fix(test): mock storage.get_download_url，修复_sign_media_url内部调用mock泄漏问题

fix(test): 统一test_lipsync_tts持久化测试upload_url参数与key一致，消除flaky
style: prettier format sentences.ts & titleCanvas.ts [skip ci-format-check]
2026-09-13 02:21:08 +08:00 · 2026-09-13 02:05:30 +08:00 · 2026-09-13 01:34:47 +08:00 · 2026-09-13 01:14:15 +08:00 · 2026-09-12 17:05:14 +00:00 · 2026-09-13 00:58:02 +08:00
25 changed files with 1952 additions and 481 deletions
@@ -0,0 +1,27 @@
+"""add sentence_timings to lipsync_jobs
+
+Revision ID: 075_add_sentence_timings
+Revises: 074_ai_avatar_render_script_id_optional
+Create Date: 2026-09-12
+"""
+
+import sqlalchemy as sa
+
+from alembic import op
+
+revision = "075_add_sentence_timings"
+down_revision = "074_render_script_id_optional"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    with op.batch_alter_table("lipsync_jobs") as batch:
+        batch.add_column(
+            sa.Column("sentence_timings", sa.JSON(), nullable=True),
+        )
+
+
+def downgrade() -> None:
+    with op.batch_alter_table("lipsync_jobs") as batch:
+        batch.drop_column("sentence_timings")
@@ -18,7 +18,6 @@ from app.dependencies import get_db_session
 from app.schemas.ai_avatar_render import (
    AiAvatarRenderJobResponse,
    CreateAiAvatarRenderRequest,
-    SmartCoverRequest,
    SmartCoverResponse,
 )
 from app.services.ai_avatar_cover_service import generate_smart_cover
@@ -191,36 +190,42 @@ def retry_render_job(
    return AiAvatarRenderJobResponse.model_validate(job)


-
-# ── POST /smart-cover — 智能获取封面（MediaKit 抽帧 + 评分选帧）────────
+# ── POST /{job_id}/smart-cover — 从最终成片智能抽封面（步骤②）────────


-@router.post("/smart-cover", response_model=SmartCoverResponse)
-def generate_avatar_smart_cover(
-    body: SmartCoverRequest,
+@router.post("/{job_id}/smart-cover", response_model=SmartCoverResponse)
+def generate_render_smart_cover(
+    job_id: str,
    current_user: AuthenticatedUser = Depends(get_current_user),
-) -> SmartCoverResponse:
-    """智能获取数字人视频封面.
+    db: Session = Depends(get_db_session),
+):
+    """从最终渲染成片智能抽帧生成封面（MediaKit 抽帧 + 评分选最佳帧 + 转存 OSS）.

-    复用智能剪辑的 MediaKit 抽帧 + 质量评分选最佳帧逻辑（非 FFmpeg 简单截帧），
-    并将选中帧转存到自家 OSS，返回非临时的封面公网 URL。
-
-    前端「智能获取封面」按钮可直接调用本接口；不依赖渲染任务完成。
+    - 必须等渲染任务 completed 后才可调用（否则返回 400）
+    - 生成成功后自动更新 render_job 的 cover_config 与 output_cover_url
    """
-    video_url = (body.video_url or "").strip()
-    if not video_url.startswith(("http://", "https://")):
-        raise HTTPException(status_code=400, detail="video_url 必须是合法的 HTTP/HTTPS URL")
+    from app.services.ai_avatar_render_service import AiAvatarRenderService
+
+    svc = AiAvatarRenderService(db)
+    job = svc.get_render_job(job_id, current_user.user.id)
+    if job is None:
+        raise HTTPException(status_code=404, detail="渲染任务不存在")
+    if job.status != "completed":
+        raise HTTPException(status_code=400, detail="请先完成视频生成")
+    video_url = (job.output_video_url or "").strip()
+    if not video_url:
+        raise HTTPException(status_code=400, detail="渲染成片视频 URL 为空")

    try:
-        cover_url = generate_smart_cover(
-            video_url,
-            max_frames=body.max_frames,
-            title_config=getattr(body, "title_config", None),
-        )
+        # 从最终成片抽帧，帧本身已含标题/B-roll，直接转存 OSS
+        cover_url = generate_smart_cover(video_url, job_id=job_id, max_frames=5)
    except Exception as exc:
        logger.error(
-            "智能封面生成异常: user=%s video_url=%s err=%s",
-            current_user.user.id, video_url[:80], exc,
+            "渲染成片智能封面生成异常: user=%s render_id=%s video_url=%s err=%s",
+            current_user.user.id,
+            job_id,
+            video_url[:80],
+            exc,
            exc_info=True,
        )
        cover_url = ""
@@ -231,5 +236,24 @@ def generate_avatar_smart_cover(
            status="fallback_failed",
            message="智能抽帧失败（MediaKit 不可用或抽帧异常），请稍后重试",
        )
-    logger.info("智能封面生成成功: user=%s cover_url=%s", current_user.user.id, cover_url[:120])
+
+    # 更新 render_job 的封面字段（异步写入 DB；失败不影响返回）
+    try:
+        job.cover_config = {
+            **(job.cover_config if isinstance(job.cover_config, dict) else {}),
+            "mode": "auto_frame",
+            "url": cover_url,
+        }
+        job.output_cover_url = cover_url
+        job.updated_at = datetime.now(timezone.utc)
+        db.commit()
+    except Exception as exc:
+        logger.warning("更新 render_job 封面字段失败（不影响返回）: job_id=%s err=%s", job_id, exc)
+
+    logger.info(
+        "渲染成片智能封面生成成功: user=%s render_id=%s cover_url=%s",
+        current_user.user.id,
+        job_id,
+        cover_url[:120],
+    )
    return SmartCoverResponse(cover_url=cover_url, status="completed")
@@ -52,7 +52,9 @@ class CreateAiAvatarRenderRequest(BaseModel):
    lipsync_job_id: str = Field(..., description="对口型任务 ID")
    script_id: str = Field("", description="文案 ID（选自文案库时传；手动输入文案直生场景可留空）")
    b_roll_segments: list[BRollSegment] = Field(default_factory=list, description="B-roll 片段列表")
-    title_config: dict[str, Any] = Field(default_factory=dict, description="标题配置")
+    title_config: dict[str, Any] = Field(
+        default_factory=dict, description="标题配置（可含 title_image_dataurl：前端 Canvas 渲染的标题 PNG dataURL）"
+    )
    cover_config: dict[str, Any] = Field(default_factory=dict, description="封面配置")
    project_id: str = Field("", description="项目 ID")

@@ -67,7 +69,6 @@ class CreateAiAvatarRenderRequest(BaseModel):
    @field_validator("script_id")
    @classmethod
    def validate_script_id(cls, v: str) -> str:
-        # script_id 可选：手动输入文案（TTS 直生）场景不关联文案库条目
        return (v or "").strip()


@@ -109,18 +110,8 @@ class AiAvatarRenderProgressResponse(BaseModel):
    error_message: str


-class SmartCoverRequest(BaseModel):
-    """智能封面请求 — MediaKit 抽帧 + 质量评分选最佳帧 + 可选标题 drawtext 叠加."""
-
-    video_url: str = Field(..., description="数字人视频 URL（对口型/渲染成片）")
-    max_frames: int = Field(5, ge=1, le=10, description="抽帧数量（默认 5）")
-    title_config: Optional[dict[str, Any]] = Field(
-        None, description="标题配置；传入时在封面上用 drawtext 叠加标题（竖屏 720x1280）"
-    )
-
-
 class SmartCoverResponse(BaseModel):
-    """智能封面响应."""
+    """智能封面响应（封面从最终成片抽帧，不再叠加标题）."""

    cover_url: str = Field("", description="封面图公网 URL（OSS，非临时）；失败为空")
    status: str = Field("completed", description="completed / fallback_failed")
@@ -33,6 +33,7 @@ class LipsyncJobResponse(BaseModel):
    output_duration: float
    error_message: str
    error_code: str
+    sentence_timings: Optional[list] = None
    submitted_at: Optional[datetime] = None
    completed_at: Optional[datetime] = None
    created_at: datetime
@@ -1,18 +1,19 @@
-"""AI 数字人封面服务 — 复用智能剪辑的 MediaKit 抽帧 + 质量评分选最佳帧.
+"""AI 数字人封面服务 — MediaKit 抽帧 + 质量评分选最佳帧 + 转存 OSS.

 与 generation_cover.py 的智能选帧能力对齐（不再用 FFmpeg 简单截帧）：
 1. MediaKit extract_frames 抽取多帧（默认 5 帧，SpecifiedFrames 策略）
 2. cover_frame_scorer.score_frames 按清晰度/亮度/色彩评分选最佳
 3. 下载最佳帧并转存 OSS，返回公网封面 URL

+设计原则：封面一律从最终成片（已叠加标题/B-roll）抽帧，帧本身已含标题，
+本服务**不再叠加标题**。对口型阶段的裸视频封面入口已删除（废弃）。
+
 降级：MediaKit 不可用或抽帧失败时返回空字符串，由调用方决定回退策略。
 """

 from __future__ import annotations

 import logging
-import os
-import subprocess
 import tempfile
 import uuid
 from pathlib import Path
@@ -51,7 +52,6 @@ def _sign_video_url_for_mediakit(video_url: str) -> str:
        own_host = urlparse(public_base).netloc.lower()
        url_host = urlparse(video_url).netloc.lower()
        if own_host and url_host == own_host:
-            # 是自家 OSS URL，重签 7 天有效期供 MediaKit 拉取
            signed = storage.get_download_url(video_url, expires_seconds=MEDIAKIT_URL_TTL_SECONDS)
            if signed:
                logger.info("[数字人封面] video_url 已重签（自家 OSS 私有桶）")
@@ -62,19 +62,10 @@ def _sign_video_url_for_mediakit(video_url: str) -> str:


 def select_best_cover_frame(video_url: str, *, max_frames: int = 5) -> str:
-    """从视频抽取多帧并评分选最佳帧，返回最佳帧的临时 URL.
-
-    Args:
-        video_url: 可公网访问的视频 URL
-        max_frames: 抽帧数量
-
-    Returns:
-        最佳帧图片 URL；失败返回空字符串
-    """
+    """从视频抽取多帧并评分选最佳帧，返回最佳帧的临时 URL."""
    if not video_url:
        return ""

-    # 确保 MediaKit 能访问 video_url（自家 OSS 私有桶需重签）
    video_url = _sign_video_url_for_mediakit(video_url)

    try:
@@ -87,11 +78,9 @@ def select_best_cover_frame(video_url: str, *, max_frames: int = 5) -> str:
            return ""

        logger.info(
-            "[数字人封面] 开始抽帧: video_url=%s max_frames=%d poll_interval=%.1f max_poll=%d",
+            "[数字人封面] 开始抽帧: video_url=%s max_frames=%d",
            video_url[:80],
            max_frames,
-            COVER_POLL_INTERVAL,
-            COVER_MAX_POLL_ATTEMPTS,
        )

        snapshots = mk.extract_frames(
@@ -109,7 +98,6 @@ def select_best_cover_frame(video_url: str, *, max_frames: int = 5) -> str:
        if len(snapshots) == 1:
            return snapshots[0].get("image_url") or snapshots[0].get("url") or ""

-        # 使用连接池下载各帧（复用 TCP 连接，减少延迟）
        import httpx

        candidates = []
@@ -137,7 +125,6 @@ def select_best_cover_frame(video_url: str, *, max_frames: int = 5) -> str:
        best = scored[0] if scored else None
        best_url = best.get("url", "") if best else ""

-        # 清理临时文件
        for c in candidates:
            p = c.get("image_path")
            if p:
@@ -158,87 +145,19 @@ def select_best_cover_frame(video_url: str, *, max_frames: int = 5) -> str:
        return ""


-def apply_title_to_cover(local_frame: str, *, title_config: dict | None) -> str:
-    """用 ffmpeg drawtext 在封面图上叠加标题，返回叠加后图片的本地路径.
-
-    ffmpeg 失败时回退返回原始 local_frame。竖屏封面按 720x1280 计算位置。
-    """
-    if not title_config or not isinstance(title_config, dict):
-        return local_frame
-    text = (title_config.get("text") or title_config.get("content") or "").strip()
-    if not text:
-        return local_frame
-    enabled = title_config.get("enabled", True)
-    if not enabled:
-        return local_frame
-
-    try:
-        from packages.domain.video_filter_builder import build_title_drawtext_filter
-
-        drawtext_filter = build_title_drawtext_filter(
-            title_config,
-            output_width=720,
-            output_height=1280,
-        )
-        if not drawtext_filter:
-            return local_frame
-
-        base, ext = os.path.splitext(local_frame)
-        titled_path = f"{base}_titled{ext or '.jpg'}"
-        cmd = [
-            "ffmpeg",
-            "-i",
-            local_frame,
-            "-vf",
-            drawtext_filter,
-            "-y",
-            titled_path,
-        ]
-        logger.info("[数字人封面] 叠加标题: text=%s", text[:30])
-        result = subprocess.run(
-            cmd,
-            capture_output=True,
-            text=True,
-            timeout=30,
-        )
-        if result.returncode != 0:
-            logger.warning(
-                "[数字人封面] drawtext 失败，回退无标题: exit=%s stderr=%s",
-                result.returncode,
-                (result.stderr or "")[-300:],
-            )
-            return local_frame
-        if not os.path.exists(titled_path) or os.path.getsize(titled_path) == 0:
-            logger.warning("[数字人封面] drawtext 输出为空，回退无标题")
-            return local_frame
-        return titled_path
-    except Exception as exc:
-        logger.warning("[数字人封面] 标题叠加异常，回退无标题: %s", exc, exc_info=True)
-        return local_frame
-
-
 def persist_cover_to_oss(
    frame_url: str,
    *,
    job_id: str = "",
    prefix: str = "ai-avatar/covers",
-    title_config: dict | None = None,
 ) -> str:
-    """下载帧图并转存到 OSS，返回公网封面 URL.
+    """下载最佳帧图并转存到 OSS，返回公网封面 URL（预签名）.

-    Args:
-        frame_url: MediaKit 返回的临时帧图 URL
-        job_id: 关联任务 ID（用于 OSS key 命名）
-        prefix: OSS key 前缀
-        title_config: 可选标题配置；传入时用 drawtext 叠加标题（竖屏 720x1280）
-
-    Returns:
-        OSS 公网 URL；失败回退原始 frame_url
+    封面来自最终成片抽帧，帧本身已含标题，本函数不再做任何文字/图片叠加。
    """
    if not frame_url:
        return ""
    tmp_path: Optional[str] = None
-    titled_path: Optional[str] = None
    try:
        import httpx

@@ -259,21 +178,12 @@ def persist_cover_to_oss(
        token = job_id or uuid.uuid4().hex[:12]
        cover_key = f"{prefix}/{token}/cover_{uuid.uuid4().hex[:8]}.jpg"

-        upload_path = apply_title_to_cover(tmp_path, title_config=title_config)
-        if upload_path != tmp_path:
-            titled_path = upload_path
-
        public_url = storage.upload_file(
-            file_or_path=upload_path,
+            file_or_path=tmp_path,
            storage_key=cover_key,
            content_type="image/jpeg",
        )
-        logger.info(
-            "[数字人封面] 封面已转存 OSS: key=%s titled=%s",
-            cover_key,
-            bool(titled_path),
-        )
-        # 私有桶：返回预签名 URL（前端才能加载）
+        logger.info("[数字人封面] 封面已转存 OSS: key=%s", cover_key)
        if public_url:
            signed = storage.get_download_url(cover_key, expires_seconds=86400)
            return signed
@@ -282,12 +192,11 @@ def persist_cover_to_oss(
        logger.warning("[数字人封面] 封面转存 OSS 失败，返回原始 URL", exc_info=True)
        return frame_url
    finally:
-        for p in (tmp_path, titled_path):
-            if p:
-                try:
-                    Path(p).unlink(missing_ok=True)
-                except Exception:
-                    pass
+        if tmp_path:
+            try:
+                Path(tmp_path).unlink(missing_ok=True)
+            except Exception:
+                pass


 def generate_smart_cover(
@@ -295,19 +204,12 @@ def generate_smart_cover(
    *,
    job_id: str = "",
    max_frames: int = 5,
-    title_config: dict | None = None,
 ) -> str:
-    """一站式：MediaKit 智能抽帧选最佳 → （可选）drawtext 叠加标题 → 转存 OSS.
+    """一站式：MediaKit 智能抽帧选最佳 → 转存 OSS。失败返回空字符串。

-    供独立封面接口与渲染管线复用。失败返回空字符串。
-
-    Args:
-        video_url: 可公网访问的视频 URL
-        job_id: 关联任务 ID
-        max_frames: 抽帧数量
-        title_config: 可选标题配置；传入时在封面上叠加 drawtext 标题（竖屏 720x1280）
+    封面从最终成片抽帧，不再叠加任何标题（帧本身已含）。
    """
    best_frame = select_best_cover_frame(video_url, max_frames=max_frames)
    if not best_frame:
        return ""
-    return persist_cover_to_oss(best_frame, job_id=job_id, title_config=title_config)
+    return persist_cover_to_oss(best_frame, job_id=job_id)
@@ -9,6 +9,8 @@

 from __future__ import annotations

+import base64
+import binascii
 import logging
 import os
 import subprocess
@@ -27,6 +29,7 @@ from packages.adapters.sqlalchemy_impl.models import (
 from packages.domain.video_filter_builder import (
    build_broll_overlay_filter,
    build_title_drawtext_filter,
+    build_title_overlay_filter,
 )
 from packages.shared.storage import get_shared_storage_service

@@ -197,9 +200,8 @@ class AiAvatarRenderService:
        1. 下载对口型输出视频 (20%)
        2. 构建 FFmpeg 滤镜链 (40%)
        3. 执行 FFmpeg 渲染 (80%)
-        4. 提取封面 (90%)
-        5. 上传到 OSS (95%)
-        6. 更新任务状态 (100%)
+        4. 上传到 OSS (95%) — 封面不再自动生成，改由前端主动抽帧
+        5. 更新任务状态 (100%)
        """
        job = self.db.query(AiAvatarRenderJob).filter(AiAvatarRenderJob.id == job_id).first()
        if job is None:
@@ -249,29 +251,12 @@ class AiAvatarRenderService:
                output_height=output_height,
            )

-            # 标题叠加（传入实际输出尺寸，保证位置计算正确）
-            title_filter = build_title_drawtext_filter(
-                job.title_config,
-                output_width=output_width,
-                output_height=output_height,
-            )
-
-            filter_complex = ""
-            final_label = None
-            if broll_filter and title_filter:
-                # B-roll → 标题叠在 B-roll 输出上
-                filter_complex = broll_filter + f";[{broll_label}]{title_filter}[vout_titled]"
-                final_label = "vout_titled"
-            elif broll_filter:
-                filter_complex = broll_filter
-                final_label = broll_label
-            elif title_filter:
-                filter_complex = f"[0:v]{title_filter}[vout_titled]"
-                final_label = "vout_titled"
-            else:
-                # 无滤镜：直接拷贝视频流
-                filter_complex = ""
-                final_label = None
+            # 标题叠加路径：优先前端 Canvas 渲染的 PNG 图层（所见即所得），
+            # 无 title_image_dataurl 时降级到 drawtext 重画文字。
+            title_cfg = job.title_config if isinstance(job.title_config, dict) else {}
+            title_dataurl = (title_cfg or {}).get("title_image_dataurl") if title_cfg else None
+            use_title_png = isinstance(title_dataurl, str) and title_dataurl.startswith("data:image/")
+            title_input_index = 1 + len(job.b_roll_segments or []) if use_title_png else None

            job.progress = 40
            self.db.commit()
@@ -280,9 +265,81 @@ class AiAvatarRenderService:
            with tempfile.TemporaryDirectory() as tmpdir:
                output_video_path = os.path.join(tmpdir, "output.mp4")

+                # 在临时目录里解码保存标题 PNG（with 退出自动清理）
+                title_png_path: Optional[str] = None
+                extra_inputs: list[str] = []
+                title_filter = None
+                if use_title_png:
+                    try:
+                        title_png_path = os.path.join(tmpdir, f"title_{job.id}.png")
+                        self._save_title_dataurl_to_file(title_dataurl, dst_path=title_png_path)
+                        extra_inputs.append(title_png_path)
+                        logger.info(
+                            "[数字人渲染] 标题 PNG 已保存: %s (input index %d)", title_png_path, title_input_index
+                        )
+                    except Exception as exc:
+                        logger.warning("[数字人渲染] 标题 PNG 解码/保存失败，降级 drawtext: %s", exc)
+                        title_png_path = None
+                        extra_inputs = []
+
+                # 构建标题滤镜
+                final_label = None
+                if title_png_path and title_input_index is not None:
+                    title_input_label = f"[{title_input_index}:v]"
+                    base_label = f"[{broll_label}]" if broll_label else "[0:v]"
+                    title_filter = build_title_overlay_filter(
+                        title_cfg,
+                        output_width=output_width,
+                        output_height=output_height,
+                        title_png_path=title_png_path,
+                        title_input_label=title_input_label,
+                        base_label=base_label,
+                        output_label="vout_titled",
+                    )
+                    if not title_filter:
+                        # build 返回 None → 文件不存在（极端并发情况），降级 drawtext
+                        title_png_path = None
+                        extra_inputs = []
+
+                if title_png_path:
+                    # overlay 路径
+                    if broll_filter and title_filter:
+                        filter_complex = broll_filter + f";{title_filter}"
+                    elif broll_filter:
+                        filter_complex = broll_filter
+                        final_label = broll_label
+                    elif title_filter:
+                        filter_complex = title_filter
+                    else:
+                        filter_complex = ""
+                    if title_filter:
+                        final_label = "vout_titled"
+                    elif not final_label:
+                        final_label = None
+                else:
+                    # 降级：drawtext 重画文字
+                    title_filter = build_title_drawtext_filter(
+                        title_cfg,
+                        output_width=output_width,
+                        output_height=output_height,
+                    )
+                    if broll_filter and title_filter:
+                        filter_complex = broll_filter + f";[{broll_label}]{title_filter}[vout_titled]"
+                        final_label = "vout_titled"
+                    elif broll_filter:
+                        filter_complex = broll_filter
+                        final_label = broll_label
+                    elif title_filter:
+                        filter_complex = f"[0:v]{title_filter}[vout_titled]"
+                        final_label = "vout_titled"
+                    else:
+                        filter_complex = ""
+                        final_label = None
+
                cmd_list = self._build_ffmpeg_command(
                    input_video=input_video_path,
                    b_roll_segments=job.b_roll_segments,
+                    extra_inputs=extra_inputs,
                    filter_complex=filter_complex,
                    final_label=final_label,
                    output_path=output_video_path,
@@ -311,64 +368,23 @@ class AiAvatarRenderService:
                job.progress = 80
                self.db.commit()

-                # 4. 提取封面 (90%)
-                cover_path = ""
-                if job.cover_config:
-                    cover_path = os.path.join(tmpdir, "cover.jpg")
-                    cover_cmd = self._build_cover_extract_cmd(
-                        cover_config=job.cover_config,
-                        input_video=output_video_path,
-                        output_path=cover_path,
-                    )
-                    try:
-                        cover_result = subprocess.run(
-                            cover_cmd,
-                            capture_output=True,
-                            text=True,
-                            timeout=60,
-                        )
-                        if cover_result.returncode != 0:
-                            logger.warning(
-                                "封面提取失败（非致命），跳过: exit=%s stderr=%s",
-                                cover_result.returncode,
-                                (cover_result.stderr or "")[-300:],
-                            )
-                            cover_path = ""
-                    except Exception as cover_err:
-                        logger.warning("封面提取异常（非致命），跳过: %s", cover_err)
-                        cover_path = ""
-
-                job.progress = 90
-                self.db.commit()
-
-                # 5. 上传到 OSS (95%)
+                # 4/5. 上传成片到 OSS (95%) —— 已砍掉自动抽封面逻辑（步骤⑤）；
+                # 封面由前端在渲染完成后通过 /smart-cover 接口主动从成片抽帧，不阻塞渲染链路。
                output_video_url = self._upload_to_oss(output_video_path, f"ai-avatar/{job_id}/output.mp4")
                job.output_video_url = output_video_url

-                # 封面：优先复用智能剪辑的 MediaKit 抽帧 + 质量评分选最佳帧（支持 drawtext 标题叠加）；
-                # MediaKit 不可用时回退到 FFmpeg 已按 cover_config 抽取的 cover_path
-                smart_cover_url = ""
-                if output_video_url:
-                    try:
-                        from app.services.ai_avatar_cover_service import (
-                            generate_smart_cover,
-                        )
-
-                        smart_cover_url = generate_smart_cover(
-                            output_video_url,
-                            job_id=job_id,
-                            max_frames=5,
-                            # 注意：不传 title_config —— 最终输出视频已经通过 drawtext 叠加了标题，
-                            # 再传会导致封面标题双重叠加
-                        )
-                    except Exception:
-                        logger.warning("智能封面(MediaKit)失败，回退 FFmpeg 封面 job_id=%s", job_id, exc_info=True)
-
-                if smart_cover_url:
-                    job.output_cover_url = smart_cover_url
-                elif cover_path:
-                    output_cover_url = self._upload_to_oss(cover_path, f"ai-avatar/{job_id}/cover.jpg")
-                    job.output_cover_url = output_cover_url
+                # 封面透传：如果用户已在 cover_config 中选定封面 URL（mode=upload 的自定义上传 或
+                # mode=auto_frame 已有的智能封面结果），直接透传到 output_cover_url，不再重新截帧。
+                if isinstance(job.cover_config, dict):
+                    _pre_cover_url = (
+                        job.cover_config.get("url")
+                        or job.cover_config.get("imageUrl")
+                        or job.cover_config.get("cover_url")
+                        or ""
+                    )
+                    if _pre_cover_url:
+                        job.output_cover_url = _pre_cover_url
+                        logger.info("[数字人渲染] 使用用户已选定封面 URL: job_id=%s", job_id)

                # 获取输出视频时长
                job.output_duration = lipsync_job.output_duration
@@ -450,6 +466,44 @@ class AiAvatarRenderService:
                os.unlink(tmp.name)
            raise

+    @staticmethod
+    def _save_title_dataurl_to_file(dataurl: str, *, dst_path: str | None = None, job_id: str = "") -> str:
+        """解码前端传来的 data:image/png;base64,... 并保存为本地 PNG 文件。
+
+        Args:
+            dataurl: 完整 dataURL 字符串
+            dst_path: 指定输出路径；为 None 时创建临时文件并返回路径
+            job_id: 仅在 dst_path 为空时用于临时文件命名
+
+        Returns:
+            保存后的本地文件路径
+        """
+        if not isinstance(dataurl, str) or not dataurl.startswith("data:image/"):
+            raise ValueError("title_image_dataurl 不是合法的 data:image URL")
+        # 拆分 data:image/png;base64,<payload>
+        try:
+            header, b64 = dataurl.split(",", 1)
+        except ValueError as exc:
+            raise ValueError("title_image_dataurl 缺少 base64 payload") from exc
+        if "base64" not in header:
+            raise ValueError("title_image_dataurl 不是 base64 编码")
+        try:
+            png_bytes = base64.b64decode(b64, validate=True)
+        except (binascii.Error, ValueError) as exc:
+            raise ValueError(f"title_image_dataurl base64 解码失败: {exc}") from exc
+        if not png_bytes:
+            raise ValueError("title_image_dataurl 解码后为空")
+
+        if dst_path:
+            out_path = dst_path
+            with open(out_path, "wb") as f:
+                f.write(png_bytes)
+            return out_path
+        suffix = f"_title_{job_id}.png" if job_id else "_title.png"
+        with tempfile.NamedTemporaryFile(suffix=suffix, delete=False) as tmp:
+            tmp.write(png_bytes)
+            return tmp.name
+
    @staticmethod
    def _probe_video_resolution(video_path: str) -> tuple[int, int]:
        """用 ffprobe 探测视频分辨率，返回 (width, height)；失败返回 (0, 0)。"""
@@ -486,6 +540,7 @@ class AiAvatarRenderService:
        *,
        input_video: str,
        b_roll_segments: list[dict[str, Any]],
+        extra_inputs: list[str] | None = None,
        filter_complex: str,
        final_label: Optional[str],
        output_path: str,
@@ -502,6 +557,9 @@ class AiAvatarRenderService:
            asset_url = seg.get("asset_url", "")
            if asset_url:
                cmd.extend(["-i", asset_url])
+        # 额外输入（例如前端 Canvas 渲染的标题 PNG）
+        for extra in extra_inputs or []:
+            cmd.extend(["-i", extra])

        if filter_complex and final_label:
            cmd.extend(
@@ -535,41 +593,6 @@ class AiAvatarRenderService:
        )
        return cmd

-    def _build_cover_extract_cmd(
-        self,
-        *,
-        cover_config: dict[str, Any],
-        input_video: str,
-        output_path: str,
-    ) -> list[str]:
-        """构建封面截帧 FFmpeg 命令（list 形式，shell=False）."""
-        if not cover_config or not isinstance(cover_config, dict):
-            timestamp = 0.0
-            width = 0
-            height = 0
-        else:
-            timestamp = cover_config.get("timestamp", 0.0)
-            width = cover_config.get("width", 0)
-            height = cover_config.get("height", 0)
-
-        cmd: list[str] = [
-            "ffmpeg",
-            "-ss",
-            str(timestamp),
-            "-i",
-            input_video,
-            "-frames:v",
-            "1",
-        ]
-        if width > 0 and height > 0:
-            vf = (
-                f"scale={width}:{height}:force_original_aspect_ratio=decrease,"
-                f"pad={width}:{height}:(ow-iw)/2:(oh-ih)/2"
-            )
-            cmd.extend(["-vf", vf])
-        cmd.extend(["-y", output_path])
-        return cmd
-
    def _upload_to_oss(self, local_path: str, oss_key: str) -> str:
        """上传文件到 OSS，返回 URL.

@@ -198,6 +198,12 @@ class LipsyncService:
        self.db.add(job)
        self.db.flush()

+        # ⚠️ 必须先 commit 再发 Celery 任务，避免事务竞态：
+        # worker 是独立进程+独立DB连接，任务被消费（<4ms）时若本事务还未提交，
+        # worker 查询 job 会返回 None → 静默 return 不重试，job 永远卡在 tts_processing。
+        self.db.commit()
+        self.db.refresh(job)
+
        if is_tts_mode:
            # 2a. TTS 模式：dispatch Celery 异步任务处理 TTS 合成 + MediaKit 提交
            try:
@@ -223,6 +229,7 @@ class LipsyncService:
                job.error_message = f"Celery 任务投递失败: {exc}"
                job.error_code = "AsyncDispatchFailed"
                job.updated_at = datetime.now(timezone.utc)
+                self.db.commit()  # 投递失败也要落库失败状态
        else:
            # 2b. 直接音频模式：同步签名并提交 MediaKit
            video_url = self._sign_media_url(video_url)
@@ -240,15 +247,15 @@ class LipsyncService:
                job.mediakit_task_id = result["task_id"]
                job.status = "submitted"
                job.submitted_at = datetime.now(timezone.utc)
+                self.db.commit()  # submitted 状态落库
            except MediaKitError as exc:
                job.status = "failed"
                job.error_message = str(exc)
                job.error_code = exc.code
                logger.error("提交对口型任务失败: %s", exc)
+                self.db.commit()
                raise

-        self.db.commit()
-        self.db.refresh(job)
        return job

    # ── 查询任务 ──────────────────────────────────────────────────────────
@@ -313,11 +320,26 @@ class LipsyncService:
        if mk_status == STATUS_COMPLETED:
            result = status_data.get("result", {})
            job.status = STATUS_COMPLETED
-            output_url = result.get("video_url", "")
-            # MediaKit 输出为临时 URL，转存自家 OSS 防止过期（失败则回退临时 URL）
-            job.output_video_url = self._persist_output_video(output_url, job_id, user_id)
+            temp_url = result.get("video_url", "")
+            # 先以临时 URL 立即返回前端（前端可立即播放），再异步 Celery 任务转存自家 OSS（步骤⑦）
+            job.output_video_url = temp_url
            job.output_duration = result.get("duration", 0.0)
            job.completed_at = datetime.now(timezone.utc)
+            job.updated_at = datetime.now(timezone.utc)
+            self.db.commit()
+            # 异步转存到自家 OSS（注意：必须在 commit 之后 dispatch，避免 commit 失败任务已发出）
+            try:
+                from app.tasks.lipsync_tts import persist_output_video_task
+
+                persist_output_video_task.apply_async(args=(job_id, user_id, temp_url))
+            except Exception as exc:
+                logger.warning(
+                    "提交输出视频异步转存任务失败，保留临时 URL: job_id=%s err=%s",
+                    job_id,
+                    exc,
+                )
+            self.db.refresh(job)
+            return job
        elif mk_status == STATUS_FAILED:
            error = status_data.get("error", {})
            job.status = "failed"
@@ -54,11 +54,174 @@ def _sign_media_url(url: str) -> str:
        return url


+def _split_script_into_sentences(script_text: str) -> list[str]:
+    """按句号/问号/感叹号/分号/逗号/换行分句（与前端 SENTENCE_SPLIT_RE 一致）.
+
+    中文短视频文案习惯用「，」断小句（如"卖花的叫花无缺，卖姜的叫姜子牙"），
+    必须把逗号也纳入分隔符，否则多句文案会被识别成一整句，导致 B-roll 时间戳错位。
+    """
+    import re
+
+    text = (script_text or "").strip()
+    if not text:
+        return []
+    parts = re.split(r"[。！？!?？！;；,，\n\r]+", text)
+    return [p.strip() for p in parts if p.strip()]
+
+
+def _compute_sentence_timings(audio_data: bytes, script_text: str, total_duration: float) -> list[dict]:
+    """基于 TTS 音频的静音检测，精确计算每句文案的起止时间.
+
+    使用 ffmpeg silencedetect 检测静音段，将静音点与句子边界对齐。
+    比字数比例估算准确得多。
+
+    Args:
+        audio_data: TTS 音频二进制数据（MP3）
+        script_text: 文案全文
+        total_duration: 音频总时长（秒）
+
+    Returns:
+        list[{"index": int, "text": str, "start_time": float, "end_time": float}]
+    """
+    import re
+    import subprocess
+    import tempfile
+
+    sentences = _split_script_into_sentences(script_text)
+    if not sentences:
+        return []
+
+    # 写入临时音频文件
+    with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as tmp:
+        tmp.write(audio_data)
+        tmp_path = tmp.name
+
+    try:
+        # 用 ffmpeg silencedetect 检测静音段
+        result = subprocess.run(
+            [
+                "ffmpeg",
+                "-i",
+                tmp_path,
+                "-af",
+                "silencedetect=noise=-25dB:d=0.3",
+                "-f",
+                "null",
+                "-",
+            ],
+            capture_output=True,
+            text=True,
+            timeout=30,
+        )
+        stderr = result.stderr or ""
+
+        # 解析静音结束时间点（silence_end: X.XXX）
+        silence_ends = []
+        for match in re.finditer(r"silence_end:\s*([\d.]+)", stderr):
+            t = float(match.group(1))
+            if 0 < t < total_duration:
+                silence_ends.append(t)
+
+        # 如果没有检测到足够的静音点，降级为字数比例估算
+        if len(silence_ends) < len(sentences) - 1:
+            logger.warning(
+                "[sentence_timings] 静音点不足(%d < %d)，降级为字数比例估算",
+                len(silence_ends),
+                len(sentences) - 1,
+            )
+            return _estimate_sentence_timings_by_chars(sentences, total_duration)
+
+        # 贪心匹配：N-1 个句子边界对应 N-1 个静音点
+        # 按时间均匀分布期望值，选择最近的静音点
+        n_boundaries = len(sentences) - 1
+        boundaries = []
+        used_indices = set()
+
+        for i in range(n_boundaries):
+            # 期望的边界位置（按句子数量均匀分布）
+            expected_pos = (i + 1) / len(sentences) * total_duration
+            # 找最近的未使用静音点
+            best_idx = None
+            best_dist = float("inf")
+            for j, t in enumerate(silence_ends):
+                if j in used_indices:
+                    continue
+                dist = abs(t - expected_pos)
+                if dist < best_dist:
+                    best_dist = dist
+                    best_idx = j
+            if best_idx is not None:
+                used_indices.add(best_idx)
+                boundaries.append(silence_ends[best_idx])
+
+        boundaries.sort()
+
+        # 构建 sentence_timings
+        timings = []
+        prev_end = 0.0
+        for i, sent in enumerate(sentences):
+            start = prev_end
+            end = boundaries[i] if i < len(boundaries) else total_duration
+            timings.append(
+                {
+                    "index": i,
+                    "text": sent,
+                    "start_time": round(start, 2),
+                    "end_time": round(end, 2),
+                }
+            )
+            prev_end = end
+
+        return timings
+
+    except Exception as exc:
+        logger.warning("[sentence_timings] 静音检测异常，降级为字数比例估算: %s", exc)
+        return _estimate_sentence_timings_by_chars(sentences, total_duration)
+    finally:
+        import os
+
+        try:
+            os.unlink(tmp_path)
+        except Exception:
+            pass
+
+
+def _estimate_sentence_timings_by_chars(sentences: list[str], total_duration: float) -> list[dict]:
+    """降级方案：按字数比例估算句子时间（与原前端逻辑一致）."""
+    if not sentences or total_duration <= 0:
+        return []
+    total_chars = sum(len(s.replace(r"\s", "")) for s in sentences)
+    if total_chars == 0:
+        return []
+
+    timings = []
+    acc = 0
+    for i, sent in enumerate(sentences):
+        chars = len(sent.replace(r"\s", ""))
+        start = (acc / total_chars) * total_duration
+        end = ((acc + chars) / total_chars) * total_duration
+        timings.append(
+            {
+                "index": i,
+                "text": sent,
+                "start_time": round(start, 2),
+                "end_time": round(end, 2),
+            }
+        )
+        acc += chars
+    return timings
+
+
@shared_task(
    bind=True,
    name="lipsync_tts.synthesize_and_submit",
-    max_retries=2,
+    max_retries=5,  # 事务竞态重试3次（job not found）+ TTS偶发错误2次
    default_retry_delay=30,
+    autoretry_for=(OSError, ConnectionError),  # 网络/连接错误自动重试
+    retry_backoff=True,
+    retry_backoff_max=30,
+    soft_time_limit=180,
+    time_limit=200,
 )
 def tts_synthesize_and_submit(
    self,
@@ -103,7 +266,28 @@ def tts_synthesize_and_submit(
        )

        if job is None:
-            logger.error("[lipsync_tts] Job not found: job_id=%s", job_id)
+            # 事务竞态防御：API 在 commit 前投递了任务，worker 消费时事务尚未提交。
+            # Celery 内置 autoretry_for 不支持"业务条件重试"，这里手动 retry 3 次，
+            # 间隔递增（1s/3s/7s），让 API 事务有时间提交。
+            # max_retries 由 self.request(retries) 维护；默认 self.max_retries=3 由装饰器 soft_time_limit 下方指定。
+            retries = getattr(self.request, "retries", 0)
+            max_retries = 3
+            if retries < max_retries:
+                backoff = (2**retries) + (retries * 1)  # 1s, 3s, 7s
+                logger.warning(
+                    "[lipsync_tts] Job not found yet (retry %d/%d, backoff %ds): job_id=%s",
+                    retries + 1,
+                    max_retries,
+                    backoff,
+                    job_id,
+                )
+                self.db.close()
+                raise self.retry(countdown=backoff, max_retries=max_retries)
+            logger.error(
+                "[lipsync_tts] Job not found after %d retries, giving up: job_id=%s",
+                max_retries,
+                job_id,
+            )
            return

        # 已取消的任务不再处理
@@ -112,6 +296,13 @@ def tts_synthesize_and_submit(
            return

        # 1. TTS 合成
+        logger.info(
+            "[lipsync_tts] 开始 TTS 合成: job_id=%s voice_id=%s text_len=%d speed=%.2f",
+            job_id,
+            voice_id,
+            len(script_text),
+            speed,
+        )
        try:
            cosyvoice = CosyVoiceService()
            result = cosyvoice.submit_synthesize_task(
@@ -147,38 +338,113 @@ def tts_synthesize_and_submit(
            db.commit()
            return

-        # 2. 下载并转存到自家 OSS
+        # 2. 下载 TTS 音频到内存（用于 2.5 静音检测；不转存自家 OSS，直接使用 CosyVoice 临时 URL）
+        audio_data: bytes | None = None
+        _st_tmp_path: str | None = None
        try:
            audio_data = safe_download_bytes(
                temp_url,
                purpose="lipsync_tts_audio",
-                allowed_mime_types=(
+                allowed_mime_types={
                    "audio/mpeg",
                    "audio/mp3",
                    "audio/wav",
                    "audio/x-wav",  # CosyVoice 部分接口返回 audio/x-wav，与 audio/wav 等价（RIFF/WAVE）
                    "audio/mp4",
                    "audio/x-m4a",
-                ),
+                },
                timeout=60.0,
            )
-            from packages.shared.storage import get_shared_storage_service
-
-            storage = get_shared_storage_service()
-            storage_key = f"lipsync-tts/{user_id}/{job_id}.mp3"
-            permanent_url = storage.upload_file(io.BytesIO(audio_data), storage_key, content_type="audio/mpeg")
-            logger.info("[lipsync_tts] TTS 音频已转存 OSS: job_id=%s key=%s", job_id, storage_key)
-            job.audio_url = permanent_url
+            logger.info(
+                "[lipsync_tts] TTS 音频已下载到内存: job_id=%s size=%d",
+                job_id,
+                len(audio_data) if audio_data else 0,
+            )
        except Exception as exc:
+            # 下载失败：audio_data 保持 None，2.5 静音检测会跳过；后续仍用 temp_url 提交 MediaKit
            logger.warning(
-                "[lipsync_tts] TTS 音频转存 OSS 失败，回退临时 URL: job_id=%s err=%s",
+                "[lipsync_tts] TTS 音频下载失败，跳过静音检测，直接使用临时 URL 提交: job_id=%s err=%s",
                job_id,
                exc,
            )
-            job.audio_url = temp_url
+        # TTS 音频使用 CosyVoice 临时 URL，跳过自家 OSS 转存（加速，步骤⑥）
+        job.audio_url = temp_url
+        logger.info("[lipsync_tts] TTS 音频使用 CosyVoice 临时 URL（跳过 OSS 转存）: job_id=%s", job_id)

        db.commit()

+        # 2.5 计算精确句子时间戳（基于 TTS 音频静音检测）
+        # 直接复用步骤 2 已下载到内存的 audio_data，避免重新下载
+        import os as _os
+
+        try:
+            import subprocess as _sp
+            import tempfile as _tmpf
+
+            if not audio_data:
+                logger.warning("[lipsync_tts] 无音频数据，跳过句子时间戳计算: job_id=%s", job_id)
+            else:
+                # 写入临时文件供 ffprobe/ffmpeg 使用
+                with _tmpf.NamedTemporaryFile(suffix=".mp3", delete=False) as _atmp:
+                    _atmp.write(audio_data)
+                    _st_tmp_path = _atmp.name
+
+                # ffprobe 获取音频时长
+                _probe_result = _sp.run(
+                    [
+                        "ffprobe",
+                        "-v",
+                        "error",
+                        "-show_entries",
+                        "format=duration",
+                        "-of",
+                        "default=noprint_wrappers=1:nokey=1",
+                        _st_tmp_path,
+                    ],
+                    capture_output=True,
+                    text=True,
+                    timeout=10,
+                )
+                _audio_duration = float(_probe_result.stdout.strip()) if _probe_result.stdout.strip() else 0.0
+                logger.info(
+                    "[lipsync_tts] 音频时长探测: job_id=%s duration=%.2f probe_stdout=%s probe_stderr=%s",
+                    job_id,
+                    _audio_duration,
+                    _probe_result.stdout.strip()[:50],
+                    _probe_result.stderr.strip()[:100] if _probe_result.stderr else "",
+                )
+
+                if _audio_duration > 0:
+                    _timings = _compute_sentence_timings(audio_data, script_text, _audio_duration)
+                    if _timings:
+                        job.sentence_timings = _timings
+                        logger.info(
+                            "[lipsync_tts] 句子时间戳已计算: job_id=%s sentences=%d duration=%.1f",
+                            job_id,
+                            len(_timings),
+                            _audio_duration,
+                        )
+                    else:
+                        logger.warning("[lipsync_tts] 句子时间戳计算返回空结果: job_id=%s", job_id)
+                else:
+                    logger.warning(
+                        "[lipsync_tts] ffprobe 未获取到有效时长，跳过句子时间戳: job_id=%s stdout=%s stderr=%s",
+                        job_id,
+                        _probe_result.stdout.strip()[:100],
+                        _probe_result.stderr.strip()[:200] if _probe_result.stderr else "",
+                    )
+                db.commit()
+        except Exception as _st_err:
+            logger.warning(
+                "[lipsync_tts] 句子时间戳计算失败（不影响主流程）: job_id=%s err=%s", job_id, _st_err, exc_info=True
+            )
+        finally:
+            if _st_tmp_path:
+                try:
+                    _os.unlink(_st_tmp_path)
+                except Exception:
+                    pass
+
        # 3. 签名 URL 并提交到 MediaKit（复用模块内 _sign_media_url，避免对 LipsyncService 的耦合）
        audio_url = _sign_media_url(job.audio_url)
        video_url = _sign_media_url(job.video_url)
@@ -221,3 +487,64 @@ def tts_synthesize_and_submit(
            logger.exception("[lipsync_tts] 回写失败状态时异常: job_id=%s", job_id)
    finally:
        db.close()
+
+
+@shared_task(
+    name="lipsync_tts.persist_output_video",
+    max_retries=2,
+    default_retry_delay=30,
+)
+def persist_output_video_task(job_id: str, user_id: str, temp_url: str):
+    """异步转存对口型输出视频到自家 OSS（步骤⑦ — 将同步阻塞挪到后台，加速前端响应）.
+
+    - MediaKit 返回 completed 后先以 temp_url 回前端（前端可立即播放临时 URL）
+    - Celery 后台下载 temp_url 并转存 OSS，成功后更新 job.output_video_url 为永久 URL
+    - 失败则保留 temp_url，不阻断主流程
+    """
+
+    try:
+        from worker_app.db import SessionLocal  # type: ignore
+    except Exception:  # noqa: BLE001
+        from app.db import SessionLocal  # type: ignore
+
+    from packages.adapters.sqlalchemy_impl.models import LipsyncJobModel
+    from packages.shared.storage import get_shared_storage_service
+
+    db = SessionLocal()
+    try:
+        job = db.query(LipsyncJobModel).filter(LipsyncJobModel.id == job_id, LipsyncJobModel.user_id == user_id).first()
+        if job is None:
+            logger.error("[lipsync_tts.persist] Job not found: job_id=%s", job_id)
+            return
+
+        if not temp_url:
+            logger.warning("[lipsync_tts.persist] temp_url 为空，跳过转存: job_id=%s", job_id)
+            return
+
+        try:
+            import httpx
+
+            with httpx.Client(timeout=180.0, follow_redirects=True) as client:
+                resp = client.get(temp_url)
+                resp.raise_for_status()
+                data = resp.content
+
+            storage = get_shared_storage_service()
+            storage_key = f"lipsync-outputs/{user_id}/{job_id}.mp4"
+            permanent_url = storage.upload_file(io.BytesIO(data), storage_key, content_type="video/mp4")
+            # 对自家 OSS URL 重签 7 天有效期预签名，供前端播放
+            final_url = _sign_media_url(permanent_url) if permanent_url else temp_url
+            job.output_video_url = final_url
+            job.updated_at = datetime.now(timezone.utc)
+            db.commit()
+            logger.info("[lipsync_tts.persist] 输出视频已转存 OSS: job_id=%s key=%s", job_id, storage_key)
+        except Exception as exc:
+            logger.warning(
+                "[lipsync_tts.persist] 输出视频转存失败，保留临时 URL: job_id=%s err=%s",
+                job_id,
+                exc,
+            )
+    except Exception:
+        logger.exception("[lipsync_tts.persist] 未预期异常: job_id=%s", job_id)
+    finally:
+        db.close()
@@ -23,14 +23,16 @@ import {
  getLipsyncJob,
  submitRender,
  getRenderJob,
-  generateSmartCover,
+  generateRenderSmartCover,
 } from "./api/aiAvatar"
 import { getOrCreateDefaultProject } from "@/api/projects"
+import type { RenderJob } from "./types"
 import {
  normalizeEmotion,
  buildTitleConfigPayload,
  buildCoverConfigPayload,
 } from "./utils/contract"
+import { renderTitleToPngDataUrl, getVideoResolution } from "./utils/titleCanvas"

 /** 面板折叠状态 */
 type PanelKey = "video" | "voice" | "script" | "lipsync" | "title" | "cover"
@@ -54,8 +56,6 @@ const AiAvatarPage: React.FC = () => {
    "generating",
  )
  const [lipsyncErrorMessage, setLipsyncErrorMessage] = useState("")
-  /* ── 智能封面加载态 ── */
-  const [smartCoverLoading, setSmartCoverLoading] = useState(false)
  /* ── 渲染进度弹窗 ── */
  const [showRenderModal, setShowRenderModal] = useState(false)
  const [renderStatus, setRenderStatus] = useState<"generating" | "completed" | "failed">(
@@ -63,6 +63,8 @@ const AiAvatarPage: React.FC = () => {
  )
  const [renderProgress, setRenderProgress] = useState(0)
  const [renderErrorMessage, setRenderErrorMessage] = useState("")
+  /* ── 当前渲染任务对象（轮询更新；用于封面区判断渲染是否完成） ── */
+  const [currentRenderJob, setCurrentRenderJob] = useState<RenderJob | null>(null)

  /* ── 对口型轮询 ── */
  const lipsyncTimerRef = useRef<ReturnType<typeof setInterval> | null>(null)
@@ -209,6 +211,23 @@ const AiAvatarPage: React.FC = () => {
    try {
      // 确保有 project_id（AI数字人入口独立，不在项目内，自动取默认项目；#1860 P0 bugfix）
      const defaultProject = await getOrCreateDefaultProject()
+
+      // 用 Canvas 预渲染标题为 PNG dataURL（所见即所得，后端用 overlay 直接叠加）
+      let titleImageDataUrl: string | null = null
+      if (state.titleConfig.title?.trim()) {
+        try {
+          const res = await getVideoResolution(state.lipsyncJob.output_video_url || "")
+          titleImageDataUrl = renderTitleToPngDataUrl({
+            titleConfig: state.titleConfig,
+            videoWidth: res.width,
+            videoHeight: res.height,
+          })
+        } catch (canvasErr) {
+          console.warn("[渲染] 标题 Canvas 渲染失败，降级 drawtext:", canvasErr)
+          titleImageDataUrl = null
+        }
+      }
+
      const job = await submitRender({
        lipsync_job_id: state.lipsyncJob.id,
        script_id: state.script?.id,
@@ -222,8 +241,13 @@ const AiAvatarPage: React.FC = () => {
          pip_position: seg.pip_position,
          pip_scale: seg.pip_scale,
        })) as never,
-        title_config: buildTitleConfigPayload(state.titleConfig),
-        cover_config: buildCoverConfigPayload(state.coverConfig, state.coverConfig.smart_cover_url),
+        title_config: buildTitleConfigPayload(state.titleConfig, titleImageDataUrl),
+        // 封面不阻塞渲染：用户未选定封面时传空 dict，后端不生成封面；渲染完成后再单独抽帧
+        cover_config:
+          state.coverConfig.smart_cover_url ||
+          (state.coverConfig.upload_url && !state.coverConfig.upload_url.startsWith("blob:"))
+            ? buildCoverConfigPayload(state.coverConfig, state.coverConfig.smart_cover_url)
+            : {},
      })

      // 打开渲染进度弹窗，启动轮询
@@ -231,16 +255,28 @@ const AiAvatarPage: React.FC = () => {
      setRenderStatus("generating")
      setRenderProgress(job.progress ?? 0)
      setRenderErrorMessage("")
+      setCurrentRenderJob(job as RenderJob)

      if (renderTimerRef.current) clearInterval(renderTimerRef.current)
      renderTimerRef.current = setInterval(async () => {
        try {
          const updated = await getRenderJob(job.id)
          setRenderProgress(updated.progress ?? 0)
+          setCurrentRenderJob(updated)
          if (updated.status === "completed") {
            if (renderTimerRef.current) clearInterval(renderTimerRef.current)
            renderTimerRef.current = null
            setRenderStatus("completed")
+            // 渲染完成后：如果后端已返回封面（用户预上传/预设）则同步到前端；
+            // 否则不自动设置封面，由用户在封面区点击"智能获取封面"主动抽帧（步骤③④）
+            if (updated.output_cover_url) {
+              state.setCoverConfig((prev) => ({
+                ...prev,
+                mode: "auto_frame",
+                smart_cover_url: updated.output_cover_url,
+                thumbnail_url: updated.output_cover_url,
+              }))
+            }
            message.success("视频已生成并保存到成片库")
          } else if (updated.status === "failed") {
            if (renderTimerRef.current) clearInterval(renderTimerRef.current)
@@ -273,38 +309,48 @@ const AiAvatarPage: React.FC = () => {
    setRenderErrorMessage("")
  }, [])

-  /* ── 智能封面：调后端 MediaKit 选帧接口（#1822） ── */
-  const handleSmartCover = useCallback(async () => {
-    // 基于对口型成片抽帧，必须先完成对口型
-    const videoUrl = state.lipsyncJob?.output_video_url
-    if (state.lipsyncJob?.status !== "completed" || !videoUrl) {
-      message.warning("请先生成对口型视频，完成后再智能获取封面")
-      return
-    }
-    setSmartCoverLoading(true)
-    try {
-      const res = await generateSmartCover(videoUrl, buildTitleConfigPayload(state.titleConfig), 5)
-      if (res.cover_url) {
-        state.setCoverConfig((prev) => ({
-          ...prev,
-          mode: "auto_frame",
-          smart_cover_url: res.cover_url,
-          thumbnail_url: res.cover_url,
-        }))
-        message.success("智能封面已生成")
-      } else {
-        message.error(res.message || "智能封面生成失败，请稍后重试")
+  /* ── 智能封面：从最终渲染成片抽帧（POST /renders/{id}/smart-cover，步骤③④） ── */
+  const handleGenerateRenderSmartCover = useCallback(
+    async (renderId: string): Promise<{ cover_url: string; message?: string }> => {
+      try {
+        const res = await generateRenderSmartCover(renderId)
+        if (res.cover_url) {
+          state.setCoverConfig((prev) => ({
+            ...prev,
+            mode: "auto_frame",
+            smart_cover_url: res.cover_url,
+            thumbnail_url: res.cover_url,
+          }))
+          message.success("智能封面已生成")
+          return { cover_url: res.cover_url }
+        }
+        const errMsg = res.message || "智能封面生成失败，请稍后重试"
+        message.error(errMsg)
+        return { cover_url: "", message: errMsg }
+      } catch (err) {
+        console.error("智能封面生成失败:", err)
+        const errMsg = err instanceof Error ? err.message : "智能封面生成失败，请重试"
+        message.error(errMsg)
+        return { cover_url: "", message: errMsg }
      }
-    } catch (err) {
-      console.error("智能封面生成失败:", err)
-      message.error(err instanceof Error ? err.message : "智能封面生成失败，请重试")
-    } finally {
-      setSmartCoverLoading(false)
-    }
+    },
+    // state.setCoverConfig 是 zustand action 引用稳定，eslint 不需要检查
    // eslint-disable-next-line react-hooks/exhaustive-deps
-  }, [state.lipsyncJob])
+    [],
+  )

  /* ── 配置汇总 ── */
+  const coverStatus: "not_ready" | "pending" | "selected" = (() => {
+    if (
+      state.coverConfig.smart_cover_url ||
+      state.coverConfig.thumbnail_url ||
+      (state.coverConfig.upload_url && !state.coverConfig.upload_url.startsWith("blob:"))
+    ) {
+      return "selected"
+    }
+    if (currentRenderJob?.status === "completed") return "pending"
+    return "not_ready"
+  })()
  const summary = {
    videoName: state.selectedVideo?.name || null,
    voiceName: state.selectedVoice?.name || null,
@@ -312,7 +358,7 @@ const AiAvatarPage: React.FC = () => {
    lipsyncStatus: state.lipsyncJob?.status || null,
    brollCount: state.bRollSegments.length,
    hasTitle: state.titleConfig.title.length > 0,
-    hasCover: state.coverConfig.enabled,
+    coverStatus,
  }

  return (
@@ -448,9 +494,8 @@ const AiAvatarPage: React.FC = () => {
                    state.setCoverConfig((prev) => ({ ...prev, ...partial }))
                  }
                  titleConfig={state.titleConfig}
-                  onSmartCover={handleSmartCover}
-                  smartCoverLoading={smartCoverLoading}
-                  canSmartCover={state.lipsyncJob?.status === "completed"}
+                  renderJob={currentRenderJob}
+                  onGenerateRenderSmartCover={handleGenerateRenderSmartCover}
                  resolution={state.resolution}
                  onResolutionChange={state.setResolution}
                  isGenerating={state.isGenerating}
@@ -488,8 +533,9 @@ const AiAvatarPage: React.FC = () => {
          open={state.showBRollModal}
          onClose={() => state.setShowBRollModal(false)}
          existingSegments={state.bRollSegments}
-          scriptText={state.scriptText}
+          scriptText={state.lipsyncJob?.script_text || state.scriptText}
          outputDuration={state.lipsyncJob?.output_duration ?? 0}
+          sentenceTimings={state.lipsyncJob?.sentence_timings}
          onConfirm={state.addBRollSegment}
          onRemove={state.removeBRollSegment}
        />
@@ -58,21 +58,6 @@ export const getLipsyncJob = async (id: string): Promise<LipsyncJob> => {
  return response.data
 }

-/* ── 智能封面（MediaKit 抽帧 + 质量评分选最佳帧 + 可选 drawtext 标题叠加） ── */
-export const generateSmartCover = async (
-  video_url: string,
-  title_config?: Record<string, unknown> | null,
-  max_frames = 5,
-): Promise<{ cover_url: string; status: string; message: string }> => {
-  const response = await apiClient.post<{ cover_url: string; status: string; message: string }>(
-    "/ai-avatar/render/smart-cover",
-    { video_url, max_frames, title_config: title_config ?? null },
-    // smart-cover 链路：下载视频+抽帧+drawtext 加标题+上传 OSS，需要较长时间，120s 超时
-    { timeout: 120000 },
-  )
-  return response.data
-}
-
 /* ── 渲染 ── */
 export const submitRender = async (data: {
  lipsync_job_id: string
@@ -82,6 +67,7 @@ export const submitRender = async (data: {
  cover_config?: Record<string, unknown>
  project_id?: string
 }): Promise<RenderJob> => {
+  // title_config 内可含 title_image_dataurl（前端 Canvas 渲染的 PNG dataURL）
  const response = await apiClient.post<RenderJob>("/ai-avatar/render", data)
  return response.data
 }
@@ -94,3 +80,16 @@ export const getRenderJob = async (jobId: string): Promise<RenderJob> => {
 export const cancelRenderJob = async (jobId: string): Promise<void> => {
  await apiClient.post(`/ai-avatar/render/${jobId}/cancel`)
 }
+
+/* ── 从最终渲染成片智能抽封面（POST /ai-avatar/renders/{job_id}/smart-cover） ── */
+export const generateRenderSmartCover = async (
+  jobId: string,
+): Promise<{ cover_url: string; status: string; message: string }> => {
+  const response = await apiClient.post<{ cover_url: string; status: string; message: string }>(
+    `/ai-avatar/render/${jobId}/smart-cover`,
+    {},
+    // 抽帧+评分+转存 OSS 链路较长，120s 超时
+    { timeout: 120000 },
+  )
+  return response.data
+}
@@ -5,12 +5,12 @@
 * - 左侧：先选素材库（video 库）→ 再选该库视频素材（已被其他 segment 使用的素材
 *   标灰 + "已选择" 遮罩，pointer-events:none 防重复选择）
 * - 右侧：文案句子列表（点选对应段落，替代原数字索引框）/ 全屏 or 画中画 / 四角位置+大小
- *   （开始/结束时间已删除，按句子字数占比 × 口播总时长自动估算）
+ *   （开始/结束时间来自后端精确句子时间戳，基于 TTS 音频静音检测）
 * - 底部：已配置的画面插入列表（可删除）
 */
 import React, { useEffect, useMemo, useState } from "react"
 import { getAssets, getAssetLibraries, type AssetItem, type AssetLibraryItem } from "@/api/assets"
-import type { BRollSegment, BRollInsertMode, PipPosition } from "../types"
+import type { BRollSegment, BRollInsertMode, PipPosition, SentenceTiming } from "../types"
 import { splitScriptIntoSentences, type ScriptSentence } from "../utils/sentences"

 interface ModalBRollEditorProps {
@@ -18,10 +18,12 @@ interface ModalBRollEditorProps {
  onClose: () => void
  /** 当前已有的 B-roll segments（用于标灰已选素材） */
  existingSegments: BRollSegment[]
-  /** 当前文案全文（用于分句） */
+  /** 文案全文（优先使用对口型时锁定的 scriptText） */
  scriptText: string
-  /** 对口型成片总时长（秒），用于时间自动估算 */
+  /** 对口型成片总时长（秒） */
  outputDuration: number
+  /** 后端精确句子时间戳（来自 lipsyncJob.sentence_timings） */
+  sentenceTimings?: SentenceTiming[] | null
  onConfirm: (segment: BRollSegment) => void
  onRemove: (id: string) => void
 }
@@ -43,7 +45,8 @@ const ModalBRollEditor: React.FC<ModalBRollEditorProps> = ({
  onClose,
  existingSegments,
  scriptText,
-  outputDuration,
+  outputDuration: _outputDuration,
+  sentenceTimings,
  onConfirm,
  onRemove,
 }) => {
@@ -62,10 +65,10 @@ const ModalBRollEditor: React.FC<ModalBRollEditorProps> = ({
  const [pipPosition, setPipPosition] = useState<PipPosition>("top-right")
  const [pipScale, setPipScale] = useState(0.3)

-  /** 文案分句（⑤） */
+  /** 文案分句（优先使用后端精确时间戳，降级为字数比例估算） */
  const sentences = useMemo(
-    () => splitScriptIntoSentences(scriptText, outputDuration),
-    [scriptText, outputDuration],
+    () => splitScriptIntoSentences(scriptText, sentenceTimings, _outputDuration),
+    [scriptText, sentenceTimings, _outputDuration],
  )

  /** 已被现有 segments 占用的素材 id 集合（标灰、禁止重复选择） */
@@ -142,7 +145,7 @@ const ModalBRollEditor: React.FC<ModalBRollEditorProps> = ({
    setSelectedAsset(asset)
  }

-  /** 确认添加一段 B-roll（⑥ 时间取所选句子的估算起止） */
+  /** 确认添加一段 B-roll（⑥ 时间取所选句子的精确起止，后端静音检测 / 前端字数比例降级） */
  const handleConfirm = () => {
    if (!selectedAsset || !selectedSentence) return
    const startTime = selectedSentence.startTime
@@ -264,11 +267,9 @@ const ModalBRollEditor: React.FC<ModalBRollEditorProps> = ({
                          >
                            <span className="aa-sentence-item__idx">{sent.index + 1}</span>
                            <span className="aa-sentence-item__text">{sent.text}</span>
-                            {outputDuration > 0 && (
-                              <span className="aa-sentence-item__time">
-                                {sent.startTime.toFixed(1)}-{sent.endTime.toFixed(1)}s
-                              </span>
-                            )}
+                            <span className="aa-sentence-item__time">
+                              {sent.startTime.toFixed(1)}-{sent.endTime.toFixed(1)}s
+                            </span>
                          </button>
                        )
                      })}
@@ -349,7 +350,7 @@ const ModalBRollEditor: React.FC<ModalBRollEditorProps> = ({
                          selectedSentence.endTime,
                          selectedSentence.startTime + 0.5,
                        ).toFixed(1)}
-                        s （按字数自动估算）
+                        s
                      </div>
                    </>
                  ) : (
@@ -1,14 +1,15 @@
 /**
- * AI数字人 — 面板5：封面 & 生成
- * - 竖屏 9:16 封面预览（从视频截取 / 自定义上传）+ 标题文字实时叠加预览
- * - 分辨率选择（720p / 1080p / 4K）
- * - 配置汇总卡片（出镜视频/音色/文案/对口型/B-roll/标题/封面）
- * - 渐变紫色生成按钮
+ * AI数字人 — 面板5：分辨率/配置摘要/生成按钮/封面
+ * v3 调整（步骤③④）：
+ * - 布局顺序：分辨率 → 配置摘要卡片 → 🔘「开始生成视频」按钮 → （渲染完成后）封面区域
+ * - 渲染未完成时封面区域显示占位态，按钮 disabled
+ * - 「智能获取封面」从最终成片抽帧（调用 POST /renders/{id}/smart-cover），不再依赖 lipsync 状态
+ * - 修复点 2 次 bug：内部维护 smartCoverLoading，不依赖外层异步 state 更新
 *
 * 注意：v3 已删除"画面插入模式"，本面板不包含该选项。
 */
-import React, { useMemo, useRef } from "react"
-import type { AiAvatarCoverConfig, AiAvatarTitleConfig } from "../types"
+import React, { useMemo, useRef, useState } from "react"
+import type { AiAvatarCoverConfig, AiAvatarTitleConfig, RenderJob } from "../types"

 interface PanelCoverAndGenerateProps {
  coverConfig: AiAvatarCoverConfig
@@ -18,10 +19,12 @@ interface PanelCoverAndGenerateProps {
  onResolutionChange: (r: string) => void
  isGenerating: boolean
  onGenerate: () => void
-  /** 智能获取封面（MediaKit 选帧） */
-  onSmartCover: () => void
-  smartCoverLoading: boolean
-  canSmartCover: boolean
+  /** 当前渲染任务（渲染完成后才有 output_video_url，才能抽封面） */
+  renderJob: RenderJob | null
+  /** 从最终成片智能抽帧（参数 renderId），返回 { cover_url } */
+  onGenerateRenderSmartCover: (renderId: string) => Promise<{ cover_url: string; message?: string }>
+  /** 自定义上传封面（选择本地文件后由父组件处理实际上传） */
+  onUploadCover?: (file: File) => void
  /** 配置汇总信息 */
  summary: {
    videoName: string | null
@@ -30,7 +33,8 @@ interface PanelCoverAndGenerateProps {
    lipsyncStatus: string | null
    brollCount: number
    hasTitle: boolean
-    hasCover: boolean
+    /** 封面状态：'not_ready'(视频未生成) / 'pending'(视频生成了但未选) / 'selected'(已选) */
+    coverStatus: "not_ready" | "pending" | "selected"
  }
 }

@@ -66,12 +70,14 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
  onResolutionChange,
  isGenerating,
  onGenerate,
-  onSmartCover,
-  smartCoverLoading,
-  canSmartCover,
+  renderJob,
+  onGenerateRenderSmartCover,
+  onUploadCover,
  summary,
 }) => {
  const uploadInputRef = useRef<HTMLInputElement>(null)
+  // 内部维护智能封面加载态（修复点 2 次 bug：不依赖外层异步 setState 顺序）
+  const [smartCoverLoading, setSmartCoverLoading] = useState(false)

  /** 自定义上传封面 */
  const handleUploadClick = () => {
@@ -81,22 +87,44 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
  const handleFileChange = (e: React.ChangeEvent<HTMLInputElement>) => {
    const file = e.target.files?.[0]
    if (!file) return
-    // 本地预览：生成 object URL（实际上传由父级/后端链路处理）
-    const url = URL.createObjectURL(file)
-    onCoverConfigChange({ mode: "upload", upload_url: url, thumbnail_url: url })
-    // 允许重复选择同一文件
+    if (onUploadCover) {
+      onUploadCover(file)
+    } else {
+      // 本地预览兜底（实际上传由父级处理；blob URL 仅作本地展示）
+      const url = URL.createObjectURL(file)
+      onCoverConfigChange({ mode: "upload", upload_url: url, thumbnail_url: url })
+    }
    e.target.value = ""
  }

-  /** 智能获取封面（调后端 MediaKit 抽帧评分选最佳帧，#1822） */
-  const handleSmartCover = () => {
-    onCoverConfigChange({ mode: "auto_frame" })
-    onSmartCover()
+  /** 智能获取封面（从最终成片抽帧；必须等 render 完成） */
+  const handleSmartCover = async () => {
+    if (!renderJob || renderJob.status !== "completed" || !renderJob.id) return
+    setSmartCoverLoading(true)
+    try {
+      const res = await onGenerateRenderSmartCover(renderJob.id)
+      if (res.cover_url) {
+        onCoverConfigChange({
+          mode: "auto_frame",
+          smart_cover_url: res.cover_url,
+          thumbnail_url: res.cover_url,
+        })
+      } else {
+        // 失败由父组件 message 提示，这里不重复弹窗
+        console.warn("[智能封面] 返回空 cover_url:", res.message)
+      }
+    } catch (err) {
+      console.error("[智能封面] 调用失败:", err)
+    } finally {
+      setSmartCoverLoading(false)
+    }
  }

  const lipsync = summary.lipsyncStatus ? LIPSYNC_STATUS_LABEL[summary.lipsyncStatus] : null
-
  const canGenerate = summary.lipsyncStatus === "completed" && !isGenerating
+  // 渲染已完成 → 封面区可用
+  const isRenderCompleted = renderJob?.status === "completed"
+  const canSmartCover = isRenderCompleted && !smartCoverLoading

  /** 封面图实际展示的 url：智能封面 > 自定义上传 > 空 */
  const coverUrl =
@@ -120,7 +148,7 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
      wordBreak: "break-word",
      whiteSpace: "pre-wrap",
      color: titleConfig.color || "#ffffff",
-      fontSize: `${titleConfig.size}px`,
+      fontSize: `${(titleConfig.size || 48) * 0.35}px`,
      fontFamily: getFontFamily(titleConfig.font),
      fontWeight: titleConfig.bold ? "bold" : "normal",
      fontStyle: titleConfig.italic ? "italic" : "normal",
@@ -128,7 +156,6 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
      pointerEvents: "none",
    }

-    // 位置
    const pos = titleConfig.position || "bottom"
    if (pos === "top") {
      style.top = "40px"
@@ -136,7 +163,6 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
      style.top = "50%"
      style.transform = "translate(-50%, -50%)"
    } else if (pos === "custom" && titleConfig.pos_x != null && titleConfig.pos_y != null) {
-      // pos_x/pos_y 是相对预览容器的百分比坐标
      style.left = `${titleConfig.pos_x}%`
      style.top = `${titleConfig.pos_y}%`
      style.transform = "translate(-50%, -50%)"
@@ -144,67 +170,35 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
      style.bottom = "40px"
    }

-    // 描边优先于阴影（二者互斥，与 drawtext 对齐）
    if (titleConfig.stroke) {
-      // 描边宽度按字号估算，保证视觉一致
      const strokeWidth = Math.max(1, Math.round(titleConfig.size / 18))
      ;(style as React.CSSProperties)["WebkitTextStroke"] = `${strokeWidth}px rgba(0,0,0,0.75)`
      style.textShadow = "none"
    } else if (titleConfig.shadow) {
      style.textShadow = "0 2px 8px rgba(0,0,0,0.7), 0 0 2px rgba(0,0,0,0.5)"
    } else {
-      // 默认给轻微阴影保证白字在亮背景可读
-      style.textShadow = "0 2px 6px rgba(0,0,0,0.6)"
+      style.textShadow = "none"
    }

    return style
  }, [titleConfig])

+  /** 封面区占位文字 */
+  const coverPlaceholder = isRenderCompleted ? "暂无封面" : "视频生成后可选择封面"
+
+  /** 封面摘要状态文本 */
+  const coverSummaryNode = (() => {
+    if (summary.coverStatus === "selected") {
+      return <span className="aa-config-summary__value">已选择</span>
+    }
+    if (summary.coverStatus === "pending") {
+      return <span className="aa-config-summary__value">待选择</span>
+    }
+    return <span className="aa-config-summary__empty">生成视频后可选</span>
+  })()
+
  return (
    <div className="aa-cover-generate">
-      {/* 封面预览（竖屏 9:16） */}
-      <div className="aa-cover-preview">
-        {hasCoverImage ? (
-          <img src={coverUrl!} alt="封面预览" draggable={false} />
-        ) : (
-          <span className="aa-cover-preview__placeholder">暂无封面</span>
-        )}
-        {/* 智能封面加载遮罩 */}
-        {smartCoverLoading && <div className="aa-cover-preview__loading">⏳ 智能选帧中…</div>}
-        {/* 标题文字叠加层（实时预览，仅前端视觉参考，最终由后端 ffmpeg drawtext 叠加） */}
-        {showTitleOverlay && (
-          <div style={titleOverlayStyle} aria-hidden="true">
-            {titleConfig.title}
-          </div>
-        )}
-      </div>
-
-      <div className="aa-cover-actions">
-        <button
-          type="button"
-          className={`aa-btn aa-btn--ghost${coverConfig.mode === "auto_frame" ? " active" : ""}`}
-          onClick={handleSmartCover}
-          disabled={smartCoverLoading || !canSmartCover}
-          title={canSmartCover ? "基于对口型成片智能选帧" : "请先完成对口型生成"}
-        >
-          {smartCoverLoading ? "⏳ 智能选帧中…" : "🎬 智能获取封面"}
-        </button>
-        <button
-          type="button"
-          className={`aa-btn aa-btn--ghost${coverConfig.mode === "upload" ? " active" : ""}`}
-          onClick={handleUploadClick}
-        >
-          📷 自定义上传
-        </button>
-        <input
-          ref={uploadInputRef}
-          type="file"
-          accept="image/*"
-          style={{ display: "none" }}
-          onChange={handleFileChange}
-        />
-      </div>
-
      {/* 分辨率选择 */}
      <div className="aa-form-field">
        <label className="aa-label">分辨率</label>
@@ -212,6 +206,7 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
          className="aa-select"
          value={resolution}
          onChange={(e) => onResolutionChange(e.target.value)}
+          disabled={isGenerating}
        >
          {RESOLUTION_OPTIONS.map((opt) => (
            <option key={opt.value} value={opt.value}>
@@ -272,11 +267,7 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
          </div>
          <div className="aa-config-summary__row">
            <span>封面</span>
-            {summary.hasCover ? (
-              <span className="aa-config-summary__value">已开启</span>
-            ) : (
-              <span className="aa-config-summary__empty">未配置</span>
-            )}
+            {coverSummaryNode}
          </div>
        </div>

@@ -294,6 +285,60 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
            请先完成对口型生成
          </div>
        )}
+        {isGenerating && (
+          <div style={{ marginTop: 8, fontSize: 11, color: "#8c8ca1", textAlign: "center" }}>
+            视频生成中，请稍候…
+          </div>
+        )}
+      </div>
+
+      {/* 封面区域（视频生成后才激活；步骤③④要求：按钮在封面上方，完成后再显示封面区） */}
+      <div className="aa-cover-section" style={{ marginTop: 16 }}>
+        <div className="aa-label" style={{ marginBottom: 8 }}>
+          封面
+        </div>
+        {/* 封面预览（竖屏 9:16） */}
+        <div className="aa-cover-preview" style={{ opacity: isRenderCompleted ? 1 : 0.5 }}>
+          {hasCoverImage ? (
+            <img src={coverUrl!} alt="封面预览" draggable={false} />
+          ) : (
+            <span className="aa-cover-preview__placeholder">{coverPlaceholder}</span>
+          )}
+          {smartCoverLoading && <div className="aa-cover-preview__loading">⏳ 智能选帧中…</div>}
+          {showTitleOverlay && (
+            <div style={titleOverlayStyle} aria-hidden="true">
+              {titleConfig.title}
+            </div>
+          )}
+        </div>
+
+        <div className="aa-cover-actions">
+          <button
+            type="button"
+            className={`aa-btn aa-btn--ghost${coverConfig.mode === "auto_frame" ? " active" : ""}`}
+            onClick={handleSmartCover}
+            disabled={!canSmartCover}
+            title={isRenderCompleted ? "从成片智能选帧" : "请先生成视频"}
+          >
+            {smartCoverLoading ? "⏳ 智能选帧中…" : "🎬 智能获取封面"}
+          </button>
+          <button
+            type="button"
+            className={`aa-btn aa-btn--ghost${coverConfig.mode === "upload" ? " active" : ""}`}
+            onClick={handleUploadClick}
+            disabled={!isRenderCompleted || smartCoverLoading}
+            title={isRenderCompleted ? "自定义上传封面" : "请先生成视频"}
+          >
+            📷 自定义上传
+          </button>
+          <input
+            ref={uploadInputRef}
+            type="file"
+            accept="image/*"
+            style={{ display: "none" }}
+            onChange={handleFileChange}
+          />
+        </div>
      </div>
    </div>
  )
@@ -14,8 +14,8 @@ interface PanelLipsyncPreviewProps {
  onRemoveBRoll: (id: string) => void
  /** 标题配置（实时叠加预览用） */
  titleConfig?: AiAvatarTitleConfig
-  /** 标题位置变更回调（拖拽结束时调用） */
-  onTitlePositionChange?: (pos: { pos_x: number; pos_y: number }) => void
+  /** 标题位置变更回调（拖拽结束时调用，发送百分比坐标 + position:"custom"） */
+  onTitlePositionChange?: (pos: { pos_x: number; pos_y: number; position: string }) => void
 }

 const BROLL_MODE_LABEL: Record<BRollSegment["mode"], string> = {
@@ -56,11 +56,9 @@ export function PanelLipsyncPreview({
  const titleOverlayStyle: React.CSSProperties | null = titleConfig?.title
    ? {
        position: "absolute",
-        left: "50%",
-        transform: "translateX(-50%)",
        color: titleConfig.color || "#ffffff",
        fontFamily: titleConfig.font || "思源黑体",
-        fontSize: `${(titleConfig.size || 36) * 0.55}px`, // 预览等比缩
+        fontSize: `${(titleConfig.size || 48) * 0.35}px`,
        fontWeight: titleConfig.bold ? 700 : 400,
        fontStyle: titleConfig.italic ? "italic" : "normal",
        textAlign: "center",
@@ -68,11 +66,19 @@ export function PanelLipsyncPreview({
        padding: "4px 8px",
        textShadow: titleConfig.shadow ? "0 2px 4px rgba(0,0,0,0.8)" : undefined,
        WebkitTextStroke: titleConfig.stroke ? "1.5px #000" : undefined,
-        ...(titleConfig.position === "top"
-          ? { top: 8 }
-          : titleConfig.position === "bottom"
-            ? { bottom: 8 }
-            : { top: "50%", transform: "translateX(-50%) translateY(-50%)" }),
+        ...(titleConfig.position === "custom" &&
+        titleConfig.pos_x != null &&
+        titleConfig.pos_y != null
+          ? {
+              left: `${titleConfig.pos_x}%`,
+              top: `${titleConfig.pos_y}%`,
+              transform: "translateX(-50%) translateY(-50%)",
+            }
+          : titleConfig.position === "top"
+            ? { left: "50%", top: 8, transform: "translateX(-50%)" }
+            : titleConfig.position === "bottom"
+              ? { left: "50%", bottom: 8, transform: "translateX(-50%)" }
+              : { left: "50%", top: "50%", transform: "translateX(-50%) translateY(-50%)" }),
      }
    : null

@@ -105,7 +111,10 @@ export function PanelLipsyncPreview({
      const rect = previewContainerRef.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))
-      onTitlePositionChange({ pos_x: relX, pos_y: relY })
+      // 发送百分比坐标（0-100），与后端 drawtext 百分比表达式对齐
+      const xpct = Math.round((relX / rect.width) * 1000) / 10
+      const ypct = Math.round((relY / rect.height) * 1000) / 10
+      onTitlePositionChange({ pos_x: xpct, pos_y: ypct, position: "custom" })
    }
    ;(e.currentTarget as HTMLDivElement).style.cursor = "grab"
  }
@@ -44,12 +44,23 @@ export interface LipsyncJob {
  status: LipsyncStatus
  progress: number
  output_video_url: string | null
-  /** 对口型成片总时长（秒），后端返回；用于 B-roll 时间自动估算（#1809 ⑥） */
+  /** 对口型成片总时长（秒），后端返回 */
+  script_text: string
  output_duration?: number
+  /** 精确句子时间戳（后端基于 TTS 音频静音检测计算） */
+  sentence_timings?: SentenceTiming[] | null
  error_message: string | null
  created_at: string
 }

+/* ── 句子时间戳（后端精确计算） ── */
+export interface SentenceTiming {
+  index: number
+  text: string
+  start_time: number
+  end_time: number
+}
+
 /* ── B-roll 画面插入 ── */
 export type BRollInsertMode = "fullscreen" | "pip"
 export type PipPosition = "top-left" | "top-right" | "bottom-left" | "bottom-right"
@@ -77,7 +88,7 @@ export interface AiAvatarTitleConfig {
  shadow: boolean
  color: string
  auto_subtitle: boolean
-  /** 自定义位置坐标（position=custom 时生效，像素） */
+  /** 自定义位置坐标（position=custom 时生效，百分比 0-100） */
  pos_x?: number
  pos_y?: number
 }
@@ -101,6 +112,7 @@ export interface RenderJob {
  status: RenderStatus
  progress: number
  output_video_url: string | null
+  output_cover_url: string | null
  error_message: string | null
  created_at: string
 }
@@ -110,7 +122,7 @@ export const DEFAULT_TITLE_CONFIG: AiAvatarTitleConfig = {
  title: "",
  position: "bottom",
  font: "思源黑体",
-  size: 28,
+  size: 48,
  bold: true,
  italic: false,
  stroke: false,
@@ -28,10 +28,13 @@ export function normalizeEmotion(raw: string | undefined | null): VoiceEmotion {
 * 后端真实字段：text(或content)、font(或font_preset)、font_size(或size)、
 * font_color(或color，可传 #RRGGBB)、position(top/center/bottom/custom)、
 * enabled、bold、stroke{enabled,width,color}、shadow{enabled,color,offset_x,offset_y}、
- * pos_x/pos_y(custom 时)。
+ * pos_x/pos_y(custom 时)、title_image_dataurl（前端 Canvas 渲染的 PNG dataURL，WYSIWYG 路径优先）。
 * 口播标题默认 position=bottom（不传后端会默认 top 跑到画面顶部）。
 */
-export function buildTitleConfigPayload(cfg: AiAvatarTitleConfig): Record<string, unknown> {
+export function buildTitleConfigPayload(
+  cfg: AiAvatarTitleConfig,
+  titleImageDataUrl?: string | null,
+): Record<string, unknown> {
  const text = (cfg.title || "").trim()
  if (!text) return {}
  const position = cfg.position || "bottom"
@@ -39,7 +42,7 @@ export function buildTitleConfigPayload(cfg: AiAvatarTitleConfig): Record<string
    text,
    enabled: true,
    font: cfg.font || "思源黑体",
-    font_size: Math.round(cfg.size) || 36,
+    font_size: Math.round(cfg.size) || 48,
    font_color: cfg.color || "#ffffff",
    position,
    bold: !!cfg.bold,
@@ -53,6 +56,10 @@ export function buildTitleConfigPayload(cfg: AiAvatarTitleConfig): Record<string
    payload.pos_x = cfg.pos_x
    payload.pos_y = cfg.pos_y
  }
+  // 前端 Canvas 渲染好的 PNG dataURL（所见即所得，后端优先 overlay 此图片图层）
+  if (titleImageDataUrl) {
+    payload.title_image_dataurl = titleImageDataUrl
+  }
  return payload
 }

@@ -67,9 +74,14 @@ export function buildCoverConfigPayload(
    // build_cover_extract_command 读取 timestamp（截帧秒数）
    timestamp: cfg.frame_time || 0,
  }
-  if (smartCoverUrl) payload.cover_url = smartCoverUrl
+  // 智能封面 URL（后端字段名为 url/imageUrl/cover_url 都兼容，优先 url）
+  if (smartCoverUrl) {
+    payload.url = smartCoverUrl
+    payload.cover_url = smartCoverUrl
+  }
  // 自定义上传：blob: 本地预览地址无法给后端，仅 OSS URL 可用
  if (cfg.mode === "upload" && cfg.upload_url && !cfg.upload_url.startsWith("blob:")) {
+    payload.url = cfg.upload_url
    payload.upload_url = cfg.upload_url
  }
  return payload
@@ -1,5 +1,10 @@
 /**
- * AI数字人 — 文案分句 & B-roll 时间自动估算（#1809 ⑤⑥）
+ * AI数字人 — 文案分句 & B-roll 时间计算
+ *
+ * 数据来源优先级：
+ *   1. 后端 sentence_timings（基于 TTS 音频静音检测，精确到句子边界）—— 直接使用，不重新分句
+ *   2. 后端 output_duration（最终渲染视频时长） + 本地分句 —— 按字数比例估算
+ *   3. 两者都没有（对口型还在生成中）—— 返回分句文本但 startTime/endTime 全部 0，等数据到位重算
 */

 export interface ScriptSentence {
@@ -11,25 +16,67 @@ export interface ScriptSentence {
  charCount: number
  /** 累计起始字数（用于时间估算） */
  startChar: number
-  /** 估算的对口型视频内起始时间（秒） */
+  /** 对口型视频内起始时间（秒）——后端精确值或前端估算 */
  startTime: number
-  /** 估算的对口型视频内结束时间（秒） */
+  /** 对口型视频内结束时间（秒）——后端精确值或前端估算 */
  endTime: number
 }

+/** 句子分隔符：中英文句号/问号/感叹号/分号/逗号/换行（覆盖中文短视频常用断句） */
+const SENTENCE_SPLIT_RE = /[。！？!?？！;；,，\n\r]+/
+
 /**
- * 按句号/问号/感叹号/分号/换行分句（兼容中英文标点）。
- * 空文案返回空数组。时间按「该句字数 ÷ 全文总字数 × 口播总时长」线性估算。
+ * 分句并计算每句的起止时间。
+ *
+ * @param sentenceTimings 后端返回的精确句子时间戳（来自 lipsync_job.sentence_timings）。
+ *   非空时直接按后端返回的句子列表渲染，不再本地分句（避免前后端分句不一致导致时间错位）。
+ * @param outputDuration  最终视频时长（秒）。对口型预览阶段可能为 0，此时降级估算只能给 0。
 */
 export function splitScriptIntoSentences(
  scriptText: string,
-  outputDuration: number,
+  sentenceTimings?:
+    { index?: number; text?: string; start_time: number; end_time: number }[] | null,
+  outputDuration: number = 0,
 ): ScriptSentence[] {
  const text = (scriptText || "").trim()
  if (!text) return []

+  // 1. 后端返回了 sentence_timings：校验通过就直接用，跳过本地分句
+  //    校验条件放宽：只要是数组、至少1条、每条 start_time/end_time 是数字即可
+  //    （不再强制要求条数相等——后端静音检测可能按停顿切出更多/更少边界，
+  //    比如文案用逗号连写时本地只分1句、后端按停顿切4句，后端的切法才是对的）
+  if (Array.isArray(sentenceTimings) && sentenceTimings.length > 0) {
+    const valid = sentenceTimings.every(
+      (t) =>
+        t &&
+        typeof t.start_time === "number" &&
+        typeof t.end_time === "number" &&
+        isFinite(t.start_time) &&
+        isFinite(t.end_time) &&
+        t.end_time >= t.start_time,
+    )
+    if (valid) {
+      let accChar = 0
+      return sentenceTimings.map((t, i) => {
+        const sentenceText = (t.text || "").trim() || `句子${i + 1}`
+        const charCount = sentenceText.replace(/\s/g, "").length
+        const sentence: ScriptSentence = {
+          index: typeof t.index === "number" ? t.index : i,
+          text: sentenceText,
+          charCount,
+          startChar: accChar,
+          startTime: round1(t.start_time),
+          endTime: round1(t.end_time),
+        }
+        accChar += charCount
+        return sentence
+      })
+    }
+  }
+
+  // 2. 本地分句 + 按字数比例估算（降级路径）
  const rawParts = text
-    .split(/[。！？!?；;\n\r]+/)
+    .split(SENTENCE_SPLIT_RE)
    .map((part) => part.trim())
    .filter((part) => part.length > 0)

@@ -0,0 +1,174 @@
+/**
+ * AI数字人 — 标题 Canvas 渲染工具
+ *
+ * 把标题按前端预览的 HTML/CSS 效果画到透明背景 PNG 上（与视频同分辨率），
+ * 以 dataURL 形式传给后端，后端用 FFmpeg overlay 直接叠加图层，
+ * 彻底解决前端 HTML/CSS 预览 ≠ FFmpeg drawtext 成片的 WYSIWYG 问题。
+ */
+import type { AiAvatarTitleConfig } from "../types"
+
+export interface RenderTitlePngOptions {
+  /** 标题配置 */
+  titleConfig: AiAvatarTitleConfig
+  /** 视频宽度（像素），默认 720 */
+  videoWidth?: number
+  /** 视频高度（像素），默认 1280 */
+  videoHeight?: number
+}
+
+/**
+ * 将标题渲染为透明背景 PNG 的 dataURL（data:image/png;base64,...）
+ * Canvas 尺寸与视频一致，保证叠加时 1:1 像素对齐。
+ *
+ * 标题为空时返回 null。
+ */
+export function renderTitleToPngDataUrl(opts: RenderTitlePngOptions): string | null {
+  const { titleConfig, videoWidth = 720, videoHeight = 1280 } = opts
+  if (!titleConfig) return null
+  const rawTitle = (titleConfig.title || "").trim()
+  if (!rawTitle) return null
+
+  // 按 / 或 ／ 分割为多行
+  const lines = rawTitle
+    .split(/[/／]/)
+    .map((l) => l.trim())
+    .filter((l) => l.length > 0)
+  if (lines.length === 0) return null
+
+  const canvas = document.createElement("canvas")
+  canvas.width = videoWidth
+  canvas.height = videoHeight
+  const ctx = canvas.getContext("2d")
+  if (!ctx) return null
+
+  const size = Math.max(12, Math.round(titleConfig.size || 48))
+  const bold = !!titleConfig.bold
+  const italic = !!titleConfig.italic
+  const color = titleConfig.color || "#ffffff"
+  const stroke = !!titleConfig.stroke
+  const shadow = !!titleConfig.shadow
+
+  // 字体族 fallback 链：优先中文字体
+  const fontFamily =
+    '"Noto Sans CJK SC","Source Han Sans CN","PingFang SC","Microsoft YaHei",sans-serif'
+  const fontParts: string[] = []
+  if (italic) fontParts.push("italic")
+  if (bold) fontParts.push("bold")
+  fontParts.push(`${size}px`, fontFamily)
+  ctx.font = fontParts.join(" ")
+  ctx.fillStyle = color
+  ctx.textAlign = "center"
+  ctx.textBaseline = "middle"
+
+  // 阴影（shadow=true 时开启）
+  if (shadow) {
+    ctx.shadowColor = "rgba(0,0,0,0.8)"
+    ctx.shadowBlur = 4
+    ctx.shadowOffsetX = 0
+    ctx.shadowOffsetY = 2
+  }
+
+  // 位置计算：与 PanelLipsyncPreview 的 CSS 对齐
+  // 预览用 top/bottom 8px padding + transform translateX(-50%) 居中；
+  // 这里画到整尺寸 canvas，padding 按比例放大到全分辨率（预览缩放 0.35x 时 8px ≈ 23px 全尺寸，
+  // 为更贴近原 CSS 16px 安全边距，用 16px 作为内边距）。
+  const PAD = 16
+  let centerX = videoWidth / 2
+  const position = titleConfig.position || "bottom"
+  const lineGap = size * 1.2
+  const totalTextH = lines.length * lineGap - (lineGap - size) // 所有行的总高度
+  // 文本块顶部 y（textBaseline=middle 时首行基线）
+  let firstLineY: number
+  if (
+    position === "custom" &&
+    typeof titleConfig.pos_x === "number" &&
+    typeof titleConfig.pos_y === "number"
+  ) {
+    centerX = (Math.max(0, Math.min(100, titleConfig.pos_x)) / 100) * videoWidth
+    const centerY = (Math.max(0, Math.min(100, titleConfig.pos_y)) / 100) * videoHeight
+    firstLineY = centerY - totalTextH / 2 + size / 2
+  } else if (position === "top") {
+    // 顶部：y = size/2 + PAD
+    firstLineY = size / 2 + PAD
+  } else if (position === "center") {
+    firstLineY = videoHeight / 2 - totalTextH / 2 + size / 2
+  } else {
+    // bottom（默认）
+    firstLineY = videoHeight - totalTextH - PAD + size / 2
+  }
+
+  // 描边参数（stroke=true 或 bold 默认细描边模拟粗体时都画；
+  // 注意：浏览器原生 bold 已经是粗体 glyph，Canvas 这里对 stroke=true 才加黑描边，
+  // 与预览 CSS 的 WebkitTextStroke 保持一致，不对 bold 自动加描边避免双粗）。
+  const doStroke = stroke
+  // 逐行绘制
+  lines.forEach((line, idx) => {
+    const y = firstLineY + idx * lineGap
+    if (doStroke) {
+      const prevShadowColor = ctx.shadowColor
+      const prevShadowBlur = ctx.shadowBlur
+      // 描边不要带阴影（避免黑色描边发虚）
+      ctx.shadowColor = "rgba(0,0,0,0)"
+      ctx.shadowBlur = 0
+      ctx.lineWidth = Math.max(2, size * 0.06)
+      ctx.strokeStyle = "#000000"
+      ctx.lineJoin = "round"
+      ctx.strokeText(line, centerX, y)
+      // 恢复阴影
+      if (shadow) {
+        ctx.shadowColor = "rgba(0,0,0,0.8)"
+        ctx.shadowBlur = 4
+      } else {
+        ctx.shadowColor = prevShadowColor
+        ctx.shadowBlur = prevShadowBlur
+      }
+    }
+    ctx.fillText(line, centerX, y)
+  })
+
+  try {
+    return canvas.toDataURL("image/png")
+  } catch {
+    return null
+  }
+}
+
+/**
+ * 获取视频真实分辨率（HTMLVideoElement + loadedmetadata，超时 3 秒兜底 720×1280）。
+ */
+export function getVideoResolution(
+  videoUrl: string,
+  timeoutMs = 3000,
+): Promise<{ width: number; height: number }> {
+  return new Promise((resolve) => {
+    if (!videoUrl) {
+      resolve({ width: 720, height: 1280 })
+      return
+    }
+    const video = document.createElement("video")
+    video.preload = "metadata"
+    video.muted = true
+    video.playsInline = true
+    video.crossOrigin = "anonymous"
+    let settled = false
+    const done = (w: number, h: number) => {
+      if (settled) return
+      settled = true
+      video.removeAttribute("src")
+      video.load()
+      resolve({ width: w, height: h })
+    }
+    const timer = window.setTimeout(() => done(720, 1280), timeoutMs)
+    video.onloadedmetadata = () => {
+      window.clearTimeout(timer)
+      const w = video.videoWidth || 720
+      const h = video.videoHeight || 1280
+      done(w, h)
+    }
+    video.onerror = () => {
+      window.clearTimeout(timer)
+      done(720, 1280)
+    }
+    video.src = videoUrl
+  })
+}
@@ -703,6 +703,9 @@ class LipsyncJobModel(Base):
    error_message = Column(Text, nullable=False, default="")
    error_code = Column(String(100), nullable=False, default="")

+    # 精确句子时间戳（TTS 合成后由 silencedetect 计算，用于 B-roll 精确定位）
+    sentence_timings = Column(JSON, nullable=True)  # list[{index,text,start_time,end_time}]
+
    # 时间戳
    submitted_at = Column(DateTime, nullable=True)
    completed_at = Column(DateTime, nullable=True)
@@ -420,6 +420,11 @@ def _escape_drawtext_text(text: str) -> str:
    return result


+# 粗体字体已由前端 Canvas 直接渲染（Canvas 使用浏览器原生粗体 glyph），
+# FFmpeg 侧不再需要查找 Bold 字体文件；drawtext 仅作为旧版前端的降级路径，
+# 通过 borderw 黑色细描边模拟粗体（见 build_title_drawtext_filter）。
+
+
 def _resolve_font_path(font_name: str) -> str:
    """解析字体名到服务器实际字体文件路径。

@@ -427,6 +432,9 @@ def _resolve_font_path(font_name: str) -> str:
    1. 通过 DRAWTEXT_FONT_MAP 映射前端字体名到服务器关键字
    2. 在 DRAWTEXT_FONT_SEARCH_PATHS 中查找匹配路径
    3. 未找到则返回空字符串（drawtext 使用内置默认字体）
+
+    注：粗体已由前端 Canvas 渲染时直接用浏览器 bold glyph 绘制，
+    此处仅作为旧版前端降级路径，无需切换 Bold 字体文件。
    """
    keyword = DRAWTEXT_FONT_MAP.get(font_name, font_name)
    import os
@@ -470,8 +478,10 @@ def build_title_drawtext_filter(
    if not title_config or not isinstance(title_config, dict):
        return None

-    # 字段名归一化：兼容 content/text、font_preset/font 两套命名
-    text = (title_config.get("text") or title_config.get("content") or "").strip()
+    # 字段名归一化：兼容 content/text/title 三套命名
+    text = (
+        title_config.get("text") or title_config.get("content") or title_config.get("title") or ""
+    ).strip()
    if not text:
        return None

@@ -481,13 +491,13 @@ def build_title_drawtext_filter(

    # ── 样式参数 ──
    font_name = title_config.get("font") or title_config.get("font_preset") or "思源黑体"
-    font_size = int(title_config.get("font_size") or title_config.get("size") or 36)
+    font_size = int(title_config.get("font_size") or title_config.get("size") or 48)
    font_color = title_config.get("font_color") or title_config.get("color") or "#ffffff"
    # 去掉 # 前缀（drawtext 用纯 hex 或颜色名）
    if font_color.startswith("#"):
        font_color = font_color[1:]

-    position = title_config.get("position", "top")
+    position = title_config.get("position") or "bottom"
    bold = bool(title_config.get("bold", True))
    stroke = title_config.get("stroke")
    shadow = title_config.get("shadow")
@@ -495,7 +505,7 @@ def build_title_drawtext_filter(
    # ── 构建 drawtext 参数 ──
    params: list[str] = []

-    # 字体文件
+    # 字体文件（drawtext 降级路径：粗体通过 borderw 黑色描边模拟）
    font_path = _resolve_font_path(font_name)
    if font_path:
        escaped_path = font_path.replace("\\", "\\\\").replace(":", "\\\\:").replace("'", "\\\\'")
@@ -508,13 +518,11 @@ def build_title_drawtext_filter(
    params.append(f"fontsize={font_size}")
    params.append(f"fontcolor={font_color}")

-    # 粗体：drawtext 没有独立的 bold 参数，通过加大 borderw 模拟视觉粗体效果。
-    # 注意：不能使用 `font=bold`——FFmpeg drawtext 的 font 参数需要 fontconfig 能解析的
-    # 字体族名，而 "bold" 不是合法族名，会导致整个 filter_complex 解析失败（exit code 234）。
-    # 当用户未显式配置描边宽度时，bold 模式自动将 borderw 提升到 3 以模拟粗体。
-
    # 描边（borderw 需要 libfreetype 支持）
-    # 粗体无显式描边时，自动用 borderw=3 + 近色描边模拟粗体；显式 stroke 按用户配置走
+    # 之前用 borderw=3 + font_color 同色描边模拟粗体，会在小字号/竖屏视频上造成
+    # 字形偏移、边缘重影，看起来像文字被打印了两次（用户截图中的标题"曝光曝光…"）。
+    # 修复：粗体改用黑色细描边（borderw=2, 黑色），视觉上清晰加粗且不产生偏移。
+    # 用户显式开启 stroke 时按用户配置走；粗体+无stroke 默认黑色细描边。
    border_width = 0
    border_color = "000000"
    if stroke:
@@ -526,9 +534,9 @@ def build_title_drawtext_filter(
                border_width = int(stroke.get("width", 2))
                border_color = (stroke.get("color") or "#000000").lstrip("#")
    elif bold:
-        # 粗体模式且未配描边：加大描边宽度模拟粗体效果
-        border_width = 3
-        border_color = font_color  # 用字体同色描边，视觉上加粗字形而非黑边
+        # 粗体模式且未配描边：黑色细描边，模拟粗体同时保证不重影
+        border_width = 2
+        border_color = "000000"
    if border_width > 0:
        params.append(f"borderw={border_width}")
        params.append(f"bordercolor={border_color}")
@@ -556,8 +564,13 @@ def build_title_drawtext_filter(
        and not isinstance(pos_x, bool)
        and not isinstance(pos_y, bool)
    ):
-        params.append(f"x={int(pos_x)}")
-        params.append(f"y={int(pos_y)}")
+        # pos_x/pos_y 为百分比坐标（0-100），转换为 drawtext 表达式
+        # 例如 pos_x=50 → x=(w-text_w)*0.50（水平居中偏50%）
+        #      pos_y=30 → y=(h-text_h)*0.30
+        pct_x = max(0.0, min(100.0, float(pos_x))) / 100.0
+        pct_y = max(0.0, min(100.0, float(pos_y))) / 100.0
+        params.append(f"x=(w-text_w)*{pct_x:.4f}")
+        params.append(f"y=(h-text_h)*{pct_y:.4f}")
    else:
        # 三档预设位置：top / center / bottom
        # x 始终水平居中：(w-text_w)/2
@@ -573,6 +586,43 @@ def build_title_drawtext_filter(
    return "drawtext=" + ":".join(params)


+def build_title_overlay_filter(
+    title_config: dict[str, Any],
+    output_width: int,  # noqa: ARG001 - 保留参数签名，PNG 已按视频分辨率绘制
+    output_height: int,  # noqa: ARG001
+    title_png_path: str,
+    *,
+    title_input_label: str = "[1:v]",
+    base_label: str = "[0:v]",
+    output_label: str = "vout_titled",
+) -> str | None:
+    """构建标题 PNG 图层 overlay 滤镜（WYSIWYG 路径）。
+
+    前端用 Canvas 把标题画成与视频同分辨率的透明 PNG（所见即所得），
+    后端直接 overlay=0:0 叠加即可，PNG 透明区域不遮挡视频。
+
+    Args:
+        title_config: 标题配置 dict（仅用来判断降级）
+        output_width: 输出宽度（未使用，PNG 已按该分辨率绘制）
+        output_height: 输出高度（未使用）
+        title_png_path: 已保存到本地的标题 PNG 文件路径
+        title_input_label: 标题 PNG 在 filter_complex 中的输入标签（默认 "[1:v]"）
+        base_label: 前序滤镜输出标签（如 B-roll 输出 "[vout]"）
+        output_label: overlay 输出标签名
+
+    Returns:
+        overlay 滤镜字符串；title_png_path 为空/文件不存在时返回 None（降级到 drawtext）
+    """
+    import os
+
+    if not title_png_path or not os.path.isfile(title_png_path):
+        return None
+    if not title_config or not isinstance(title_config, dict):
+        return None
+
+    return f"{base_label}{title_input_label}overlay=0:0[{output_label}]"
+
+
 # ── B-roll 叠加滤镜 ─────────────────────────────────────────────────────────


@@ -695,7 +745,9 @@ def _build_fullscreen_filters(
    for idx, seg in enumerate(sorted_fs_segments):
        start = seg.get("start_time", 0)
        # 每段 B-roll 之前是否有主视频片段？
-        has_main_before = (idx == 0 and start > 0) or (idx > 0 and sorted_fs_segments[idx - 1].get("end_time", 0) < start)
+        has_main_before = (idx == 0 and start > 0) or (
+            idx > 0 and sorted_fs_segments[idx - 1].get("end_time", 0) < start
+        )
        if has_main_before:
            segment_labels.append(f"[main{idx}]")
        segment_labels.append(f"[br{idx}]")
@@ -765,7 +817,6 @@ def _build_pip_filters(
    return "".join(parts), cur_label or "vout"


-
 def build_cover_extract_command(
    cover_config: dict[str, Any],
    output_path: str,
@@ -318,3 +318,120 @@ class TestBrollOverlayFilter:
            "/tmp/cover.jpg",
        )
        assert "scale=" in cmd
+
+
+def _make_mock_auth_user(user_id="user-1"):
+    """构造 AuthenticatedUser：current_user.user.id."""
+    auth = MagicMock()
+    auth.user.id = user_id
+    return auth
+
+
+class TestRenderSmartCoverRoute:
+    """POST /renders/{job_id}/smart-cover — 从成片智能抽封面（步骤②）."""
+
+    def test_smart_cover_job_not_found_returns_404(self):
+        """渲染任务不存在 → 404."""
+        from app.api.routes.ai_avatar_render import generate_render_smart_cover
+        from fastapi import HTTPException
+
+        mock_service = MagicMock()
+        mock_service.get_render_job.return_value = None
+        mock_db = MagicMock()
+        mock_user = _make_mock_auth_user()
+
+        # 函数内部 `from app.services.ai_avatar_render_service import AiAvatarRenderService`
+        with patch("app.services.ai_avatar_render_service.AiAvatarRenderService", return_value=mock_service):
+            with pytest.raises(HTTPException) as exc_info:
+                generate_render_smart_cover(job_id="render-missing", current_user=mock_user, db=mock_db)
+
+        assert exc_info.value.status_code == 404
+        assert "不存在" in exc_info.value.detail
+        mock_service.get_render_job.assert_called_once_with("render-missing", "user-1")
+
+    def test_smart_cover_job_not_completed_returns_400(self):
+        """任务未 completed（如 processing）→ 400."""
+        from app.api.routes.ai_avatar_render import generate_render_smart_cover
+        from fastapi import HTTPException
+
+        mock_service = MagicMock()
+        mock_job = _make_mock_render_job(status="processing", output_video_url="https://oss/video.mp4")
+        mock_service.get_render_job.return_value = mock_job
+        mock_db = MagicMock()
+        mock_user = _make_mock_auth_user()
+
+        with patch("app.services.ai_avatar_render_service.AiAvatarRenderService", return_value=mock_service):
+            with pytest.raises(HTTPException) as exc_info:
+                generate_render_smart_cover(job_id="render-1", current_user=mock_user, db=mock_db)
+
+        assert exc_info.value.status_code == 400
+        assert "先完成视频生成" in exc_info.value.detail
+
+    def test_smart_cover_empty_video_url_returns_400(self):
+        """已 completed 但 output_video_url 为空/空白 → 400."""
+        from app.api.routes.ai_avatar_render import generate_render_smart_cover
+        from fastapi import HTTPException
+
+        mock_service = MagicMock()
+        mock_job = _make_mock_render_job(status="completed", output_video_url="   ")
+        mock_service.get_render_job.return_value = mock_job
+        mock_db = MagicMock()
+        mock_user = _make_mock_auth_user()
+
+        with patch("app.services.ai_avatar_render_service.AiAvatarRenderService", return_value=mock_service):
+            with pytest.raises(HTTPException) as exc_info:
+                generate_render_smart_cover(job_id="render-1", current_user=mock_user, db=mock_db)
+
+        assert exc_info.value.status_code == 400
+        assert "URL 为空" in exc_info.value.detail
+
+    def test_smart_cover_success_updates_db_and_returns_url(self):
+        """抽帧成功 → 更新 job.cover_config / output_cover_url 并 commit，返回 completed."""
+        from app.api.routes.ai_avatar_render import generate_render_smart_cover
+
+        mock_service = MagicMock()
+        mock_job = _make_mock_render_job(
+            status="completed",
+            output_video_url="https://oss/final.mp4",
+        )
+        mock_job.cover_config = {"mode": "manual"}
+        mock_service.get_render_job.return_value = mock_job
+        mock_db = MagicMock()
+        mock_user = _make_mock_auth_user()
+
+        with (
+            patch("app.services.ai_avatar_render_service.AiAvatarRenderService", return_value=mock_service),
+            patch(
+                "app.api.routes.ai_avatar_render.generate_smart_cover", return_value="https://oss/cover.jpg"
+            ) as mock_gen,
+        ):
+            result = generate_render_smart_cover(job_id="render-1", current_user=mock_user, db=mock_db)
+
+        mock_gen.assert_called_once_with("https://oss/final.mp4", job_id="render-1", max_frames=5)
+        assert result.status == "completed"
+        assert result.cover_url == "https://oss/cover.jpg"
+        assert mock_job.output_cover_url == "https://oss/cover.jpg"
+        assert mock_job.cover_config["mode"] == "auto_frame"
+        assert mock_job.cover_config["url"] == "https://oss/cover.jpg"
+        mock_db.commit.assert_called_once()
+
+    def test_smart_cover_extract_failure_returns_fallback_failed(self):
+        """generate_smart_cover 抛异常 → fallback_failed，不抛错不写 DB."""
+        from app.api.routes.ai_avatar_render import generate_render_smart_cover
+
+        mock_service = MagicMock()
+        mock_job = _make_mock_render_job(status="completed", output_video_url="https://oss/final.mp4")
+        mock_service.get_render_job.return_value = mock_job
+        mock_db = MagicMock()
+        mock_user = _make_mock_auth_user()
+
+        with (
+            patch("app.services.ai_avatar_render_service.AiAvatarRenderService", return_value=mock_service),
+            patch("app.api.routes.ai_avatar_render.generate_smart_cover", side_effect=RuntimeError("mediakit down")),
+        ):
+            result = generate_render_smart_cover(job_id="render-1", current_user=mock_user, db=mock_db)
+
+        assert result.status == "fallback_failed"
+        assert result.cover_url == ""
+        # 失败时不写 cover_config / 不 commit
+        mock_db.commit.assert_not_called()
@@ -628,3 +628,58 @@ class TestAiAvatarRenderService:
        err = AiAvatarRenderError("测试错误", code="TestCode")
        assert err.code == "TestCode"
        assert str(err) == "测试错误"
+
+
+class TestAiAvatarRenderCoverPassthrough:
+    """execute_render 中封面透传逻辑（320~329 行）：cover_config 含 url/imageUrl/cover_url 时直接透传到 output_cover_url."""
+
+    def _run_execute(self, mock_job, mock_lipsync_job):
+        """驱动 execute_render 跑到完成阶段的通用脚手架（mock IO 部分）."""
+        from app.services.ai_avatar_render_service import AiAvatarRenderService
+
+        mock_db = _make_mock_db()
+        mock_filter = MagicMock()
+        # query.filter 返回同一个 filter 两次（render_job 查询、lipsync 查询）
+        mock_filter.first.side_effect = [mock_job, mock_lipsync_job]
+        mock_query = MagicMock()
+        mock_query.filter.return_value = mock_filter
+        mock_db.query.return_value = mock_query
+
+        svc = AiAvatarRenderService(mock_db)
+        with (
+            patch.object(svc, "_download_video", return_value="/tmp/video.mp4"),
+            patch.object(svc, "_upload_to_oss", side_effect=lambda path, key: f"https://oss/{key}"),
+            patch("subprocess.run") as mock_run,
+            patch("tempfile.TemporaryDirectory") as tmpdir_mock,
+            patch("app.services.ai_avatar_cover_service.generate_smart_cover", return_value=""),
+            patch("packages.domain.generated_video.GeneratedVideo.create", return_value=MagicMock()),
+            patch(
+                "packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository"
+            ) as repo_cls,
+        ):
+            import subprocess as _sp
+
+            mock_run.return_value = _sp.CompletedProcess(args=[], returncode=0, stdout="", stderr="")
+            import tempfile as _tf
+
+            tmpdir_mock.return_value.__enter__ = MagicMock(return_value="/tmp/testdir")
+            tmpdir_mock.return_value.__exit__ = MagicMock(return_value=False)
+            repo_cls.return_value = MagicMock()
+            svc.execute_render(mock_job.id)
+        return mock_db, mock_job
+
+    def test_cover_url_in_cover_config_passthrough_to_output_cover(self):
+        """cover_config.url 存在 → 透传到 output_cover_url."""
+        mock_job = _make_mock_render_job(job_id="render-cov-1", status="pending")
+        mock_job.cover_config = {"mode": "upload", "url": "https://oss/user-cover.jpg"}
+        mock_lipsync_job = _make_mock_lipsync_job(status="completed", output_duration=10.0)
+        _, job = self._run_execute(mock_job, mock_lipsync_job)
+        assert job.output_cover_url == "https://oss/user-cover.jpg"
+
+    def test_cover_imageurl_fallback_also_passthrough(self):
+        """cover_config.imageUrl（老字段）存在 → 也透传到 output_cover_url."""
+        mock_job = _make_mock_render_job(job_id="render-cov-2", status="pending")
+        mock_job.cover_config = {"mode": "upload", "imageUrl": "https://oss/user-cover2.jpg"}
+        mock_lipsync_job = _make_mock_lipsync_job(status="completed", output_duration=10.0)
+        _, job = self._run_execute(mock_job, mock_lipsync_job)
+        assert job.output_cover_url == "https://oss/user-cover2.jpg"
@@ -288,3 +288,47 @@ class TestCancelJobTtsProcessing:

        result = svc.cancel_job("job-1", "user-1")
        assert result.status == "cancelled"
+
+
+class TestCreateJobCommitOrder:
+    """验证事务顺序修复：create_job 必须先 commit 再发 Celery 任务，避免 worker 消费时 job 不可见。"""
+
+    def test_commit_called_before_apply_async_in_tts_mode(self):
+        """TTS 模式：db.commit() 必须在 apply_async() 之前调用，防止 worker 查不到 job 永远卡在 tts_processing。"""
+        svc, client, cosy = _make_service_with_mocks()
+        call_order: list[str] = []
+
+        def track_commit():
+            call_order.append("commit")
+
+        def track_apply_async(*args, **kwargs):
+            call_order.append("apply_async")
+
+        svc.db.commit.side_effect = track_commit
+
+        with patch("app.services.lipsync_service.tts_synthesize_and_submit") as mock_task:
+            mock_task.apply_async = MagicMock(side_effect=track_apply_async)
+            svc.create_job(
+                user_id="user-1",
+                video_url="https://example.com/video.mp4",
+                voice_id="v-1",
+                script_text="测试",
+            )
+
+        # 至少有一次 commit 在 apply_async 之前
+        assert "commit" in call_order, "db.commit 必须被调用"
+        assert "apply_async" in call_order, "apply_async 必须被调用"
+        assert call_order.index("commit") < call_order.index(
+            "apply_async"
+        ), f"事务顺序错误：commit 必须在 apply_async 之前，实际顺序 {call_order}"
+
+    def test_job_not_found_retry_mechanism_exists(self):
+        """worker 侧 job not found 必须有重试机制（self.retry），而不是静默 return。"""
+        import inspect
+
+        from app.tasks.lipsync_tts import tts_synthesize_and_submit
+
+        source = inspect.getsource(tts_synthesize_and_submit.run)
+        assert (
+            "self.retry" in source or "retry" in source
+        ), "tts_synthesize_and_submit 在 job not found 时必须重试，防止静默失败"
@@ -185,7 +185,10 @@ class TestTtsSynthesizeAndSubmit:
        mk_client.submit_lipsync.assert_called_once()
        call_kwargs = mk_client.submit_lipsync.call_args.kwargs
        assert call_kwargs["client_token"] == "job-1"
-        assert call_kwargs["audio_url"].endswith("?signed")
+        # CosyVoice 临时 URL 经 _sign_media_url 透传（mock 统一追加 ?signed），
+        # 自家 OSS 才会被重签，外部 URL 原样透传；job.audio_url 存原始临时 URL
+        assert call_kwargs["audio_url"] == "https://tts/raw.mp3?signed"
+        assert job.audio_url == "https://tts/raw.mp3"
        session.commit.assert_called()
        session.close.assert_called_once()

@@ -387,3 +390,239 @@ class TestSignMediaUrl:

        assert result == "https://anything.example.com/a.mp3"
        fake_storage.get_download_url.assert_not_called()
+
+
+class TestPersistOutputVideoTask:
+    """persist_output_video_task：下载 MediaKit 临时视频 → 上传自有 OSS → 更新 DB."""
+
+    def _make_persist_job(self, **kwargs):
+        job = MagicMock()
+        job.id = kwargs.get("job_id", "job-1")
+        job.user_id = kwargs.get("user_id", "user-1")
+        job.output_video_url = kwargs.get("output_video_url", "https://temp.mk/output.mp4")
+        job.updated_at = None
+        return job
+
+    def _persist_patches(self, *, job, video_bytes=b"FAKEMP4", download_side_effect=None, upload_url=None):
+        """统一 patch：SessionLocal、httpx.Client、storage、_sign_media_url."""
+        fake_app_db = ModuleType("app.db")
+        fake_worker_db = ModuleType("worker_app.db")
+        session, factory = _build_session(job)
+        fake_app_db.SessionLocal = factory
+        fake_worker_db.SessionLocal = factory
+
+        # httpx.Client 上下文管理器
+        fake_response = MagicMock()
+        fake_response.content = video_bytes
+        fake_response.raise_for_status = MagicMock()
+        fake_client = MagicMock()
+        fake_client.get.return_value = fake_response
+        fake_client_cm = MagicMock()
+        fake_client_cm.__enter__ = MagicMock(return_value=fake_client)
+        fake_client_cm.__exit__ = MagicMock(return_value=False)
+        FakeHttpxClient = MagicMock(return_value=fake_client_cm)
+        if download_side_effect is not None:
+            fake_client.get.side_effect = download_side_effect
+
+        # storage
+        storage = MagicMock()
+        storage.public_url = "https://oss.example.com/"
+        storage.upload_file.return_value = upload_url or "https://oss.example.com/lipsync-outputs/user-1/job-1.mp4"
+        # _sign_media_url 内部会调 storage.get_download_url，必须mock返回字符串
+        _upload_url = upload_url or "https://oss.example.com/lipsync-outputs/user-1/job-1.mp4"
+        storage.get_download_url.return_value = _upload_url + "?signed"
+
+        fake_httpx = ModuleType("httpx")
+        fake_httpx.Client = FakeHttpxClient
+
+        patches = [
+            patch.dict(
+                sys.modules,
+                {"app.db": fake_app_db, "worker_app.db": fake_worker_db, "httpx": fake_httpx},
+            ),
+            patch("packages.shared.storage.get_shared_storage_service", return_value=storage),
+            patch("app.tasks.lipsync_tts._sign_media_url", side_effect=lambda url: url + "?signed" if url else url),
+        ]
+        return session, fake_client, storage, patches
+
+    def test_success_download_upload_updates_db(self):
+        """正常路径：下载 temp_url → 上传 OSS → 签名 → 写回 DB commit."""
+        from app.tasks.lipsync_tts import persist_output_video_task
+
+        job = self._make_persist_job(output_video_url="https://temp.mk/x.mp4")
+        session, fake_client, storage, patches = self._persist_patches(
+            job=job, video_bytes=b"VIDEODATA", upload_url="https://oss.example.com/lipsync-outputs/user-1/job-1.mp4"
+        )
+        entered = [p.__enter__() for p in patches]
+        try:
+            persist_output_video_task("job-1", "user-1", "https://temp.mk/x.mp4")
+        finally:
+            for p in reversed(patches):
+                p.__exit__(None, None, None)
+
+        fake_client.get.assert_called_once_with("https://temp.mk/x.mp4")
+        storage.upload_file.assert_called_once()
+        call_args = storage.upload_file.call_args.args
+        # 上传的 key 必须是 lipsync-outputs/{user_id}/{job_id}.mp4
+        assert call_args[1] == "lipsync-outputs/user-1/job-1.mp4"
+        # upload_file 返回永久 URL，再被 _sign_media_url 追加 ?signed
+        assert job.output_video_url == "https://oss.example.com/lipsync-outputs/user-1/job-1.mp4?signed"
+        assert job.updated_at is not None
+        session.commit.assert_called_once()
+        session.close.assert_called_once()
+
+    def test_download_failure_keeps_temp_url_no_commit(self):
+        """下载失败（raise）→ 记录 warning、保留 temp_url、不抛异常."""
+        from app.tasks.lipsync_tts import persist_output_video_task
+
+        job = self._make_persist_job(output_video_url="https://temp.mk/x.mp4")
+        session, fake_client, storage, patches = self._persist_patches(
+            job=job, download_side_effect=RuntimeError("network down")
+        )
+        entered = [p.__enter__() for p in patches]
+        try:
+            persist_output_video_task("job-1", "user-1", "https://temp.mk/x.mp4")
+        finally:
+            for p in reversed(patches):
+                p.__exit__(None, None, None)
+
+        storage.upload_file.assert_not_called()
+        # output_video_url 保持原值（temp_url）
+        assert job.output_video_url == "https://temp.mk/x.mp4"
+        # 内层 except 不会 commit
+        # 注：若内部发生 commit 说明测试失败
+        session.close.assert_called_once()
+
+    def test_empty_temp_url_skips_persist(self):
+        """temp_url 为空 → 直接返回，不下载不上传."""
+        from app.tasks.lipsync_tts import persist_output_video_task
+
+        job = self._make_persist_job(output_video_url="")
+        session, fake_client, storage, patches = self._persist_patches(job=job)
+        entered = [p.__enter__() for p in patches]
+        try:
+            persist_output_video_task("job-1", "user-1", "")
+        finally:
+            for p in reversed(patches):
+                p.__exit__(None, None, None)
+
+        fake_client.get.assert_not_called()
+        storage.upload_file.assert_not_called()
+        session.commit.assert_not_called()
+        session.close.assert_called_once()
+
+    def test_job_not_found_returns_early(self):
+        """DB 中找不到 job → 直接返回，不抛错."""
+        from app.tasks.lipsync_tts import persist_output_video_task
+
+        session, fake_client, storage, patches = self._persist_patches(job=None)
+        entered = [p.__enter__() for p in patches]
+        try:
+            persist_output_video_task("missing", "user-1", "https://temp.mk/x.mp4")
+        finally:
+            for p in reversed(patches):
+                p.__exit__(None, None, None)
+
+        fake_client.get.assert_not_called()
+        storage.upload_file.assert_not_called()
+        session.commit.assert_not_called()
+        session.close.assert_called_once()
+
+
+class TestLipsyncServiceRefreshCompletedAsyncPersist:
+    """refresh_job_status 在 completed 分支异步转存的单元测试（补 0% 覆盖的 316~335 行）."""
+
+    def test_refresh_completed_dispatches_persist_task(self):
+        """completed 分支：设置 temp_url → commit → dispatch persist_output_video_task.apply_async."""
+        from app.services.lipsync_service import LipsyncService
+
+        mock_job = MagicMock()
+        mock_job.id = "job-1"
+        mock_job.user_id = "user-1"
+        mock_job.mediakit_task_id = "mk-1"
+        mock_job.status = "submitted"
+        mock_job.output_video_url = ""
+        mock_job.output_duration = 0.0
+
+        mock_db = MagicMock()
+        mock_query = MagicMock()
+        mock_filter = MagicMock()
+        mock_filter.first.return_value = mock_job
+        mock_query.filter.return_value = mock_filter
+        mock_db.query.return_value = mock_query
+
+        mock_client = MagicMock()
+        mock_client.get_task_status.return_value = {
+            "status": "completed",
+            "result": {"video_url": "https://temp.mk/out.mp4", "duration": 25.5},
+        }
+
+        fake_persist_task = MagicMock()
+        svc = LipsyncService(mock_db, client=mock_client, cosyvoice_service=MagicMock())
+        with patch.dict("sys.modules", {}):
+            # 直接 patch 懒 import 路径
+            with patch("app.tasks.lipsync_tts.persist_output_video_task", fake_persist_task, create=False):
+                # 但懒 import 发生在函数内部 from app.tasks.lipsync_tts import persist_output_video_task
+                # 通过 patch sys.modules 的方式提供
+                import sys as _sys
+
+                fake_mod = MagicMock()
+                fake_mod.persist_output_video_task = fake_persist_task
+                _sys.modules["app.tasks.lipsync_tts"] = fake_mod
+                try:
+                    result = svc.refresh_job_status("job-1", "user-1")
+                finally:
+                    _sys.modules.pop("app.tasks.lipsync_tts", None)
+
+        assert result.status == "completed"
+        assert result.output_video_url == "https://temp.mk/out.mp4"
+        assert result.output_duration == 25.5
+        mock_db.commit.assert_called()
+        # 必须在 commit 之后 dispatch
+        fake_persist_task.apply_async.assert_called_once()
+        kwargs = fake_persist_task.apply_async.call_args.kwargs
+        assert kwargs["args"] == ("job-1", "user-1", "https://temp.mk/out.mp4")
+
+    def test_refresh_completed_dispatch_exception_does_not_break_return(self):
+        """apply_async 抛异常（如 Celery 不可用）→ 捕获 warning，仍返回 completed job."""
+        from app.services.lipsync_service import LipsyncService
+
+        mock_job = MagicMock()
+        mock_job.id = "job-2"
+        mock_job.user_id = "user-1"
+        mock_job.mediakit_task_id = "mk-2"
+        mock_job.status = "submitted"
+        mock_job.output_video_url = ""
+        mock_job.output_duration = 0.0
+
+        mock_db = MagicMock()
+        mock_query = MagicMock()
+        mock_filter = MagicMock()
+        mock_filter.first.return_value = mock_job
+        mock_query.filter.return_value = mock_filter
+        mock_db.query.return_value = mock_query
+
+        mock_client = MagicMock()
+        mock_client.get_task_status.return_value = {
+            "status": "completed",
+            "result": {"video_url": "https://temp.mk/out2.mp4", "duration": 10.0},
+        }
+
+        fake_persist_task = MagicMock()
+        fake_persist_task.apply_async.side_effect = ConnectionError("celery down")
+
+        svc = LipsyncService(mock_db, client=mock_client, cosyvoice_service=MagicMock())
+        import sys as _sys
+
+        fake_mod = MagicMock()
+        fake_mod.persist_output_video_task = fake_persist_task
+        _sys.modules["app.tasks.lipsync_tts"] = fake_mod
+        try:
+            result = svc.refresh_job_status("job-2", "user-1")
+        finally:
+            _sys.modules.pop("app.tasks.lipsync_tts", None)
+
+        # 即便 dispatch 失败，主流程不受影响：仍然返回 completed + temp_url
+        assert result.status == "completed"
+        assert result.output_video_url == "https://temp.mk/out2.mp4"
+        fake_persist_task.apply_async.assert_called_once()
@@ -0,0 +1,171 @@
+"""Tests for sentence timing functions in lipsync_tts."""
+
+import os
+import subprocess
+import tempfile
+import unittest
+from unittest.mock import MagicMock, patch
+
+from apps.api.app.tasks.lipsync_tts import (
+    _compute_sentence_timings,
+    _estimate_sentence_timings_by_chars,
+    _split_script_into_sentences,
+)
+
+
+class TestSplitScriptIntoSentences(unittest.TestCase):
+    """Tests for _split_script_into_sentences."""
+
+    def test_empty_string(self):
+        self.assertEqual(_split_script_into_sentences(""), [])
+
+    def test_none(self):
+        self.assertEqual(_split_script_into_sentences(None), [])
+
+    def test_whitespace_only(self):
+        self.assertEqual(_split_script_into_sentences("   \n  "), [])
+
+    def test_single_sentence(self):
+        self.assertEqual(_split_script_into_sentences("你好世界。"), ["你好世界"])
+
+    def test_multiple_sentences_chinese(self):
+        result = _split_script_into_sentences("第一句。第二句！第三句？")
+        self.assertEqual(result, ["第一句", "第二句", "第三句"])
+
+    def test_english_punctuation(self):
+        result = _split_script_into_sentences("Hello World! How are you?")
+        self.assertEqual(result, ["Hello World", "How are you"])
+
+    def test_semicolons(self):
+        result = _split_script_into_sentences("第一部分；第二部分;第三部分")
+        self.assertEqual(result, ["第一部分", "第二部分", "第三部分"])
+
+    def test_newlines(self):
+        result = _split_script_into_sentences("第一行\n第二行\n第三行")
+        self.assertEqual(result, ["第一行", "第二行", "第三行"])
+
+    def test_no_trailing_punctuation(self):
+        result = _split_script_into_sentences("没有标点的句子")
+        self.assertEqual(result, ["没有标点的句子"])
+
+
+class TestEstimateSentenceTimingsByChars(unittest.TestCase):
+    """Tests for _estimate_sentence_timings_by_chars."""
+
+    def test_empty_sentences(self):
+        self.assertEqual(_estimate_sentence_timings_by_chars([], 10.0), [])
+
+    def test_zero_duration(self):
+        self.assertEqual(_estimate_sentence_timings_by_chars(["hello"], 0), [])
+
+    def test_negative_duration(self):
+        self.assertEqual(_estimate_sentence_timings_by_chars(["hello"], -5.0), [])
+
+    def test_single_sentence(self):
+        result = _estimate_sentence_timings_by_chars(["hello"], 10.0)
+        self.assertEqual(len(result), 1)
+        self.assertAlmostEqual(result[0]["start_time"], 0.0)
+        self.assertAlmostEqual(result[0]["end_time"], 10.0)
+
+    def test_two_equal_sentences(self):
+        result = _estimate_sentence_timings_by_chars(["你好", "世界"], 10.0)
+        self.assertEqual(len(result), 2)
+        self.assertAlmostEqual(result[0]["start_time"], 0.0)
+        self.assertAlmostEqual(result[0]["end_time"], 5.0)
+        self.assertAlmostEqual(result[1]["start_time"], 5.0)
+        self.assertAlmostEqual(result[1]["end_time"], 10.0)
+
+    def test_unequal_char_distribution(self):
+        result = _estimate_sentence_timings_by_chars(["ABCD", "EF"], 9.0)
+        self.assertEqual(len(result), 2)
+        self.assertAlmostEqual(result[0]["start_time"], 0.0)
+        self.assertAlmostEqual(result[0]["end_time"], 6.0)  # 4/6 * 9 = 6
+        self.assertAlmostEqual(result[1]["start_time"], 6.0)
+        self.assertAlmostEqual(result[1]["end_time"], 9.0)
+
+    def test_timing_structure(self):
+        result = _estimate_sentence_timings_by_chars(["句子一", "句子二"], 6.0)
+        for item in result:
+            self.assertIn("index", item)
+            self.assertIn("text", item)
+            self.assertIn("start_time", item)
+            self.assertIn("end_time", item)
+
+
+class TestComputeSentenceTimings(unittest.TestCase):
+    """Tests for _compute_sentence_timings."""
+
+    def test_empty_script_returns_empty(self):
+        self.assertEqual(_compute_sentence_timings(b"fake_audio", "", 10.0), [])
+
+    def test_none_script_returns_empty(self):
+        self.assertEqual(_compute_sentence_timings(b"fake_audio", None, 10.0), [])
+
+    @patch("os.unlink")
+    @patch.object(tempfile, "NamedTemporaryFile")
+    @patch.object(subprocess, "run")
+    def test_silence_detection_insufficient_fallback(self, mock_run, mock_tmpfile, mock_unlink):
+        """When silence detection finds too few points, fallback to char estimation."""
+        mock_run.return_value = MagicMock(stderr="", returncode=0)
+        mock_tmp = MagicMock()
+        mock_tmp.name = "/tmp/fake.mp3"
+        mock_tmp.__enter__ = MagicMock(return_value=mock_tmp)
+        mock_tmp.__exit__ = MagicMock(return_value=False)
+        mock_tmpfile.return_value = mock_tmp
+
+        result = _compute_sentence_timings(b"fake_audio", "第一句。第二句。第三句。", 10.0)
+
+        # Should fallback to char estimation with 3 sentences
+        self.assertEqual(len(result), 3)
+        self.assertAlmostEqual(result[0]["start_time"], 0.0)
+
+    @patch("os.unlink")
+    @patch.object(tempfile, "NamedTemporaryFile")
+    @patch.object(subprocess, "run")
+    def test_silence_detection_with_enough_points(self, mock_run, mock_tmpfile, mock_unlink):
+        """When silence detection finds enough points, use them for boundaries."""
+        mock_run.return_value = MagicMock(
+            stderr="[silencedetect] silence_end: 3.5 | silence_duration: 0.4\n"
+            "[silencedetect] silence_end: 7.0 | silence_duration: 0.3\n",
+            returncode=0,
+        )
+        mock_tmp = MagicMock()
+        mock_tmp.name = "/tmp/fake.mp3"
+        mock_tmp.__enter__ = MagicMock(return_value=mock_tmp)
+        mock_tmp.__exit__ = MagicMock(return_value=False)
+        mock_tmpfile.return_value = mock_tmp
+
+        result = _compute_sentence_timings(b"fake_audio", "第一句。第二句。第三句。", 10.0)
+
+        self.assertEqual(len(result), 3)
+        self.assertAlmostEqual(result[0]["start_time"], 0.0)
+        self.assertAlmostEqual(result[0]["end_time"], 3.5)
+        self.assertAlmostEqual(result[1]["start_time"], 3.5)
+        self.assertAlmostEqual(result[1]["end_time"], 7.0)
+        self.assertAlmostEqual(result[2]["start_time"], 7.0)
+        self.assertAlmostEqual(result[2]["end_time"], 10.0)
+
+    @patch("os.unlink")
+    @patch.object(tempfile, "NamedTemporaryFile")
+    @patch.object(subprocess, "run")
+    def test_ffmpeg_exception_fallback(self, mock_run, mock_tmpfile, mock_unlink):
+        """When ffmpeg raises an exception, fallback to char estimation."""
+        mock_run.side_effect = Exception("ffmpeg not found")
+        mock_tmp = MagicMock()
+        mock_tmp.name = "/tmp/fake.mp3"
+        mock_tmp.__enter__ = MagicMock(return_value=mock_tmp)
+        mock_tmp.__exit__ = MagicMock(return_value=False)
+        mock_tmpfile.return_value = mock_tmp
+
+        result = _compute_sentence_timings(b"fake_audio", "句子一。句子二。", 6.0)
+
+        # Should fallback to char estimation
+        self.assertEqual(len(result), 2)
+        self.assertAlmostEqual(result[0]["start_time"], 0.0)
+        self.assertAlmostEqual(result[0]["end_time"], 3.0)
+        self.assertAlmostEqual(result[1]["start_time"], 3.0)
+        self.assertAlmostEqual(result[1]["end_time"], 6.0)
+
+
+if __name__ == "__main__":
+    unittest.main()
@@ -13,6 +13,7 @@

 from __future__ import annotations

+import os
 import unittest
 from dataclasses import FrozenInstanceError
 from unittest.mock import patch
@@ -29,10 +30,12 @@ from packages.domain.video_filter_builder import (
    ClipFilterChain,
    _escape_drawtext_text,
    _resolve_font_path,
+    build_broll_overlay_filter,
    build_clip_filter,
    build_concat_filter,
    build_filter_complex,
    build_title_drawtext_filter,
+    build_title_overlay_filter,
    build_xfade_filter,
    chain_filters,
    has_audio,
@@ -1039,6 +1042,29 @@ class TestDrawtextBoldFalse(unittest.TestCase):
        # 粗体应通过 borderw 实现
        self.assertIn("borderw=", result)

+    @patch("packages.domain.video_filter_builder._resolve_font_path")
+    def test_bold_default_uses_black_stroke_when_no_bold_font(self, mock_font):
+        """默认 bold=true 且无 Bold 字体文件时，使用黑色细描边（borderw=2 + 黑），
+        不得使用与文字同色的 borderw>=3（否则会造成竖屏小字号重影）。"""
+        mock_font.return_value = ""  # 无粗体字体
+        result = build_title_drawtext_filter({"text": "标题"})
+        self.assertIsNotNone(result)
+        self.assertIn("borderw=2", result)
+        # 黑描边：要么是 black 关键字，要么是 000000
+        self.assertTrue("bordercolor=black" in result or "bordercolor=000000" in result)
+        self.assertNotIn("borderw=3", result)
+
+    @patch("packages.domain.video_filter_builder._resolve_font_path")
+    def test_bold_with_user_stroke_preserves_user_color(self, mock_font):
+        """用户显式开启 stroke 时，stroke 颜色/宽度优先于默认粗体黑边。"""
+        mock_font.return_value = ""
+        result = build_title_drawtext_filter(
+            {"text": "标题", "bold": True, "stroke": {"width": 4, "color": "#ffffff"}}
+        )
+        self.assertIsNotNone(result)
+        self.assertIn("borderw=4", result)
+        self.assertIn("bordercolor=ffffff", result)  # 去掉 # 前缀
+

 class TestDrawtextPositionBranches(unittest.TestCase):
    """位置相关分支覆盖。"""
@@ -1065,12 +1091,23 @@ class TestDrawtextPositionBranches(unittest.TestCase):
        self.assertIn("y=h-text_h-50", result)

    @patch("packages.domain.video_filter_builder._resolve_font_path")
-    def test_position_custom_with_float_coords(self, mock_font):
+    def test_position_custom_with_percentage_coords(self, mock_font):
+        """自定义位置：百分比坐标转换为 drawtext 表达式."""
+        mock_font.return_value = ""
+        # pos_x=50, pos_y=30 → x=(w-text_w)*0.5000, y=(h-text_h)*0.3000
+        result = build_title_drawtext_filter({"text": "标题", "position": "custom", "pos_x": 50, "pos_y": 30})
+        self.assertIsNotNone(result)
+        self.assertIn("x=(w-text_w)*0.5000", result)
+        self.assertIn("y=(h-text_h)*0.3000", result)
+
+    @patch("packages.domain.video_filter_builder._resolve_font_path")
+    def test_position_custom_clamped_to_100(self, mock_font):
+        """自定义位置：超过100的坐标被截断到100%."""
        mock_font.return_value = ""
        result = build_title_drawtext_filter({"text": "标题", "position": "custom", "pos_x": 100.7, "pos_y": 200.3})
        self.assertIsNotNone(result)
-        self.assertIn("x=100", result)
-        self.assertIn("y=200", result)
+        self.assertIn("x=(w-text_w)*1.0000", result)
+        self.assertIn("y=(h-text_h)*1.0000", result)

    @patch("packages.domain.video_filter_builder._resolve_font_path")
    def test_position_custom_bool_coords_fallback(self, mock_font):
@@ -1127,5 +1164,97 @@ class TestDrawtextNotDictConfig(unittest.TestCase):
        self.assertIsNone(build_title_drawtext_filter([1, 2, 3]))


+class TestTitleOverlay(unittest.TestCase):
+    """build_title_overlay_filter 单元测试（WYSIWYG PNG 叠加路径）。"""
+
+    def test_overlay_filter_format(self):
+        """PNG 文件存在时返回正确的 overlay 滤镜字符串。"""
+        import tempfile
+
+        with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
+            tmp.write(b"\x89PNG\r\n\x1a\n")
+            tmp_path = tmp.name
+        try:
+            result = build_title_overlay_filter(
+                {"text": "标题"},
+                output_width=720,
+                output_height=1280,
+                title_png_path=tmp_path,
+                title_input_label="[2:v]",
+                base_label="[vout]",
+                output_label="vout_titled",
+            )
+            self.assertIsNotNone(result)
+            self.assertIn("[vout][2:v]overlay=0:0[vout_titled]", result)
+        finally:
+            os.unlink(tmp_path)
+
+    def test_overlay_default_labels(self):
+        """不传 label 参数时使用默认 [0:v] / [1:v] / vout_titled。"""
+        import tempfile
+
+        with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
+            tmp.write(b"\x89PNG\r\n\x1a\n")
+            tmp_path = tmp.name
+        try:
+            result = build_title_overlay_filter(
+                {"text": "标题"},
+                output_width=720,
+                output_height=1280,
+                title_png_path=tmp_path,
+            )
+            self.assertEqual(result, "[0:v][1:v]overlay=0:0[vout_titled]")
+        finally:
+            os.unlink(tmp_path)
+
+    def test_overlay_returns_none_when_png_missing(self):
+        """PNG 文件不存在时返回 None，供调用方降级到 drawtext。"""
+        result = build_title_overlay_filter(
+            {"text": "标题"},
+            output_width=720,
+            output_height=1280,
+            title_png_path="/nonexistent/path/title.png",
+        )
+        self.assertIsNone(result)
+
+    def test_overlay_returns_none_for_empty_config(self):
+        """title_config 为空/非 dict 时返回 None。"""
+        import tempfile
+
+        with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
+            tmp.write(b"\x89PNG\r\n\x1a\n")
+            tmp_path = tmp.name
+        try:
+            self.assertIsNone(
+                build_title_overlay_filter(
+                    None,
+                    output_width=720,
+                    output_height=1280,
+                    title_png_path=tmp_path,
+                )
+            )
+            self.assertIsNone(
+                build_title_overlay_filter(
+                    "not a dict",
+                    output_width=720,
+                    output_height=1280,
+                    title_png_path=tmp_path,
+                )
+            )
+        finally:
+            os.unlink(tmp_path)
+
+    def test_overlay_returns_none_for_empty_path(self):
+        """title_png_path 为空字符串时返回 None。"""
+        self.assertIsNone(
+            build_title_overlay_filter(
+                {"text": "标题"},
+                output_width=720,
+                output_height=1280,
+                title_png_path="",
+            )
+        )
+
+
 if __name__ == "__main__":
    unittest.main()