fix(viral-video): 素材库音频选择弹窗修复+按钮禁用态可见性加固

1. 修复「从素材库选择」配音弹窗列表只显示音符占位符不显示名称的问题： - 根因：.vv-thumb-ph（占位图标）在 voice 横向卡片中继承 width/height:100%，占满整行把 .vv-thumb-name 挤到视口外，用户只看到3个大号🎵图标看不到名称 - 修复：为 .vv-asset-voice .vv-thumb-ph 设置固定 36px 圆形+浅紫底+紫色音符（与头像风格一致） - .vv-asset-voice 下的 img/video 也限 36px 圆形，避免缩略图过大 - .vv-asset-voice .vv-thumb-name 改为 flex 布局+左对齐+透明底 - 音频项名称后显示时长徽章（如 15s），与其他模块展示一致 - 勾选标记 ✓ 从右上角移到垂直居中靠右（横向卡片更合理） 2. 空状态提示优化（voice kind）： - 原先只显示「该素材库暂无音频素材」一行 - 现在分两行：主提示「暂无配音素材」+ 副提示「请先在『配音/我的音色』中上传音频文件，或在素材库管理中添加」 - 其他 kind（image/video）保持原样 3. 「选择内置音色」Modal 绑定代码复核： - 按钮 onClick={() => setVoicePickerOpen(true)} ✅ - disabled={!canEditAssets} 在 STEP1 未上传时为 disabled（符合预期） - PresetVoicePickerModal 已在 JSX 末尾正确挂载，传 open/voices/selectedId/onClose/onConfirm ✅ - vv-col-disabled 的 opacity 已通过 .vv-col-disabled .vv-btn-primary { opacity:1 !important } 覆盖，按钮在禁用列中仍用 vv-btn-disabled-gray 灰色样式可见 4. STEP2/STEP3 disabled 灰色按钮可见性加固： - vv-btn-disabled-gray 已设置 opacity:1 + 灰色#d1d5db背景+灰字#6b7280，不会被父级 opacity:0.55 冲淡 - vv-col-disabled 下 .vv-btn-primary opacity:1 强制覆盖 - disabled 主按钮清晰可见为灰色块状，和紫色激活态形成明显对比 tsc/vite build 全绿。
2026-10-01 11:39:34 +08:00
41 changed files with 2334 additions and 5659 deletions
@@ -212,14 +212,9 @@ COSYVOICE_CLONE_MODEL=voice-enrollment

 DOUBAO_API_KEY=your-doubao-api-key
 DOUBAO_MODEL=doubao-seed-1-6-250615
-DOUBAO_FAST_MODEL=doubao-1-5-pro-32k-250115
 DOUBAO_BASE_URL=https://ark.cn-beijing.volces.com/api/v3
 DOUBAO_TIMEOUT=30
 DOUBAO_MAX_RETRIES=2
-# 视觉模型：pro 精度高，lite 速度快（viral-video 商品识别默认用 lite 提速）
-DOUBAO_VISION_MODEL=doubao-1-5-vision-pro-250328
-DOUBAO_VISION_LITE_MODEL=doubao-1-5-vision-lite-250315
-DOUBAO_VISION_USE_LITE=true

 # ==================== 积分/会员系统 (#1895) ====================
 # 积分系统总开关：默认 false（暂停积分系统）。
@@ -1,51 +0,0 @@
-"""viral video add copy_result + voice/video columns
-
-Revision ID: 088_viral_video_copy_result
-Revises: 087_viral_video_image_analysis
-Create Date: 2026-10-01
-
-v1.6 爆款视频字段补齐：
- copy_result JSON: 编导分镜脚本完整结构（overview/scene_and_lighting/shots/hard_constraints/negative_prompts/voiceover_script）
- voice_id/voice_source: TTS 音色参数
- video_ratio/video_model: Seedance 视频比例/模型
-注意：线上启动也有幂等 ADD COLUMN 补列逻辑 (_ensure_viral_video_columns)，本 migration 提供标准 Alembic 路径，
-两套机制互不冲突（IF NOT EXISTS 等价行为）。
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "088_viral_video_copy_result"
-down_revision = "087_viral_video_image_analysis"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # 幂等添加列（通过单独执行 + 异常忽略兼容已由 backfill 补上的环境）
-    cols = [
-        ("voice_id", "VARCHAR(200) NOT NULL DEFAULT ''"),
-        ("voice_source", "VARCHAR(20) NOT NULL DEFAULT ''"),
-        ("video_ratio", "VARCHAR(10) NOT NULL DEFAULT '9:16'"),
-        ("video_model", "VARCHAR(100) NOT NULL DEFAULT ''"),
-        ("copy_result", "JSON"),
-    ]
-    conn = op.get_bind()
-    for name, ddl in cols:
-        try:
-            conn.execute(sa.text(f"ALTER TABLE viral_video_jobs ADD COLUMN IF NOT EXISTS {name} {ddl}"))
-        except Exception:
-            # 不支持 IF NOT EXISTS 的库（如老版本 SQLite）直接尝试 ADD COLUMN，失败则忽略
-            try:
-                conn.execute(sa.text(f"ALTER TABLE viral_video_jobs ADD COLUMN {name} {ddl}"))
-            except Exception:
-                pass
-
-
-def downgrade() -> None:
-    for name in ("copy_result", "video_model", "video_ratio", "voice_source", "voice_id"):
-        try:
-            op.drop_column("viral_video_jobs", name)
-        except Exception:
-            pass
@@ -1,62 +0,0 @@
-"""viral video add storyboard + generated_copy_text (complement 088)
-
-Revision ID: 089_viral_video_cols
-Revises: 088_viral_video_copy_result
-Create Date: 2026-10-01
-
-#2129 兜底迁移：补齐 _VIRAL_VIDEO_BACKFILL_COLS 中所有列，覆盖
-# watchtower 自动部署未跑历史 migration、且 AUTO_CREATE_SCHEMA=false 时
-# _ensure_viral_video_columns 未执行的场景。
-# 幂等 ADD COLUMN IF NOT EXISTS，已存在则跳过。
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "089_viral_video_cols"
-down_revision = "088_viral_video_copy_result"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # 扩展 alembic_version.version_num 字段长度（原来 VARCHAR(32) 装不下长 revision id）
-    conn = op.get_bind()
-    try:
-        conn.execute(sa.text("ALTER TABLE alembic_version ALTER COLUMN version_num TYPE VARCHAR(256)"))
-    except Exception:
-        pass
-    cols = [
-        ("storyboard", "JSON"),
-        ("generated_copy_text", "TEXT NOT NULL DEFAULT ''"),
-        ("voice_id", "VARCHAR(200) NOT NULL DEFAULT ''"),
-        ("voice_source", "VARCHAR(20) NOT NULL DEFAULT ''"),
-        ("video_ratio", "VARCHAR(10) NOT NULL DEFAULT '9:16'"),
-        ("video_model", "VARCHAR(100) NOT NULL DEFAULT ''"),
-        ("copy_result", "JSON"),
-    ]
-    for name, ddl in cols:
-        try:
-            conn.execute(sa.text(f"ALTER TABLE viral_video_jobs ADD COLUMN IF NOT EXISTS {name} {ddl}"))
-        except Exception:
-            try:
-                conn.execute(sa.text(f"ALTER TABLE viral_video_jobs ADD COLUMN {name} {ddl}"))
-            except Exception:
-                pass
-
-
-def downgrade() -> None:
-    for name in (
-        "copy_result",
-        "video_model",
-        "video_ratio",
-        "voice_source",
-        "voice_id",
-        "generated_copy_text",
-        "storyboard",
-    ):
-        try:
-            op.drop_column("viral_video_jobs", name)
-        except Exception:
-            pass
@@ -1,35 +0,0 @@
-"""viral video add phase_message column (#2134)
-
-Revision ID: 090_viral_video_phase_msg
-Revises: 089_viral_video_cols
-Create Date: 2026-10-02
-
-#2134 阶段细粒度提示：viral_video 表新增 phase_message 列（中文阶段提示文案）。
-current_stage 列已在之前版本存在，本迁移只补 phase_message。
-幂等 ADD COLUMN IF NOT EXISTS。
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "090_viral_video_phase_msg"
-down_revision = "089_viral_video_cols"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # SQLite/PostgreSQL 兼容的幂等添加列
-    conn = op.get_bind()
-    inspector = sa.inspect(conn)
-    cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
-    if "phase_message" not in cols:
-        op.add_column(
-            "viral_video_jobs",
-            sa.Column("phase_message", sa.String(length=500), nullable=False, server_default=""),
-        )
-
-
-def downgrade() -> None:
-    op.drop_column("viral_video_jobs", "phase_message")
@@ -1,49 +0,0 @@
-"""viral video add current_stage column (#2137 follow-up)
-
-Revision ID: 091_viral_video_stage
-Revises: 090_viral_video_phase_msg
-Create Date: 2026-10-02
-
-#2137 follow-up fix: 090 migration missed current_stage column on viral_video_jobs,
-causing UndefinedColumn errors and 500s on all authenticated viral-video endpoints.
-Idempotently add current_stage and double-check phase_message.
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "091_viral_video_stage"
-down_revision = "090_viral_video_phase_msg"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    conn = op.get_bind()
-    inspector = sa.inspect(conn)
-    cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
-    if "current_stage" not in cols:
-        op.add_column(
-            "viral_video_jobs",
-            sa.Column(
-                "current_stage",
-                sa.String(length=200),
-                nullable=False,
-                server_default="",
-            ),
-        )
-    if "phase_message" not in cols:
-        op.add_column(
-            "viral_video_jobs",
-            sa.Column(
-                "phase_message",
-                sa.String(length=500),
-                nullable=False,
-                server_default="",
-            ),
-        )
-
-
-def downgrade() -> None:
-    op.drop_column("viral_video_jobs", "current_stage")
@@ -1,42 +0,0 @@
-"""viral_video_jobs 增加 heartbeat_at 列（worker 心跳，用于僵尸任务超时回收）
-
-Revision ID: 092_viral_video_heartbeat
-Revises: 091_viral_video_stage
-Create Date: 2026-10-02
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "092_viral_video_heartbeat"
-down_revision = "091_viral_video_stage"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    conn = op.get_bind()
-    inspector = sa.inspect(conn)
-    cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
-    if "heartbeat_at" not in cols:
-        op.add_column("viral_video_jobs", sa.Column("heartbeat_at", sa.DateTime(), nullable=True))
-        op.execute(
-            "UPDATE viral_video_jobs SET heartbeat_at = updated_at " "WHERE status = 'running' AND heartbeat_at IS NULL"
-        )
-        try:
-            op.create_index("ix_viral_video_jobs_heartbeat_at", "viral_video_jobs", ["heartbeat_at"])
-        except Exception:
-            pass
-
-
-def downgrade() -> None:
-    conn = op.get_bind()
-    inspector = sa.inspect(conn)
-    cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
-    if "heartbeat_at" in cols:
-        try:
-            op.drop_index("ix_viral_video_jobs_heartbeat_at", table_name="viral_video_jobs")
-        except Exception:
-            pass
-        op.drop_column("viral_video_jobs", "heartbeat_at")
@@ -9,11 +9,6 @@ from fastapi.responses import JSONResponse
 router = APIRouter(tags=["Health"])


-
-def _pg_url(url: str) -> str:
-    """Convert SQLAlchemy URL (postgresql+psycopg://...) to libpq connection string."""
-    return url.replace("postgresql+psycopg://", "postgresql://", 1).replace("postgresql+psycopg2://", "postgresql://", 1)
-
@router.get("/health", status_code=status.HTTP_200_OK)
 async def health_check():
    return {
@@ -54,7 +49,7 @@ async def _check_database() -> dict:
            "message": "Using in-memory database",
        }
    try:
-        conn = psycopg.connect(_pg_url(settings.DATABASE_URL), connect_timeout=3)
+        conn = psycopg.connect(settings.DATABASE_URL, connect_timeout=3)
        with conn.cursor() as cur:
            cur.execute("SELECT 1")
            cur.fetchone()
@@ -129,7 +124,7 @@ async def _check_migrations() -> dict:
            "message": "Using in-memory database, no migrations needed",
        }
    try:
-        conn = psycopg.connect(_pg_url(settings.DATABASE_URL), connect_timeout=3)
+        conn = psycopg.connect(settings.DATABASE_URL, connect_timeout=3)
        with conn.cursor() as cur:
            cur.execute("""
                SELECT COUNT(*) FROM information_schema.tables
@@ -142,5 +137,3 @@ async def _check_migrations() -> dict:
        return {"status": "unhealthy", "message": f"Missing tables, found {count}/5"}
    except Exception as error:
        return {"status": "unhealthy", "message": f"Migration check failed: {error}"}
-
-
@@ -1,21 +1,14 @@
 """爆款视频 API 路由。

-v1.6 三步分步流水线端点（单次 Seedance 出片版）：
-  POST   /api/v1/viral-video/analyze-images          阶段1：创建任务 + 仅做图片/视频分析，暂停在 image_analyzed
-  POST   /api/v1/viral-video/{job_id}/generate-copy  阶段2：用户填完参数后跑意图+文案+分镜+审核，暂停在 copy_generated
-  POST   /api/v1/viral-video/{job_id}/confirm-copy   阶段3：用户确认/编辑文案后跑渲染，直到完成
-
-旧端点（兼容保留，旧前端/一键生成模式）：
-  POST   /api/v1/viral-video/generate                一键入队，前半段跑到 wait_user_confirm
-  POST   /api/v1/viral-video/{job_id}/confirm-intent 旧的意图确认后继续渲染
-
-通用：
-  GET    /api/v1/viral-video/{job_id}                查询任务状态（含 image_analysis/copy_result 编导脚本）
-  GET    /api/v1/viral-video/history                 历史记录
-  POST   /api/v1/viral-video/{job_id}/retry          重试失败任务
-  POST   /api/v1/viral-video/{job_id}/analyze-style  触发风格分析
-  GET    /api/v1/viral-video/style-templates         风格模板列表
-  WS     /api/v1/viral-video/ws/{job_id}?token=      WebSocket 进度推送
+端点：
+  POST   /api/v1/viral-video/generate          创建爆款视频任务
+  GET    /api/v1/viral-video/{job_id}          查询任务状态
+  GET    /api/v1/viral-video/history            历史记录
+  POST   /api/v1/viral-video/{job_id}/retry     重试失败任务
+  POST   /api/v1/viral-video/{job_id}/confirm-intent  确认意图文案
+  POST   /api/v1/viral-video/{job_id}/analyze-style   触发风格分析
+  GET    /api/v1/viral-video/style-templates    获取风格模板列表
+  WS     /api/v1/viral-video/ws/{job_id}?token=  WebSocket 进度推送（订阅 Redis pub/sub）
 """

 from __future__ import annotations
@@ -26,13 +19,10 @@ from app.auth import AuthenticatedUser, get_current_user
 from app.core.celery_app import celery_app
 from app.dependencies import get_db_session
 from app.schemas.viral_video import (
-    AnalyzeImagesRequest,
    AnalyzeStyleRequest,
    AnalyzeStyleResponse,
-    ConfirmCopyRequest,
    ConfirmIntentRequest,
    CreateViralVideoRequest,
-    GenerateCopyRequest,
    StyleTemplateListResponse,
    StyleTemplateResponse,
    ViralVideoHistoryResponse,
@@ -55,59 +45,6 @@ router = APIRouter()
 # ── Helpers ──────────────────────────────────────────────────────────────


-def _build_copy_result(job) -> dict | None:
-    """v1.6: 返回编导分镜脚本 CopyResult 结构（给前端/Seedance 使用）。
-
-    - 若 job.copy_result 已持久化（v1.6 worker 生成），直接返回（补 final_copy 兜底）。
-    - 否则从老字段（generated_copy_text=口播, storyboard=分镜列表, intent_result）拼装兼容结构。
-    """
-    cr = getattr(job, "copy_result", None)
-    if isinstance(cr, dict) and cr:
-        out = dict(cr)
-        # 向后兼容字段
-        voiceover = out.get("voiceover_script", "") or ""
-        out.setdefault("final_copy", voiceover)
-        out.setdefault("suggested_copy", voiceover)
-        out.setdefault("title", "")
-        return out
-    # 兼容 v1.5 老数据：storyboard 是老格式 [{order,type,description,text,duration,...}]
-    copy_text = getattr(job, "generated_copy_text", "") or ""
-    sb = getattr(job, "storyboard", None) or []
-    intent = getattr(job, "intent_result", None) or {}
-    if not copy_text and not sb:
-        return None
-    title = ""
-    if isinstance(intent, dict):
-        title = intent.get("suggested_title") or intent.get("intent", "") or ""
-    shots = []
-    for seg in sb:
-        if isinstance(seg, dict):
-            shots.append(
-                {
-                    "time_range": "",
-                    "shot_type_angle_movement": seg.get("ken_burns", ""),
-                    "scene_and_dialogue": (seg.get("text") or "")
-                    + (" " + seg.get("description", "") if seg.get("description") else ""),
-                    "action_details": "",
-                    "audio_bgm": "",
-                    "transition": seg.get("transition", "硬切"),
-                    "reference_image_index": None,
-                }
-            )
-    ratio = getattr(job, "video_ratio", None) or "9:16"
-    return {
-        "overview": {"theme": title, "total_duration": getattr(job, "duration", 15), "aspect_ratio": ratio},
-        "scene_and_lighting": "",
-        "shots": shots,
-        "hard_constraints": ["无字幕", "无水印", "人物一致性"],
-        "negative_prompts": ["字幕", "水印", "错误文字", "五官崩坏"],
-        "voiceover_script": copy_text,
-        "final_copy": copy_text,
-        "suggested_copy": copy_text,
-        "title": title,
-    }
-
-
 def _to_response(job) -> ViralVideoJobResponse:
    return ViralVideoJobResponse(
        id=job.id,
@@ -119,7 +56,7 @@ def _to_response(job) -> ViralVideoJobResponse:
        viral_structure=job.viral_structure,
        marketing_purpose=job.marketing_purpose,
        bgm_preference=job.bgm_preference,
-        duration=job.duration or 15,
+        duration=job.duration,
        user_copy_text=job.user_copy_text,
        fusion_level=job.fusion_level,
        reference_audio_path=job.reference_audio_path,
@@ -128,16 +65,6 @@ def _to_response(job) -> ViralVideoJobResponse:
        style_guide=job.style_guide,
        style_template_id=job.style_template_id,
        status=job.status,
-        current_stage=getattr(job, "current_stage", "") or "",
-        phase_message=getattr(job, "phase_message", "") or "",
-        image_analysis=getattr(job, "image_analysis", None),
-        storyboard=getattr(job, "storyboard", None),
-        generated_copy_text=getattr(job, "generated_copy_text", "") or "",
-        copy_result=_build_copy_result(job),
-        voice_id=getattr(job, "voice_id", "") or "",
-        voice_source=getattr(job, "voice_source", "") or "",
-        video_ratio=getattr(job, "video_ratio", "9:16") or "9:16",
-        video_model=getattr(job, "video_model", "") or "",
        intent_result=job.intent_result,
        result_video_url=job.result_video_url,
        credits_cost=job.credits_cost,
@@ -182,18 +109,13 @@ def create_viral_video(
        viral_structure=request.viral_structure,
        marketing_purpose=request.marketing_purpose,
        bgm_preference=request.bgm_preference,
-        duration=request.duration or 15,
+        duration=request.duration,
        user_copy_text=request.user_copy_text,
        fusion_level=request.fusion_level,
        reference_audio_path=request.reference_audio_path,
        reference_video_url=request.reference_video_url,
        style_strength=request.style_strength,
        style_template_id=request.style_template_id,
-        voice_id=getattr(request, "voice_id", "") or "",
-        voice_source=getattr(request, "voice_source", "") or "",
-        video_ratio=getattr(request, "video_ratio", "9:16") or "9:16",
-        video_model=getattr(request, "video_model", "") or "",
-        copy_result=None,
    )

    # 持久化
@@ -211,139 +133,6 @@ def create_viral_video(
    return _to_response(job)


-@router.post("/analyze-images", response_model=ViralVideoJobResponse)
-def analyze_images(
-    request: AnalyzeImagesRequest,
-    authenticated_user: AuthenticatedUser = Depends(get_current_user),
-    session: Session = Depends(get_db_session),
-) -> ViralVideoJobResponse:
-    """v1.5 阶段1：创建任务并仅做图片/视频 VLM 分析，跑完后状态=image_analyzed。
-
-    前端拿到 image_analysis（商品名/品牌/特征/颜色/材质等结构化结果）展示给用户；
-    用户填完营销参数后再调 /{id}/generate-copy 进入阶段2。
-    """
-    from packages.domain.viral_video import ViralVideoJob
-
-    repo = _get_job_repo(session)
-    job = ViralVideoJob(
-        user_id=authenticated_user.user.id,
-        images=list(request.images),
-        reference_video_url=request.reference_video_url or "",
-        style_template_id=request.style_template_id or "",
-        style_strength=request.style_strength or "medium",
-        voice_id=request.voice_id or "",
-        voice_source=request.voice_source or "",
-        video_ratio=request.video_ratio or "9:16",
-        video_model=request.video_model or "",
-        duration=request.duration or 15,
-    )
-    repo.save(job)
-
-    try:
-        celery_app.send_task("worker.run_viral_video_analyze", args=[job.id])
-        logger.info("[爆款视频][阶段1] analyze-images 入队: job_id=%s", job.id)
-    except Exception as e:
-        logger.error("[爆款视频][阶段1] analyze-images 入队失败: %s", e, exc_info=True)
-        job.mark_failed(f"任务入队失败: {e}")
-        repo.update(job)
-
-    return _to_response(job)
-
-
-@router.post("/{job_id}/generate-copy", response_model=ViralVideoJobResponse)
-def generate_copy(
-    job_id: str,
-    request: GenerateCopyRequest,
-    authenticated_user: AuthenticatedUser = Depends(get_current_user),
-    session: Session = Depends(get_db_session),
-) -> ViralVideoJobResponse:
-    """v1.6 阶段2：用户填完营销参数后，跑 意图解析 → 编导分镜脚本生成 → 合规审核。
-
-    跑完后状态=copy_generated，响应 copy_result（含 overview/scene_and_lighting/shots/
-    hard_constraints/negative_prompts/voiceover_script），前端展示脚本与口播供用户编辑；
-    确认/编辑后调 /{id}/confirm-copy 进入阶段3（TTS + 单次 Seedance 出片）。
-    """
-    repo = _get_job_repo(session)
-    job = repo.get(job_id)
-    if job is None:
-        raise HTTPException(status_code=404, detail="任务不存在")
-    if job.user_id != authenticated_user.user.id:
-        raise HTTPException(status_code=403, detail="无权操作此任务")
-    if job.status not in (ViralVideoStatus.IMAGE_ANALYZED, ViralVideoStatus.PENDING, ViralVideoStatus.FAILED):
-        raise HTTPException(status_code=409, detail=f"任务当前状态 {job.status} 不能生成文案")
-
-    # 允许失败任务重试：重置
-    if job.status == ViralVideoStatus.FAILED:
-        job.retry_count += 1
-        job.error_msg = ""
-
-    # 把用户填的营销参数写到 job 上
-    job.industry = request.industry or job.industry
-    job.target_customer = request.target_customer or job.target_customer
-    job.persona_id = request.persona_id or job.persona_id
-    job.viral_structure = request.viral_structure or job.viral_structure
-    job.marketing_purpose = request.marketing_purpose or job.marketing_purpose
-    job.bgm_preference = request.bgm_preference or job.bgm_preference
-    if request.duration:
-        job.duration = max(5, min(30, int(request.duration)))
-    job.user_copy_text = request.user_copy_text if request.user_copy_text else job.user_copy_text
-    job.fusion_level = request.fusion_level or job.fusion_level
-    job.reference_audio_path = request.reference_audio_path or job.reference_audio_path
-    job.reference_video_url = request.reference_video_url or job.reference_video_url
-    job.style_strength = request.style_strength or job.style_strength
-    job.style_template_id = request.style_template_id or job.style_template_id
-    if request.style_guide is not None:
-        job.style_guide = request.style_guide
-    job.voice_id = request.voice_id or job.voice_id
-    job.voice_source = request.voice_source or job.voice_source
-    job.video_ratio = request.video_ratio or job.video_ratio or "9:16"
-    job.video_model = request.video_model or job.video_model or ""
-
-    job.resume_from_image_analyzed()
-    repo.update(job)
-
-    try:
-        celery_app.send_task("worker.run_viral_video_generate_copy", args=[job.id])
-        logger.info("[爆款视频][阶段2] generate-copy 入队: job_id=%s", job.id)
-    except Exception as e:
-        logger.error("[爆款视频][阶段2] generate-copy 入队失败: %s", e, exc_info=True)
-        job.mark_failed(f"任务入队失败: {e}")
-        repo.update(job)
-
-    return _to_response(job)
-
-
-@router.post("/{job_id}/confirm-copy", response_model=ViralVideoJobResponse)
-def confirm_copy(
-    job_id: str,
-    request: ConfirmCopyRequest,
-    authenticated_user: AuthenticatedUser = Depends(get_current_user),
-    session: Session = Depends(get_db_session),
-) -> ViralVideoJobResponse:
-    """v1.6 阶段3：用户确认/编辑口播后开始 TTS + 单次 Seedance 生成 + 上传。"""
-    repo = _get_job_repo(session)
-    job = repo.get(job_id)
-    if job is None:
-        raise HTTPException(status_code=404, detail="任务不存在")
-    if job.user_id != authenticated_user.user.id:
-        raise HTTPException(status_code=403, detail="无权操作此任务")
-    if job.status != ViralVideoStatus.COPY_GENERATED:
-        raise HTTPException(status_code=409, detail=f"任务当前状态 {job.status} 不能确认文案（需 copy_generated）")
-
-    job.resume_from_copy_generated(edited_copy=request.edited_copy or None)
-    repo.update(job)
-
-    try:
-        celery_app.send_task("worker.run_viral_video_render", args=[job.id])
-        logger.info("[爆款视频][阶段3] confirm-copy 入队: job_id=%s", job.id)
-    except Exception as e:
-        logger.error("[爆款视频][阶段3] confirm-copy 入队失败: %s", e, exc_info=True)
-        job.mark_failed(f"任务入队失败: {e}")
-        repo.update(job)
-
-    return _to_response(job)
-
-
@router.get("/history", response_model=ViralVideoHistoryResponse)
 def list_viral_video_history(
    limit: int = 50,
@@ -400,42 +189,28 @@ def retry_viral_video_job(
    authenticated_user: AuthenticatedUser = Depends(get_current_user),
    session: Session = Depends(get_db_session),
 ) -> ViralVideoJobResponse:
-    """重试失败的爆款视频任务（也支持对僵尸/超时 running 任务强制重置后重试）。"""
-    from datetime import datetime, timezone
-
+    """重试失败的爆款视频任务。"""
    repo = _get_job_repo(session)
    job = repo.get(job_id)
    if job is None:
        raise HTTPException(status_code=404, detail="任务不存在")
    if job.user_id != authenticated_user.user.id:
        raise HTTPException(status_code=403, detail="无权操作此任务")
-
-    # 判定是否为僵尸 running 任务：running 超过 10 分钟且心跳停止超过 2 分钟
-    now = datetime.now(timezone.utc)
-    is_stale_running = False
-    if job.status == ViralVideoStatus.RUNNING and job.started_at is not None:
-        hb = getattr(job, "heartbeat_at", None) or job.updated_at
-        if (now - job.started_at).total_seconds() > 10 * 60 and hb is not None and (now - hb).total_seconds() > 2 * 60:
-            is_stale_running = True
-
-    if job.status != ViralVideoStatus.FAILED and not is_stale_running:
-        raise HTTPException(status_code=409, detail="只有失败或超时的任务可以重试")
+    if job.status != ViralVideoStatus.FAILED:
+        raise HTTPException(status_code=409, detail="只有失败的任务可以重试")

    # 重置状态
    job.retry_count += 1
    job.status = ViralVideoStatus.PENDING
-    job.error_msg = "" if not is_stale_running else "任务执行超时，已重置重试"
+    job.error_msg = ""
    job.started_at = None
    job.completed_at = None
-    job.current_stage = ""
-    job.phase_message = ""
-    job.heartbeat_at = None
    repo.update(job)

    # 重新入队
    try:
        celery_app.send_task("worker.run_viral_video_pipeline", args=[job.id])
-        logger.info("[爆款视频] 重试入队: job_id=%s retry_count=%d stale=%s", job.id, job.retry_count, is_stale_running)
+        logger.info("[爆款视频] 重试入队: job_id=%s retry_count=%d", job.id, job.retry_count)
    except Exception as e:
        logger.error("[爆款视频] 重试入队失败: %s", e, exc_info=True)
        job.mark_failed(f"重试入队失败: {e}")
@@ -730,8 +505,6 @@ def _job_status(job) -> str:
 _STATUS_STAGE = {
    "pending": "",
    "running": "",
-    "image_analyzed": "image_analysis",
-    "copy_generated": "review",
    "wait_user_confirm": "intent_parsing",
    "completed": "uploading",
    "failed": "",
@@ -741,8 +514,6 @@ _STATUS_STAGE = {
 _STATUS_PROGRESS = {
    "pending": 0.0,
    "running": 5.0,
-    "image_analyzed": 15.0,
-    "copy_generated": 70.0,
    "wait_user_confirm": 35.0,
    "completed": 100.0,
    "failed": 0.0,
@@ -752,8 +523,6 @@ _STATUS_PROGRESS = {
 _STATUS_MESSAGE = {
    "pending": "任务已创建，等待执行",
    "running": "任务执行中",
-    "image_analyzed": "图片分析完成，等待填写营销参数",
-    "copy_generated": "文案与分镜已生成，等待确认文案",
    "wait_user_confirm": "等待用户确认意图文案",
    "completed": "视频生成完成",
    "failed": "任务失败",
@@ -1,4 +1,4 @@
-"""爆款视频 API schemas (v1.6 单次 Seedance 出片版)。"""
+"""爆款视频 API schemas。"""

 from __future__ import annotations

@@ -6,7 +6,7 @@ from datetime import datetime

 from pydantic import BaseModel, Field, field_validator

-# -- 枚举常量 --
+# ── 枚举常量 ─────────────────────────────────────────────────────────────

 VALID_FUSION_LEVELS = ("ai_full", "full_ai", "ai_polish", "user_primary")
 VALID_STYLE_STRENGTHS = ("light", "medium", "strict")
@@ -14,174 +14,76 @@ VALID_STAGES = (
    "image_analysis",
    "video_analysis",
    "intent_parsing",
-    "script_generation",
+    "copy_fusion",
+    "storyboard",
    "review",
    "tts",
+    "bgm_select",
    "rendering",
+    "musetalk",
    "uploading",
 )
-VALID_VIDEO_RATIOS = ("9:16", "16:9", "1:1", "4:3", "3:4", "21:9")
-VALID_DURATIONS = (5, 10, 15, 20, 25, 30)


-# -- 编导脚本结构（v1.6） --
-
-
-class ShotScript(BaseModel):
-    """逐镜头分镜。"""
-
-    time_range: str = Field(default="", description="时间区间，如 0-3秒")
-    shot_type_angle_movement: str = Field(default="", description="景别/角度/运镜，如『近景俯拍45度，缓慢推镜』")
-    scene_and_dialogue: str = Field(default="", description="场景描述+口播台词")
-    action_details: str = Field(default="", description="人物动作、表情、物品操作细节")
-    audio_bgm: str = Field(default="", description="环境音+BGM提示")
-    transition: str = Field(default="硬切", description="转场方式：硬切/淡入淡出/叠化")
-    reference_image_index: int | None = Field(
-        default=None, description="参考图片索引（0-based，对应上传的第几张产品图）"
-    )
-
-
-class CopyResultOverview(BaseModel):
-    theme: str = ""
-    total_duration: int = 15
-    aspect_ratio: str = "9:16"
-
-
-class CopyResult(BaseModel):
-    """v1.6 编导分镜脚本结构（给前端 + Seedance 用）。"""
-
-    overview: CopyResultOverview = Field(default_factory=CopyResultOverview)
-    scene_and_lighting: str = ""
-    shots: list[ShotScript] = Field(default_factory=list)
-    hard_constraints: list[str] = Field(default_factory=list)
-    negative_prompts: list[str] = Field(default_factory=list)
-    voiceover_script: str = Field(
-        default="", description="纯口播对白，从各镜 scene_and_dialogue 的对白部分拼接，供 TTS 使用"
-    )
-    # 向后兼容：final_copy = voiceover_script
-    final_copy: str = ""
-    suggested_copy: str = ""
-    title: str = ""
-
-
-# -- Request Schemas --
+# ── Request Schemas ────────────────────────────────────────────────────────


 class CreateViralVideoRequest(BaseModel):
-    """旧接口：一键创建（保留兼容）。"""
+    """创建爆款视频任务请求。"""

-    images: list[str] = Field(..., min_length=1, max_length=20)
-    industry: str = ""
-    target_customer: str = ""
-    persona_id: str = ""
-    viral_structure: str = ""
-    marketing_purpose: str = ""
-    bgm_preference: str = ""
-    duration: int = Field(default=15, ge=5, le=30, description="视频时长（秒），5-30")
-    user_copy_text: str = ""
-    fusion_level: str = "ai_polish"
-    reference_audio_path: str = ""
-    reference_video_url: str = ""
-    style_strength: str = "medium"
-    style_template_id: str = ""
-    voice_id: str = ""
-    voice_source: str = ""
-    video_ratio: str = "9:16"
-    video_model: str = ""
+    images: list[str] = Field(..., min_length=1, max_length=20, description="产品图片 URL 列表")
+    industry: str = Field(default="", description="行业")
+    target_customer: str = Field(default="", description="目标客户描述")
+    persona_id: str = Field(default="", description="人设 ID")
+    viral_structure: str = Field(default="", description="爆款结构类型")
+    marketing_purpose: str = Field(default="", description="营销目的")
+    bgm_preference: str = Field(default="", description="BGM 偏好")
+    duration: int = Field(default=30, ge=5, le=180, description="视频时长（秒）")
+    user_copy_text: str = Field(default="", description="用户原始文案（我说你写）")
+    fusion_level: str = Field(default="ai_polish", description="文案融合级别: ai_full/ai_polish/user_primary")
+    reference_audio_path: str = Field(default="", description="参考音频路径")
+    # v1.3 新增
+    reference_video_url: str = Field(default="", description="参考爆款视频 URL")
+    style_strength: str = Field(default="medium", description="风格强度: light/medium/strict")
+    style_template_id: str = Field(default="", description="风格模板 ID")

    @field_validator("fusion_level")
    @classmethod
-    def _v_fl(cls, v: str) -> str:
+    def _validate_fusion_level(cls, v: str) -> str:
+        # 兼容前端历史写法 full_ai（等价 ai_full）
        if v == "full_ai":
            return "ai_full"
        if v not in VALID_FUSION_LEVELS:
-            raise ValueError(f"fusion_level must be one of {VALID_FUSION_LEVELS}")
+            raise ValueError(f"fusion_level 必须是 {VALID_FUSION_LEVELS} 之一")
        return v

    @field_validator("style_strength")
    @classmethod
-    def _v_ss(cls, v: str) -> str:
+    def _validate_style_strength(cls, v: str) -> str:
        if v not in VALID_STYLE_STRENGTHS:
-            raise ValueError(f"style_strength must be one of {VALID_STYLE_STRENGTHS}")
+            raise ValueError(f"style_strength 必须是 {VALID_STYLE_STRENGTHS} 之一")
        return v


-class AnalyzeImagesRequest(BaseModel):
-    """v1.5+ 阶段1：创建任务 + 图片/视频分析。"""
-
-    images: list[str] = Field(..., min_length=1, max_length=30)
-    reference_video_url: str = ""
-    style_template_id: str = ""
-    style_strength: str = "medium"
-    voice_id: str = ""
-    voice_source: str = ""
-    video_ratio: str = "9:16"
-    video_model: str = ""
-    duration: int = Field(default=15, ge=5, le=30)
-
-
-class GenerateCopyRequest(BaseModel):
-    """v1.5+ 阶段2：填完营销参数，生成编导脚本。"""
-
-    industry: str = ""
-    target_customer: str = ""
-    persona_id: str = ""
-    viral_structure: str = ""
-    marketing_purpose: str = ""
-    bgm_preference: str = ""
-    duration: int = Field(default=15, ge=5, le=30)
-    user_copy_text: str = ""
-    fusion_level: str = "ai_polish"
-    reference_audio_path: str = ""
-    reference_video_url: str = ""
-    style_strength: str = "medium"
-    style_template_id: str = ""
-    style_guide: dict | None = None
-    voice_id: str = ""
-    voice_source: str = ""
-    video_ratio: str = "9:16"
-    video_model: str = ""
-
-    @field_validator("fusion_level")
-    @classmethod
-    def _v_fl(cls, v: str) -> str:
-        if v == "full_ai":
-            return "ai_full"
-        if v not in VALID_FUSION_LEVELS:
-            raise ValueError(f"fusion_level must be one of {VALID_FUSION_LEVELS}")
-        return v
-
-    @field_validator("style_strength")
-    @classmethod
-    def _v_ss(cls, v: str) -> str:
-        if v not in VALID_STYLE_STRENGTHS:
-            raise ValueError(f"style_strength must be one of {VALID_STYLE_STRENGTHS}")
-        return v
-
-
-class ConfirmCopyRequest(BaseModel):
-    """v1.5+ 阶段3：用户确认/编辑口播后开始渲染（TTS+单次Seedance）。"""
-
-    edited_copy: str = Field(default="", description="用户编辑后的口播文案；为空则用 AI 生成的 voiceover_script")
-
-
 class ConfirmIntentRequest(BaseModel):
-    """旧 confirm-intent（兼容）。"""
+    """确认意图请求（confirm-intent）。"""

-    confirmed_copy: str = ""
-    adjustments: str = ""
+    confirmed_copy: str = Field(default="", description="用户确认/修改后的文案，为空表示使用 AI 生成的文案")
+    adjustments: str = Field(default="", description="用户对 AI 文案的调整意见")


 class AnalyzeStyleRequest(BaseModel):
+    """触发参考视频风格分析请求。"""
+
    reference_video_url: str = Field(..., description="参考视频 URL")
-    style_template_id: str = ""
+    style_template_id: str = Field(default="", description="风格模板 ID（可选覆盖）")


-# -- Response Schemas --
+# ── Response Schemas ───────────────────────────────────────────────────────


 class ViralVideoJobResponse(BaseModel):
-    """爆款视频任务响应（v1.6 包含 copy_result 编导脚本结构）。"""
+    """爆款视频任务响应。"""

    id: str
    user_id: str
@@ -192,7 +94,7 @@ class ViralVideoJobResponse(BaseModel):
    viral_structure: str = ""
    marketing_purpose: str = ""
    bgm_preference: str = ""
-    duration: int = 15
+    duration: int = 30
    user_copy_text: str = ""
    fusion_level: str = "ai_polish"
    reference_audio_path: str = ""
@@ -201,21 +103,6 @@ class ViralVideoJobResponse(BaseModel):
    style_guide: dict | None = None
    style_template_id: str = ""
    status: str
-    current_stage: str = (
-        ""  # 细粒度阶段 snake_case（analyzing_images/parsing_intent/generating_script/reviewing/tts_synthesizing/rendering_video/uploading）
-    )
-    phase_message: str = ""  # 中文阶段提示文案（前端轮询/SSE 直接展示）
-    image_analysis: dict | None = None
-    # v1.6 编导脚本（推荐前端使用）
-    copy_result: dict | None = None
-    # v1.5 兼容字段
-    storyboard: list | None = None
-    generated_copy_text: str = ""
-    # 音色/视频参数
-    voice_id: str = ""
-    voice_source: str = ""
-    video_ratio: str = "9:16"
-    video_model: str = ""
    intent_result: dict | None = None
    result_video_url: str = ""
    credits_cost: int = 0
@@ -228,11 +115,15 @@ class ViralVideoJobResponse(BaseModel):


 class ViralVideoHistoryResponse(BaseModel):
+    """历史记录列表响应。"""
+
    items: list[ViralVideoJobResponse]
    total: int


 class StyleTemplateResponse(BaseModel):
+    """风格模板响应。"""
+
    id: str
    name: str
    description: str = ""
@@ -241,19 +132,25 @@ class StyleTemplateResponse(BaseModel):


 class StyleTemplateListResponse(BaseModel):
+    """风格模板列表响应。"""
+
    items: list[StyleTemplateResponse]


 class AnalyzeStyleResponse(BaseModel):
+    """风格分析结果响应。"""
+
    job_id: str
    status: str
    style_guide: dict | None = None


-# -- WebSocket 事件 Schema --
+# ── WebSocket 事件 Schema ──────────────────────────────────────────────────


 class WSProgressEvent(BaseModel):
+    """WebSocket 进度推送事件。"""
+
    type: str = "viral_video:progress"
    job_id: str
    stage: str
@@ -6,9 +6,6 @@ import type {
  ViralVideoJob,
  ImageAnalysisResult,
  CopyResult,
-  AnalyzeImagesRequest,
-  GenerateCopyRequest,
-  ConfirmCopyRequest,
 } from "./types"

 /** 创建爆款视频任务 */
@@ -108,24 +105,3 @@ export function mockGenerateCopy(params: {
    }, 2200)
  })
 }
-
-/** ── 三步拆分 v1.5 真实后端 API（PR #2117 合入后启用，前端可替换 mock 调用） ── */
-
-/** 阶段1：上传图片后仅做 VLM 图片分析 + 可选参考视频风格分析，完成后状态=image_analyzed */
-export function analyzeViralImages(payload: AnalyzeImagesRequest) {
-  return apiClient.post<ViralVideoJob>("/viral-video/analyze-images", payload).then((r) => r.data)
-}
-
-/** 阶段2：用户填完营销参数后生成文案+分镜+合规审核，完成后状态=copy_generated，返回 copy_result */
-export function generateViralCopy(id: string, payload: GenerateCopyRequest) {
-  return apiClient
-    .post<ViralVideoJob>(`/viral-video/${id}/generate-copy`, payload)
-    .then((r) => r.data)
-}
-
-/** 阶段3：用户确认/编辑文案后开始 TTS→渲染→上传，完成后状态=completed */
-export function confirmViralCopy(id: string, payload: ConfirmCopyRequest = {}) {
-  return apiClient
-    .post<ViralVideoJob>(`/viral-video/${id}/confirm-copy`, payload)
-    .then((r) => r.data)
-}
@@ -12,14 +12,6 @@ export const STYLE_STRENGTHS: { value: StyleStrength; label: string }[] = [
  { value: "strict", label: "像素级复刻" },
 ]

-/** v1.6 前端时长下拉选项（5/10/15/20/25/30秒） */
-export const VALID_DURATIONS = [5, 10, 15, 20, 25, 30] as const
-export type VideoDuration = (typeof VALID_DURATIONS)[number]
-
-/** v1.6 支持的画幅比例 */
-export const VALID_RATIOS = ["9:16", "16:9", "1:1"] as const
-export type VideoRatio = (typeof VALID_RATIOS)[number]
-
 export type ViralVideoStatus =
  | "pending"
  | "running"
@@ -31,25 +23,39 @@ export type ViralVideoStatus =
  | "cancelled"

 /**
- * v1.6 后端流水线阶段。单次 Seedance 出片版：
- * image_analysis → video_analysis(可选) → intent_parsing → script_generation → review → tts → rendering → uploading
+ * 后端流水线阶段字符串。前端不展示逐阶段进度列表，仅保留类型
+ * 用于轮询时判断当前在哪个大阶段（分析中 vs 文案生成 vs 视频生成）。
 */
 export type ViralVideoStage =
  | "image_analysis"
  | "video_analysis"
  | "intent_parsing"
-  | "script_generation"
+  | "copy_fusion"
+  | "storyboard"
  | "review"
  | "tts"
+  | "bgm_select"
  | "rendering"
+  | "musetalk"
  | "uploading"

 /** 图片+视频分析阶段：属于「分析图片」按钮的范围 */
 const IMAGE_ANALYSIS_STAGES = new Set<ViralVideoStage>(["image_analysis", "video_analysis"])
-/** 编导脚本阶段：属于「生成文案」按钮的范围 */
-const COPY_STAGES = new Set<ViralVideoStage>(["intent_parsing", "script_generation", "review"])
-/** 视频生成阶段：属于「开始生成视频」按钮的范围（v1.6: TTS+单次Seedance+上传） */
-const VIDEO_STAGES = new Set<ViralVideoStage>(["tts", "rendering", "uploading"])
+/** 文案相关阶段：属于「生成文案」按钮的范围 */
+const COPY_STAGES = new Set<ViralVideoStage>([
+  "intent_parsing",
+  "copy_fusion",
+  "storyboard",
+  "review",
+])
+/** 视频相关阶段：属于「开始生成视频」按钮的范围 */
+const VIDEO_STAGES = new Set<ViralVideoStage>([
+  "tts",
+  "bgm_select",
+  "rendering",
+  "musetalk",
+  "uploading",
+])

 export function isImageAnalysisStage(stage: ViralVideoStage | undefined): boolean {
  return !!stage && IMAGE_ANALYSIS_STAGES.has(stage)
@@ -60,7 +66,7 @@ export function isCopyStage(stage: ViralVideoStage | undefined): boolean {
 export function isVideoStage(stage: ViralVideoStage | undefined): boolean {
  return !!stage && VIDEO_STAGES.has(stage)
 }
-/** 兼容旧调用：分析图片+生成文案 的所有前置阶段 */
+/** 兼容旧调用：旧的 isAnalysisStage 视为「图片分析+文案」的所有前置阶段 */
 export function isAnalysisStage(stage: ViralVideoStage | undefined): boolean {
  return isImageAnalysisStage(stage) || isCopyStage(stage)
 }
@@ -68,20 +74,12 @@ export function isAnalysisStage(stage: ViralVideoStage | undefined): boolean {
 /** 单张图片 VLM 识别出的商品信息 */
 export interface ImageProductAnalysis {
  name?: string
-  category?: string
-  brand?: string
-  colors?: string[]
-  material_or_texture?: string
-  key_features?: string[]
-  visual_style?: string
-  scene?: string
-  target_audience_hint?: string
-  text_on_image?: string
-  /** 旧字段兼容 */
  spec?: string
+  brand?: string
  features?: string[] | string
  label_text?: string
-  selling_points?: string
+  selling_points?: string[]
+  scene?: string
  image_index?: number
 }

@@ -89,50 +87,10 @@ export interface ImageAnalysisResult {
  products?: ImageProductAnalysis[]
 }

-/** v1.6 编导分镜脚本 - 单镜头 */
-export interface ShotScript {
-  /** 时间区间，如 "0-3秒" */
-  time_range?: string
-  /** 景别/角度/运镜，如 "近景俯拍45度，缓慢推镜" */
-  shot_type_angle_movement?: string
-  /** 场景描述+对白 */
-  scene_and_dialogue?: string
-  /** 人物动作/表情/物品操作细节 */
-  action_details?: string
-  /** 环境音+BGM提示 */
-  audio_bgm?: string
-  /** 转场方式（硬切/淡入淡出/叠化/结束） */
-  transition?: string
-  /** 参考图片索引（0-based，对应上传产品图数组） */
-  reference_image_index?: number | null
-}
-
-/** v1.6 编导分镜脚本 - 总览 */
-export interface CopyResultOverview {
-  theme?: string
-  total_duration?: number
-  aspect_ratio?: string
-}
-
-/** v1.6 编导分镜脚本（核心输出结构，给 Seedance 做 prompt，给 TTS 取 voiceover_script） */
 export interface CopyResult {
-  overview?: CopyResultOverview
-  /** 整体场景+光线描述 */
-  scene_and_lighting?: string
-  /** 逐镜头时间轴 */
-  shots?: ShotScript[]
-  /** 硬性约束（禁止字幕/水印/变形等） */
-  hard_constraints?: string[]
-  /** 负面提示词 */
-  negative_prompts?: string[]
-  /** 完整口播稿（纯文本，用于 TTS 合成） */
-  voiceover_script?: string
-  /** 向后兼容：= voiceover_script */
  final_copy?: string
-  /** 向后兼容：= voiceover_script */
  suggested_copy?: string
  title?: string
-  /** v1.5 旧字段兼容（老数据降级时可能出现） */
  scenes?: Array<{ shot: string; narration: string; duration?: number }>
 }

@@ -146,18 +104,13 @@ export interface StyleTemplate {
 }

 export interface IntentResult {
-  intent?: string
-  key_messages?: string[]
-  tone?: string
-  target_emotion?: string
-  call_to_action?: string
+  product: string
+  selling_points: string[]
+  target_audience: string
+  tone: string
+  structure: string
+  duration: number
  suggested_title?: string
-  /** v1.5 旧字段兼容 */
-  product?: string
-  selling_points?: string[]
-  target_audience?: string
-  structure?: string
-  duration?: number
  suggested_copy?: string
 }

@@ -170,9 +123,7 @@ export interface ViralVideoJob {
  style_template_id?: string
  style_guide?: string | Record<string, unknown>
  user_copy_text?: string
-  /** v1.6: = copy_result.voiceover_script（从 copy_result 派生，向后兼容） */
  final_copy_text?: string
-  generated_copy_text?: string
  fusion_level?: FusionLevel
  voice_id?: string
  voice_mode?: "global" | "per_video"
@@ -180,17 +131,8 @@ export interface ViralVideoJob {
  bgm_preference?: string
  intent_result?: IntentResult
  intent_text?: string
-  /** v1.6 编导分镜脚本（核心产物） */
  copy_result?: CopyResult
-  /** 向后兼容：= copy_result.shots */
-  storyboard?: ShotScript[]
  image_analysis?: ImageAnalysisResult
-  /** 视频比例：9:16 / 16:9 / 1:1，默认 9:16 */
-  video_ratio?: string
-  /** Seedance 模型 ID（空=后端默认） */
-  video_model?: string
-  /** 视频时长（秒，5-30，默认15） */
-  duration?: number
  progress_stage?: ViralVideoStage
  progress_percent?: number
  progress_message?: string
@@ -220,7 +162,6 @@ export interface GenerateViralVideoRequest {
  persona_id?: string
  viral_structure?: string
  marketing_purpose?: string
-  /** 视频时长（5-30秒，默认15） */
  duration?: number
  video_model?: string
  video_ratio?: string
@@ -234,65 +175,3 @@ export interface HistoryResponse {
  page: number
  page_size: number
 }
-
-/** v1.6 阶段1请求：图片/视频分析（POST /viral-video/analyze-images） */
-export interface AnalyzeImagesRequest {
-  images: string[]
-  reference_video_url?: string
-  style_template_id?: string
-  style_strength?: StyleStrength
-  /** TTS 音色 ID（STEP1 已选音色时传） */
-  voice_id?: string
-  /** 音色来源：preset | library | clone | upload */
-  voice_source?: "preset" | "library" | "clone" | "upload"
-  /** Seedance 视频比例：9:16 | 16:9 | 1:1 */
-  video_ratio?: string
-  /** Seedance 模型 ID（空则使用服务端默认） */
-  video_model?: string
-  /** 视频时长（秒，5-30，默认15） */
-  duration?: number
-}
-
-/** v1.6 阶段2请求：填完营销参数后生成编导分镜脚本（POST /viral-video/{id}/generate-copy） */
-export interface GenerateCopyRequest {
-  industry?: string
-  target_customer?: string
-  persona_id?: string
-  viral_structure?: string
-  marketing_purpose?: string
-  bgm_preference?: string
-  /** 视频时长（秒，5-30，默认15） */
-  duration?: number
-  user_copy_text?: string
-  fusion_level?: FusionLevel
-  reference_audio_path?: string
-  reference_video_url?: string
-  style_strength?: StyleStrength
-  style_template_id?: string
-  style_guide?: string | Record<string, unknown>
-  /** TTS 音色 ID（优先级高于 persona_id） */
-  voice_id?: string
-  /** 音色来源：preset | library | clone | upload */
-  voice_source?: "preset" | "library" | "clone" | "upload"
-  /** Seedance 视频比例（9:16/16:9/1:1 等） */
-  video_ratio?: string
-  /** Seedance 模型 ID（空则使用服务端默认） */
-  video_model?: string
-}
-
-/** v1.6 阶段3请求：用户确认/编辑口播文案后开始单次 Seedance 出片（POST /viral-video/{id}/confirm-copy） */
-export interface ConfirmCopyRequest {
-  /** 用户编辑后的口播文案；为空则使用 AI 生成的 voiceover_script */
-  edited_copy?: string
-}
-
-/** 旧分镜片段结构（保留兼容；新代码请使用 ShotScript） */
-export interface StoryboardSegment {
-  order: number
-  type: string
-  description: string
-  text: string
-  duration: number
-  ken_burns?: string
-  transition?: string
-}
@@ -34,63 +34,83 @@ interface Props {

 /** 兜底 mock 音色（后端 /api/v1/tts/presets 返回字段不够时使用） */
 const MOCK_VOICES: PresetVoice[] = [
-  // ⚠️ 兜底 mock，仅在 /voices/presets 接口不可达时使用；ID 必须与后端
-  // packages/domain/preset_voices.py PRESET_VOICES 的 voice_id 对齐（v3后缀）
  {
-    id: "longxiaochun_v3",
+    id: "long-xiaochun",
    name: "龙小淳",
    gender: "female",
    category: "女声",
    desc: "知性积极女声，适合语音助手",
  },
  {
-    id: "longxiaoxia_v3",
+    id: "long-xiaoxia",
    name: "龙小夏",
    gender: "female",
    category: "女声",
    desc: "沉稳权威女声，适合新闻播报",
  },
  {
-    id: "longsanshu_v3",
+    id: "long-xiaoyan",
+    name: "龙小颜",
+    gender: "female",
+    category: "女声",
+    desc: "温柔甜美女声，适合情感口播",
+  },
+  {
+    id: "long-xiaotong",
+    name: "龙小彤",
+    gender: "female",
+    category: "女声",
+    desc: "活力少女音，适合短视频带货",
+  },
+  {
+    id: "long-sanshu",
    name: "龙三叔",
    gender: "male",
    category: "男声",
    desc: "沉稳质感男声，适合有声书",
  },
  {
-    id: "longyue_v3",
+    id: "long-xiaogang",
+    name: "龙小刚",
+    gender: "male",
+    category: "男声",
+    desc: "阳光活力男声，适合解说",
+  },
+  {
+    id: "long-xiaocheng",
+    name: "龙小诚",
+    gender: "male",
+    category: "男声",
+    desc: "磁性商务男声，适合品牌宣传",
+  },
+  {
+    id: "long-xiaozhi",
+    name: "龙小智",
+    gender: "child",
+    category: "童声",
+    desc: "可爱童声，适合亲子内容",
+  },
+  {
+    id: "long-yue",
    name: "龙悦",
    gender: "female",
-    category: "女声",
-    desc: "温暖磁性女声，适合广告配音",
+    category: "情绪",
+    desc: "温柔治愈女声，适合睡前/助眠",
  },
  {
-    id: "longshu_v3",
-    name: "龙书",
+    id: "long-xiaodong",
+    name: "龙晓东",
    gender: "male",
-    category: "男声",
-    desc: "沉稳青年男声，适合教育讲解",
+    category: "方言",
+    desc: "东北方言男声，接地气",
  },
+  { id: "long-xiaoling", name: "龙小玲", gender: "female", category: "方言", desc: "粤语女声" },
  {
-    id: "longyingjing_v3",
-    name: "龙应静",
+    id: "long-xiaoxiao-neural",
+    name: "晓晓",
    gender: "female",
    category: "女声",
-    desc: "低调冷静女声，适合纪录片解说",
-  },
-  {
-    id: "longshuo_v3",
-    name: "龙硕",
-    gender: "male",
-    category: "男声",
-    desc: "博才干练男声，适合科技类内容",
-  },
-  {
-    id: "longtian_v3",
-    name: "龙甜",
-    gender: "female",
-    category: "女声",
-    desc: "活泼女声，适合短视频配音",
+    desc: "温柔女声",
  },
 ]

@@ -158,22 +178,23 @@ const PresetVoicePickerModal: React.FC<Props> = ({

  // 合并真实数据和 mock：如果真实数据 gender/category 缺失，用 mock 兜底
  const allVoices: PresetVoice[] = useMemo(() => {
-    // 真实 API 返回的 voice_id 以 API 为准（如 longxiaochun_v3），前端不做硬编码覆盖
    const realList: PresetVoice[] = (voices || []).map((v) => {
-      // 按 id 精确匹配 mock 获取补充元信息（id 即 voice_id，唯一稳定键）
-      const mockMatch = MOCK_VOICES.find((m) => m.id === v.id)
+      // 按 name 模糊匹配 mock 获取补充信息
+      const mockMatch = MOCK_VOICES.find(
+        (m) => v.name?.includes(m.name.slice(1)) || m.name.includes(v.name?.slice(0, 2) || "___"),
+      )
      return {
        ...v,
        gender: v.gender || mockMatch?.gender,
        category:
          v.category ||
          mockMatch?.category ||
-          (v.gender === "female" ? "女声" : v.gender === "male" ? "男声" : "其他"),
+          (v.gender === "female" ? "女声" : v.gender === "male" ? "男声" : undefined),
        desc: v.desc || mockMatch?.desc,
        sample_audio_url: v.sample_audio_url,
      }
    })
-    // 如果没有真实数据，使用兜底 mock（接口失败时）
+    // 如果没有真实数据，使用 mock
    return realList.length > 0 ? realList : MOCK_VOICES
  }, [voices])

@@ -1,45 +0,0 @@
-import { describe, it, expect } from "vitest"
-import { getErrorMessage, isErrorMsgShown } from "@/api/errors"
-
-describe("api/errors", () => {
-  it("returns string error directly", () => {
-    expect(getErrorMessage("plain")).toBe("plain")
-  })
-  it("uses Error.message", () => {
-    expect(getErrorMessage(new Error("boom"))).toBe("boom")
-  })
-  it("returns fallback for empty/unknown", () => {
-    expect(getErrorMessage(null)).toBe("操作失败，请稍后重试")
-    expect(getErrorMessage(undefined, "f")).toBe("f")
-  })
-  it("reads axios-like response.data.detail", () => {
-    const err = { response: { data: { detail: "后端报错" } }, isAxiosError: true }
-    expect(getErrorMessage(err)).toContain("后端报错")
-  })
-  it("reads axios-like response.data.message", () => {
-    const err = { response: { data: { message: "消息字段" } }, isAxiosError: true }
-    expect(getErrorMessage(err)).toContain("消息字段")
-  })
-  it("HTTP 404 fallback", () => {
-    const err = { response: { status: 404, data: null }, isAxiosError: true }
-    expect(getErrorMessage(err)).toContain("404")
-  })
-  it("HTTP 401 fallback", () => {
-    const err = { response: { status: 401, data: null }, isAxiosError: true }
-    expect(getErrorMessage(err)).toContain("登录")
-  })
-  it("network error", () => {
-    const err = { request: {}, isAxiosError: true }
-    expect(getErrorMessage(err)).toContain("网络")
-  })
-  it("isErrorMsgShown returns false for auth/abort", () => {
-    const authErr = { response: { status: 401 } }
-    const abortErr = { code: "ECONNABORTED" }
-    expect(isErrorMsgShown(authErr)).toBe(false)
-    expect(isErrorMsgShown(abortErr)).toBe(false)
-    const e: any = new Error("x")
-    e.__msgShown = true
-    expect(isErrorMsgShown(e)).toBe(true)
-    expect(isErrorMsgShown(new Error("x"))).toBe(false)
-  })
-})
@@ -1,226 +0,0 @@
-import { describe, expect, it, vi, beforeEach, afterEach } from "vitest"
-import {
-  generateViralVideo,
-  getViralVideoJob,
-  confirmViralVideoIntent,
-  retryViralVideo,
-  getViralVideoHistory,
-  getViralStyleTemplates,
-  analyzeViralStyle,
-  mockImageAnalysis,
-  mockGenerateCopy,
-  analyzeViralImages,
-  generateViralCopy,
-  confirmViralCopy,
-} from "@/api/viral-video"
-import {
-  VALID_DURATIONS,
-  VALID_RATIOS,
-  isVideoStage,
-  isImageAnalysisStage,
-  isCopyStage,
-  isAnalysisStage,
-} from "@/api/viral-video/types"
-
-const mockGet = vi.fn()
-const mockPost = vi.fn()
-
-vi.mock("@/api/client", () => ({
-  default: {
-    get: (...args: unknown[]) => mockGet(...args),
-    post: (...args: unknown[]) => mockPost(...args),
-  },
-}))
-
-vi.mock("antd", () => ({ message: { error: vi.fn(), success: vi.fn() } }))
-
-// 让 setTimeout 同步执行，避免测试等待 1.8s/2.2s
-beforeEach(() => {
-  vi.useFakeTimers()
-  vi.clearAllMocks()
-  mockGet.mockResolvedValue({ data: {} })
-  mockPost.mockResolvedValue({ data: {} })
-})
-afterEach(() => {
-  vi.useRealTimers()
-})
-
-describe("viral-video constants & stage helpers", () => {
-  afterEach(() => {
-    vi.useRealTimers()
-  })
-  beforeEach(() => {
-    vi.useFakeTimers()
-    vi.clearAllMocks()
-  })
-
-  it("VALID_DURATIONS/VALID_RATIOS", () => {
-    expect(VALID_DURATIONS).toEqual([5, 10, 15, 20, 25, 30])
-    expect(VALID_RATIOS).toEqual(expect.arrayContaining(["9:16", "16:9", "1:1"]))
-  })
-
-  it("isVideoStage", () => {
-    expect(isVideoStage("tts")).toBe(true)
-    expect(isVideoStage("rendering")).toBe(true)
-    expect(isVideoStage("uploading")).toBe(true)
-    expect(isVideoStage("script_generation")).toBe(false)
-    expect(isVideoStage("completed")).toBe(false)
-    expect(isVideoStage(undefined)).toBe(false)
-  })
-
-  it("isImageAnalysisStage", () => {
-    expect(isImageAnalysisStage("image_analysis")).toBe(true)
-    expect(isImageAnalysisStage("video_analysis")).toBe(true)
-    expect(isImageAnalysisStage("script_generation")).toBe(false)
-    expect(isImageAnalysisStage(undefined)).toBe(false)
-  })
-
-  it("isCopyStage", () => {
-    expect(isCopyStage("intent_parsing")).toBe(true)
-    expect(isCopyStage("script_generation")).toBe(true)
-    expect(isCopyStage("review")).toBe(true)
-    expect(isCopyStage("tts")).toBe(false)
-  })
-
-  it("isAnalysisStage is union", () => {
-    expect(isAnalysisStage("image_analysis")).toBe(true)
-    expect(isAnalysisStage("script_generation")).toBe(true)
-    expect(isAnalysisStage("tts")).toBe(false)
-    expect(isAnalysisStage(undefined)).toBe(false)
-  })
-})
-
-describe("viral-video API wrappers", () => {
-  afterEach(() => {
-    vi.useRealTimers()
-  })
-  beforeEach(() => {
-    vi.useFakeTimers()
-    vi.clearAllMocks()
-    mockGet.mockResolvedValue({ data: {} })
-    mockPost.mockResolvedValue({ data: {} })
-  })
-
-  it("generateViralVideo", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j1" } })
-    const r = generateViralVideo({ images: ["img1"] } as never)
-    vi.runAllTimersAsync()
-    expect(await r).toEqual({ id: "j1" })
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/generate", { images: ["img1"] })
-  })
-
-  it("getViralVideoJob", async () => {
-    mockGet.mockResolvedValue({ data: { id: "j2" } })
-    const r = getViralVideoJob("j2")
-    vi.runAllTimersAsync()
-    expect(await r).toEqual({ id: "j2" })
-    expect(mockGet).toHaveBeenCalledWith("/viral-video/j2")
-  })
-
-  it("confirmViralVideoIntent", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j3" } })
-    const r = confirmViralVideoIntent("j3", { confirmed_copy: "hi" })
-    vi.runAllTimersAsync()
-    await r
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/j3/confirm-intent", {
-      confirmed_copy: "hi",
-    })
-  })
-
-  it("retryViralVideo", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j4" } })
-    await retryViralVideo("j4")
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/j4/retry")
-  })
-
-  it("getViralVideoHistory", async () => {
-    mockGet.mockResolvedValue({ data: { items: [], total: 0 } })
-    await getViralVideoHistory({ page: 1, page_size: 20 })
-    expect(mockGet).toHaveBeenCalledWith("/viral-video/history", {
-      params: { page: 1, page_size: 20 },
-    })
-  })
-
-  it("getViralStyleTemplates", async () => {
-    mockGet.mockResolvedValue({ data: [] })
-    await getViralStyleTemplates()
-    expect(mockGet).toHaveBeenCalledWith("/viral-video/style-templates")
-  })
-
-  it("analyzeViralStyle", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j5" } })
-    await analyzeViralStyle("j5")
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/j5/analyze-style")
-  })
-
-  it("analyzeViralImages", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j6" } })
-    await analyzeViralImages({ images: ["a.png"] } as never)
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/analyze-images", { images: ["a.png"] })
-  })
-
-  it("generateViralCopy", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j7" } })
-    await generateViralCopy("j7", { duration: 15 } as never)
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/j7/generate-copy", { duration: 15 })
-  })
-
-  it("confirmViralCopy", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j8" } })
-    await confirmViralCopy("j8", { edited_copy: "xxx" })
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/j8/confirm-copy", { edited_copy: "xxx" })
-    mockPost.mockClear()
-    await confirmViralCopy("j8")
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/j8/confirm-copy", {})
-  })
-})
-
-describe("viral-video client mocks", () => {
-  beforeEach(() => {
-    vi.useFakeTimers()
-    vi.clearAllMocks()
-  })
-  afterEach(() => {
-    vi.useRealTimers()
-  })
-
-  it("mockImageAnalysis returns product list", async () => {
-    const p = mockImageAnalysis([
-      { name: "a.png" },
-      { name: "b.jpg" },
-      { name: "c.webp" },
-      { name: "d.png" },
-    ])
-    vi.advanceTimersByTime(2000)
-    const r = await p
-    expect(r.products).toHaveLength(3)
-    expect(r.products[0].image_index).toBe(0)
-    expect(r.products[0].brand).toBe("示例品牌")
-    expect(r.products[1].spec).toBe("300g/盒")
-  })
-
-  it("mockImageAnalysis handles empty array", async () => {
-    const p = mockImageAnalysis([])
-    vi.advanceTimersByTime(2000)
-    const r = await p
-    expect(r.products).toHaveLength(0)
-  })
-
-  it("mockGenerateCopy returns copy_result shape", async () => {
-    const p = mockGenerateCopy({ product: "矿泉水", industry: "饮料", marketingPurpose: "种草" })
-    vi.advanceTimersByTime(3000)
-    const r = await p
-    expect(r.title).toContain("种草")
-    expect(r.title).toContain("矿泉水")
-    expect(r.final_copy.length).toBeGreaterThan(50)
-    expect(r.suggested_copy).toBeTruthy()
-  })
-
-  it("mockGenerateCopy uses defaults when params missing", async () => {
-    const p = mockGenerateCopy({} as never)
-    vi.advanceTimersByTime(3000)
-    const r = await p
-    expect(r.title).toContain("品牌种草")
-    expect(r.final_copy).toContain("这款产品")
-  })
-})
@@ -1,21 +0,0 @@
-import { describe, it, expect } from "vitest"
-import { getGenerationPhase } from "@/pages/generate/hooks/generate-video/phase"
-
-describe("getGenerationPhase", () => {
-  it("returns 分析素材与配置 for p<20", () => {
-    expect(getGenerationPhase(0)).toEqual({ label: "分析素材与配置", icon: "🔍" })
-    expect(getGenerationPhase(19).label).toBe("分析素材与配置")
-  })
-  it("returns 智能剪辑合成 for 20<=p<50", () => {
-    expect(getGenerationPhase(20).label).toBe("智能剪辑合成")
-    expect(getGenerationPhase(49).label).toBe("智能剪辑合成")
-  })
-  it("returns 渲染视频中 for 50<=p<80", () => {
-    expect(getGenerationPhase(50).label).toBe("渲染视频中")
-    expect(getGenerationPhase(79).label).toBe("渲染视频中")
-  })
-  it("returns 即将完成 for p>=80", () => {
-    expect(getGenerationPhase(80)).toEqual({ label: "即将完成", icon: "✨" })
-    expect(getGenerationPhase(100).label).toBe("即将完成")
-  })
-})
@@ -1,26 +0,0 @@
-import { describe, it, expect, vi, afterEach } from "vitest"
-import { formatDuration, formatFileSize, formatDate } from "@/pages/products/detailUtils"
-
-describe("products/detailUtils", () => {
-  afterEach(() => {
-    vi.useRealTimers()
-  })
-  it("formatDuration", () => {
-    expect(formatDuration(0)).toBe("00:00")
-    expect(formatDuration(-1)).toBe("00:00")
-    expect(formatDuration(5)).toBe("00:05")
-    expect(formatDuration(65)).toBe("01:05")
-    expect(formatDuration(3600)).toBe("60:00")
-  })
-  it("formatFileSize MB/GB", () => {
-    expect(formatFileSize(0)).toBe("-")
-    expect(formatFileSize(-1)).toBe("-")
-    expect(formatFileSize(5.3)).toBe("5.3 MB")
-    expect(formatFileSize(2048)).toBe("2.00 GB")
-  })
-  it("formatDate returns zh-CN format", () => {
-    vi.setSystemTime(new Date("2026-01-15T10:30:00"))
-    expect(formatDate("2026-01-15T10:30:00Z")).toMatch(/2026/)
-    expect(formatDate("")).toBe("-")
-  })
-})
@@ -1,54 +0,0 @@
-import { describe, it, expect, beforeEach, vi, afterEach } from "vitest"
-import { renderHook, act } from "@testing-library/react"
-import { useViralVideoPolling } from "@/pages/viral-video/hooks/useViralVideoPolling"
-
-const getViralVideoJobMock = vi.fn()
-vi.mock("@/api/viral-video", () => ({
-  getViralVideoJob: (...args: unknown[]) => getViralVideoJobMock(...args),
-}))
-
-describe("useViralVideoPolling", () => {
-  beforeEach(() => {
-    vi.clearAllMocks()
-    vi.useFakeTimers()
-  })
-  afterEach(() => {
-    vi.useRealTimers()
-  })
-
-  it("不传入 jobId 时不发起请求", () => {
-    renderHook(() => useViralVideoPolling(null, vi.fn()))
-    expect(getViralVideoJobMock).not.toHaveBeenCalled()
-  })
-
-  it("传入 jobId 后立即调用 getViralVideoJob", () => {
-    getViralVideoJobMock.mockResolvedValue({
-      id: "j1",
-      status: "completed",
-      progress_stage: "completed",
-    })
-    renderHook(() => useViralVideoPolling("j1", vi.fn()))
-    expect(getViralVideoJobMock).toHaveBeenCalledWith("j1")
-  })
-
-  it("stop() 会停止后续轮询（终态也会 stop）", async () => {
-    getViralVideoJobMock.mockResolvedValue({
-      id: "j2",
-      status: "completed",
-      progress_stage: "completed",
-    })
-    const { result } = renderHook(() => useViralVideoPolling("j2", vi.fn(), { intervalMs: 50 }))
-    // 等第一次 promise 完成
-    await act(async () => {
-      await Promise.resolve()
-      await Promise.resolve()
-    })
-    // 终态后不会再调度新请求
-    const calls = getViralVideoJobMock.mock.calls.length
-    act(() => {
-      vi.advanceTimersByTime(2000)
-    })
-    expect(getViralVideoJobMock).toHaveBeenCalledTimes(calls)
-    expect(result.current.stop).toBeTypeOf("function")
-  })
-})
@@ -1,35 +0,0 @@
-import { describe, it, expect } from "vitest"
-import {
-  genderLabel,
-  languageLabel,
-  genderClass,
-  formatTime,
-  formatFileSize,
-} from "@/pages/voices/utils/format"
-
-describe("voices utils/format", () => {
-  it("genderLabel returns label or falls back to value", () => {
-    expect(genderLabel("female")).toContain("女")
-    expect(genderLabel("male")).toContain("男")
-    expect(genderLabel("unknown" as never)).toBe("unknown")
-  })
-  it("languageLabel returns label or falls back", () => {
-    expect(languageLabel("zh-CN" as never)).toBeTruthy()
-    expect(languageLabel("xx-XX" as never)).toBe("xx-XX")
-  })
-  it("genderClass returns css class", () => {
-    expect(genderClass("female")).toBe("xx-voice-gender--female")
-  })
-  it("formatTime pads minutes/seconds", () => {
-    expect(formatTime(0)).toBe("00:00")
-    expect(formatTime(5)).toBe("00:05")
-    expect(formatTime(65)).toBe("01:05")
-    expect(formatTime(3600)).toBe("60:00")
-  })
-  it("formatFileSize human-readable", () => {
-    expect(formatFileSize(0)).toBe("0 B")
-    expect(formatFileSize(512)).toBe("512 B")
-    expect(formatFileSize(2048)).toBe("2.0 KB")
-    expect(formatFileSize(2 * 1024 * 1024)).toBe("2.0 MB")
-  })
-})
@@ -28,12 +28,11 @@ export default defineConfig({
        "src/pages/editing-planner/EditingPlanner.tsx",
        "src/pages/assets/AssetLibrary.tsx",
        "src/pages/voice-materials/VoiceMaterialLibrary.tsx",
-        "src/pages/viral-video/ViralVideoPage.tsx",
      ],
      // CI 覆盖率门禁（Phase 4 后提升，逐步逼近目标）
      // 当前实际：行 ~62% / 分支 ~61% / 函数 ~25%
      thresholds: {
-        lines: 49,
+        lines: 50,
        branches: 50,
        functions: 20,
      },
@@ -104,43 +104,6 @@ Staging 当前可以保持 no-op；Production 开启前必须先验证 SMTP/Redi

 ---

-## Staging 服务器 Docker 凭证配置
-
-Staging 服务器（116.62.226.203）需要配置 ACR 和 Gitea Registry 凭证，否则 docker pull 和 Watchtower 自动更新会失败。
-
-### 凭证文件位置
- Docker 配置文件：`/root/.docker/config.json`
- 包含两个 registry 的认证信息：
-  - `xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com`（阿里云 ACR）
-  - `git.xiaoxiajianji.com`（Gitea 容器镜像仓库）
-
-### 服务器迁移后恢复步骤
-```bash
-# 1. 登录 ACR
-docker login xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com -u <ACR_USERNAME>
-
-# 2. 登录 Gitea Registry
-docker login git.xiaoxiajianji.com -u xiaoxia -p <GITEA_REGISTRY_TOKEN>
-
-# 3. 重启 Watchtower（确保挂载最新 config.json）
-docker restart watchtower
-```
-
-### Watchtower 配置
- 容器名：`watchtower`
- 检查间隔：300 秒（5 分钟）
- 监控容器：`xiaoxia-api-staging`、`xiaoxia-worker-staging`、`xiaoxia-web-staging`
- 必须挂载 `-v /root/.docker/config.json:/config.json` 才能拉取私有镜像
- 必须挂载 `-v /var/run/docker.sock:/var/run/docker.sock` 才能管理容器
- 容器使用 `:dev` 稳定 tag，Watchtower 通过检测 `:dev` tag 的 digest 变化来发现更新
-
-### 镜像 Tag 策略
- CI 每次构建推送三种 tag：`${GITHUB_SHA}`（精确版本）、`${GITHUB_REF_NAME}`（分支名）、`:dev`（滚动 tag，仅 develop 分支）
- Staging 容器统一使用 `:dev` tag 启动，确保 Watchtower 能自动发现新版本
- Migration（alembic）使用 commit SHA tag 执行，不依赖 Watchtower
-
---
-
 ## Gitea Actions 约定

 - `develop` 分支触发 staging 部署。
@@ -30,10 +30,6 @@ COPY deploy/configs/douyin_cookies.txt /app/configs/douyin_cookies.txt
 # 强制升级 yt-dlp 到最新（抖音反爬经常变更，旧版 cookies 支持失效；#1968/#1963）
 RUN pip install --no-cache-dir -i https://mirrors.aliyun.com/pypi/simple/ --trusted-host mirrors.aliyun.com --upgrade "yt-dlp>=2026.8.19"

-# API 启动入口（幂等迁移 + uvicorn）—— #2129: watchtower 自动部署兜底
-COPY infra/docker/entrypoint-api.sh /usr/local/bin/entrypoint-api.sh
-RUN chmod +x /usr/local/bin/entrypoint-api.sh
-
 # 设置环境变量
 ENV PATH="/opt/venv/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin"
 ENV PYTHONPATH=/app:/app/apps/api
@@ -45,4 +41,4 @@ HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
    CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/health', timeout=5)"

 # API 入口点
-ENTRYPOINT ["/usr/local/bin/entrypoint-api.sh"]
+CMD ["uvicorn", "apps.api.main:app", "--host", "0.0.0.0", "--port", "8000"]
@@ -1,22 +0,0 @@
-#!/bin/bash
-# API 启动入口：先幂等执行数据库迁移，再启动传入的 CMD（默认 uvicorn）
-# 解决 watchtower 自动拉取新镜像后容器重启、未跑 alembic upgrade head 导致新列缺失 500 的问题（#2129）
-set -e
-
-cd /app
-
-echo "[entrypoint-api] Running alembic upgrade head..."
-if alembic upgrade head; then
-  echo "[entrypoint-api] Migrations ok."
-else
-  echo "[entrypoint-api] WARNING: alembic upgrade failed, continuing (existing columns should be fine)..." >&2
-fi
-
-# 若有显式 CMD（CI 部署时 docker compose run --rm api sh -c '...' 传入），直接 exec 它
-if [ "$#" -gt 0 ]; then
-  echo "[entrypoint-api] Exec custom command: $*"
-  exec "$@"
-fi
-
-echo "[entrypoint-api] Starting uvicorn..."
-exec uvicorn apps.api.main:app --host 0.0.0.0 --port 8000
@@ -18,17 +18,6 @@

 set -e

-# #2129: 幂等执行数据库迁移（watchtower 自动部署兜底）
-# worker 容器独立启动，不能依赖 API 容器先跑迁移
-cd /app
-echo "[entrypoint-worker] Running alembic upgrade head..."
-if alembic upgrade head; then
-  echo "[entrypoint-worker] Migrations ok."
-else
-  echo "[entrypoint-worker] WARNING: alembic upgrade failed, continuing to start workers..." >&2
-fi
-cd - >/dev/null
-
 MAX_TASKS="${WORKER_MAX_TASKS_PER_CHILD:-100}"

 # ── 并发计算：显式 env 优先；否则从 WORKER_CONCURRENCY 按比例推导 ──
@@ -34,7 +34,6 @@ ENV APP_VERSION=$APP_VERSION

 # 复制文件（按变化频率从低到高排序，最大化层缓存命中）
 COPY alembic.ini /app/alembic.ini
-COPY alembic/ /app/alembic/
 COPY migrations/ /app/migrations/
 COPY packages/ /app/packages/
 # PR #1844 起，worker 还需要加载 apps.api.app.tasks.lipsync_tts，
@@ -943,23 +943,10 @@ class ViralVideoJobModel(Base):
    style_strength = Column(String(20), nullable=False, default="medium")
    style_guide = Column(JSON, nullable=True)
    style_template_id = Column(String(36), nullable=False, default="", index=True)
-    # v1.5 音频/视频参数
-    voice_id = Column(String(200), nullable=False, default="")
-    voice_source = Column(String(20), nullable=False, default="")
-    video_ratio = Column(String(10), nullable=False, default="9:16")
-    video_model = Column(String(100), nullable=False, default="")
    # 结果与状态
    status = Column(String(30), nullable=False, default="pending", index=True)
-    current_stage = Column(String(200), nullable=False, default="")  # 细粒度阶段 snake_case
-    phase_message = Column(String(500), nullable=False, default="")  # 阶段中文提示文案
-    heartbeat_at = Column(DateTime, nullable=True, index=True)  # worker 心跳，用于僵尸任务超时回收
    intent_result = Column(JSON, nullable=True)
    image_analysis = Column(JSON, nullable=True)
-    storyboard = Column(JSON, nullable=True)
-    generated_copy_text = Column(Text, nullable=False, default="")
-    copy_result = Column(
-        JSON, nullable=True
-    )  # v1.6: 编导脚本结构{overview,scene_and_lighting,shots,hard_constraints,negative_prompts,voiceover_script}
    result_video_url = Column(String(1000), nullable=False, default="")
    credits_cost = Column(Integer, nullable=False, default=0)
    error_msg = Column(Text, nullable=False, default="")
@@ -81,41 +81,6 @@ def ensure_database_exists(database_url: str) -> None:
        admin_engine.dispose()


-_VIRAL_VIDEO_BACKFILL_COLS = [
-    ("storyboard", "JSON"),
-    ("generated_copy_text", "TEXT NOT NULL DEFAULT ''"),
-    ("voice_id", "VARCHAR(200) NOT NULL DEFAULT ''"),
-    ("voice_source", "VARCHAR(20) NOT NULL DEFAULT ''"),
-    ("video_ratio", "VARCHAR(10) NOT NULL DEFAULT '9:16'"),
-    ("video_model", "VARCHAR(100) NOT NULL DEFAULT ''"),
-    ("copy_result", "JSON"),
-]
-
-
-def _ensure_viral_video_columns(connection) -> None:
-    """Idempotently add new columns to viral_video_jobs; create_all will not ALTER existing tables."""
-    from sqlalchemy import inspect as _inspect
-
-    try:
-        insp = _inspect(connection)
-        if not insp.has_table("viral_video_jobs"):
-            return
-        existing = {c["name"] for c in insp.get_columns("viral_video_jobs")}
-    except Exception:
-        return
-    import logging as _logging
-
-    _log = _logging.getLogger(__name__)
-    for col, ddl in _VIRAL_VIDEO_BACKFILL_COLS:
-        if col in existing:
-            continue
-        try:
-            connection.execute(text(f"ALTER TABLE viral_video_jobs ADD COLUMN {col} {ddl}"))
-            _log.info("added column viral_video_jobs.%s", col)
-        except Exception as e:
-            _log.warning("add column %s failed: %s", col, e)
-
-
 def initialize_database(engine) -> None:
    """初始化数据库 schema。

@@ -135,5 +100,4 @@ def initialize_database(engine) -> None:
                text("SELECT pg_advisory_unlock(:lock_id)"),
                {"lock_id": SCHEMA_INIT_LOCK_ID},
            )
-            _ensure_viral_video_columns(connection)
            connection.commit()
@@ -24,7 +24,7 @@ def _to_domain(model: ViralVideoJobModel) -> ViralVideoJob:
        viral_structure=model.viral_structure or "",
        marketing_purpose=model.marketing_purpose or "",
        bgm_preference=model.bgm_preference or "",
-        duration=model.duration or 15,
+        duration=model.duration or 30,
        user_copy_text=model.user_copy_text or "",
        fusion_level=model.fusion_level or "ai_polish",
        reference_audio_path=model.reference_audio_path or "",
@@ -32,19 +32,9 @@ def _to_domain(model: ViralVideoJobModel) -> ViralVideoJob:
        style_strength=getattr(model, "style_strength", "medium") or "medium",
        style_guide=dict(model.style_guide) if model.style_guide else None,
        style_template_id=getattr(model, "style_template_id", "") or "",
-        voice_id=getattr(model, "voice_id", "") or "",
-        voice_source=getattr(model, "voice_source", "") or "",
-        video_ratio=getattr(model, "video_ratio", "9:16") or "9:16",
-        video_model=getattr(model, "video_model", "") or "",
        status=ViralVideoStatus(model.status) if model.status else ViralVideoStatus.PENDING,
-        current_stage=getattr(model, "current_stage", "") or "",
-        phase_message=getattr(model, "phase_message", "") or "",
-        heartbeat_at=getattr(model, "heartbeat_at", None),
        intent_result=dict(model.intent_result) if model.intent_result else None,
        image_analysis=dict(model.image_analysis) if getattr(model, "image_analysis", None) else None,
-        storyboard=list(model.storyboard) if getattr(model, "storyboard", None) else None,
-        generated_copy_text=getattr(model, "generated_copy_text", "") or "",
-        copy_result=dict(model.copy_result) if getattr(model, "copy_result", None) else None,
        result_video_url=model.result_video_url or "",
        credits_cost=model.credits_cost or 0,
        error_msg=model.error_msg or "",
@@ -81,19 +71,9 @@ class SQLAlchemyViralVideoJobRepository:
            style_strength=job.style_strength,
            style_guide=job.style_guide,
            style_template_id=job.style_template_id,
-            voice_id=job.voice_id,
-            voice_source=job.voice_source,
-            video_ratio=job.video_ratio,
-            video_model=job.video_model,
            status=job.status,
-            current_stage=job.current_stage or "",
-            phase_message=job.phase_message or "",
-            heartbeat_at=job.heartbeat_at,
            intent_result=job.intent_result,
            image_analysis=job.image_analysis,
-            storyboard=job.storyboard,
-            generated_copy_text=job.generated_copy_text,
-            copy_result=job.copy_result,
            result_video_url=job.result_video_url,
            credits_cost=job.credits_cost,
            error_msg=job.error_msg,
@@ -112,14 +92,8 @@ class SQLAlchemyViralVideoJobRepository:
        if model is None:
            raise ValueError(f"ViralVideoJob {job.id} not found")
        model.status = job.status
-        model.current_stage = job.current_stage or ""
-        model.phase_message = job.phase_message or ""
-        model.heartbeat_at = job.heartbeat_at
        model.intent_result = job.intent_result
        model.image_analysis = job.image_analysis
-        model.storyboard = job.storyboard
-        model.generated_copy_text = job.generated_copy_text or ""
-        model.copy_result = job.copy_result
        model.result_video_url = job.result_video_url
        model.credits_cost = job.credits_cost
        model.error_msg = job.error_msg
@@ -127,24 +101,6 @@ class SQLAlchemyViralVideoJobRepository:
        model.started_at = job.started_at
        model.completed_at = job.completed_at
        model.style_guide = job.style_guide
-        # v1.5 three-stage: persist user-editable params so resume uses latest values
-        model.user_copy_text = job.user_copy_text
-        model.industry = job.industry
-        model.target_customer = job.target_customer
-        model.persona_id = job.persona_id
-        model.viral_structure = job.viral_structure
-        model.marketing_purpose = job.marketing_purpose
-        model.bgm_preference = job.bgm_preference
-        model.duration = job.duration
-        model.fusion_level = job.fusion_level
-        model.reference_audio_path = job.reference_audio_path
-        model.reference_video_url = job.reference_video_url
-        model.style_strength = job.style_strength
-        model.style_template_id = job.style_template_id
-        model.voice_id = job.voice_id or ""
-        model.voice_source = job.voice_source or ""
-        model.video_ratio = job.video_ratio or "9:16"
-        model.video_model = job.video_model or ""
        model.updated_at = datetime.now(timezone.utc)
        self.session.commit()

@@ -170,9 +126,7 @@ class SQLAlchemyViralVideoJobRepository:
            self.session.query(ViralVideoJobModel)
            .filter(
                ViralVideoJobModel.user_id == user_id,
-                ViralVideoJobModel.status.in_(
-                    ["pending", "running", "wait_user_confirm", "image_analyzed", "copy_generated"]
-                ),
+                ViralVideoJobModel.status.in_(["pending", "running", "wait_user_confirm"]),
            )
            .count()
        )
@@ -90,14 +90,11 @@ class SharedSettings(BaseSettings):

    # ── 豆包大模型（火山引擎方舟） ────────────────────────────────────────
    doubao_api_key: str = ""
-    doubao_model: str = "doubao-seed-1-6-250615"  # 推理模型（通用兜底）
-    doubao_fast_model: str = "doubao-1-5-pro-32k-250115"  # 快速结构化输出模型（编导脚本/意图解析/审核）
+    doubao_model: str = "doubao-seed-1-6-250615"
    doubao_base_url: str = "https://ark.cn-beijing.volces.com/api/v3"
    doubao_timeout: int = 30
    doubao_max_retries: int = 2
-    doubao_vision_model: str = "doubao-1-5-vision-pro-250328"  # 高精度视觉（备用）
-    doubao_vision_lite_model: str = "doubao-1-5-vision-lite-250315"  # 快速视觉（商品识别默认，速度优先）
-    doubao_vision_use_lite: bool = True  # viral-video 图片分析默认用 lite 提速
+    doubao_vision_model: str = "doubao-1-5-vision-pro-250915"
    doubao_embedding_model: str = "doubao-embedding-large-text-240915"
    doubao_video_model: str = "doubao-seedance-2-5-260628"
    doubao_video_timeout: int = 600  # 视频生成轮询总超时（秒）
@@ -1,11 +1,10 @@
 """ViralVideoJob 领域模型 — 爆款视频任务.

-v1.6 重大简化：Seedance 2.5 单次最长30秒，单次调用直接出片，不再分段/拼接/ffmpeg concat。
-状态机（三步分步）：
-  pending -> running -> image_analyzed -> running -> copy_generated -> running -> completed
-                                 wait_user_confirm -> running -> completed (旧路径兼容)
-  任意阶段 fail; 任意非终态 cancel.
-  failed -> pending (retry 重置后重跑)。
+状态机：
+  pending → running → completed
+              ↘ failed → pending (retry)
+       ↘ cancelled
+  running 中可暂停：running → wait_user_confirm → running (confirm-intent resume)
 """

 from __future__ import annotations
@@ -27,10 +26,10 @@ from uuid import uuid4


 class ViralVideoStatus(StrEnum):
+    """爆款视频任务状态枚举。"""
+
    PENDING = "pending"
    RUNNING = "running"
-    IMAGE_ANALYZED = "image_analyzed"
-    COPY_GENERATED = "copy_generated"
    WAIT_USER_CONFIRM = "wait_user_confirm"
    COMPLETED = "completed"
    FAILED = "failed"
@@ -38,32 +37,44 @@ class ViralVideoStatus(StrEnum):


 class ViralVideoStage(StrEnum):
+    """编排流水线阶段枚举（用于 WS 进度推送）。"""
+
    IMAGE_ANALYSIS = "image_analysis"
    VIDEO_ANALYSIS = "video_analysis"
    INTENT_PARSING = "intent_parsing"
-    SCRIPT_GENERATION = "script_generation"  # v1.6: 编导分镜脚本（融合原 copy_fusion+storyboard+review）
+    COPY_FUSION = "copy_fusion"
+    STORYBOARD = "storyboard"
    REVIEW = "review"
    TTS = "tts"
-    RENDERING = "rendering"  # v1.6: 单次 Seedance 生成（BGM/音效/画面一次出片）
+    BGM_SELECT = "bgm_select"
+    RENDERING = "rendering"
+    MUSETALK = "musetalk"
    UPLOADING = "uploading"


 class FusionLevel(StrEnum):
+    """文案融合级别。"""
+
    AI_FULL = "ai_full"
    AI_POLISH = "ai_polish"
    USER_PRIMARY = "user_primary"


 class StyleStrength(StrEnum):
+    """风格强度。"""
+
    LIGHT = "light"
    MEDIUM = "medium"
    STRICT = "strict"


 class PromptType(StrEnum):
+    """Prompt 模板类型（与 #2040 seed 对齐）。"""
+
    IMAGE_ANALYSIS = "image_analysis"
    INTENT_PARSING = "intent_parsing"
-    SCRIPT_GENERATION = "script_generation"
+    COPY_FUSION = "copy_fusion"
+    STORYBOARD = "storyboard"
    REVIEW = "review"
    VIDEO_STYLE_INTEGRATION = "video_style_integration"
    STYLE_CONSTRAINT = "style_constraint"
@@ -75,17 +86,20 @@ STAGE_LABELS = {
    ViralVideoStage.IMAGE_ANALYSIS: "图片分析",
    ViralVideoStage.VIDEO_ANALYSIS: "视频风格分析",
    ViralVideoStage.INTENT_PARSING: "意图解析",
-    ViralVideoStage.SCRIPT_GENERATION: "编导脚本生成",
+    ViralVideoStage.COPY_FUSION: "文案融合",
+    ViralVideoStage.STORYBOARD: "分镜脚本",
    ViralVideoStage.REVIEW: "合规审核",
    ViralVideoStage.TTS: "AI 配音",
-    ViralVideoStage.RENDERING: "视频生成",
+    ViralVideoStage.BGM_SELECT: "BGM 选择",
+    ViralVideoStage.RENDERING: "视频渲染",
+    ViralVideoStage.MUSETALK: "数字人口型",
    ViralVideoStage.UPLOADING: "上传发布",
 }


@dataclass
 class ViralVideoJob:
-    """爆款视频任务领域实体（v1.6 单次 Seedance 出片版）。"""
+    """爆款视频任务领域实体。"""

    user_id: str
    images: list[str] = field(default_factory=list)
@@ -95,31 +109,21 @@ class ViralVideoJob:
    viral_structure: str = ""
    marketing_purpose: str = ""
    bgm_preference: str = ""
-    duration: int = 15  # v1.6: 默认15秒，上限30秒（Seedance 2.5 单次最大30s）
+    duration: int = 30
    user_copy_text: str = ""
    fusion_level: str = FusionLevel.AI_POLISH
    reference_audio_path: str = ""
+    # v1.3
    reference_video_url: str = ""
    style_strength: str = StyleStrength.MEDIUM
    style_guide: dict | None = None
    style_template_id: str = ""
-    # v1.5.1 音频/视频参数
-    voice_id: str = ""
-    voice_source: str = ""
-    video_ratio: str = "9:16"
-    video_model: str = ""
-    # v1.4+ 产物
+    # v1.4 图片分析结果（run_pipeline 持久化，resume 时读取给文案/分镜）
    image_analysis: dict | None = None
-    intent_result: dict | None = None
-    generated_copy_text: str = ""  # v1.6: 存 voiceover_script（纯口播对白），字段名兼容
-    storyboard: list | None = None  # v1.6: 存 copy_result.shots，字段名兼容
-    copy_result: dict | None = None  # v1.6: 完整编导脚本结构
    # 状态
    id: str = field(default_factory=lambda: uuid4().hex)
    status: ViralVideoStatus = ViralVideoStatus.PENDING
-    current_stage: str = ""  # 细粒度阶段（ViralVideoStage.value，snake_case）
-    phase_message: str = ""  # 阶段中文提示文案，前端轮询直接展示
-    heartbeat_at: datetime | None = None  # worker 心跳时间，用于超时僵尸任务检测
+    intent_result: dict | None = None
    result_video_url: str = ""
    credits_cost: int = 0
    error_msg: str = ""
@@ -129,54 +133,13 @@ class ViralVideoJob:
    created_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
    updated_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))

-    # -- 状态转换 --
+    # ── 状态转换 ──

    def mark_running(self) -> None:
-        if self.status not in (
-            ViralVideoStatus.PENDING,
-            ViralVideoStatus.IMAGE_ANALYZED,
-            ViralVideoStatus.COPY_GENERATED,
-            ViralVideoStatus.WAIT_USER_CONFIRM,
-            ViralVideoStatus.RUNNING,
-        ):
+        if self.status not in (ViralVideoStatus.PENDING, ViralVideoStatus.RUNNING):
            raise ValueError(f"Cannot transition from {self.status} to running")
        self.status = ViralVideoStatus.RUNNING
-        now = datetime.now(timezone.utc)
-        if self.started_at is None:
-            self.started_at = now
-        self.heartbeat_at = now
-        self.updated_at = now
-
-    def touch_heartbeat(self) -> None:
-        """更新心跳时间（worker 在长任务中周期性调用，用于超时检测）。"""
-        now = datetime.now(timezone.utc)
-        if self.started_at is None:
-            self.started_at = now
-        self.heartbeat_at = now
-        self.updated_at = now
-
-    def mark_image_analyzed(self) -> None:
-        if self.status not in (ViralVideoStatus.PENDING, ViralVideoStatus.RUNNING):
-            raise ValueError(f"Cannot transition from {self.status} to image_analyzed")
-        self.status = ViralVideoStatus.IMAGE_ANALYZED
-        if self.started_at is None:
-            self.started_at = datetime.now(timezone.utc)
-        self.updated_at = datetime.now(timezone.utc)
-
-    def mark_copy_generated(self, copy_result: dict) -> None:
-        """v1.6 阶段2完成：编导脚本（含 voiceover_script/shots/硬约束/负面词）已生成。"""
-        if self.status not in (
-            ViralVideoStatus.IMAGE_ANALYZED,
-            ViralVideoStatus.RUNNING,
-            ViralVideoStatus.PENDING,
-        ):
-            raise ValueError(f"Cannot transition from {self.status} to copy_generated")
-        self.status = ViralVideoStatus.COPY_GENERATED
-        self.copy_result = copy_result or {}
-        if isinstance(copy_result, dict):
-            self.generated_copy_text = copy_result.get("voiceover_script", "") or ""
-            shots = copy_result.get("shots") or []
-            self.storyboard = list(shots) if isinstance(shots, list) else []
+        self.started_at = datetime.now(timezone.utc)
        self.updated_at = datetime.now(timezone.utc)

    def mark_wait_user_confirm(self, intent_result: dict) -> None:
@@ -186,25 +149,6 @@ class ViralVideoJob:
        self.intent_result = intent_result
        self.updated_at = datetime.now(timezone.utc)

-    def resume_from_image_analyzed(self, **kwargs) -> None:
-        if self.status not in (ViralVideoStatus.IMAGE_ANALYZED, ViralVideoStatus.PENDING):
-            raise ValueError(f"Cannot resume from {self.status} to copy-gen")
-        for k, v in kwargs.items():
-            if hasattr(self, k) and v not in (None, "", []):
-                setattr(self, k, v)
-        self.status = ViralVideoStatus.RUNNING
-        self.updated_at = datetime.now(timezone.utc)
-
-    def resume_from_copy_generated(self, edited_copy: str | None = None) -> None:
-        """阶段2->阶段3：用户确认/编辑口播文案，开始跑 TTS+单次Seedance渲染。"""
-        if self.status != ViralVideoStatus.COPY_GENERATED:
-            raise ValueError(f"Cannot resume from {self.status} to render")
-        if edited_copy and isinstance(self.copy_result, dict):
-            self.copy_result = {**self.copy_result, "voiceover_script": edited_copy}
-            self.generated_copy_text = edited_copy
-        self.status = ViralVideoStatus.RUNNING
-        self.updated_at = datetime.now(timezone.utc)
-
    def resume_from_confirm(self) -> None:
        if self.status != ViralVideoStatus.WAIT_USER_CONFIRM:
            raise ValueError(f"Cannot resume from {self.status}")
@@ -237,14 +181,3 @@ class ViralVideoJob:
            ViralVideoStatus.FAILED,
            ViralVideoStatus.CANCELLED,
        )
-
-    @property
-    def effective_copy_text(self) -> str:
-        """TTS 用的最终口播文案：优先 copy_result.voiceover_script，兼容老字段。"""
-        if isinstance(self.copy_result, dict) and self.copy_result.get("voiceover_script"):
-            return self.copy_result["voiceover_script"]
-        return self.generated_copy_text or self.user_copy_text or "你好，给大家推荐一款好物"
-
-    @property
-    def voiceover_script(self) -> str:
-        return self.effective_copy_text
@@ -40,8 +40,6 @@ class DoubaoClient:
        self.timeout: int = settings.doubao_timeout
        self.max_retries: int = settings.doubao_max_retries
        self.vision_model: str = settings.doubao_vision_model
-        self.vision_lite_model: str = settings.doubao_vision_lite_model
-        self.fast_model: str = settings.doubao_fast_model

    def embed_text(self, text: str, timeout: int | None = None) -> list[float] | None:
        """调用豆包文本 Embedding API，返回浮点向量；失败返回 None。"""
@@ -94,7 +92,6 @@ class DoubaoClient:
        messages: list[dict[str, str]],
        temperature: float = 0.7,
        max_tokens: int = 1024,
-        model: str | None = None,
    ) -> Optional[str]:
        """调用 Chat Completion 接口.

@@ -115,7 +112,7 @@ class DoubaoClient:
            "Content-Type": "application/json",
        }
        payload: dict[str, Any] = {
-            "model": model or self.model,
+            "model": self.model,
            "messages": messages,
            "temperature": temperature,
            "max_tokens": max_tokens,
@@ -157,12 +154,11 @@ class DoubaoClient:
        max_tokens: int = 2048,
        temperature: float = 0.3,
        timeout: int | None = None,
-        model: str | None = None,
    ) -> Optional[str]:
        """调用豆包视觉理解 API（OpenAI 兼容多模态格式）.

        将 images 附加到最后一条 user message 的 content 中，
-        使用 vision_model（默认 doubao-1-5-vision-pro-250328）。
+        使用 vision_model（默认 doubao-1-5-vision-pro-250915）。

        Args:
            messages: 对话消息列表。最后一条 user message 会被注入图片内容。
@@ -208,7 +204,7 @@ class DoubaoClient:
            "Content-Type": "application/json",
        }
        payload: dict[str, Any] = {
-            "model": model or self.vision_model,
+            "model": self.vision_model,
            "messages": vision_messages,
            "temperature": temperature,
            "max_tokens": max_tokens,
@@ -254,21 +250,24 @@ class DoubaoClient:
        duration: int = 5,
        ratio: str | None = "9:16",
        resolution: str = "720p",
-        generate_audio: bool = True,
+        generate_audio: bool = False,
        watermark: bool = False,
        output_dir: str | None = None,
-        model: str | None = None,
-        reference_images: list[str] | None = None,
-        reference_audios: list[str] | None = None,
-        reference_videos: list[str] | None = None,
    ) -> str | None:
-        """调用 Seedance 2.5 生视频（异步任务→轮询→下载），返回本地 MP4 路径；失败返回 None。
+        """调用 Seedance 2.5 文生/图生视频（异步任务→轮询→下载），返回本地 MP4 路径；失败返回 None。

-        【v1.6.1 修复】严格按官方 content 数组协议构造请求：
-        - 所有参考（图/音/视）必须放进 content 数组并带 role 字段，不能放顶层 reference_audios/reference_videos（非官方字段，会被忽略或导致异常）。
-        - 首帧图（first_frame 模式）Seedance 2.5 强制 ratio=adaptive；走 omni_reference（参考生视频）模式时才能指定 9:16/1:1 等具体比例。
-          判定：传了参考音频/视频或 ≥1 张多参考图时，走 omni_reference（首张图 role=reference_image）；纯首帧无参考时走 first_frame（ratio 强制 adaptive）。
-        - 创建任务若因 ratio 报错（HTTP 400），自动回退到 ratio=adaptive 重试一次。
+        Args:
+            prompt: 文本提示词
+            image_url: 首帧参考图 URL（可选，提供则走图生视频）
+            duration: 视频时长 2~30 秒，默认 5
+            ratio: 宽高比 16:9/9:16/1:1/4:3/3:4/21:9/adaptive
+            resolution: 480p/720p/1080p
+            generate_audio: 是否生成模型自带音效（默认 False，我们自己混 TTS）
+            watermark: 是否加水印
+            output_dir: 下载目录，默认 /tmp
+
+        Returns:
+            本地 MP4 文件路径，失败返回 None。
        """
        if not self.is_available:
            return None
@@ -277,58 +276,24 @@ class DoubaoClient:

        settings = get_shared_settings()
        poll_interval = getattr(settings, "doubao_video_poll_interval", 10) or 10
-        # 收紧总超时：轮询 8min + 下载 2min = 最长 ~10min，防止出现 20min 卡死
-        total_timeout = getattr(settings, "doubao_video_timeout", 480) or 480
-        default_video_model = getattr(settings, "doubao_video_model", None) or "doubao-seedance-2-5-260628"
-        video_model = model or default_video_model
+        total_timeout = getattr(settings, "doubao_video_timeout", 600) or 600
+        video_model = getattr(settings, "doubao_video_model", None) or "doubao-seedance-2-5-260628"

-        ref_audios = [u for u in (reference_audios or [])[:10] if u and isinstance(u, str)]
-        ref_videos = [u for u in (reference_videos or [])[:3] if u and isinstance(u, str)]
-        ref_imgs = [u for u in (reference_images or [])[:9] if u and isinstance(u, str)]
-
-        # 判断任务模式：有参考音/视/多图 → omni_reference（支持指定 ratio）；纯首帧 → first_frame（ratio=adaptive）
-        has_extra_refs = bool(ref_audios or ref_videos or ref_imgs)
-        is_first_frame_mode = bool(image_url) and not has_extra_refs
-        # 最终 ratio：first_frame 模式强制 adaptive，否则按用户传值（默认 9:16）
-        final_ratio = "adaptive" if is_first_frame_mode else (ratio or "9:16")
-
-        # 构造 content 数组：text + 图 + 音 + 视
        content: list[dict[str, Any]] = [{"type": "text", "text": prompt.strip()}]
        if image_url:
-            if has_extra_refs:
-                # omni_reference：首张图作为 reference_image，允许指定 ratio
-                content.append(
-                    {
-                        "type": "image_url",
-                        "image_url": {"url": image_url},
-                        "role": "reference_image",
-                    }
-                )
-            else:
-                # 纯首帧：不带 role，服务端识别为 first_frame（或显式 role=first_frame）
-                content.append(
-                    {
-                        "type": "image_url",
-                        "image_url": {"url": image_url},
-                        "role": "first_frame",
-                    }
-                )
-        for u in ref_imgs:
-            content.append({"type": "image_url", "image_url": {"url": u}, "role": "reference_image"})
-        for u in ref_audios:
-            content.append({"type": "audio_url", "audio_url": {"url": u}, "role": "reference_audio"})
-        for u in ref_videos:
-            content.append({"type": "video_url", "video_url": {"url": u}, "role": "reference_video"})
+            content.append({"type": "image_url", "image_url": {"url": image_url}})

        create_payload: dict[str, Any] = {
            "model": video_model,
            "content": content,
-            "generate_audio": bool(generate_audio),
+            "generate_audio": generate_audio,
            "duration": int(duration),
            "resolution": resolution,
-            "watermark": bool(watermark),
-            "ratio": final_ratio,
+            "watermark": watermark,
        }
+        # Bug #2110: ratio=None 时不传（首帧图生视频跟随原图比例，传 ratio 会 400 InvalidParameter）
+        if ratio:
+            create_payload["ratio"] = ratio

        headers = {
            "Authorization": f"Bearer {self.api_key}",
@@ -336,94 +301,69 @@ class DoubaoClient:
        }
        create_url = f"{self.base_url}/contents/generations/tasks"
        logger.info(
-            "Seedance 创建任务: model=%s dur=%ds ratio=%s mode=%s gen_audio=%s img=%d aud=%d vid=%d",
+            "Seedance 创建任务请求: url=%s model=%s duration=%ds ratio=%s gen_audio=%s image_url=%s",
+            create_url,
            video_model,
            duration,
-            final_ratio,
-            "first_frame" if is_first_frame_mode else "omni_ref",
+            ratio or "(follow-image)",
            generate_audio,
-            (1 if image_url else 0) + len(ref_imgs),
-            len(ref_audios),
-            len(ref_videos),
+            bool(image_url),
        )

-        def _do_create(payload: dict) -> tuple[str | None, Exception | None, int, str]:
-            """返回 (task_id, last_err, status_code, body_text)。"""
-            last_err: Exception | None = None
-            for attempt in range(self.max_retries + 1):
+        # 1) 创建任务（带重试）
+        task_id: str | None = None
+        last_error: Exception | None = None
+        for attempt in range(self.max_retries + 1):
+            try:
+                resp = httpx.post(create_url, headers=headers, json=create_payload, timeout=self.timeout)
+                # 测试环境下 MagicMock().status_code 是 MagicMock，与 int 比较会抛 TypeError；
+                # 用显式 int() 转换+类型判断，避免误判。
                try:
-                    resp = httpx.post(create_url, headers=headers, json=payload, timeout=self.timeout)
-                    sc = int(getattr(resp, "status_code", 0) or 0)
-                    body = (getattr(resp, "text", "") or "")[:1500]
-                    if sc >= 400:
-                        logger.error("Seedance 创建任务 HTTP %d: body=%s", sc, body)
-                        try:
-                            resp.raise_for_status()
-                        except Exception as ee:
-                            last_err = ee
-                            if attempt < self.max_retries:
-                                time.sleep(0.5 * (2**attempt))
-                                continue
-                            return None, last_err, sc, body
-                    data = resp.json()
-                    tid = data.get("id")
-                    if tid:
-                        return tid, None, sc, body
-                    last_err = RuntimeError(f"create ok but no id: {str(data)[:300]}")
-                except Exception as e:
-                    last_err = e
-                    if attempt < self.max_retries:
-                        wait = 0.5 * (2**attempt)
-                        logger.warning(
-                            "Seedance 创建任务失败，%.1fs 后重试 (%d/%d): %s",
-                            wait,
-                            attempt + 1,
-                            self.max_retries + 1,
-                            e,
-                        )
-                        time.sleep(wait)
-            return None, last_err, 0, ""
-
-        # 第一次尝试
-        task_id, last_err, sc, body = _do_create(create_payload)
-
-        # ratio 兜底：HTTP 400 且 body 提到 ratio / adaptive → 回退 adaptive 再试一次
-        if (
-            not task_id
-            and sc == 400
-            and final_ratio != "adaptive"
-            and (
-                "ratio" in (body or "").lower()
-                or "aspect" in (body or "").lower()
-                or "adaptive" in (body or "").lower()
-            )
-        ):
-            logger.warning("Seedance 创建因 ratio 失败，回退 ratio=adaptive 重试")
-            create_payload["ratio"] = "adaptive"
-            task_id, last_err, sc2, body2 = _do_create(create_payload)
-
+                    _status = int(resp.status_code)
+                except (TypeError, ValueError):
+                    _status = 200
+                if _status >= 400:
+                    # 把响应体完整打出来（通常含 error.code/message，能直接定位：模型未开通/Key 无权限/模型 ID 错误）
+                    logger.error(
+                        "Seedance 创建任务 HTTP %d: body=%s",
+                        resp.status_code,
+                        (resp.text or "")[:1000],
+                    )
+                resp.raise_for_status()
+                data = resp.json()
+                task_id = data.get("id")
+                if task_id:
+                    break
+                last_error = RuntimeError(f"create task returned no id: {str(data)[:200]}")
+            except Exception as e:
+                last_error = e
+                if attempt < self.max_retries:
+                    wait = 0.5 * (2**attempt)
+                    logger.warning(
+                        "Seedance 创建任务失败，%.1fs 后重试 (%d/%d): %s", wait, attempt + 1, self.max_retries + 1, e
+                    )
+                    time.sleep(wait)
        if not task_id:
            logger.error(
-                "Seedance 创建任务最终失败: model=%s base_url=%s err=%s body=%s  【排查】"
-                "1) 方舟控制台已开通 doubao-seedance-2-5-260628；2) API Key 有该模型权限；"
-                "3) DOUBAO_BASE_URL=https://ark.cn-beijing.volces.com/api/v3；4) 参考素材 URL 公网可访问。",
+                "Seedance 创建任务最终失败: model=%s base_url=%s err=%s  【排查建议】"
+                "1) 确认方舟控制台已开通 Doubao-Seedance-2.5 模型；"
+                "2) DOUBAO_API_KEY 对应的账号有该模型调用权限；"
+                "3) DOUBAO_BASE_URL 必须为 https://ark.cn-beijing.volces.com/api/v3；"
+                "4) 若控制台用「推理接入点」(endpoint)，请把 DOUBAO_VIDEO_MODEL 改为 ep-xxx 接入点 ID。",
                video_model,
                self.base_url,
-                last_err,
-                (body or "")[:500],
+                last_error,
            )
            return None

-        logger.info("Seedance 任务已创建: task_id=%s ratio=%s", task_id, create_payload["ratio"])
+        logger.info("Seedance 任务已创建: task_id=%s model=%s duration=%ds", task_id, video_model, duration)

        # 2) 轮询状态
        poll_url = f"{create_url}/{task_id}"
        deadline = time.time() + total_timeout
        video_url: str | None = None
        last_status: str = "queued"
-        poll_count = 0
        while time.time() < deadline:
-            poll_count += 1
            try:
                resp = httpx.get(poll_url, headers=headers, timeout=self.timeout)
                try:
@@ -438,71 +378,48 @@ class DoubaoClient:
                    content_obj = data.get("content") or {}
                    video_url = content_obj.get("video_url")
                    if video_url:
-                        logger.info("Seedance 任务成功: task_id=%s polls=%d", task_id, poll_count)
                        break
-                    last_err = RuntimeError(f"task succeeded but no video_url: {str(data)[:300]}")
-                    logger.error("Seedance succeeded 但无 video_url: %s", last_err)
+                    last_error = RuntimeError(f"task succeeded but no video_url: {str(data)[:300]}")
                    break
                if status == "failed":
                    err = data.get("error") or {}
-                    last_err = RuntimeError(f"task failed: code={err.get('code','')} msg={err.get('message','')}")
-                    logger.error("Seedance 任务失败 task_id=%s: %s", task_id, last_err)
+                    last_error = RuntimeError(f"task failed: {err.get('code','')} {err.get('message','')}")
                    break
                if status in ("expired", "cancelled"):
-                    last_err = RuntimeError(f"task {status}")
-                    logger.error("Seedance 任务 %s: task_id=%s", status, task_id)
+                    last_error = RuntimeError(f"task {status}")
                    break
-                # 每 5 次轮询打一次 info 日志，便于观察进度
-                if poll_count % 5 == 0:
-                    logger.info("Seedance 轮询中: task_id=%s status=%s polls=%d", task_id, status, poll_count)
+                # queued / running: 继续轮询
            except httpx.HTTPStatusError as e:
-                last_err = e
-                logger.warning("Seedance 轮询 HTTP %d: %s", e.response.status_code, (e.response.text or "")[:300])
+                last_error = e
+                logger.warning(
+                    "Seedance 轮询 HTTP %d: body=%s",
+                    e.response.status_code,
+                    (e.response.text or "")[:500],
+                )
            except Exception as e:
-                last_err = e
+                last_error = e
                logger.debug("Seedance 轮询异常: %s", e)
            time.sleep(poll_interval)

        if not video_url:
-            logger.error(
-                "Seedance 任务未成功: task_id=%s last_status=%s polls=%d err=%s (总等待 %.0fs)",
-                task_id,
-                last_status,
-                poll_count,
-                last_err,
-                total_timeout,
-            )
+            logger.error("Seedance 任务未成功: task_id=%s status=%s err=%s", task_id, last_status, last_error)
            return None

-        # 3) 下载到本地（下载超时收紧到 120s）
+        # 3) 下载到本地
        try:
            out_dir = output_dir or "/tmp"
            os.makedirs(out_dir, exist_ok=True)
            local_path = f"{out_dir}/seedance_{task_id}_{uuid.uuid4().hex[:8]}.mp4"
-            download_timeout = 120.0
-            logger.info(
-                "Seedance 开始下载: task_id=%s url=%s timeout=%.0fs", task_id, video_url[:120], download_timeout
-            )
-            with httpx.stream("GET", video_url, timeout=download_timeout) as r:
+            with httpx.stream("GET", video_url, timeout=300) as r:
                r.raise_for_status()
-                downloaded = 0
                with open(local_path, "wb") as f:
                    for chunk in r.iter_bytes(chunk_size=1024 * 256):
                        if chunk:
                            f.write(chunk)
-                            downloaded += len(chunk)
-            size = os.path.getsize(local_path)
-            logger.info("Seedance 视频下载完成: %s size=%d bytes", local_path, size)
-            if size == 0:
-                logger.error("Seedance 下载文件大小为 0")
-                try:
-                    os.remove(local_path)
-                except Exception:
-                    pass
-                return None
+            logger.info("Seedance 视频下载完成: %s (%d bytes)", local_path, os.path.getsize(local_path))
            return local_path
        except Exception as e:
-            logger.error("Seedance 视频下载失败: %s", e, exc_info=True)
+            logger.error("Seedance 视频下载失败: %s", e)
            return None


@@ -496,32 +496,16 @@ def run_generate_cover(
 # ── 通用 LLM / Vision 调用（#2039 ViralVideoOrchestrator 使用，复用现有豆包客户端）──


-def call_llm(
-    prompt: str,
-    temperature: float = 0.7,
-    max_tokens: int = 2048,
-    model: str | None = None,
-    system_prompt: str | None = None,
-) -> object:
-    """调用豆包大模型（文本对话），返回解析后的 JSON（dict/list）或原文字符串；失败返回 None。
-
-    Args:
-        prompt: 用户侧提示。
-        temperature: 采样温度。
-        max_tokens: 输出上限（结构化任务默认 2048，长文案可按需加大）。
-        model: 覆盖默认模型（如 fast_model 提速用），None 走配置默认推理模型。
-        system_prompt: 覆盖默认 system prompt。
-    """
+def call_llm(prompt: str, temperature: float = 0.7) -> object:
+    """调用豆包大模型（文本对话），返回解析后的 JSON（dict/list）或原文字符串；失败返回 None。"""
    client = get_doubao_client()
    if not client.is_available:
        return None
-    if system_prompt is None:
-        system_prompt = "你是专业的短视频内容策划助手。需要结构化输出时请严格使用 JSON。"
    messages = [
-        {"role": "system", "content": system_prompt},
+        {"role": "system", "content": "你是专业的短视频内容策划助手。需要结构化输出时请严格使用 JSON。"},
        {"role": "user", "content": prompt},
    ]
-    raw = client.chat_completion(messages, temperature=temperature, max_tokens=max_tokens, model=model)
+    raw = client.chat_completion(messages, temperature=temperature, max_tokens=4096)
    if raw is None:
        return None
    try:
@@ -530,26 +514,14 @@ def call_llm(
        return raw


-def call_vision(
-    image_url: str,
-    prompt: str,
-    *,
-    model: str | None = None,
-    max_tokens: int = 1024,
-    temperature: float = 0.2,
-    timeout: int = 45,
-    system_prompt: str | None = None,
-) -> object:
+def call_vision(image_url: str, prompt: str) -> object:
    """调用豆包视觉大模型分析图片，返回解析后的 JSON 或原文字符串；失败返回 None。

-    Args:
-        image_url: 可公网访问的图片 URL（直接传给豆包视觉模型，无需本地下载）。
-        prompt: 用户侧文本提示。
-        model: 覆盖默认视觉模型（如 vision_lite_model 提速用），None 走配置默认。
-        max_tokens: 输出上限，商品识别用 800~1200 足够，避免长输出拖慢首 token。
-        temperature: 温度。
-        timeout: 单次请求超时（秒）。
-        system_prompt: 覆盖默认 system prompt（viral-video 商品分析会传专门的详细 prompt）。
+    Bug #2114 (VLM 牛头不对马嘴根因修复):
+    之前误走 client.chat_completion(用文本模型 doubao-seed-1.6)，多模态 content list 被当成
+    纯文本发给文本模型 → 模型要么看不到图、要么抛 400，静默被 except 吞掉 → 返回 None →
+    _step_image_analysis fallback 到 {"name":"未识别"} → 后续文案/分镜完全没图的信息。
+    现改走 vision_completion，走视觉模型 doubao-1-5-vision-pro-250915。
    """
    client = get_doubao_client()
    if not client.is_available:
@@ -559,33 +531,28 @@ def call_vision(
        logger.warning("[call_vision] 空 image_url，跳过视觉分析")
        return None

-    if system_prompt is None:
-        system_prompt = (
-            "你是资深电商视觉分析师。请严格基于用户提供的图片观察回答，"
-            "图片里没有的信息不要凭空想象或编造；看不清或无法判断时明确说"
-            "「无法判断」，不要猜测。输出必须是严格 JSON，不要附加 Markdown 或解释文字。"
-        )
+    system_prompt = (
+        "你是资深电商视觉分析师。请严格基于用户提供的图片观察回答，"
+        "图片里没有的信息不要凭空想象或编造；看不清或无法判断时明确说"
+        "「图片中无法判断」，不要猜测。输出必须是严格 JSON，不要附加 Markdown 或解释文字。"
+    )
    messages = [
        {"role": "system", "content": system_prompt},
        {"role": "user", "content": prompt},
    ]

-    used_model = model or getattr(client, "vision_model", "?")
    logger.info(
-        "[call_vision] 调用豆包视觉模型 model=%s image_url=%s prompt_len=%d max_tokens=%d timeout=%d",
-        used_model,
+        "[call_vision] 调用豆包视觉模型 vision_model=%s image_url=%s prompt_len=%d",
+        getattr(client, "vision_model", "?"),
        image_url[:120],
        len(prompt),
-        max_tokens,
-        timeout,
    )
    raw = client.vision_completion(
        messages=messages,
        images=[image_url],
-        temperature=temperature,
-        max_tokens=max_tokens,
-        timeout=timeout,
-        model=model,
+        temperature=0.2,
+        max_tokens=2048,
+        timeout=60,
    )
    if raw is None:
        logger.warning("[call_vision] 视觉模型返回 None (image_url=%s)", image_url[:80])
@@ -608,43 +575,32 @@ def call_video_generation(
    prompt: str,
    *,
    image_url: str | None = None,
-    duration: int = 15,
+    duration: int = 5,
    ratio: str | None = "9:16",
    resolution: str = "720p",
    output_dir: str | None = None,
-    model: str | None = None,
-    generate_audio: bool = True,
-    reference_images: list[str] | None = None,
-    reference_audios: list[str] | None = None,
-    reference_videos: list[str] | None = None,
 ) -> str | None:
-    """调用 Seedance 2.5 生成视频（v1.6.1 单次出片版），返回本地 MP4 路径；失败返回 None。
+    """调用 Seedance 2.5 生成视频段，返回本地 MP4 路径；失败返回 None。

-    v1.6.1 关键约束（避免 20min 卡死）：
-    - 参考音频/视频/多图全部放进 content 数组并带 role=reference_audio/reference_video/reference_image；
-    - 纯首帧无参考时（first_frame 模式），Seedance 2.5 强制 ratio=adaptive；
-      传了参考音/视/多图时走 omni_reference 模式，ratio 可指定为 9:16（客户端内部自动判断）。
-    - ratio 默认 9:16（竖屏），客户端会根据是否有参考自动在 first_frame/adaptive 与 omni/9:16 间切换；
-      若创建任务因 ratio 报错（HTTP 400），客户端会自动回退到 adaptive 再试一次。
+    封装 ai_client.video_generation：提交异步任务→轮询→下载到本地。
+    Bug #2110: 首帧参考图模式下不传 ratio（API 要求跟随首帧图比例，传 ratio=9:16
+    会返回 400 InvalidParameter）。
    """
    client = get_doubao_client()
    if not client.is_available:
        logger.warning("[ai_service] 豆包客户端未配置，跳过视频生成")
        return None
-    effective_ratio = ratio or "9:16"
+    # 首帧模式：不强制 ratio，让模型跟随首帧图比例
+    effective_ratio = None if image_url else ratio
    try:
        kwargs: dict = dict(
            prompt=prompt,
            image_url=image_url,
-            duration=int(duration),
+            duration=duration,
            resolution=resolution,
-            generate_audio=bool(generate_audio),
+            generate_audio=False,  # 我们自己混 TTS
            watermark=False,
            output_dir=output_dir,
-            model=model,
-            reference_images=reference_images,
-            reference_audios=reference_audios,
-            reference_videos=reference_videos,
        )
        if effective_ratio:
            kwargs["ratio"] = effective_ratio
@@ -368,21 +368,6 @@ fi

 echo "All images pulled."

-# ====== 打稳定 tag（:dev），供 Watchtower 监控 ======
-# Watchtower 只能检测同一个 tag 的 digest 变化。
-# commit SHA tag 每次构建都不同，Watchtower 无法感知更新。
-# 因此每次部署都将最新镜像 tag 为 :dev，容器统一使用 :dev 启动。
-DEV_API="${REGISTRY}/xiaoxia-saas-api:dev"
-DEV_WORKER="${REGISTRY}/xiaoxia-saas-worker:dev"
-DEV_WEB="${REGISTRY}/xiaoxia-saas-web:dev"
-docker tag "$REGISTRY_API" "$DEV_API"
-docker tag "$REGISTRY_WORKER" "$DEV_WORKER"
-docker tag "$REGISTRY_WEB" "$DEV_WEB"
-echo "✅ Tagged images as :dev for Watchtower monitoring"
-echo "  API:    $DEV_API"
-echo "  Worker: $DEV_WORKER"
-echo "  Web:    $DEV_WEB"
-
 # ====== 镜像内容校验 ======
 echo ""
 echo "=========================================="
@@ -548,7 +533,7 @@ docker run -d \
  --health-retries 3 \
  --health-start-period 40s \
  $LOG_OPTS \
-  "$DEV_API" &
+  "$REGISTRY_API" &
 PID_API_START=$!

 # ── Worker: 通过 compose 启动（单一事实来源）──
@@ -556,7 +541,7 @@ PID_API_START=$!
 # healthcheck 匹配 'celery.*worker'（不把 beat 算活）、资源限制 4C/8G。
 # WORKER_IMAGE 通过环境变量覆盖镜像 tag（compose.yml 默认 :dev）。
 echo "Starting worker via docker compose (from $INFRA_DOCKER_DIR)..."
-WORKER_IMAGE="$DEV_WORKER" APP_VERSION="$IMAGE_TAG" compose up -d --no-deps worker &
+WORKER_IMAGE="$REGISTRY_WORKER" APP_VERSION="$IMAGE_TAG" compose up -d --no-deps worker &
 PID_WORKER_START=$!

 # ── Web: 暂保留 docker run（TODO: 后续收敛到 compose）──
@@ -572,7 +557,7 @@ docker run -d \
  --health-timeout 5s \
  --health-retries 3 \
  $LOG_OPTS \
-  "$DEV_WEB" &
+  "$REGISTRY_WEB" &
 PID_WEB_START=$!

 wait $PID_API_START $PID_WORKER_START $PID_WEB_START
@@ -703,5 +688,5 @@ echo "=== Staging deployment complete ==="
 echo "API:      http://127.0.0.1:8000"
 echo "Web:      http://127.0.0.1:3001"
 echo "Worker:   managed by docker compose (project=$COMPOSE_PROJECT)"
-echo "Version:  $IMAGE_TAG (running as :dev for Watchtower)"
+echo "Version:  $IMAGE_TAG"
 docker ps --format "table {{.Names}}\t{{.Status}}\t{{.Image}}" | grep staging
@@ -57,7 +57,7 @@ if [ "$TARGET_ENV" = "staging" ]; then
 fi

 # 共用 secrets 直接导出（如果存在）
-SHARED_SECRETS="OSS_ACCESS_KEY_ID OSS_ACCESS_KEY_SECRET COSYVOICE_API_KEY DASHSCOPE_API_KEY MEDIAKIT_API_KEY DOUBAO_API_KEY DOUBAO_MODEL DOUBAO_FAST_MODEL DOUBAO_BASE_URL DOUBAO_VISION_MODEL DOUBAO_VISION_LITE_MODEL DOUBAO_VISION_USE_LITE WECHAT_APP_ID WECHAT_APP_SECRET TIKHUB_API_KEY APIZERO_API_KEY GPU_WORKER_TOKEN"
+SHARED_SECRETS="OSS_ACCESS_KEY_ID OSS_ACCESS_KEY_SECRET COSYVOICE_API_KEY DASHSCOPE_API_KEY MEDIAKIT_API_KEY DOUBAO_API_KEY DOUBAO_MODEL DOUBAO_BASE_URL DOUBAO_VISION_MODEL WECHAT_APP_ID WECHAT_APP_SECRET TIKHUB_API_KEY APIZERO_API_KEY GPU_WORKER_TOKEN"
 for var in $SHARED_SECRETS; do
  value="${!var:-}"
  # 已经在环境中了，无需额外操作
@@ -14,13 +14,10 @@ from packages.shared.ai_client import DoubaoClient
 class _FakeSettings:
    doubao_api_key = "test-key"
    doubao_model = "test-model"
-    doubao_fast_model = "test-fast-model"
    doubao_base_url = "https://ark.cn-beijing.volces.com/api/v3"
    doubao_timeout = 10
    doubao_max_retries = 0
    doubao_vision_model = "test-vision"
-    doubao_vision_lite_model = "test-vision-lite"
-    doubao_vision_use_lite = False
    doubao_embedding_model = "test-embedding"


@@ -44,7 +44,7 @@ class TestCheckDatabase:
        assert result["type"] == "postgresql"
        assert result["message"] == "Database connection successful"
        mock_psycopg.connect.assert_called_once_with(
-            "postgresql://test:test@localhost/test", connect_timeout=3
+            "postgresql+psycopg://test:test@localhost/test", connect_timeout=3
        )
        mock_cur.execute.assert_called_once_with("SELECT 1")
        mock_conn.close.assert_called_once()
@@ -96,7 +96,7 @@ class TestCheckMigrations:
        assert result["status"] == "healthy"
        assert result["message"] == "Database migrations applied"
        mock_psycopg.connect.assert_called_once_with(
-            "postgresql://test:test@localhost/test", connect_timeout=3
+            "postgresql+psycopg://test:test@localhost/test", connect_timeout=3
        )
        mock_conn.close.assert_called_once()

@@ -120,7 +120,7 @@ class TestViralVideoJobDefaults:
        job = ViralVideoJob(user_id="u1")
        assert job.images == []
        assert job.industry == ""
-        assert job.duration == 15
+        assert job.duration == 30
        assert job.fusion_level == FusionLevel.AI_POLISH
        assert job.style_strength == StyleStrength.MEDIUM
        assert job.status == ViralVideoStatus.PENDING
@@ -145,10 +145,13 @@ class TestViralVideoStage:
            "image_analysis",
            "video_analysis",
            "intent_parsing",
-            "script_generation",
+            "copy_fusion",
+            "storyboard",
            "review",
            "tts",
+            "bgm_select",
            "rendering",
+            "musetalk",
            "uploading",
        ]
        actual_order = [s.value for s in ViralVideoStage]
@@ -168,7 +171,7 @@ class TestViralVideoSchemas:
        assert req.images == ["https://example.com/img.jpg"]
        assert req.fusion_level == "ai_polish"
        assert req.style_strength == "medium"
-        assert req.duration == 15
+        assert req.duration == 30

    def test_create_request_empty_images_raises(self):
        from app.schemas.viral_video import CreateViralVideoRequest
@@ -362,10 +365,9 @@ class TestViralVideoPipeline:
            industry="美妆",
            target_customer="年轻女性",
            marketing_purpose="品牌推广",
-            duration=15,
+            duration=30,
            user_copy_text="这款产品超好用",
            fusion_level="ai_polish",
-            video_ratio="9:16",
        )

    @patch("packages.shared.ai_service.call_vision")
@@ -403,110 +405,63 @@ class TestViralVideoPipeline:
        assert "intent" in result

    @patch("packages.shared.ai_service.call_llm")
-    def test_script_generation_returns_copy_result(self, mock_llm, mock_job):
-        """v1.6: _step_script_generation 返回 dict 形式的 CopyResult，含 voiceover_script + shots。"""
-        from apps.worker.worker_app.tasks.viral_video import _step_script_generation
+    def test_copy_fusion_ai_polish(self, mock_llm, mock_job):
+        from apps.worker.worker_app.tasks.viral_video import _step_copy_fusion

-        mock_llm.return_value = {
-            "overview": {"theme": "口红推荐", "total_duration": 15, "aspect_ratio": "9:16"},
-            "scene_and_lighting": "明亮化妆台，柔和自然光",
-            "shots": [
-                {
-                    "time_range": "0-5秒",
-                    "shot_type_angle_movement": "近景平视，缓慢推镜",
-                    "scene_and_dialogue": "女主微笑展示口红：大家好，今天分享一款口红",
-                    "action_details": "手持口红特写",
-                    "audio_bgm": "轻快流行BGM",
-                    "transition": "硬切",
-                    "reference_image_index": 0,
-                },
-                {
-                    "time_range": "5-15秒",
-                    "shot_type_angle_movement": "特写，固定镜头",
-                    "scene_and_dialogue": "涂抹口红：颜色特别好看很显白",
-                    "action_details": "嘴唇涂抹特写",
-                    "audio_bgm": "轻快BGM继续",
-                    "transition": "结束",
-                    "reference_image_index": 1,
-                },
-            ],
-            "hard_constraints": ["无字幕无水印"],
-            "negative_prompts": ["字幕", "水印"],
-            "voiceover_script": "大家好，今天分享一款口红，颜色特别好看很显白。",
-        }
-        result = _step_script_generation(
-            mock_job, {"intent": "推广口红", "key_messages": [], "tone": "亲切"}, {"products": []}
-        )
-        assert isinstance(result, dict)
-        assert "voiceover_script" in result
-        assert "shots" in result
-        assert isinstance(result["shots"], list)
-        assert len(result["shots"]) == 2
-        assert result["overview"]["total_duration"] == 15
-        # final_copy 必须 = voiceover_script（向后兼容）
-        assert result.get("final_copy") == result["voiceover_script"]
+        mock_llm.return_value = "融合后的文案内容"
+        result = _step_copy_fusion(mock_job, {"intent": "推广"}, {"products": []})
+        assert isinstance(result, str)
+        assert len(result) > 0

    @patch("packages.shared.ai_service.call_llm")
-    def test_script_generation_fallback(self, mock_llm, mock_job):
-        """LLM 返回异常时使用兜底脚本（不会抛错）。"""
-        from apps.worker.worker_app.tasks.viral_video import _fallback_script
+    def test_storyboard_generation(self, mock_llm, mock_job):
+        from apps.worker.worker_app.tasks.viral_video import _step_storyboard

-        result = _fallback_script(mock_job)
-        assert isinstance(result, dict)
-        assert result["voiceover_script"]
-        assert len(result["shots"]) >= 1
+        mock_llm.return_value = [
+            {"order": 0, "type": "product_shot", "duration": 10},
+            {"order": 1, "type": "closing", "duration": 5},
+        ]
+        result = _step_storyboard(mock_job, "测试文案", {})
+        assert isinstance(result, list)
+        assert len(result) == 2

    @patch("packages.shared.ai_service.call_llm")
-    def test_review_pass_v16(self, mock_llm, mock_job):
-        """v1.6 _step_review 接收 copy_result dict。"""
+    def test_review_pass(self, mock_llm, mock_job):
        from apps.worker.worker_app.tasks.viral_video import _step_review

        mock_llm.return_value = {"passed": True, "score": 90, "details": {}}
-        cr = {"voiceover_script": "大家好", "shots": []}
-        result = _step_review(mock_job, cr)
+        result = _step_review(mock_job, "测试文案", [])
        assert result["passed"] is True

-    def test_assemble_seedance_prompt(self, mock_job):
-        """编导脚本必须能拼出完整的 Seedance prompt，含总览/场景/逐镜头/约束。"""
-        from apps.worker.worker_app.tasks.viral_video import _assemble_seedance_prompt
+    def test_bgm_select(self, mock_job):
+        from apps.worker.worker_app.tasks.viral_video import _step_bgm_select

-        cr = {
-            "overview": {"theme": "口红", "total_duration": 15, "aspect_ratio": "9:16"},
-            "scene_and_lighting": "明亮化妆台",
-            "shots": [
-                {
-                    "time_range": "0-15秒",
-                    "shot_type_angle_movement": "中景平视",
-                    "scene_and_dialogue": "你好分享",
-                    "action_details": "展示",
-                    "audio_bgm": "BGM",
-                    "transition": "结束",
-                    "reference_image_index": 0,
-                }
-            ],
-            "hard_constraints": ["无字幕"],
-            "negative_prompts": ["水印"],
-        }
-        prompt = _assemble_seedance_prompt(cr, mock_job)
-        assert "【视频总览】" in prompt
-        assert "【逐镜头时间轴】" in prompt
-        assert "【硬性约束】" in prompt
-        assert "【负面提示词】" in prompt
-        assert "0-15秒" in prompt
+        # P1: BGM 素材未就绪前 _step_bgm_select 统一返回 None（跳过 BGM 混音）
+        mock_job.bgm_preference = "upbeat"
+        bgm = _step_bgm_select(mock_job)
+        assert bgm is None
+
+    def test_bgm_select_default(self, mock_job):
+        from apps.worker.worker_app.tasks.viral_video import _step_bgm_select
+
+        mock_job.bgm_preference = ""
+        bgm = _step_bgm_select(mock_job)
+        assert bgm is None


 # ── 端到端流水线集成测试 ────────────────────────────────────────────────


 class TestPipelineIntegration:
-    """v1.6 流水线端到端集成测试（mock 外部依赖）：TTS+单次 Seedance+上传。"""
+    """流水线端到端集成测试（mock 外部依赖）。"""

    @patch("apps.worker.worker_app.tasks.viral_video._step_upload")
    @patch("apps.worker.worker_app.tasks.viral_video._step_render")
-    @patch("apps.worker.worker_app.tasks.viral_video._upload_tts_to_oss")
+    @patch("apps.worker.worker_app.tasks.viral_video._step_bgm_select")
    @patch("apps.worker.worker_app.tasks.viral_video._step_tts")
    @patch("apps.worker.worker_app.tasks.viral_video._step_review")
-    @patch("apps.worker.worker_app.tasks.viral_video._step_script_generation")
+    @patch("apps.worker.worker_app.tasks.viral_video._step_storyboard")
+    @patch("apps.worker.worker_app.tasks.viral_video._step_copy_fusion")
    @patch("apps.worker.worker_app.tasks.viral_video._step_intent_parsing")
    @patch("apps.worker.worker_app.tasks.viral_video._step_video_analysis")
    @patch("apps.worker.worker_app.tasks.viral_video._step_image_analysis")
@@ -519,46 +474,38 @@ class TestPipelineIntegration:
        mock_img_analysis,
        mock_video_analysis,
        mock_intent,
-        mock_script,
+        mock_copy_fusion,
+        mock_storyboard,
        mock_review,
        mock_tts,
-        mock_tts_upload,
+        mock_bgm,
        mock_render,
        mock_upload,
    ):
-        """v1.6: TTS整段合成 → 上传TTS到OSS → 单次 Seedance → 上传成片。"""
+        """测试 resume 流水线能从确认状态走到完成。"""
        from apps.worker.worker_app.tasks.viral_video import (
            resume_viral_video_pipeline,
        )

+        # 构造 mock job
        job = ViralVideoJob(
            user_id="user-001",
            images=["https://img.com/1.jpg"],
            industry="美妆",
            status=ViralVideoStatus.RUNNING,
            intent_result={"intent": "推广"},
-            duration=15,
-            video_ratio="9:16",
        )

        mock_repo = MagicMock()
        mock_session = MagicMock()
        mock_get_repo.return_value = (mock_session, mock_repo, job)

-        # v1.6: 如果没有 copy_result 会现场补生成
-        mock_intent.return_value = {"intent": "推广", "key_messages": [], "tone": "亲切"}
-        mock_script.return_value = {
-            "overview": {"theme": "口红", "total_duration": 15, "aspect_ratio": "9:16"},
-            "scene_and_lighting": "明亮化妆台",
-            "shots": [],
-            "hard_constraints": [],
-            "negative_prompts": [],
-            "voiceover_script": "大家好，分享一款口红。",
-            "final_copy": "大家好，分享一款口红。",
-        }
+        # 设置各步骤返回值
+        mock_copy_fusion.return_value = "融合文案"
+        mock_storyboard.return_value = [{"order": 0, "duration": 10}]
        mock_review.return_value = {"passed": True, "score": 90}
-        mock_tts.return_value = None  # TTS 失败也能走下去（Seedance generate_audio=True 会自己合成音效）
-        mock_tts_upload.return_value = None
+        mock_tts.return_value = None  # P1: TTS 返回 Path|None，mock 用 None 跳过混音
+        mock_bgm.return_value = None  # P1: BGM 未就绪前返回 None
        mock_render.return_value = "/tmp/video.mp4"
        mock_upload.return_value = "https://oss.example.com/final.mp4"

@@ -67,70 +67,49 @@ class TestImageAnalysisField:
 # ── P0-1: storyboard 规范化 ────────────────────────────────────────


-class TestScriptGenerationV16:
-    """v1.6 编导分镜脚本生成相关纯函数测试。"""
+class TestStoryboardNormalize:
+    def test_normalize_fills_defaults(self):
+        from apps.worker.worker_app.tasks.viral_video import _normalize_storyboard

-    def test_fallback_script_has_required_fields(self, mock_job):
-        from apps.worker.worker_app.tasks.viral_video import _fallback_script
+        raw = [{"order": 0, "description": "镜头一"}]
+        out = _normalize_storyboard(raw, total_duration=10, n_segments=1, copy_text="文案")
+        assert len(out) == 1
+        assert out[0]["duration"] >= 3
+        assert out[0]["ken_burns"] in {"zoom_in", "zoom_out", "pan_left", "pan_right", "static"}
+        assert out[0]["type"] == "product_shot"
+        assert out[0]["text"] == ""

-        out = _fallback_script(mock_job)
-        assert isinstance(out, dict)
-        assert "overview" in out
-        assert "shots" in out
-        assert "voiceover_script" in out
-        assert "hard_constraints" in out
-        assert "negative_prompts" in out
-        assert out["overview"]["total_duration"] == mock_job.duration
-        assert out["final_copy"] == out["voiceover_script"]
-        assert len(out["shots"]) >= 1
+    def test_normalize_scales_to_total_duration(self):
+        from apps.worker.worker_app.tasks.viral_video import _normalize_storyboard

-    def test_safe_json_loads_parses_fenced_code(self):
-        from apps.worker.worker_app.tasks.viral_video import _safe_json_loads
+        raw = [
+            {"order": 0, "duration": 10, "description": "a"},
+            {"order": 1, "duration": 10, "description": "b"},
+        ]
+        out = _normalize_storyboard(raw, total_duration=10, n_segments=2, copy_text="x")
+        total = sum(s["duration"] for s in out)
+        assert total == 10

-        fenced = '```json\n{"voiceover_script": "你好", "shots": []}\n```'
-        out = _safe_json_loads(fenced)
-        assert out is not None
-        assert out["voiceover_script"] == "你好"
+    def test_fallback_storyboard(self):
+        from apps.worker.worker_app.tasks.viral_video import _fallback_storyboard

-    def test_safe_json_loads_handles_none(self):
-        from apps.worker.worker_app.tasks.viral_video import _safe_json_loads
+        out = _fallback_storyboard("文案", total_duration=15, n_segments=3)
+        assert len(out) == 3
+        assert sum(s["duration"] for s in out) == 15
+        assert all(s["duration"] >= 3 for s in out)

-        assert _safe_json_loads(None) is None
-        assert _safe_json_loads("not json") is None
+    def test_storyboard_llm_list(self, mock_job):
+        from apps.worker.worker_app.tasks.viral_video import _step_storyboard

-    def test_validate_normalize_fills_defaults(self, mock_job):
-        from apps.worker.worker_app.tasks.viral_video import _validate_and_normalize_script
-
-        raw = {"voiceover_script": "你好", "shots": [{"scene_and_dialogue": "测试"}]}
-        out = _validate_and_normalize_script(raw, mock_job)
-        assert out["voiceover_script"] == "你好"
-        assert len(out["shots"]) == 1
-        assert out["shots"][0]["shot_type_angle_movement"]
-        assert out["overview"]["total_duration"] == mock_job.duration
-
-    def test_assemble_seedance_prompt_contains_sections(self, mock_job):
-        from apps.worker.worker_app.tasks.viral_video import _assemble_seedance_prompt
-
-        cr = {
-            "overview": {"theme": "测试", "total_duration": 15, "aspect_ratio": "9:16"},
-            "scene_and_lighting": "明亮",
-            "shots": [
-                {
-                    "time_range": "0-15秒",
-                    "shot_type_angle_movement": "中景",
-                    "scene_and_dialogue": "你好",
-                    "action_details": "展示",
-                    "audio_bgm": "BGM",
-                    "transition": "结束",
-                    "reference_image_index": 0,
-                }
-            ],
-            "hard_constraints": ["无字幕"],
-            "negative_prompts": ["水印"],
-        }
-        p = _assemble_seedance_prompt(cr, mock_job)
-        for key in ("【视频总览】", "【场景与光线】", "【逐镜头时间轴】", "【硬性约束】", "【负面提示词】"):
-            assert key in p
+        with patch("packages.shared.ai_service.call_llm") as mock_llm:
+            mock_llm.return_value = [
+                {"order": 0, "description": "产品特写", "duration": 5, "text": "t1"},
+                {"order": 1, "description": "使用场景", "duration": 5, "text": "t2"},
+                {"order": 2, "description": "CTA", "duration": 5, "text": "t3"},
+            ]
+            result = _step_storyboard(mock_job, "文案", {"products": []})
+            assert len(result) == 3
+            assert all("description" in s for s in result)


 # ── P1: TTS 返回 Path|None ────────────────────────────────────────
@@ -171,24 +150,12 @@ class TestTTSPath:
 # ── P1: BGM 跳过 / MuseTalk 无 persona 跳过 ───────────────────────


-class TestDurationClamp:
-    """v1.6 mark_copy_generated 派生字段 + duration clamp。"""
+class TestBGMSkip:
+    def test_bgm_returns_none(self, mock_job):
+        from apps.worker.worker_app.tasks.viral_video import _step_bgm_select

-    def test_mark_copy_generated_derives_fields(self):
-        job = ViralVideoJob(user_id="u1", duration=15)
-        cr = {
-            "overview": {"theme": "x", "total_duration": 15, "aspect_ratio": "9:16"},
-            "scene_and_lighting": "亮",
-            "shots": [{"time_range": "0-15秒", "scene_and_dialogue": "对白"}],
-            "voiceover_script": "你好",
-            "hard_constraints": [],
-            "negative_prompts": [],
-        }
-        job.mark_copy_generated(cr)
-        assert job.copy_result is cr
-        assert job.generated_copy_text == "你好"
-        assert job.storyboard == cr["shots"]
-        assert job.effective_copy_text == "你好"
+        mock_job.bgm_preference = "upbeat"
+        assert _step_bgm_select(mock_job) is None


 # ── P0-1: call_video_generation 参数构造 ──────────────────────────
@@ -221,61 +188,23 @@ class TestCallVideoGeneration:
            assert kwargs["prompt"] == "测试"
            assert kwargs["image_url"] == "https://img/x.jpg"
            assert kwargs["duration"] == 5
-            assert kwargs["generate_audio"] is True


 # ── P0-1: _step_render 占位片段生成 ──────────────────────────────


-class TestCallVideoGenerationV16:
-    """v1.6 call_video_generation 透传 reference_audios/reference_images 等参数到 client。"""
+class TestPlaceholderClip:
+    def test_make_placeholder_clip(self, tmp_path):
+        import shutil

-    def test_passes_reference_params_to_client(self, tmp_path):
-        from packages.shared.ai_service import call_video_generation
+        from apps.worker.worker_app.tasks.viral_video import _make_placeholder_clip, _probe_ok

-        out = tmp_path / "v.mp4"
-        out.write_bytes(b"fake")
-        with patch("packages.shared.ai_service.get_doubao_client") as mock_get:
-            mock_client = MagicMock()
-            mock_client.is_available = True
-            mock_client.video_generation.return_value = str(out)
-            mock_get.return_value = mock_client
-            result = call_video_generation(
-                prompt="测试",
-                image_url="https://img/x.jpg",
-                duration=15,
-                ratio="9:16",
-                reference_images=["https://img/r1.jpg"],
-                reference_audios=["https://oss/tts.mp3"],
-                reference_videos=["https://oss/ref.mp4"],
-                generate_audio=True,
-                model="doubao-seedance-2-5-260628",
-            )
-            assert result == str(out)
-            kwargs = mock_client.video_generation.call_args.kwargs
-            # 图生视频也必须传 ratio（避免首帧方图导致默认输出 1:1）
-            assert kwargs.get("ratio") == "9:16", f"ratio 应透传，got {kwargs.get('ratio')!r}"
-            assert kwargs["image_url"] == "https://img/x.jpg"
-            assert kwargs["reference_audios"] == ["https://oss/tts.mp3"]
-            assert kwargs["reference_images"] == ["https://img/r1.jpg"]
-            assert kwargs["reference_videos"] == ["https://oss/ref.mp4"]
-            assert kwargs["generate_audio"] is True
-            assert kwargs["model"] == "doubao-seedance-2-5-260628"
+        if not shutil.which("ffmpeg"):
+            pytest.skip("ffmpeg not available")

-    def test_ratio_passed_when_no_image(self, tmp_path):
-        from packages.shared.ai_service import call_video_generation
-
-        out = tmp_path / "v.mp4"
-        out.write_bytes(b"fake")
-        with patch("packages.shared.ai_service.get_doubao_client") as mock_get:
-            mock_client = MagicMock()
-            mock_client.is_available = True
-            mock_client.video_generation.return_value = str(out)
-            mock_get.return_value = mock_client
-            call_video_generation(prompt="测试", duration=10, ratio="16:9")
-            kwargs = mock_client.video_generation.call_args.kwargs
-            assert kwargs["ratio"] == "16:9"
-            assert kwargs["image_url"] is None
+        out = _make_placeholder_clip(tmp_path, 0, 3)
+        assert out.exists()
+        assert _probe_ok(str(out))


 # ── P0-1: DoubaoClient.video_generation 在不可用时返回 None ───────
@@ -295,15 +224,10 @@ class TestDoubaoClientVideoGen:

 class TestResumeReadsImageAnalysis:
    def test_resume_uses_persisted_image_analysis(self):
-        """resume/render pipeline 应从 job.image_analysis 读（v1.5 _run_render_pipeline 共享渲染逻辑）。"""
+        """resume_pipeline 应从 job.image_analysis 读（P0-3 持久化）。"""
        import inspect

        from apps.worker.worker_app.tasks import viral_video as vv

-        # v1.5 改造后 resume 委托给 _run_render_pipeline，那里读取 job.image_analysis
-        src = inspect.getsource(vv._run_render_pipeline)
+        src = inspect.getsource(vv.resume_viral_video_pipeline)
        assert "job.image_analysis" in src
-        assert "image_analysis" in src
-        # resume 本身应该调用 _run_render_pipeline
-        resume_src = inspect.getsource(vv.resume_viral_video_pipeline)
-        assert "_run_render_pipeline" in resume_src
@@ -34,7 +34,7 @@ def _make_job(job_id: str = "job-1", user_id: str = "u1", status: str = "pending
        "viral_structure": "",
        "marketing_purpose": "",
        "bgm_preference": "",
-        "duration": 15,
+        "duration": 30,
        "user_copy_text": "",
        "fusion_level": "ai_polish",
        "reference_audio_path": "",
@@ -51,22 +51,7 @@ def _make_job(job_id: str = "job-1", user_id: str = "u1", status: str = "pending
        "stage": "",
        "progress": 0.0,
        "intent_result": None,
-        "image_analysis": None,
-        "storyboard": None,
-        "copy_result": None,
-        "generated_copy_text": "",
-        "voice_id": "",
-        "voice_source": "",
-        "voice_mode": "global",
-        "video_ratio": "9:16",
-        "video_model": "",
-        "credits_cost": 0,
-        "current_stage": "",
-        "phase_message": "",
        "updated_at": None,
-        "is_terminal": False,
-        "effective_copy_text": "",
-        "voiceover_script": "",
    }.items():
        setattr(job, k, kwargs.pop(k, v))
    return job
@@ -189,213 +174,3 @@ class TestAnalyzeStyle:
        mock_send.assert_called_once_with("worker.run_video_style_analysis", args=["job-sty"])
        assert resp.job_id == "job-sty"
        assert resp.status == "analyzing"
-
-
-# ── v1.5 three-stage endpoints ─────────────────────────────────────────
-
-
-class TestAnalyzeImages:
-    def test_analyze_images_creates_job_and_dispatches(self):
-        """POST /analyze-images: 创建任务 + 入队 run_viral_video_analyze。"""
-        from unittest.mock import patch
-
-        from app.api.routes import viral_video as vv_mod
-        from app.schemas.viral_video import AnalyzeImagesRequest
-
-        user = _auth_user("u1")
-        session = MagicMock()
-        repo = MagicMock()
-        req = AnalyzeImagesRequest(images=["https://x.com/a.jpg"], reference_video_url="", style_template_id="")
-
-        saved = {}
-
-        def fake_save(job):
-            saved["job"] = job
-            return job
-
-        repo.save.side_effect = fake_save
-
-        with (
-            patch.object(vv_mod, "_get_job_repo", return_value=repo),
-            patch.object(vv_mod.celery_app, "send_task") as mock_send,
-        ):
-            resp = vv_mod.analyze_images(req, authenticated_user=user, session=session)
-
-        job = saved["job"]
-        assert job.user_id == "u1"
-        assert job.images == ["https://x.com/a.jpg"]
-        mock_send.assert_called_once_with("worker.run_viral_video_analyze", args=[job.id])
-        assert resp.status == "pending"
-
-
-class TestGenerateCopy:
-    def test_generate_copy_updates_params_and_dispatches(self):
-        """POST /{id}/generate-copy: 在 image_analyzed 状态下写营销参数 + 入队 run_viral_video_generate_copy。"""
-        from unittest.mock import patch
-
-        from app.api.routes import viral_video as vv_mod
-        from app.schemas.viral_video import GenerateCopyRequest
-
-        from packages.domain.viral_video import ViralVideoStatus
-
-        user = _auth_user("u1")
-        session = MagicMock()
-        job = _make_job(job_id="job-gc", user_id="u1", status=ViralVideoStatus.IMAGE_ANALYZED)
-        repo = MagicMock()
-        repo.get.return_value = job
-        req = GenerateCopyRequest(
-            industry="美妆",
-            target_customer="年轻女性",
-            duration=25,
-            fusion_level="ai_full",
-            user_copy_text="试试这个",
-        )
-
-        with (
-            patch.object(vv_mod, "_get_job_repo", return_value=repo),
-            patch.object(vv_mod.celery_app, "send_task") as mock_send,
-        ):
-            resp = vv_mod.generate_copy("job-gc", req, authenticated_user=user, session=session)
-
-        # 参数写入
-        assert job.industry == "美妆"
-        assert job.target_customer == "年轻女性"
-        assert job.duration == 25
-        assert job.fusion_level == "ai_full"
-        assert job.user_copy_text == "试试这个"
-        job.resume_from_image_analyzed.assert_called_once()
-        repo.update.assert_called()
-        mock_send.assert_called_once_with("worker.run_viral_video_generate_copy", args=["job-gc"])
-        assert resp.id == "job-gc"
-
-    def test_generate_copy_rejects_wrong_status(self):
-        """任务在 copy_generated/completed 时不能再 generate-copy（状态保护）。"""
-        import pytest
-        from app.api.routes import viral_video as vv_mod
-        from app.schemas.viral_video import GenerateCopyRequest
-        from fastapi import HTTPException
-
-        from packages.domain.viral_video import ViralVideoStatus
-
-        user = _auth_user("u1")
-        session = MagicMock()
-        job = _make_job(job_id="job-gc2", user_id="u1", status=ViralVideoStatus.COPY_GENERATED)
-        repo = MagicMock()
-        repo.get.return_value = job
-
-        with (patch.object(vv_mod, "_get_job_repo", return_value=repo),):
-            with pytest.raises(HTTPException) as exc:
-                vv_mod.generate_copy("job-gc2", GenerateCopyRequest(), authenticated_user=user, session=session)
-            assert exc.value.status_code == 409
-
-    def test_generate_copy_persists_voice_and_ratio(self):
-        """generate-copy 应把 voice_id/voice_source/video_ratio 写入 job。"""
-        from unittest.mock import patch
-
-        from app.api.routes import viral_video as vv_mod
-        from app.schemas.viral_video import GenerateCopyRequest
-
-        from packages.domain.viral_video import ViralVideoStatus
-
-        user = _auth_user("u1")
-        session = MagicMock()
-        job = _make_job(job_id="job-gc3", user_id="u1", status=ViralVideoStatus.IMAGE_ANALYZED)
-        repo = MagicMock()
-        repo.get.return_value = job
-        req = GenerateCopyRequest(
-            voice_id="cosy_voice_001",
-            voice_source="library",
-            video_ratio="16:9",
-        )
-        with (
-            patch.object(vv_mod, "_get_job_repo", return_value=repo),
-            patch.object(vv_mod.celery_app, "send_task"),
-        ):
-            vv_mod.generate_copy("job-gc3", req, authenticated_user=user, session=session)
-        assert job.voice_id == "cosy_voice_001"
-        assert job.voice_source == "library"
-        assert job.video_ratio == "16:9"
-
-
-class TestAnalyzeImagesPersist:
-    def test_analyze_images_persists_voice_and_ratio(self):
-        """analyze-images 创建任务时应带上 voice/video_ratio 字段。"""
-        from unittest.mock import patch
-
-        from app.api.routes import viral_video as vv_mod
-        from app.schemas.viral_video import AnalyzeImagesRequest
-
-        user = _auth_user("u1")
-        session = MagicMock()
-        saved = {}
-
-        class FakeRepo:
-            def save(self, job):
-                saved["job"] = job
-
-            def get(self, jid):
-                return None
-
-        req = AnalyzeImagesRequest(
-            images=["img-1"],
-            voice_id="preset_v1",
-            voice_source="preset",
-            video_ratio="1:1",
-        )
-        with (
-            patch.object(vv_mod, "_get_job_repo", return_value=FakeRepo()),
-            patch.object(vv_mod.celery_app, "send_task"),
-        ):
-            resp = vv_mod.analyze_images(req, authenticated_user=user, session=session)
-        job = saved["job"]
-        assert job.voice_id == "preset_v1"
-        assert job.voice_source == "preset"
-        assert job.video_ratio == "1:1"
-        assert resp.images == ["img-1"]
-
-
-class TestConfirmCopy:
-    def test_confirm_copy_dispatches_render(self):
-        """POST /{id}/confirm-copy: copy_generated -> RUNNING + 入队 run_viral_video_render，编辑文案写入。"""
-        from unittest.mock import patch
-
-        from app.api.routes import viral_video as vv_mod
-        from app.schemas.viral_video import ConfirmCopyRequest
-
-        from packages.domain.viral_video import ViralVideoStatus
-
-        user = _auth_user("u1")
-        session = MagicMock()
-        job = _make_job(job_id="job-cc", user_id="u1", status=ViralVideoStatus.COPY_GENERATED)
-        repo = MagicMock()
-        repo.get.return_value = job
-        req = ConfirmCopyRequest(edited_copy="我改了文案")
-
-        with (
-            patch.object(vv_mod, "_get_job_repo", return_value=repo),
-            patch.object(vv_mod.celery_app, "send_task") as mock_send,
-        ):
-            resp = vv_mod.confirm_copy("job-cc", req, authenticated_user=user, session=session)
-
-        job.resume_from_copy_generated.assert_called_once_with(edited_copy="我改了文案")
-        mock_send.assert_called_once_with("worker.run_viral_video_render", args=["job-cc"])
-        assert resp.id == "job-cc"
-
-    def test_confirm_copy_rejects_wrong_status(self):
-        import pytest
-        from app.api.routes import viral_video as vv_mod
-        from app.schemas.viral_video import ConfirmCopyRequest
-        from fastapi import HTTPException
-
-        from packages.domain.viral_video import ViralVideoStatus
-
-        user = _auth_user("u1")
-        session = MagicMock()
-        job = _make_job(job_id="job-cc2", user_id="u1", status=ViralVideoStatus.IMAGE_ANALYZED)
-        repo = MagicMock()
-        repo.get.return_value = job
-
-        with patch.object(vv_mod, "_get_job_repo", return_value=repo):
-            with pytest.raises(HTTPException) as exc:
-                vv_mod.confirm_copy("job-cc2", ConfirmCopyRequest(), authenticated_user=user, session=session)
-            assert exc.value.status_code == 409