull_request)", - "CI/CD Pipeline / Validate - Type Check (mypy) (pull_request)", - "CI/CD Pipeline / Validate - Migration (alembic) (pull_request)", + # CI 优化后 job 名称（2026-08）：Code Quality 拆分为 Style+Security，Type Check+Migration 合并为 Python + "CI/CD Pipeline / Validate - Style (pull_request)", + "CI/CD Pipeline / Validate - Security (pull_request)", + "CI/CD Pipeline / Validate - Python (mypy + alembic) (pull_request)", "CI/CD Pipeline / Frontend Lint (pull_request)", ] FRONTEND_ONLY_CONTEXT = [ diff --git a/scripts/ci/run_integration_tests.sh b/scripts/ci/run_integration_tests.sh index 192b538c4..0390285a8 100755 --- a/scripts/ci/run_integration_tests.sh +++ b/scripts/ci/run_integration_tests.sh @@ -197,8 +197,8 @@ if [ "$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='${SHARED_PG_PASSWORD}', dbname='postgres') conn.autocommit = True cur = conn.cursor() @@ -344,4 +344,4 @@ python3 scripts/ci_coverage_summary.py set -e echo "" -echo "=== CI Integration Tests 全部通过 ✅ ===" +echo "=== CI Integration Tests 全部通过 ✅ ===" \ No newline at end of file diff --git a/scripts/ci/run_unit_tests.sh b/scripts/ci/run_unit_tests.sh index 4ba9466cc..0084e3c59 100755 --- a/scripts/ci/run_unit_tests.sh +++ b/scripts/ci/run_unit_tests.sh @@ -1,77 +1,136 @@ #!/bin/bash # CI Unit Tests Job 主脚本 -# 包含：依赖安装、增量测试选择、覆盖率测试、diff覆盖率门禁 +# 包含：依赖缓存、增量测试选择、覆盖率测试、diff覆盖率门禁 set -eu JOB_NAME="${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 diff --git a/scripts/ci/run_validate.sh b/scripts/ci/run_validate.sh index c85c299a1..94fdfae93 100755 --- a/scripts/ci/run_validate.sh +++ b/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 \"$CI_DB_NAME\" WITH (FORCE)') diff --git a/scripts/ci/validate_migration.sh b/scripts/ci/validate_migration.sh index 20388fc18..6d604406c 100755 --- a/scripts/ci/validate_migration.sh +++ b/scripts/ci/validate_migration.sh @@ -169,8 +169,8 @@ if [ "$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)') diff --git a/scripts/ci_staging_deploy.sh b/scripts/ci_staging_deploy.sh index 5b055c68b..70aa0955c 100755 --- a/scripts/ci_staging_deploy.sh +++ b/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 diff --git a/scripts/ci_staging_healthcheck.sh b/scripts/ci_staging_healthcheck.sh index f8609f956..79c30fa80 100644 --- a/scripts/ci_staging_healthcheck.sh +++ b/scripts/ci_staging_healthcheck.sh @@ -187,7 +187,7 @@ health_check() { return 0 fi - sleep 5 + sleep 3 done # 超时了 diff --git a/tests/unit/test_asset_availability.py b/tests/unit/test_asset_availability.py index c37874394..4192a5ca8 100755 --- a/tests/unit/test_asset_availability.py +++ b/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。 diff --git a/tests/unit/test_asset_segment_tracker.py b/tests/unit/test_asset_segment_tracker.py index 9174226a0..54f66b73f 100644 --- a/tests/unit/test_asset_segment_tracker.py +++ b/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 diff --git a/tests/unit/test_dedup_helpers_user_id.py b/tests/unit/test_dedup_helpers_user_id.py new file mode 100644 index 000000000..4584fc3f0 --- /dev/null +++ b/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 diff --git a/tests/unit/test_duplicate_rate.py b/tests/unit/test_duplicate_rate.py index b9d6fd2ed..f92a67a85 100644 --- a/tests/unit/test_duplicate_rate.py +++ b/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.""" diff --git a/tests/unit/test_duration_compensation.py b/tests/unit/test_duration_compensation.py new file mode 100644 index 000000000..abd4c08da --- /dev/null +++ b/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 diff --git a/tests/unit/test_editor_clips_random_start.py b/tests/unit/test_editor_clips_random_start.py index bba35e223..4d7489b8d 100644 --- a/tests/unit/test_editor_clips_random_start.py +++ b/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, diff --git a/tests/unit/test_mediakit_conflicts.py b/tests/unit/test_mediakit_conflicts.py index 5c5a7cf96..c9f257be7 100755 --- a/tests/unit/test_mediakit_conflicts.py +++ b/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 diff --git a/tests/unit/test_mediakit_smart_clips.py b/tests/unit/test_mediakit_smart_clips.py index 61f114d28..bdfadb417 100644 --- a/tests/unit/test_mediakit_smart_clips.py +++ b/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。""" diff --git a/tests/unit/test_plan_generator.py b/tests/unit/test_plan_generator.py index 10d02f62c..37544c067 100755 --- a/tests/unit/test_plan_generator.py +++ b/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) diff --git a/tests/unit/test_scene_change_prerender.py b/tests/unit/test_scene_change_prerender.py new file mode 100644 index 000000000..3f7d5f25a --- /dev/null +++ b/tests/unit/test_scene_change_prerender.py @@ -0,0 +1,368 @@ +"""测试 SceneChange 场景检测前置到渲染前 + 场景点缓存读写。 + +验证： +- 场景点缓存读取（extract_scene_points_from_metadata）：合法/非法/脏数据 +- pick_scene_aware_start：随机镜头段选取、冲突避让、shuffle 随机化、无缓存回退 None +- from-assets 路径：metadata 有 scene_change_points 时，start_time 落在镜头段内 +- 一键生成路径：distribute_assets 传入 asset_scene_points 时使用镜头段 +- 后台任务：检测结果写入素材 metadata（缓存） +""" + +from __future__ import annotations + +import os +import sys +from pathlib import Path +from unittest.mock import MagicMock, patch + +os.environ.setdefault("JWT_SECRET_KEY", "unit-test-secret-key-for-testing") +os.environ.setdefault("DATABASE_URL", "sqlite:///test.db") + +sys.path.insert(0, str(Path(__file__).resolve().parents[2] / "apps" / "api")) + +import pytest + +from packages.domain.plan_generator_utils import ( + _calc_random_start_time, + build_scene_segments, + distribute_assets, + extract_scene_points_from_metadata, + pick_scene_aware_start, +) + +# ── metadata 缓存解析 ───────────────────────────────────────────────────────── + + +class TestExtractScenePoints: + def test_valid_points(self): + md = {"scene_change_points": [0.0, 3.2, 7.8, 12.5]} + assert extract_scene_points_from_metadata(md) == [0.0, 3.2, 7.8, 12.5] + + def test_missing_returns_none(self): + assert extract_scene_points_from_metadata({}) is None + assert extract_scene_points_from_metadata(None) is None + assert extract_scene_points_from_metadata("not-a-dict") is None + + def test_empty_list_returns_none(self): + assert extract_scene_points_from_metadata({"scene_change_points": []}) is None + assert extract_scene_points_from_metadata({"scene_change_points": [0.0]}) is None + + def test_dirty_data_returns_none(self): + assert extract_scene_points_from_metadata({"scene_change_points": ["a", 1.0]}) is None + + def test_auto_prepends_zero(self): + result = extract_scene_points_from_metadata({"scene_change_points": [3.2, 7.8]}) + assert result == [0.0, 3.2, 7.8] + + def test_sorts_unsorted(self): + result = extract_scene_points_from_metadata({"scene_change_points": [0.0, 12.5, 3.2, 7.8]}) + assert result == [0.0, 3.2, 7.8, 12.5] + + def test_negative_rejected(self): + assert extract_scene_points_from_metadata({"scene_change_points": [-1.0, 3.2]}) is None + + +# ── 镜头段选取 ──────────────────────────────────────────────────────────────── + + +class TestPickSceneAwareStart: + def test_start_within_some_scene_segment(self): + """有缓存时，起点落在某个镜头段内部。""" + points = [0.0, 5.0, 10.0, 15.0] + durations = {"a1": 18.0} + scene_points = {"a1": points} + used: dict = {} + start = pick_scene_aware_start("a1", 3.0, durations, scene_points, used) + assert start is not None + segments = build_scene_segments(points, 18.0) + assert any(seg_start <= start and start + 3.0 <= seg_end for seg_start, seg_end in segments) + + def test_no_cache_returns_none(self): + """无缓存返回 None（调用方回退随机起点）。""" + result = pick_scene_aware_start("a1", 3.0, {"a1": 18.0}, {}, {}) + assert result is None + + def test_bounds_respected(self): + """起点 + 片段时长不超过素材总时长。""" + points = [0.0, 5.0, 10.0, 15.0] + for _ in range(30): + start = pick_scene_aware_start("a1", 4.0, {"a1": 18.0}, {"a1": points}, {}) + assert start is not None + assert start + 4.0 <= 18.0 + 1e-6 + + def test_conflict_avoidance(self): + """所有镜头段都被占满时返回 None（回退随机路径）。""" + # 3 段各 6s，片段 5s；把所有段占满（[0,5.5] [5.5,11] 覆盖段1/2，段3太短放不下5s） + points = [0.0, 6.0, 12.0] + used = {"a1": [(0.0, 5.6), (6.0, 11.6)]} + # 段3 [12, 18] 可用 → 应返回其中起点 + start = pick_scene_aware_start("a1", 5.0, {"a1": 18.0}, {"a1": points}, used) + assert start is not None + assert start >= 12.0 + + def test_all_segments_conflict_returns_none(self): + """全部镜头段都冲突时返回 None。""" + points = [0.0, 6.0, 12.0] + # 占满整个素材 + used = {"a1": [(0.0, 18.0)]} + start = pick_scene_aware_start("a1", 5.0, {"a1": 18.0}, {"a1": points}, used) + assert start is None + + def test_shuffle_produces_varied_segments(self): + """镜头段顺序被 shuffle：30 次选取，起点分布应覆盖多个镜头段。""" + points = [0.0, 5.0, 10.0, 15.0] + observed: set[int] = set() + for _ in range(40): + start = pick_scene_aware_start("a1", 2.0, {"a1": 18.0}, {"a1": points}, {}) + assert start is not None + # 记录起点落在哪个段（段宽 5s） + observed.add(int(start // 5.0)) + assert len(observed) >= 3, f"镜头段 shuffle 后应覆盖多个段，实际 {observed}" + + +# ── 一键生成路径：distribute_assets 接入场景缓存 ────────────────────────────── + + +class TestDistributeWithScenePoints: + def _make_clips(self, n): + from packages.domain.edit_plan_clip import EditPlanClip + + return [EditPlanClip(id=f"c{i}", plan_id="p1", clip_type="main", duration=4.0, order=i) for i in range(n)] + + def test_one_take_uses_scene_segments(self): + """ONE_TAKE 模式下，有场景缓存的素材起点落在镜头段内。""" + from packages.domain.editing_mode import EditingMode + + clips = self._make_clips(2) + points = [0.0, 6.0, 12.0, 18.0] + distribute_assets( + clips, + ["a1"], + EditingMode.ONE_TAKE.value, + asset_durations={"a1": 24.0}, + asset_scene_points={"a1": points}, + ) + segments = build_scene_segments(points, 24.0) + for clip in clips: + assert clip.start_time is not None + assert any( + s <= clip.start_time and clip.start_time + 4.0 <= e for s, e in segments + ), f"起点 {clip.start_time} 不在任何镜头段内" + + def test_no_scene_points_falls_back_random(self): + """无场景缓存时正常分配（回退随机起点），不报错。""" + from packages.domain.editing_mode import EditingMode + + clips = self._make_clips(1) + distribute_assets( + clips, + ["a1"], + EditingMode.ONE_TAKE.value, + asset_durations={"a1": 24.0}, + asset_scene_points={}, + ) + for clip in clips: + assert clip.asset_id == "a1" + assert clip.start_time is not None + assert 0.0 <= clip.start_time <= 20.0 + + def test_random_preview_ignores_scene_points(self): + """random_selection 预览模式行为不变（不崩溃、正常分配）。""" + from packages.domain.editing_mode import EditingMode + + clips = self._make_clips(2) + distribute_assets( + clips, + ["a1", "a2"], + EditingMode.ONE_TAKE.value, + random_selection=True, + asset_durations={"a1": 24.0, "a2": 24.0}, + asset_scene_points={"a1": [0.0, 6.0]}, + ) + assert all(c.asset_id for c in clips) + + +# ── from-assets 路径：渲染前读缓存选镜头段 ──────────────────────────────────── + + +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_asset_with_scenes(aid, duration, scene_points=None): + asset = MagicMock() + asset.id = aid + asset.duration = duration + asset.quality_score = None + asset.created_at = None + asset.metadata = {"scene_change_points": scene_points} if scene_points is not None else {} + return asset + + +class TestFromAssetsSceneCache: + def test_cached_scene_points_used_for_start_time(self): + """素材 metadata 有场景点缓存时，片段起点落在镜头段内。""" + from app.api.routes.templates_editor.clips import create_clips_from_assets_editor + from app.api.routes.templates_editor.schemas import ClipsFromAssetsRequest + + # 镜头段宽度 10s，片段最长 ~5.3s（含转场补偿），每段都能容纳 + scene_points = [0.0, 10.0, 20.0, 30.0] + asset_duration = 40.0 + mock_asset_repo = MagicMock() + mock_asset_repo.get = MagicMock( + side_effect=lambda aid: _make_asset_with_scenes(aid, asset_duration, scene_points) + ) + mock_plan_svc = MagicMock() + mock_plan_svc.replace_all_clips_transactional = MagicMock(return_value=3) + + segments = [(0, 3.0, 5.0), (1, 3.0, 5.0), (2, 3.0, 5.0)] + + with ( + patch( + "app.api.routes.templates_editor.clips._get_template_segments", + return_value=segments, + ), + patch("app.api.routes.templates_editor.clips.get_used_segments", return_value={}), + patch("app.api.routes.templates_editor.clips.record_used_segments", return_value=None), + ): + body = ClipsFromAssetsRequest(asset_ids=["a1"], required_clips_count=3) + create_clips_from_assets_editor( + template_id="tmpl-1", + body=body, + background_tasks=MagicMock(), + plan_id="plan-scene-1", + 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] + scene_segments = build_scene_segments(scene_points, asset_duration) + for clip in clips_data: + start = clip["start_time"] + dur = clip["duration"] + in_segment = any(s <= start and start + dur <= e + 0.1 for s, e in scene_segments) + assert in_segment, f"起点 {start:.2f} 时长 {dur:.2f} 不在任何镜头段内" + + def test_no_cache_falls_back_random_no_error(self): + """素材无场景缓存时正常走随机起点，流程不报错。""" + 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() + mock_asset_repo.get = MagicMock(side_effect=lambda aid: _make_asset_with_scenes(aid, 30.0, None)) + mock_plan_svc = MagicMock() + mock_plan_svc.replace_all_clips_transactional = MagicMock(return_value=2) + + segments = [(0, 3.0, 5.0), (1, 3.0, 5.0)] + with ( + patch( + "app.api.routes.templates_editor.clips._get_template_segments", + return_value=segments, + ), + patch("app.api.routes.templates_editor.clips.get_used_segments", return_value={}), + patch("app.api.routes.templates_editor.clips.record_used_segments", return_value=None), + ): + body = ClipsFromAssetsRequest(asset_ids=["a1"], required_clips_count=2) + create_clips_from_assets_editor( + template_id="tmpl-1", + body=body, + background_tasks=MagicMock(), + plan_id="plan-scene-2", + 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] + assert len(clips_data) == 2 + assert all(c["start_time"] is not None for c in clips_data) + + +# ── 后台任务：检测结果写缓存 ────────────────────────────────────────────────── + + +class TestAsyncCacheWrite: + def test_scene_points_persisted_to_metadata(self): + """detect_scene_changes 返回结果后写入素材 metadata 并调用 repo.update。""" + from app.api.routes.templates_editor import clips as clips_module + + detected_points = [0.0, 4.5, 9.0, 14.2] + + mock_asset = MagicMock() + mock_asset.id = "a1" + mock_asset.duration = 20.0 + mock_asset.storage_key = "v.mp4" + mock_asset.mime_type = "video/mp4" + mock_asset.metadata = {} + + mock_asset_repo = MagicMock() + mock_asset_repo.find_by_ids = MagicMock(return_value=[mock_asset]) + mock_asset_repo.update = MagicMock(side_effect=lambda a: a) + + mock_clip = MagicMock() + mock_clip.id = "clip-1" + mock_clip.asset_id = "a1" + mock_clip.order = 0 + mock_clip.start_time = 2.0 + mock_clip.duration = 4.0 + + mock_plan_svc = MagicMock() + mock_plan_svc.list_clips = MagicMock(return_value=[mock_clip]) + mock_plan_svc.update_clip = MagicMock() + plan_svc_factory = MagicMock(return_value=mock_plan_svc) + + mock_client = MagicMock() + mock_client.is_available = True + mock_client.detect_scene_changes = MagicMock(return_value=detected_points) + + mock_storage = MagicMock() + mock_storage.get_download_url = MagicMock(return_value="https://example.com/v.mp4") + + mock_session = MagicMock() + + with ( + patch( + "packages.adapters.sqlalchemy_impl.asset_repository.SQLAlchemyAssetRepository", + return_value=mock_asset_repo, + ), + patch( + "app.api.routes.templates_editor.clips.EditPlanService", + plan_svc_factory, + ), + patch( + "packages.adapters.sqlalchemy_impl.session.SessionLocal", + MagicMock(return_value=mock_session), + ), + patch( + "app.api.routes.templates_editor.clips.get_storage_service", + return_value=mock_storage, + ), + patch( + "app.api.routes.templates_editor.clips.get_mediakit_client", + return_value=mock_client, + ), + 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, + ), + patch( + "app.api.routes.templates_editor.clips.remove_used_segment", + return_value=False, + ), + ): + clips_module._update_mediakit_recommendations_async("plan-1", ["a1"]) + + # 验证素材 metadata 被写入场景点并持久化 + assert mock_asset.metadata.get("scene_change_points") == detected_points + mock_asset_repo.update.assert_called() diff --git a/tests/unit/test_scene_change_shuffle.py b/tests/unit/test_scene_change_shuffle.py new file mode 100644 index 000000000..5ad9cc4c0 --- /dev/null +++ b/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 diff --git a/tests/unit/test_smart_match_integration.py b/tests/unit/test_smart_match_integration.py new file mode 100644 index 000000000..b9966072a --- /dev/null +++ b/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}"