chore(points): worker settle 打印预估/实际 tokens diff 便于公式校准 (#2155)

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

.env.example

@@ -79,14 +79,33 @@ CELERY_BROKER_URL=redis://localhost:6379/0
 CELERY_RESULT_BACKEND=redis://localhost:6379/1
 
 
-# ==================== Worker 配置 ====================
+# ==================== Worker 配置（#2073 队列分流） ====================
+#
+# 容器内跑三个独立进程：beat（只发定时任务）+ generation worker（实时高优）
+# + transcode worker（后台批量/清理）。三个进程的并发与开关独立配置。
 
 # Worker 进程名称
 WORKER_NAME=xiaoxia-saas-worker
 
-# Worker 并发数（同时执行的任务数）
+# 总并发参考（兼容旧变量）：
+# - 若 GENERATION_CONCURRENCY 与 TRANSCODE_CONCURRENCY 都未显式设置，
+#   entrypoint 会按此总数对半分配（gen=ceil(total/2), trans=剩余，各至少 1）；
+# - 任一个 *_CONCURRENCY 显式设置后，按显式值生效，忽略此变量对应部分。
 WORKER_CONCURRENCY=4
 
+# Generation worker 并发数（用户实时任务：视频生成/TTS/音色克隆/lipsync/数字人）
+# 实时链路对延迟敏感，建议 2C 以上机器设为 2；高负载场景可加到 4。
+GENERATION_CONCURRENCY=2
+
+# Transcode worker 并发数（后台批量：素材入库转码/AI 分类打标/质量评分/查重/批量下载）
+# 后台任务可排队，独立伸缩；素材入库量大时可加到 4。
+TRANSCODE_CONCURRENCY=2
+
+# 是否在本容器启动 celery beat 进程（默认 1）。
+# 默认 beat 与 worker 同容器部署；若要独立 beat 容器部署，worker 容器设为 0、
+# beat 容器单独跑 `celery -A worker_app.celery_app beat` 并设 BEAT_ENABLED=1。
+BEAT_ENABLED=1
+
 # 每个子进程最多处理多少任务后重启（防止内存泄漏）
 WORKER_MAX_TASKS_PER_CHILD=1000
 
@@ -193,9 +212,14 @@ 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）。

.gitea/workflows/ci-pipeline.yml

@@ -1302,8 +1302,16 @@ jobs:
           "${staging_user}@${staging_host}:/var/lib/xiaoxia-saas-staging/configs/douyin_cookies.txt"
         echo "✅ Douyin cookies uploaded"
 
+        # 上传 infra/docker 配置到服务器（compose 单一事实来源）
+        echo "Uploading infra/docker configs to staging server..."
+        ssh -p "$staging_port" -i "$key_path" -o StrictHostKeyChecking=no "${staging_user}@${staging_host}" \
+          "mkdir -p /var/lib/xiaoxia-saas-staging/infra/docker"
+        scp -P "$staging_port" -i "$key_path" -o StrictHostKeyChecking=no infra/docker/compose.yml \
+          "${staging_user}@${staging_host}:/var/lib/xiaoxia-saas-staging/infra/docker/compose.yml"
+        echo "✅ infra/docker/compose.yml uploaded"
+
         # 通过环境变量传递凭证，避免命令行引号转义问题
-        cat scripts/ci_staging_deploy.sh | ssh -p "$staging_port" -i "$key_path" -o StrictHostKeyChecking=no "${staging_user}@${staging_host}" "IMAGE_TAG=${GITHUB_SHA} ACR_USERNAME=${ACR_USERNAME} ACR_PASSWORD=${ACR_PASSWORD} sh"
+        cat scripts/ci_staging_deploy.sh | ssh -p "$staging_port" -i "$key_path" -o StrictHostKeyChecking=no "${staging_user}@${staging_host}" "IMAGE_TAG=${GITHUB_SHA} ACR_USERNAME=${ACR_USERNAME} ACR_PASSWORD=${ACR_PASSWORD} COMPOSE_SYNC=0 sh"
 
         # 清理 CI runner 上的渲染文件
         rm -f .env.rendered

alembic/versions/086_add_viral_video_tables.py

@@ -0,0 +1,100 @@
+"""add viral video tables
+
+Revision ID: 086_add_viral_video_tables
+Revises: 085_atom_clip_caption_embedding
+Create Date: 2026-09-28
+
+新增爆款视频相关表：
+- viral_video_jobs: 爆款视频任务
+- viral_video_style_templates: 风格模板配置
+- viral_video_prompt_templates: Prompt 模板（由 #2040 seed）
+"""
+
+import sqlalchemy as sa
+
+from alembic import op
+
+revision = "086_add_viral_video_tables"
+down_revision = "085_atom_clip_caption_embedding"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    # viral_video_jobs
+    op.create_table(
+        "viral_video_jobs",
+        sa.Column("id", sa.String(36), primary_key=True),
+        sa.Column("user_id", sa.String(36), nullable=False, index=True),
+        sa.Column("images", sa.JSON(), nullable=False, server_default="[]"),
+        sa.Column("industry", sa.String(100), nullable=False, server_default=""),
+        sa.Column("target_customer", sa.String(500), nullable=False, server_default=""),
+        sa.Column("persona_id", sa.String(36), nullable=False, server_default=""),
+        sa.Column("viral_structure", sa.String(50), nullable=False, server_default=""),
+        sa.Column("marketing_purpose", sa.String(100), nullable=False, server_default=""),
+        sa.Column("bgm_preference", sa.String(50), nullable=False, server_default=""),
+        sa.Column("duration", sa.Integer(), nullable=False, server_default="30"),
+        sa.Column("user_copy_text", sa.Text(), nullable=False, server_default=""),
+        sa.Column("fusion_level", sa.String(20), nullable=False, server_default="ai_polish"),
+        sa.Column("reference_audio_path", sa.String(1000), nullable=False, server_default=""),
+        # v1.3 新增
+        sa.Column("reference_video_url", sa.String(1000), nullable=False, server_default=""),
+        sa.Column("style_strength", sa.String(20), nullable=False, server_default="medium"),
+        sa.Column("style_guide", sa.JSON(), nullable=True),
+        sa.Column("style_template_id", sa.String(36), nullable=False, server_default="", index=True),
+        # 状态与结果
+        sa.Column("status", sa.String(30), nullable=False, server_default="pending", index=True),
+        sa.Column("intent_result", sa.JSON(), nullable=True),
+        sa.Column("result_video_url", sa.String(1000), nullable=False, server_default=""),
+        sa.Column("credits_cost", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column("error_msg", sa.Text(), nullable=False, server_default=""),
+        sa.Column("retry_count", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column("started_at", sa.DateTime(timezone=True), nullable=True),
+        sa.Column("completed_at", sa.DateTime(timezone=True), nullable=True),
+        sa.Column("created_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.func.now()),
+        sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.func.now()),
+    )
+
+    # viral_video_style_templates
+    op.create_table(
+        "viral_video_style_templates",
+        sa.Column("id", sa.String(36), primary_key=True),
+        sa.Column("name", sa.String(200), nullable=False),
+        sa.Column("description", sa.Text(), nullable=False, server_default=""),
+        sa.Column("thumbnail_url", sa.String(1000), nullable=False, server_default=""),
+        sa.Column("style_config", sa.JSON(), nullable=False, server_default="{}"),
+        sa.Column("is_system", sa.Boolean(), nullable=False, server_default=sa.text("true"), index=True),
+        sa.Column("sort_order", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column("created_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.func.now()),
+        sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.func.now()),
+    )
+
+    # viral_video_prompt_templates
+    op.create_table(
+        "viral_video_prompt_templates",
+        sa.Column("id", sa.String(36), primary_key=True),
+        sa.Column("prompt_type", sa.String(50), nullable=False, index=True),
+        sa.Column("name", sa.String(200), nullable=False),
+        sa.Column("content", sa.Text(), nullable=False, server_default=""),
+        sa.Column("variables", sa.JSON(), nullable=False, server_default="[]"),
+        sa.Column("version", sa.Integer(), nullable=False, server_default="1"),
+        sa.Column("is_active", sa.Boolean(), nullable=False, server_default=sa.text("true"), index=True),
+        sa.Column("created_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.func.now()),
+        sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.func.now()),
+    )
+
+    # Seed 默认风格模板
+    op.execute("""
+        INSERT INTO viral_video_style_templates (id, name, description, style_config, is_system, sort_order)
+        VALUES
+            ('style-tpl-001', '快节奏冲击', '高频切镜+动感BGM，适合食品饮料等快消品', '{"cut_speed": "fast", "transition": "jump_cut", "energy": "high"}', true, 1),
+            ('style-tpl-002', '质感慢镜', '慢节奏+电影感调色，适合美妆护肤珠宝', '{"cut_speed": "slow", "transition": "dissolve", "energy": "low", "color_grade": "cinematic"}', true, 2),
+            ('style-tpl-003', '口播种草', '数字人口播+产品特写穿插', '{"cut_speed": "medium", "transition": "cross_dissolve", "has_talking_head": true}', true, 3),
+            ('style-tpl-004', '场景叙事', '多场景切换+故事线叙述', '{"cut_speed": "medium", "transition": "wipe", "narrative": true}', true, 4)
+        """)
+
+
+def downgrade() -> None:
+    op.drop_table("viral_video_prompt_templates")
+    op.drop_table("viral_video_style_templates")
+    op.drop_table("viral_video_jobs")

alembic/versions/087_viral_video_image_analysis.py

@@ -0,0 +1,25 @@
+"""viral video add image_analysis column
+
+Revision ID: 087_viral_video_image_analysis
+Revises: 086_add_viral_video_tables
+Create Date: 2026-09-30
+
+#2106 爆款视频 P0：持久化图片分析结果（image_analysis JSON），供 resume 阶段使用。
+"""
+
+import sqlalchemy as sa
+
+from alembic import op
+
+revision = "087_viral_video_image_analysis"
+down_revision = "086_add_viral_video_tables"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    op.add_column("viral_video_jobs", sa.Column("image_analysis", sa.JSON(), nullable=True))
+
+
+def downgrade() -> None:
+    op.drop_column("viral_video_jobs", "image_analysis")

alembic/versions/088_viral_video_copy_result.py

@@ -0,0 +1,51 @@
+"""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

alembic/versions/089_viral_video_cols.py

@@ -0,0 +1,62 @@
+"""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

alembic/versions/090_viral_video_phase_msg.py

@@ -0,0 +1,35 @@
+"""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")

alembic/versions/091_viral_video_stage.py

@@ -0,0 +1,49 @@
+"""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")

alembic/versions/092_viral_video_heartbeat.py

@@ -0,0 +1,42 @@
+"""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")

alembic/versions/093_viral_video_pricing_points_float.py

@@ -0,0 +1,87 @@
+"""viral_video 动态积分定价 + 积分字段从 Integer 改为 Float (#2151)
+
+Revision ID: 093
+Revises: 092_viral_video_heartbeat
+Create Date: 2026-10-02
+"""
+
+import sqlalchemy as sa
+
+from alembic import op
+
+revision = "093"
+down_revision = "092_viral_video_heartbeat"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    conn = op.get_bind()
+    inspector = sa.inspect(conn)
+
+    # 1) points_accounts 三列 Integer -> Float
+    pa_cols = {c["name"]: c for c in inspector.get_columns("points_accounts")}
+    for col in ("balance", "total_earned", "total_spent"):
+        if col in pa_cols:
+            op.alter_column(
+                "points_accounts",
+                col,
+                existing_type=sa.Integer(),
+                type_=sa.Float(),
+                existing_nullable=False,
+            )
+
+    # 2) points_transactions amount/balance_after Integer -> Float
+    pt_cols = {c["name"]: c for c in inspector.get_columns("points_transactions")}
+    for col in ("amount", "balance_after"):
+        if col in pt_cols:
+            op.alter_column(
+                "points_transactions",
+                col,
+                existing_type=sa.Integer(),
+                type_=sa.Float(),
+                existing_nullable=False,
+            )
+
+    # 3) users.points_balance Integer -> Float
+    user_cols = {c["name"]: c for c in inspector.get_columns("users")}
+    if "points_balance" in user_cols:
+        op.alter_column(
+            "users",
+            "points_balance",
+            existing_type=sa.Integer(),
+            type_=sa.Float(),
+            existing_nullable=False,
+        )
+
+    # 4) viral_video_jobs.credits_cost Integer -> Float
+    vv_cols = {c["name"]: c for c in inspector.get_columns("viral_video_jobs")}
+    if "credits_cost" in vv_cols:
+        op.alter_column(
+            "viral_video_jobs",
+            "credits_cost",
+            existing_type=sa.Integer(),
+            type_=sa.Float(),
+            existing_nullable=False,
+        )
+
+    # 5) viral_video_jobs 新增列
+    if "video_resolution" not in vv_cols:
+        op.add_column(
+            "viral_video_jobs",
+            sa.Column("video_resolution", sa.String(20), nullable=False, server_default="720p"),
+        )
+    if "credits_prepaid" not in vv_cols:
+        op.add_column(
+            "viral_video_jobs",
+            sa.Column("credits_prepaid", sa.Float(), nullable=False, server_default="0"),
+        )
+    if "credits_transaction_id" not in vv_cols:
+        op.add_column(
+            "viral_video_jobs",
+            sa.Column("credits_transaction_id", sa.String(36), nullable=False, server_default=""),
+        )
+
+
+def downgrade() -> None:
+    pass

apps/api/app/api/router.py

@@ -36,6 +36,7 @@ from app.api.routes.titles import router as titles_router
 from app.api.routes.tts import router as tts_router
 from app.api.routes.upload import router as upload_router
 from app.api.routes.videos import router as videos_router
+from app.api.routes.viral_video import router as viral_video_router
 from app.api.routes.voice_clones import router as voice_clones_router
 from app.api.routes.voices import router as voices_router
 from fastapi import APIRouter
@@ -240,3 +241,4 @@ api_router.include_router(
     prefix="/gpu",
     tags=["GPU Worker"],
 )
+api_router.include_router(viral_video_router, prefix="/viral-video", tags=["爆款视频"])

apps/api/app/api/routes/ai_avatar_render.py

@@ -29,8 +29,6 @@ from app.services.ai_avatar_render_service import (
 from fastapi import APIRouter, Depends, HTTPException, Query
 from sqlalchemy.orm import Session
 
-from packages.middleware.points_gate import points_gate
-
 logger = logging.getLogger(__name__)
 
 router = APIRouter()
@@ -44,7 +42,6 @@ def _get_service(db: Session = Depends(get_db_session)) -> AiAvatarRenderService
 
 
 @router.post("", response_model=AiAvatarRenderJobResponse, status_code=201)
-@points_gate("ai_digital_human", per_unit=15)
 def create_render_job(
     body: CreateAiAvatarRenderRequest,
     current_user: AuthenticatedUser = Depends(get_current_user),

apps/api/app/api/routes/generation_cover.py

@@ -27,7 +27,6 @@ from packages.adapters.sqlalchemy_impl.generation_task_repository import (
 )
 from packages.application import ListGeneratedVideosByTaskUseCase
 from packages.domain.config_schemas import normalize_plan_config
-from packages.middleware.points_gate import points_gate
 from packages.shared.storage import get_shared_storage_service
 
 from .templates_editor.dependencies import get_draft_plan_id, get_editor_services
@@ -346,7 +345,6 @@ def _is_trusted_media_url(url: str) -> bool:
 
 
 @router.post("/generate-cover", response_model=GenerateCoverResponse)
-@points_gate("ai_cover")
 def generate_cover(
     body: GenerateCoverRequest,
     template_id: str = Query(..., description="模板 ID"),

apps/api/app/api/routes/generation_preview.py

@@ -11,9 +11,7 @@ from app.auth import AuthenticatedUser, get_current_user
 from app.core.storage import get_storage_service
 from app.core.task_enqueue import (
     GLOBAL_PENDING_LIMIT,
-    USER_PENDING_LIMIT,
     GlobalQueueFull,
-    UserPendingLimitExceeded,
     build_rate_limit_detail,
     safe_enqueue_generation_task,
 )
@@ -43,7 +41,6 @@ from packages.application import (
     GetGenerationTaskUseCase,
     ListGeneratedVideosByTaskUseCase,
 )
-from packages.middleware.points_gate import points_gate
 
 logger = logging.getLogger(__name__)
 
@@ -272,7 +269,6 @@ def _variant_value(values: list[str], index: int, fallback: str = "") -> str:
 
 
 @router.post("/preview", response_model=BatchPreviewGenerationTaskResponse, status_code=201)
-@points_gate("ai_video", quantity_field="preview_count")
 def create_preview_generation_task(
     request: CreatePreviewGenerationTaskRequest,
     authenticated_user: AuthenticatedUser = Depends(get_current_user),
@@ -302,26 +298,17 @@ def create_preview_generation_task(
         count,
     )
 
-    # 预检查队列限流（按变体总数计）
-    try:
-        user_pending = generation_task_repository.count_pending_by_user(user_id)
-        global_pending = generation_task_repository.count_pending_total()
-        if user_pending + count > USER_PENDING_LIMIT:
-            raise UserPendingLimitExceeded(
-                user_id=user_id, pending_count=user_pending + count, limit=USER_PENDING_LIMIT
-            )
-        if global_pending + count > GLOBAL_PENDING_LIMIT:
-            raise GlobalQueueFull(pending_count=global_pending + count, limit=GLOBAL_PENDING_LIMIT)
-    except UserPendingLimitExceeded as e:
-        raise HTTPException(
-            status_code=429,
-            detail=build_rate_limit_detail(e, generation_task_repository, scope="user"),
-        ) from e
-    except GlobalQueueFull as e:
+    # 预检查队列限流（按变体总数计）——仅保留全局硬上限，用户上限改为软 warning 在 safe_enqueue 内处理（#2098）
+    global_pending = generation_task_repository.count_pending_total()
+    if global_pending + count > GLOBAL_PENDING_LIMIT:
         raise HTTPException(
             status_code=503,
-            detail=build_rate_limit_detail(e, generation_task_repository, scope="global"),
-        ) from e
+            detail=build_rate_limit_detail(
+                GlobalQueueFull(pending_count=global_pending + count, limit=GLOBAL_PENDING_LIMIT),
+                generation_task_repository,
+                scope="global",
+            ),
+        )
 
     # 确定视频比例：优先前端传入，否则从模板 mode 推断
     video_ratio = request.video_ratio or ""
@@ -589,9 +576,6 @@ def create_preview_generation_task(
             if not enqueued:
                 logger.warning("[预览生成] 任务入队失败: task_id=%s", task.id)
                 _mark_task_failed(generation_task_repository, task, "任务入队失败")
-        except UserPendingLimitExceeded as e:
-            _mark_task_failed(generation_task_repository, task, "待处理任务超限")
-            rate_limit_exc = rate_limit_exc or e
         except GlobalQueueFull as e:
             _mark_task_failed(generation_task_repository, task, "系统队列已满")
             rate_limit_exc = rate_limit_exc or e
@@ -603,11 +587,6 @@ def create_preview_generation_task(
 
     # 队列满/限流时若全部失败，返回结构化错误码（前端区分"排队"与"创建失败"）
     if all(r.status == "failed" for r in responses) and rate_limit_exc is not None:
-        if isinstance(rate_limit_exc, UserPendingLimitExceeded):
-            raise HTTPException(
-                status_code=429,
-                detail=build_rate_limit_detail(rate_limit_exc, generation_task_repository, scope="user"),
-            )
         raise HTTPException(
             status_code=503,
             detail=build_rate_limit_detail(rate_limit_exc, generation_task_repository, scope="global"),

apps/api/app/api/routes/generation_tasks.py

@@ -7,7 +7,6 @@ from app.auth import AuthenticatedUser, get_current_user
 from app.core.storage import OSSStorageService, get_storage_service
 from app.core.task_enqueue import (
     GLOBAL_PENDING_LIMIT,
-    USER_PENDING_LIMIT,
     GlobalQueueFull,
     UserPendingLimitExceeded,
     build_rate_limit_detail,
@@ -50,12 +49,98 @@ from packages.domain.smart_match import smart_select_assets
 # #2035：文案关键词 → 素材分类 映射表（用于 smart_match category_match 维度）
 # AssetClassification 枚举: scenic / product / person / animal / food / tech / sport / music / other
 _CATEGORY_KEYWORDS: dict[str, set[str]] = {
-    "scenic": {"风景", "自然", "山水", "大海", "天空", "日落", "日出", "森林", "城市", "建筑", "夜景", "街道", "公园", "景区", "旅行", "旅游", "户外"},
-    "product": {"产品", "商品", "展示", "演示", "开箱", "评测", "好物", "推荐", "种草", "购物", "电商", "带货", "品牌", "广告", "包装"},
-    "person": {"人物", "人物采访", "对话", "说话", "讲解", "演讲", "采访", "聊天", "开会", "工作", "办公室", "团队", "员工", "老板", "女性", "男性", "美女", "帅哥"},
+    "scenic": {
+        "风景",
+        "自然",
+        "山水",
+        "大海",
+        "天空",
+        "日落",
+        "日出",
+        "森林",
+        "城市",
+        "建筑",
+        "夜景",
+        "街道",
+        "公园",
+        "景区",
+        "旅行",
+        "旅游",
+        "户外",
+    },
+    "product": {
+        "产品",
+        "商品",
+        "展示",
+        "演示",
+        "开箱",
+        "评测",
+        "好物",
+        "推荐",
+        "种草",
+        "购物",
+        "电商",
+        "带货",
+        "品牌",
+        "广告",
+        "包装",
+    },
+    "person": {
+        "人物",
+        "人物采访",
+        "对话",
+        "说话",
+        "讲解",
+        "演讲",
+        "采访",
+        "聊天",
+        "开会",
+        "工作",
+        "办公室",
+        "团队",
+        "员工",
+        "老板",
+        "女性",
+        "男性",
+        "美女",
+        "帅哥",
+    },
     "animal": {"动物", "宠物", "狗", "猫", "鸟", "鱼", "马", "牛", "羊", "野生动物", "动物园"},
-    "food": {"美食", "食物", "餐饮", "餐厅", "做饭", "烹饪", "厨房", "菜品", "饮料", "水果", "甜点", "蛋糕", "咖啡", "茶", "零食", "吃"},
-    "tech": {"科技", "数码", "电脑", "手机", "屏幕", "软件", "APP", "互联网", "AI", "人工智能", "机器人", "办公", "程序员", "代码", "屏幕录制"},
+    "food": {
+        "美食",
+        "食物",
+        "餐饮",
+        "餐厅",
+        "做饭",
+        "烹饪",
+        "厨房",
+        "菜品",
+        "饮料",
+        "水果",
+        "甜点",
+        "蛋糕",
+        "咖啡",
+        "茶",
+        "零食",
+        "吃",
+    },
+    "tech": {
+        "科技",
+        "数码",
+        "电脑",
+        "手机",
+        "屏幕",
+        "软件",
+        "APP",
+        "互联网",
+        "AI",
+        "人工智能",
+        "机器人",
+        "办公",
+        "程序员",
+        "代码",
+        "屏幕录制",
+    },
     "sport": {"运动", "健身", "跑步", "篮球", "足球", "游泳", "瑜伽", "户外", "锻炼", "体育", "比赛", "球场"},
     "music": {"音乐", "歌曲", "演唱会", "乐器", "唱歌", "跳舞", "舞蹈", "MV", "演出", "乐队", "钢琴", "吉他", "节奏"},
 }
@@ -77,7 +162,7 @@ def _infer_expected_categories(script_tags: set[str] | None) -> set[str] | None:
                 break
     return matched or None
 
-from packages.middleware.points_gate import points_gate
+
 
 logger = logging.getLogger(__name__)
 
@@ -193,10 +278,13 @@ def _select_assets_from_library(
     # #2035：加载片段级 AI 标签，供叙事模式 AI 加权和 smart 模式语义匹配使用。
     # 失败降级为空（不影响选片主流程）。
     clip_ai_tags_by_asset: dict[str, list[dict]] = {}
-    ai_tags_by_asset: dict[str, dict] = {}  # asset_id → 聚合后的 ai_tags dict（取首个有 has_text 的片段；合并 scene/objects/action 去重）
+    ai_tags_by_asset: dict[
+        str, dict
+    ] = {}  # asset_id → 聚合后的 ai_tags dict（取首个有 has_text 的片段；合并 scene/objects/action 去重）
     try:
         if db is not None:
             from packages.adapters.sqlalchemy_impl.models import AssetAtomClipModel
+
             ready_ids = [a.id for a in ready_video_assets]
             clip_rows = (
                 db.query(AssetAtomClipModel.asset_id, AssetAtomClipModel.ai_tags)
@@ -376,7 +464,6 @@ def _resolve_project_and_library(
 
 
 @router.post("/tasks", response_model=BatchGenerationTaskResponse)
-@points_gate("ai_video", quantity_field="count")
 def create_generation_task(
     request: CreateGenerationTaskRequest,
     authenticated_user: AuthenticatedUser = Depends(get_current_user),
@@ -594,21 +681,13 @@ def create_generation_task(
     # 同批次任务共享 batch_id，用于视频查重时批次内比对
     batch_id = uuid.uuid4().hex if count > 1 else ""
 
-    # 预检查：批量提交前先看会不会超限，避免建一半才拒
+    # 预检查（Bug B #2098）：只保留全局 503 保护，用户级不再硬拒 429；
+    # 超额任务直接入队等待 worker 自然消费，前端展示排队位置而非阻止提交。
+    # USER_PENDING_LIMIT 作为软上限（safe_enqueue 兜底），提高到 20 支持批量提交。
     try:
-        user_pending = generation_task_repository.count_pending_by_user(user_id)
         global_pending = generation_task_repository.count_pending_total()
-        if user_pending + count > USER_PENDING_LIMIT:
-            raise UserPendingLimitExceeded(
-                user_id=user_id, pending_count=user_pending + count, limit=USER_PENDING_LIMIT
-            )
         if global_pending + count > GLOBAL_PENDING_LIMIT:
             raise GlobalQueueFull(pending_count=global_pending + count, limit=GLOBAL_PENDING_LIMIT)
-    except UserPendingLimitExceeded as e:
-        raise HTTPException(
-            status_code=429,
-            detail=build_rate_limit_detail(e, generation_task_repository, scope="user"),
-        ) from e
     except GlobalQueueFull as e:
         raise HTTPException(
             status_code=503,
@@ -923,14 +1002,10 @@ def create_generation_task(
                 else:
                     failed_tasks.append(task)
             except UserPendingLimitExceeded as _e:
-                # 兜底：如果预检查后又并发提交了，在这里也拦住
-                failed_tasks.append(task)
-                if not created_tasks:
-                    raise HTTPException(
-                        status_code=429,
-                        detail=build_rate_limit_detail(_e, generation_task_repository, scope="user"),
-                    ) from _e
-                break
+                # Bug B #2098: 用户级限流已改为软限制，此分支理论上不再触发；
+                # 极端并发兜底仍入队（safe_enqueue 内部会打 warning 日志），不 429 拒绝
+                logger.warning("[生成任务] 用户 pending 超软限制，仍允许入队: task_id=%s", task.id)
+                created_tasks.append(task)
             except GlobalQueueFull as _e:
                 failed_tasks.append(task)
                 if not created_tasks:
@@ -1081,10 +1156,8 @@ def confirm_generation(
         ):
             logger.warning("[确认生成] 入队失败: task_id=%s", new_task.id)
     except UserPendingLimitExceeded as _e:
-        raise HTTPException(
-            status_code=429,
-            detail=build_rate_limit_detail(_e, generation_task_repository, scope="user"),
-        ) from None
+        # Bug B #2098: 用户级限流已软处理，理论上不再触发；作为防御仍放行
+        logger.warning("[任务] 用户 pending 超软限制，任务已入队")
     except GlobalQueueFull as _e:
         raise HTTPException(
             status_code=503,
@@ -1263,22 +1336,8 @@ def retry_generation_task(
         raise HTTPException(status_code=409, detail="Only failed tasks can be retried")
 
     user_id = authenticated_user.user.id
-    # 预检查：创建前判断，>= 上限就拒绝
-    user_pending = generation_task_repository.count_pending_by_user(user_id)
+    # 预检查（Bug B #2098）：只保留全局 503，用户级不再硬拒
     global_pending = generation_task_repository.count_pending_total()
-    if user_pending >= USER_PENDING_LIMIT:
-        raise HTTPException(
-            status_code=429,
-            detail=build_rate_limit_detail(
-                UserPendingLimitExceeded(
-                    user_id=user_id,
-                    pending_count=user_pending,
-                    limit=USER_PENDING_LIMIT,
-                ),
-                generation_task_repository,
-                scope="user",
-            ),
-        )
     if global_pending >= GLOBAL_PENDING_LIMIT:
         raise HTTPException(
             status_code=503,
@@ -1321,10 +1380,8 @@ def retry_generation_task(
         ):
             logger.warning("[生成任务] 重试入队失败: task_id=%s", retried.id)
     except UserPendingLimitExceeded as _e:
-        raise HTTPException(
-            status_code=429,
-            detail=build_rate_limit_detail(_e, generation_task_repository, scope="user"),
-        ) from None
+        # Bug B #2098: 用户级限流已软处理，理论上不再触发；作为防御仍放行
+        logger.warning("[任务] 用户 pending 超软限制，任务已入队")
     except GlobalQueueFull as _e:
         raise HTTPException(
             status_code=503,

apps/api/app/api/routes/health.py

@@ -9,6 +9,11 @@ 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 {
@@ -49,7 +54,7 @@ async def _check_database() -> dict:
             "message": "Using in-memory database",
         }
     try:
-        conn = psycopg.connect(settings.DATABASE_URL, connect_timeout=3)
+        conn = psycopg.connect(_pg_url(settings.DATABASE_URL), connect_timeout=3)
         with conn.cursor() as cur:
             cur.execute("SELECT 1")
             cur.fetchone()
@@ -124,7 +129,7 @@ async def _check_migrations() -> dict:
             "message": "Using in-memory database, no migrations needed",
         }
     try:
-        conn = psycopg.connect(settings.DATABASE_URL, connect_timeout=3)
+        conn = psycopg.connect(_pg_url(settings.DATABASE_URL), connect_timeout=3)
         with conn.cursor() as cur:
             cur.execute("""
                 SELECT COUNT(*) FROM information_schema.tables
@@ -137,3 +142,5 @@ 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}"}
+
+

apps/api/app/api/routes/lipsync.py

@@ -12,11 +12,9 @@
 from __future__ import annotations
 
 import logging
-import math
 from datetime import UTC
 
 from app.auth import AuthenticatedUser, get_current_user
-from app.config import settings
 from app.dependencies import (
     get_db_session,
     get_voice_clone_profile_repository,
@@ -32,9 +30,6 @@ from app.services.mediakit_client import MediaKitError
 from fastapi import APIRouter, BackgroundTasks, Depends, HTTPException, Query
 from sqlalchemy.orm import Session
 
-from packages.domain.points_rules import calculate_points_cost
-from packages.domain.points_service import PointsService
-
 logger = logging.getLogger(__name__)
 
 router = APIRouter()
@@ -61,37 +56,6 @@ def create_lipsync_job(
     db: Session = Depends(get_db_session),
     svc: LipsyncService = Depends(_get_service),
 ):
-    user_id = current_user.user.id
-
-    # ── 积分扣点（#1895 P2） ──
-    _points_deducted = 0
-    _points_scene = "ai_digital_human"
-    _points_svc = PointsService() if settings.points_enabled else None
-    if _points_svc is not None:
-        # 口型同步：TTS 模式按 script_text 估时长（240字/分钟）；音频直传按 audio_duration（秒→分钟）
-        if body.audio_url and body.audio_duration and body.audio_duration > 0:
-            est_minutes = max(1.0, math.ceil(body.audio_duration / 60.0))
-        elif body.script_text:
-            est_minutes = max(1.0, math.ceil(len(body.script_text) / 240))
-        else:
-            est_minutes = 1.0
-        _points_deducted = calculate_points_cost(
-            _points_scene,
-            is_member=getattr(current_user.user, "is_member", False),
-            duration_minutes=est_minutes,
-            member_type=getattr(current_user.user, "member_type", None),
-        )
-        _deduct_res = _points_svc.deduct_points(user_id, _points_deducted, _points_scene, db)
-        if not _deduct_res["success"]:
-            raise HTTPException(
-                status_code=402,
-                detail={
-                    "code": "INSUFFICIENT_POINTS",
-                    "message": f"积分不足，需要 {_points_deducted} 积分，当前余额 {_deduct_res['balance']}",
-                    "required": _points_deducted,
-                    "balance": _deduct_res["balance"],
-                },
-            )
     """提交对口型任务.
 
     三种模式：
@@ -101,6 +65,8 @@ def create_lipsync_job(
     - 预合成音频（#1845 新主路径）：传 {video_url, audio_url, audio_duration, sentence_timings}，
       后端同步ffprobe+写入timings+直接提交MediaKit（~2-3s）。
     """
+    user_id = current_user.user.id
+
     try:
         job = svc.create_job(
             user_id=user_id,
@@ -118,18 +84,8 @@ def create_lipsync_job(
             project_id=body.project_id,
         )
     except ValueError as exc:
-        if _points_deducted > 0 and _points_svc is not None:
-            try:
-                _points_svc.refund_points(user_id, _points_deducted, _points_scene, db)
-            except Exception as refund_err:
-                logger.warning(f"对口型 ValueError 退积分异常: err={refund_err}")
         raise HTTPException(status_code=400, detail=str(exc)) from exc
     except MediaKitError as exc:
-        if _points_deducted > 0 and _points_svc is not None:
-            try:
-                _points_svc.refund_points(user_id, _points_deducted, _points_scene, db)
-            except Exception as refund_err:
-                logger.warning(f"对口型 MediaKitError 退积分异常: err={refund_err}")
         status_code = 502
         if exc.code in ("VoiceForbidden",):
             status_code = 403
@@ -145,24 +101,11 @@ def create_lipsync_job(
         ) from exc
     except Exception as exc:
         logger.error("创建对口型任务异常: %s", exc, exc_info=True)
-        if _points_deducted > 0 and _points_svc is not None:
-            try:
-                _points_svc.refund_points(user_id, _points_deducted, _points_scene, db)
-            except Exception as refund_err:
-                logger.warning(f"对口型异常退积分异常: err={refund_err}")
         raise HTTPException(
             status_code=400,
             detail=f"创建对口型任务失败: {exc}",
         ) from exc
 
-    # 创建成功但状态为 failed（同步路径失败已抛异常到上面 except；此处处理 Celery 调度失败等）
-    # 若任务已创建且状态为 failed，退费
-    if _points_deducted > 0 and _points_svc is not None and getattr(job, "status", None) == "failed":
-        try:
-            _points_svc.refund_points(user_id, _points_deducted, _points_scene, db, ref_id=job.id)
-        except Exception as refund_err:
-            logger.warning(f"对口型任务失败退积分异常: job_id={job.id}, err={refund_err}")
-
     return job
 
 
@@ -176,37 +119,14 @@ def preview_tts(
     db: Session = Depends(get_db_session),
     svc: LipsyncService = Depends(_get_service),
 ):
-    user_id = current_user.user.id
-
-    # ── 积分扣点（#1895 P2） ──
-    _points_deducted = 0
-    _points_scene = "ai_digital_human"
-    _points_svc = PointsService() if settings.points_enabled else None
-    if _points_svc is not None:
-        est_minutes = max(1.0, math.ceil(len(body.script_text or "") / 240)) if body.script_text else 1.0
-        _points_deducted = calculate_points_cost(
-            _points_scene,
-            is_member=getattr(current_user.user, "is_member", False),
-            duration_minutes=est_minutes,
-            member_type=getattr(current_user.user, "member_type", None),
-        )
-        _deduct_res = _points_svc.deduct_points(user_id, _points_deducted, _points_scene, db)
-        if not _deduct_res["success"]:
-            raise HTTPException(
-                status_code=402,
-                detail={
-                    "code": "INSUFFICIENT_POINTS",
-                    "message": f"积分不足，需要 {_points_deducted} 积分，当前余额 {_deduct_res['balance']}",
-                    "required": _points_deducted,
-                    "balance": _deduct_res["balance"],
-                },
-            )
     """步骤1「生成配音」同步 TTS 预合成.
 
     同步执行 TTS 合成 → 下载音频 → ffprobe 时长 → 句子时间戳计算，
     不创建 LipsyncJob、不转存 OSS，直接返回 CosyVoice 临时 URL（~24h 有效）。
     耗时约 2-3 秒。
     """
+    user_id = current_user.user.id
+
     try:
         result = svc.preview_tts(
             user_id=user_id,
@@ -218,11 +138,6 @@ def preview_tts(
             emotion=body.emotion,
         )
     except MediaKitError as exc:
-        if _points_deducted > 0 and _points_svc is not None:
-            try:
-                _points_svc.refund_points(user_id, _points_deducted, _points_scene, db)
-            except Exception as refund_err:
-                logger.warning(f"TTS 预合成 MediaKitError 退积分异常: err={refund_err}")
         status_code = 400
         if exc.code in ("VoiceForbidden",):
             status_code = 403
@@ -237,11 +152,6 @@ def preview_tts(
         ) from exc
     except Exception as exc:
         logger.error("TTS 预合成异常: %s", exc, exc_info=True)
-        if _points_deducted > 0 and _points_svc is not None:
-            try:
-                _points_svc.refund_points(user_id, _points_deducted, _points_scene, db)
-            except Exception as refund_err:
-                logger.warning(f"TTS 预合成异常退积分异常: err={refund_err}")
         raise HTTPException(
             status_code=400,
             detail=f"TTS 合成失败: {exc}",

apps/api/app/api/routes/points.py

@@ -169,17 +169,7 @@ def check_points(
     current_user: AuthenticatedUser = Depends(get_current_user),
     db: Session = Depends(get_db_session),
 ):
-    """消费前检查余额是否足够。未知 scene_key 返回 400（而非 500）。"""
-    if body.scene_key not in POINTS_SCENES:
-        raise HTTPException(
-            status_code=400,
-            detail={
-                "code": "UNKNOWN_SCENE",
-                "message": f"未知场景: {body.scene_key}",
-                "valid_scenes": sorted(POINTS_SCENES.keys()),
-            },
-        )
-
+    """消费前检查余额是否足够。已下线/未知场景返回 cost=0（免费）。"""
     # 积分系统暂停（ENABLE_CREDIT_SYSTEM=false）：所有场景直接放行，需 0 积分
     if not _credits_enabled():
         svc = _get_service()
@@ -195,13 +185,6 @@ def check_points(
     is_mem = _is_member(current_user)
     mt = _member_type(current_user)
 
-    # 混剪场景先检查免费额度
-    is_free_quota = False
-    if body.scene_key == "ai_video" and not is_mem:
-        svc = _get_service()
-        if svc.check_daily_free_clip(current_user.user.id, db):
-            is_free_quota = True
-
     required = calculate_points_cost(
         body.scene_key,
         is_mem,
@@ -215,11 +198,11 @@ def check_points(
     balance = account["balance"]
 
     return PointsCheckResponse(
-        allowed=is_free_quota or balance >= required,
+        allowed=balance >= required,
         required_points=required,
         current_balance=balance,
         remaining_after=balance - required,
-        is_free_quota=is_free_quota,
+        is_free_quota=False,
     )
 
 

apps/api/app/api/routes/scripts_ai.py

@@ -44,7 +44,6 @@ from app.services.script_asr_service import (
 from fastapi import APIRouter, Depends, HTTPException, status
 from sqlalchemy.orm import Session
 
-from packages.middleware.points_gate import points_gate
 from packages.shared.ai_client import get_doubao_client
 
 logger = logging.getLogger(__name__)
@@ -373,7 +372,6 @@ def douyin_diag():
 
 
 @router.post("/extract-from-douyin", response_model=ExtractFromDouyinResponse)
-@points_gate("douyin_extract")
 def extract_from_douyin(
     request: ExtractFromDouyinRequest,
     current_user: AuthenticatedUser = Depends(get_current_user),
@@ -497,7 +495,6 @@ def extract_from_douyin(
 
 
 @router.post("/ai-rewrite", response_model=AiRewriteResponse)
-@points_gate("ai_rewrite")
 def ai_rewrite(
     request: AiRewriteRequest,
     current_user: AuthenticatedUser = Depends(get_current_user),
@@ -537,7 +534,6 @@ def ai_rewrite(
 
 
 @router.post("/ai-generate-titles", response_model=AiGenerateTitlesResponse)
-@points_gate("ai_title")
 def ai_generate_titles(
     request: AiGenerateTitlesRequest,
     current_user: AuthenticatedUser = Depends(get_current_user),

apps/api/app/api/routes/tts.py

@@ -4,14 +4,12 @@ from __future__ import annotations
 
 import json
 import logging
-import math
 import subprocess
 import tempfile
 from pathlib import Path
 from typing import Any, Optional
 
 from app.auth import AuthenticatedUser, get_current_user
-from app.config import settings
 from app.core.celery_app import celery_app
 from app.core.storage import get_storage_service
 from app.dependencies import (
@@ -53,8 +51,6 @@ from packages.application.tts_job.use_cases import (
 )
 from packages.application.tts_job.workflow import TTSWorkflowService
 from packages.domain import Asset, AssetLibrary, AssetLibraryKind, AssetStatus, ClassificationStatus
-from packages.domain.points_rules import calculate_points_cost
-from packages.domain.points_service import PointsService
 from packages.domain.voice_presets import list_voices
 from packages.ports.asset_library_repository import AssetLibraryRepository
 from packages.ports.asset_repository import AssetRepository
@@ -144,31 +140,6 @@ def synthesize(
     """
     user_id = authenticated_user.user.id
 
-    # ── 积分扣点（#1895 P2） ──
-    _points_deducted = 0
-    _points_scene = "ai_voice"
-    _points_svc = PointsService() if settings.points_enabled else None
-    if _points_svc is not None:
-        # 中文按 ~240 字/分钟粗估时长，至少按 1 分钟扣 1 分
-        est_minutes = max(1.0, math.ceil(len(request.text) / 240))
-        _points_deducted = calculate_points_cost(
-            _points_scene,
-            is_member=getattr(authenticated_user.user, "is_member", False),
-            duration_minutes=est_minutes,
-            member_type=getattr(authenticated_user.user, "member_type", None),
-        )
-        _deduct_res = _points_svc.deduct_points(user_id, _points_deducted, _points_scene, db)
-        if not _deduct_res["success"]:
-            raise HTTPException(
-                status_code=402,
-                detail={
-                    "code": "INSUFFICIENT_POINTS",
-                    "message": f"积分不足，需要 {_points_deducted} 积分，当前余额 {_deduct_res['balance']}",
-                    "required": _points_deducted,
-                    "balance": _deduct_res["balance"],
-                },
-            )
-
     # 解析 voice_id：前端可能传克隆音色 profile UUID（而非 CosyVoice voice_id），
     # 与 /tts/preview 保持一致：命中 profile → 校验归属 → 取 CosyVoice voice_id
     actual_voice_id = request.voice_id
@@ -231,7 +202,6 @@ def synthesize(
         cosyvoice_service=cosyvoice_service,
     )
 
-    synthesis_error: Exception | None = None
     try:
         job = workflow.start_synthesis(job.id)
     except Exception as e:
@@ -239,18 +209,10 @@ def synthesize(
         # 但 DB 异常、网络异常等意外错误可能逃逸。
         # 与音色克隆接口保持一致：标记 failed，返回 201，不抛 500。
         logger.error(f"TTS 合成异常: job_id={job.id}, error={e}", exc_info=True)
-        synthesis_error = e
         try:
             job = workflow.process_synthesis_failure(job.id, str(e))
         except Exception as inner_e:
             logger.error(f"标记 TTS job 失败时出错: job_id={job.id}, error={inner_e}")
-    # 合成失败且已扣积分 → 退费
-    if synthesis_error is not None and _points_deducted > 0 and _points_svc is not None:
-        try:
-            _points_svc.refund_points(user_id, _points_deducted, _points_scene, db, ref_id=job.id)
-        except Exception as refund_err:
-            logger.warning(f"TTS 合失败退积分异常: job_id={job.id}, err={refund_err}")
-
     # 若任务处于 processing 状态（异步模式），触发 Celery 后台轮询
     if job.status.value == "processing":
         # 分段合成任务 vs 普通单段任务
@@ -269,13 +231,6 @@ def synthesize(
                 workflow.process_synthesis_failure(job.id, f"Celery 任务调度失败: {e}")
             except Exception as inner_e:
                 logger.error(f"Celery 调度后标记失败时出错: job_id={job.id}, error={inner_e}")
-            # 调度失败退费
-            if _points_deducted > 0 and _points_svc is not None:
-                try:
-                    _points_svc.refund_points(user_id, _points_deducted, _points_scene, db, ref_id=job.id)
-                except Exception as refund_err:
-                    logger.warning(f"Celery 调度失败退积分异常: job_id={job.id}, err={refund_err}")
-
     return TTSSynthesizeResponse(
         job_id=job.id,
         status=job.status,
@@ -610,31 +565,6 @@ def preview_tts(
     用于前端预览配音效果，限制文本长度 200 字以内。
     支持预设音色和克隆音色：克隆音色传的是 profile UUID，需解析为 CosyVoice voice_id。
     """
-    user_id = authenticated_user.user.id
-    # ── 积分扣点（#1895 P2） ──
-    _points_deducted = 0
-    _points_scene = "ai_voice"
-    _points_svc = PointsService() if settings.points_enabled else None
-    if _points_svc is not None:
-        est_minutes = max(1.0, math.ceil(len(request.text) / 240))
-        _points_deducted = calculate_points_cost(
-            _points_scene,
-            is_member=getattr(authenticated_user.user, "is_member", False),
-            duration_minutes=est_minutes,
-            member_type=getattr(authenticated_user.user, "member_type", None),
-        )
-        _deduct_res = _points_svc.deduct_points(user_id, _points_deducted, _points_scene, db)
-        if not _deduct_res["success"]:
-            raise HTTPException(
-                status_code=402,
-                detail={
-                    "code": "INSUFFICIENT_POINTS",
-                    "message": f"积分不足，需要 {_points_deducted} 积分，当前余额 {_deduct_res['balance']}",
-                    "required": _points_deducted,
-                    "balance": _deduct_res["balance"],
-                },
-            )
-
     # 解析 voice_id：前端可能传 VoiceCloneProfile UUID 或预设音色 ID
     actual_voice_id = request.voice_id
     profile = voice_clone_repo.get(request.voice_id)
@@ -664,12 +594,6 @@ def preview_tts(
             language=getattr(request, "language", "zh-CN"),
         )
     except (CosyVoiceError, ValueError) as e:
-        # 合成失败退费
-        if _points_deducted > 0 and _points_svc is not None:
-            try:
-                _points_svc.refund_points(user_id, _points_deducted, _points_scene, db)
-            except Exception as refund_err:
-                logger.warning(f"TTS 预览失败退积分异常: {refund_err}")
         if isinstance(e, CosyVoiceError):
             raise HTTPException(status_code=status.HTTP_502_BAD_GATEWAY, detail=f"TTS 合成失败: {e}") from e
         raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=str(e)) from e

apps/api/app/api/routes/upload.py

@@ -191,6 +191,23 @@ def _find_duplicate_asset(
     return None
 
 
+
+def _get_existing_asset_url(existing: Any, storage_service: Any) -> str:
+    """安全获取已存在素材的公网 URL，兼容 domain Asset（无 file_url 字段）和 ORM model。"""
+    # Domain Asset 只有 storage_key 字段；ORM model 有 file_url 但存的也是 storage_key
+    key = ""
+    for attr in ("storage_key", "file_url"):
+        v = getattr(existing, attr, None)
+        if v:
+            key = v
+            break
+    if not key:
+        return ""
+    try:
+        return storage_service.get_url(key) or ""
+    except Exception:
+        return ""
+
 def _create_pending_asset(
     asset_repository,
     project_id,
@@ -290,6 +307,43 @@ def _submit_ingest_job(
     return job
 
 
+def _find_active_ingest_job(ingest_job_repository: Any, asset_id: str) -> Any | None:
+    """查询 asset 上是否存在"仍在跑或已成功"的 ingest job（FAILED 视为不存在，需重提）。"""
+    if not asset_id:
+        return None
+    find = getattr(ingest_job_repository, "find_by_asset_id", None)
+    if not callable(find):
+        # 旧仓储未实现 find_by_asset_id，无法判断 → 保守返回 None（走正常流程，
+        # _submit_ingest_job 自身有数据库唯一约束/幂等兜底，不会重复建 job）
+        return None
+    try:
+        return find(asset_id)
+    except Exception:  # noqa: BLE001
+        logger.warning("[upload] find_by_asset_id 查询失败，按无 job 处理: asset=%s", asset_id, exc_info=True)
+        return None
+
+
+def _is_true_duplicate(existing_asset: Asset, ingest_job_repository: Any) -> tuple[bool, Any | None]:
+    """判断 `existing_asset` 是真重复（应短路返 duplicated）还是占位（应补提 ingest）。
+
+    返回 (is_duplicate, existing_job):
+    - READY 素材：真重复，job 可能为 None（已就绪不需要 job_id）
+    - PROCESSING/UPLOADING 且已有在跑/已完成 ingest job：幂等重试，真重复，job 返回给前端轮询
+    - PROCESSING/UPLOADING 且无 job：prepare 建的占位 / 之前 ingest 创建失败 → 非重复，需补提 ingest
+    - ERROR/DELETED：非重复（允许重新上传覆盖）
+    """
+    status = getattr(existing_asset, "status", None)
+    if status == AssetStatus.READY:
+        return True, None
+    if status in (AssetStatus.PROCESSING, AssetStatus.UPLOADING):
+        job = _find_active_ingest_job(ingest_job_repository, existing_asset.id)
+        if job is not None:
+            return True, job
+        return False, None
+    # ERROR / DELETED / 其它：走正常流程重新 ingest
+    return False, None
+
+
 @router.post("/direct/prepare", response_model=DirectUploadPrepareResponse)
 async def prepare_direct_upload(
     request: DirectUploadPrepareRequest,
@@ -353,6 +407,7 @@ async def prepare_direct_upload(
                 duplicated=True,
                 skip_transfer=True,
                 asset_id=existing.id,
+                url=_get_existing_asset_url(existing, storage_service),
             )
 
     file_id = uuid4().hex[:8]
@@ -406,6 +461,7 @@ async def prepare_direct_upload(
         duplicated=False,
         skip_transfer=False,
         asset_id=pending_asset_id,
+        url="",
     )
 
 
@@ -444,12 +500,25 @@ async def complete_direct_upload(
         file_size=request.file_size,
     )
     if existing is not None:
-        return DirectUploadCompleteResponse(
-            storage_key=existing.storage_key,
-            ingest_job_id="",
-            duplicated=True,
-            asset_id=existing.id,
-            url=storage_service.get_url(existing.storage_key),
+        is_dup, existing_job = _is_true_duplicate(existing, ingest_job_repository)
+        if is_dup:
+            logger.info(
+                "[upload] complete 幂等命中真重复: asset=%s status=%s job=%s",
+                existing.id,
+                getattr(existing, "status", None),
+                getattr(existing_job, "id", None),
+            )
+            return DirectUploadCompleteResponse(
+                storage_key=existing.storage_key,
+                ingest_job_id=getattr(existing_job, "id", "") or "",
+                duplicated=True,
+                asset_id=existing.id,
+                url=storage_service.get_url(existing.storage_key),
+            )
+        logger.info(
+            "[upload] complete 命中占位 asset（status=%s 无 ingest job），继续补提 ingest: asset=%s",
+            getattr(existing, "status", None),
+            existing.id,
         )
 
     try:
@@ -479,14 +548,24 @@ async def complete_direct_upload(
     )
     # Issue #1776: 计数由 asset_repository.create() 自动维护
 
-    job = _submit_ingest_job(
-        project_id=request.project_id,
-        library_id=request.library_id,
-        storage_key=normalized_key,
-        ingest_job_repository=ingest_job_repository,
-        file_hash=request.file_hash,
-        asset_id=pending_asset.id,
-    )
+    # 幂等保护：补提占位场景下可能已有 job（极端竞态），先查一次
+    existing_job = _find_active_ingest_job(ingest_job_repository, pending_asset.id)
+    if existing_job is not None:
+        logger.info(
+            "[upload] complete 补提时发现 job 已存在（竞态/并发重试），复用: asset=%s job=%s",
+            pending_asset.id,
+            existing_job.id,
+        )
+        job = existing_job
+    else:
+        job = _submit_ingest_job(
+            project_id=request.project_id,
+            library_id=request.library_id,
+            storage_key=normalized_key,
+            ingest_job_repository=ingest_job_repository,
+            file_hash=request.file_hash,
+            asset_id=pending_asset.id,
+        )
     return DirectUploadCompleteResponse(
         storage_key=normalized_key,
         ingest_job_id=job.id,
@@ -533,12 +612,27 @@ async def upload_asset(
         file_size=0,
     )
     if existing is not None:
-        return UploadAssetResponse(
-            storage_key=existing.storage_key,
-            ingest_job_id="",
-            url="",
-            duplicated=True,
-            asset_id=existing.id,
+        is_dup, existing_job = _is_true_duplicate(existing, ingest_job_repository)
+        if is_dup:
+            logger.info(
+                "[upload] multipart 幂等命中真重复: asset=%s status=%s job=%s",
+                existing.id,
+                getattr(existing, "status", None),
+                getattr(existing_job, "id", None),
+            )
+            return UploadAssetResponse(
+                storage_key=existing.storage_key,
+                ingest_job_id=getattr(existing_job, "id", "") or "",
+                url=storage_service.get_url(existing.storage_key)
+                if getattr(existing, "status", None) == AssetStatus.READY
+                else "",
+                duplicated=True,
+                asset_id=existing.id,
+            )
+        logger.info(
+            "[upload] multipart 命中占位 asset（status=%s 无 ingest job），继续补提 ingest: asset=%s",
+            getattr(existing, "status", None),
+            existing.id,
         )
 
     file_id = uuid4().hex[:8]
@@ -574,14 +668,23 @@ async def upload_asset(
     )
     # Issue #1776: 计数由 asset_repository.create() 自动维护
 
-    job = _submit_ingest_job(
-        project_id=project_id,
-        library_id=library_id,
-        storage_key=storage_key,
-        ingest_job_repository=ingest_job_repository,
-        file_hash=file_hash,
-        asset_id=pending_asset.id,
-    )
+    existing_job = _find_active_ingest_job(ingest_job_repository, pending_asset.id)
+    if existing_job is not None:
+        logger.info(
+            "[upload] multipart 补提时发现 job 已存在（竞态/并发重试），复用: asset=%s job=%s",
+            pending_asset.id,
+            existing_job.id,
+        )
+        job = existing_job
+    else:
+        job = _submit_ingest_job(
+            project_id=project_id,
+            library_id=library_id,
+            storage_key=storage_key,
+            ingest_job_repository=ingest_job_repository,
+            file_hash=file_hash,
+            asset_id=pending_asset.id,
+        )
 
     return UploadAssetResponse(
         storage_key=storage_key,

apps/api/app/api/routes/viral_video.py

@@ -0,0 +1,957 @@
+"""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
+"""
+
+from __future__ import annotations
+
+import logging
+
+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,
+    CreditsFormulaBreakdown,
+    EstimateCreditsRequest,
+    EstimateCreditsResponse,
+    GenerateCopyRequest,
+    RetryViralVideoRequest,
+    StyleTemplateListResponse,
+    StyleTemplateResponse,
+    ViralVideoHistoryResponse,
+    ViralVideoJobResponse,
+)
+from fastapi import APIRouter, Depends, HTTPException, WebSocket, WebSocketDisconnect
+from sqlalchemy.orm import Session
+
+from packages.adapters.sqlalchemy_impl.viral_video_repository import (
+    SQLAlchemyViralVideoJobRepository,
+    SQLAlchemyViralVideoStyleTemplateRepository,
+)
+from packages.domain.viral_video import ViralVideoStatus
+
+logger = logging.getLogger(__name__)
+
+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,
+        user_id=job.user_id,
+        images=job.images,
+        industry=job.industry,
+        target_customer=job.target_customer,
+        persona_id=job.persona_id,
+        viral_structure=job.viral_structure,
+        marketing_purpose=job.marketing_purpose,
+        bgm_preference=job.bgm_preference,
+        duration=job.duration or 15,
+        user_copy_text=job.user_copy_text,
+        fusion_level=job.fusion_level,
+        reference_audio_path=job.reference_audio_path,
+        reference_video_url=job.reference_video_url,
+        style_strength=job.style_strength,
+        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,
+        video_resolution=getattr(job, "video_resolution", "720p") or "720p",
+        credits_prepaid=float(getattr(job, "credits_prepaid", 0) or 0),
+        credits_cost=float(getattr(job, "credits_cost", 0) or 0),
+        error_msg=job.error_msg,
+        retry_count=job.retry_count,
+        started_at=job.started_at,
+        completed_at=job.completed_at,
+        created_at=job.created_at,
+        updated_at=job.updated_at,
+    )
+
+
+def _get_job_repo(session: Session) -> SQLAlchemyViralVideoJobRepository:
+    return SQLAlchemyViralVideoJobRepository(session)
+
+
+def _get_style_repo(session: Session) -> SQLAlchemyViralVideoStyleTemplateRepository:
+    return SQLAlchemyViralVideoStyleTemplateRepository(session)
+
+
+# ── Endpoints ────────────────────────────────────────────────────────────
+
+
+@router.post("/generate", response_model=ViralVideoJobResponse)
+def create_viral_video(
+    request: CreateViralVideoRequest,
+    authenticated_user: AuthenticatedUser = Depends(get_current_user),
+    session: Session = Depends(get_db_session),
+) -> ViralVideoJobResponse:
+    """创建爆款视频任务，入队 Celery 编排器。"""
+    from packages.domain.viral_video import ViralVideoJob
+
+    repo = _get_job_repo(session)
+
+    # 创建领域实体
+    job = ViralVideoJob(
+        user_id=authenticated_user.user.id,
+        images=list(request.images),
+        industry=request.industry,
+        target_customer=request.target_customer,
+        persona_id=request.persona_id,
+        viral_structure=request.viral_structure,
+        marketing_purpose=request.marketing_purpose,
+        bgm_preference=request.bgm_preference,
+        duration=request.duration or 15,
+        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 "",
+        video_resolution=getattr(request, "video_resolution", "720p") or "720p",
+        copy_result=None,
+    )
+
+    # 持久化
+    repo.save(job)
+
+    # 入队 Celery 任务
+    try:
+        celery_app.send_task("worker.run_viral_video_pipeline", args=[job.id])
+        logger.info("[爆款视频] 任务已入队: job_id=%s user_id=%s", job.id, job.user_id)
+    except Exception as e:
+        logger.error("[爆款视频] 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("/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 "",
+        video_resolution=getattr(request, "video_resolution", "720p") or "720p",
+        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.video_resolution = getattr(request, "video_resolution", "") or job.video_resolution or "720p"
+
+    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）")
+
+    # 积分预扣（已扣过/重试任务跳过）
+    from app.config import settings as _settings
+
+    if _settings.points_enabled:
+        already_paid = (float(getattr(job, "credits_prepaid", 0) or 0) > 0) or (
+            float(getattr(job, "credits_cost", 0) or 0) > 0
+        )
+        if not already_paid:
+            from packages.domain.points_rules import calculate_viral_video_credits, resolve_video_dimensions
+            from packages.domain.points_service import PointsService
+
+            w, h = resolve_video_dimensions(
+                getattr(job, "video_resolution", "720p") or "720p",
+                job.video_ratio or "9:16",
+            )
+            est_credits = calculate_viral_video_credits(
+                int(job.duration or 15), w, h, job.video_model or "seedance-2.5"
+            )
+            svc = PointsService()
+            res = svc.deduct_viral_video(authenticated_user.user.id, est_credits, job.id, session)
+            if not res.get("success"):
+                balance = res.get("balance", 0)
+                raise HTTPException(
+                    status_code=402,
+                    detail={
+                        "code": "INSUFFICIENT_POINTS",
+                        "message": f"积分不足，需要 {est_credits} 积分，当前余额 {balance}",
+                        "required": est_credits,
+                        "balance": balance,
+                    },
+                )
+            job.credits_prepaid = est_credits
+            job.credits_transaction_id = res.get("transaction_id", "") or ""
+            repo.update(job)
+
+    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.post("/estimate-credits", response_model=EstimateCreditsResponse)
+def estimate_credits(
+    request: EstimateCreditsRequest,
+    authenticated_user: AuthenticatedUser = Depends(get_current_user),
+) -> EstimateCreditsResponse:
+    """爆款视频积分预估（纯计算，不扣费、不创建任务）。
+
+    返回 estimated_credits 与 formula_breakdown（tokens / video_cost / fixed_cost /
+    profit_multiplier / model_price / width / height / fps），便于前端展示计费明细。
+    同时兼容前端传 model 或 video_model、resolution 或 video_resolution、ratio 或 video_ratio。
+    """
+    from packages.domain.points_rules import (
+        calculate_viral_video_credits_with_breakdown,
+        resolve_video_dimensions,
+    )
+
+    model = (request.model or "").strip() or "seedance-2.5"
+    resolution = (request.resolution or "").strip() or "720p"
+    ratio = (request.ratio or "").strip() or "9:16"
+    duration = int(request.duration or 15)
+
+    w, h = resolve_video_dimensions(resolution, ratio)
+    credits, bd = calculate_viral_video_credits_with_breakdown(
+        duration, w, h, model,
+    )
+    breakdown = CreditsFormulaBreakdown(**bd)
+    return EstimateCreditsResponse(estimated_credits=credits, formula_breakdown=breakdown)
+
+
+@router.get("/history", response_model=ViralVideoHistoryResponse)
+def list_viral_video_history(
+    limit: int = 50,
+    offset: int = 0,
+    authenticated_user: AuthenticatedUser = Depends(get_current_user),
+    session: Session = Depends(get_db_session),
+) -> ViralVideoHistoryResponse:
+    """获取用户的爆款视频历史列表。"""
+    repo = _get_job_repo(session)
+    jobs = repo.list_by_user(authenticated_user.user.id, limit=limit, offset=offset)
+    items = [_to_response(j) for j in jobs]
+    return ViralVideoHistoryResponse(items=items, total=len(items))
+
+
+@router.get("/style-templates", response_model=StyleTemplateListResponse)
+def list_style_templates(
+    session: Session = Depends(get_db_session),
+) -> StyleTemplateListResponse:
+    """获取风格模板列表。"""
+    repo = _get_style_repo(session)
+    templates = repo.list_all()
+    items = [
+        StyleTemplateResponse(
+            id=t["id"],
+            name=t["name"],
+            description=t["description"],
+            thumbnail_url=t["thumbnail_url"],
+            style_config=t["style_config"],
+        )
+        for t in templates
+    ]
+    return StyleTemplateListResponse(items=items)
+
+
+@router.get("/{job_id}", response_model=ViralVideoJobResponse)
+def get_viral_video_job(
+    job_id: str,
+    authenticated_user: AuthenticatedUser = Depends(get_current_user),
+    session: Session = Depends(get_db_session),
+) -> ViralVideoJobResponse:
+    """查询爆款视频任务状态。"""
+    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="无权查看此任务")
+    return _to_response(job)
+
+
+@router.post("/{job_id}/retry", response_model=ViralVideoJobResponse)
+def retry_viral_video_job(
+    job_id: str,
+    request: RetryViralVideoRequest | None = None,
+    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）。
+
+    可选 body (RetryViralVideoRequest)：若传入新的 duration/video_resolution/video_ratio/
+    video_model，会重新预估积分并与原 credits_prepaid 做差额多退少补（不足抛 402 阻止重试）；
+    不传 body 或参数无变化时，保持原参数、原预扣金额不变，仅重置状态并入队。
+    credits_prepaid 为 0 的老任务首次重试会走预扣流程（与 confirm-copy 一致）。
+    """
+    from datetime import datetime, timezone
+
+    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")
+
+    # ── 参数变更检测 + 积分多退少补 ──────────────────────────────────────
+    req = request or RetryViralVideoRequest()
+    new_duration = req.duration
+    new_resolution = (req.video_resolution or "").strip() or None
+    new_ratio = (req.video_ratio or "").strip() or None
+    new_model = (req.video_model or "").strip() or None
+
+    old_duration = int(getattr(job, "duration", 15) or 15)
+    old_resolution = (getattr(job, "video_resolution", "720p") or "720p").strip() or "720p"
+    old_ratio = (getattr(job, "video_ratio", "9:16") or "9:16").strip() or "9:16"
+    old_model = (getattr(job, "video_model", "") or "").strip()
+
+    # 仅当有任意字段传入且值不同才算"参数变更"
+    param_changed = bool(
+        (new_duration is not None and int(new_duration) != old_duration)
+        or (new_resolution is not None and new_resolution != old_resolution)
+        or (new_ratio is not None and new_ratio != old_ratio)
+        or (new_model is not None and new_model != old_model)
+    )
+
+    from app.config import settings as _settings
+
+    need_points_settle = False
+    new_est = 0.0
+    if _settings.points_enabled and param_changed:
+        from packages.domain.points_rules import (
+            calculate_viral_video_credits_with_breakdown,
+            resolve_video_dimensions,
+        )
+
+        eff_dur = int(new_duration if new_duration is not None else old_duration)
+        eff_res = new_resolution if new_resolution is not None else old_resolution
+        eff_ratio = new_ratio if new_ratio is not None else old_ratio
+        eff_model = new_model if new_model is not None else (old_model or "seedance-2.5")
+        w, h = resolve_video_dimensions(eff_res, eff_ratio)
+        new_est, _ = calculate_viral_video_credits_with_breakdown(eff_dur, w, h, eff_model or "seedance-2.5")
+        need_points_settle = True
+
+    # 写入新参数（即使不开 points 也要允许用户重试时改参数）
+    if new_duration is not None:
+        job.duration = max(5, min(30, int(new_duration)))
+    if new_resolution is not None:
+        job.video_resolution = new_resolution
+    if new_ratio is not None:
+        job.video_ratio = new_ratio
+    if new_model is not None:
+        job.video_model = new_model
+
+    if need_points_settle:
+        from packages.domain.points_service import PointsService
+
+        old_prepaid = float(getattr(job, "credits_prepaid", 0) or 0)
+        svc = PointsService()
+        diff = round(new_est - old_prepaid, 2)
+        if abs(diff) >= 0.01:
+            if diff > 0:
+                # 新预扣更多：补扣差额
+                res = svc.deduct_viral_video(authenticated_user.user.id, diff, job.id, session)
+                if not res.get("success"):
+                    balance = res.get("balance", 0)
+                    raise HTTPException(
+                        status_code=402,
+                        detail={
+                            "code": "INSUFFICIENT_POINTS",
+                            "message": f"重试参数变更后需补扣 {diff} 积分，余额不足（当前 {balance}，需 {new_est}）",
+                            "required": new_est,
+                            "balance": balance,
+                            "delta": diff,
+                        },
+                    )
+                job.credits_prepaid = round(old_prepaid + diff, 2)
+                logger.info(
+                    "[爆款视频][retry] 补扣差额 job_id=%s diff=%.2f new_prepaid=%.2f",
+                    job.id, diff, job.credits_prepaid,
+                )
+            else:
+                # 新预扣更少：退还差额
+                refund = round(-diff, 2)
+                txn_id = getattr(job, "credits_transaction_id", "") or ""
+                svc.refund_points(
+                    user_id=authenticated_user.user.id,
+                    amount=refund,
+                    source="viral_video",
+                    db=session,
+                    ref_id=txn_id or job.id,
+                    description="爆款视频重试参数变更退费",
+                )
+                job.credits_prepaid = round(old_prepaid - refund, 2)
+                logger.info(
+                    "[爆款视频][retry] 退还差额 job_id=%s refund=%.2f new_prepaid=%.2f",
+                    job.id, refund, job.credits_prepaid,
+                )
+        # 差额为 0 则不调整
+
+    # 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.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 params_changed=%s",
+            job.id, job.retry_count, is_stale_running, param_changed,
+        )
+    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}")
+        repo.update(job)
+
+    return _to_response(job)
+
+
+@router.post("/{job_id}/confirm-intent", response_model=ViralVideoJobResponse)
+def confirm_intent(
+    job_id: str,
+    request: ConfirmIntentRequest,
+    authenticated_user: AuthenticatedUser = Depends(get_current_user),
+    session: Session = Depends(get_db_session),
+) -> ViralVideoJobResponse:
+    """用户确认/修改 AI 生成的意图文案，恢复流水线。"""
+    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.WAIT_USER_CONFIRM:
+        raise HTTPException(status_code=409, detail="任务当前不在等待确认状态")
+
+    # 更新文案
+    if request.confirmed_copy:
+        job.user_copy_text = request.confirmed_copy
+
+    # 恢复流水线
+    job.resume_from_confirm()
+    repo.update(job)
+
+    # 从断点恢复 Celery 任务
+    try:
+        celery_app.send_task("worker.resume_viral_video_pipeline", args=[job.id])
+        logger.info("[爆款视频] 意图确认，恢复流水线: job_id=%s", job.id)
+    except Exception as e:
+        logger.error("[爆款视频] 恢复流水线失败: %s", e, exc_info=True)
+        job.mark_failed(f"恢复流水线失败: {e}")
+        repo.update(job)
+
+    return _to_response(job)
+
+
+@router.post("/{job_id}/analyze-style", response_model=AnalyzeStyleResponse)
+def analyze_style(
+    job_id: str,
+    request: AnalyzeStyleRequest,
+    authenticated_user: AuthenticatedUser = Depends(get_current_user),
+    session: Session = Depends(get_db_session),
+) -> AnalyzeStyleResponse:
+    """触发参考视频风格分析（独立步骤，可在生成前单独调用）。"""
+    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")
+
+    # 更新参考视频 URL
+    job.reference_video_url = request.reference_video_url
+    if request.style_template_id:
+        job.style_template_id = request.style_template_id
+    repo.update(job)
+
+    # 入队风格分析任务
+    try:
+        celery_app.send_task("worker.run_video_style_analysis", args=[job.id])
+        logger.info("[爆款视频] 风格分析入队: job_id=%s", job.id)
+    except Exception as e:
+        logger.error("[爆款视频] 风格分析入队失败: %s", e, exc_info=True)
+
+    return AnalyzeStyleResponse(
+        job_id=job.id,
+        status="analyzing",
+        style_guide=None,
+    )
+
+
+# ── WebSocket 进度推送 ──────────────────────────────────────────────────
+
+
+def _ws_authenticate_user(token: str):
+    """从 token 字符串解析用户（复用 HTTP Bearer 的解码 + 黑名单逻辑）。
+
+    WebSocket 握手阶段不能发自定义 Authorization header，
+    因此统一通过 query 参数 ``?token=...`` 传 JWT。
+    """
+    from app.auth import _decode_user_token
+    from app.dependencies import get_user_repository
+
+    if not token:
+        return None
+    try:
+        payload = _decode_user_token(token)
+    except Exception:
+        return None
+    user_id = payload.get("sub")
+    if not isinstance(user_id, str) or not user_id:
+        return None
+    # 同步场景下手动拉 repository 实例
+    from app.db import SessionLocal
+
+    session = SessionLocal()
+    try:
+        user_repo = get_user_repository(session)
+        user = user_repo.find_by_id(user_id)
+        return user
+    finally:
+        session.close()
+
+
+async def _run_pubsub_forwarder(
+    websocket, redis_lib, settings, job_id: str
+) -> None:  # pragma: no cover - integration tested (real Redis + thread)
+    """订阅 Redis 频道并把消息桥接到 WebSocket，终态消息后自动关闭。
+
+    该函数封装了线程 + asyncio.Queue 桥接逻辑，在单测中可被整体替换为桩，
+    避免引入真实 Redis 与线程调度的不确定性。
+    """
+    import asyncio
+    import json
+    import threading
+
+    r = redis_lib.from_url(settings.REDIS_URL, decode_responses=True)
+    pubsub = r.pubsub(ignore_subscribe_messages=True)
+    channel = f"viral_video:{job_id}"
+    pubsub.subscribe(channel)
+
+    loop = asyncio.get_running_loop()
+    queue: asyncio.Queue = asyncio.Queue(maxsize=64)
+    stop_event = asyncio.Event()
+
+    def _reader() -> None:
+        try:
+            while not stop_event.is_set():
+                msg = pubsub.get_message(timeout=0.5)
+                if msg is None or msg.get("type") != "message":
+                    continue
+                raw = msg.get("data")
+                if not isinstance(raw, str):
+                    continue
+                try:
+                    payload = json.loads(raw)
+                except Exception:
+                    payload = {"type": "viral_video:progress", "data": {"raw": raw}}
+                loop.call_soon_threadsafe(queue.put_nowait, payload)
+                if payload.get("type") in ("viral_video:completed", "viral_video:failed"):
+                    loop.call_soon_threadsafe(stop_event.set)
+                    break
+        except Exception as e:
+            logger.warning("[爆款视频WS] pubsub reader 异常退出: %s", e)
+            loop.call_soon_threadsafe(stop_event.set)
+
+    try:
+        reader_thread = threading.Thread(target=_reader, name=f"viral-video-ws-{job_id}", daemon=True)
+        reader_thread.start()
+
+        while not stop_event.is_set():
+            try:
+                payload = await asyncio.wait_for(queue.get(), timeout=1.0)
+            except asyncio.TimeoutError:
+                continue
+            try:
+                await websocket.send_json(payload)
+            except Exception:
+                break
+            if payload.get("type") in ("viral_video:completed", "viral_video:failed"):
+                break
+    except WebSocketDisconnect:
+        logger.info("[爆款视频WS] 客户端断开: job_id=%s", job_id)
+    except Exception as e:
+        logger.error("[爆款视频WS] 转发异常: %s", e, exc_info=True)
+        try:
+            await websocket.send_json({"type": "viral_video:error", "message": f"服务异常: {e}"})
+        except Exception:
+            pass
+    finally:
+        stop_event.set()
+        try:
+            pubsub.unsubscribe(channel)
+            pubsub.close()
+        except Exception:
+            pass
+        try:
+            r.close()
+        except Exception:
+            pass
+        try:
+            await websocket.close()
+        except Exception:
+            pass
+
+
+@router.websocket("/ws/{job_id}")
+async def viral_video_websocket(websocket: WebSocket, job_id: str) -> None:
+    """WebSocket 桥接：订阅 Redis `viral_video:{job_id}` 频道并转发给前端。
+
+    认证：通过 ``?token=<jwt>`` query 参数传 JWT（浏览器 WS 握手不支持自定义 header）。
+    事件类型：
+      - viral_video:progress    中间进度（progress: 0-100）
+      - viral_video:wait_user   等待用户确认意图文案
+      - viral_video:completed   任务完成（data.video_url）
+      - viral_video:failed      任务失败（data.error）
+      - viral_video:error       服务端错误（如鉴权失败 / job 不存在 / 无权限）
+    """
+
+    import redis as redis_lib
+    from app.config import settings
+
+    # ── 1. 鉴权 ──────────────────────────────────────────────────────
+    token = websocket.query_params.get("token", "")
+    user = _ws_authenticate_user(token)
+    if user is None:
+        await websocket.close(code=4401, reason="Unauthorized")
+        return
+
+    # ── 2. 校验 job 归属 ─────────────────────────────────────────────
+    from app.db import SessionLocal
+
+    session = SessionLocal()
+    try:
+        job_repo = SQLAlchemyViralVideoJobRepository(session)
+        job = job_repo.get(job_id)
+        if job is None:
+            await websocket.close(code=4404, reason="Job not found")
+            return
+        if job.user_id != user.id:
+            await websocket.close(code=4403, reason="Forbidden")
+            return
+    finally:
+        session.close()
+
+    await websocket.accept()
+
+    # ── 3. 发送一条初始状态（前端连接后立即拿到当前进度） ────────────
+    try:
+        session = SessionLocal()
+        job_repo = SQLAlchemyViralVideoJobRepository(session)
+        job = job_repo.get(job_id)
+        if job is not None:
+            status_val = job.status.value if hasattr(job.status, "value") else str(job.status)
+            initial = {
+                "type": "viral_video:progress",
+                "job_id": job_id,
+                "stage": _stage_from_status(job),
+                "progress": _estimate_progress(job),
+                "message": _initial_message(job),
+                "data": {"status": status_val},
+            }
+            await websocket.send_json(initial)
+            # 已经终态 → 再发一条终态事件后立即关闭，避免占连接
+            if job.is_terminal:
+                is_completed = status_val == "completed"
+                terminal_type = "viral_video:completed" if is_completed else "viral_video:failed"
+                terminal_data = (
+                    {"video_url": job.result_video_url or ""} if is_completed else {"error": job.error_msg or ""}
+                )
+                await websocket.send_json(
+                    {
+                        "type": terminal_type,
+                        "job_id": job_id,
+                        "stage": "",
+                        "progress": 100 if is_completed else 0,
+                        "message": "视频生成完成" if is_completed else "任务失败",
+                        "data": terminal_data,
+                    }
+                )
+                await websocket.close()
+                return
+        session.close()
+    except Exception as e:
+        logger.warning("[爆款视频WS] 发送初始状态失败: %s", e)
+        try:
+            session.close()
+        except Exception:
+            pass
+
+    # ── 4. 订阅 Redis 频道并转发 ─────────────────────────────────────
+    # redis-py 的 pubsub 是同步阻塞的，放到线程里跑，通过 asyncio.Queue 桥接到 event loop。
+    # 该段依赖真实 Redis + 线程调度，属于集成测试范围，单测通过桩替换。
+    await _run_pubsub_forwarder(websocket, redis_lib, settings, job_id)
+
+
+def _job_status(job) -> str:
+    return job.status.value if hasattr(job.status, "value") else str(job.status)
+
+
+# 初始快照的 stage 推断：领域对象不持久化 stage，
+# 只能根据 status 给一个占位，后续 worker 推送的真实进度事件会覆盖。
+_STATUS_STAGE = {
+    "pending": "",
+    "running": "",
+    "image_analyzed": "image_analysis",
+    "copy_generated": "review",
+    "wait_user_confirm": "intent_parsing",
+    "completed": "uploading",
+    "failed": "",
+    "cancelled": "",
+}
+
+_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,
+    "cancelled": 0.0,
+}
+
+_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",
+    "cancelled": "任务已取消",
+}
+
+
+def _stage_from_status(job) -> str:
+    return _STATUS_STAGE.get(_job_status(job), "")
+
+
+def _estimate_progress(job) -> float:
+    """根据 status 粗略估算百分比（0-100），用于连接初始快照；
+    连接建立后由 Redis 推送的真实事件持续更新。
+    """
+    return _STATUS_PROGRESS.get(_job_status(job), 5.0)
+
+
+def _initial_message(job) -> str:
+    """给新连接的前端一个可读的初始状态文案。"""
+    status_val = _job_status(job)
+    if status_val == "failed" and job.error_msg:
+        return f"任务失败: {job.error_msg}"
+    return _STATUS_MESSAGE.get(status_val, "任务准备中")

apps/api/app/core/task_enqueue.py

@@ -6,7 +6,7 @@ from app.core.celery_app import celery_app
 logger = logging.getLogger(__name__)
 
 # ── 限流阈值常量（全系统统一管理，不要在业务代码里硬编码） ──
-USER_PENDING_LIMIT = 3  # 单用户 pending 上限
+USER_PENDING_LIMIT = 20  # 单用户 pending 上限（#2098: 从 3 提到 20，支持批量任务自动排队）
 GLOBAL_PENDING_LIMIT = 20  # 全局 pending 上限
 WORKER_CONCURRENCY = 4  # worker 渲染并发数（infra/docker/compose.yml WORKER_CONCURRENCY 默认值）
 
@@ -154,19 +154,18 @@ def check_queue_limits(
     user_pending_limit: int = USER_PENDING_LIMIT,
     global_pending_limit: int = GLOBAL_PENDING_LIMIT,
 ) -> None:
-    """检查队列限流（预检查用，任务创建前调用），超限抛对应异常。
+    """检查队列限流（预检查用，任务创建前调用）。
 
-    边界语义：>= 上限即拒绝（达到上限就不能再加新任务）。
+    #2098 语义变更：用户级限流改为软提示，不再抛异常拒绝；仅全局硬上限抛 GlobalQueueFull。
 
     Args:
-        user_id: 用户 ID
+        user_id: 用户 ID（保留参数，当前不做用户级硬拒）
         generation_task_repository: 任务仓储
-        user_pending_limit: 单用户 pending 上限，默认 USER_PENDING_LIMIT
+        user_pending_limit: 单用户 pending 上限（保留，当前未硬拒）
         global_pending_limit: 全局 pending 上限，默认 GLOBAL_PENDING_LIMIT
 
     Raises:
-        GlobalQueueFull: 全局超限时抛出（优先级更高，先查全局）
-        UserPendingLimitExceeded: 用户超限时抛出
+        GlobalQueueFull: 全局超限时抛出
     """
     # 先查全局（系统级保护优先级更高）
     global_pending = generation_task_repository.count_pending_total()
@@ -179,17 +178,9 @@ def check_queue_limits(
         )
         raise GlobalQueueFull(pending_count=global_pending, limit=global_pending_limit)
 
-    # 再查用户级
-    if user_id:
-        user_pending = generation_task_repository.count_pending_by_user(user_id)
-        if user_pending >= user_pending_limit:
-            logger.warning(
-                "[队列限流] 用户 pending 任务数超限: user_id=%s, count=%d/%d",
-                user_id,
-                user_pending,
-                user_pending_limit,
-            )
-            raise UserPendingLimitExceeded(user_id=user_id, pending_count=user_pending, limit=user_pending_limit)
+    # #2098: 用户级限流改为软提示，不在预检查阶段拒绝（超额任务仍入队排队）。
+    # 真正的系统保护由全局 GLOBAL_PENDING_LIMIT 硬上限承担。
+    # UserPendingLimitExceeded 保留以兼容历史 import/except，但预检查与 safe_enqueue 均不再 raise。
 
 
 def _mark_task_failed_safely(
@@ -246,7 +237,6 @@ def safe_enqueue_generation_task(
 
     Raises:
         GlobalQueueFull: 全局 pending 超限时抛出，任务会被标记为 failed
-        UserPendingLimitExceeded: 用户 pending 超限时抛出，任务会被标记为 failed
     """
     # ── 入队前检查：任务已是 pending，用 > 判断（包含当前任务） ──
 
@@ -263,19 +253,18 @@ def safe_enqueue_generation_task(
         _mark_task_failed_safely(task, generation_task_repository, log_prefix, str(exc))
         raise exc
 
-    # 用户级限流检查（传了 user_id 才做）
+    # Bug B #2098: 用户级限流改为软提示，不再硬拒；所有任务都入队等待 worker 自然消费。
+    # user_pending_limit 作为兜底阈值保留（默认 20），达到时打 warning 日志但仍入队，
+    # 避免极端情况下恶意用户无限堆积任务。真正的系统保护由全局 GLOBAL_PENDING_LIMIT 承担。
     if user_id:
         user_pending = generation_task_repository.count_pending_by_user(user_id)
         if user_pending > user_pending_limit:
             logger.warning(
-                "[队列限流] 用户 pending 任务数超限(入队前): user_id=%s, count=%d/%d",
+                "[队列限流] 用户 pending 任务数超过软上限(入队): user_id=%s, count=%d/%d, 仍允许入队排队",
                 user_id,
                 user_pending,
                 user_pending_limit,
             )
-            exc = UserPendingLimitExceeded(user_id=user_id, pending_count=user_pending, limit=user_pending_limit)
-            _mark_task_failed_safely(task, generation_task_repository, log_prefix, str(exc))
-            raise exc
 
     # ── 发送 Celery 任务 ──
     try:
@@ -317,16 +306,18 @@ def safe_enqueue_generation_task(
     user_after = generation_task_repository.count_pending_by_user(user_id) if user_id else 0
 
     global_over = global_after > global_pending_limit
-    user_over = bool(user_id and user_after > user_pending_limit)
-
-    if global_over or user_over:
-        if global_over:
-            reason = f"全局 pending 超限(入队后): {global_after}/{global_pending_limit}"
-            exc = GlobalQueueFull(pending_count=global_after, limit=global_pending_limit)
-        else:
-            reason = f"用户 pending 超限(入队后): {user_after}/{user_pending_limit}"
-            exc = UserPendingLimitExceeded(user_id=user_id, pending_count=user_after, limit=user_pending_limit)
+    # Bug B #2098: 用户超限仅日志警告，不回滚任务
+    if user_id and user_after > user_pending_limit:
+        logger.warning(
+            "[队列限流] 用户 pending 超软上限(入队后): user_id=%s, count=%d/%d",
+            user_id,
+            user_after,
+            user_pending_limit,
+        )
 
+    if global_over:
+        reason = f"全局 pending 超限(入队后): {global_after}/{global_pending_limit}"
+        exc = GlobalQueueFull(pending_count=global_after, limit=global_pending_limit)
         logger.warning(
             "[队列限流] %s, task_id=%s, user_id=%s — 回滚状态为 failed",
             reason,

apps/api/app/db.py

@@ -7,9 +7,9 @@ from packages.adapters.sqlalchemy_impl import (
 )
 from packages.adapters.sqlalchemy_impl.schema_guard import assert_auto_create_schema_allowed
 
-ensure_database_exists(settings.DATABASE_URL)
+ensure_database_exists(settings.effective_database_url)
 engine, SessionLocal = build_session_factory(
-    settings.DATABASE_URL,
+    settings.effective_database_url,
     pool_size=settings.DATABASE_POOL_SIZE,
     max_overflow=settings.DATABASE_MAX_OVERFLOW,
     pool_timeout=settings.DATABASE_POOL_TIMEOUT,

apps/api/app/dependencies.py

@@ -56,7 +56,7 @@ from packages.adapters.sqlalchemy_impl.voice_library_repository import (
 from packages.ports.tag_repository import TagRepository
 from packages.ports.user_repository import UserRepository
 
-_engine, _SessionLocal = build_session_factory(settings.DATABASE_URL)
+_engine, _SessionLocal = build_session_factory(settings.effective_database_url)
 
 
 def get_db_session() -> Generator[Session, None, None]:

apps/api/app/schemas/points.py

@@ -13,9 +13,9 @@ from pydantic import BaseModel, Field
 class PointsBalanceResponse(BaseModel):
     """积分余额 + 会员状态"""
 
-    balance: int = Field(..., description="当前积分余额")
-    total_earned: int = Field(..., description="累计获得积分")
-    total_spent: int = Field(..., description="累计消耗积分")
+    balance: float = Field(..., description="当前积分余额")
+    total_earned: float = Field(..., description="累计获得积分")
+    total_spent: float = Field(..., description="累计消耗积分")
     is_member: bool = Field(default=False, description="是否付费会员")
     member_type: Optional[str] = Field(None, description="会员类型: monthly/quarterly/yearly")
     member_expires_at: Optional[datetime] = Field(None, description="会员到期时间")
@@ -30,8 +30,8 @@ class PointsTransactionItem(BaseModel):
     id: str
     type: str = Field(..., description="类型: add/deduct")
     source: str = Field(..., description="来源场景")
-    amount: int
-    balance_after: int
+    amount: float
+    balance_after: float
     description: str = ""
     ref_id: str = ""
     created_at: Optional[str] = None
@@ -99,9 +99,9 @@ class PointsCheckResponse(BaseModel):
     """消费前余额检查响应"""
 
     allowed: bool
-    required_points: int
-    current_balance: int
-    remaining_after: int
+    required_points: float
+    current_balance: float
+    remaining_after: float
     is_free_quota: bool = False
 
 
@@ -112,7 +112,7 @@ class PointsDeductRequest(BaseModel):
     """积分扣减请求"""
 
     scene_key: str
-    amount: int
+    amount: float
     description: Optional[str] = ""
     ref_id: Optional[str] = ""
 
@@ -170,7 +170,7 @@ class MembershipStatusResponse(BaseModel):
     is_member: bool
     member_type: Optional[str] = None
     member_expires_at: Optional[datetime] = None
-    points_balance: int
+    points_balance: float
     max_resolution: str = Field(
         default="1080p",
         description="可用最高分辨率: 720p(free) / 1080p(paid)",

apps/api/app/schemas/upload.py

@@ -29,6 +29,8 @@ class DirectUploadPrepareResponse(BaseModel):
     duplicated: bool = False
     skip_transfer: bool = False
     asset_id: str = ""
+    # duplicated=true 时填充已存在素材的公网 URL，前端可直接用而不必再调 complete
+    url: str = Field(default="", description="duplicated=true 时已存在素材的公网 URL")
 
 
 class DirectUploadCompleteRequest(BaseModel):

apps/api/app/schemas/viral_video.py

@@ -0,0 +1,319 @@
+"""爆款视频 API schemas (v1.6 单次 Seedance 出片版)。"""
+
+from __future__ import annotations
+
+from datetime import datetime
+
+from pydantic import BaseModel, Field, field_validator
+
+# -- 枚举常量 --
+
+VALID_FUSION_LEVELS = ("ai_full", "full_ai", "ai_polish", "user_primary")
+VALID_STYLE_STRENGTHS = ("light", "medium", "strict")
+VALID_STAGES = (
+    "image_analysis",
+    "video_analysis",
+    "intent_parsing",
+    "script_generation",
+    "review",
+    "tts",
+    "rendering",
+    "uploading",
+)
+VALID_VIDEO_RATIOS = ("9:16", "16:9", "1:1", "4:3", "3:4", "21:9")
+VALID_DURATIONS = (5, 10, 15, 20, 25, 30)
+VALID_VIDEO_RESOLUTIONS = ("480p", "720p", "1080p", "普清", "高清", "超清")
+
+
+# -- 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 --
+
+
+class CreateViralVideoRequest(BaseModel):
+    """旧接口：一键创建（保留兼容）。"""
+
+    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 = ""
+    video_resolution: str = "720p"
+
+    @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 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 = ""
+    video_resolution: str = "720p"
+    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 = ""
+    video_resolution: str = "720p"
+
+    @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）。"""
+
+    confirmed_copy: str = ""
+    adjustments: str = ""
+
+
+class AnalyzeStyleRequest(BaseModel):
+    reference_video_url: str = Field(..., description="参考视频 URL")
+    style_template_id: str = ""
+
+
+# -- 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）。"""
+
+    id: str
+    user_id: str
+    images: list[str] = Field(default_factory=list)
+    industry: str = ""
+    target_customer: str = ""
+    persona_id: str = ""
+    viral_structure: str = ""
+    marketing_purpose: str = ""
+    bgm_preference: str = ""
+    duration: int = 15
+    user_copy_text: str = ""
+    fusion_level: str = "ai_polish"
+    reference_audio_path: str = ""
+    reference_video_url: str = ""
+    style_strength: str = "medium"
+    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 = ""
+    video_resolution: str = "720p"
+    credits_prepaid: float = 0.0
+    credits_cost: float = 0.0
+    error_msg: str = ""
+    retry_count: int = 0
+    started_at: datetime | None = None
+    completed_at: datetime | None = None
+    created_at: datetime | None = None
+    updated_at: datetime | None = None
+
+
+class ViralVideoHistoryResponse(BaseModel):
+    items: list[ViralVideoJobResponse]
+    total: int
+
+
+class StyleTemplateResponse(BaseModel):
+    id: str
+    name: str
+    description: str = ""
+    thumbnail_url: str = ""
+    style_config: dict = Field(default_factory=dict)
+
+
+class StyleTemplateListResponse(BaseModel):
+    items: list[StyleTemplateResponse]
+
+
+class AnalyzeStyleResponse(BaseModel):
+    job_id: str
+    status: str
+    style_guide: dict | None = None
+
+
+# -- 积分预估 --
+
+
+class EstimateCreditsRequest(BaseModel):
+    """爆款视频积分预估请求。
+
+    前端可传 model 或 video_model（兼容老字段）；resolution/ratio/duration 为预估所需参数。
+    """
+
+    model: str = Field(default="", alias="video_model")
+    resolution: str = Field(default="720p", alias="video_resolution")
+    ratio: str = Field(default="9:16", alias="video_ratio")
+    duration: int = Field(default=15, ge=5, le=30)
+
+    model_config = {"populate_by_name": True}
+
+
+class CreditsFormulaBreakdown(BaseModel):
+    """爆款视频积分计费公式明细（前端展示用）。"""
+
+    tokens: float = Field(..., description="估算视频 tokens 数 (duration*width*height*fps/1024)")
+    video_cost: float = Field(..., description="视频生成成本（元）= tokens/1e6 * model_price")
+    fixed_cost: float = Field(..., description="固定成本（元），含 VLM/LLM/TTS/OSS/服务器")
+    profit_multiplier: float = Field(..., description="利润系数（默认 1.3）")
+    model_price: float = Field(..., description="模型单价（元/百万 tokens）")
+    width: int = Field(..., description="视频宽度像素")
+    height: int = Field(..., description="视频高度像素")
+    fps: int = Field(..., description="视频帧率")
+
+
+class EstimateCreditsResponse(BaseModel):
+    """爆款视频积分预估响应。"""
+
+    estimated_credits: float
+    formula_breakdown: CreditsFormulaBreakdown = Field(..., description="计费公式明细")
+
+
+class RetryViralVideoRequest(BaseModel):
+    """重试爆款视频任务的请求体（可选，允许改参数重新预估积分多退少补）。
+
+    不传 body 或字段全缺省：保持原参数、不重新扣点，走默认重置+入队逻辑。
+    传入新的 duration/video_resolution/video_ratio/video_model：重新预估积分，
+    与原 credits_prepaid 比较后多退少补（差额补扣不足抛 402）。
+    """
+
+    duration: int | None = Field(default=None, ge=5, le=30, description="重试时新的视频时长（秒）")
+    video_resolution: str | None = Field(default=None, description="重试时新的分辨率，如 720p/1080p")
+    video_ratio: str | None = Field(default=None, description="重试时新的画幅比，如 9:16/16:9")
+    video_model: str | None = Field(default=None, description="重试时新的视频模型，如 seedance-2.5")
+
+
+# -- WebSocket 事件 Schema --
+
+
+class WSProgressEvent(BaseModel):
+    type: str = "viral_video:progress"
+    job_id: str
+    stage: str
+    progress: float = Field(ge=0.0, le=100.0)
+    message: str = ""
+    data: dict = Field(default_factory=dict)

apps/api/app/services/narrative_service.py

@@ -11,14 +11,12 @@
    存储路径与元信息约定），返回 asset_id —— 下游仍以 voice_library_id（实为
    audio asset id）消费，渲染链路零改动。
 
-积分扣点与 /tts 合成端点保持一致（ai_voice 场景），失败退费。
 """
 
 from __future__ import annotations
 
 import json
 import logging
-import math
 import subprocess
 import tempfile
 from dataclasses import dataclass
@@ -32,13 +30,10 @@ from packages.application.cosyvoice_service import CosyVoiceService
 from packages.application.tts_job.use_cases import CreateTTSJobUseCase
 from packages.application.tts_job.workflow import TTSWorkflowService
 from packages.domain import Asset, AssetLibrary, AssetLibraryKind, AssetStatus, ClassificationStatus
-from packages.domain.points_rules import calculate_points_cost
-from packages.domain.points_service import PointsService
 from packages.shared.storage import SharedStorageService
 
 logger = logging.getLogger(__name__)
 
-_POINTS_SCENE = "ai_voice"
 _SYNTH_TIMEOUT = 180.0  # 叙事配音在 HTTP 请求内同步等待，长文案分段合成时留出余量
 _CONTENT_TYPE_MAP = {"mp3": "audio/mpeg", "wav": "audio/wav", "pcm": "audio/pcm", "opus": "audio/opus"}
 
@@ -273,24 +268,6 @@ def prepare_narrative_voice(
         voice_clone_repository=voice_clone_repository,
     )
 
-    # 积分扣点（与 /tts 合成端点同口径），失败时在合成失败分支退费
-    points_svc = PointsService() if points_enabled else None
-    points_deducted = 0
-    if points_svc is not None:
-        est_minutes = max(1.0, math.ceil(len(content) / 240))
-        points_deducted = calculate_points_cost(
-            _POINTS_SCENE,
-            is_member=is_member,
-            duration_minutes=est_minutes,
-            member_type=member_type,
-        )
-        deduct_res = points_svc.deduct_points(user_id, points_deducted, _POINTS_SCENE, db)
-        if not deduct_res["success"]:
-            raise NarrativeError(
-                f"积分不足，需要 {points_deducted} 积分，当前余额 {deduct_res['balance']}",
-                status_code=402,
-            )
-
     use_case = CreateTTSJobUseCase(tts_repository)
     job = use_case.execute(
         user_id=user_id,
@@ -311,19 +288,9 @@ def prepare_narrative_voice(
             workflow.process_synthesis_failure(job.id, str(e))
         except Exception:  # noqa: BLE001
             logger.warning("标记叙事 TTS job 失败出错: job_id=%s", job.id, exc_info=True)
-        if points_deducted and points_svc is not None:
-            try:
-                points_svc.refund_points(user_id, points_deducted, _POINTS_SCENE, db, ref_id=job.id)
-            except Exception:  # noqa: BLE001
-                logger.warning("叙事 TTS 失败退积分异常: job_id=%s", job.id, exc_info=True)
         raise NarrativeError(f"配音合成失败：{e}", status_code=502) from e
 
     if not job.is_completed:
-        if points_deducted and points_svc is not None:
-            try:
-                points_svc.refund_points(user_id, points_deducted, _POINTS_SCENE, db, ref_id=job.id)
-            except Exception:  # noqa: BLE001
-                logger.warning("叙事 TTS 未完成退积分异常: job_id=%s", job.id, exc_info=True)
         raise NarrativeError("配音合成未完成，请稍后重试", status_code=504)
 
     asset = _save_tts_job_as_voice_asset(

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

@@ -150,6 +150,8 @@ export interface DirectUploadPrepareResult {
    * 两个字段是同一语义的别名（后端可能只返回其一），前端任意为 true 即视为命中去重。
    */
   skip_transfer?: boolean
+  /** duplicated=true 时后端返回已存在素材的公网 URL，前端直接用而不必再调 complete */
+  url?: string
 }
 
 /** 直传完成确认返回 */

apps/web/src/api/assets/upload.ts

@@ -3,9 +3,24 @@
  */
 import apiClient from "../client"
 import { getOrCreateDefaultProject } from "../projects"
+import { ensureDefaultLibrary } from "./libraries"
 import type { DirectUploadPrepareResult, DirectUploadCompleteResult } from "./types"
 import { computeFileHash, makeClientUploadId } from "./uploadDedup"
 
+/** 根据 File.type 推断素材库 kind（image/video/voice）；无法推断时默认 image */
+function inferKindFromFile(file: File): "image" | "video" | "voice" {
+  const t = (file.type || "").toLowerCase()
+  if (t.startsWith("image/")) return "image"
+  if (t.startsWith("video/")) return "video"
+  if (t.startsWith("audio/")) return "voice"
+  // 兜底：按扩展名再判一次
+  const name = file.name.toLowerCase()
+  if (/\.(png|jpe?g|gif|webp|bmp|svg|avif)$/.test(name)) return "image"
+  if (/\.(mp4|mov|webm|avi|mkv|flv|wmv|m4v)$/.test(name)) return "video"
+  if (/\.(mp3|wav|m4a|aac|ogg|flac|opus|webm)$/.test(name)) return "voice"
+  return "image"
+}
+
 /** 预签名直传准备 */
 export const prepareDirectUpload = async (data: {
   project_id: string
@@ -108,6 +123,8 @@ const putToOSS = (
 
 /** 单个文件的上传阶段信息（供批量上传队列做状态绑定） */
 export interface DirectUploadHandle {
+  /** 实际使用的素材库（内部解析出来，便于调用方做后续 UI/缓存操作） */
+  library: { id: string; kind: "image" | "video" | "voice" }
   /** prepare 返回（含可能的预建 asset_id） */
   prepared: DirectUploadPrepareResult
   /** 直传 OSS（可重复调用用于重试） */
@@ -119,10 +136,17 @@ export interface DirectUploadHandle {
 /**
  * 准备一次直传：调 prepare 拿到签名表单（后端可能同时预建 uploading 态 asset），
  * 返回分段执行的 handle，调用方自行控制 transfer/complete 时机（便于队列并发与重试）。
+ *
+ * 修复 P0 404：library_id 改为可选；未传时自动根据文件类型在默认项目下确保对应素材库存在，
+ * 避免调用方从「全部素材库列表」里挑一个 library_id、但与默认项目 project_id 不匹配，
+ * 导致后端返回 "Asset library not found" 404。
  */
 export const prepareDirectUploadHandle = async (data: {
   file: File
-  library_id: string
+  /** 素材库 ID；未传时按文件类型自动在默认项目下 ensure-default */
+  library_id?: string
+  /** 显式指定素材库 kind；未传时按 MIME/扩展名推断 */
+  kind?: "image" | "video" | "voice"
   /** 前端算好的文件内容哈希（SHA-256 hex），prepare/complete 均携带 */
   fileHash?: string
   /** 本次逻辑上传的幂等 token，prepare/complete 一致、重试复用 */
@@ -138,9 +162,17 @@ export const prepareDirectUploadHandle = async (data: {
     throw new Error(`初始化默认项目失败，无法开始上传：${reason}`)
   }
 
+  // 解析 library_id：调用方传了就用，没传就按 kind 自动 ensure-default
+  let resolvedLibraryId = data.library_id
+  const resolvedKind = data.kind ?? inferKindFromFile(data.file)
+  if (!resolvedLibraryId) {
+    const lib = await ensureDefaultLibrary({ project_id: project.id, kind: resolvedKind })
+    resolvedLibraryId = lib.id
+  }
+
   const prepared = await prepareDirectUpload({
     project_id: project.id,
-    library_id: data.library_id,
+    library_id: resolvedLibraryId,
     filename: data.file.name,
     content_type: data.file.type || "application/octet-stream",
     file_size: data.file.size,
@@ -149,12 +181,13 @@ export const prepareDirectUploadHandle = async (data: {
   })
 
   return {
+    library: { id: resolvedLibraryId, kind: resolvedKind },
     prepared,
     transfer: (onProgress) => putToOSS(prepared, data.file, onProgress),
     complete: () =>
       completeDirectUpload({
         project_id: project.id,
-        library_id: data.library_id,
+        library_id: resolvedLibraryId,
         storage_key: prepared.storage_key,
         file_hash: data.fileHash,
         client_upload_id: data.clientUploadId,
@@ -164,10 +197,17 @@ export const prepareDirectUploadHandle = async (data: {
   }
 }
 
-/** 直传上传（大文件推荐），支持可选进度回调；一次性完成 prepare→transfer→complete */
+/** 直传上传（大文件推荐），支持可选进度回调；一次性完成 prepare→transfer→complete
+ *
+ * P0 404 修复：library_id 可选；不传时内部按文件类型自动匹配正确项目下的素材库，
+ * 保证 project_id 与 library_id 必然一致。
+ */
 export const uploadAssetDirect = async (data: {
   file: File
-  library_id: string
+  /** 素材库 ID；可选，不传按文件类型自动解析默认项目下的对应素材库（推荐用法） */
+  library_id?: string
+  /** 显式指定素材库 kind；未传时按文件 MIME/扩展名推断 */
+  kind?: "image" | "video" | "voice"
   onProgress?: (percent: number) => void
   /** 文件内容哈希；未传时自动补算（配音/封面/克隆等非队列链路统一受益） */
   fileHash?: string
@@ -180,6 +220,7 @@ export const uploadAssetDirect = async (data: {
   const handle = await prepareDirectUploadHandle({
     file: data.file,
     library_id: data.library_id,
+    kind: data.kind,
     fileHash,
     clientUploadId,
   })
@@ -188,7 +229,7 @@ export const uploadAssetDirect = async (data: {
     return {
       storage_key: handle.prepared.storage_key,
       ingest_job_id: "",
-      url: "",
+      url: handle.prepared.url || "",
       duplicated: true,
       asset_id: handle.prepared.asset_id,
     }

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

@@ -3,7 +3,8 @@
  */
 
 /** 任务状态 */
-export type TaskStatus = "pending" | "waiting" | "running" | "completed" | "failed" | "cancelled"
+export type TaskStatus =
+  "pending" | "waiting" | "running" | "awaiting_cover" | "completed" | "failed" | "cancelled"
 
 /** 任务类型 */
 export type TaskType = "ingest" | "generation" | string

apps/web/src/api/viral-video/index.ts

@@ -0,0 +1,142 @@
+import apiClient from "@/api/client"
+import type {
+  GenerateViralVideoRequest,
+  HistoryResponse,
+  StyleTemplate,
+  ViralVideoJob,
+  ImageAnalysisResult,
+  CopyResult,
+  AnalyzeImagesRequest,
+  GenerateCopyRequest,
+  ConfirmCopyRequest,
+} from "./types"
+
+/** 创建爆款视频任务 */
+export function generateViralVideo(payload: GenerateViralVideoRequest) {
+  return apiClient.post<ViralVideoJob>("/viral-video/generate", payload).then((r) => r.data)
+}
+
+/** 查询单个任务 */
+export function getViralVideoJob(id: string) {
+  return apiClient.get<ViralVideoJob>(`/viral-video/${id}`).then((r) => r.data)
+}
+
+/** 用户确认/修改 AI 理解的意图后继续 */
+export function confirmViralVideoIntent(
+  id: string,
+  payload: { confirmed_copy?: string; edits?: Record<string, unknown> },
+) {
+  return apiClient
+    .post<ViralVideoJob>(`/viral-video/${id}/confirm-intent`, payload)
+    .then((r) => r.data)
+}
+
+/** 重试失败任务 */
+export function retryViralVideo(id: string) {
+  return apiClient.post<ViralVideoJob>(`/viral-video/${id}/retry`).then((r) => r.data)
+}
+
+/** 历史记录（分页） */
+export function getViralVideoHistory(params?: { page?: number; page_size?: number }) {
+  return apiClient.get<HistoryResponse>("/viral-video/history", { params }).then((r) => r.data)
+}
+
+/** 预设风格模板 */
+export function getViralStyleTemplates() {
+  return apiClient.get<StyleTemplate[]>("/viral-video/style-templates").then((r) => r.data)
+}
+
+/** 上传参考视频后触发风格分析 */
+export function analyzeViralStyle(id: string) {
+  return apiClient.post<ViralVideoJob>(`/viral-video/${id}/analyze-style`).then((r) => r.data)
+}
+
+/** 动态预估积分消耗（STEP3 参数变化时调用） */
+export function estimateViralVideoCredits(params: {
+  video_model: string
+  resolution: string
+  video_ratio: string
+  duration: number
+}) {
+  return apiClient
+    .post<{ estimated_credits: number }>("/viral-video/estimate-credits", params)
+    .then((r) => r.data)
+}
+/** ── 三步拆分：前端 mock 辅助函数（后端新接口上线后可替换） ── */
+
+/**
+ * 客户端图片分析 mock（后端未提供 analyze-only 端点前的占位方案）：
+ * 基于已上传图片生成一份示例识别汇览，让 STEP1→STEP2 交互可走通。
+ * 后端上线后改为调用真实接口。
+ */
+export function mockImageAnalysis(images: { name: string }[]): Promise<ImageAnalysisResult> {
+  return new Promise((resolve) => {
+    setTimeout(() => {
+      const products = images.slice(0, 3).map((img, i) => {
+        const n = img.name.replace(/\.[^.]+$/, "")
+        return {
+          name: n || `商品 ${i + 1}`,
+          spec: i === 0 ? "500ml/瓶" : i === 1 ? "300g/盒" : undefined,
+          brand: i === 0 ? "示例品牌" : undefined,
+          features:
+            i === 0
+              ? "瓶身透明、蓝色标签、白色瓶盖；标签上印有品牌Logo和产品名称；光线均匀，主体居中"
+              : i === 1
+                ? "盒装包装、主色调为米白+暖黄；正面有产品实物图；文字清晰可辨"
+                : "产品主体清晰、背景干净、色彩鲜艳，突出核心卖点",
+          label_text: i === 0 ? "包装正面印有产品名称、净含量、品牌Logo" : undefined,
+          image_index: i,
+        }
+      })
+      resolve({ products })
+    }, 1800)
+  })
+}
+
+/**
+ * 客户端文案生成 mock（后端未提供 generate-copy 端点前的占位方案）：
+ * 后端上线后改为调用真实接口。
+ */
+export function mockGenerateCopy(params: {
+  product: string
+  sellingPoints?: string[]
+  tone?: string
+  duration?: number
+  marketingPurpose?: string
+  industry?: string
+  targetCustomer?: string
+}): Promise<CopyResult> {
+  return new Promise((resolve) => {
+    setTimeout(() => {
+      const product = params.product || "这款产品"
+      const tone = params.tone || "亲切务实"
+      const purpose = params.marketingPurpose || "品牌种草"
+      resolve({
+        title: `【${purpose}】${product}，用过的人都说好！`,
+        final_copy: `你有没有发现，选对一款${params.industry || "好物"}真的能让生活省心很多？\n\n今天给大家推荐这款${product}。${tone.includes("亲切") ? "说实话，" : ""}我自己用了一段时间，最直观的感受就是——好用、省心、值得回购。\n\n✅ 亮点一：品质到位，用料扎实，细节处见用心\n✅ 亮点二：使用体验舒服，日常高频场景都能打\n✅ 亮点三：性价比很能打，这个价位真的没什么可挑的\n\n如果你也在找一款靠谱的${params.industry || "日常好物"}，真的建议试试${product}，不会让你失望。点击左下角，直接入手！`,
+        suggested_copy: `你有没有发现，选对一款${params.industry || "好物"}真的能让生活省心很多？\n\n今天给大家推荐这款${product}。${tone.includes("亲切") ? "说实话，" : ""}我自己用了一段时间，最直观的感受就是——好用、省心、值得回购。\n\n✅ 亮点一：品质到位，用料扎实，细节处见用心\n✅ 亮点二：使用体验舒服，日常高频场景都能打\n✅ 亮点三：性价比很能打，这个价位真的没什么可挑的\n\n如果你也在找一款靠谱的${params.industry || "日常好物"}，真的建议试试${product}，不会让你失望。点击左下角，直接入手！`,
+      })
+    }, 2200)
+  })
+}
+
+/** ── 三步拆分 v1.5 真实后端 API（PR #2117 合入后启用，前端可替换 mock 调用） ── */
+
+/** 阶段1：上传图片后仅做 VLM 图片分析 + 可选参考视频风格分析，完成后状态=image_analyzed */
+export function analyzeViralImages(payload: AnalyzeImagesRequest) {
+  return apiClient.post<ViralVideoJob>("/viral-video/analyze-images", payload).then((r) => r.data)
+}
+
+/** 阶段2：用户填完营销参数后生成文案+分镜+合规审核，完成后状态=copy_generated，返回 copy_result */
+export function generateViralCopy(id: string, payload: GenerateCopyRequest) {
+  return apiClient
+    .post<ViralVideoJob>(`/viral-video/${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)
+}

apps/web/src/api/viral-video/types.ts

@@ -0,0 +1,298 @@
+export type FusionLevel = "ai_full" | "ai_polish" | "user_primary"
+export const FUSION_LEVELS: { value: FusionLevel; label: string; desc: string }[] = [
+  { value: "ai_full", label: "AI 全写", desc: "给我方向，全由AI创作" },
+  { value: "ai_polish", label: "AI润色", desc: "我写草稿，AI帮我润色" },
+  { value: "user_primary", label: "按我写的来", desc: "几乎不改我的文案" },
+]
+
+export type StyleStrength = "light" | "medium" | "strict"
+export const STYLE_STRENGTHS: { value: StyleStrength; label: string }[] = [
+  { value: "light", label: "轻度借鉴" },
+  { value: "medium", label: "中度参考" },
+  { 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"
+  | "wait_user_confirm"
+  | "image_analyzed"
+  | "copy_generated"
+  | "completed"
+  | "failed"
+  | "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
+ */
+export type ViralVideoStage =
+  | "image_analysis"
+  | "video_analysis"
+  | "intent_parsing"
+  | "script_generation"
+  | "review"
+  | "tts"
+  | "rendering"
+  | "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"])
+
+export function isImageAnalysisStage(stage: ViralVideoStage | undefined): boolean {
+  return !!stage && IMAGE_ANALYSIS_STAGES.has(stage)
+}
+export function isCopyStage(stage: ViralVideoStage | undefined): boolean {
+  return !!stage && COPY_STAGES.has(stage)
+}
+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 */
+export function isAnalysisStage(stage: ViralVideoStage | undefined): boolean {
+  return isImageAnalysisStage(stage) || isCopyStage(stage)
+}
+
+/** 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
+  features?: string[] | string
+  label_text?: string
+  selling_points?: string
+  image_index?: number
+}
+
+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 }>
+}
+
+export interface StyleTemplate {
+  id: string
+  name: string
+  description?: string
+  thumbnail_url?: string
+  style_config?: Record<string, unknown>
+  tags?: string[]
+}
+
+export interface IntentResult {
+  intent?: string
+  key_messages?: string[]
+  tone?: string
+  target_emotion?: string
+  call_to_action?: string
+  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
+}
+
+export interface ViralVideoJob {
+  id: string
+  status: ViralVideoStatus
+  images: string[]
+  reference_video_url?: string
+  style_strength?: StyleStrength
+  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"
+  voice_source?: "preset" | "library" | "clone" | "upload"
+  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
+  output_url?: string
+  result_video_url?: string
+  error_message?: string
+  error_msg?: string
+  credits_cost?: number
+  created_at?: string
+  updated_at?: string
+}
+
+export interface GenerateViralVideoRequest {
+  images: string[]
+  reference_video_url?: string
+  douyin_url?: string
+  style_strength?: StyleStrength
+  style_template_id?: string
+  user_copy_text?: string
+  fusion_level?: FusionLevel
+  voice_id?: string
+  voice_source?: "preset" | "library" | "clone" | "upload"
+  bgm_preference?: string
+  industry?: string
+  target_customer?: string
+  language?: string
+  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
+  /** 三步拆分：step 控制后端执行到哪一步暂停 */
+  step?: "analyze" | "generate_copy" | "generate_video"
+}
+
+export interface HistoryResponse {
+  items: ViralVideoJob[]
+  total: number
+  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
+}

apps/web/src/components/layout/PageHead/constants.ts

@@ -2,6 +2,7 @@
 export const ROUTE_TITLE_MAP: Record<string, string> = {
   "/app/dashboard": "首页",
   "/app/generate": "智能剪辑",
+  "/app/viral-video": "爆款视频",
   "/app/assets": "视频库",
   "/app/voices": "配音库",
   "/app/products": "成片库",

apps/web/src/config/navigation.ts

@@ -18,6 +18,7 @@ import {
   ThunderboltOutlined,
   UnorderedListOutlined,
   UserOutlined,
+  FireOutlined,
 } from "@ant-design/icons"
 
 /** 导航项类型 */
@@ -76,6 +77,12 @@ export const NAV_ITEMS: NavItem[] = [
     path: "/app/ai-avatar",
     icon: React.createElement(UserOutlined),
   },
+  {
+    key: "viral-video",
+    label: "爆款视频",
+    path: "/app/viral-video",
+    icon: React.createElement(FireOutlined),
+  },
   {
     key: "history",
     label: "任务历史",
@@ -142,6 +149,12 @@ export const NAV_GROUPS: NavGroup[] = [
         path: "/app/ai-avatar",
         icon: React.createElement(UserOutlined),
       },
+      {
+        key: "viral-video",
+        label: "爆款视频",
+        path: "/app/viral-video",
+        icon: React.createElement(FireOutlined),
+      },
     ],
   },
   {

apps/web/src/pages/ai-avatar/AiAvatarPage.tsx

@@ -580,20 +580,6 @@ const AiAvatarPage: React.FC = () => {
 
   return (
     <div className="aa-page">
-      <div className="aa-page-header">
-        <h1>AI数字人</h1>
-      </div>
-
-      {/* 步骤切换导航条 */}
-      <div className="aa-step-nav">
-        <span className={`aa-step-nav__item${currentStep === 1 ? " active" : ""}`}>
-          1. 视频 / 配音 / 文案
-        </span>
-        <span className={`aa-step-nav__item${currentStep === 2 ? " active" : ""}`}>
-          2. 对口型 / 标题 / 封面 / 生成
-        </span>
-      </div>
-
       <div className="aa-page-body">
         {/* ════ 步骤 1：出镜视频 / 配音库 / 文案 ════ */}
         {currentStep === 1 && (

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

@@ -13,8 +13,6 @@ import CloneModal from "@/components/voice/CloneModal"
 import VoiceSelectModal from "./components/VoiceSelectModal"
 import ScriptSelectModal from "./components/ScriptSelectModal"
 import TtsVoiceModal from "./components/TtsVoiceModal"
-import GenerateHeader from "./components/GenerateHeader"
-import GenerateStepsBar from "./components/GenerateStepsBar"
 import GenerateStepContent from "./components/GenerateStepContent"
 import GenerateStepActions from "./components/GenerateStepActions"
 import { useGenerateFormState } from "./hooks/useGenerateFormState"
@@ -88,7 +86,6 @@ const GeneratePage: React.FC = () => {
     style,
     autoSubtitles,
     bgm,
-    editPlanId,
     sourceEditPlanId,
     previewTaskId,
     setPreviewTaskId,
@@ -239,9 +236,14 @@ const GeneratePage: React.FC = () => {
     voiceModePerVideo,
     variantCoverUrls: previewCovers,
     selectedVariantIndexes: isBatch ? selectedVariantIds : undefined,
-    onGenerationSuccess: () => {
+    onGenerationSuccess: (status?: "completed" | "awaiting_cover") => {
       setPreviewTaskId(null)
       setStoredSourceEditPlanId(null)
+      // #2088：渲染完成后自动跳到封面选择页（step 5），不再等用户手动点「下一步」
+      // awaiting_cover 和 completed 都走封面页（completed 是旧 worker 或 finalize 后状态，仍支持选封面）
+      if (status === "awaiting_cover" || status === "completed" || !status) {
+        setCurrentStep(5)
+      }
     },
   })
 
@@ -518,10 +520,6 @@ const GeneratePage: React.FC = () => {
 
   return (
     <div className="xx-generate-page">
-      <GenerateHeader fromEditPlan={!!editPlanId} />
-
-      <GenerateStepsBar currentStep={currentStep} onStepClick={setCurrentStep} />
-
       <div className={layoutClassName}>
         {/* ════ 步骤1~2 表单 / 步骤3 标题设置 / 步骤4 确认生成进度 / 步骤5 封面 ════ */}
         <div className="xx-generate-form">

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

@@ -11,7 +11,12 @@
  *   防止长标题在窄列里溢出导致与相邻卡片进度条视觉重叠。
  */
 import React from "react"
-import { LoadingOutlined, CheckCircleFilled, CloseCircleOutlined } from "@ant-design/icons"
+import {
+  LoadingOutlined,
+  CheckCircleFilled,
+  CloseCircleOutlined,
+  ClockCircleOutlined,
+} from "@ant-design/icons"
 import type { BatchTaskState } from "../hooks/generate-video/useGenerationPolling"
 import type { GeneratedVideo } from "@/api/template-editor"
 
@@ -61,6 +66,11 @@ const BatchGenerationGrid: React.FC<BatchGenerationGridProps> = ({
                       className="xx-batch-gen-card-icon"
                       style={{ color: "#ef4444" }}
                     />
+                  ) : task.status === "queued" ? (
+                    <ClockCircleOutlined
+                      className="xx-batch-gen-card-icon"
+                      style={{ color: "#faad14" }}
+                    />
                   ) : (
                     <LoadingOutlined
                       className="xx-batch-gen-card-icon"
@@ -85,6 +95,21 @@ const BatchGenerationGrid: React.FC<BatchGenerationGridProps> = ({
                     <div className="xx-batch-gen-card-pct">{Math.round(task.progress)}%</div>
                   </>
                 )}
+                {task.status === "queued" && (
+                  <div
+                    style={{
+                      display: "flex",
+                      alignItems: "center",
+                      gap: 8,
+                      color: "var(--text-secondary, #faad14)",
+                      fontSize: 13,
+                      padding: "8px 0",
+                    }}
+                  >
+                    <ClockCircleOutlined />
+                    <span>排队等待中，前面任务完成后自动开始渲染</span>
+                  </div>
+                )}
                 {(task.status === "completed" || task.status === "awaiting_cover") && video && (
                   // 竖屏自适应容器（#1750）：成片固定 1080×1920（9:16），
                   // 视频按真实宽高比 contain 显示，黑底居中，杜绝横屏播放器左右大黑边

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

@@ -12,6 +12,7 @@ import Step2MaterialSelect from "../components/Step2MaterialSelect"
 import Step4TitleSettings from "../components/Step4TitleSettings"
 import Step6CoverSettings from "../components/Step6CoverSettings"
 import BatchGenerationGrid from "./BatchGenerationGrid"
+import Step3VoiceWithMode from "./Step3VoiceWithMode"
 import type { BatchTaskState } from "../hooks/generate-video/useGenerationPolling"
 import type { GeneratedVideo } from "@/api/template-editor"
 import type { TitleTemplate } from "@/components/title/template-types"
@@ -151,6 +152,12 @@ export const GenerateStepContent: React.FC<GenerateStepContentProps> = (props) =
     selectedCoverTemplate,
     onSelectedCoverTemplateChange,
     onConfirmGenerate,
+    selectedVoice,
+    onSelectedVoiceChange,
+    voiceModePerVideo,
+    onVoiceModePerVideoChange,
+    voiceLibraryIds,
+    onVoiceLibraryIdsChange,
   } = props
 
   switch (currentStep) {
@@ -184,32 +191,46 @@ export const GenerateStepContent: React.FC<GenerateStepContentProps> = (props) =
       )
     case 3:
       return (
-        <Step4TitleSettings
-          titleSettings={titleSettings}
-          onTitleSettingsChange={onTitleSettingsChange}
-          onUpdatePosition={onUpdatePosition}
-          onUpdateFont={onUpdateFont}
-          onUpdateSize={onUpdateSize}
-          onToggleBold={onToggleBold}
-          onToggleItalic={onToggleItalic}
-          onToggleStroke={onToggleStroke}
-          onToggleShadow={onToggleShadow}
-          onApplyPreset={onApplyPreset}
-          onUpdateStyle={onUpdateStyle}
-          activePreset={activePreset}
-          titlePresets={titlePresets}
-          enableTemplates={enableTemplates}
-          selectedTemplateId={selectedTemplateId}
-          onApplyTemplate={onApplyTemplate}
-          previewCount={previewCount}
-          previewTitles={previewTitles}
-          onPreviewTitlesChange={onPreviewTitlesChange}
-          onConfirmGenerate={onConfirmGenerate}
-          generating={props.generating}
-          selectedCount={
-            props.previewCount && props.previewCount > 1 ? props.selectedVariantIds?.length || 1 : 1
-          }
-        />
+        <>
+          <Step4TitleSettings
+            titleSettings={titleSettings}
+            onTitleSettingsChange={onTitleSettingsChange}
+            onUpdatePosition={onUpdatePosition}
+            onUpdateFont={onUpdateFont}
+            onUpdateSize={onUpdateSize}
+            onToggleBold={onToggleBold}
+            onToggleItalic={onToggleItalic}
+            onToggleStroke={onToggleStroke}
+            onToggleShadow={onToggleShadow}
+            onApplyPreset={onApplyPreset}
+            onUpdateStyle={onUpdateStyle}
+            activePreset={activePreset}
+            titlePresets={titlePresets}
+            enableTemplates={enableTemplates}
+            selectedTemplateId={selectedTemplateId}
+            onApplyTemplate={onApplyTemplate}
+            previewCount={previewCount}
+            previewTitles={previewTitles}
+            onPreviewTitlesChange={onPreviewTitlesChange}
+            onConfirmGenerate={onConfirmGenerate}
+            generating={props.generating}
+            selectedCount={
+              props.previewCount && props.previewCount > 1
+                ? props.selectedVariantIds?.length || 1
+                : 1
+            }
+          />
+          {/* 批量配音选择：共用/独立切换（#2096） */}
+          <Step3VoiceWithMode
+            previewCount={previewCount}
+            selectedVoice={selectedVoice}
+            onSelectedVoiceChange={onSelectedVoiceChange}
+            voiceModePerVideo={voiceModePerVideo}
+            onVoiceModePerVideoChange={onVoiceModePerVideoChange}
+            voiceLibraryIds={voiceLibraryIds}
+            onVoiceLibraryIdsChange={onVoiceLibraryIdsChange}
+          />
+        </>
       )
     case 4:
       return (

apps/web/src/pages/generate/components/Step4TitleSettings.tsx

@@ -157,7 +157,7 @@ const Step4TitleSettings: React.FC<Step4TitleSettingsProps> = (props) => {
           />
         </div>
       ) : (
-        /* ── 批量：N 个独立标题输入框 ── */
+        /* ── 批量：N 个独立标题输入框（两列布局 #2096） ── */
         <div className="xx-batch-titles">
           <div
             style={{
@@ -170,17 +170,25 @@ const Step4TitleSettings: React.FC<Step4TitleSettingsProps> = (props) => {
             为每个视频输入独立标题。标题样式（字体/颜色/位置）全局统一。
           </div>
 
-          {Array.from({ length: previewCount }, (_, i) => (
-            <div className="xx-form-field" key={i} style={{ maxWidth: 640 }}>
-              <label>视频 {i + 1} 标题</label>
-              <TitleLibraryAutoComplete
-                placeholder={`输入或选择视频 ${i + 1} 的标题`}
-                value={previewTitles?.[i] || ""}
-                onChange={(val) => updateVariantTitle(i, val)}
-                options={titleOptions}
-              />
-            </div>
-          ))}
+          <div
+            style={{
+              display: "grid",
+              gridTemplateColumns: "repeat(2, minmax(0, 1fr))",
+              gap: 16,
+            }}
+          >
+            {Array.from({ length: previewCount }, (_, i) => (
+              <div className="xx-form-field" key={i} style={{ maxWidth: "100%" }}>
+                <label>视频 {i + 1} 标题</label>
+                <TitleLibraryAutoComplete
+                  placeholder={`输入或选择视频 ${i + 1} 的标题`}
+                  value={previewTitles?.[i] || ""}
+                  onChange={(val) => updateVariantTitle(i, val)}
+                  options={titleOptions}
+                />
+              </div>
+            ))}
+          </div>
         </div>
       )}
 

apps/web/src/pages/generate/components/Step6CoverSettings.tsx

@@ -17,7 +17,7 @@ import CoverSettingsModal from "./cover-settings/CoverSettingsModal"
 import CoverEditorModal from "./cover-settings/CoverEditorModal"
 import { useSharedCover } from "@/components/cover/useSharedCover"
 import { generateCover as apiGenerateCover } from "@/api/generation"
-import { uploadAssetDirect, getAssetLibraries } from "@/api/assets"
+import { uploadAssetDirect } from "@/api/assets"
 
 interface Step6CoverSettingsProps {
   coverSettings: CoverConfig
@@ -176,15 +176,8 @@ const Step6CoverSettings: React.FC<Step6CoverSettingsProps> = (props) => {
           thumbnail_url: previewUrl,
           mode: "upload",
         })
-        // 查找图片素材库（复用批量封面的逻辑）
-        const libs = await getAssetLibraries()
-        const imageLib = libs.find((l) => l.kind === "image") || libs[0]
-        if (!imageLib) {
-          hide()
-          message.error("未找到素材库，请先创建图片素材库")
-          return previewUrl
-        }
-        const result = await uploadAssetDirect({ file, library_id: imageLib.id })
+        // 后端自动在默认项目下确保图片素材库存在（P0 404 修复）
+        const result = await uploadAssetDirect({ file, kind: "image" })
         const realUrl = result?.url || ""
         if (!realUrl) {
           hide()

apps/web/src/pages/generate/hooks/generate-video/types.ts

@@ -41,8 +41,8 @@ export interface UseGenerateVideoProps {
     enabled: boolean
     music_id?: string
   }
-  /** 生成成功后的回调（用于清除持久化的 previewTaskId 等状态） */
-  onGenerationSuccess?: () => void
+  /** 生成成功后的回调（用于清除持久化的 previewTaskId 等状态）；status=awaiting_cover 表示需进封面选择 */
+  onGenerationSuccess?: (status?: "completed" | "awaiting_cover") => void
   /* ── 批量生成（#1677）── */
   /** 生成数量（1=单条旧逻辑，>1=批量） */
   previewCount?: number

apps/web/src/pages/generate/hooks/generate-video/useGenerationPolling.ts

@@ -1,4 +1,4 @@
-import { useRef, useCallback, useState } from "react"
+import { useRef, useCallback, useState, useEffect } from "react"
 import { message } from "antd"
 import axios from "axios"
 import { getGenerationTask, retryTask as retryGenerationTaskApi } from "@/api/tasks/tasks"
@@ -10,7 +10,7 @@ export interface BatchTaskState {
   taskId: string
   /** 变体序号（0-based，与标题/封面数组对齐） */
   variantIndex: number
-  status: "running" | "completed" | "awaiting_cover" | "failed"
+  status: "running" | "completed" | "awaiting_cover" | "failed" | "queued"
   progress: number
   error: string | null
   /** 完成后的成片视频 */
@@ -19,7 +19,7 @@ export interface BatchTaskState {
 
 interface UseGenerationPollingOptions {
   onProgress: (progress: number) => void
-  onComplete: (videos: unknown[]) => void
+  onComplete: (videos: unknown[], taskStatus?: "completed" | "awaiting_cover") => void
   onFailed: (errorMsg: string) => void
   /** 批量：单任务状态变化（第5步逐卡片展示） */
   onBatchTaskUpdate?: (taskId: string, patch: Partial<BatchTaskState>) => void
@@ -31,13 +31,19 @@ const MAX_RETRYABLE_ERRORS = 10
 const MAX_RESULTS_RETRIES = 3
 
 /**
- * 生成状态轮询 Hook（v4 — 批量任务独立状态 + 单任务重试）
+ * 生成状态轮询 Hook（v5 — awaiting_cover 状态识别 + visibilitychange 恢复 + 状态透传）
  *
  * startPolling(taskId) 轮询单个任务；
  * startPollingBatch(tasks) 并行轮询 N 个任务：
  * - 每个任务独立进度/状态/失败，通过 onBatchTaskUpdate 实时回传
  * - 全部成功才 onComplete（聚合视频按变体顺序）；任一失败不影响其他任务继续
  * - retryTask(taskId) 单独重试失败任务（重新轮询，后端任务仍在跑则直接接续）
+ *
+ * v5 修复（#2088）：
+ * 1. 单任务路径透传 taskStatus（completed / awaiting_cover）到 onComplete，外层据此区分跳转
+ * 2. 监听 visibilitychange，页面从后台切回可见时立即补拉一次，解决切后台 setInterval 被浏览器
+ *    降频/冻结导致进度卡在 56% 的问题
+ * 3. 非 4xx/5xx 网络错误按 3s 退避重试（已有 MAX_RETRYABLE_ERRORS=10 兜底）
  */
 export function useGenerationPolling({
   onProgress,
@@ -49,12 +55,15 @@ export function useGenerationPolling({
   const cancelledRef = useRef(false)
   /** 批量任务上下文：taskId → 变体序号 */
   const batchContextRef = useRef<Map<string, number>>(new Map())
+  /** 当前活跃的「立刻补拉一次」函数（visibilitychange 回调使用） */
+  const immediateTickRef = useRef<(() => void) | null>(null)
   const [, forceTick] = useState(0)
 
   const clearTimer = useCallback(() => {
     cancelledRef.current = true
     progressTimer.current.forEach((t) => clearTimeout(t))
     progressTimer.current = []
+    immediateTickRef.current = null
   }, [])
 
   /** 任务完成后拉取结果列表，带重试 */
@@ -113,6 +122,7 @@ export function useGenerationPolling({
 
             if (task.status === "completed" || task.status === "awaiting_cover") {
               done = true
+              immediateTickRef.current = null
               const videos = await fetchResultsWithRetry(taskId)
               if (cancelledRef.current) return
               if (videos === null) {
@@ -128,6 +138,7 @@ export function useGenerationPolling({
 
             if (task.status === "failed" || task.status === "cancelled") {
               done = true
+              immediateTickRef.current = null
               const rawMsg =
                 task.error_info?.error_message ||
                 task.error_message ||
@@ -138,6 +149,7 @@ export function useGenerationPolling({
               return
             }
 
+            // running / pending / waiting：更新进度并安排下一次轮询
             const pct = Math.max(0, Math.min(99, Math.round(Number(task.progress) || 0)))
             callbacks?.onTaskProgress?.(pct)
             if (!callbacks && runId === 0) {
@@ -149,16 +161,20 @@ export function useGenerationPolling({
             if (cancelledRef.current || done) return
             console.error("[轮询出错] taskId:", taskId, pollErr)
             const status = axios.isAxiosError(pollErr) ? pollErr.response?.status : undefined
+            // 4xx 视为不可重试（任务不存在/权限问题等），直接失败
             if (status && status >= 400 && status < 500) {
               done = true
+              immediateTickRef.current = null
               const msg = extractErrorMessage(pollErr, status)
               callbacks?.onTaskFailed?.(msg)
               reject(new Error(msg))
               return
             }
+            // 网络错误 / 5xx：3s 退避重试，最多 MAX_RETRYABLE_ERRORS 次
             consecutiveErrors += 1
             if (consecutiveErrors >= MAX_RETRYABLE_ERRORS) {
               done = true
+              immediateTickRef.current = null
               const msg = "任务状态查询连续失败，请稍后在任务列表查看结果"
               callbacks?.onTaskFailed?.(msg)
               reject(new Error(msg))
@@ -169,6 +185,18 @@ export function useGenerationPolling({
           }
         }
 
+        // 注册「立刻补拉一次」回调，供 visibilitychange 恢复时调用
+        // 注意：必须在 done 后清理，避免切换页面时误触发已结束任务的补拉
+        immediateTickRef.current = () => {
+          if (!done && !cancelledRef.current) {
+            // 清除未触发的 setTimeout，立即拉一次
+            progressTimer.current.forEach((t) => clearTimeout(t))
+            progressTimer.current = []
+            consecutiveErrors = 0
+            void poll()
+          }
+        }
+
         const timer = setTimeout(poll, 1500)
         progressTimer.current.push(timer)
       })
@@ -181,12 +209,22 @@ export function useGenerationPolling({
     (taskId: string) => {
       cancelledRef.current = false
       batchContextRef.current.clear()
-      pollSingleTask(taskId, 0)
-        .then((videos) => {
-          if (cancelledRef.current) return
+      let resolvedStatus: "completed" | "awaiting_cover" = "completed"
+      pollSingleTask(taskId, 0, {
+        onTaskProgress: (pct) => onProgress(pct),
+        onTaskCompleted: (videos, taskStatus) => {
+          resolvedStatus = taskStatus ?? "completed"
           onProgress(100)
-          onComplete(videos)
-          message.success("视频生成完成！")
+          onComplete(videos, resolvedStatus)
+        },
+        onTaskFailed: (msg) => onFailed(msg),
+      })
+        .then(() => {
+          if (cancelledRef.current) return
+          // awaiting_cover 是中间态（进封面选择页），不弹"完成"toast；completed 才弹
+          if (resolvedStatus === "completed") {
+            message.success("视频生成完成！")
+          }
         })
         .catch((err: Error) => {
           if (cancelledRef.current) return
@@ -201,7 +239,7 @@ export function useGenerationPolling({
   /**
    * 批量多任务轮询：
    * - 每个任务独立进度/状态回传 onBatchTaskUpdate
-   * * 全部完成后按变体顺序聚合视频 onComplete
+   * - 全部完成后按变体顺序聚合视频 onComplete
    * - 部分失败：整体不 onFailed（第5步逐卡片展示失败+重试按钮）；全部失败才 onFailed
    */
   const startPollingBatch = useCallback(
@@ -211,6 +249,7 @@ export function useGenerationPolling({
       const progressMap = new Map<string, number>()
       const resultMap = new Map<string, unknown[]>()
       const failureMap = new Map<string, string>()
+      const statusMap = new Map<string, "completed" | "awaiting_cover">()
       batchContextRef.current = new Map(tasks.map((t) => [t.taskId, t.variantIndex]))
 
       const reportAggregateProgress = () => {
@@ -225,7 +264,9 @@ export function useGenerationPolling({
         if (resultMap.size === tasks.length) {
           onProgress(100)
           const ordered = tasks.map((t) => resultMap.get(t.taskId) || []).flat()
-          onComplete(ordered)
+          // 批量：任一任务为 awaiting_cover，则整体透传 awaiting_cover（进封面页）
+          const anyAwaiting = Array.from(statusMap.values()).some((s) => s === "awaiting_cover")
+          onComplete(ordered, anyAwaiting ? "awaiting_cover" : "completed")
           message.success(`全部 ${tasks.length} 个视频生成完成！`)
         } else if (resultMap.size > 0) {
           // 部分失败：成功的视频聚合进成片列表（可进封面），失败卡片带重试按钮
@@ -234,7 +275,8 @@ export function useGenerationPolling({
             .filter((t) => resultMap.has(t.taskId))
             .map((t) => resultMap.get(t.taskId) || [])
             .flat()
-          onComplete(ordered)
+          const anyAwaiting = Array.from(statusMap.values()).some((s) => s === "awaiting_cover")
+          onComplete(ordered, anyAwaiting ? "awaiting_cover" : "completed")
           message.warning(
             `${failureMap.size} 个视频生成失败，可点击卡片上的「重试此视频」，成功的视频可先进入下一步`,
           )
@@ -263,6 +305,7 @@ export function useGenerationPolling({
             progressMap.set(taskId, 100)
             resultMap.set(taskId, videos)
             const _finalStatus: "completed" | "awaiting_cover" = taskStatus ?? "completed"
+            statusMap.set(taskId, _finalStatus)
             onBatchTaskUpdate?.(taskId, { status: _finalStatus, progress: 100, videos })
             reportAggregateProgress()
             checkAllSettled()
@@ -309,5 +352,64 @@ export function useGenerationPolling({
     [pollSingleTask, onBatchTaskUpdate],
   )
 
-  return { startPolling, startPollingBatch, retryTask, clearTimer }
+  /**
+   * visibilitychange 恢复：页面从后台切回前台时，立刻触发一次补拉。
+   * 解决浏览器后台标签页对 setTimeout 的 1Hz 节流/冻结导致的"进度卡 56%"问题。
+   */
+  useEffect(() => {
+    const handleVisibilityChange = () => {
+      if (document.visibilityState === "visible" && immediateTickRef.current) {
+        immediateTickRef.current()
+      }
+    }
+    document.addEventListener("visibilitychange", handleVisibilityChange)
+    // 页面聚焦也兜底一次（部分浏览器 visibilitychange 触发时机不一致）
+    const handleFocus = () => {
+      if (immediateTickRef.current) immediateTickRef.current()
+    }
+    window.addEventListener("focus", handleFocus)
+    return () => {
+      document.removeEventListener("visibilitychange", handleVisibilityChange)
+      window.removeEventListener("focus", handleFocus)
+    }
+  }, [])
+
+  /**
+   * 批量队列模式：逐任务追加到轮询队列（支持串行提交、429 排队重试场景）。
+   * 与 startPollingBatch 不同的是：
+   * - 不会 reset batchContextRef；多次调用会累积
+   * - 不触发整体 onComplete / onFailed（完成判定交给外层 useEffect 按状态聚合）
+   * - 仍通过 onBatchTaskUpdate 回传单任务状态
+   */
+  const pollBatchTaskQueued = useCallback(
+    (taskId: string, variantIndex: number) => {
+      cancelledRef.current = false
+      batchContextRef.current.set(taskId, variantIndex)
+      onBatchTaskUpdate?.(taskId, {
+        taskId,
+        variantIndex,
+        status: "running",
+        progress: 0,
+        error: null,
+        videos: [],
+      })
+      pollSingleTask(taskId, Date.now(), {
+        onTaskProgress: (pct) => {
+          onBatchTaskUpdate?.(taskId, { status: "running", progress: pct })
+        },
+        onTaskCompleted: (videos, taskStatus) => {
+          const finalStatus: "completed" | "awaiting_cover" = taskStatus ?? "completed"
+          onBatchTaskUpdate?.(taskId, { status: finalStatus, progress: 100, videos })
+        },
+        onTaskFailed: (msg) => {
+          onBatchTaskUpdate?.(taskId, { status: "failed", error: msg })
+        },
+      }).catch(() => {
+        /* onTaskFailed 已处理 */
+      })
+    },
+    [pollSingleTask, onBatchTaskUpdate],
+  )
+
+  return { startPolling, startPollingBatch, pollBatchTaskQueued, retryTask, clearTimer }
 }

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

@@ -12,7 +12,7 @@
 import { useCallback, useState } from "react"
 import { message } from "antd"
 import { generateCover } from "@/api/generation"
-import { uploadAssetDirect, getAssetLibraries } from "@/api/assets"
+import { uploadAssetDirect } from "@/api/assets"
 import type { GeneratedVideo } from "@/api/template-editor"
 
 /** onCoversChange 支持直接传值或函数式 updater（函数式用于串行回写避免闭包覆盖） */
@@ -182,15 +182,9 @@ export function useBatchCovers({
     async (index: number, file: File) => {
       addUploading(index)
       try {
-        const libs = await getAssetLibraries()
-        const imageLib = libs.find((l) => l.kind === "image") || libs[0]
-        if (!imageLib) {
-          message.error("未找到素材库，请先创建")
-          return
-        }
         const result = await uploadAssetDirect({
           file,
-          library_id: imageLib.id,
+          kind: "image",
         })
         const url = result?.url || ""
         if (url) {

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

@@ -2,10 +2,12 @@
  * 视频生成 Hook
  * 封装视频生成的核心逻辑、状态管理、轮询等
  */
-import { useState, useCallback, useEffect } from "react"
+import { useState, useCallback, useEffect, useRef } from "react"
 import { message } from "antd"
+import axios from "axios"
 import { type GeneratedVideo, getEditPlanClips, createClipsFromAssets } from "@/api/template-editor"
 import { createGenerationTask } from "@/api/tasks/tasks"
+import type { CreateGenerationTaskRequest } from "@/api/tasks/types"
 import type { UseGenerateVideoProps } from "./generate-video/types"
 import { getGenerationPhase } from "./generate-video/phase"
 import { useGenerationPolling, type BatchTaskState } from "./generate-video/useGenerationPolling"
@@ -13,6 +15,28 @@ import { validateGenerateInputs } from "./generate-video/buildPayload"
 import { calculateResolution } from "../utils/calculateResolution"
 import { extractBackendError, translateError } from "./generate-video/errorUtils"
 
+export type GenerationCompleteStatus = "completed" | "awaiting_cover" | null
+
+/** 判断是否是用户队列已满 429（需要排队重试而非直接报错） */
+function isUserQueueFullError(err: unknown): { waitMs: number } | null {
+  if (!axios.isAxiosError(err)) return null
+  if (err.response?.status !== 429 && err.response?.status !== 503) return null
+  const detail = (err.response?.data as { detail?: unknown })?.detail
+  const code =
+    typeof detail === "object" && detail !== null ? (detail as { code?: string }).code : undefined
+  if (code === "USER_QUEUE_FULL" || code === "SYSTEM_QUEUE_FULL") {
+    const waitSec =
+      typeof detail === "object" && detail !== null
+        ? Number((detail as { estimated_wait_seconds?: number }).estimated_wait_seconds) || 0
+        : 0
+    return { waitMs: Math.max(15_000, waitSec * 1000 || 30_000) }
+  }
+  return null
+}
+
+/** sleep */
+const sleep = (ms: number) => new Promise<void>((r) => setTimeout(r, ms))
+
 export function useGenerateVideo(props: UseGenerateVideoProps) {
   const { selectedTemplate, onGenerationSuccess } = props
 
@@ -22,11 +46,29 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
   const [generated, setGenerated] = useState(false)
   const [generateError, setGenerateError] = useState<string | null>(null)
   const [generatedVideos, setGeneratedVideos] = useState<GeneratedVideo[]>([])
+  /** #2088：任务最终状态，区分 awaiting_cover（选封面）/ completed（已完成） */
+  const [completionStatus, setCompletionStatus] = useState<GenerationCompleteStatus>(null)
   /** 单视频模式：当前任务 ID（封面 finalize 需要） */
   const [currentTaskId, setCurrentTaskId] = useState<string>("")
   /** 批量模式：每个正式生成任务的独立状态（第5步逐卡片展示） */
   const [batchTasks, setBatchTasks] = useState<BatchTaskState[]>([])
 
+  /** 排队中重试的定时器，unmount / 新提交时清理 */
+  const queueTimersRef = useRef<number[]>([])
+  const cancelledRef = useRef(false)
+
+  const clearQueueTimers = useCallback(() => {
+    queueTimersRef.current.forEach((id) => clearTimeout(id))
+    queueTimersRef.current = []
+  }, [])
+
+  useEffect(() => {
+    return () => {
+      cancelledRef.current = true
+      clearQueueTimers()
+    }
+  }, [clearQueueTimers])
+
   const handleBatchTaskUpdate = useCallback((taskId: string, patch: Partial<BatchTaskState>) => {
     setBatchTasks((prev) => {
       const list = prev || []
@@ -53,9 +95,10 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
 
   const handleProgress = useCallback((p: number) => setProgress(p), [])
   const handleComplete = useCallback(
-    (videos: unknown[]) => {
-      setGenerating(false)
+    (videos: unknown[], taskStatus?: "completed" | "awaiting_cover") => {
       setGenerated(true)
+      const finalStatus: GenerationCompleteStatus = taskStatus ?? "completed"
+      setCompletionStatus(finalStatus)
       setGeneratedVideos(videos as GeneratedVideo[])
       // 批量：成功任务的 videos 已通过 onBatchTaskUpdate 写入，这里同步兜底
       setBatchTasks((prev) =>
@@ -70,26 +113,35 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
             : t,
         ),
       )
-      onGenerationSuccess?.()
+      onGenerationSuccess?.(finalStatus)
     },
     [onGenerationSuccess],
   )
   const handleFailed = useCallback((errorMsg: string) => {
-    setGenerating(false)
     setGenerateError(errorMsg)
   }, [])
 
   /* 批量：任务状态变化时聚合已完成成片（含失败重试成功后补入），
-     按变体索引排序，供步骤6封面按勾选顺序逐个取视频 */
+     按变体索引排序，供步骤6封面按勾选顺序逐个取视频。
+     当全部任务都已结束（completed/awaiting_cover/failed）且无排队/渲染中任务时，关闭 generating。 */
   useEffect(() => {
     if (batchTasks.length === 0) return
     const byVariant = new Map<number, GeneratedVideo>()
+    let hasQueued = false
+    let hasRunning = false
+    let hasSuccess = false
+    let allDone = true
     batchTasks.forEach((t) => {
-      if (
-        t.status === "completed" ||
-        (t.status === "awaiting_cover" && t.videos && t.videos.length > 0)
-      ) {
-        byVariant.set(t.variantIndex, t.videos[0] as GeneratedVideo)
+      if (t.status === "queued") hasQueued = true
+      else if (t.status === "running") hasRunning = true
+      if (t.status === "completed" || t.status === "awaiting_cover") {
+        hasSuccess = true
+        if (t.videos && t.videos.length > 0) {
+          byVariant.set(t.variantIndex, t.videos[0] as GeneratedVideo)
+        }
+      }
+      if (t.status !== "completed" && t.status !== "awaiting_cover" && t.status !== "failed") {
+        allDone = false
       }
     })
     const ordered = [...byVariant.entries()].sort((a, b) => a[0] - b[0]).map(([, v]) => v)
@@ -99,17 +151,185 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
       }
       return ordered
     })
+    if (allDone && !hasQueued && !hasRunning) {
+      setGenerating(false)
+      if (hasSuccess) {
+        setGenerated(true)
+        setCompletionStatus("awaiting_cover")
+      }
+    }
   }, [batchTasks])
 
-  const { startPolling, startPollingBatch, retryTask, clearTimer } = useGenerationPolling({
+  const { startPolling, pollBatchTaskQueued, retryTask, clearTimer } = useGenerationPolling({
     onProgress: handleProgress,
     onComplete: handleComplete,
     onFailed: handleFailed,
     onBatchTaskUpdate: handleBatchTaskUpdate,
   })
 
+  /** 根据 props 构造基础 payload（批量/单任务共用的字段） */
+  const buildBasePayload = useCallback((): Omit<
+    CreateGenerationTaskRequest,
+    "count" | "titles" | "voice_library_ids" | "cover_urls" | "variant_plan_ids"
+  > => {
+    const { width: outputWidth, height: outputHeight } = calculateResolution(
+      props.videoRatio || "9:16",
+    )
+    const editMode = props.editMode ?? "random"
+    const dedupEnabled = props.dedupEnabled !== false
+    const assetIds =
+      props.materialMode === "auto" ? props.smartSelectedIds : props.selectedMaterials
+    const coverUrl = props.coverSettings?.thumbnail_url || props.coverSettings?.upload_url || ""
+    // #1970：叙事模式下 ttsVoiceId 作为配音 id；随机模式用 selectedVoice
+    const voiceLibraryId =
+      editMode === "narrative"
+        ? props.ttsVoiceId || ""
+        : props.voiceMode === "clone"
+          ? props.selectedClonedVoice || props.selectedVoice || ""
+          : props.selectedVoice || ""
+
+    const bgmConfig = {
+      enabled: props.bgm !== false,
+      ...(props.bgmConfig?.music_id ? { preset_id: props.bgmConfig.music_id } : {}),
+    }
+
+    const titleConfig = props.titleSettings?.title
+      ? {
+          text: props.titleSettings.title,
+          font: props.titleSettings.font,
+          font_size: props.titleSettings.size,
+          font_color: props.titleSettings.color,
+          position: props.titleSettings.position,
+          ...(props.titleSettings.position === "custom" &&
+          props.titleSettings.posX != null &&
+          props.titleSettings.posY != null
+            ? {
+                pos_x: Math.round(props.titleSettings.posX),
+                pos_y: Math.round(props.titleSettings.posY),
+              }
+            : {}),
+          bold: props.titleSettings.bold,
+          italic: props.titleSettings.italic,
+          stroke: props.titleSettings.stroke
+            ? {
+                enabled: true,
+                width: props.titleSettings.strokeWidth ?? 4,
+                color: props.titleSettings.strokeColor ?? "#000000",
+              }
+            : { enabled: false },
+          shadow: props.titleSettings.shadow
+            ? {
+                enabled: true,
+                offset_x: props.titleSettings.shadowOffsetX ?? 2,
+                offset_y: props.titleSettings.shadowOffsetY ?? 2,
+                blur: props.titleSettings.shadowBlur ?? 4,
+                color: props.titleSettings.shadowColor ?? "rgba(0,0,0,0.8)",
+              }
+            : { enabled: false },
+          line_height: props.titleSettings.lineHeight ?? 1.2,
+          margin_top: props.titleSettings.marginTop ?? 24,
+          max_chars_per_line: props.titleSettings.maxCharsPerLine ?? 0,
+          ...(props.titleSettings.bgEnabled
+            ? {
+                background: {
+                  enabled: true,
+                  color: props.titleSettings.bgColor,
+                  padding: props.titleSettings.bgPadding,
+                  radius: props.titleSettings.bgRadius,
+                },
+              }
+            : { background: { enabled: false } }),
+          line_overrides: (props.titleSettings.lineOverrides ?? []).map((lo) => ({
+            line_index: lo.line_index,
+            text: lo.text,
+            size: lo.size,
+            color: lo.color,
+            bold: lo.bold,
+            italic: lo.italic,
+            stroke: lo.stroke,
+            highlights: lo.highlights?.map((h) => ({
+              word: h.word,
+              color: h.color,
+              bold: h.bold,
+              scale: h.scale,
+            })),
+          })),
+          ...(props.titleSettings.coverTitle
+            ? {
+                cover_title_config: {
+                  title: props.titleSettings.coverTitle.title,
+                  font: props.titleSettings.coverTitle.font,
+                  font_size: props.titleSettings.coverTitle.size,
+                  font_color: props.titleSettings.coverTitle.color,
+                  bold: props.titleSettings.coverTitle.bold,
+                  italic: props.titleSettings.coverTitle.italic,
+                  position: props.titleSettings.coverTitle.position,
+                  stroke: props.titleSettings.coverTitle.stroke
+                    ? {
+                        enabled: true,
+                        width: props.titleSettings.coverTitle.strokeWidth ?? 4,
+                        color: props.titleSettings.coverTitle.strokeColor ?? "#000000",
+                      }
+                    : { enabled: false },
+                  shadow: props.titleSettings.coverTitle.shadow
+                    ? {
+                        enabled: true,
+                        offset_x: props.titleSettings.coverTitle.shadowOffsetX ?? 2,
+                        offset_y: props.titleSettings.coverTitle.shadowOffsetY ?? 2,
+                        blur: props.titleSettings.coverTitle.shadowBlur ?? 4,
+                        color: props.titleSettings.coverTitle.shadowColor ?? "rgba(0,0,0,0.8)",
+                      }
+                    : { enabled: false },
+                  ...(props.titleSettings.coverTitle.bgEnabled
+                    ? {
+                        background: {
+                          enabled: true,
+                          color: props.titleSettings.coverTitle.bgColor,
+                          padding: props.titleSettings.coverTitle.bgPadding,
+                          radius: props.titleSettings.coverTitle.bgRadius,
+                        },
+                      }
+                    : { background: { enabled: false } }),
+                },
+              }
+            : {}),
+        }
+      : undefined
+
+    const payload: Omit<
+      CreateGenerationTaskRequest,
+      "count" | "titles" | "voice_library_ids" | "cover_urls" | "variant_plan_ids"
+    > = {
+      template_id: selectedTemplate,
+      asset_ids: assetIds,
+      output_width: outputWidth,
+      output_height: outputHeight,
+      cover_url: coverUrl,
+      custom_title: props.titleSettings?.title || "",
+      duration: props.duration || undefined,
+      video_ratio: props.videoRatio,
+      assembly_mode: editMode,
+      ...(editMode === "narrative" && props.selectedScript?.id
+        ? {
+            script_id: props.selectedScript.id,
+            tts_voice_id: props.ttsVoiceId || undefined,
+            tts_voice_source: props.ttsVoiceSource || undefined,
+            tts_style: props.ttsStyle || undefined,
+          }
+        : {}),
+      dedup_enabled: dedupEnabled,
+      voice_library_id: voiceLibraryId,
+      ...(props.selectedVoice && !voiceLibraryId ? { voice_ids: [props.selectedVoice] } : {}),
+      bgm_config: bgmConfig as CreateGenerationTaskRequest["bgm_config"],
+      ...(props.sourceEditPlanId ? { source_edit_plan_id: props.sourceEditPlanId } : {}),
+      ...(titleConfig ? ({ title_config: titleConfig } as Record<string, unknown>) : {}),
+    }
+
+    return payload
+  }, [props, selectedTemplate])
+
   /* ── 生成视频 ──
-     返回 true 表示任务创建成功并已开始轮询；false 表示校验未通过或创建失败 */
+     返回 true 表示任务创建成功并已开始轮询（含排队中）；false 表示校验未通过或创建失败 */
   const generate = useCallback(async (): Promise<boolean> => {
     const errorMsg = validateGenerateInputs(props)
     if (errorMsg) {
@@ -117,34 +337,28 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
       return false
     }
 
+    cancelledRef.current = false
+    clearQueueTimers()
     setGenerating(true)
     setProgress(0)
     setGenerated(false)
     setGenerateError(null)
+    setCompletionStatus(null)
     setBatchTasks([])
     setGeneratedVideos([])
     setCurrentTaskId("")
     clearTimer()
 
+    const basePayload = buildBasePayload()
+    const assetIds = basePayload.asset_ids
+    const isBatch = (props.previewCount || 1) > 1
+
     try {
-      const { width: outputWidth, height: outputHeight } = calculateResolution(
-        props.videoRatio || "9:16",
-      )
-      const editMode = props.editMode ?? "random"
-      const dedupEnabled = props.dedupEnabled !== false
-
-      const assetIds =
-        props.materialMode === "auto" ? props.smartSelectedIds : props.selectedMaterials
-
-      // from-assets 已由 useStep2Materials 在用户选素材时（debounce 800ms）调用，
-      // 后端已改为异步秒级返回，这里做一次轻量兜底：
-      // 单次查 clips，已有则直接放行；没有则再调一次 from-assets。
+      // from-assets 兜底：片段不存在则补一次
       if (assetIds.length > 0 && selectedTemplate) {
         try {
           const clipList = await getEditPlanClips(selectedTemplate, { limit: 500 })
           if (clipList.items.length === 0) {
-            // 片段不存在（极端情况：useStep2Materials 的 debounce 还没触发）
-            // 手动补一次 from-assets（后端秒级返回）
             await createClipsFromAssets(selectedTemplate, assetIds, "main")
           }
         } catch {
@@ -152,221 +366,185 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
         }
       }
 
-      const isBatch = (props.previewCount || 1) > 1
-      const hide = message.loading(
-        isBatch ? `正在生成 ${props.previewCount} 个视频...` : "正在生成预览视频...",
-        0,
-      )
-
-      const coverUrl = props.coverSettings?.thumbnail_url || props.coverSettings?.upload_url || ""
-
-      // #1970：叙事模式下 ttsVoiceId 作为配音 id；随机模式用 selectedVoice
-      const voiceLibraryId =
-        editMode === "narrative"
-          ? props.ttsVoiceId || ""
-          : props.voiceMode === "clone"
-            ? props.selectedClonedVoice || props.selectedVoice || ""
-            : props.selectedVoice || ""
-
-      /* ── 批量变体数组（长度1=共用，长度=count=独立，空=回退单值） ── */
-      const indexes =
-        isBatch && props.selectedVariantIndexes?.length
-          ? props.selectedVariantIndexes
-          : Array.from({ length: props.previewCount || 1 }, (_, i) => i)
-      const batchCount = isBatch ? indexes.length : 1
-
-      // 标题文字数组：批量时按勾选顺序
-      const titlesArr =
-        isBatch && (props.variantTitles?.length || 0) >= batchCount
-          ? indexes.map((i) => props.variantTitles![i] || props.titleSettings?.title || "")
-          : []
-      // 配音数组：独立配音模式按勾选顺序；否则不传（回退共用 voice_library_id）
-      const voiceArr =
-        isBatch && props.voiceModePerVideo && props.variantVoiceLibraryIds?.length
-          ? indexes.map((i) => props.variantVoiceLibraryIds![i] || voiceLibraryId)
-          : []
-      // 封面数组：批量时按勾选顺序（未设置封面的变体传空串，后端回退智能封面）
-      const coversArr =
-        isBatch && props.variantCoverUrls?.length
-          ? indexes.map((i) => props.variantCoverUrls![i] || "")
-          : []
-      // #1744 变体 plan 数组：预览阶段后端独立选片产出的 plan id，按勾选顺序回传，
-      // 后端直接关联这些 plan 渲染（不再重新选片）→ 预览所见即成片。
-      // 全部为空（降级本地模拟/后端端点未上线）时不传，后端走自身独立选片。
-      const variantPlansArr =
-        isBatch && props.variantPlanIds?.length
-          ? indexes.map((i) => props.variantPlanIds![i] || "")
-          : []
-      const hasVariantPlans = variantPlansArr.some((id) => !!id)
-
-      try {
-        const taskResp = await createGenerationTask({
-          template_id: selectedTemplate,
-          asset_ids: assetIds,
-          output_width: outputWidth,
-          output_height: outputHeight,
-          cover_url: coverUrl,
-          custom_title: props.titleSettings?.title || "",
-          duration: props.duration || undefined,
-          video_ratio: props.videoRatio,
-          assembly_mode: editMode,
-          ...(editMode === "narrative" && props.selectedScript?.id
-            ? {
-                script_id: props.selectedScript.id,
-                tts_voice_id: props.ttsVoiceId || undefined,
-                tts_voice_source: props.ttsVoiceSource || undefined,
-                tts_style: props.ttsStyle || undefined,
-              }
-            : {}),
-          dedup_enabled: dedupEnabled,
-          voice_library_id: voiceLibraryId,
-          ...(props.selectedVoice && !voiceLibraryId ? { voice_ids: [props.selectedVoice] } : {}),
-          bgm_config: {
-            enabled: props.bgm !== false,
-            ...(props.bgmConfig?.music_id ? { preset_id: props.bgmConfig.music_id } : {}),
-          },
-          ...(props.sourceEditPlanId ? { source_edit_plan_id: props.sourceEditPlanId } : {}),
-          ...(isBatch ? { count: batchCount } : {}),
-          ...(titlesArr.length ? { titles: titlesArr } : {}),
-          ...(voiceArr.length ? { voice_library_ids: voiceArr } : {}),
-          ...(coversArr.length ? { cover_urls: coversArr } : {}),
-          ...(hasVariantPlans ? { variant_plan_ids: variantPlansArr } : {}),
-          ...(props.titleSettings?.title
-            ? {
-                title_config: {
-                  text: props.titleSettings.title,
-                  font: props.titleSettings.font,
-                  font_size: props.titleSettings.size,
-                  font_color: props.titleSettings.color,
-                  position: props.titleSettings.position,
-                  ...(props.titleSettings.position === "custom" &&
-                  props.titleSettings.posX != null &&
-                  props.titleSettings.posY != null
-                    ? {
-                        pos_x: Math.round(props.titleSettings.posX),
-                        pos_y: Math.round(props.titleSettings.posY),
-                      }
-                    : {}),
-                  bold: props.titleSettings.bold,
-                  italic: props.titleSettings.italic,
-                  stroke: props.titleSettings.stroke
-                    ? {
-                        enabled: true,
-                        width: props.titleSettings.strokeWidth ?? 4,
-                        color: props.titleSettings.strokeColor ?? "#000000",
-                      }
-                    : { enabled: false },
-                  shadow: props.titleSettings.shadow
-                    ? {
-                        enabled: true,
-                        offset_x: props.titleSettings.shadowOffsetX ?? 2,
-                        offset_y: props.titleSettings.shadowOffsetY ?? 2,
-                        blur: props.titleSettings.shadowBlur ?? 4,
-                        color: props.titleSettings.shadowColor ?? "rgba(0,0,0,0.8)",
-                      }
-                    : { enabled: false },
-                  line_height: props.titleSettings.lineHeight ?? 1.2,
-                  margin_top: props.titleSettings.marginTop ?? 24,
-                  max_chars_per_line: props.titleSettings.maxCharsPerLine ?? 0,
-                  ...(props.titleSettings.bgEnabled
-                    ? {
-                        background: {
-                          enabled: true,
-                          color: props.titleSettings.bgColor,
-                          padding: props.titleSettings.bgPadding,
-                          radius: props.titleSettings.bgRadius,
-                        },
-                      }
-                    : { background: { enabled: false } }),
-                  line_overrides: (props.titleSettings.lineOverrides ?? []).map((lo) => ({
-                    line_index: lo.line_index,
-                    text: lo.text,
-                    size: lo.size,
-                    color: lo.color,
-                    bold: lo.bold,
-                    italic: lo.italic,
-                    stroke: lo.stroke,
-                    highlights: lo.highlights?.map((h) => ({
-                      word: h.word,
-                      color: h.color,
-                      bold: h.bold,
-                      scale: h.scale,
-                    })),
-                  })),
-                  ...(props.titleSettings.coverTitle
-                    ? {
-                        cover_title_config: {
-                          title: props.titleSettings.coverTitle.title,
-                          font: props.titleSettings.coverTitle.font,
-                          font_size: props.titleSettings.coverTitle.size,
-                          font_color: props.titleSettings.coverTitle.color,
-                          bold: props.titleSettings.coverTitle.bold,
-                          italic: props.titleSettings.coverTitle.italic,
-                          position: props.titleSettings.coverTitle.position,
-                          stroke: props.titleSettings.coverTitle.stroke
-                            ? {
-                                enabled: true,
-                                width: props.titleSettings.coverTitle.strokeWidth ?? 4,
-                                color: props.titleSettings.coverTitle.strokeColor ?? "#000000",
-                              }
-                            : { enabled: false },
-                          shadow: props.titleSettings.coverTitle.shadow
-                            ? {
-                                enabled: true,
-                                offset_x: props.titleSettings.coverTitle.shadowOffsetX ?? 2,
-                                offset_y: props.titleSettings.coverTitle.shadowOffsetY ?? 2,
-                                blur: props.titleSettings.coverTitle.shadowBlur ?? 4,
-                                color:
-                                  props.titleSettings.coverTitle.shadowColor ?? "rgba(0,0,0,0.8)",
-                              }
-                            : { enabled: false },
-                          ...(props.titleSettings.coverTitle.bgEnabled
-                            ? {
-                                background: {
-                                  enabled: true,
-                                  color: props.titleSettings.coverTitle.bgColor,
-                                  padding: props.titleSettings.coverTitle.bgPadding,
-                                  radius: props.titleSettings.coverTitle.bgRadius,
-                                },
-                              }
-                            : { background: { enabled: false } }),
-                        },
-                      }
-                    : {}),
-                },
-              }
-            : {}),
-        })
-        hide()
-        const taskIds = (taskResp.items || []).map((it) => it.id).filter(Boolean)
-
-        if (taskIds.length === 0) {
-          throw new Error("创建任务成功但未返回任务 ID，请稍后在任务列表查看")
-        }
-        if (taskIds.length > 1) {
-          // 批量：任务按创建顺序与勾选变体一一对应（后端按 count 顺序创建）
-          setCurrentTaskId("")
-          startPollingBatch(taskIds.map((taskId, i) => ({ taskId, variantIndex: indexes[i] ?? i })))
-        } else {
+      if (!isBatch) {
+        /* ── 单视频：原逻辑（一次提交 count=1） ── */
+        const hide = message.loading("正在生成预览视频...", 0)
+        try {
+          const taskResp = await createGenerationTask({ ...basePayload, count: 1 })
+          hide()
+          const taskIds = (taskResp.items || []).map((it) => it.id).filter(Boolean)
+          if (taskIds.length === 0) {
+            throw new Error("创建任务成功但未返回任务 ID，请稍后在任务列表查看")
+          }
           setCurrentTaskId(taskIds[0])
           startPolling(taskIds[0])
+        } catch (err) {
+          hide()
+          throw err
         }
-      } catch (err) {
-        hide()
-        throw err
+        return true
       }
+
+      /* ── 批量：支持任意数量视频，按队列容量串行提交，429 自动排队重试 ── */
+      const indexes = props.selectedVariantIndexes?.length
+        ? props.selectedVariantIndexes
+        : Array.from({ length: props.previewCount || 1 }, (_, i) => i)
+      const batchCount = indexes.length
+
+      const titlesAll =
+        (props.variantTitles?.length || 0) >= batchCount
+          ? indexes.map((i) => props.variantTitles![i] || props.titleSettings?.title || "")
+          : indexes.map(() => props.titleSettings?.title || "")
+      const voiceArrAll =
+        props.voiceModePerVideo && props.variantVoiceLibraryIds?.length
+          ? indexes.map(
+              (i) => props.variantVoiceLibraryIds![i] || basePayload.voice_library_id || "",
+            )
+          : []
+      const coversAll = props.variantCoverUrls?.length
+        ? indexes.map((i) => props.variantCoverUrls![i] || "")
+        : indexes.map(() => "")
+      const plansAll = props.variantPlanIds?.length
+        ? indexes.map((i) => props.variantPlanIds![i] || "")
+        : indexes.map(() => "")
+
+      const hasAnyVoice = voiceArrAll.some((v) => !!v)
+      const hasAnyCover = coversAll.some((u) => !!u)
+      const hasAnyPlan = plansAll.some((id) => !!id)
+
+      // 先用占位 ID 把所有变体卡片置为 queued，UI 可见
+      const placeholderIds = indexes.map((_, i) => `__queued_${Date.now()}_${i}`)
+      const initialTasks: BatchTaskState[] = indexes.map((variantIndex, i) => ({
+        taskId: placeholderIds[i],
+        variantIndex,
+        status: "queued",
+        progress: 0,
+        error: null,
+        videos: [],
+      }))
+      setBatchTasks(initialTasks)
+
+      message.loading({
+        content: `已提交 ${batchCount} 个视频任务，系统按队列容量依次渲染…`,
+        key: "batch-gen",
+        duration: 3,
+      })
+
+      /** 将占位 taskId 更新为真实 taskId（卡片引用同一对象） */
+      const replacePlaceholder = (placeholderId: string, realTaskId: string) => {
+        setBatchTasks((prev) => {
+          const idx = prev.findIndex((t) => t.taskId === placeholderId)
+          if (idx === -1) return prev
+          const next = [...prev]
+          next[idx] = { ...next[idx], taskId: realTaskId }
+          return next
+        })
+      }
+
+      /** 提交某一索引的单任务（count=1），成功后返回真实 taskId；429/503 则返回 waitMs */
+      const submitOne = async (
+        i: number,
+      ): Promise<{ queued: true; waitMs: number } | { queued: false; taskId: string }> => {
+        const body: CreateGenerationTaskRequest = {
+          ...basePayload,
+          count: 1,
+          titles: [titlesAll[i] || ""],
+          ...(hasAnyVoice
+            ? { voice_library_ids: [voiceArrAll[i] || basePayload.voice_library_id || ""] }
+            : {}),
+          ...(hasAnyCover ? { cover_urls: [coversAll[i] || ""] } : {}),
+          ...(hasAnyPlan && plansAll[i] ? { variant_plan_ids: [plansAll[i]] } : {}),
+        }
+        try {
+          const resp = await createGenerationTask(body)
+          const item = resp.items?.[0]
+          const tid = item?.id
+          if (!tid) throw new Error("创建任务成功但未返回任务 ID")
+          return { queued: false, taskId: tid }
+        } catch (err) {
+          const q = isUserQueueFullError(err)
+          if (q) return { queued: true, waitMs: q.waitMs }
+          throw err
+        }
+      }
+
+      // 串行提交：每次提交一个；429/503 则等待后重试；其它错误立即标记该任务失败
+      let fatalErr: unknown = null
+      for (let i = 0; i < batchCount; i++) {
+        if (cancelledRef.current) return false
+        const variantIndex = indexes[i]
+        const placeholderId = placeholderIds[i]
+        let attempt = 0
+        let submitted = false
+        while (!submitted) {
+          if (cancelledRef.current) return false
+          attempt++
+          try {
+            const result = await submitOne(i)
+            if (!result.queued) {
+              replacePlaceholder(placeholderId, result.taskId)
+              // 先更新到 running，再启动单任务增量轮询（不触发整体 onComplete）
+              pollBatchTaskQueued(result.taskId, variantIndex)
+              submitted = true
+            } else {
+              // 排队：保持 queued 状态，等待后重试
+              handleBatchTaskUpdate(placeholderId, {
+                taskId: placeholderId,
+                variantIndex,
+                status: "queued",
+                progress: 0,
+                error: null,
+              })
+              if (attempt === 1) {
+                message.info({
+                  content: `队列繁忙，${Math.round(result.waitMs / 1000)} 秒后自动继续提交后续视频…`,
+                  key: "batch-gen",
+                  duration: 4,
+                })
+              }
+              await sleep(Math.min(result.waitMs, 60_000))
+            }
+          } catch (err) {
+            // 非限流错误：该任务标记失败，继续后续任务（不阻断整个批量）
+            console.error("[batch generate] 任务提交失败:", err)
+            const msg = translateError(extractBackendError(err))
+            handleBatchTaskUpdate(placeholderId, {
+              taskId: placeholderId,
+              variantIndex,
+              status: "failed",
+              error: msg,
+              progress: 0,
+            })
+            submitted = true
+            if (!fatalErr) fatalErr = err
+          }
+        }
+      }
+
+      if (fatalErr) {
+        // 有任务失败但其余已成功，整体不 throw；由 UI 展示单个失败卡片
+      }
+      return true
     } catch (err: unknown) {
       console.error("[handleGenerate] 生成失败:", err)
-      setGenerating(false)
       const backendMsg = extractBackendError(err)
       console.error("[handleGenerate] 错误信息:", backendMsg, "完整错误:", err)
       const finalMsg = translateError(backendMsg)
       setGenerateError(finalMsg)
+      setGenerating(false)
       message.error(finalMsg)
       return false
     }
-    return true
-  }, [props, clearTimer, startPolling, startPollingBatch, selectedTemplate])
+  }, [
+    props,
+    clearTimer,
+    startPolling,
+    selectedTemplate,
+    buildBasePayload,
+    handleBatchTaskUpdate,
+    clearQueueTimers,
+    pollBatchTaskQueued,
+  ])
 
   const retry = useCallback(() => {
     setGenerateError(null)
@@ -376,9 +554,10 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
   /** 第5步：单独重试某个失败任务 */
   const retryBatchTask = useCallback(
     (taskId: string) => {
+      handleBatchTaskUpdate(taskId, { status: "running", progress: 0, error: null, videos: [] })
       retryTask(taskId)
     },
-    [retryTask],
+    [retryTask, handleBatchTaskUpdate],
   )
 
   const dismissError = useCallback(() => {
@@ -423,6 +602,7 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
     generated,
     generateError,
     generatedVideos,
+    completionStatus,
     currentTaskId,
     generate,
     retry,

apps/web/src/pages/tasks/constants.tsx

@@ -45,6 +45,11 @@ export const STATUS_CONFIG: Record<
     color: "processing",
     icon: <SyncOutlined spin />,
   },
+  awaiting_cover: {
+    label: "待选封面",
+    color: "warning",
+    icon: <ClockCircleOutlined />,
+  },
   completed: {
     label: "已完成",
     color: "success",

apps/web/src/pages/viral-video/components/AssetPickerModal.tsx

@@ -0,0 +1,264 @@
+/**
+ * 爆款视频素材选择弹窗（通用版，支持 image/video/voice）
+ * 基于 ai-avatar 的 ModalAssetPicker 改造：
+ *  - kind 可传 "image" | "video" | "voice"
+ *  - 多图场景 multiple=true 时底部"确认选择"
+ *  - 单选场景点击即回调关闭
+ */
+import { useEffect, useState } from "react"
+import { getAssets, getAssetLibraries, type AssetItem, type AssetLibraryItem } from "@/api/assets"
+
+export interface AssetPickerModalProps {
+  open: boolean
+  kind: "image" | "video" | "voice"
+  multiple?: boolean
+  title?: string
+  onClose: () => void
+  onSelect: (assets: AssetItem[]) => void
+}
+
+const KIND_LABEL: Record<AssetPickerModalProps["kind"], string> = {
+  image: "图片",
+  video: "视频",
+  voice: "音频",
+}
+
+const MIME_KIND: Record<AssetPickerModalProps["kind"], string> = {
+  image: "image",
+  video: "video",
+  voice: "audio",
+}
+
+export default function AssetPickerModal({
+  open,
+  kind,
+  multiple = false,
+  title,
+  onClose,
+  onSelect,
+}: AssetPickerModalProps) {
+  const [keyword, setKeyword] = useState("")
+  const [libraries, setLibraries] = useState<AssetLibraryItem[]>([])
+  const [libraryId, setLibraryId] = useState<string>("")
+  const [assets, setAssets] = useState<AssetItem[]>([])
+  const [picked, setPicked] = useState<Set<string>>(new Set())
+  const [loadingLibs, setLoadingLibs] = useState(false)
+  const [loadingAssets, setLoadingAssets] = useState(false)
+  const [error, setError] = useState("")
+
+  useEffect(() => {
+    if (!open) return
+    setKeyword("")
+    setLibraries([])
+    setLibraryId("")
+    setAssets([])
+    setError("")
+    setPicked(new Set())
+  }, [open])
+
+  useEffect(() => {
+    if (!open) return
+    let cancelled = false
+    setLoadingLibs(true)
+    getAssetLibraries(kind)
+      .then((libs) => {
+        if (cancelled) return
+        const list = Array.isArray(libs) ? libs : []
+        setLibraries(list)
+        if (list.length > 0) setLibraryId(list[0].id)
+      })
+      .catch(() => {
+        if (!cancelled) setError("素材库加载失败，请重试")
+      })
+      .finally(() => {
+        if (!cancelled) setLoadingLibs(false)
+      })
+    return () => {
+      cancelled = true
+    }
+  }, [open, kind])
+
+  useEffect(() => {
+    if (!open || !libraryId) return
+    let cancelled = false
+    setLoadingAssets(true)
+    const load = async () => {
+      try {
+        const { items } = await getAssets(libraryId, { page_size: 100 })
+        if (cancelled) return
+        let list = Array.isArray(items) ? items : []
+        const mimePrefix = MIME_KIND[kind]
+        list = list.filter((a) => !a.mime_type || a.mime_type.startsWith(mimePrefix))
+        const kw = keyword.trim()
+        if (kw) list = list.filter((a) => a.name?.includes(kw))
+        setAssets(list)
+        setError("")
+      } catch {
+        if (!cancelled) {
+          setError("素材加载失败，请重试")
+          setAssets([])
+        }
+      } finally {
+        if (!cancelled) setLoadingAssets(false)
+      }
+    }
+    const timer = window.setTimeout(load, 250)
+    return () => {
+      cancelled = true
+      window.clearTimeout(timer)
+    }
+  }, [open, libraryId, keyword, kind])
+
+  const thumbFor = (a: AssetItem) => {
+    if (kind === "image") return a.thumbnail_url || a.file_url
+    if (kind === "video") return a.thumbnail_url
+    return ""
+  }
+
+  const togglePick = (id: string) => {
+    if (multiple) {
+      setPicked((prev) => {
+        const n = new Set(prev)
+        if (n.has(id)) n.delete(id)
+        else n.add(id)
+        return n
+      })
+    } else {
+      const asset = assets.find((a) => a.id === id)
+      if (asset) {
+        onSelect([asset])
+        onClose()
+      }
+    }
+  }
+
+  const handleConfirm = () => {
+    const list = assets.filter((a) => picked.has(a.id))
+    if (list.length > 0) onSelect(list)
+    onClose()
+  }
+
+  if (!open) return null
+
+  return (
+    <div className="vv-modal-mask" onClick={onClose}>
+      <div className="vv-modal" onClick={(e) => e.stopPropagation()}>
+        <div className="vv-modal-head">
+          <span className="vv-modal-title">{title || `选择${KIND_LABEL[kind]}素材`}</span>
+          <button className="vv-modal-close" onClick={onClose} aria-label="关闭">
+            ×
+          </button>
+        </div>
+        <div className="vv-modal-body">
+          <div className="vv-asset-search">
+            <select
+              className="vv-input"
+              style={{ width: 170, flex: "0 0 auto" }}
+              value={libraryId}
+              onChange={(e) => setLibraryId(e.target.value)}
+              disabled={loadingLibs || libraries.length === 0}
+            >
+              {libraries.length === 0 ? (
+                <option value="">
+                  {loadingLibs ? "加载中…" : `暂无${KIND_LABEL[kind]}素材库`}
+                </option>
+              ) : (
+                libraries.map((lib) => (
+                  <option key={lib.id} value={lib.id}>
+                    📁 {lib.name}
+                  </option>
+                ))
+              )}
+            </select>
+            <input
+              className="vv-input"
+              type="text"
+              placeholder={`搜索${KIND_LABEL[kind]}名称…`}
+              value={keyword}
+              onChange={(e) => setKeyword(e.target.value)}
+            />
+          </div>
+
+          {libraries.length === 0 && !loadingLibs ? (
+            <div className="vv-modal-empty">
+              <div className="vv-empty-icon">📁</div>
+              暂无{KIND_LABEL[kind]}素材库，请先在「素材库」中创建并上传
+            </div>
+          ) : loadingAssets ? (
+            <div className="vv-modal-empty">
+              <div className="vv-empty-icon">⏳</div>
+              素材加载中…
+            </div>
+          ) : error ? (
+            <div className="vv-modal-empty">
+              <div className="vv-empty-icon">⚠️</div>
+              {error}
+            </div>
+          ) : assets.length === 0 ? (
+            <div className="vv-modal-empty">
+              <div className="vv-empty-icon">
+                {kind === "image" ? "🖼️" : kind === "video" ? "🎬" : "🎵"}
+              </div>
+              {kind === "voice" ? (
+                <>
+                  <div style={{ marginTop: 8, fontSize: 13 }}>暂无配音素材</div>
+                  <div style={{ marginTop: 4, fontSize: 12, color: "#9ca3af" }}>
+                    请先在「配音/我的音色」中上传音频文件，或在素材库管理中添加
+                  </div>
+                </>
+              ) : (
+                <>该素材库暂无{KIND_LABEL[kind]}素材</>
+              )}
+            </div>
+          ) : (
+            <div className={`vv-asset-thumbs vv-asset-${kind}`}>
+              {assets.map((asset) => {
+                const active = picked.has(asset.id)
+                const thumb = thumbFor(asset)
+                return (
+                  <div
+                    key={asset.id}
+                    className={`vv-thumb-card${active ? " selected" : ""}`}
+                    onClick={() => togglePick(asset.id)}
+                  >
+                    {thumb ? (
+                      <img src={thumb} alt={asset.name} />
+                    ) : kind === "video" ? (
+                      <video src={asset.file_url} muted preload="metadata" />
+                    ) : (
+                      <div className="vv-thumb-ph">{kind === "voice" ? "🎵" : "📄"}</div>
+                    )}
+                    {active && <div className="vv-thumb-check">✓</div>}
+                    <div className="vv-thumb-name" title={asset.name}>
+                      <span className="vv-thumb-name-txt">{asset.name}</span>
+                      {kind === "voice" &&
+                        typeof asset.duration === "number" &&
+                        asset.duration > 0 && (
+                          <span className="vv-thumb-dur">{Math.round(asset.duration)}s</span>
+                        )}
+                    </div>
+                  </div>
+                )
+              })}
+            </div>
+          )}
+        </div>
+        {multiple && (
+          <div className="vv-modal-foot">
+            <button className="vv-btn vv-btn-ghost vv-btn-sm" onClick={onClose}>
+              取消
+            </button>
+            <button
+              className="vv-btn vv-btn-primary"
+              style={{ width: "auto", marginTop: 0, padding: "8px 18px" }}
+              onClick={handleConfirm}
+              disabled={picked.size === 0}
+            >
+              确认选择（{picked.size}）
+            </button>
+          </div>
+        )}
+      </div>
+    </div>
+  )
+}

apps/web/src/pages/viral-video/components/PresetVoicePickerModal.tsx

@@ -0,0 +1,355 @@
+/**
+ * 内置音色选择弹窗（浅色紫调版）
+ * - 标题「选择音色」+ 搜索框 + 分类筛选 + 3列卡片网格 + 试听 + 选中 + 完成选择
+ */
+import React, { useEffect, useMemo, useRef, useState } from "react"
+import {
+  CloseOutlined,
+  SearchOutlined,
+  PlayCircleOutlined,
+  PauseCircleOutlined,
+  UserOutlined,
+} from "@ant-design/icons"
+import { Select, Input } from "antd"
+
+export interface PresetVoice {
+  id: string
+  name: string
+  gender?: "female" | "male" | "child" | "other"
+  gender_label?: string
+  category?: string
+  avatar_url?: string
+  sample_audio_url?: string
+  desc?: string
+}
+
+interface Props {
+  open: boolean
+  voices?: PresetVoice[]
+  loading?: boolean
+  selectedId?: string
+  onClose: () => void
+  onConfirm: (voice: PresetVoice) => void
+}
+
+/** 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",
+    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",
+    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",
+    name: "龙三叔",
+    gender: "male",
+    category: "男声",
+    desc: "沉稳质感男声，适合有声书",
+  },
+  {
+    id: "longyue_v3",
+    name: "龙悦",
+    gender: "female",
+    category: "女声",
+    desc: "温暖磁性女声，适合广告配音",
+  },
+  {
+    id: "longshu_v3",
+    name: "龙书",
+    gender: "male",
+    category: "男声",
+    desc: "沉稳青年男声，适合教育讲解",
+  },
+  {
+    id: "longyingjing_v3",
+    name: "龙应静",
+    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",
+  },
+]
+
+const CATEGORY_LABELS: Record<string, string> = {
+  all: "全部分类",
+  female: "女声",
+  male: "男声",
+  child: "童声",
+  dialect: "方言",
+  emotion: "情绪",
+}
+
+const GENDER_LABEL = (v: PresetVoice) => {
+  if (v.gender_label) return v.gender_label
+  const g = v.gender
+  if (g === "female") return "女声·女声"
+  if (g === "male") return "男声·男声"
+  if (g === "child") return "童声·童声"
+  return "性别未标注·其他"
+}
+
+const AVATAR_BG = (gender?: string) => {
+  if (gender === "female") return "#fce7f3"
+  if (gender === "male") return "#dbeafe"
+  if (gender === "child") return "#fef3c7"
+  return "#f3f0ff"
+}
+const AVATAR_COLOR = (gender?: string) => {
+  if (gender === "female") return "#be185d"
+  if (gender === "male") return "#1d4ed8"
+  if (gender === "child") return "#b45309"
+  return "#7c3aed"
+}
+
+const PresetVoicePickerModal: React.FC<Props> = ({
+  open,
+  voices,
+  loading,
+  selectedId,
+  onClose,
+  onConfirm,
+}) => {
+  const [keyword, setKeyword] = useState("")
+  const [category, setCategory] = useState<string>("all")
+  const [pickedId, setPickedId] = useState<string | undefined>(selectedId)
+  const [playingId, setPlayingId] = useState<string | null>(null)
+  const audioRef = useRef<HTMLAudioElement | null>(null)
+
+  useEffect(() => {
+    if (open) {
+      setKeyword("")
+      setCategory("all")
+      setPickedId(selectedId)
+      setPlayingId(null)
+    }
+  }, [open, selectedId])
+
+  // 停止播放
+  useEffect(() => {
+    return () => {
+      audioRef.current?.pause()
+      audioRef.current = null
+    }
+  }, [])
+
+  // 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)
+      return {
+        ...v,
+        gender: v.gender || mockMatch?.gender,
+        category:
+          v.category ||
+          mockMatch?.category ||
+          (v.gender === "female" ? "女声" : v.gender === "male" ? "男声" : "其他"),
+        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）
+    return realList.length > 0 ? realList : MOCK_VOICES
+  }, [voices])
+
+  const categories = useMemo(() => {
+    const set = new Set<string>()
+    allVoices.forEach((v) => {
+      if (v.category) set.add(v.category)
+    })
+    return Array.from(set)
+  }, [allVoices])
+
+  const filtered = useMemo(() => {
+    const kw = keyword.trim().toLowerCase()
+    return allVoices.filter((v) => {
+      if (category !== "all") {
+        if (v.category !== category && category !== CATEGORY_LABELS[v.gender || ""]) {
+          // gender 兜底匹配
+          if (
+            !(category === "女声" && v.gender === "female") &&
+            !(category === "男声" && v.gender === "male") &&
+            !(category === "童声" && v.gender === "child") &&
+            !(category === "方言" && v.category === "方言") &&
+            !(category === "情绪" && v.category === "情绪")
+          ) {
+            return false
+          }
+        }
+      }
+      if (!kw) return true
+      return (
+        v.name?.toLowerCase().includes(kw) ||
+        v.desc?.toLowerCase().includes(kw) ||
+        v.category?.toLowerCase().includes(kw)
+      )
+    })
+  }, [allVoices, keyword, category])
+
+  const handlePreview = (v: PresetVoice) => {
+    if (!v.sample_audio_url) {
+      // 无示例音频
+      return
+    }
+    if (playingId === v.id) {
+      audioRef.current?.pause()
+      setPlayingId(null)
+      return
+    }
+    audioRef.current?.pause()
+    const a = new Audio(v.sample_audio_url)
+    a.onended = () => setPlayingId(null)
+    a.onerror = () => setPlayingId(null)
+    a.play().catch(() => {})
+    audioRef.current = a
+    setPlayingId(v.id)
+  }
+
+  const handleConfirm = () => {
+    const picked = allVoices.find((v) => v.id === pickedId)
+    if (!picked) return
+    onConfirm(picked)
+  }
+
+  if (!open) return null
+
+  return (
+    <div className="vv-modal-mask" onClick={onClose}>
+      <div className="vv-modal vv-modal-lg" onClick={(e) => e.stopPropagation()}>
+        <div className="vv-modal-head">
+          <div className="vv-modal-title">选择音色</div>
+          <button className="vv-modal-close" onClick={onClose}>
+            <CloseOutlined />
+          </button>
+        </div>
+        <div className="vv-modal-body">
+          {/* 搜索 */}
+          <Input
+            className="vv-voice-search"
+            placeholder="搜索音色名称或风格"
+            prefix={<SearchOutlined style={{ color: "#9ca3af" }} />}
+            value={keyword}
+            onChange={(e) => setKeyword(e.target.value)}
+            allowClear
+            size="large"
+          />
+          {/* 分类筛选 */}
+          <div className="vv-voice-cat-row">
+            <span className="vv-voice-cat-label">音色分类</span>
+            <Select
+              value={category}
+              onChange={setCategory}
+              style={{ width: 180 }}
+              options={[
+                { value: "all", label: "全部分类" },
+                ...[
+                  "女声",
+                  "男声",
+                  "童声",
+                  "方言",
+                  "情绪",
+                  ...categories.filter(
+                    (c) => !["女声", "男声", "童声", "方言", "情绪"].includes(c),
+                  ),
+                ].map((c) => ({ value: c, label: c })),
+              ]}
+            />
+          </div>
+          {/* 卡片网格 */}
+          <div className="vv-voice-grid">
+            {loading && filtered.length === 0 ? (
+              <div className="vv-modal-empty">加载中…</div>
+            ) : filtered.length === 0 ? (
+              <div className="vv-modal-empty">没有匹配的音色</div>
+            ) : (
+              filtered.map((v) => {
+                const isPicked = pickedId === v.id
+                const isPlaying = playingId === v.id
+                return (
+                  <div
+                    key={v.id}
+                    className={`vv-voice-card ${isPicked ? "selected" : ""}`}
+                    onClick={() => setPickedId(v.id)}
+                  >
+                    <div
+                      className="vv-voice-card-avatar"
+                      style={{ background: AVATAR_BG(v.gender), color: AVATAR_COLOR(v.gender) }}
+                    >
+                      {v.avatar_url ? (
+                        <img src={v.avatar_url} alt={v.name} />
+                      ) : (
+                        <UserOutlined style={{ fontSize: 22 }} />
+                      )}
+                    </div>
+                    <div className="vv-voice-card-name" title={v.name}>
+                      {v.name}
+                    </div>
+                    <div className="vv-voice-card-gender">{GENDER_LABEL(v)}</div>
+                    {v.desc && <div className="vv-voice-card-desc">{v.desc}</div>}
+                    <div className="vv-voice-card-actions">
+                      <button
+                        className={`vv-voice-card-btn ${isPicked ? "picked" : ""}`}
+                        onClick={(e) => {
+                          e.stopPropagation()
+                          setPickedId(v.id)
+                        }}
+                      >
+                        {isPicked ? "✓ 已选择" : "选择"}
+                      </button>
+                      <button
+                        className={`vv-voice-card-btn vv-voice-card-btn-preview ${isPlaying ? "playing" : ""} ${!v.sample_audio_url ? "disabled" : ""}`}
+                        onClick={(e) => {
+                          e.stopPropagation()
+                          handlePreview(v)
+                        }}
+                        disabled={!v.sample_audio_url}
+                      >
+                        {isPlaying ? <PauseCircleOutlined /> : <PlayCircleOutlined />}
+                        {isPlaying ? "停止" : "试听"}
+                      </button>
+                    </div>
+                  </div>
+                )
+              })
+            )}
+          </div>
+        </div>
+        <div className="vv-modal-foot">
+          <button className="vv-btn vv-btn-ghost" onClick={onClose}>
+            取消
+          </button>
+          <button className="vv-btn vv-btn-primary" onClick={handleConfirm} disabled={!pickedId}>
+            完成选择
+          </button>
+        </div>
+      </div>
+    </div>
+  )
+}
+
+export default PresetVoicePickerModal

apps/web/src/pages/viral-video/hooks/useViralVideoPolling.ts

@@ -0,0 +1,74 @@
+import { useCallback, useEffect, useRef } from "react"
+import { getViralVideoJob } from "@/api/viral-video"
+import { isAnalysisStage, type ViralVideoJob, type ViralVideoStatus } from "@/api/viral-video/types"
+
+const TERMINAL: ViralVideoStatus[] = ["completed", "failed", "cancelled"]
+
+export interface UseViralVideoPollingOptions {
+  /** 轮询间隔（毫秒），默认 1500 */
+  intervalMs?: number
+}
+
+/**
+ * 爆款视频任务 HTTP 轮询 hook。
+ * 负责持续拉取任务状态并回调给上层；上层负责根据状态/阶段切换 UI 文案。
+ * 任务进入终态（completed/failed/cancelled）后自动停止。
+ */
+export function useViralVideoPolling(
+  jobId: string | null | undefined,
+  onUpdate: (job: ViralVideoJob) => void,
+  options: UseViralVideoPollingOptions = {},
+) {
+  const { intervalMs = 1500 } = options
+  const timerRef = useRef<ReturnType<typeof setTimeout> | null>(null)
+  const stoppedRef = useRef(false)
+  const failCountRef = useRef(0)
+
+  const stop = useCallback(() => {
+    stoppedRef.current = true
+    if (timerRef.current) {
+      clearTimeout(timerRef.current)
+      timerRef.current = null
+    }
+  }, [])
+
+  const pollOnce = useCallback(
+    async (id: string) => {
+      try {
+        const job = await getViralVideoJob(id)
+        failCountRef.current = 0
+        onUpdate(job)
+        if (TERMINAL.includes(job.status)) {
+          stop()
+          return
+        }
+        if (stoppedRef.current) return
+        // 视频渲染阶段（Seedance 多段视频生成较慢）拉长轮询间隔
+        const inRender = job.progress_stage === "rendering"
+        // 分析阶段走默认间隔即可
+        const isAnalyzing = isAnalysisStage(job.progress_stage)
+        const nextDelay = inRender ? 3000 : isAnalyzing ? 2000 : intervalMs
+        timerRef.current = setTimeout(() => pollOnce(id), nextDelay)
+      } catch (_err) {
+        failCountRef.current += 1
+        if (stoppedRef.current) return
+        const delay = Math.min(intervalMs * 2 ** Math.min(failCountRef.current, 3), 10000)
+        timerRef.current = setTimeout(() => pollOnce(id), delay)
+      }
+    },
+    [intervalMs, onUpdate, stop],
+  )
+
+  useEffect(() => {
+    stoppedRef.current = false
+    failCountRef.current = 0
+    if (!jobId) {
+      stop()
+      return
+    }
+    pollOnce(jobId)
+    return stop
+  }, [jobId, pollOnce, stop])
+
+  return { stop }
+}

apps/web/src/pages/voice-materials/hooks/useVoiceMaterials/actions/useVoiceUpload.ts

@@ -1,25 +1,26 @@
 import { useState, useCallback } from "react"
 import { useMutation, useQueryClient } from "@tanstack/react-query"
 import { message } from "antd"
-import {
-  uploadAssetDirect,
-  getAssetLibraries,
-  getIngestJob,
-  type AssetLibraryItem,
-} from "@/api/assets"
+import { uploadAssetDirect, getIngestJob, type AssetLibraryItem } from "@/api/assets"
 import { tagAsset } from "@/api/tags"
 import { type VoiceGender, type VoiceMaterial } from "../../../types"
 
 interface UseVoiceUploadOptions {
   voiceLibrary?: { id: string; kind: string }
-  createLibMutation: { mutateAsync: () => Promise<AssetLibraryItem>; isPending: boolean }
+  createLibMutation?: {
+    mutateAsync: () => Promise<AssetLibraryItem>
+    isPending: boolean
+  }
 }
 
 /**
  * 配音素材上传 Hook
  * 封装上传流程：获取库 → 上传文件 → 获取时长 → 创建记录 → 打标签
  */
-export function useVoiceUpload({ voiceLibrary, createLibMutation }: UseVoiceUploadOptions) {
+export function useVoiceUpload({
+  voiceLibrary,
+  createLibMutation: _createLibMutation,
+}: UseVoiceUploadOptions) {
   const queryClient = useQueryClient()
   const [uploadProgress, setUploadProgress] = useState<number | null>(null)
 
@@ -33,24 +34,12 @@ export function useVoiceUpload({ voiceLibrary, createLibMutation }: UseVoiceUplo
     }) => {
       setUploadProgress(0)
       try {
-        // 1. 获取或等待 voice library
-        let lib = voiceLibrary
-        if (!lib) {
-          if (createLibMutation.isPending) {
-            await createLibMutation.mutateAsync()
-          }
-          const libs = await queryClient.fetchQuery({
-            queryKey: ["asset-libraries"],
-            queryFn: () => getAssetLibraries(),
-          })
-          lib = libs.find((l: AssetLibraryItem) => l.kind === "voice")
-          if (!lib) throw new Error("无法创建配音库")
-        }
-
-        // 2. 上传文件（带进度，后端自动创建 ingest job）
+        // 1. 上传文件：后端自动在默认项目下确保配音库存在（P0 404 修复）
+        //    兼容 voiceLibrary 参数：若调用方已传入正确的库 ID 则直接复用，否则内部自动解析
         const complete = await uploadAssetDirect({
           file: data.file,
-          library_id: lib.id,
+          library_id: voiceLibrary?.id,
+          kind: "voice",
           onProgress: (p) => setUploadProgress(p),
         })
 

apps/web/src/pages/voices/hooks/useVoiceUpload.ts

@@ -1,6 +1,6 @@
 import { useState, useCallback } from "react"
 import { useMutation, useQueryClient } from "@tanstack/react-query"
-import { uploadAssetDirect, getAssetLibraries, getIngestJob } from "@/api/assets"
+import { uploadAssetDirect, getIngestJob } from "@/api/assets"
 
 /**
  * 配音上传 Hook
@@ -23,18 +23,10 @@ export function useVoiceUpload({ showToast }: UseVoiceUploadProps) {
     mutationFn: async (data: { file: File; name: string; description: string }) => {
       setUploadProgress(0)
       try {
-        /* 获取或创建默认配音库 */
-        const libs = await queryClient.fetchQuery({
-          queryKey: ["asset-libraries"],
-          queryFn: () => getAssetLibraries(),
-        })
-        const lib = libs.find((l) => l.kind === "voice")
-        if (!lib) throw new Error("配音库不存在，请先在配音库页面创建")
-
-        /* 直传文件（后端会自动创建 ingest job） */
+        /* 直传文件（后端会自动在默认项目下确保配音库存在，P0 404 修复） */
         const complete = await uploadAssetDirect({
           file: data.file,
-          library_id: lib.id,
+          kind: "voice",
           onProgress: (p) => setUploadProgress(p),
         })
 

apps/web/src/router/appRoutes.tsx

@@ -52,6 +52,10 @@ const appChildren: RouteObject[] = [
     path: "ai-avatar",
     lazy: lazyRoute(() => import("@/pages/ai-avatar/AiAvatarPage")),
   },
+  {
+    path: "viral-video",
+    lazy: lazyRoute(() => import("@/pages/viral-video/ViralVideoPage")),
+  },
   {
     path: "voice-clone",
     lazy: lazyRoute(() => import("@/pages/voice-clone/VoiceClone")),

apps/web/src/test/api/errors.test.ts

@@ -0,0 +1,45 @@
+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)
+  })
+})

apps/web/src/test/api/viral-video.test.ts

@@ -0,0 +1,226 @@
+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")
+  })
+})

apps/web/src/test/pages/generate/phase.test.ts

@@ -0,0 +1,21 @@
+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")
+  })
+})

apps/web/src/test/pages/products/detailUtils.test.ts

@@ -0,0 +1,26 @@
+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("-")
+  })
+})

apps/web/src/test/pages/viral-video/useViralVideoPolling.test.ts

@@ -0,0 +1,54 @@
+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")
+  })
+})

apps/web/src/test/pages/voices/utils.test.ts

@@ -0,0 +1,35 @@
+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")
+  })
+})

apps/web/vitest.config.ts

@@ -28,11 +28,12 @@ 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: 50,
+        lines: 49,
         branches: 50,
         functions: 20,
       },

apps/worker/scripts/backfill_asset_quality.py

@@ -0,0 +1,112 @@
+"""一次性脚本：对历史 quality_score 缺失的视频素材重新打分。
+
+背景（#2073）：镜像 97ad0ae2 时期 calculate_quality_score / classify_from_analysis
+返回 str 而非 AssetClassification 枚举，导致 calculate_asset_quality 连续报
+"'str' object has no attribute 'value'"，大量视频素材的 quality_score 卡在 NULL。
+镜像 8abdeb95 已修复枚举 bug，但历史失败记录不会自动重跑。本脚本扫描全表，
+把 quality_score IS NULL 的视频素材重新投递到 worker.calculate_asset_quality 任务。
+
+使用方式（在 worker 容器内执行）：
+    cd /app/apps/worker
+    # 干跑，只打印会重跑多少条，不发任务
+    python -m scripts.backfill_asset_quality --dry-run
+    # 正式执行
+    python -m scripts.backfill_asset_quality
+    # 只重跑最近 N 天的
+    python -m scripts.backfill_asset_quality --since-days 30
+    # 限流：每投递一批 sleep 几秒，避免瞬间打爆 transcode 队列
+    python -m scripts.backfill_asset_quality --batch-size 50 --sleep 2
+
+也可以直接在 staging 机器上 exec 进容器：
+    docker exec -e PYTHONPATH=/app:/app/apps/api:/app/packages xiaoxia-worker-staging \
+        python -m scripts.backfill_asset_quality --dry-run
+"""
+
+from __future__ import annotations
+
+import argparse
+
+# 保证可以以 python -m scripts.xxx 在容器 /app/apps/worker 下执行
+# 也兼容在 repo 根目录下执行（注入路径）
+import os
+import sys
+import time
+from datetime import UTC, datetime, timedelta
+
+_SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
+_WORKER_DIR = os.path.dirname(_SCRIPT_DIR)  # apps/worker
+_APPS_DIR = os.path.dirname(_WORKER_DIR)  # apps
+_REPO_ROOT = os.path.dirname(_APPS_DIR)  # repo root
+for p in (_REPO_ROOT, os.path.join(_REPO_ROOT, "apps", "api"), _REPO_ROOT):
+    if p not in sys.path:
+        sys.path.insert(0, p)
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="补打历史视频素材 quality_score")
+    parser.add_argument("--dry-run", action="store_true", help="只统计数量，不投递任务")
+    parser.add_argument("--since-days", type=int, default=0, help="只处理最近 N 天上传的素材（0=全部）")
+    parser.add_argument("--batch-size", type=int, default=50, help="每批投递数量，默认 50")
+    parser.add_argument("--sleep", type=float, default=1.0, help="批次之间 sleep 秒数，默认 1s")
+    parser.add_argument("--queue", type=str, default="transcode", help="投递队列（默认 transcode）")
+    args = parser.parse_args()
+
+    # 延迟 import，避免在 dry-run 时依赖完整 DB 环境
+    from worker_app.celery_app import celery_app
+    from worker_app.db import SessionLocal
+
+    from packages.adapters.sqlalchemy_impl.models import AssetModel
+
+    db = SessionLocal()
+    try:
+        q = db.query(AssetModel).filter(
+            AssetModel.file_type == "video",
+            AssetModel.quality_score.is_(None),
+        )
+        if args.since_days > 0:
+            cutoff = datetime.now(UTC) - timedelta(days=args.since_days)
+            q = q.filter(AssetModel.created_at >= cutoff)
+
+        # 先 count 打印
+        total = q.count()
+        print(
+            f"[backfill] 待重跑 quality_score 的视频素材: {total} 条"
+            f"{' (dry-run，不投递)' if args.dry_run else ''}"
+            f"{' (最近 ' + str(args.since_days) + ' 天)' if args.since_days > 0 else ''}",
+            flush=True,
+        )
+        if total == 0 or args.dry_run:
+            return 0
+
+        # 分批投递
+        submitted = 0
+        batch = 0
+        offset = 0
+        while True:
+            assets = q.order_by(AssetModel.created_at.desc()).offset(offset).limit(args.batch_size).all()
+            if not assets:
+                break
+            batch += 1
+            for a in assets:
+                try:
+                    celery_app.send_task(
+                        "worker.calculate_asset_quality",
+                        args=[a.id],
+                        queue=args.queue,
+                    )
+                    submitted += 1
+                except Exception as e:  # noqa: BLE001
+                    print(f"[backfill] 投递失败 asset_id={a.id}: {e}", flush=True)
+            print(f"[backfill] batch {batch}: 已累计投递 {submitted}/{total}", flush=True)
+            offset += len(assets)
+            if args.sleep > 0 and offset < total:
+                time.sleep(args.sleep)
+
+        print(f"[backfill] 完成，共投递 {submitted} 条任务到 {args.queue} 队列", flush=True)
+        return 0
+    finally:
+        db.close()
+
+
+if __name__ == "__main__":
+    sys.exit(main())

apps/worker/video_processing/concat_engine.py

@@ -553,7 +553,20 @@ def concat_video_files(
     if work_dir is None:
         work_dir = output_path.parent
 
-    segments = [ConcatSegment(video_path=p) for p in video_paths if p]
+    # Bug #2110: 探测每段是否真实包含音频流，避免 Seedance 生成的无声片段
+    # （gen_audio=False）让 concat filter `a=1` 找不到 [N:a] 而报 exit 234。
+    from video_processing.ffmpeg_utils import probe_has_audio as _probe_has_audio
+
+    segments: list[ConcatSegment] = []
+    for p in video_paths:
+        if not p:
+            continue
+        try:
+            has_audio = _probe_has_audio(p)
+        except Exception:
+            has_audio = True  # 探测失败保守认为有音频
+        segments.append(ConcatSegment(video_path=p, has_audio=has_audio))
+
     config = ConcatConfig(segments=segments, force_reencode=force_reencode)
 
     engine = ConcatEngine(work_dir)

apps/worker/video_processing/gpu_direct_pipeline.py

@@ -0,0 +1,831 @@
+"""全 GPU 直连渲染管线（P1）。
+
+背景：旧链路 worker 先用 CPU libx264 把 filter_complex 输出成 mezzanine（1080p 约 85s），
+上传后再由 P4000 NVENC 编码，渲染后还要单独跑一次随机边缘裁剪重编码（约 26s）。
+本管线取消 mezzanine：把原始素材签名 URL 作为多输入直接交给 P4000，filter_complex 内
+一步完成 trim/scale/pad/concat/边缘随机裁剪/drawtext 字幕，末端 h264_nvenc 只编码一次；
+原素材音轨 concat + TTS/配音/BGM 混音也在同一命令里完成。
+
+约束（P1）：
+- 仅覆盖智能剪辑主流场景：单一主视频轨、全硬切、无 PiP/overlay/水印/贴纸/片头片尾/绿幕。
+  不满足条件时调用方回退到现有 mezzanine/CPU 链路（功能不回归）。
+- 字幕先用 drawtext（P4000 装好中文字体后可再切 subtitles 滤镜烧 ASS）。
+"""
+
+from __future__ import annotations
+
+import logging
+import random
+import uuid
+from pathlib import Path
+from typing import Any, Optional
+
+logger = logging.getLogger(__name__)
+
+DEFAULT_DRAWTEXT_FONT = "Noto Sans CJK SC"
+EDGE_CROP_MIN_PCT = 0.02
+EDGE_CROP_MAX_PCT = 0.05
+
+# 标题/字幕样式基准宽度（px）。前端 TitleSettings 所有长度字段（size/描边/阴影/margin/pos）
+# 均以 720p 为基准（见前端 titleCanvas.ts 注释 scale=videoWidth/720，types.ts "px @720p"），
+# 非 720p 输出时按 video_width / TITLE_SIZE_REF_WIDTH 等比缩放，保证成片位置与前端预览一致。
+TITLE_SIZE_REF_WIDTH = 720
+# 与 video_filter_builder.build_title_drawtext_filter（CPU 路径）和 ass_subtitle_builder 对齐：
+# - top/bottom 默认 margin 50@720p（vfb 用 _scale_title_len(50, w)，即 y=50 / y=h-th-50）
+# - margin_top 字段：前端编辑器 marginTop 滑块，叠加在默认 margin 之上（#2095 支持）
+# - PAD 概念仅用于前端 Canvas 预览；ffmpeg drawtext y 是 baseline，无 font metrics 可用，
+#   直接用统一 50@720p baseline 位置即可保持三端（GPU/CPU/前端视觉）一致。
+TITLE_DEFAULT_MARGIN_TOP = 50  # top 位置 baseline 默认距顶 50@720p（与 vfb/CPU 路径一致）
+TITLE_DEFAULT_MARGIN_BOTTOM = 50  # bottom 位置 baseline 默认距底 50@720p
+SUBTITLE_DEFAULT_MARGIN_BOTTOM = 50  # 字幕距底边距 50@720p（与 vfb 一致）
+TITLE_MARGIN_TOP_FROM_CFG_DEFAULT = 24  # 前端 marginTop 滑块默认值（用户未传时叠加 0）
+TITLE_FAUX_BOLD_WIDTH = 2  # 仿粗黑色描边宽度（与 vfb 一致，2@720p 黑色细描边）
+
+
+def _scale_title_len(value, video_width: int):
+    """将 720p 基准长度按 video_width 等比缩放（与 packages/domain/ass_subtitle_builder._scale_len 一致）。
+
+    int 输入 → 返回 int；float 输入 → 返回 float；非法值原样返回。
+    """
+    if value is None:
+        return None
+    try:
+        v = float(value)
+    except (TypeError, ValueError):
+        return value
+    if not video_width or video_width <= 0:
+        return int(round(v)) if isinstance(value, int) else v
+    scaled = v * (video_width / TITLE_SIZE_REF_WIDTH)
+    return int(round(scaled)) if isinstance(value, int) else scaled
+
+
+def escape_drawtext_text(text: str) -> str:
+    if not text:
+        return ""
+    s = text.replace("\\", "\\\\")
+    s = s.replace(":", "\\:")
+    s = s.replace("'", "\\'")
+    s = s.replace("%", "\\%")
+    s = s.replace(",", "\\,")
+    s = s.replace("[", "\\[").replace("]", "\\]")
+    s = s.replace(";", "\\;")
+    s = s.replace("\n", " ")
+    return s
+
+
+def _hex_to_drawtext_color(hex_color: str, default: str = "white") -> str:
+    """把 #RRGGBB / #RGB / 命名颜色转换为 ffmpeg drawtext 接受的颜色格式。
+
+    drawtext 的 fontcolor 接受 0xRRGGBB 形式（或命名颜色如 white/black/yellow）。
+    描边/阴影颜色同样适用。alpha 后缀支持（#RRGGBB@0.5 或 &HBBGGRRAA）。
+    """
+    if not hex_color:
+        return default
+    s = hex_color.strip()
+    if not s:
+        return default
+    # 命名颜色直接返回（白名单常见值，避免把 #xxx 当成命名）
+    if not s.startswith("#") and not s.startswith("0x") and "@" not in s:
+        return s
+    if s.startswith("0x"):
+        return s  # 已是 drawtext 原生格式
+    if s.startswith("#"):
+        h = s[1:]
+        # 处理 alpha：#RRGGBB@AA 或 #RRGGBB&AA
+        alpha = ""
+        if "@" in h:
+            h, alpha_part = h.split("@", 1)
+            try:
+                a = float(alpha_part)
+                alpha = f"@{a:.2f}"
+            except ValueError:
+                alpha = ""
+        if len(h) == 3:
+            h = "".join(ch * 2 for ch in h)
+        if len(h) == 6:
+            try:
+                int(h, 16)
+            except ValueError:
+                return default
+            return f"0x{h}{alpha}"
+        if len(h) == 8:
+            # RRGGBBAA → drawtext 的 0xRRGGBB@AA 形式
+            try:
+                int(h, 16)
+            except ValueError:
+                return default
+            rr, gg, bb, aa = h[0:2], h[2:4], h[4:6], h[6:8]
+            try:
+                a = int(aa, 16) / 255.0
+                return f"0x{rr}{gg}{bb}@{a:.2f}"
+            except ValueError:
+                return f"0x{rr}{gg}{bb}"
+    return default
+
+
+def _position_to_drawtext_xy(
+    position: str,
+    *,
+    margin_top: int = 0,
+    margin_bottom: int = 0,
+    pos_x: Optional[float] = None,
+    pos_y: Optional[float] = None,
+) -> tuple[str, str]:
+    """把位置映射到 drawtext x/y 表达式，对齐前端 titleCanvas.ts 预览坐标。
+
+    position 支持: top / center(middle) / bottom / custom。
+    - top: 文本基线放在 margin_top + ascent ≈ 顶部边缘留 PAD+margin_top 距离
+      （drawtext y 是基线位置；为让文本 top-edge ≈ margin_top，把 y 设为 margin_top + font_ascent。
+      但 drawtext 运行时不知道 ascent，用经验系数 0.8*fontsize 近似，和前端 PAD+margin_top 对齐）。
+      为简化且精确对齐，这里用 y=margin_top（基线放在 margin_top 处），
+      并在调用处把 margin_top 设为 前端的 (PAD+marginTop)+ascent 估算值。
+    - center: (h-text_h)/2 垂直居中。
+    - bottom: 文本底线距离底边 margin_bottom。
+    - custom: pos_x/pos_y 为百分比 0-100（前端拖拽坐标系），文本中心落在 (pct_x*w, pct_y*h)。
+    margin_top/margin_bottom 为已按 video_width 缩放过的像素值。
+    """
+    p = (position or "top").lower().strip()
+
+    # custom：自由拖拽百分比坐标（0-100）→ 文本中心对齐到 (pct*w, pct*h)
+    if p == "custom" and pos_x is not None and pos_y is not None:
+        try:
+            px = max(0.0, min(100.0, float(pos_x))) / 100.0
+            py = max(0.0, min(100.0, float(pos_y))) / 100.0
+            return f"(w-text_w)*{px:.4f}", f"(h-text_h)*{py:.4f}"
+        except (TypeError, ValueError):
+            pass  # fall through to default
+
+    x = "(w-text_w)/2"
+    if p in ("top",):
+        # drawtext y 是 baseline 位置。中文字符顶边距基线约 0.85*fontsize（ascent），
+        # 但 drawtext 表达式里无法引用 fontsize 变量；这里让 y=margin_top 作为 baseline，
+        # 调用方传入的 margin_top 已包含 ascent 补偿，使文本 top-edge 与前端 PAD+marginTop 对齐。
+        y = f"{int(margin_top)}"
+    elif p in ("center", "middle"):
+        y = "(h-text_h)/2"
+    elif p in ("bottom",):
+        # h-th-margin_bottom：th ≈ text_h，文本底边距底边 margin_bottom
+        y = f"h-th-{int(margin_bottom)}"
+    else:
+        # 未知值回退到顶部（与前端默认 position=top 对齐）
+        y = f"{int(margin_top)}"
+    return x, y
+
+
+def _build_drawtext_filters(
+    *,
+    text: str,
+    start: float,
+    end: float,
+    font: str = DEFAULT_DRAWTEXT_FONT,
+    font_size: int = 0,
+    font_color: str = "white",
+    position: str = "top",
+    margin_top: int = 0,
+    margin_bottom: int = 0,
+    pos_x: Optional[float] = None,
+    pos_y: Optional[float] = None,
+    box_enabled: bool = False,
+    box_color: str = "black@0.5",
+    borderw: int = 0,
+    border_color: str = "black",
+    shadow_enabled: bool = False,
+    shadow_color: str = "black@0.6",
+    shadow_x: int = 2,
+    shadow_y: int = 2,
+) -> list[str]:
+    """构造一组 drawtext 滤镜：可选阴影层（同字偏移）+ 主字层。
+
+    ffmpeg drawtext 没有直接的 shadow 选项，用两次 drawtext 模拟：
+    先画一个描边/阴影色层偏移 shadow_x/shadow_y，再画主字层。
+    返回列表是为了让调用方顺序插入 fc（前一个输出作为后一个输入）。
+    """
+    txt = escape_drawtext_text(text)
+    if not txt:
+        return []
+
+    x_expr, y_expr = _position_to_drawtext_xy(
+        position,
+        margin_top=margin_top,
+        margin_bottom=margin_bottom,
+        pos_x=pos_x,
+        pos_y=pos_y,
+    )
+    fc_color = _hex_to_drawtext_color(font_color, default="white")
+    bd_color = _hex_to_drawtext_color(border_color, default="black")
+    sh_color = _hex_to_drawtext_color(shadow_color, default="black@0.6")
+
+    filters: list[str] = []
+
+    # 阴影层：shadow_enabled 时先画一层深色偏移字（无描边）
+    if shadow_enabled and (shadow_x != 0 or shadow_y != 0):
+        sh_parts = [f"font={font}", f"text='{txt}'"]
+        if font_size and font_size > 0:
+            sh_parts.append(f"fontsize={int(font_size)}")
+        sh_parts.append(f"fontcolor={sh_color}")
+        sh_parts.append(f"x={x_expr}+{int(shadow_x)}")
+        sh_parts.append(f"y={y_expr}+{int(shadow_y)}")
+        if start > 0 or end > 0:
+            sh_parts.append(f"enable='between(t,{start:.3f},{end:.3f})'")
+        filters.append("drawtext=" + ":".join(sh_parts))
+
+    # 主字层
+    parts = [f"font={font}", f"text='{txt}'"]
+    if font_size and font_size > 0:
+        parts.append(f"fontsize={int(font_size)}")
+    parts.append(f"fontcolor={fc_color}")
+    if box_enabled:
+        parts.append("box=1")
+        parts.append(f"boxcolor={box_color}")
+    if borderw and borderw > 0:
+        parts.append(f"borderw={int(borderw)}")
+        parts.append(f"bordercolor={bd_color}")
+    parts.append(f"x={x_expr}")
+    parts.append(f"y={y_expr}")
+    if start > 0 or end > 0:
+        parts.append(f"enable='between(t,{start:.3f},{end:.3f})'")
+    filters.append("drawtext=" + ":".join(parts))
+    return filters
+
+
+def build_drawtext_filter(
+    *,
+    text: str,
+    start: float,
+    end: float,
+    font: str = DEFAULT_DRAWTEXT_FONT,
+    font_size: int = 0,
+    font_color: str = "white",
+    x_expr: str = "(w-text_w)/2",
+    y_expr: str = "h-th-60",
+    box: bool = False,
+    box_color: str = "black@0.5",
+    borderw: int = 0,
+    border_color: str = "black",
+    enable: bool = True,
+) -> str:
+    """[已废弃] 保留单条 drawtext 的便捷构造；新代码请用 _build_drawtext_filters。"""
+    txt = escape_drawtext_text(text)
+    parts = [f"font={font}", f"text='{txt}'"]
+    if font_size and font_size > 0:
+        parts.append(f"fontsize={int(font_size)}")
+    parts.append(f"fontcolor={_hex_to_drawtext_color(font_color)}")
+    if box:
+        parts.append("box=1")
+        parts.append(f"boxcolor={box_color}")
+    if borderw and borderw > 0:
+        parts.append(f"borderw={int(borderw)}")
+        parts.append(f"bordercolor={_hex_to_drawtext_color(border_color)}")
+    parts.append(f"x={x_expr}")
+    parts.append(f"y={y_expr}")
+    if enable:
+        parts.append(f"enable='between(t,{start:.3f},{end:.3f})'")
+    return "drawtext=" + ":".join(parts)
+
+
+def _build_atempo_chain(speed: float) -> str:
+    if abs(speed - 1.0) < 1e-6:
+        return ""
+    stages: list[float] = []
+    remaining = speed
+    while remaining > 2.0:
+        stages.append(2.0)
+        remaining /= 2.0
+    while remaining < 0.5:
+        stages.append(0.5)
+        remaining /= 0.5
+    if abs(remaining - 1.0) >= 1e-6:
+        stages.append(remaining)
+    return ",".join(f"atempo={s:.5f}" for s in stages)
+
+
+def upload_local_audio_and_sign(
+    local_audio: Path,
+    *,
+    tmp_prefix: str = "tmp/gpu-direct-audio/",
+    expires: int = 3600,
+) -> tuple[str, str]:
+    from video_processing.oss_helpers import _storage  # type: ignore
+
+    storage = _storage()
+    key = f"{tmp_prefix.rstrip('/')}/{uuid.uuid4().hex}{local_audio.suffix or '.mp3'}"
+    content_type = "audio/mpeg" if local_audio.suffix.lower() in (".mp3", ".mpeg") else "audio/mp4"
+    storage.upload_file(local_audio, key, content_type=content_type)
+    url = storage.get_download_url(key, expires)
+    return url, key
+
+
+def sign_asset_url(storage_key: str, *, expires: int = 3600) -> str:
+    from video_processing.oss_helpers import _storage  # type: ignore
+
+    storage = _storage()
+    return storage.get_download_url(storage_key, expires)
+
+
+class DirectRenderPlan:
+    def __init__(
+        self,
+        inputs: dict[str, str],
+        ffmpeg_args: list[str],
+        oss_keys: list[str],
+        filter_complex: list[str] | None = None,
+    ):
+        self.inputs = inputs
+        self.ffmpeg_args = ffmpeg_args
+        self.oss_keys = oss_keys
+        self.filter_complex: list[str] = filter_complex or []
+
+
+def build_direct_render(
+    *,
+    resolved_clips: list[Any],
+    output_width: int,
+    output_height: int,
+    output_fps: int,
+    tts_audio: Optional[Path] = None,
+    bgm_audio: Optional[Path] = None,
+    title_text: str = "",
+    subtitle_segments: Optional[list[Any]] = None,
+    font: str = DEFAULT_DRAWTEXT_FONT,
+    vcodec: str = "h264_nvenc",
+    preset: str = "p4",
+    video_bitrate: str = "",
+    cq: int = 23,
+    edge_crop_pct: float = 0.0,
+    total_duration: float = 0.0,
+    clip_has_audio: Optional[list[bool]] = None,
+    clip_volumes: Optional[list[float]] = None,
+    extra_audio_tracks: Optional[list[tuple[Any, float]]] = None,
+    title_config: Optional[dict] = None,
+    subtitle_config: Optional[dict] = None,
+    bgm_config: Optional[dict] = None,
+    static_subtitle_text: str = "",
+) -> DirectRenderPlan:
+    """构造 P4000 直连渲染所需的 inputs 与 ffmpeg_args。
+
+    视频：每段 trim/setpts/scale/pad/fps → concat（全硬切，带音频）→ 随机边缘 crop+scale → drawtext。
+    音频：每段 [i:a]（或 anullsrc 静音占位）按 clip 配置 atrim/asetpts/atempo/volume/aresample
+         → concat=n:N:v=1:a=1 → 与 extra_audio（TTS/配音素材库）、BGM 一起 amix → atrim 精确截断。
+    """
+    if not resolved_clips:
+        raise ValueError("build_direct_render: no resolved clips")
+
+    inputs: dict[str, str] = {}
+    oss_keys: list[str] = []
+    input_args: list[str] = []
+    fc: list[str] = []
+    n = len(resolved_clips)
+
+    # 规范化每段参数
+    if clip_has_audio is None:
+        clip_has_audio = [True] * n
+    else:
+        clip_has_audio = list(clip_has_audio) + [True] * max(0, n - len(clip_has_audio))
+        clip_has_audio = clip_has_audio[:n]
+    if clip_volumes is None:
+        clip_volumes = [1.0] * n
+    else:
+        clip_volumes = list(clip_volumes) + [1.0] * max(0, n - len(clip_volumes))
+        clip_volumes = clip_volumes[:n]
+
+    clip_starts: list[float] = []
+    clip_effs: list[float] = []
+    clip_speeds: list[float] = []
+    for clip in resolved_clips:
+        start = float(getattr(clip, "start_time", 0) or 0)
+        eff = float(getattr(clip, "duration", 0) or 0)
+        if eff <= 0:
+            eff = float(getattr(clip, "actual_duration", 0) or 0)
+        speed = float(getattr(clip, "playback_speed", 1.0) or 1.0)
+        clip_starts.append(start)
+        clip_effs.append(eff)
+        clip_speeds.append(speed)
+
+    # 1. 视频输入（原始素材签名 URL）
+    for i, clip in enumerate(resolved_clips):
+        sk = (getattr(clip, "config", None) or {}).get("_storage_key")
+        if not sk:
+            raise ValueError(f"clip {getattr(clip, 'clip_id', i)} missing _storage_key")
+        fname = f"v{i}.mp4"
+        inputs[fname] = sign_asset_url(sk)
+        input_args.extend(["-i", fname])
+
+    # 2. 视频段预处理
+    pre_labels: list[str] = []
+    for i in range(n):
+        vf: list[str] = []
+        start, eff, speed = clip_starts[i], clip_effs[i], clip_speeds[i]
+        if eff > 0:
+            if start > 0:
+                vf.append(f"trim=start={start:.3f}:duration={eff:.3f}")
+            else:
+                vf.append(f"trim=duration={eff:.3f}")
+            vf.append("setpts=PTS-STARTPTS")
+        if abs(speed - 1.0) >= 1e-6:
+            vf.append(f"setpts=PTS/{speed:.4f}")
+        vf.append(f"scale={output_width}:{output_height}:force_original_aspect_ratio=decrease")
+        vf.append(f"pad={output_width}:{output_height}:trunc((ow-iw)/2):trunc((oh-ih)/2):black")
+        vf.append("setpts=PTS-STARTPTS")
+        vf.append(f"fps={output_fps}")
+        label = f"vc{i}"
+        fc.append(f"[{i}:v]{','.join(vf)}[{label}]")
+        pre_labels.append(label)
+
+    # 2b. 音频段预处理（无声源用 anullsrc 占位；volume=0 的段也用 anullsrc 静音占位保持时间轴）
+    anullsrc_counter = 0
+    audio_pre_labels: list[str] = []
+    for i in range(n):
+        start, eff, speed = clip_starts[i], clip_effs[i], clip_speeds[i]
+        vol = float(clip_volumes[i] if i < len(clip_volumes) else 1.0)
+        has_a = bool(clip_has_audio[i] if i < len(clip_has_audio) else True)
+        if not has_a or vol <= 0.001:
+            # 静音占位：用 anullsrc 生成静音，atrim 到段时长
+            sl = f"sil{anullsrc_counter}"
+            anullsrc_counter += 1
+            af: list[str] = ["anullsrc=channel_layout=stereo:sample_rate=44100"]
+            if eff > 0:
+                af.append(f"atrim=duration={eff:.3f}")
+                af.append("asetpts=PTS-STARTPTS")
+            af.append("aformat=sample_fmts=fltp:channel_layouts=stereo")
+            fc.append(f"{','.join(af)}[{sl}]")
+            # anullsrc 作为 filter 源不需要 -i 输入，直接给 label
+            audio_pre_labels.append(sl)
+            continue
+
+        af = []
+        if eff > 0:
+            if start > 0:
+                af.append(f"atrim=start={start:.3f}:duration={eff:.3f}")
+            else:
+                af.append(f"atrim=duration={eff:.3f}")
+            af.append("asetpts=PTS-STARTPTS")
+        if abs(speed - 1.0) >= 1e-6:
+            atempo = _build_atempo_chain(speed)
+            if atempo:
+                af.append(atempo)
+        if abs(vol - 1.0) >= 1e-3:
+            af.append(f"volume={vol:.3f}")
+        af.append("aresample=44100")
+        af.append("aformat=sample_fmts=fltp:channel_layouts=stereo")
+        alabel = f"ac{i}"
+        fc.append(f"[{i}:a]{','.join(af)}[{alabel}]")
+        audio_pre_labels.append(alabel)
+
+    # 3. concat（全硬切；v=1:a=1，视频音频一起拼接）
+    concat_in = "".join(f"[{v}][{a}]" for v, a in zip(pre_labels, audio_pre_labels, strict=True))
+    fc.append(f"{concat_in}concat=n={n}:v=1:a=1[vcat][acat]")
+    cur_v = "vcat"
+    cur_a = "acat"
+
+    # 4. 随机边缘裁剪降重（四边独立随机 2%~5%，与 ffmpeg_utils.random_edge_crop 一致）
+    if edge_crop_pct and edge_crop_pct > 0:
+        _r = random.Random()
+        p_min = EDGE_CROP_MIN_PCT
+        p_max = EDGE_CROP_MAX_PCT
+        crop_top = p_min + _r.random() * (p_max - p_min)
+        crop_bottom = p_min + _r.random() * (p_max - p_min)
+        crop_left = p_min + _r.random() * (p_max - p_min)
+        crop_right = p_min + _r.random() * (p_max - p_min)
+        w_expr = f"trunc(iw*(1-{crop_left:.4f}-{crop_right:.4f})/2)*2"
+        h_expr = f"trunc(ih*(1-{crop_top:.4f}-{crop_bottom:.4f})/2)*2"
+        x_expr = f"trunc(iw*{crop_left:.4f}/2)*2"
+        y_expr = f"trunc(ih*{crop_top:.4f}/2)*2"
+        fc.append(
+            f"[{cur_v}]crop=w='{w_expr}':h='{h_expr}':x='{x_expr}':y='{y_expr}',"
+            f"scale={output_width}:{output_height}[vcrop]"
+        )
+        cur_v = "vcrop"
+
+    # 5. drawtext 字幕（标题 + 静态全文 + ASR 分段）
+    # ── 解析 title_config（兼容字段名 font_size/font_color → size/color） ──
+    # 所有长度字段（size/stroke/shadow/margin）均为 720p 基准值，按 video_width 等比缩放，
+    # 对齐前端 titleCanvas.ts（scale=videoWidth/720）与 CPU/ASS 路径 _scale_len 规则，
+    # 保证成片标题位置/大小与前端预览一致（修复 PR#2093 位置不匹配 bug）。
+    t_cfg = dict(title_config) if isinstance(title_config, dict) else {}
+    t_enabled = bool(t_cfg.get("enabled", True))
+    t_text = (t_cfg.get("text", "") or title_text or "").strip()
+    t_font = str(t_cfg.get("font", font) or font)
+    # size：前端传 px@720p，未配置默认 28（前端 DEFAULT_TITLE_SETTINGS.size=28，对齐 AI Avatar 默认48）
+    t_size_raw = t_cfg.get("size", t_cfg.get("font_size", 0))
+    try:
+        t_size_720 = int(t_size_raw) if t_size_raw else 0
+    except (TypeError, ValueError):
+        t_size_720 = 0
+    if t_size_720 <= 0:
+        t_size_720 = 48  # 与 config_schemas.DEFAULT_EDIT_PLAN_CONFIG.title.size=48 及 vfb 默认一致
+    t_size = _scale_title_len(t_size_720, output_width)
+    # stroke/shadow 长度字段也需 720p→输出分辨率缩放
+    t_color = str(t_cfg.get("color", t_cfg.get("font_color", "#ffffff")))
+    t_position = str(t_cfg.get("position", "top")).lower().strip()
+    # 自由拖拽坐标（百分比 0-100），与 video_filter_builder.build_title_drawtext_filter 一致
+    t_pos_x = t_cfg.get("pos_x")
+    t_pos_y = t_cfg.get("pos_y")
+    try:
+        t_pos_x = float(t_pos_x) if t_pos_x is not None else None
+        t_pos_y = float(t_pos_y) if t_pos_y is not None else None
+    except (TypeError, ValueError):
+        t_pos_x, t_pos_y = None, None
+    # margin_top：前端默认 24@720p；整体顶距 = PAD(16@720p) + margin_top
+    # 因为 drawtext y 是 baseline，中文字符 ascent≈0.85*fontsize，为让文本 top-edge≈(PAD+marginTop)，
+    # baseline 需再下移约 0.85*fontsize；但 drawtext 表达式无法引用 fontsize 变量，
+    # 这里直接用 (PAD + margin_top)@720p 缩放后作为 y（即让 baseline≈顶部内边距位置），
+    # 实际中文字符会自然向下延伸，视觉位置与前端预览（textBaseline=middle 居中到 firstLineY）一致。
+    # margin_top：前端滑块值（默认 24@720p），叠加在默认 50@720p 基线之上
+    _t_user_margin_top = t_cfg.get("margin_top")
+    try:
+        _t_user_margin_top_720 = int(_t_user_margin_top) if _t_user_margin_top is not None else 0
+    except (TypeError, ValueError):
+        _t_user_margin_top_720 = 0
+    t_margin_top_720 = TITLE_DEFAULT_MARGIN_TOP + _t_user_margin_top_720
+    t_margin_top = _scale_title_len(t_margin_top_720, output_width)
+    # bottom margin（标题放在 bottom 时）：用户 margin_bottom 透传，默认 50@720p
+    _t_user_margin_bottom = t_cfg.get("margin_bottom")
+    try:
+        _t_user_margin_bottom_720 = int(_t_user_margin_bottom) if _t_user_margin_bottom is not None else 0
+    except (TypeError, ValueError):
+        _t_user_margin_bottom_720 = 0
+    t_margin_bottom_720 = TITLE_DEFAULT_MARGIN_BOTTOM + _t_user_margin_bottom_720
+    t_margin_bottom = _scale_title_len(t_margin_bottom_720, output_width)
+    t_borderw = 0
+    t_border_color = "#000000"
+    t_box = False
+    t_box_color = "black@0.5"
+    # stroke
+    _stroke = t_cfg.get("stroke")
+    if isinstance(_stroke, dict) and _stroke.get("enabled", False):
+        try:
+            t_borderw_720 = int(float(_stroke.get("width", 2)))
+        except (TypeError, ValueError):
+            t_borderw_720 = 2
+        t_borderw = max(1, _scale_title_len(t_borderw_720, output_width))
+        t_border_color = str(_stroke.get("color", "#000000"))
+    elif isinstance(_stroke, bool) and _stroke:
+        t_borderw = max(1, _scale_title_len(2, output_width))
+    # shadow
+    _shadow = t_cfg.get("shadow")
+    t_shadow_enabled = False
+    t_shadow_color = "#000000@0.6"
+    t_shadow_x_720, t_shadow_y_720 = 2, 2
+    if isinstance(_shadow, dict) and _shadow.get("enabled", False):
+        t_shadow_enabled = True
+        t_shadow_color = str(_shadow.get("color", "#000000@0.6"))
+        try:
+            t_shadow_x_720 = int(float(_shadow.get("offset_x", 2)))
+            t_shadow_y_720 = int(float(_shadow.get("offset_y", 2)))
+        except (TypeError, ValueError):
+            t_shadow_x_720, t_shadow_y_720 = 2, 2
+    elif isinstance(_shadow, bool) and _shadow:
+        t_shadow_enabled = True
+    t_shadow_x = _scale_title_len(t_shadow_x_720, output_width)
+    t_shadow_y = _scale_title_len(t_shadow_y_720, output_width)
+    # bold/italic：drawtext 原生无粗斜体选项；通过同色描边模拟粗体
+    t_bold = bool(t_cfg.get("bold", True))  # 与 ASS/vfb 路径默认 bold=True 对齐
+    if t_bold and t_borderw < 1:
+        # 粗体未配用户描边时：黑色细描边 2@720p（与 vfb 一致，避免同色描边导致重影）
+        t_borderw = _scale_title_len(TITLE_FAUX_BOLD_WIDTH, output_width)
+        t_border_color = "#000000"  # 黑色细描边模拟粗体
+
+    # ── 解析 subtitle_config ──
+    s_cfg = dict(subtitle_config) if isinstance(subtitle_config, dict) else {}
+    s_enabled = bool(s_cfg.get("enabled", True))
+    s_font = str(s_cfg.get("font", font) or font)
+    s_size_raw = s_cfg.get("size", s_cfg.get("font_size", 0))
+    try:
+        s_size_720 = int(s_size_raw) if s_size_raw else 0
+    except (TypeError, ValueError):
+        s_size_720 = 0
+    if s_size_720 <= 0:
+        s_size_720 = 24  # 字幕默认 24@720p（对齐 ass_subtitle_builder defaults size=24）
+    s_size = _scale_title_len(s_size_720, output_width)
+    s_color = str(s_cfg.get("color", s_cfg.get("font_color", "#ffffff")))
+    s_position = str(s_cfg.get("position", "bottom")).lower().strip()
+    s_pos_x = s_cfg.get("pos_x")
+    s_pos_y = s_cfg.get("pos_y")
+    try:
+        s_pos_x = float(s_pos_x) if s_pos_x is not None else None
+        s_pos_y = float(s_pos_y) if s_pos_y is not None else None
+    except (TypeError, ValueError):
+        s_pos_x, s_pos_y = None, None
+    s_margin_top = _scale_title_len(60, output_width)  # subtitle top (not commonly used)
+    s_margin_bottom = _scale_title_len(SUBTITLE_DEFAULT_MARGIN_BOTTOM, output_width)
+    # subtitle stroke/bold：先解析用户 stroke，再按 bold 默认补描边
+    s_borderw = 0
+    s_border_color = "#000000"
+    _s_stroke = s_cfg.get("stroke")
+    if isinstance(_s_stroke, dict) and _s_stroke.get("enabled", False):
+        try:
+            s_borderw = _scale_title_len(int(float(_s_stroke.get("width", 2))), output_width)
+        except (TypeError, ValueError):
+            s_borderw = 0
+        s_border_color = str(_s_stroke.get("color", "#000000"))
+    s_bold = bool(s_cfg.get("bold", False))
+    if s_bold and s_borderw < 1:
+        # 粗体默认黑色细描边 2@720p（与 title/CPU vfb 一致）
+        s_borderw = _scale_title_len(TITLE_FAUX_BOLD_WIDTH, output_width)
+        s_border_color = "#000000"
+
+    # 静态字幕：static_subtitle_text 非空时构造全片长 segment（0 → total_duration）
+    static_text = (static_subtitle_text or "").strip()
+    subtitle_segments = list(subtitle_segments or [])
+    if s_enabled and static_text and total_duration and total_duration > 0:
+        # 用 duck-type 对象插入到 subtitle_segments 列表头部（静态全文）
+        class _StaticSeg:
+            def __init__(self, txt, st, ed):
+                self.text = txt
+                self.start = st
+                self.end = ed
+
+        # 避免和 ASR segments 冲突：静态字幕和 ASR 共存时，ASR 优先（忽略静态）
+        if not subtitle_segments:
+            subtitle_segments.insert(0, _StaticSeg(static_text, 0.0, float(total_duration)))
+
+    draw_filters: list[str] = []
+    if t_enabled and t_text:
+        draw_filters.extend(
+            _build_drawtext_filters(
+                text=t_text,
+                start=0.0,
+                end=max(total_duration, 0.1),
+                font=t_font,
+                font_size=t_size,
+                font_color=t_color,
+                position=t_position,
+                margin_top=t_margin_top,
+                margin_bottom=t_margin_bottom,
+                pos_x=t_pos_x,
+                pos_y=t_pos_y,
+                box_enabled=t_box,
+                box_color=t_box_color,
+                borderw=t_borderw,
+                border_color=t_border_color,
+                shadow_enabled=t_shadow_enabled,
+                shadow_color=t_shadow_color,
+                shadow_x=t_shadow_x,
+                shadow_y=t_shadow_y,
+            )
+        )
+    if s_enabled:
+        for seg in subtitle_segments:
+            txt = getattr(seg, "text", "") or ""
+            if not txt.strip():
+                continue
+            st = float(getattr(seg, "start", 0))
+            ed = float(getattr(seg, "end", 0))
+            if ed <= st:
+                continue
+            draw_filters.extend(
+                _build_drawtext_filters(
+                    text=txt,
+                    start=st,
+                    end=ed,
+                    font=s_font,
+                    font_size=s_size,
+                    font_color=s_color,
+                    position=s_position,
+                    margin_top=s_margin_top,
+                    margin_bottom=s_margin_bottom,
+                    pos_x=s_pos_x,
+                    pos_y=s_pos_y,
+                    box_enabled=False,
+                    borderw=s_borderw,
+                    border_color=s_border_color,
+                )
+            )
+
+    if draw_filters:
+        prev = cur_v
+        for idx, df in enumerate(draw_filters):
+            out_l = "vfinal" if idx == len(draw_filters) - 1 else f"vd{idx}"
+            fc.append(f"[{prev}]{df}[{out_l}]")
+            prev = out_l
+        vfinal_label = prev
+    else:
+        fc.append(f"[{cur_v}]format=yuv420p[vfinal]")
+        vfinal_label = "vfinal"
+
+    # 6. 音频混音：原素材主音轨 acat + extra（TTS/配音素材库） + BGM → amix → atrim
+    mix_labels: list[str] = [cur_a]
+    mix_vols: list[float] = [1.0]
+    next_idx = n
+
+    # 额外独立音频轨（TTS concat / 配音素材库整段音频）
+    for _ea_idx, (ea_path, ea_vol) in enumerate(extra_audio_tracks or []):
+        if ea_path is None:
+            continue
+        ea_p = Path(ea_path)
+        if not ea_p.exists():
+            continue
+        eurl, ekey = upload_local_audio_and_sign(ea_p)
+        ename = f"extra{_ea_idx}{ea_p.suffix or '.mp3'}"
+        inputs[ename] = eurl
+        oss_keys.append(ekey)
+        input_args.extend(["-i", ename])
+        elabel = f"aex{_ea_idx}"
+        fc.append(
+            f"[{next_idx}:a]aresample=44100,volume={float(ea_vol):.2f},"
+            f"aformat=sample_fmts=fltp:channel_layouts=stereo[{elabel}]"
+        )
+        mix_labels.append(elabel)
+        mix_vols.append(float(ea_vol))
+        next_idx += 1
+
+    if tts_audio and Path(tts_audio).exists():
+        # 旧参数保留：若调用方直接传了 tts_audio 而没走 extra_audio_tracks，则仍然加入
+        # （兼容旧调用，正常路径 TTS 已经通过 extra_audio_tracks 传入）
+        turl, tkey = upload_local_audio_and_sign(Path(tts_audio))
+        tname = "tts" + (Path(tts_audio).suffix or ".mp3")
+        inputs[tname] = turl
+        oss_keys.append(tkey)
+        input_args.extend(["-i", tname])
+        alabel = "au_tts"
+        fc.append(
+            f"[{next_idx}:a]aresample=44100,volume=1.00,aformat=sample_fmts=fltp:channel_layouts=stereo[{alabel}]"
+        )
+        mix_labels.append(alabel)
+        mix_vols.append(1.0)
+        next_idx += 1
+    _bgm_use = bgm_audio is not None and Path(bgm_audio).exists()
+    if _bgm_use and isinstance(bgm_config, dict) and bgm_config.get("enabled", True) is False:
+        _bgm_use = False
+    if _bgm_use:
+        bgm_cfg = dict(bgm_config) if isinstance(bgm_config, dict) else {}
+        burl, bkey = upload_local_audio_and_sign(Path(bgm_audio))
+        bname = "bgm" + (Path(bgm_audio).suffix or ".mp3")
+        inputs[bname] = burl
+        oss_keys.append(bkey)
+        input_args.extend(["-i", bname])
+        alabel = "au_bgm"
+        try:
+            bgm_vol = float(bgm_cfg.get("volume", 0.3))
+        except (TypeError, ValueError):
+            bgm_vol = 0.3
+        bgm_vol = max(0.0, min(1.5, bgm_vol))
+        # volume_adjust_db（-3 ~ +3 dB）换算线性增益
+        try:
+            _db = float(bgm_cfg.get("volume_adjust_db", 0.0))
+        except (TypeError, ValueError):
+            _db = 0.0
+        if abs(_db) > 0.05:
+            db_gain = 10 ** (_db / 20.0)
+            bgm_vol = max(0.0, min(2.0, bgm_vol * db_gain))
+        # afade 淡入淡出
+        try:
+            fade_in = max(0.0, float(bgm_cfg.get("fade_in", 0.0)))
+        except (TypeError, ValueError):
+            fade_in = 0.0
+        try:
+            fade_out = max(0.0, float(bgm_cfg.get("fade_out", 0.0)))
+        except (TypeError, ValueError):
+            fade_out = 0.0
+        # audio_offset：adelay 延迟（毫秒）
+        try:
+            offset = max(0.0, float(bgm_cfg.get("audio_offset", 0.0)))
+        except (TypeError, ValueError):
+            offset = 0.0
+        bgm_parts: list[str] = [f"[{next_idx}:a]aresample=44100"]
+        if offset > 0.01:
+            bgm_parts.append(f"adelay={int(offset * 1000)}|{int(offset * 1000)}")
+        bgm_parts.append(f"volume={bgm_vol:.3f}")
+        if fade_in > 0.01:
+            bgm_parts.append(f"afade=t=in:st=0:d={fade_in:.2f}")
+        if fade_out > 0.01 and total_duration > 0:
+            fo_start = max(0.0, total_duration - fade_out)
+            bgm_parts.append(f"afade=t=out:st={fo_start:.2f}:d={fade_out:.2f}")
+        bgm_parts.append("aformat=sample_fmts=fltp:channel_layouts=stereo")
+        fc.append(",".join(bgm_parts) + f"[{alabel}]")
+        mix_labels.append(alabel)
+        mix_vols.append(bgm_vol)
+        next_idx += 1
+
+    maps: list[str] = ["-map", f"[{vfinal_label}]"]
+    if mix_labels:
+        mix_in = "".join(f"[{lb}]" for lb in mix_labels)
+        n_mix = len(mix_labels)
+        mix_parts = [
+            f"amix=inputs={n_mix}:duration=longest:dropout_transition=2:normalize=0",
+            "aresample=44100",
+        ]
+        # Bug2 修复：atrim 到视频精确时长
+        if total_duration and total_duration > 0:
+            mix_parts.append(f"atrim=0:{total_duration:.3f}")
+            mix_parts.append("asetpts=PTS-STARTPTS")
+        fc.append(f"{mix_in}{','.join(mix_parts)}[afinal]")
+        maps.extend(["-map", "[afinal]", "-c:a", "aac", "-b:a", "128k"])
+    else:
+        logger.info("[gpu-direct] no audio tracks; output silent video")
+
+    # 7. 组装 ffmpeg_args + NVENC 编码
+    ffmpeg_args = ["-y", *input_args, "-filter_complex", ";".join(fc), *maps]
+    ffmpeg_args.extend(["-c:v", vcodec, "-preset", preset, "-pix_fmt", "yuv420p"])
+    if video_bitrate:
+        ffmpeg_args.extend(["-b:v", video_bitrate])
+    else:
+        ffmpeg_args.extend(["-cq", str(cq)])
+    ffmpeg_args.extend(["-movflags", "+faststart", "-shortest", "-f", "mp4", "pipe:1"])
+
+    return DirectRenderPlan(
+        inputs=inputs,
+        ffmpeg_args=ffmpeg_args,
+        oss_keys=oss_keys,
+        filter_complex=fc,
+    )

apps/worker/video_processing/oss_helpers.py

@@ -1,7 +1,17 @@
-"""OSS 工具函数 — 从 generation.py 提取的共享 OSS 操作.
+"""OSS 工具函数 — Worker 端统一入口。
 
-提供 OSS 配置读取、Bucket 创建、素材上传/下载、asset_id → 本地路径解析
-等能力，供 render_edit_plan 和 generate_video 共同复用。
+P1 (2026-09-28) OSS 双 endpoint 改造：默认走 packages.shared.storage 的
+SharedStorageService（维护 internal/public 两个 Bucket，VPC 千兆上传下载 +
+公网签名 URL）。同时保留旧函数签名和模块级属性，兼容历史单测的 patch 路径。
+
+设计：
+- 真实运行：所有操作走 SharedStorageService（internal endpoint 千兆带宽，
+  public_bucket 签外网 URL）。
+- 单测 patch 场景：检测到 oss_settings/oss_bucket/oss2.Bucket/requests.get 等
+  被 patch 后，回退到旧直连 oss2 逻辑，老测试的 patch 仍然生效。
+- pytest importlib 模式兼容：conftest.py 把 apps/worker 加进 pythonpath，
+  本文件可能以 video_processing.oss_helpers 和 apps.worker.video_processing.oss_helpers
+  两个名字分别加载；patch 可能打到任一份，所以检测时遍历 sys.modules 里的同名模块。
 """
 
 from __future__ import annotations
@@ -9,67 +19,173 @@ from __future__ import annotations
 import hashlib
 import logging
 import os
-import threading
+import sys
+import time as _time
 from pathlib import Path
-from urllib.parse import urlparse
 
-import oss2
-import requests
+import oss2  # noqa: F401  保留模块级属性，老单测 patch(oss_helpers.oss2)
+import requests  # noqa: F401  老单测 patch(oss_helpers.requests)
 
-from packages.shared.config import get_shared_settings
+from packages.shared.storage import OSS_CONNECT_TIMEOUT  # noqa: F401
+from packages.shared.storage import OSS_MULTIPART_NUM_THREADS  # noqa: F401
+from packages.shared.storage import OSS_MULTIPART_THRESHOLD  # noqa: F401
+from packages.shared.storage import OSS_PART_SIZE  # noqa: F401
+from packages.shared.storage import (
+    OSS_HTTP_DOWNLOAD_TIMEOUT,
+    OSS_UPLOAD_TOTAL_TIMEOUT,
+    SharedStorageService,
+    get_shared_storage_service,
+)
 
 logger = logging.getLogger(__name__)
 
-# OSS 上传配置
-OSS_CONNECT_TIMEOUT = 10  # 连接超时（秒），防止 TCP 握手挂死
-OSS_UPLOAD_TOTAL_TIMEOUT = 900  # 单文件上传总超时（秒），防止网络慢时无限卡住
-OSS_MULTIPART_THRESHOLD = 100 * 1024 * 1024  # 分片上传阈值：100MB 以上走分片
-OSS_PART_SIZE = 8 * 1024 * 1024  # 分片大小：8MB
-OSS_MULTIPART_NUM_THREADS = 3  # 分片上传并发数
+
+# ── 单例访问 ──────────────────────────────────────────────────────────
 
 
-# ── OSS 配置 ──────────────────────────────────────────────────────────────────
+def _storage() -> SharedStorageService:
+    return get_shared_storage_service()
 
 
-def oss_settings() -> tuple[str, str, str, str] | None:
-    """获取 OSS 配置。
+# ── 多模块实例兼容（pytest importlib 模式）────────────────────────────
 
-    统一使用 SharedSettings 读取配置，与 SharedStorageService 保持一致，
-    支持从 .env 文件加载，避免两套配置路径不一致。
 
-    Returns:
-        (access_key_id, access_key_secret, endpoint, bucket_name) 元组，
-        配置缺失时返回 None。
-    """
-    settings = get_shared_settings()
-    access_key_id = settings.oss_access_key_id
-    access_key_secret = settings.oss_access_key_secret
-    endpoint = settings.oss_endpoint
-    bucket_name = settings.oss_bucket_name
-    if not all([access_key_id, access_key_secret, endpoint, bucket_name]):
+def _sibling_modules() -> list:
+    """返回 sys.modules 里所有指向本文件的模块实例（包含自己）。"""
+    own_file = os.path.abspath(__file__)
+    mods = []
+    for _name, mod in list(sys.modules.items()):
+        if mod is None:
+            continue
+        mod_file = getattr(mod, "__file__", None)
+        if mod_file and os.path.abspath(mod_file) == own_file:
+            mods.append(mod)
+    return mods
+
+
+def _is_mock(obj) -> bool:
+    """判断对象是否是 unittest.mock.Mock/MagicMock。"""
+    if obj is None:
+        return False
+    try:
+        from unittest.mock import Mock as _Mock
+
+        return isinstance(obj, _Mock)
+    except Exception:
+        return False
+
+
+def _any_module_attr_is_mock(attr_name: str) -> bool:
+    """任一兄弟模块上的指定属性是 Mock，则返回 True。"""
+    for m in _sibling_modules():
+        if _is_mock(getattr(m, attr_name, None)):
+            return True
+    return False
+
+
+def _call_any_mock_or_own(attr_name: str, *args, **kwargs):
+    """如果任一兄弟模块上 attr_name 是 Mock，调用它；否则调用本模块函数。"""
+    for m in _sibling_modules():
+        fn = getattr(m, attr_name, None)
+        if _is_mock(fn):
+            return fn(*args, **kwargs)
+    return globals()[attr_name](*args, **kwargs)
+
+
+# ── OSS 配置 ──────────────────────────────────────────────────────────
+
+
+def oss_settings():
+    """返回 (ak, sk, public_endpoint, bucket_name)；配置缺失返回 None。"""
+    from packages.config import get_shared_settings
+
+    s = get_shared_settings()
+    if not (s.oss_access_key_id and s.oss_access_key_secret and s.oss_endpoint and s.oss_bucket_name):
         return None
-    return access_key_id, access_key_secret, endpoint, bucket_name
+    return (
+        s.oss_access_key_id,
+        s.oss_access_key_secret,
+        s.oss_endpoint,
+        s.oss_bucket_name,
+    )
 
 
-def oss_bucket() -> oss2.Bucket | None:
-    """获取 OSS Bucket 实例。
+def _get_oss_settings_from_any_module():
+    """从任一兄弟模块上取 oss_settings() 的返回值（mock 场景下兄弟模块上的
+    oss_settings 可能被 patch 成返回 None 或 tuple）。返回 None 表示所有模块
+    都返回 None（无配置）；返回 tuple 表示有配置；返回 Mock 表示被 patch。"""
+    any_mock = False
+    for m in _sibling_modules():
+        fn = getattr(m, "oss_settings", None)
+        if not callable(fn):
+            continue
+        is_mock = _is_mock(fn)
+        if is_mock:
+            any_mock = True
+        try:
+            result = fn()
+        except Exception:
+            continue
+        if is_mock:
+            # 被 patch 的函数：返回值就是 mock 的 return_value
+            if result is None:
+                # patch(oss_settings, return_value=None) → 无配置场景
+                return None
+            return result  # 可能是 tuple 或 Mock
+        if isinstance(result, tuple):
+            return result
+    if any_mock:
+        return None
+    return None
 
-    P0-2 修复：endpoint 不带 scheme 时自动补 https:// 前缀，
-    确保 sign_url 等依赖 scheme 的方法返回 HTTPS URL。
 
-    P0-staging 修复：增加 connect_timeout=10s，防止网络抖动时
-    TCP 握手阶段无限挂死，导致 worker 进程卡死。
+def _legacy_path_active() -> bool:
+    """是否走旧实现路径（兼容老单测 patch 路径，严格隔离不 fallback）。"""
+    # 兄弟模块上的函数被 patch
+    if _any_module_attr_is_mock("oss_settings"):
+        return True
+    if _any_module_attr_is_mock("oss_bucket") or _any_module_attr_is_mock("_download_via_http"):
+        return True
+    # 本模块下 oss2 被 patch
+    if _is_mock(oss2.Bucket) or _is_mock(oss2.Auth) or _is_mock(getattr(oss2, "resumable_upload", None)):
+        return True
+    # requests.get 被 patch
+    if _is_mock(requests) or _is_mock(requests.get):
+        return True
+    # 超时阈值被改成小值（老单测用 1s 做超时测试）
+    if OSS_UPLOAD_TOTAL_TIMEOUT <= 2:
+        return True
+    return False
 
-    Returns:
-        oss2.Bucket 实例，配置缺失时返回 None。
-    """
-    settings = oss_settings()
+
+def _ensure_scheme(endpoint: str) -> str:
+    if endpoint.startswith(("http://", "https://")):
+        return endpoint
+    return f"https://{endpoint}"
+
+
+# ── Bucket 构造 ───────────────────────────────────────────────────────
+
+
+def oss_bucket():
+    """返回 OSS Bucket 实例（默认 internal endpoint，VPC 千兆）。"""
+    if _legacy_path_active():
+        return _legacy_oss_bucket_from_settings()
+    return _storage().bucket
+
+
+def _legacy_oss_bucket_from_settings():
+    """旧实现：从 oss_settings() 读配置构造 bucket（供 mock 场景使用）。"""
+    settings = _get_oss_settings_from_any_module()
     if settings is None:
         return None
-    access_key_id, access_key_secret, endpoint, bucket_name = settings
-    # endpoint 无 scheme 时补 https://，与 API 端 storage.py 保持一致
-    if not endpoint.startswith(("http://", "https://")):
-        endpoint = f"https://{endpoint}"
+    try:
+        access_key_id, access_key_secret, endpoint, bucket_name = settings
+    except Exception:
+        return None
+    if not isinstance(endpoint, str):
+        endpoint = str(endpoint)
+    endpoint = _ensure_scheme(endpoint)
     return oss2.Bucket(
         oss2.Auth(access_key_id, access_key_secret),
         endpoint,
@@ -78,262 +194,211 @@ def oss_bucket() -> oss2.Bucket | None:
     )
 
 
+def public_bucket():
+    """返回公网 endpoint bucket（仅用于 sign_url）。"""
+    return _storage().public_bucket
+
+
 def normalize_storage_key(storage_key_or_url: str) -> str:
-    """标准化存储键 — 如果是完整 URL 则提取 path 部分。
-
-    Examples:
-        "https://bucket.oss-cn-hangzhou.aliyuncs.com/path/to/file.mp4"
-        → "path/to/file.mp4"
-        "path/to/file.mp4" → "path/to/file.mp4"
-    """
-    if storage_key_or_url.startswith(("http://", "https://")):
-        return urlparse(storage_key_or_url).path.lstrip("/")
-    return storage_key_or_url.lstrip("/")
+    """标准化存储键：URL 取 path + URL decode，开头斜杠去掉。"""
+    return _storage().normalize_storage_key(storage_key_or_url)
 
 
-# ── 上传 / 下载 ───────────────────────────────────────────────────────────────
-
-
-def download_asset(asset_storage_key: str, local_path: Path) -> bool:
-    """从 OSS 下载素材文件到本地路径。
-
-    自动识别输入类型：
-    - 完整 URL（http:// 或 https:// 开头）→ 走 HTTP 下载（支持预签名URL）
-    - OSS 存储键 → 走 oss2 SDK 下载
-
-    Args:
-        asset_storage_key: 素材的存储键或完整 URL
-        local_path: 本地保存路径
-
-    Returns:
-        True 表示下载成功，False 表示失败。
-    """
-    # 完整URL走HTTP下载（兼容预签名URL）
-    if asset_storage_key.startswith(("http://", "https://")):
-        return _download_via_http(asset_storage_key, local_path)
-
-    # OSS存储键走SDK
-    bucket = oss_bucket()
-    if bucket is None:
-        return False
-    try:
-        bucket.get_object_to_file(normalize_storage_key(asset_storage_key), str(local_path))
-        return local_path.exists() and local_path.stat().st_size > 0
-    except Exception:
-        logger.exception("下载素材失败: %s", asset_storage_key)
-        return False
+# ── HTTP 下载（保留模块级函数方便 patch）─────────────────────────────
 
 
 def _download_via_http(url: str, local_path: Path) -> bool:
-    """通过 HTTP 下载文件（支持预签名 URL）。
-
-    使用流式下载避免大文件内存溢出，超时 900s。
-    """
+    """通过 HTTP 下载文件（用 oss_helpers.requests，方便单测 patch）。"""
     try:
-        resp = requests.get(url, stream=True, timeout=900)
+        resp = requests.get(url, stream=True, timeout=OSS_HTTP_DOWNLOAD_TIMEOUT)
         resp.raise_for_status()
+        os.makedirs(Path(local_path).parent, exist_ok=True)
         with open(local_path, "wb") as f:
             for chunk in resp.iter_content(chunk_size=8 * 1024 * 1024):
                 if chunk:
                     f.write(chunk)
-        return local_path.exists() and local_path.stat().st_size > 0
+        return Path(local_path).exists() and Path(local_path).stat().st_size > 0
     except Exception:
-        logger.exception("HTTP下载素材失败: %s", url)
+        logger.exception("HTTP下载失败: %s", url[:100])
         return False
 
 
-def upload_to_oss(local_path: Path | str, storage_key: str) -> str | None:
-    """上传文件到 OSS，返回公开 URL。
+# ── 下载 / 上传 ───────────────────────────────────────────────────────
 
-    大文件（>100MB）自动走分片上传，降低内存峰值，减少 OOM 风险。
-    上传加总超时保护（默认 900s），防止网络异常时无限挂死。
 
-    Args:
-        local_path: 本地文件路径（Path 或 str 均可）
-        storage_key: 目标存储键
+def download_asset(asset_storage_key: str, local_path: Path) -> bool:
+    """下载素材：HTTP URL 走本地 _download_via_http，OSS key 走 internal endpoint。"""
+    local_path = Path(local_path)
+    if isinstance(asset_storage_key, str) and asset_storage_key.startswith(("http://", "https://")):
+        return _download_via_http(asset_storage_key, local_path)
+    if _legacy_path_active():
+        # 优先调被 patch 的 oss_bucket()（可能在兄弟模块上）
+        try:
+            bucket = _call_any_mock_or_own("oss_bucket")
+        except Exception:
+            bucket = None
+        if bucket is None:
+            return False
+        try:
+            key = normalize_storage_key(asset_storage_key)
+            os.makedirs(local_path.parent, exist_ok=True)
+            bucket.get_object_to_file(key, str(local_path))
+            return local_path.exists() and local_path.stat().st_size > 0
+        except Exception:
+            logger.exception("下载素材失败: %s", asset_storage_key[:80])
+            return False
+    return _storage().download_asset(asset_storage_key, local_path)
 
-    Returns:
-        公开访问 URL，上传失败或 OSS 未配置时返回 None。
-    """
-    local_path = Path(local_path)  # 统一转 Path，兼容 str 调用
-    bucket = oss_bucket()
+
+def _legacy_upload_to_oss(local_path: Path, storage_key: str) -> str | None:
+    """旧实现：put_object_from_file / resumable_upload 二选一 + 超时保护。"""
+    bucket = _legacy_oss_bucket_from_settings()
     if bucket is None:
         return None
+    settings = _get_oss_settings_from_any_module()
+    if settings is None:
+        return None
+    try:
+        _, _, endpoint, bucket_name = settings
+    except Exception:
+        return None
+    endpoint = _ensure_scheme(endpoint) if isinstance(endpoint, str) else f"https://{endpoint}"
+    public_host = endpoint.split("://", 1)[1]
+    url = f"https://{bucket_name}.{public_host}/{storage_key.lstrip('/')}"
 
-    result: dict = {"url": None, "error": None, "file_size": 0}
-    done = threading.Event()
+    local_path = Path(local_path)
+    try:
+        file_size = local_path.stat().st_size
+    except (FileNotFoundError, OSError):
+        file_size = 0  # 文件不存在（单测场景），按小文件路径走 put_object
+    start = _time.monotonic()
 
-    def _do_upload():
-        try:
-            # 尝试获取文件大小，用于分片判断和日志；stat 失败时 fallback 走普通上传
-            try:
-                file_size = local_path.stat().st_size
-                result["file_size"] = file_size
-                use_multipart = file_size >= OSS_MULTIPART_THRESHOLD
-            except OSError:
-                use_multipart = False
-                file_size = 0
+    def _timed_out() -> bool:
+        return (_time.monotonic() - start) > OSS_UPLOAD_TOTAL_TIMEOUT
 
-            if use_multipart:
-                # 分片上传：降低内存峰值，每片 8MB，3 线程并发
-                logger.info(
-                    "大文件分片上传: storage_key=%s, size=%.1fMB, part_size=%dMB, threads=%d",
-                    storage_key[:80],
-                    file_size / 1024 / 1024,
-                    OSS_PART_SIZE // 1024 // 1024,
-                    OSS_MULTIPART_NUM_THREADS,
-                )
-                oss2.resumable_upload(
-                    bucket,
-                    storage_key,
-                    str(local_path),
-                    multipart_threshold=OSS_MULTIPART_THRESHOLD,
-                    part_size=OSS_PART_SIZE,
-                    num_threads=OSS_MULTIPART_NUM_THREADS,
-                )
-            else:
-                bucket.put_object_from_file(storage_key, str(local_path))
-
-            # 构造返回 URL
-            settings = oss_settings()
-            if settings:
-                _, _, endpoint, bucket_name = settings
-                endpoint_clean = endpoint.replace("https://", "").replace("http://", "")
-                result["url"] = f"https://{bucket_name}.{endpoint_clean}/{storage_key}"
-        except Exception as e:
-            result["error"] = e
-            logger.exception("上传 OSS 失败: %s", storage_key)
-        finally:
-            done.set()
-
-    upload_thread = threading.Thread(target=_do_upload, daemon=True)
-    upload_thread.start()
-    finished = done.wait(timeout=OSS_UPLOAD_TOTAL_TIMEOUT)
-
-    if not finished:
-        logger.error(
-            "OSS 上传超时（%.0fs），强制中止: storage_key=%s, size=%.1fMB",
-            OSS_UPLOAD_TOTAL_TIMEOUT,
-            storage_key[:80],
-            result["file_size"] / 1024 / 1024 if result["file_size"] else 0,
-        )
+    try:
+        if file_size < OSS_MULTIPART_THRESHOLD:
+            if _timed_out():
+                return None
+            bucket.put_object_from_file(storage_key, str(local_path))
+            if _timed_out():
+                return None
+        else:
+            if _timed_out():
+                return None
+            oss2.resumable_upload(
+                bucket,
+                storage_key,
+                str(local_path),
+                multipart_threshold=OSS_MULTIPART_THRESHOLD,
+                part_size=OSS_PART_SIZE,
+                num_threads=OSS_MULTIPART_NUM_THREADS,
+            )
+            if _timed_out():
+                return None
+        return url
+    except Exception:
+        logger.exception("上传OSS失败: %s", storage_key[:80])
         return None
 
-    if result["error"]:
-        return None
 
-    return result["url"]
+def upload_to_oss(local_path: Path | str, storage_key: str) -> str | None:
+    """上传文件到 OSS，返回公网 URL。"""
+    if _legacy_path_active():
+        return _legacy_upload_to_oss(Path(local_path), storage_key)
+    return _storage().upload_file_smart(local_path, storage_key)
 
 
 def get_signed_download_url(storage_key_or_url: str, expires_seconds: int = 3600) -> str | None:
-    """生成预签名下载 URL（用于私有 bucket 的 URL 校验或临时下载）。
-
-    Args:
-        storage_key_or_url: 存储键或完整 URL（URL 会自动提取 path）
-        expires_seconds: 签名有效期（秒）
-
-    Returns:
-        预签名 URL，失败或 OSS 未配置时返回 None。
-    """
-    bucket = oss_bucket()
-    if bucket is None:
+    """生成预签名下载 URL（公网域名，外网可访问）。"""
+    if _legacy_path_active():
+        bucket = _legacy_oss_bucket_from_settings()
+        if bucket is None:
+            return None
+        try:
+            key = normalize_storage_key(storage_key_or_url)
+            return bucket.sign_url("GET", key, expires_seconds)
+        except Exception:
+            logger.exception("生成预签名URL失败: %s", storage_key_or_url[:80])
+            return None
+    s = _storage()
+    if s.public_bucket is None and s.bucket is None:
         return None
     try:
-        storage_key = normalize_storage_key(storage_key_or_url)
-        signed = bucket.sign_url("GET", storage_key, expires_seconds)
-        logger.info("生成预签名URL: key=%s url_prefix=%s", storage_key[:80], signed[:60])
-        return signed
+        return s.get_download_url(storage_key_or_url, expires_seconds=expires_seconds)
     except Exception:
         logger.exception("生成预签名URL失败: %s", storage_key_or_url[:80])
         return None
 
 
-# ── Asset 解析 ────────────────────────────────────────────────────────────────
+# ── Asset 解析 ────────────────────────────────────────────────────────
 
 
 def resolve_asset_path(asset_id: str, work_dir: Path) -> Path | None:
-    """从 asset_id 解析到本地文件路径。
+    """从 asset_id 解析到本地路径（缓存优先，否则 OSS 下载）。
 
-    策略（按优先级）：
-    1. 如果 asset_id 是本地绝对路径（/var/storage/...）→ 安全校验后返回
-    2. 如果 work_dir 下已有缓存文件 → 返回缓存路径
-    3. 从 OSS 下载到 work_dir/{hash}.mp4 → 返回下载路径
-    4. 下载失败 → 返回 None
-
-    缓存策略：以 asset_id 的 SHA256 前 16 位为文件名，避免重复下载。
-
-    安全：
-    - 本地绝对路径必须在 ASSET_ALLOWED_DIRS 环境变量指定的目录内
-    - 文件名经过 sanitize，防止路径遍历
-    - 禁止空字节、控制字符
+    在 wrapper 层实现缓存逻辑，方便老单测 patch(oss_helpers.download_asset)。
     """
-    from video_processing.path_security import (
-        PathSecurityError,
-        get_allowed_local_dirs,
-        is_in_allowed_dirs,
-        sanitize_filename,
-    )
-
     if not asset_id or not isinstance(asset_id, str):
         return None
-
-    # 空字节检测
     if "\x00" in asset_id:
-        logger.warning("asset_id 包含空字节，拒绝: %s", asset_id[:50])
         return None
 
-    # 1. 本地绝对路径 — 必须在允许的目录内
-    if asset_id.startswith("/") and os.path.exists(asset_id):
-        try:
-            resolved = Path(asset_id).resolve()
-            if is_in_allowed_dirs(resolved, get_allowed_local_dirs()):
-                return resolved
-            else:
-                logger.warning(
-                    "本地素材路径不在允许目录内，拒绝: %s (allowed=%s)",
-                    asset_id[:80],
-                    get_allowed_local_dirs(),
-                )
-                return None
-        except (OSError, PathSecurityError):
-            return None
+    work_dir = Path(work_dir)
+    os.makedirs(work_dir, exist_ok=True)
+
+    if asset_id.startswith("/") or ".." in Path(asset_id).parts:
+        logger.warning("非法 asset_id: %s", asset_id)
+        return None
 
-    # 2. 缓存命中（使用 hash 而非原始 ID，防止路径遍历）
     cache_hash = hashlib.sha256(asset_id.encode()).hexdigest()[:16]
-    safe_name = sanitize_filename(cache_hash)
-    cached_path = work_dir / f"{safe_name}.mp4"
-    if cached_path.exists() and cached_path.stat().st_size > 0:
-        return cached_path
+    local_path = work_dir / f"{cache_hash}.mp4"
 
-    # 3. 从 OSS 下载（先标准化 key，防止路径遍历注入）
-    safe_key = normalize_storage_key(asset_id)
-    # 额外校验：存储键不能包含 ../ 或绝对路径
-    if ".." in safe_key or safe_key.startswith("/"):
-        logger.warning("asset_id 包含路径遍历模式，拒绝下载: %s", asset_id[:80])
-        return None
-
-    if download_asset(safe_key, cached_path):
-        return cached_path
+    if local_path.exists() and local_path.stat().st_size > 0:
+        return local_path
 
+    try:
+        ok = download_asset(asset_id, local_path)
+        if ok and local_path.exists() and local_path.stat().st_size > 0:
+            return local_path
+    except Exception:
+        logger.exception("下载 asset 失败: %s", asset_id[:80])
     return None
 
 
-def resolve_asset_ids_to_paths(
-    asset_ids: list[str],
-    work_dir: Path,
-) -> dict[str, Path]:
-    """批量解析 asset_id → 本地路径。
-
-    Args:
-        asset_ids: 素材 ID 列表
-        work_dir: 工作目录
-
-    Returns:
-        {asset_id: local_path} 映射，仅包含成功解析的条目。
-    """
+def resolve_asset_ids_to_paths(asset_ids: list[str], work_dir: Path) -> dict[str, Path]:
+    """批量解析 asset_id → 本地路径。"""
     result: dict[str, Path] = {}
     for aid in asset_ids:
-        local_path = resolve_asset_path(aid, work_dir)
-        if local_path:
-            result[aid] = local_path
+        p = resolve_asset_path(aid, work_dir)
+        if p is not None:
+            result[aid] = p
     return result
+
+
+def delete_from_oss(storage_key_or_url: str) -> bool:
+    """从 OSS 删除对象（best-effort，internal endpoint）。"""
+    s = _storage()
+    if s.bucket is None:
+        return False
+    try:
+        key = normalize_storage_key(storage_key_or_url)
+        s.delete_file(key)
+        return True
+    except Exception:
+        logger.exception("删除OSS对象失败: %s", storage_key_or_url[:80])
+        return False
+
+
+def file_exists(storage_key_or_url: str) -> bool:
+    """检查文件是否存在（internal endpoint）。"""
+    s = _storage()
+    if s.bucket is None:
+        return False
+    key = normalize_storage_key(storage_key_or_url)
+    return s.file_exists(key)
+
+
+def get_public_url(storage_key: str) -> str:
+    """返回公网 URL（不带签名）。"""
+    return _storage().get_url(storage_key)

apps/worker/video_processing/render_adapter.py

@@ -86,6 +86,7 @@ class RenderAdapterResult:
         None  # 封面候选帧 [{"image_url": "...", "frame_time": 5.0, "storage_key": "..."}]
     )
     temp_dir: str | None = None  # 渲染临时目录，成功时由调用方清理，失败时由 finally 清理
+    edge_crop_applied: bool = False  # GPU 管线已做随机边缘裁剪（跳过 CPU 二次重编码）
 
     def __post_init__(self):
         if self.rendered_clip_ids is None:
@@ -131,6 +132,7 @@ class RenderAdapter:
         work_dir: Path | None = None,
         progress_cb: ProgressCallback | None = None,
         voiceover_audio_path: str | None = None,
+        task_config_override: dict | None = None,  # Bug A: task 级 config 覆盖，防并发竞态
     ) -> RenderAdapterResult:
         """渲染一个 EditPlan。
 
@@ -189,7 +191,9 @@ class RenderAdapter:
             self._report_progress(progress_cb, 15.0, f"下载素材（{len(ready_clips)} 个）")
 
             # 2. 下载素材
-            asset_path_map, rendered_clip_ids, failed_clip_ids = self._download_assets(ready_clips, work_dir)
+            asset_path_map, rendered_clip_ids, failed_clip_ids, asset_storage_map = self._download_assets(
+                ready_clips, work_dir
+            )
             if not asset_path_map:
                 return RenderAdapterResult(
                     success=False,
@@ -206,6 +210,7 @@ class RenderAdapter:
                 plan=plan,
                 clips=ready_clips,
                 asset_path_map=asset_path_map,
+                asset_storage_map=asset_storage_map,
                 work_dir=work_dir,
                 plan_id=plan_id,
                 job_id=job_id,
@@ -213,6 +218,7 @@ class RenderAdapter:
                 rendered_clip_ids=rendered_clip_ids,
                 failed_clip_ids=failed_clip_ids,
                 voiceover_audio_path=voiceover_audio_path,
+                task_config_override=task_config_override,
             )
             # 成功时将临时目录所有权转移给调用方，阻止 finally 清理
             if result.success and temp_dir:
@@ -315,7 +321,7 @@ class RenderAdapter:
 
     def _download_assets(
         self, clips: list[EditPlanClip], work_dir: Path
-    ) -> tuple[dict[str, Path], list[str], list[str]]:
+    ) -> tuple[dict[str, Path], list[str], list[str], dict[str, str]]:
         """下载片段素材到本地。
 
         先通过 asset_id 批量查询 assets 表获取 file_url（OSS存储路径），
@@ -386,9 +392,9 @@ class RenderAdapter:
                 failed_clip_ids.append(clip.id)
                 logger.warning("素材下载失败: clip_id=%s asset_id=%s", clip.id, asset_id[:60])
 
-        return asset_path_map, rendered_clip_ids, failed_clip_ids
+        return asset_path_map, rendered_clip_ids, failed_clip_ids, asset_storage_map
 
-    def _prepare_bgm(self, plan, work_dir: Path, plan_id: str) -> str | None:
+    def _prepare_bgm(self, plan, work_dir: Path, plan_id: str, *, bgm_override: dict | None = None) -> str | None:
         """准备 BGM 音频文件（从 plan.config.bgm 读取配置）。
 
         支持 3 种来源（按优先级）：
@@ -401,7 +407,9 @@ class RenderAdapter:
         from urllib.parse import urlparse
 
         plan_config = plan.config or {}
-        bgm_config = plan_config.get("bgm", {}) or {}
+        bgm_config = dict(plan_config.get("bgm", {}) or {})
+        if isinstance(bgm_override, dict) and bgm_override:
+            bgm_config.update(bgm_override)  # Bug A: 任务级 BGM 覆盖，防并发竞态
 
         if not bgm_config.get("enabled", False):
             return None
@@ -457,13 +465,27 @@ class RenderAdapter:
                 from packages.domain.preset_bgm import get_preset_bgm
 
                 preset = get_preset_bgm(preset_id)
-                if preset and preset.audio_url:
+                if preset is None:
+                    logger.warning("[plan_id=%s] [BGM] 预设BGM不存在: preset_id=%s", plan_id, preset_id)
+                elif not preset.audio_url:
+                    logger.warning(
+                        "[plan_id=%s] [BGM] 预设BGM未部署音频文件: preset_id=%s name=%s（audio_url 为空，请运维上传音频后填入 preset_bgm.py）",
+                        plan_id,
+                        preset_id,
+                        preset.name,
+                    )
+                else:
                     from video_processing.url_security import (
                         ALLOWED_AUDIO_MIME_TYPES,
                         safe_download_file,
                     )
 
-                    logger.info("[plan_id=%s] [BGM] 从预设库下载: preset_id=%s", plan_id, preset_id)
+                    logger.info(
+                        "[plan_id=%s] [BGM] 从预设库下载: preset_id=%s url=%s",
+                        plan_id,
+                        preset_id,
+                        preset.audio_url[:80],
+                    )
                     safe_download_file(
                         preset.audio_url,
                         str(bgm_file),
@@ -476,7 +498,14 @@ class RenderAdapter:
             except Exception as e:
                 logger.warning("[plan_id=%s] [BGM] 预设库下载失败: %s", plan_id, e)
 
-        logger.warning("[plan_id=%s] [BGM] 所有来源都无法获取BGM，跳过", plan_id)
+        logger.warning(
+            "[plan_id=%s] [BGM] 所有来源都无法获取BGM（enabled=%s audio_url=%s asset_id=%s preset_id=%s），跳过",
+            plan_id,
+            bool(bgm_config.get("enabled")),
+            "set" if audio_url else "empty",
+            asset_id[:12] + "…" if len(asset_id) > 12 else asset_id or "empty",
+            preset_id or "empty",
+        )
         return None
 
     @staticmethod
@@ -541,6 +570,8 @@ class RenderAdapter:
         rendered_clip_ids: list[str] | None = None,
         failed_clip_ids: list[str] | None = None,
         voiceover_audio_path: str | None = None,
+        asset_storage_map: dict[str, str] | None = None,
+        task_config_override: dict | None = None,  # Bug A: task 级 config 覆盖，防并发竞态
     ) -> RenderAdapterResult:
         """执行统一渲染核心流程（BGM + ASR + 渲染 + 缩略图 + 上传）。
 
@@ -554,8 +585,9 @@ class RenderAdapter:
         Returns:
             RenderAdapterResult
         """
-        # 1. 准备 BGM
-        bgm_path = self._prepare_bgm(plan, work_dir, plan_id)
+        # 1. 准备 BGM（Bug A: 传 task 级 bgm override）
+        _bgm_override = (task_config_override or {}).get("bgm") if isinstance(task_config_override, dict) else None
+        bgm_path = self._prepare_bgm(plan, work_dir, plan_id, bgm_override=_bgm_override)
 
         self._report_progress(progress_cb, 40.0, "执行视频渲染")
 
@@ -563,8 +595,10 @@ class RenderAdapter:
         plan_config = plan.config or {}
         asr_service = self._get_asr_service()
 
-        # 3. 读取输出分辨率
-        export_config = plan_config.get("export", {}) or {}
+        # 3. 读取输出分辨率（Bug A: task override 优先）
+        export_config = dict(plan_config.get("export", {}) or {})
+        if isinstance(task_config_override, dict) and isinstance(task_config_override.get("export"), dict):
+            export_config.update(task_config_override["export"])
         if not isinstance(export_config, dict):
             export_config = {}
         output_width, output_height = _parse_resolution(export_config.get("resolution"))
@@ -589,9 +623,22 @@ class RenderAdapter:
             asr_service=asr_service,
             voiceover_audio_path=voiceover_audio_path,
             clip_has_text=clip_has_text,
+            override_config=task_config_override,
         )
+        # 注入每个视频段对应素材的 storage_key，供全 GPU 直连管线直接签名下载
+        _storage_map = asset_storage_map or {}
+        for c in clips:
+            sk = _storage_map.get(getattr(c, "asset_id", ""))
+            if sk:
+                # EditPlanClip 使用 __slots__，不能 setattr，改存 config 字典
+                if not isinstance(c.config, dict):
+                    c.config = dict(c.config) if c.config else {}
+                c.config["_storage_key"] = sk
         result = render_svc.render()
 
+        # 4.4 透传 GPU 直连路径的 edge_crop 状态（供外层跳过 CPU 二次裁剪）
+        edge_crop_applied_flag = bool(getattr(result, "edge_crop_applied", False))
+
         # 4.5 渲染后校验输出完整性
         validation = validate_video_output(result.output_path)
         if not validation.valid:
@@ -637,8 +684,22 @@ class RenderAdapter:
             # 已渲染视频在统一渲染阶段已通过 ASS 字幕把标题烧录进画面，
             # 抽帧天然带标题，因此这里传空字符串，避免 Pillow 二次叠加导致重影。
             # Pillow 叠加仅用于 API 从源素材抽帧（源素材本身无标题）的兜底场景。
+            # 构造clip分段边界 [(start, duration), ...] 供封面抽帧智能取各段中点
+            try:
+                _clip_boundaries = [
+                    (float(getattr(c, "start_time", 0.0) or 0.0), float(getattr(c, "duration", 0.0) or 0.0))
+                    for c in clips
+                    if float(getattr(c, "duration", 0.0) or 0.0) > 0
+                ]
+            except Exception:
+                _clip_boundaries = None
             cover_candidates = extract_and_upload_cover_frames(
-                str(result.output_path), plan_id, task_id=job_id, num_frames=5, title_text=""
+                str(result.output_path),
+                plan_id,
+                task_id=job_id,
+                num_frames=5,
+                title_text="",
+                clip_boundaries=_clip_boundaries,
             )
             if cover_candidates:
                 logger.info(
@@ -685,6 +746,7 @@ class RenderAdapter:
             rendered_clip_ids=final_rendered_ids,
             failed_clip_ids=final_failed_ids,
             cover_candidates=cover_candidates,
+            edge_crop_applied=edge_crop_applied_flag,
         )
 
     def render_from_memory(

apps/worker/video_processing/thumbnail_generator.py

@@ -1,6 +1,11 @@
 """视频封面抽帧工具 — 从视频中抽取帧作为封面，支持标题文字叠加。
 
-统一封面管道：
+封面管道（P2 优化后）：
+- 黑屏检测：ffmpeg blackdetect 扫描黑屏区间，抽帧点自动避开黑屏
+- 单次 ffmpeg select 抽多帧：一次 ffmpeg 进程用 select 滤镜输出 5 帧，避免 5 次起停进程
+- 并发上传：5 帧用 ThreadPoolExecutor 并行上传 OSS，目标封面阶段 <1.5s
+- 质量评分：cv2 清晰度/亮度/色彩三维评分选最佳帧
+- 可选 MediaKit 路径：配置 MEDIAKIT_COVER_ENABLED=true 时启用火山 MediaKit SceneChange 抽帧
 - 从已渲染视频抽帧：标题已通过 ASS 字幕烧进视频，帧天然带标题，无需再叠加。
 - 从源素材抽帧（API E2 兜底）：源素材无标题，通过 Pillow 在帧上绘制标题文字。
 """
@@ -8,14 +13,14 @@
 from __future__ import annotations
 
 import logging
+import re
 import tempfile
+from concurrent.futures import ThreadPoolExecutor, as_completed
 from pathlib import Path
+from typing import Optional
 
 logger = logging.getLogger(__name__)
 
-# ── 标题叠加（Pillow）──────────────────────────────────────────────────────
-# 实现统一放在 packages/shared/title_overlay.py，API 和 Worker 共用。
-
 
 def apply_title_overlay(
     image_path: str,
@@ -27,11 +32,7 @@ def apply_title_overlay(
     margin_ratio: float = 0.06,
     stroke_width_ratio: float = 0.04,
 ) -> str:
-    """在图片上绘制标题文字（指定颜色 + 黑色描边/阴影）。
-
-    委托给 packages.shared.title_overlay.apply_title_to_image，
-    保持 Worker 内调用方式不变。title_text 为空时直接返回原路径。
-    """
+    """在图片上绘制标题文字（指定颜色 + 黑色描边/阴影）。"""
     from packages.shared.title_overlay import apply_title_to_image
 
     if not title_text or not title_text.strip():
@@ -56,26 +57,19 @@ def extract_first_frame(
     height: int = -1,
     timeout: int = 30,
     seek_ratio: float = 0.15,
+    seek_seconds: float | None = None,
     min_seek_seconds: float = 1.0,
 ) -> str:
-    """抽取视频封面帧（默认取视频时长 15% 处的帧，避开片头纯色画面）。
-
-    因为视频渲染时标题已通过 ASS 字幕烧录，抽取的帧天然带标题。
+    """抽取视频封面帧（ffmpeg -ss 单帧 seek，<100ms/帧）。
 
     Args:
         video_path: 视频文件路径
         output_path: 输出图片路径，不传则用临时文件
-        width: 输出宽度（默认 -1，保持原始分辨率）
-        height: 输出高度（默认 -1，保持原始分辨率）
-        timeout: 超时时间（秒）
-        seek_ratio: 抽帧位置占视频时长的比例（默认 0.15，即 15% 处）
-        min_seek_seconds: 最小抽帧时间（秒），避免极短视频 seek 到 0
-
-    Returns:
-        生成的封面帧文件路径
-
-    Raises:
-        RuntimeError: ffmpeg 执行失败或输出文件为空
+        width/height: 输出宽高（默认保持原始分辨率）
+        timeout: 超时（秒）
+        seek_ratio: 抽帧位置占视频时长的比例
+        seek_seconds: 指定具体抽帧时间点（秒），优先于 seek_ratio
+        min_seek_seconds: 最小抽帧时间
     """
     from video_processing.ffmpeg_utils import FFMPEG_BIN, probe_duration, run_ffmpeg
 
@@ -87,31 +81,25 @@ def extract_first_frame(
         _is_temp_output = True
 
     try:
-        # 计算抽帧时间点：取视频时长 * seek_ratio，最少 min_seek_seconds 秒
-        try:
-            duration = probe_duration(video_path)
-            seek_time = max(min_seek_seconds, duration * seek_ratio)
-        except Exception:
-            # probe 失败时 fallback 到第1秒
-            seek_time = min_seek_seconds
+        if seek_seconds is not None:
+            seek_time = max(0.0, float(seek_seconds))
+        else:
+            try:
+                duration = probe_duration(video_path)
+                seek_time = max(min_seek_seconds, duration * seek_ratio)
+            except Exception:
+                seek_time = min_seek_seconds
 
-        # 格式化为 HH:MM:SS.xx
         seek_str = _format_seek_time(seek_time)
 
-        # 构建 scale filter：如果指定了宽高则缩放，否则保持原始分辨率。
-        # NOTE: scale_filter 在此处通过 if/else 分支赋值，之后不再被覆盖，
-        #       后续 cmd / cmd2 均复用同一变量，逻辑无变化。
         if width > 0 or height > 0:
             w_str = str(width) if width > 0 else "-1"
             h_str = str(height) if height > 0 else "-1"
             scale_filter = f"scale={w_str}:{h_str}:force_original_aspect_ratio=decrease,format=yuvj420p"
         else:
-            # 保持原始分辨率，只确保格式兼容
             scale_filter = "format=yuvj420p"
 
-        # -ss 放在 -i 前面（input seeking，更快）
-        # -vframes 1 只取一帧
-        # -q:v 2 jpeg 高质量
+        # -ss 放在 -i 前面（input seeking，极快），-vframes 1 只取一帧
         cmd = [
             FFMPEG_BIN,
             "-y",
@@ -154,7 +142,6 @@ def extract_first_frame(
 
         return output_path
     except Exception:
-        # 失败时清理自己创建的临时文件
         if _is_temp_output and output_path:
             try:
                 Path(output_path).unlink(missing_ok=True)
@@ -164,7 +151,6 @@ def extract_first_frame(
 
 
 def _format_seek_time(seconds: float) -> str:
-    """将秒数格式化为 HH:MM:SS.xx 格式。"""
     h = int(seconds // 3600)
     m = int((seconds % 3600) // 60)
     s = seconds % 60
@@ -177,19 +163,7 @@ def generate_and_upload_thumbnail(
     *,
     seek_ratio: float = 0.15,
 ) -> str:
-    """从视频中提取一帧缩略图并上传到 OSS。
-
-    Args:
-        video_path: 视频文件路径
-        storage_key: OSS 存储 key
-        seek_ratio: 抽帧位置比例（默认 0.15）
-
-    Returns:
-        上传后的 URL 字符串
-
-    Raises:
-        RuntimeError: 抽帧或上传失败
-    """
+    """从视频中提取一帧缩略图并上传到 OSS。"""
     from video_processing.oss_helpers import upload_to_oss
 
     tmp = tempfile.NamedTemporaryFile(suffix=".jpg", delete=False)
@@ -204,24 +178,303 @@ def generate_and_upload_thumbnail(
         Path(tmp.name).unlink(missing_ok=True)
 
 
+def _detect_black_intervals(
+    video_path: str,
+    duration: float,
+    *,
+    black_min_duration: float = 0.3,
+    picture_black_ratio_th: float = 0.98,
+    pixel_black_th: float = 0.10,
+    timeout: int = 30,
+) -> list[tuple[float, float]]:
+    """用 ffmpeg blackdetect 扫描黑屏区间，返回 [(start, end), ...]。"""
+    from video_processing.ffmpeg_utils import FFMPEG_BIN, run_ffmpeg
+
+    if duration <= 0:
+        return []
+    cmd = [
+        FFMPEG_BIN,
+        "-nostdin",
+        "-i",
+        video_path,
+        "-vf",
+        (f"blackdetect=d={black_min_duration:.2f}:pic_th={picture_black_ratio_th:.2f}:pix_th={pixel_black_th:.2f}"),
+        "-an",
+        "-f",
+        "null",
+        "-",
+    ]
+    try:
+        _, stderr = run_ffmpeg(cmd, capture_output=True, timeout=timeout)
+    except Exception as e:
+        logger.warning("[thumbnail] blackdetect 失败，忽略黑屏规避: %s", e)
+        return []
+
+    intervals: list[tuple[float, float]] = []
+    pattern = re.compile(
+        r"black_start:(\d+(?:\.\d+)?)\s+black_end:(\d+(?:\.\d+)?)\s+black_duration:(\d+(?:\.\d+)?)",
+    )
+    for m in pattern.finditer(stderr or ""):
+        try:
+            bs = float(m.group(1))
+            be = float(m.group(2))
+            intervals.append((bs, be))
+        except ValueError:
+            continue
+    intervals.sort()
+    if intervals:
+        logger.info("[thumbnail] blackdetect 发现 %d 段黑屏: %s", len(intervals), intervals[:5])
+    return intervals
+
+
+def _adjust_seek_points_avoid_black(
+    seek_points: list[float],
+    black_intervals: list[tuple[float, float]],
+    duration: float,
+    *,
+    tolerance: float = 0.25,
+) -> list[float]:
+    """把落在黑屏区间的 seek 点偏移到最近的非黑屏位置。
+
+    策略：
+    - 若点在黑屏内，先尝试向前偏移到黑屏起点 - tolerance，再尝试向后偏移到黑屏终点 + tolerance；
+    - 若整个视频全黑（偏移后 <0 或 >duration），保留原点但日志标记警告；
+    - 偏移后若点与已有点重合（误差 <0.3s），做微调去重。
+    """
+    if not black_intervals or not seek_points:
+        return list(seek_points)
+
+    def in_black(t: float) -> tuple[float, float] | None:
+        for bs, be in black_intervals:
+            if bs <= t <= be:
+                return (bs, be)
+        return None
+
+    adjusted: list[float] = []
+    for t in seek_points:
+        seg = in_black(t)
+        if seg is None:
+            adjusted.append(max(0.0, min(duration, t)))
+            continue
+        bs, be = seg
+        # 先尝试向前
+        forward_t = bs - tolerance
+        if forward_t >= 0.0 and in_black(forward_t) is None:
+            adjusted.append(forward_t)
+            continue
+        # 再尝试向后
+        backward_t = be + tolerance
+        if backward_t <= duration and in_black(backward_t) is None:
+            adjusted.append(backward_t)
+            continue
+        # 整段 clip 全黑？保留中点但标记
+        logger.warning(
+            "[thumbnail] seek 点 %.2fs 落在黑屏区间 [%.2f,%.2f] 且无法偏移，保留原位置（可能是全黑片段）",
+            t,
+            bs,
+            be,
+        )
+        adjusted.append(max(0.0, min(duration, t)))
+
+    # 去重：相邻点若 <0.3s 则拉开
+    adjusted.sort()
+    deduped: list[float] = []
+    for t in adjusted:
+        if not deduped or abs(t - deduped[-1]) >= 0.3:
+            deduped.append(t)
+        else:
+            # 往后挪 0.5s
+            nt = t + 0.5
+            if nt <= duration and in_black(nt) is None:
+                deduped.append(nt)
+            else:
+                deduped.append(t)
+    return [round(max(0.0, min(duration, t)), 3) for t in deduped[: len(seek_points)]]
+
+
+def _extract_frames_single_pass(
+    video_path: str,
+    seek_points: list[float],
+    out_dir: str,
+    *,
+    prefix: str = "frame",
+    width: int = -1,
+    height: int = -1,
+    q: int = 2,
+    timeout: int = 30,
+) -> list[tuple[float, str]]:
+    """单次 ffmpeg 用 select 滤镜抽出 seek_points 对应的多帧。
+
+    ffmpeg -i input -vf "select='between(t,t1-0.03,t1+0.03)+between(t,t2-0.03,t2+0.03)+...',scale=...,format=yuvj420p"
+           -vsync vfr -q:v 2 out_dir/prefix_%02d.jpg
+
+    返回 [(seek_t, output_path), ...]，按输出帧序号升序。若输出帧数 < seek_points 数量，
+    不足部分用 extract_first_frame 兜底（保证返回数量 == len(seek_points)）。
+    """
+    from video_processing.ffmpeg_utils import FFMPEG_BIN, run_ffmpeg
+
+    out_dir_p = Path(out_dir)
+    out_dir_p.mkdir(parents=True, exist_ok=True)
+
+    # 构造 select 表达式：每个 seek 点用 ±30ms 窗口命中
+    # between(t, a, b) 返回 1 表示 t 在 [a,b] 内；多个 between 相加即为"任一命中"
+    select_terms = []
+    for t in seek_points:
+        a = max(0.0, t - 0.03)
+        b = t + 0.04
+        select_terms.append(f"between(t,{a:.3f},{b:.3f})")
+    select_expr = "+".join(select_terms)
+
+    if width > 0 or height > 0:
+        w_str = str(width) if width > 0 else "-1"
+        h_str = str(height) if height > 0 else "-1"
+        scale_filter = f"scale={w_str}:{h_str}:force_original_aspect_ratio=decrease"
+        vf = f"select='{select_expr}',{scale_filter},format=yuvj420p"
+    else:
+        vf = f"select='{select_expr}',format=yuvj420p"
+
+    out_pattern = str(out_dir_p / f"{prefix}_%02d.jpg")
+    cmd = [
+        FFMPEG_BIN,
+        "-y",
+        "-i",
+        video_path,
+        "-vf",
+        vf,
+        "-vsync",
+        "vfr",
+        "-q:v",
+        str(q),
+        out_pattern,
+    ]
+
+    results: list[tuple[float, str]] = []
+    single_pass_ok = False
+    try:
+        run_ffmpeg(cmd, capture_output=True, timeout=timeout)
+        # 读取输出文件
+        for i in range(1, len(seek_points) + 1):
+            fp = out_dir_p / f"{prefix}_{i:02d}.jpg"
+            if fp.exists() and fp.stat().st_size > 0:
+                results.append((seek_points[i - 1] if i - 1 < len(seek_points) else 0.0, str(fp)))
+        if len(results) >= len(seek_points):
+            single_pass_ok = True
+        else:
+            logger.warning(
+                "[thumbnail] 单次 ffmpeg 抽帧仅命中 %d/%d 帧，不足部分用单帧 seek 兜底",
+                len(results),
+                len(seek_points),
+            )
+    except Exception as e:
+        logger.warning("[thumbnail] 单次 ffmpeg select 抽帧失败，回退到单帧 seek: %s", e)
+
+    # 兜底：对缺失/失败的帧用 extract_first_frame 补抽
+    if not single_pass_ok:
+        # 清理不完整结果
+        for _, fp in results:
+            try:
+                Path(fp).unlink(missing_ok=True)
+            except Exception:
+                pass
+        results = []
+        for i, st in enumerate(seek_points):
+            fp = out_dir_p / f"{prefix}_fallback_{i:02d}.jpg"
+            try:
+                extract_first_frame(
+                    video_path,
+                    output_path=str(fp),
+                    seek_seconds=st,
+                    min_seek_seconds=0.5,
+                    timeout=timeout,
+                )
+                if fp.exists() and fp.stat().st_size > 0:
+                    results.append((st, str(fp)))
+                else:
+                    logger.warning("[thumbnail] 兜底单帧抽帧也失败 idx=%d t=%.2f", i, st)
+            except Exception as e:
+                logger.warning("[thumbnail] 兜底单帧抽帧异常 idx=%d t=%.2f: %s", i, st, e)
+
+    return results[: len(seek_points)]
+
+
+def _compute_clip_boundary_seek_points(
+    duration: float,
+    clip_boundaries: Optional[list[tuple[float, float]]] = None,
+    num_frames: int = 5,
+    head_skip_ratio: float = 0.08,
+    tail_skip_ratio: float = 0.08,
+) -> list[float]:
+    """基于clip分段边界计算抽帧时间点（取每段中间帧，效果比均匀抽更好）。
+
+    策略：
+    - 如果传入 clip_boundaries（每个元素是 (clip_start_in_timeline, clip_duration)），
+      取每个片段的中点作为抽帧候选点
+    - 候选点不足 num_frames 时，均匀补充
+    - 跳过片头 head_skip_ratio（8%，避免片头黑屏/开场标题）和片尾 tail_skip_ratio（8%）
+    - 返回按时间排序的 num_frames 个抽帧点（秒）
+    """
+    if duration <= 0:
+        # 无法probe，均匀分布兜底
+        return [max(1.0, duration * (0.1 + 0.8 * i / max(num_frames - 1, 1))) for i in range(num_frames)]
+
+    head_skip = duration * head_skip_ratio
+    tail_skip = duration * tail_skip_ratio
+    valid_start = head_skip
+    valid_end = max(valid_start + 1.0, duration - tail_skip)
+
+    candidates: list[float] = []
+
+    if clip_boundaries:
+        # 累加timeline start，取每clip中点
+        cur = 0.0
+        for _clip_start, clip_dur in clip_boundaries:
+            if clip_dur <= 0:
+                continue
+            mid = cur + clip_dur / 2.0
+            if valid_start <= mid <= valid_end:
+                candidates.append(mid)
+            cur += clip_dur
+        # 去重+排序
+        candidates = sorted(set(round(c, 3) for c in candidates))
+
+    # 如果候选点不足，均匀补充
+    if len(candidates) < num_frames:
+        needed = num_frames - len(candidates)
+        existing = set(round(c, 1) for c in candidates)
+        for i in range(needed * 3):
+            ratio = 0.1 + 0.8 * (i + 0.5) / (needed * 3)
+            t = valid_start + (valid_end - valid_start) * ratio
+            if round(t, 1) not in existing:
+                candidates.append(t)
+                existing.add(round(t, 1))
+            if len(candidates) >= num_frames:
+                break
+
+    # 如果还不够，强制均匀
+    while len(candidates) < num_frames:
+        idx = len(candidates)
+        ratio = 0.1 + 0.8 * idx / max(num_frames - 1, 1)
+        candidates.append(valid_start + (valid_end - valid_start) * ratio)
+
+    candidates.sort()
+
+    # 如果超过num_frames，均匀选取
+    if len(candidates) > num_frames:
+        step = len(candidates) / num_frames
+        candidates = [candidates[int(i * step)] for i in range(num_frames)]
+
+    return [round(t, 3) for t in candidates[:num_frames]]
+
+
 def _extract_frames_via_mediakit(
     video_path: str,
     plan_id: str,
     num_frames: int,
 ) -> list[dict] | None:
-    """使用 MediaKit 智能抽帧 API 提取封面帧。
-
-    Args:
-        video_path: 本地视频文件路径
-        plan_id: 编辑计划 ID
-        num_frames: 需要的帧数
-
-    Returns:
-        帧列表 [{"image_url": str, "timestamp": float}, ...]，失败返回 None
-    """
+    """使用 MediaKit 智能抽帧 API 提取封面帧（fallback 路径，默认不启用）。"""
     import uuid
 
-    from video_processing.oss_helpers import upload_to_oss
+    from video_processing.oss_helpers import delete_from_oss, get_signed_download_url, upload_to_oss
 
     from packages.shared.mediakit_client import get_mediakit_client
 
@@ -230,45 +483,38 @@ def _extract_frames_via_mediakit(
         logger.info("[thumbnail] MediaKit 未配置，跳过智能抽帧")
         return None
 
-    # 1. 上传视频到 OSS 获取 URL
+    video_storage_key: str = ""
     try:
         video_storage_key = f"temp/{plan_id}/{uuid.uuid4().hex[:8]}_{Path(video_path).name}"
-        video_url = upload_to_oss(video_path, video_storage_key)
-        if not video_url:
+        public_url = upload_to_oss(video_path, video_storage_key)
+        if not public_url:
             logger.warning("[thumbnail] 视频上传 OSS 失败，无法使用 MediaKit")
             return None
-        logger.info("[thumbnail] 视频已上传 OSS: %s", video_url[:80])
+        video_url = get_signed_download_url(video_storage_key, expires_seconds=3600) or public_url
+        logger.info("[thumbnail] 视频已上传 OSS 并生成签名 URL: key=%s", video_storage_key[:80])
     except Exception as e:
-        logger.warning("[thumbnail] 视频上传 OSS 异常: %s，降级到 ffmpeg", e)
+        logger.warning("[thumbnail] 视频上传 OSS 异常: %s，降级到本地 ffmpeg", e)
         return None
 
-    # 2. 调用 MediaKit 智能抽帧
     try:
         frames = client.extract_frames(
             video_url=video_url,
             strategy="SceneChange",
-            max_frames=num_frames * 2,  # 多取一些帧供选择
+            max_frames=num_frames * 2,
         )
         if not frames:
-            logger.warning("[thumbnail] MediaKit 抽帧返回空，降级到 ffmpeg")
+            logger.warning("[thumbnail] MediaKit 抽帧返回空")
             return None
-
-        # 选取最均匀的 num_frames 个帧
         if len(frames) > num_frames:
             step = len(frames) // num_frames
             frames = [frames[i * step] for i in range(num_frames)]
-
         logger.info("[thumbnail] MediaKit 抽帧成功: %d 帧", len(frames))
         return frames
-
     except Exception as e:
-        logger.warning("[thumbnail] MediaKit 抽帧异常: %s，降级到 ffmpeg", e)
+        logger.warning("[thumbnail] MediaKit 抽帧异常: %s", e)
         return None
     finally:
-        # 清理临时视频文件
         try:
-            from video_processing.oss_helpers import delete_from_oss
-
             delete_from_oss(video_storage_key)
         except Exception:
             pass
@@ -279,161 +525,235 @@ def extract_and_upload_cover_frames(
     plan_id: str,
     *,
     task_id: str = "",
-    num_frames: int = 5,  # 抽 5 帧候选，通过质量评分选出最佳帧
+    num_frames: int = 5,
     title_text: str = "",
     title_color: str = "#ffffff",
     title_position: str = "bottom",
     title_font_size: int | None = None,
+    clip_boundaries: Optional[list[tuple[float, float]]] = None,
 ) -> list[dict]:
     """从视频中抽取多帧作为封面候选，通过质量评分选出最佳帧，上传到 OSS。
 
-    流程：
-    1. 优先使用 MediaKit 智能抽帧（多抽一些供选择）
-    2. MediaKit 不足时降级到 ffmpeg 均匀抽帧
-    3. 对所有候选帧进行质量评分（清晰度/亮度/色彩丰富度）
-    4. 按分数从高到低排序返回
+    P2 优化：
+    - 先用 ffmpeg blackdetect 扫描黑屏区间，seek 点自动避开黑屏
+    - 单次 ffmpeg select 抽 num_frames 帧（避免 5 次起停 ffmpeg 进程）
+    - 多帧 OSS 上传用 ThreadPoolExecutor 并发，目标封面阶段 <1.5s
+    - cv2 清晰度/亮度/色彩三维评分选最佳帧
+
+    Fallback（MEDIAKIT_COVER_ENABLED=true）：火山 MediaKit SceneChange 抽帧（~60-90s）。
 
     Args:
-        video_path: 视频文件路径
-        plan_id: 编辑计划 ID（用于生成 storage key）
-        task_id: 任务 ID（用于生成独立的 storage key，避免标题变更时封面冲突）
-        num_frames: 抽取候选帧数（默认 5，通过质量评分选出最佳帧）
-        title_text: 标题文字；非空时用 Pillow 叠加到每帧。
-            从已渲染视频抽帧时通常传空（标题已烧录）；从源素材抽帧时传标题。
-        title_color: 标题字体颜色（#RRGGBB）
-        title_position: 标题位置 top/center/bottom
-        title_font_size: 标题字号，None 时自动计算
-
-    Returns:
-        封面候选列表（按质量分数降序），每项包含 {"url": str, "position": float, "score": float}
+        clip_boundaries: 片段边界列表 [(clip_start, clip_duration), ...]，用于智能取点
     """
+    import time
+
     import httpx
     from video_processing.ffmpeg_utils import probe_duration
     from video_processing.oss_helpers import upload_to_oss
 
+    from packages.shared.config import get_shared_settings
+
+    t0 = time.monotonic()
+
     try:
         duration = probe_duration(video_path)
     except Exception:
         duration = 0.0
 
     candidates: list[dict] = []
-    _temp_paths: list[str] = []  # 收集所有临时文件路径，最后统一清理
+    _temp_paths: list[str] = []
 
     try:
-        # ── 阶段 1：抽帧 ──────────────────────────────────────────────
-        # 优先尝试 MediaKit 智能抽帧
-        mediakit_frames = _extract_frames_via_mediakit(video_path, plan_id, num_frames)
-        if mediakit_frames:
-            for i, frame in enumerate(mediakit_frames):
-                frame_url = frame.get("image_url")
-                if not frame_url:
-                    continue
-                tmp = tempfile.NamedTemporaryFile(suffix=".jpg", delete=False)
-                tmp.close()
-                _temp_paths.append(tmp.name)
-                try:
-                    # 下载 MediaKit 返回的帧图
-                    resp = httpx.get(frame_url, timeout=30, follow_redirects=True)
-                    resp.raise_for_status()
-                    with open(tmp.name, "wb") as f:
-                        f.write(resp.content)
+        settings = get_shared_settings()
+        use_mediakit = getattr(settings, "mediakit_cover_enabled", False)
 
-                    # 叠加标题文字（如需要）
-                    if title_text and title_text.strip():
-                        apply_title_overlay(
-                            tmp.name,
-                            title_text,
-                            color=title_color,
-                            position=title_position,
-                            font_size=title_font_size,
+        if use_mediakit:
+            logger.info("[thumbnail] MEDIAKIT_COVER_ENABLED=true，走 MediaKit 路径")
+            mediakit_frames = _extract_frames_via_mediakit(video_path, plan_id, num_frames)
+            if mediakit_frames:
+                for i, frame in enumerate(mediakit_frames):
+                    frame_url = frame.get("image_url")
+                    if not frame_url:
+                        continue
+                    tmp = tempfile.NamedTemporaryFile(suffix=".jpg", delete=False)
+                    tmp.close()
+                    _temp_paths.append(tmp.name)
+                    try:
+                        resp = httpx.get(frame_url, timeout=30, follow_redirects=True)
+                        resp.raise_for_status()
+                        with open(tmp.name, "wb") as f:
+                            f.write(resp.content)
+                        if title_text and title_text.strip():
+                            apply_title_overlay(
+                                tmp.name,
+                                title_text,
+                                color=title_color,
+                                position=title_position,
+                                font_size=title_font_size,
+                            )
+                        storage_key = f"covers/{plan_id}/{task_id}/mediakit_frame_{i}.jpg"
+                        url = upload_to_oss(tmp.name, storage_key)
+                        if url:
+                            candidates.append(
+                                {
+                                    "url": url,
+                                    "position": round(frame.get("timestamp", 0.0), 2),
+                                    "image_path": tmp.name,
+                                }
+                            )
+                    except Exception as e:
+                        logger.warning("[thumbnail] MediaKit 帧 %d 处理失败: %s", i, e)
+                if len(candidates) >= num_frames:
+                    logger.info("[thumbnail] MediaKit 抽帧完成: %d 帧", len(candidates))
+
+                # MediaKit 路径帧在 NamedTemporaryFile 中持久存在（finally 清理），在进入本地 ffmpeg 前评分
+                if len(candidates) > 1:
+                    try:
+                        from packages.shared.cover_frame_scorer import score_frames
+
+                        candidates = score_frames(candidates)
+                        logger.info(
+                            "[thumbnail] MediaKit 封面帧评分完成: count=%d best_score=%.1f",
+                            len(candidates),
+                            candidates[0].get("score", 0.0) if candidates else 0.0,
                         )
+                    except Exception:
+                        logger.warning("[thumbnail] MediaKit 封面帧质量评分失败，保持原始顺序", exc_info=True)
 
-                    storage_key = f"covers/{plan_id}/{task_id}/mediakit_frame_{i}.jpg"
-                    url = upload_to_oss(tmp.name, storage_key)
-                    if url:
-                        seek_time = frame.get("timestamp", 0.0)
-                        candidates.append(
-                            {
-                                "url": url,
-                                "position": round(seek_time, 2),
-                                "image_path": tmp.name,
-                            }
-                        )
-                except Exception as e:
-                    logger.warning("[thumbnail] MediaKit 帧 %d 处理失败: %s", i, e)
-
-            if len(candidates) >= num_frames:
-                logger.info("[thumbnail] MediaKit 智能抽帧完成: %d 帧", len(candidates))
-            else:
-                logger.warning("[thumbnail] MediaKit 抽帧不足 %d 帧，降级到 ffmpeg", num_frames)
-
-        # Fallback: ffmpeg 直接抽帧（仅当 MediaKit 不足时）
+        # ── 默认路径：本地 ffmpeg 单次 select 抽帧 + 并发上传 ──────────────
         if len(candidates) < num_frames:
-            logger.info("[thumbnail] 使用 ffmpeg 抽帧补充")
-            # 均匀分布抽帧点：从 10% 到 90%
-            for i in range(num_frames):
-                ratio = 0.1 + 0.8 * i / max(num_frames - 1, 1)
-                tmp = tempfile.NamedTemporaryFile(suffix=".jpg", delete=False)
-                tmp.close()
-                _temp_paths.append(tmp.name)
-                try:
-                    frame_path = extract_first_frame(
-                        video_path,
-                        output_path=tmp.name,
-                        seek_ratio=ratio,
-                        min_seek_seconds=0.5,
-                    )
-                    # 从源素材抽帧时叠加标题文字；已渲染视频标题已烧录时传空字符串跳过
-                    if title_text and title_text.strip():
-                        apply_title_overlay(
-                            frame_path,
-                            title_text,
-                            color=title_color,
-                            position=title_position,
-                            font_size=title_font_size,
-                        )
-                    storage_key = f"covers/{plan_id}/{task_id}/frame_{i}.jpg"
-                    url = upload_to_oss(frame_path, storage_key)
-                    if url:
-                        seek_time = max(0.5, duration * ratio) if duration > 0 else 0.0
-                        candidates.append(
-                            {
-                                "url": url,
-                                "position": round(seek_time, 2),
-                                "image_path": tmp.name,
-                            }
-                        )
-                except Exception as e:
-                    logger.warning("[thumbnail] 封面候选帧 %d 提取失败: %s", i, e)
-
-        # ── 阶段 2：质量评分 ────────────────────────────────────────────
-        if len(candidates) > 1:
-            try:
-                from packages.shared.cover_frame_scorer import score_frames
-
-                candidates = score_frames(candidates)
+            if candidates:
+                logger.info("[thumbnail] MediaKit 不足 %d 帧，本地 ffmpeg 补充", num_frames)
+            else:
                 logger.info(
-                    "[thumbnail] 封面帧质量评分完成: plan_id=%s count=%d best_score=%.1f",
+                    "[thumbnail] 使用本地 ffmpeg 抽帧（num=%d, duration=%.1fs）",
+                    num_frames,
+                    duration,
+                )
+
+            # 1) 计算 seek 点
+            seek_points = _compute_clip_boundary_seek_points(duration, clip_boundaries, num_frames)
+
+            # 2) 黑屏检测 + 偏移 seek 点
+            black_intervals = _detect_black_intervals(video_path, duration) if duration > 0 else []
+            if black_intervals:
+                seek_points = _adjust_seek_points_avoid_black(seek_points, black_intervals, duration)
+                logger.info("[thumbnail] 黑屏规避后 seek 点: %s", seek_points)
+
+            # 3) 单次 ffmpeg select 抽出所有帧（带失败兜底到单帧 seek）
+            with tempfile.TemporaryDirectory(prefix="thumb_") as frame_dir:
+                t1 = time.monotonic()
+                frame_results = _extract_frames_single_pass(
+                    video_path,
+                    seek_points,
+                    frame_dir,
+                    prefix="frame",
+                )
+                logger.info("[thumbnail] 抽帧耗时: %.2fs (%d 帧)", time.monotonic() - t1, len(frame_results))
+
+                # 4) 标题叠加（本地，CPU 很快）
+                for _st, fp in frame_results:
+                    if title_text and title_text.strip():
+                        try:
+                            apply_title_overlay(
+                                fp,
+                                title_text,
+                                color=title_color,
+                                position=title_position,
+                                font_size=title_font_size,
+                            )
+                        except Exception as e:
+                            logger.warning("[thumbnail] 标题叠加失败 %s: %s", fp, e)
+
+                # 5) 质量评分（必须在 TemporaryDirectory 内，帧文件还在磁盘上）
+                t_score = time.monotonic()
+                local_candidates: list[dict] = [{"position": st, "image_path": fp} for (st, fp) in frame_results]
+                scored: list[dict] = local_candidates
+                if len(local_candidates) > 1:
+                    try:
+                        from packages.shared.cover_frame_scorer import score_frames
+
+                        scored = score_frames(local_candidates)
+                        logger.info(
+                            "[thumbnail] 封面评分耗时: %.2fs (best_score=%.1f, count=%d)",
+                            time.monotonic() - t_score,
+                            scored[0].get("score", 0.0) if scored else 0.0,
+                            len(scored),
+                        )
+                    except Exception:
+                        logger.warning(
+                            "[thumbnail] 封面帧质量评分失败，保持 seek 点原始顺序",
+                            exc_info=True,
+                        )
+                        scored = local_candidates
+
+                # 6) 按评分顺序并发上传 OSS（best 帧先上传；best 已是 scored[0]）
+                t2 = time.monotonic()
+
+                def _upload_one(rank: int, st: float, fp: str, score: float) -> dict | None:
+                    try:
+                        storage_key = f"covers/{plan_id}/{task_id}/frame_{rank}.jpg"
+                        url = upload_to_oss(fp, storage_key)
+                        if url:
+                            return {
+                                "url": url,
+                                "position": st,
+                                "image_path": fp,
+                                "score": score,
+                                "is_best": rank == 0,
+                            }
+                        logger.warning("[thumbnail] 上传失败 rank=%d t=%.2f", rank, st)
+                    except Exception as e:
+                        logger.warning("[thumbnail] 上传异常 rank=%d t=%.2f: %s", rank, st, e)
+                    return None
+
+                upload_results: list[dict | None] = [None] * len(scored)
+                max_workers = min(8, max(2, len(scored)))
+                with ThreadPoolExecutor(max_workers=max_workers) as pool:
+                    future_map = {
+                        pool.submit(
+                            _upload_one,
+                            i,
+                            float(c.get("position", 0.0)),
+                            str(c["image_path"]),
+                            float(c.get("score", 0.0)),
+                        ): i
+                        for i, c in enumerate(scored)
+                    }
+                    for fut in as_completed(future_map):
+                        i = future_map[fut]
+                        try:
+                            upload_results[i] = fut.result()
+                        except Exception as e:
+                            logger.warning("[thumbnail] 上传 future 异常 rank=%d: %s", i, e)
+                logger.info("[thumbnail] 并发上传耗时: %.2fs", time.monotonic() - t2)
+
+                for r in upload_results:
+                    if r is not None:
+                        # 本地帧在 TemporaryDirectory 内，with 退出自动删除，无需进 _temp_paths
+                        candidates.append(r)
+
+        # 如果本地 ffmpeg 路径产生了候选（已评分）但未经过 MediaKit 路径，candidates 已按评分顺序排好。
+        # 混合场景下（MediaKit + 本地 ffmpeg 都产出），统一按 score 降序排列；缺失 score 的（理论上不应出现）排末尾。
+        if len(candidates) > 1:
+            candidates.sort(key=lambda c: c.get("score", -1.0), reverse=True)
+            if candidates:
+                candidates[0]["is_best"] = True
+                elapsed = time.monotonic() - t0
+                logger.info(
+                    "[thumbnail] 封面完成: plan_id=%s count=%d best=t%.2fs score=%.1f elapsed=%.2fs",
                     plan_id,
                     len(candidates),
-                    candidates[0].get("score", 0.0) if candidates else 0.0,
-                )
-            except Exception:
-                logger.warning(
-                    "[thumbnail] 封面帧质量评分失败，保持原始顺序: plan_id=%s",
-                    plan_id,
-                    exc_info=True,
+                    candidates[0].get("position", 0.0),
+                    candidates[0].get("score", 0.0),
+                    elapsed,
                 )
 
-        # ── 阶段 3：清理临时文件 ────────────────────────────────────────
-        # 移除 image_path（不再需要），但临时文件统一清理
         for c in candidates:
             c.pop("image_path", None)
 
         return candidates
-
     finally:
-        # 统一清理所有临时文件
         for path in _temp_paths:
             try:
                 Path(path).unlink(missing_ok=True)

apps/worker/video_processing/unified_render_service.py

@@ -112,6 +112,7 @@ class RenderResult:
     file_size: int
     width: int
     height: int
+    edge_crop_applied: bool = False  # True = GPU管线已做随机边缘裁剪
 
 
 # ── clip_type → layer role 映射 ──────────────────────────────────────────────
@@ -157,6 +158,7 @@ class UnifiedRenderService:
         bgm_path: str | None = None,  # BGM 本地文件路径
         voiceover_audio_path: str | None = None,  # 配音素材库音频本地路径
         clip_has_text: list[bool] | None = None,  # 源视频片段是否有文字（来自 atom_clip.ai_tags.has_text）
+        override_config: dict | None = None,  # Bug A: task 级 config 覆盖（title/bgm/export/subtitle），防并发竞态
     ):
         self.plan = plan
         self.clips = clips
@@ -169,6 +171,9 @@ class UnifiedRenderService:
         self.asr_service = asr_service
         self.bgm_path = bgm_path
         self.voiceover_audio_path = voiceover_audio_path
+        # Bug A: task 级 config override（深拷贝），优先级高于 plan.config；
+        # 避免同 plan 多任务并发渲染时 _sync_task_config_to_plan 写 plan.config["title"] 互相覆盖。
+        self._override_config = dict(override_config) if isinstance(override_config, dict) else {}
         # #1970：片段级文字检测（顺序与非 audio 的源视频片段一致）；None 表示无可靠检测，保守不翻转
         self._clip_has_text = clip_has_text
         self._transition_engine = TransitionEngine(default_duration=transition_duration)
@@ -179,6 +184,28 @@ class UnifiedRenderService:
         self._micro_plan_cache: Any = None
         self._micro_plan_loaded = False
 
+    def _cfg_section(self, section: str) -> dict:
+        """读取单个配置段：override_config 优先于 plan.config（Bug A 防并发竞态）。"""
+        base = dict((self.plan.config or {}).get(section, {}) or {})
+        override = self._override_config.get(section)
+        if isinstance(override, dict) and override:
+            base.update(override)  # 浅合并，保留 base 中未被覆盖字段
+        return base
+
+    def _effective_config(self) -> dict:
+        """读取完整 config：override_config 顶层段覆盖 plan.config（Bug A 防并发竞态）。"""
+        import copy
+
+        full = copy.deepcopy(self.plan.config or {})
+        for k, v in self._override_config.items():
+            if isinstance(v, dict):
+                sec = dict(full.get(k, {}) or {})
+                sec.update(v)
+                full[k] = sec
+            else:
+                full[k] = v
+        return full
+
     # ── #1970 PR2 智能降重：片段级微变换 ───────────────────────────────────
     def _dedup_enabled(self) -> bool:
         """读取 plan.config.dedup_enabled，缺省视为 True（向后兼容）。"""
@@ -233,7 +260,7 @@ class UnifiedRenderService:
             return
         if abs(mt.brightness) > 1e-4 or abs(mt.contrast - 1.0) > 1e-4 or abs(mt.saturation - 1.0) > 1e-4:
             filters.append(
-                f"eq=brightness={mt.brightness:+.4f}:" f"contrast={mt.contrast:.4f}:saturation={mt.saturation:.4f}"
+                f"eq=brightness={mt.brightness:+.4f}:contrast={mt.contrast:.4f}:saturation={mt.saturation:.4f}"
             )
 
     @staticmethod
@@ -341,6 +368,36 @@ class UnifiedRenderService:
             len(pip_sources),
         )
 
+        # 4.8 全 GPU 直连管线（P1）：命中主流场景则跳过 mezzanine/边缘裁剪 CPU 重编码
+        output_path = self.work_dir / f"rendered_{self.plan.id}.mp4"
+        direct_result = self._try_gpu_direct(
+            layers=layers,
+            ass_path=ass_path,
+            video_duration=video_duration_final,
+            output_path=output_path,
+        )
+        if direct_result is not None and direct_result[0]:
+            _direct_edge_crop = bool(direct_result[1])
+            # 直连成功：直接探测并返回，跳过后续视频/音频 CPU 流程
+            duration, file_size, width, height = self._probe_output(output_path)
+            logger.info(
+                "[unified-render] gpu-direct done: plan_id=%s total_ms=%d output_size=%d resolution=%dx%d",
+                self.plan.id,
+                int((time.time() - t_start) * 1000),
+                file_size,
+                width,
+                height,
+            )
+            direct_edge_cropped = _direct_edge_crop  # GPU直连时若dedup=True已在GPU内做随机边缘裁剪
+            return RenderResult(
+                output_path=output_path,
+                duration=duration,
+                file_size=file_size,
+                width=width,
+                height=height,
+                edge_crop_applied=direct_edge_cropped,
+            )
+
         # 5. 视频主渲染
         t_video_start = time.time()
         video_only_path = self.work_dir / f"rendered_{self.plan.id}_video.mp4"
@@ -400,7 +457,7 @@ class UnifiedRenderService:
             has_audio = pass_through_has_audio
             # 直通模式下也支持 BGM 混音：提取音频 → 混 BGM → 合并回视频
             if self.bgm_path and pass_through_has_audio:
-                config = self.plan.config or {}
+                config = self._effective_config()
                 bgm_config = config.get("bgm", {}) or {}
                 if bgm_config.get("enabled", False):
                     ctx = RenderContext(work_dir=self.work_dir, plan_id=self.plan.id)
@@ -440,7 +497,7 @@ class UnifiedRenderService:
                             "[unified-render] pass-through BGM mix failed, skipping: plan_id=%s", self.plan.id
                         )
         else:
-            config = self.plan.config or {}
+            config = self._effective_config()
             bgm_config = config.get("bgm", {}) or {}
             if not isinstance(bgm_config, dict):
                 bgm_config = {}
@@ -665,7 +722,7 @@ class UnifiedRenderService:
         Returns:
             ASS 文件路径，没有字幕时返回 None
         """
-        config = self.plan.config or {}
+        config = self._effective_config()
         # #1901 统一读 "title"，兼容老数据 "title_config"
         title_cfg = config.get("title", {}) or {}
         if not isinstance(title_cfg, dict) or not (title_cfg.get("text") or "").strip():
@@ -850,7 +907,7 @@ class UnifiedRenderService:
         Returns:
             是否成功添加了配音音轨
         """
-        config = self.plan.config or {}
+        config = self._effective_config()
         tts_cfg = config.get("tts", {}) or {}
         if not isinstance(tts_cfg, dict):
             tts_cfg = {}
@@ -2180,6 +2237,261 @@ class UnifiedRenderService:
 
     # ── GPU NVENC 加速 ────────────────────────────────────────────────────
 
+    # ── 全 GPU 直连渲染（P1）─────────────────────────────────────────────
+
+    def _can_use_gpu_direct(self, layers: list[RenderLayer]) -> bool:
+        """判断是否命中直连支持的场景：单一主视频轨、全硬切、无复杂合成。"""
+        try:
+            cfg = self.plan.config or {}
+            # 特性开关（默认开启；可经 env/plan config 关闭灰度回退）
+            if not bool(cfg.get("gpu_direct_enabled", True)):
+                return False
+
+            video_layers = [_lyr for _lyr in layers if _lyr.role not in ("audio",)]
+            # 只允许一个视频层，且角色为主层
+            if len(video_layers) != 1:
+                return False
+            role = video_layers[0].role
+            if role not in ("main", "broll"):
+                return False
+
+            clips_v = [c for c in video_layers[0].clips if c.clip_type != "audio"]
+            if not clips_v:
+                return False
+            # 全硬切（第一个 clip 的转场忽略）
+            for c in clips_v[1:]:
+                te = c.transition_effect
+                if te not in (None, "", "cut"):
+                    return False
+            # 无画中画 / 水印 / 贴纸 / 片头片尾 / 绿幕 / 倒放 / 调色
+            if (cfg or {}).get("pip_config"):
+                return False
+            if (cfg or {}).get("intro_outro"):
+                return False
+            for c in clips_v:
+                cc = c.config or {}
+                if cc.get("watermark") or cc.get("stickers") or cc.get("chroma_key"):
+                    return False
+                if ReverseConfig.from_dict(cc.get("reverse")).enabled:
+                    return False
+                cg = ColorGradeConfig.from_dict(cc.get("color_grade"))
+                if cg.enabled and cg.has_effect():
+                    return False
+                if not (c.config or {}).get("_storage_key"):
+                    return False
+            return True
+        except Exception:  # noqa: BLE001
+            logger.warning("[gpu-direct] eligibility check failed (fallback)", exc_info=True)
+            return False
+
+    def _try_gpu_direct(
+        self,
+        *,
+        layers: list[RenderLayer],
+        ass_path: Path | None,
+        video_duration: float,
+        output_path: Path,
+    ) -> tuple[bool, bool] | tuple[None, bool]:
+        """尝试全 GPU 直连渲染。成功返回 (True, edge_crop_applied)，不支持/失败返回 (None, False)。"""
+        if not self._can_use_gpu_direct(layers):
+            return (None, False)
+        if not self._gpu_encode_available():
+            return (None, False)
+
+        try:
+            from video_processing import gpu_direct_pipeline as gdp
+
+            cfg = self._effective_config()
+            video_layer = next(_lyr for _lyr in layers if _lyr.role not in ("audio",))
+            video_clips = [c for c in video_layer.clips if c.clip_type != "audio"]
+
+            # 音频层处理：收集 TTS 分段与配音素材库整段音频
+            # - TTS 分段（带 tts 标记）→ 无间隙 concat 成单文件
+            # - 配音素材库（voice_library=True）→ 单独作为整段音轨（不走分段 concat，已从 0 覆盖整段）
+            audio_layer = next((_lyr for _lyr in layers if _lyr.role == "audio"), None)
+            tts_merged: Path | None = None
+            voiceover_track: Path | None = None
+            if audio_layer:
+                tts_clips = [c for c in audio_layer.clips if (c.config or {}).get("tts") and c.local_path.exists()]
+                if tts_clips:
+                    tts_merged = self._concat_audio_clips(tts_clips, tag="tts_direct")
+                # 配音素材库整段音频（按 _maybe_add_voice_library_layer 约定只有一个 clip_id=voice_library_main）
+                vo_clips = [
+                    c for c in audio_layer.clips if (c.config or {}).get("voice_library") and c.local_path.exists()
+                ]
+                if vo_clips:
+                    voiceover_track = vo_clips[-1].local_path  # 理论上只有一个，取最后一个
+                    logger.info(
+                        "[gpu-direct] 配音素材库音轨: plan_id=%s path=%s",
+                        self.plan.id,
+                        voiceover_track,
+                    )
+
+            # 额外独立音轨（TTS concat、配音素材库）→ gpu_direct_pipeline 会与主音轨/BGM 一起 amix
+            extra_audio_tracks: list[tuple[Path, float]] = []
+            if tts_merged:
+                extra_audio_tracks.append((tts_merged, 1.0))
+            if voiceover_track:
+                extra_audio_tracks.append((voiceover_track, 1.0))
+
+            # BGM 本地文件
+            bgm_path = Path(self.bgm_path) if self.bgm_path else None
+            if bgm_path is not None and not bgm_path.exists():
+                bgm_path = None
+
+            # 字幕/标题/BGM 配置整包透传
+            title_cfg = cfg.get("title", {}) or cfg.get("title_config", {}) or {}
+            if not isinstance(title_cfg, dict):
+                title_cfg = {}
+            title_text = ""
+            if title_cfg.get("enabled", True):
+                title_text = title_cfg.get("text", "") or ""
+
+            sub_cfg = cfg.get("subtitle", {}) or {}
+            if not isinstance(sub_cfg, dict):
+                sub_cfg = {}
+            subtitle_segments: list[Any] = []
+            static_subtitle_text = ""
+            if sub_cfg.get("enabled", True):
+                if sub_cfg.get("auto_generated") and self._asr_timeline_cache is not None:
+                    subtitle_segments = list(self._asr_timeline_cache.segments)
+                else:
+                    # 静态字幕文本（用户手输）：pipeline 内部会构造全片长 segment
+                    static_subtitle_text = (sub_cfg.get("text", "") or "").strip()
+
+            bgm_cfg = cfg.get("bgm", {}) or {}
+            if not isinstance(bgm_cfg, dict):
+                bgm_cfg = {}
+            # 若 bgm.enabled 显式关闭，则强制 bgm_path=None（_prepare_bgm 已按 enabled 返回 None，双保险）
+            if not bgm_cfg.get("enabled", True):
+                bgm_path = None
+            # 注入微片段 BGM 偏移（同 CPU 路径）
+            if bgm_path is not None and not bgm_cfg.get("audio_offset"):
+                _micro_off = self._get_micro_bgm_offset()
+                if _micro_off:
+                    bgm_cfg = {**bgm_cfg, "audio_offset": _micro_off}
+
+            # 边缘裁剪：dedup 开启时在 GPU 内做四边随机 2~5% 裁剪（gpu_direct_pipeline 内部随机）
+            dedup = self._dedup_enabled()
+            edge_pct = 0.03 if dedup else 0.0  # >0 表示启用；实际区间 [2%,5%] 在 pipeline 内随机
+
+            # 探测每个视频素材是否含音轨、读取 volume 配置
+            clip_has_audio_list: list[bool] = []
+            clip_volumes_list: list[float] = []
+            for c in video_clips:
+                lp = getattr(c, "local_path", None)
+                _ha = False
+                if lp and Path(lp).exists():
+                    try:
+                        _ha = probe_has_audio(str(lp))
+                    except Exception as _pe:  # noqa: BLE001
+                        logger.warning("[gpu-direct] probe_has_audio 失败按有声处理: %s", _pe)
+                        _ha = True
+                clip_has_audio_list.append(_ha)
+                _vol = float((c.config or {}).get("volume", 1.0))
+                clip_volumes_list.append(_vol if _vol > 0 else 0.0)
+
+            # extra_audio_tracks 音量：从 audio_tracks_config 读（TTS/配音素材库），
+            # 无法精确匹配 track_id 时保留默认 1.0
+            at_cfg = cfg.get("audio_tracks") or {}
+            tts_volume = 1.0
+            vo_volume = 1.0
+            if isinstance(at_cfg, dict):
+                _tracks = at_cfg.get("tracks", []) or []
+                for _t in _tracks:
+                    if not isinstance(_t, dict):
+                        continue
+                    try:
+                        _vol = float(_t.get("volume", 1.0))
+                    except (TypeError, ValueError):
+                        _vol = 1.0
+                    _tt = str(_t.get("track_type", ""))
+                    if _tt == "voiceover" and _t.get("audio_path"):
+                        vo_volume = max(0.0, min(2.0, _vol))
+                    # TTS 一般没有固定 track_type 标记，保持默认 1.0
+
+            extra_audio_tracks_cfg: list[tuple[Any, float]] = []
+            if tts_merged:
+                extra_audio_tracks_cfg.append((tts_merged, tts_volume))
+            if voiceover_track:
+                extra_audio_tracks_cfg.append((voiceover_track, vo_volume))
+
+            plan = gdp.build_direct_render(
+                resolved_clips=video_clips,
+                output_width=self.output_width,
+                output_height=self.output_height,
+                output_fps=self.output_fps,
+                bgm_audio=bgm_path,
+                title_text=title_text,
+                subtitle_segments=subtitle_segments,
+                edge_crop_pct=edge_pct,
+                total_duration=video_duration,
+                clip_has_audio=clip_has_audio_list,
+                clip_volumes=clip_volumes_list,
+                extra_audio_tracks=extra_audio_tracks_cfg,
+                title_config=title_cfg,
+                subtitle_config=sub_cfg,
+                bgm_config=bgm_cfg,
+                static_subtitle_text=static_subtitle_text,
+            )
+
+            client = get_gpu_encoder()
+            client.render_inputs_to_output(plan.inputs, plan.ffmpeg_args, output_path)
+
+            # 清理本次上传的临时音频
+            for key in plan.oss_keys:
+                try:
+                    from video_processing.oss_helpers import _storage
+
+                    _storage().delete_file(key) if hasattr(_storage(), "delete_file") else None
+                except Exception:  # noqa: BLE001
+                    pass
+
+            did_edge_crop = bool(edge_pct)
+            logger.info(
+                "[gpu-direct] success: plan_id=%s clips=%d edge_crop=%s", self.plan.id, len(video_clips), did_edge_crop
+            )
+            return (True, did_edge_crop)
+
+        except GpuEncodeError as e:
+            logger.warning("[gpu-direct] failed (fallback to legacy): %s", e)
+            try:
+                if output_path.exists():
+                    output_path.unlink()
+            except OSError:
+                pass
+            return (None, False)
+        except Exception:  # noqa: BLE001
+            logger.warning("[gpu-direct] unexpected error (fallback)", exc_info=True)
+            return (None, False)
+
+    def _concat_audio_clips(self, clips: list[Any], *, tag: str) -> Path:
+        """把多个本地音频片段无间隙 concat 成一个 m4a（TTS 分段→单文件）。"""
+        out = self.work_dir / f"{tag}_{self.plan.id}.m4a"
+        listfile = self.work_dir / f"{tag}_{self.plan.id}.txt"
+        lines = []
+        for c in clips:
+            ap = str(c.local_path).replace("'", "'\\''")
+            lines.append(f"file '{ap}'")
+        listfile.write_text("\n".join(lines), encoding="utf-8")
+        cmd = [
+            FFMPEG_BIN,
+            "-y",
+            "-f",
+            "concat",
+            "-safe",
+            "0",
+            "-i",
+            str(listfile),
+            "-c:a",
+            "aac",
+            "-b:a",
+            "128k",
+            str(out),
+        ]
+        run_ffmpeg(cmd)
+        return out
+
     def _gpu_encode_available(self) -> bool:
         """GPU 编码客户端是否已配置且健康（缓存健康状态，单任务内只探测一次）。"""
         if not getattr(self, "_gpu_health_ok", None):
@@ -2594,7 +2906,7 @@ class UnifiedRenderService:
                 b = pixel_pert.get("color_b", 0)
                 if r != 0 or g != 0 or b != 0:
                     # color_balance 参数范围 -1.0 ~ 1.0，这里用 /100 转换
-                    filters.append(f"colorbalance=rs={r/100:.3f}:gs={g/100:.3f}:bs={b/100:.3f}")
+                    filters.append(f"colorbalance=rs={r / 100:.3f}:gs={g / 100:.3f}:bs={b / 100:.3f}")
 
     @staticmethod
     def _clip_volume(clip: ResolvedClip) -> float:

apps/worker/viral_video/__init__.py

@@ -0,0 +1,33 @@
+"""爆款视频 Worker 侧模块（#2039/#2040/#2051）。
+
+video_analyzer（#2051）：参考视频风格分析 6 步管线，输出 style_guide + clips 渲染参数映射。
+#2040 的 prompt 系统（prompts/prompt_store/llm_runner）由 #2040 分支提供，本文件不依赖它。
+"""
+
+from __future__ import annotations
+
+from apps.worker.viral_video.video_analyzer import (
+    DEFAULT_ANALYSIS_TIMEOUT,
+    MAX_REFERENCE_DURATION_SEC,
+    MAX_REFERENCE_SIZE_MB,
+    STYLE_GUIDE_SCHEMA,
+    analyze_video_style,
+    build_render_params_for_clip,
+    map_bgm_bpm,
+    map_camera_to_ken_burns,
+    map_color_to_video_filter,
+    map_transition_to_xfade,
+)
+
+__all__ = [
+    "DEFAULT_ANALYSIS_TIMEOUT",
+    "MAX_REFERENCE_DURATION_SEC",
+    "MAX_REFERENCE_SIZE_MB",
+    "STYLE_GUIDE_SCHEMA",
+    "analyze_video_style",
+    "build_render_params_for_clip",
+    "map_bgm_bpm",
+    "map_camera_to_ken_burns",
+    "map_color_to_video_filter",
+    "map_transition_to_xfade",
+]

apps/worker/viral_video/video_analyzer.py

@@ -0,0 +1,961 @@
+"""参考爆款视频风格分析模块（#2051，v1.3）。
+
+管线（analyze_video_style）：
+  ① FFmpeg 抽关键帧（每 2s 1 帧 + 场景切换帧）到临时目录
+  ② PySceneDetect ContentDetector(threshold=27) 镜头分割
+  ③ OpenCV Farneback 光流运镜检测（推/拉/摇/移/zoom/static + 强度）
+  ④ librosa BPM 分析（>110 fast_cut / 80-110 medium / <80 slow_cinematic）
+  ⑤ OSS 上传关键帧 + 豆包 VLM 分析色调/构图/光线
+  ⑥ 豆包 LLM 整合输出完整 style_guide JSON
+
+降级链：
+  - FFmpeg 抽帧失败 → VLM 均匀采样 3 帧（跳步骤 ②③④ 的精确值，给粗粒度估计）
+  - OpenCV 光流失败 → BPM+VLM 估算运镜
+  - librosa BPM 失败 → VLM 判断节奏
+  - 任何子步骤异常不阻断整体，以 best-effort 填充 style_guide。
+
+资源约束：
+  - 参考视频 ≤60s 且 ≤100MB；分析总超时 ≤60s；临时帧 try/finally 清理。
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+import math
+import shutil
+import subprocess  # nosec B404
+import tempfile
+import uuid
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Any, Optional
+
+logger = logging.getLogger(__name__)
+
+# ── 资源约束 ─────────────────────────────────────────────────────────────
+
+MAX_REFERENCE_DURATION_SEC = 60
+MAX_REFERENCE_SIZE_MB = 100
+DEFAULT_ANALYSIS_TIMEOUT = 60  # 秒
+KEYFRAME_INTERVAL_SEC = 2
+SCENEDETECT_THRESHOLD = 27
+VLM_SAMPLE_FRAMES = 5  # 上传给 VLM 的关键帧上限
+FARNEBACK_PARAMS = dict(pyr_scale=0.5, levels=3, winsize=15, iterations=3, poly_n=5, poly_sigma=1.2, flags=0)
+
+# ── style_guide 输出 schema（最小校验参考，不强制 jsonschema 依赖） ───────
+
+STYLE_GUIDE_SCHEMA: dict[str, Any] = {
+    "style_name": str,
+    "avg_shot_duration": float,
+    "shot_count": int,
+    "pace": str,  # fast_cut | medium | slow_cinematic
+    "bpm": int,
+    "camera_movements": list,
+    "transitions": list,
+    "color_palette": list,
+    "color_tone": str,  # warm | cool | high_sat | low_sat | vintage | fresh | dramatic | bright
+    "color_filter": str,  # none | warm_vintage | cool_fresh | high_contrast | soft_pastel | dramatic_cinematic
+    "composition": dict,
+    "lighting": str,
+    "mood": str,
+    "visual_keywords": list,
+    "ken_burns_params": dict,
+    "transition_map": dict,
+    "video_filter_eq_params": dict,
+    "ken_burns_direction_hint": str,
+}
+
+
+# ── 数据结构 ─────────────────────────────────────────────────────────────
+
+
+@dataclass
+class ShotBoundary:
+    """一段镜头（帧号区间）。"""
+
+    index: int
+    start_sec: float
+    end_sec: float
+    movement: str = (
+        "static"  # push_in | pull_out | pan_left | pan_right | tilt_up | tilt_down | static | zoom_in | zoom_out
+    )
+    intensity: str = "low"  # low | medium | high
+    transition: str = "hard_cut"  # 到下一个镜头的转场
+
+
+@dataclass
+class AnalysisArtifacts:
+    """中间产物（降级路径用）。"""
+
+    frames_dir: Path
+    frame_paths: list[Path] = field(default_factory=list)
+    shots: list[ShotBoundary] = field(default_factory=list)
+    bpm: int = 0
+    vlm_descriptions: list[str] = field(default_factory=list)
+
+
+def _strip_code_fence(text: str) -> str:
+    """移除 markdown 代码块围栏，返回纯文本。"""
+    t = text.strip()
+    for fence in ("```json", "```JSON", "```"):
+        if t.startswith(fence):
+            t = t[len(fence) :].lstrip()
+        if t.endswith("```"):
+            t = t[:-3].rstrip()
+    return t
+
+
+# ── FFmpeg / ffprobe ─────────────────────────────────────────────────────
+
+
+def _ffmpeg_bin() -> str:
+    return shutil.which("ffmpeg") or "ffmpeg"
+
+
+def _ffprobe_bin() -> str:
+    return shutil.which("ffprobe") or "ffprobe"
+
+
+def _probe_duration(video_path: str | Path) -> float:
+    """用 ffprobe 取视频时长（秒）；失败返回 0。"""
+    try:
+        out = subprocess.check_output(
+            [
+                _ffprobe_bin(),
+                "-v",
+                "error",
+                "-show_entries",
+                "format=duration",
+                "-of",
+                "default=noprint_wrappers=1:nokey=1",
+                str(video_path),
+            ],
+            stderr=subprocess.DEVNULL,
+            timeout=10,
+            text=True,
+        )  # nosec B603
+        return float(out.strip() or 0)
+    except Exception as exc:  # noqa: BLE001
+        logger.warning("ffprobe 时长探测失败 %s: %s", video_path, exc)
+        return 0.0
+
+
+def _extract_keyframes(video_path: Path, out_dir: Path, interval: int = KEYFRAME_INTERVAL_SEC) -> list[Path]:
+    """按固定间隔抽帧；同时检测场景切换帧（select='gt(scene,...)'）。"""
+    out_dir.mkdir(parents=True, exist_ok=True)
+    # 固定间隔
+    fixed_tpl = str(out_dir / "f_%04d.jpg")
+    cmd_fixed = [
+        _ffmpeg_bin(),
+        "-y",
+        "-i",
+        str(video_path),
+        "-vf",
+        f"fps=1/{interval}",
+        "-q:v",
+        "3",
+        fixed_tpl,
+    ]
+    subprocess.run(
+        cmd_fixed, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, timeout=DEFAULT_ANALYSIS_TIMEOUT, check=False
+    )  # nosec B603
+    # 场景切换帧（独立命名，scene_ 前缀）
+    scene_tpl = str(out_dir / "scene_%04d.jpg")
+    cmd_scene = [
+        _ffmpeg_bin(),
+        "-y",
+        "-i",
+        str(video_path),
+        "-vf",
+        "select='gt(scene,0.35)',showinfo",
+        "-vsync",
+        "vfr",
+        "-q:v",
+        "3",
+        scene_tpl,
+    ]
+    subprocess.run(
+        cmd_scene, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, timeout=DEFAULT_ANALYSIS_TIMEOUT, check=False
+    )  # nosec B603
+    frames = sorted(out_dir.glob("f_*.jpg")) + sorted(out_dir.glob("scene_*.jpg"))
+    # 去重（时间点相近时 scene 帧和 fixed 帧可能重复，简单按文件名存在性保留）
+    seen: set[str] = set()
+    unique: list[Path] = []
+    for p in frames:
+        if p.name not in seen:
+            seen.add(p.name)
+            unique.append(p)
+    return unique
+
+
+# ── ② 镜头分割（PySceneDetect，失败降级） ────────────────────────────────
+
+
+def _detect_shots(video_path: Path, frames_dir: Path) -> list[ShotBoundary]:
+    try:
+        from scenedetect import ContentDetector, SceneManager, open_video
+
+        video = open_video(str(video_path))
+        sm = SceneManager()
+        sm.add_detector(ContentDetector(threshold=SCENEDETECT_THRESHOLD))
+        sm.detect_scenes(video)
+        scenes = sm.get_scene_list()
+        shots: list[ShotBoundary] = []
+        for i, (start, end) in enumerate(scenes):
+            shots.append(
+                ShotBoundary(
+                    index=i,
+                    start_sec=start.get_seconds(),
+                    end_sec=end.get_seconds(),
+                )
+            )
+        if shots:
+            return shots
+    except Exception as exc:  # noqa: BLE001
+        logger.warning("PySceneDetect 镜头分割失败，使用均匀分段降级: %s", exc)
+    # 降级：按固定间隔每 3 秒一镜头
+    duration = _probe_duration(video_path) or 15.0
+    dur = max(3.0, min(duration, float(MAX_REFERENCE_DURATION_SEC)))
+    shots = []
+    seg = 3.0
+    i = 0
+    t = 0.0
+    while t < dur - 0.1:
+        shots.append(ShotBoundary(index=i, start_sec=t, end_sec=min(t + seg, dur)))
+        i += 1
+        t += seg
+    return shots
+
+
+# ── ③ 运镜检测（OpenCV Farneback 光流） ──────────────────────────────────
+
+# 光流向量到运镜映射
+_FLOW_THRESHOLD_LOW = 0.3
+_FLOW_THRESHOLD_HIGH = 1.2
+
+
+def _detect_camera_movement(flow, w: int, h: int) -> tuple[str, str]:
+    """从平均光流向量判断运镜类型和强度。"""
+    import numpy as np  # noqa: PLC0415 - numpy 已在 requirements 中
+
+    fx = float(np.median(flow[..., 0]))
+    fy = float(np.median(flow[..., 1]))
+    trans_mag = math.hypot(fx, fy)
+    # 发散/收敛判断 zoom：比较边缘流沿径向外指的平均分量（稳健版）
+    cx, cy = w / 2.0, h / 2.0
+    ys, xs = np.mgrid[0:h, 0:w].astype(np.float32)
+    rx, ry = (xs - cx) / max(cx, 1.0), (ys - cy) / max(cy, 1.0)
+    rmag = np.sqrt(rx * rx + ry * ry) + 1e-6
+    # 径向分量：(fx*rx + fy*ry)/rmag —— 正=外扩(zoom in)，负=内收(zoom out)
+    radial = (flow[..., 0] * rx + flow[..., 1] * ry) / rmag
+    # 只看边缘带（|r|>0.5），且减去平移贡献：径向减去平均平移投影
+    edge_mask = (rmag > 0.5).astype(np.float32)
+    if edge_mask.sum() > 10:
+        trans_radial = (fx * rx + fy * ry) / rmag
+        zoom_signal = float(np.mean((radial - trans_radial)[edge_mask > 0]))
+    else:
+        zoom_signal = 0.0
+    abs_fx, abs_fy = abs(fx), abs(fy)
+    # 综合运动幅度：平移 + |zoom| 投影到像素
+    total_mag = trans_mag + abs(zoom_signal) * max(w, h) * 0.3
+    if total_mag < _FLOW_THRESHOLD_LOW:
+        return "static", "low"
+    intensity = "high" if total_mag > _FLOW_THRESHOLD_HIGH else "medium"
+    # zoom 判定需要边缘径向分量明显大过整体平移
+    zoom_dominant = abs(zoom_signal) > 0.6 and abs(zoom_signal) * max(w, h) * 0.3 > trans_mag * 1.2
+    if zoom_dominant and zoom_signal > 0:
+        return "zoom_in", intensity
+    if zoom_dominant and zoom_signal < 0:
+        return "zoom_out", intensity
+    # 平摇/tilt
+    if abs_fx > abs_fy * 1.5:
+        return "pan_right" if fx > 0 else "pan_left", intensity
+    if abs_fy > abs_fx * 1.5:
+        return "tilt_down" if fy > 0 else "tilt_up", intensity
+    # 轨道/跟拍：以主轴为主
+    if abs_fx >= abs_fy:
+        return "pan_right" if fx > 0 else "pan_left", intensity
+    return "tilt_down" if fy > 0 else "tilt_up", intensity
+
+
+def _analyze_movements(video_path: Path, shots: list[ShotBoundary]) -> None:
+    """对每个 shot 的首尾帧算光流，填充 movement/intensity。失败时静默降级为 static/low。"""
+    try:
+        import cv2  # noqa: PLC0415 - opencv-python-headless 已在 worker requirements 中
+
+    except Exception as exc:  # noqa: BLE001
+        logger.warning("OpenCV 不可用，运镜检测降级为 static/low: %s", exc)
+        return
+    try:
+        cap = cv2.VideoCapture(str(video_path))
+        for shot in shots:
+            mid_t = (shot.start_sec + shot.end_sec) / 2.0
+            dt = max(0.2, min(0.5, (shot.end_sec - shot.start_sec) / 4.0))
+            cap.set(cv2.CAP_PROP_POS_MSEC, max(0.0, (mid_t - dt)) * 1000)
+            ok1, f1 = cap.read()
+            cap.set(cv2.CAP_PROP_POS_MSEC, min(mid_t + dt, shot.end_sec - 0.05) * 1000)
+            ok2, f2 = cap.read()
+            if not (ok1 and ok2):
+                continue
+            g1 = cv2.cvtColor(f1, cv2.COLOR_BGR2GRAY)
+            g2 = cv2.cvtColor(f2, cv2.COLOR_BGR2GRAY)
+            h, w = g1.shape
+            # 降采样加速
+            scale = 360.0 / h if h > 360 else 1.0
+            if scale < 1.0:
+                g1 = cv2.resize(g1, (int(w * scale), int(h * scale)))
+                g2 = cv2.resize(g2, (int(w * scale), int(h * scale)))
+            flow = cv2.calcOpticalFlowFarneback(g1, g2, None, **FARNEBACK_PARAMS)
+            move, inten = _detect_camera_movement(flow, g1.shape[1], g1.shape[0])
+            shot.movement = move
+            shot.intensity = inten
+        cap.release()
+    except Exception as exc:  # noqa: BLE001
+        logger.warning("运镜检测异常，已降级: %s", exc)
+
+
+# ── ④ librosa BPM ────────────────────────────────────────────────────────
+
+
+def _detect_bpm(video_path: Path) -> int:
+    """提取音轨并估算 BPM；失败返回 0。"""
+    tmp_wav: Optional[Path] = None
+    try:
+        import librosa  # noqa: PLC0415
+
+        tmp_wav = Path(tempfile.mkstemp(suffix=".wav")[1])
+        # ffmpeg 抽 22050Hz 单声道 wav
+        subprocess.run(
+            [_ffmpeg_bin(), "-y", "-i", str(video_path), "-vn", "-ac", "1", "-ar", "22050", "-f", "wav", str(tmp_wav)],
+            stdout=subprocess.DEVNULL,
+            stderr=subprocess.DEVNULL,
+            timeout=20,
+            check=False,
+        )  # nosec B603
+        if not tmp_wav.exists() or tmp_wav.stat().st_size < 1024:
+            return 0
+        y, sr = librosa.load(str(tmp_wav), sr=22050, mono=True)
+        if len(y) < sr * 2:
+            return 0
+        tempo, _ = librosa.beat.beat_track(y=y, sr=sr)
+        try:
+            bpm = int(round(float(tempo)))
+        except Exception:  # noqa: BLE001
+            bpm = int(round(float(tempo[0]))) if len(tempo) else 0
+        return max(40, min(bpm, 220))
+    except Exception as exc:  # noqa: BLE001
+        logger.warning("librosa BPM 分析失败: %s", exc)
+        return 0
+    finally:
+        if tmp_wav and tmp_wav.exists():
+            try:
+                tmp_wav.unlink()
+            except OSError:
+                pass
+
+
+def _pace_from_bpm(bpm: int) -> str:
+    if bpm >= 110:
+        return "fast_cut"
+    if bpm >= 80:
+        return "medium"
+    if bpm > 0:
+        return "slow_cinematic"
+    return "medium"
+
+
+# ── ⑤ VLM 帧分析 ─────────────────────────────────────────────────────────
+
+
+def _sample_frames(frame_paths: list[Path], shots: list[ShotBoundary], k: int = VLM_SAMPLE_FRAMES) -> list[Path]:
+    """从全量帧中均匀选 k 张代表性帧（优先场景帧）。"""
+    if not frame_paths:
+        return []
+    scene_frames = sorted(p for p in frame_paths if p.name.startswith("scene_"))
+    fixed_frames = sorted(p for p in frame_paths if p.name.startswith("f_"))
+    picks: list[Path] = list(scene_frames[: max(1, k // 2)])
+    remaining = k - len(picks)
+    if remaining > 0 and fixed_frames:
+        step = max(1, len(fixed_frames) // remaining)
+        picks += fixed_frames[::step][:remaining]
+    # 去重保持顺序
+    seen: set[str] = set()
+    uniq: list[Path] = []
+    for p in picks:
+        if p.name not in seen and p.exists():
+            seen.add(p.name)
+            uniq.append(p)
+    return uniq[:k]
+
+
+def _upload_frames_to_oss(frame_paths: list[Path]) -> list[str]:
+    """把帧上传 OSS，返回公网 URL 列表。失败时降级为 data URI。"""
+    urls: list[str] = []
+    try:
+        from video_processing.oss_helpers import upload_to_oss
+
+        for p in frame_paths:
+            try:
+                key = f"viral-video/analysis/{uuid.uuid4().hex}/{p.name}"
+                url = upload_to_oss(p, key)
+                if url:
+                    urls.append(url)
+            except Exception as exc:  # noqa: BLE001
+                logger.warning("单帧 OSS 上传失败 %s: %s", p.name, exc)
+    except Exception as exc:  # noqa: BLE001
+        logger.warning("OSS 上传模块不可用，降级为 base64 data URI: %s", exc)
+    if len(urls) < len(frame_paths):
+        # 降级：base64 data URI（小图，单张 ≤100KB 才走此路）
+        import base64
+
+        for p in frame_paths[len(urls) :]:
+            try:
+                if p.stat().st_size > 120_000:
+                    continue
+                b64 = base64.b64encode(p.read_bytes()).decode("ascii")
+                urls.append(f"data:image/jpeg;base64,{b64}")
+            except Exception:  # noqa: BLE001  # nosec B112
+                continue
+    return urls
+
+
+def _vlm_analyze_frames(image_urls: list[str]) -> dict[str, Any]:
+    """调豆包 VLM 分析色调/构图/光线/转场观感。"""
+    if not image_urls:
+        return {}
+    try:
+        from packages.shared.ai_client import get_doubao_client
+
+        client = get_doubao_client()
+        if not client.is_available:
+            raise RuntimeError("豆包客户端未配置")
+        sys_prompt = (
+            "你是资深短视频导演和调色师。根据用户给出的同一支短视频的多张关键帧，"
+            "分析其视觉风格并严格输出 JSON（不要 markdown，不要解释）：\n"
+            "{"
+            '"color_palette": ["#主色1","#主色2","#主色3","#辅色","#点缀色"],'
+            '"color_tone": "warm|cool|high_sat|low_sat|vintage|fresh|dramatic|bright",'
+            '"color_filter": "none|warm_vintage|cool_fresh|high_contrast|soft_pastel|dramatic_cinematic",'
+            '"lighting": "natural|studio|backlit|soft|dramatic|bright_even",'
+            '"composition": {"closeup_ratio":0.0,"medium_ratio":0.0,"wide_ratio":0.0,'
+            '"angle":"eye_level|low_angle|high_angle|dutch"},'
+            '"mood": "整体情绪（1-4字）",'
+            '"visual_keywords": ["3-5个视觉关键词"],'
+            '"transitions_observed": ["hard_cut|cross_dissolve|zoom_whip|fade_black"],'
+            '"pace_guess": "fast_cut|medium|slow_cinematic"'
+            "}"
+        )
+        raw = client.vision_completion(
+            messages=[
+                {"role": "system", "content": sys_prompt},
+                {"role": "user", "content": "请分析这支参考视频的风格。"},
+            ],
+            images=image_urls,
+            temperature=0.2,
+            max_tokens=2048,
+        )
+        if not raw:
+            return {}
+        raw = _strip_code_fence(raw)
+        # 容忍模型可能前后加文本
+        i, j = raw.find("{"), raw.rfind("}")
+        if i >= 0 and j > i:
+            return json.loads(raw[i : j + 1])
+        return {}
+    except Exception as exc:  # noqa: BLE001
+        logger.warning("VLM 帧分析失败: %s", exc)
+        return {}
+
+
+# ── ⑥ LLM 整合 style_guide ──────────────────────────────────────────────
+
+
+def _llm_synthesize(
+    shots: list[ShotBoundary],
+    bpm: int,
+    vlm: dict[str, Any],
+    style_strength: str,
+) -> dict[str, Any]:
+    """把结构化信号整合成 style_guide；LLM 不可用时走规则合成。"""
+    payload = {
+        "style_strength": style_strength,
+        "shot_count": len(shots),
+        "shots": [
+            {
+                "index": s.index,
+                "start_sec": round(s.start_sec, 2),
+                "end_sec": round(s.end_sec, 2),
+                "movement": s.movement,
+                "intensity": s.intensity,
+                "transition": s.transition,
+            }
+            for s in shots
+        ],
+        "bpm": bpm,
+        "pace_guess": _pace_from_bpm(bpm),
+        "vlm": vlm,
+    }
+    try:
+        from packages.shared.ai_client import get_doubao_client
+
+        client = get_doubao_client()
+        if not client.is_available:
+            raise RuntimeError("豆包客户端未配置")
+        sys_prompt = (
+            "你是资深短视频导演。根据参考视频的结构化分析数据（镜头分割/运镜/BPM/关键帧VLM描述），"
+            "整合输出一份 style_guide JSON，字段必须包含："
+            "style_name,avg_shot_duration,shot_count,pace,bpm,camera_movements,transitions,"
+            "color_palette,color_tone,color_filter,composition,lighting,mood,visual_keywords,"
+            "ken_burns_direction_hint,ken_burns_params,transition_map,video_filter_eq_params。"
+            "严格输出一个合法 JSON 对象，不要 markdown/解释。"
+        )
+        user_text = "分析数据：\n" + json.dumps(payload, ensure_ascii=False)
+        raw = client.chat_completion(
+            [{"role": "system", "content": sys_prompt}, {"role": "user", "content": user_text}],
+            temperature=0.3,
+            max_tokens=4096,
+        )
+        if raw:
+            raw = _strip_code_fence(raw)
+            i, j = raw.find("{"), raw.rfind("}")
+            if i >= 0 and j > i:
+                result = json.loads(raw[i : j + 1])
+                if isinstance(result, dict) and result.get("style_name"):
+                    return result
+    except Exception as exc:  # noqa: BLE001
+        logger.warning("LLM 合成 style_guide 失败，走规则降级: %s", exc)
+    return _rule_based_style_guide(shots, bpm, vlm)
+
+
+def _rule_based_style_guide(shots: list[ShotBoundary], bpm: int, vlm: dict[str, Any]) -> dict[str, Any]:
+    """LLM 不可用时，用规则拼出可用 style_guide。"""
+    durations = [s.end_sec - s.start_sec for s in shots] or [3.0]
+    avg_dur = round(sum(durations) / len(durations), 2)
+    pace = _pace_from_bpm(bpm)
+    movements = []
+    for s in shots:
+        movements.append(
+            {
+                "shot_index": s.index + 1,
+                "movement": s.movement,
+                "intensity": s.intensity,
+                "duration": round(s.end_sec - s.start_sec, 2),
+                "subject_hint": _default_subject_hint(s.movement),
+            }
+        )
+    transitions = []
+    for i in range(len(shots) - 1):
+        transitions.append({"between_shot": [i + 1, i + 2], "type": shots[i].transition})
+    color_palette = vlm.get("color_palette") or ["#E0E0E0", "#333333", "#F5F5F5", "#888888", "#FF6B35"]
+    color_tone = vlm.get("color_tone") or "bright"
+    color_filter = vlm.get("color_filter") or "none"
+    lighting = vlm.get("lighting") or "bright_even"
+    composition = vlm.get("composition") or {
+        "closeup_ratio": 0.4,
+        "medium_ratio": 0.4,
+        "wide_ratio": 0.2,
+        "angle": "eye_level",
+    }
+    mood = vlm.get("mood") or "明快"
+    vk = vlm.get("visual_keywords") or ["节奏明快", "清晰", "真实"]
+    dominant = _dominant_movement(shots)
+    default_kb = map_camera_to_ken_burns(dominant)
+    # 每镜头独立 ken_burns 参数（key 为 shot_index 字符串）+ 默认值
+    kb_params: dict[str, Any] = {"default": default_kb}
+    for m in movements:
+        kb_params[str(m["shot_index"])] = map_camera_to_ken_burns(m["movement"])
+    trans_map = _build_transition_map(transitions)
+    eq_params = map_color_to_video_filter(color_filter)
+    direction_hint = {
+        "push_in": "zoom_in_slow",
+        "zoom_in": "zoom_in_medium",
+        "pull_out": "zoom_out_slow",
+        "zoom_out": "zoom_out_medium",
+        "pan_left": "pan_left_slow",
+        "pan_right": "pan_right_slow",
+        "tilt_up": "diagonal_push",
+        "tilt_down": "diagonal_push",
+        "track_left": "pan_left_slow",
+        "track_right": "pan_right_slow",
+        "static": "static",
+    }.get(dominant, "static")
+    return {
+        "style_name": f"{pace}节奏-{color_tone}色调",
+        "avg_shot_duration": avg_dur,
+        "shot_count": len(shots),
+        "pace": pace,
+        "bpm": bpm or (120 if pace == "fast_cut" else 90 if pace == "medium" else 70),
+        "camera_movements": movements,
+        "transitions": transitions,
+        "color_palette": color_palette,
+        "color_tone": color_tone,
+        "color_filter": color_filter,
+        "composition": composition,
+        "lighting": lighting,
+        "mood": mood,
+        "visual_keywords": vk,
+        "ken_burns_direction_hint": direction_hint,
+        "ken_burns_params": kb_params,
+        "transition_map": trans_map,
+        "video_filter_eq_params": eq_params,
+    }
+
+
+def _default_subject_hint(movement: str) -> str:
+    return {
+        "push_in": "产品特写或细节展示",
+        "pull_out": "从细节拉到全景环境",
+        "zoom_in": "产品细节放大",
+        "zoom_out": "全景交代",
+        "pan_left": "横向展示环境/产品线",
+        "pan_right": "横向展示环境/产品线",
+        "tilt_up": "从细节抬到整体/人物表情",
+        "tilt_down": "从整体俯冲到产品细节",
+        "track_left": "跟拍/横向移动",
+        "track_right": "跟拍/横向移动",
+        "static": "稳定构图画面",
+    }.get(movement, "产品展示")
+
+
+def _dominant_movement(shots: list[ShotBoundary]) -> str:
+    if not shots:
+        return "static"
+    counts: dict[str, int] = {}
+    for s in shots:
+        counts[s.movement] = counts.get(s.movement, 0) + 1
+    return max(counts, key=counts.get)
+
+
+def _build_transition_map(transitions: list[dict[str, Any]]) -> dict[str, str]:
+    """统计转场类型分布，返回 shot_index→transition 类型映射（字符串键）。"""
+    m: dict[str, str] = {}
+    for t in transitions:
+        pair = t.get("between_shot") or [0, 0]
+        if len(pair) >= 2:
+            m[f"{pair[0]}-{pair[1]}"] = t.get("type", "hard_cut")
+    return m
+
+
+# ── ③' 色调/滤镜预设（FFmpeg eq + colorchannelmixer 参数） ──────────────
+
+#: color_filter → FFmpeg 滤镜参数字典（直接可拼到 eq=.../colorchannelmixer=...）
+COLOR_FILTER_PRESETS: dict[str, dict[str, Any]] = {
+    "none": {},
+    "warm_vintage": {
+        "eq": {"brightness": 0.02, "contrast": 1.05, "saturation": 0.9, "gamma": 1.05},
+        "colorchannelmixer": {"rr": 1.1, "gg": 0.98, "bb": 0.82, "ra": 0, "ga": 0, "ba": 0, "aa": 1},
+    },
+    "cool_fresh": {
+        "eq": {"brightness": 0.03, "contrast": 1.08, "saturation": 1.05},
+        "colorchannelmixer": {"rr": 0.9, "gg": 1.0, "bb": 1.12, "ra": 0, "ga": 0, "ba": 0, "aa": 1},
+    },
+    "high_contrast": {
+        "eq": {"brightness": 0.0, "contrast": 1.3, "saturation": 1.2},
+        "colorchannelmixer": {},
+    },
+    "soft_pastel": {
+        "eq": {"brightness": 0.05, "contrast": 0.92, "saturation": 0.85},
+        "colorchannelmixer": {"rr": 1.05, "gg": 1.03, "bb": 1.05, "ra": 0, "ga": 0, "ba": 0, "aa": 1},
+    },
+    "dramatic_cinematic": {
+        "eq": {"brightness": -0.03, "contrast": 1.2, "saturation": 0.85},
+        "colorchannelmixer": {"rr": 1.05, "gg": 0.98, "bb": 0.9, "ra": 0, "ga": 0, "ba": 0, "aa": 1},
+    },
+}
+
+
+def map_color_to_video_filter(color_filter: str) -> dict[str, Any]:
+    """color_filter 枚举 → FFmpeg eq/colorchannelmixer 参数字典（渲染端直接使用）。"""
+    preset = COLOR_FILTER_PRESETS.get(color_filter) or COLOR_FILTER_PRESETS["none"]
+    # 返回深拷贝防污染
+    return json.loads(json.dumps(preset))
+
+
+# ── ③'' 运镜 → ken_burns 参数映射 ───────────────────────────────────────
+
+#: 运镜类型 → URS 可直接消费的 ken_burns 参数字典
+CAMERA_TO_KEN_BURNS: dict[str, dict[str, Any]] = {
+    "static": {
+        "type": "static",
+        "zoom_start": 1.0,
+        "zoom_end": 1.0,
+        "pan_x": 0.0,
+        "pan_y": 0.0,
+        "duration_factor": 1.0,
+    },
+    "push_in": {
+        "type": "zoom",
+        "zoom_start": 1.0,
+        "zoom_end": 1.12,
+        "pan_x": 0.0,
+        "pan_y": 0.0,
+        "duration_factor": 1.0,
+    },
+    "zoom_in": {
+        "type": "zoom",
+        "zoom_start": 1.0,
+        "zoom_end": 1.18,
+        "pan_x": 0.0,
+        "pan_y": 0.0,
+        "duration_factor": 1.0,
+    },
+    "pull_out": {
+        "type": "zoom",
+        "zoom_start": 1.12,
+        "zoom_end": 1.0,
+        "pan_x": 0.0,
+        "pan_y": 0.0,
+        "duration_factor": 1.0,
+    },
+    "zoom_out": {
+        "type": "zoom",
+        "zoom_start": 1.18,
+        "zoom_end": 1.0,
+        "pan_x": 0.0,
+        "pan_y": 0.0,
+        "duration_factor": 1.0,
+    },
+    "pan_left": {
+        "type": "pan",
+        "zoom_start": 1.05,
+        "zoom_end": 1.05,
+        "pan_x": -0.08,
+        "pan_y": 0.0,
+        "duration_factor": 1.0,
+    },
+    "pan_right": {
+        "type": "pan",
+        "zoom_start": 1.05,
+        "zoom_end": 1.05,
+        "pan_x": 0.08,
+        "pan_y": 0.0,
+        "duration_factor": 1.0,
+    },
+    "tilt_up": {
+        "type": "pan+zoom",
+        "zoom_start": 1.08,
+        "zoom_end": 1.14,
+        "pan_x": 0.0,
+        "pan_y": -0.05,
+        "duration_factor": 1.0,
+    },
+    "tilt_down": {
+        "type": "pan+zoom",
+        "zoom_start": 1.14,
+        "zoom_end": 1.08,
+        "pan_x": 0.0,
+        "pan_y": 0.05,
+        "duration_factor": 1.0,
+    },
+    "track_left": {
+        "type": "pan",
+        "zoom_start": 1.05,
+        "zoom_end": 1.05,
+        "pan_x": -0.10,
+        "pan_y": 0.0,
+        "duration_factor": 1.0,
+    },
+    "track_right": {
+        "type": "pan",
+        "zoom_start": 1.05,
+        "zoom_end": 1.05,
+        "pan_x": 0.10,
+        "pan_y": 0.0,
+        "duration_factor": 1.0,
+    },
+}
+
+
+def map_camera_to_ken_burns(movement: str) -> dict[str, Any]:
+    """运镜类型 → URS ken_burns 参数字典。未知类型回退 static。"""
+    preset = CAMERA_TO_KEN_BURNS.get(movement) or CAMERA_TO_KEN_BURNS["static"]
+    return json.loads(json.dumps(preset))
+
+
+# ── 转场 → xfade transition 名称 ────────────────────────────────────────
+
+TRANSITION_TO_XFADE: dict[str, str] = {
+    "hard_cut": "cut",
+    "cross_dissolve": "dissolve",
+    "fade_black": "fadeblack",
+    "fade": "fade",
+    "zoom_whip": "zoom",
+    "slide_left": "slideright",  # 画面左移 = 新画面从右滑入
+    "slide_right": "slideleft",
+    "wipe_left": "wipeleft",
+    "wipe_right": "wiperight",
+}
+
+
+def map_transition_to_xfade(transition_type: str) -> str:
+    """转场枚举 → TransitionEngine 支持的 xfade 名称；未知回退 cut。"""
+    return TRANSITION_TO_XFADE.get(transition_type, "cut")
+
+
+# ── BPM → BGM 推荐 BPM ──────────────────────────────────────────────────
+
+
+def map_bgm_bpm(bpm: int) -> int:
+    """BGM 选曲 BPM：参考视频 BPM ±5。bpm=0 返回 90（默认 medium）。"""
+    if bpm <= 0:
+        return 90
+    return max(60, min(bpm, 180))
+
+
+# ── 单 clip 渲染参数聚合（给 URS build_render_plan 使用） ───────────────
+
+
+def build_render_params_for_clip(
+    clip_index: int,
+    style_guide: dict[str, Any],
+    *,
+    duration_sec: Optional[float] = None,
+) -> dict[str, Any]:
+    """根据 style_guide 为第 clip_index 个 clip 生成可直接喂给 URS 的渲染参数。"""
+    shot_idx = clip_index + 1
+    movements = style_guide.get("camera_movements") or []
+    movement = "static"
+    intensity = "low"
+    for m in movements:
+        if m.get("shot_index") == shot_idx:
+            movement = m.get("movement", "static")
+            intensity = m.get("intensity", "low")
+            break
+    ken = map_camera_to_ken_burns(movement)
+    if intensity == "high":
+        ken["zoom_end"] = round(ken.get("zoom_end", 1.0) * 1.08, 3)
+        for k in ("pan_x", "pan_y"):
+            ken[k] = round(ken.get(k, 0.0) * 1.3, 3)
+    elif intensity == "low":
+        for k in ("pan_x", "pan_y"):
+            ken[k] = round(ken.get(k, 0.0) * 0.6, 3)
+    transitions = style_guide.get("transitions") or []
+    trans_type = "hard_cut"
+    for t in transitions:
+        pair = t.get("between_shot") or []
+        if len(pair) >= 2 and pair[0] == shot_idx:
+            trans_type = t.get("type", "hard_cut")
+            break
+    xfade = map_transition_to_xfade(trans_type)
+    eq = map_color_to_video_filter(style_guide.get("color_filter", "none"))
+    return {
+        "ken_burns": ken,
+        "transition": {"type": xfade, "duration": 0.3 if xfade != "cut" else 0.0},
+        "video_filter": eq,
+        "bgm_bpm_hint": map_bgm_bpm(int(style_guide.get("bpm") or 0)),
+        "duration_sec": duration_sec,
+    }
+
+
+# ── 素材本地化（URL/OSS key → 本地临时文件） ────────────────────────────
+
+
+def _ensure_local_video(reference: str, work_dir: Path) -> Optional[Path]:
+    """把 reference（URL/OSS key/本地路径）落到 work_dir 下的本地文件。"""
+    p = Path(reference)
+    if p.exists() and p.is_file():
+        return p
+    try:
+        from video_processing.oss_helpers import download_asset
+
+        target = work_dir / f"ref_{uuid.uuid4().hex}.mp4"
+        ok = download_asset(reference, target)
+        if ok and target.exists() and target.stat().st_size > 0:
+            return target
+    except Exception as exc:  # noqa: BLE001
+        logger.warning("download_asset 失败，尝试 http 直连: %s", exc)
+    if reference.startswith(("http://", "https://")):
+        try:
+            import httpx  # noqa: PLC0415 - 项目依赖，延迟导入
+
+            target = work_dir / f"ref_{uuid.uuid4().hex}.mp4"
+            with httpx.Client(timeout=20.0, follow_redirects=True) as client:
+                with client.stream("GET", reference) as resp:
+                    resp.raise_for_status()
+                    with open(target, "wb") as f:
+                        for chunk in resp.iter_bytes(chunk_size=64 * 1024):
+                            f.write(chunk)
+            if target.exists() and target.stat().st_size > 0:
+                return target
+        except Exception as exc:  # noqa: BLE001
+            logger.warning("HTTP 下载参考视频失败: %s", exc)
+    return None
+
+
+# ── 入口 ─────────────────────────────────────────────────────────────────
+
+
+def analyze_video_style(
+    reference_video_path: str | Path,
+    style_strength: str = "medium",
+    *,
+    timeout_sec: int = DEFAULT_ANALYSIS_TIMEOUT,
+) -> dict[str, Any]:
+    """分析参考视频风格，返回 style_guide dict。
+
+    Args:
+        reference_video_path: 本地路径、HTTP(S) URL 或 OSS storage key。
+        style_strength: light | medium | strict。
+        timeout_sec: 单步超时（秒），默认 60。
+
+    Returns:
+        style_guide dict，详见 STYLE_GUIDE_SCHEMA。任何子步骤失败都会降级，不抛异常。
+    """
+    style_strength = style_strength if style_strength in ("light", "medium", "strict") else "medium"
+    frames_dir: Optional[Path] = None
+    local_path: Optional[Path] = None
+    try:
+        frames_dir = Path(tempfile.mkdtemp(prefix="vstyle_"))
+        work_dir = frames_dir  # 同一临时根
+        local_path = _ensure_local_video(str(reference_video_path), work_dir)
+        if local_path is None:
+            logger.error("[video_analyzer] 无法获取参考视频: %s", reference_video_path)
+            return _rule_based_style_guide([], 0, {})
+        # 资源约束：大小 / 时长
+        try:
+            size_mb = local_path.stat().st_size / (1024 * 1024)
+            if size_mb > MAX_REFERENCE_SIZE_MB:
+                logger.warning(
+                    "[video_analyzer] 参考视频 %.1fMB 超上限，按前 %ds 分析", size_mb, MAX_REFERENCE_DURATION_SEC
+                )
+        except OSError:
+            pass
+        duration = _probe_duration(local_path)
+        if duration > MAX_REFERENCE_DURATION_SEC:
+            duration = MAX_REFERENCE_DURATION_SEC
+        # ① 抽帧
+        try:
+            frame_paths = _extract_keyframes(local_path, frames_dir / "frames")
+        except Exception as exc:  # noqa: BLE001
+            logger.warning("FFmpeg 抽帧失败: %s，降级为 VLM 均匀采样", exc)
+            frame_paths = []
+        # ② 镜头分割
+        shots = _detect_shots(local_path, frames_dir)
+        # ③ 运镜检测（有帧才跑）
+        if frame_paths or shots:
+            _analyze_movements(local_path, shots)
+        # ④ BPM
+        bpm = _detect_bpm(local_path)
+        # ⑤ 选帧→OSS→VLM
+        sampled = _sample_frames(frame_paths, shots)
+        image_urls = _upload_frames_to_oss(sampled) if sampled else []
+        vlm = _vlm_analyze_frames(image_urls) if image_urls else {}
+        # ⑥ 合成
+        style_guide = _llm_synthesize(shots, bpm, vlm, style_strength)
+        # 兜底字段校验
+        style_guide.setdefault("style_strength", style_strength)
+        style_guide.setdefault("pace", _pace_from_bpm(bpm))
+        style_guide.setdefault("bpm", bpm)
+        style_guide.setdefault("shot_count", len(shots))
+        if shots and "avg_shot_duration" not in style_guide:
+            durs = [s.end_sec - s.start_sec for s in shots]
+            style_guide["avg_shot_duration"] = round(sum(durs) / len(durs), 2)
+        return style_guide
+    except Exception as exc:  # noqa: BLE001
+        logger.exception("[video_analyzer] 整体分析异常，返回最小占位 style_guide: %s", exc)
+        return _rule_based_style_guide([], 0, {"mood": "未知"})
+    finally:
+        # 临时帧清理
+        if frames_dir and frames_dir.exists():
+            shutil.rmtree(frames_dir, ignore_errors=True)

apps/worker/worker_app/celery_app.py

@@ -38,6 +38,7 @@ celery_app.conf.imports = (
     "worker_app.tasks.voice_extraction",
     "worker_app.tasks.voice_clone",
     "worker_app.tasks.tts_synthesis",
+    "worker_app.tasks.viral_video",  # #2039 爆款视频编排器（10步流水线）
     "worker_app.tasks.batch_download",
     "worker_app.tasks.duplication_check",
     # #1798 AI 数字人渲染：必须在 Worker 实例上注册同名任务，否则消息无人消费（渲染卡 0%）

apps/worker/worker_app/tasks/asset_quality_scoring_task.py

@@ -18,6 +18,7 @@ from worker_app.celery_app import celery_app
 from worker_app.db import SessionLocal
 
 from packages.adapters.sqlalchemy_impl.asset_repository import SQLAlchemyAssetRepository
+from packages.domain.classification import ClassificationStatus
 from packages.shared.storage import get_shared_storage_service
 
 logger = get_task_logger(__name__)
@@ -96,7 +97,7 @@ def calculate_asset_quality_task(self, asset_id: str) -> dict:
                     confidence = 1.0
                 existing_meta["classification"] = classification
                 existing_meta["classification_confidence"] = confidence
-                asset.classification_status = "completed"
+                asset.classification_status = ClassificationStatus.COMPLETED
                 asset.metadata = existing_meta
                 logger.info(
                     "[quality_score] asset=%s 自动分类完成: category=%s confidence=%.2f",
@@ -110,6 +111,8 @@ def calculate_asset_quality_task(self, asset_id: str) -> dict:
                     asset_id,
                     cls_err,
                 )
+                # 分类失败显式标记 FAILED，避免停留在 PENDING 被反复重试
+                asset.classification_status = ClassificationStatus.FAILED
 
         asset_repo.update(asset)
         db.commit()

apps/worker/worker_app/tasks/generation.py

@@ -198,7 +198,7 @@ def _verify_url_accessible(
     retries: int = 2,
     max_redirects: int = 5,
 ) -> bool:
-    """HEAD 请求校验 URL 可访问（含重试，防止 OSS 抖动误报）。
+    """GET+Range 请求校验 URL 可访问（含重试，防止 OSS 抖动误报）。
 
     安全增强：
     - 请求前先做 SSRF 安全校验（内网IP/回环地址/链路本地地址等）
@@ -255,11 +255,12 @@ def _verify_url_accessible(
                 )
                 raise
 
-            req = urllib.request.Request(safe_url, method="HEAD")
+            req = urllib.request.Request(safe_url, method="GET")
+            req.add_header("Range", "bytes=0-0")
             req.add_header("User-Agent", "xiaoxia-saas-worker/1.0")
 
             with opener.open(req, timeout=timeout) as resp:  # noqa: S310
-                if 200 <= resp.status < 300:
+                if 200 <= resp.status < 300 or resp.status == 206:
                     return True
                 if resp.status in (301, 302, 303, 307, 308):
                     location = resp.headers.get("Location", "")
@@ -615,69 +616,49 @@ def _precompute_render_metadata(
 # ── Celery Task ──────────────────────────────────────────────────────────────
 
 
-def _sync_task_config_to_plan(source_edit_plan_id: str, task_info: dict, db) -> str | None:
-    """将 GenerationTask 的配置同步到 EditPlan.config，返回配音本地路径（如果有）。
+def _build_task_config_override(task_info: dict) -> dict:
+    """Bug A: 从 task_info 构建任务级 config override 深拷贝，供渲染时覆盖 plan.config。
 
-    包括：title_config、BGM、输出分辨率。配音单独处理（需下载到本地）。
+    所有渲染相关配置（title/bgm/export）从任务自身读取，不再依赖共享 plan.config，
+    彻底消除同 plan 多任务并发渲染时的竞态覆盖问题。
     """
-    from packages.adapters.sqlalchemy_impl.edit_plan_repository import (
-        SQLAlchemyEditPlanRepository,
-    )
+    import copy
 
-    plan_repo = SQLAlchemyEditPlanRepository(db)
-    plan = plan_repo.get(source_edit_plan_id)
-    if plan is None:
-        logger.error("[task] EditPlan not found: %s", source_edit_plan_id)
-        return None
+    override: dict = {}
 
-    plan_config = dict(plan.config or {})
-    changed = False
-
-    # 标题配置
+    # 标题配置（字段名归一化）
     title_config = task_info.get("title_config") or {}
-    if title_config and isinstance(title_config, dict) and title_config.get("text", "").strip():
-        cfg = dict(title_config)
-        # 字段名归一化
+    if isinstance(title_config, dict) and title_config:
+        cfg = copy.deepcopy(title_config)
         if "font_size" in cfg and "size" not in cfg:
             cfg["size"] = cfg["font_size"]
         if "font_color" in cfg and "color" not in cfg:
             cfg["color"] = cfg["font_color"]
-        plan_config["title"] = cfg
-        changed = True
-        logger.info("[task] title_config synced to plan: %s", cfg.get("text", "")[:30])
+        override["title"] = cfg
 
     # BGM 配置
     bgm_config = task_info.get("bgm_config") or {}
-    if bgm_config:
-        from packages.domain.bgm_utils import merge_bgm_config
-
-        existing_bgm = plan_config.get("bgm", {}) or {}
-        plan_config["bgm"] = merge_bgm_config(existing_bgm, bgm_config)
-        changed = True
+    if isinstance(bgm_config, dict) and bgm_config:
+        override["bgm"] = copy.deepcopy(bgm_config)
 
     # 输出分辨率
     ow = task_info.get("output_width") or OUTPUT_WIDTH
     oh = task_info.get("output_height") or OUTPUT_HEIGHT
     if ow >= 100 and oh >= 100:
-        export_cfg = dict(plan_config.get("export", {}) or {})
-        export_cfg["resolution"] = f"{ow}x{oh}"
-        plan_config["export"] = export_cfg
-        changed = True
+        override["export"] = {"resolution": f"{ow}x{oh}"}
 
-    if changed:
-        plan.config = plan_config
-        plan_repo.update(plan)
-        logger.info("[task] plan.config synced: plan_id=%s", source_edit_plan_id)
+    return override
+
+
+def _download_voice_for_task(task_info: dict, source_edit_plan_id: str) -> str | None:
+    """下载任务配音到本地临时文件，返回路径（不读写 plan.config）。"""
+    import tempfile
 
-    # 配音下载
     voiceover_path: str | None = None
     voice_library_id = task_info.get("voice_library_id", "")
-    # #1749：voice_ids 冗余字段已移除；配音一律以 voice_library_id 为准（独立配音每变体各自绑定）
     effective_voice_id = voice_library_id or ""
 
     if effective_voice_id:
-        import tempfile
-
         voice_tmp = Path(tempfile.gettempdir()) / f"voice_{source_edit_plan_id}_{id(task_info)}.mp3"
         try:
             if _download_voice_asset(effective_voice_id, voice_tmp):
@@ -693,19 +674,24 @@ def _render_from_edit_plan(
     task_id: str,
     source_edit_plan_id: str,
     task_info: dict,
-) -> tuple[Path, float, list[dict] | None, str | None, str | None, str]:
+) -> tuple[Path, float, list[dict] | None, str | None, str | None, str, bool]:
     """从 EditPlan 数据库记录直接渲染（不再内存重建clips）。
 
+    Bug A 修复：不再通过 _sync_task_config_to_plan 写共享 plan.config；
+    渲染配置通过 task_config_override 参数直接传入渲染层，彻底消除并发竞态。
+
     Returns:
-        (output_path, render_duration, cover_candidates, voiceover_path, temp_dir, thumbnail_url)
+        (output_path, render_duration, cover_candidates, voiceover_path, temp_dir, thumbnail_url, edge_crop_applied)
     """
     from video_processing.render_adapter import RenderAdapter
     from worker_app.db import SessionLocal
 
     db = SessionLocal()
     try:
-        # 同步配置到 plan.config + 下载配音
-        voiceover_path = _sync_task_config_to_plan(source_edit_plan_id, task_info, db)
+        # Bug A: 构建任务级 config override（深拷贝自 task_info），不写 plan.config，避免并发竞态
+        task_override = _build_task_config_override(task_info)
+        # 下载配音到本地临时文件（不依赖 plan.config）
+        voiceover_path = _download_voice_for_task(task_info, source_edit_plan_id)
 
         # 进度回调
         def _progress_cb(progress: float, stage: str):
@@ -721,6 +707,7 @@ def _render_from_edit_plan(
             job_id=task_id,
             progress_cb=_progress_cb,
             voiceover_audio_path=voiceover_path,
+            task_config_override=task_override,
         )
 
         if not result.success:
@@ -746,6 +733,7 @@ def _render_from_edit_plan(
             voiceover_path,
             render_temp_dir,
             result.thumbnail_url or "",
+            bool(getattr(result, "edge_crop_applied", False)),
         )
     finally:
         db.close()
@@ -899,6 +887,7 @@ def generate_video(self, task_id: str) -> dict:
                         voiceover_tmp_path,
                         render_temp_dir,
                         thumbnail_url,
+                        _gpu_edge_crop_done,
                     ) = _render_from_edit_plan(
                         task_id=task_id,
                         source_edit_plan_id=current_plan_id,
@@ -935,6 +924,12 @@ def generate_video(self, task_id: str) -> dict:
                         if gen_task and render_attempt == 0:
                             gen_task.append_log("降重", "已关闭边缘裁剪与微变换（确定性渲染）")
                             _flush_logs(task_id, gen_task)
+                    elif _gpu_edge_crop_done:
+                        # GPU 直连管线已经在 filter_complex 中做了随机边缘裁剪，跳过 CPU 二次重编码
+                        if gen_task and render_attempt == 0:
+                            gen_task.append_log("边缘裁剪", "已在 GPU 直连管线内完成随机边缘裁剪")
+                            _flush_logs(task_id, gen_task)
+                        logger.info("[task_id=%s] GPU直连已完成边缘裁剪，跳过CPU二次重编码", task_id)
                     else:
                         from video_processing.ffmpeg_utils import random_edge_crop
 
@@ -1051,20 +1046,15 @@ def generate_video(self, task_id: str) -> dict:
                         )
                         if _meta_model:
                             meta = dict(_meta_model.extra_meta or {})
+                            # #2024/P0 finalize-400: 直接展开 _precompute_render_metadata 返回的
+                            # 完整 dict（含 file_url/fingerprint_dict/fingerprint_chunks/is_duplicate
+                            # /duplicate_of/...），避免手写字段白名单漏传字段导致 finalize 读不到数据。
                             meta["rendered_output"] = {
+                                **dict(rendered_output or {}),
+                                # file_url/duration 由外层调用方拿到的实际上传结果，优先覆盖预计算值
                                 "file_url": file_url,
                                 "file_size": file_size,
                                 "duration": duration,
-                                "width": rendered_output.get("width", 1280),
-                                "height": rendered_output.get("height", 720),
-                                "fps": rendered_output.get("fps", 25.0),
-                                "name": rendered_output.get("name", ""),
-                                "thumbnail_url": rendered_output.get("thumbnail_url", ""),
-                                "mode": rendered_output.get("mode", editing_mode.value),
-                                "fingerprint_dict": rendered_output.get("fingerprint_dict"),
-                                "batch_id": batch_id,
-                                "project_id": project_id,
-                                "user_id": user_id,
                             }
                             _meta_model.extra_meta = meta
                             _finalize_meta_session.commit()

deploy/configs/.env.staging

@@ -280,3 +280,18 @@ USE_GPU_LIPSYNC=true
 GPU_LIPSYNC_POLL_INTERVAL=5
 GPU_LIPSYNC_WAIT_TIMEOUT=1200
 GPU_WORKER_STALE_SECONDS=300
+
+# ==================== P4000 NVENC 硬件编码（GPU mezzanine relay）====================
+# 注意：这些值必须写死在模板里（不是 CI Secret），否则每次 CI 重新渲染 .env 都会被丢弃，
+# 导致 staging 发版后 GPU 编码静默降级到 CPU（P0 防复发）。
+ENABLE_GPU_ENCODE=true
+GPU_ENCODE_ENDPOINT=http://100.105.75.67:8900
+GPU_ENCODE_RELAY_BASE_URL=http://100.125.116.43:8092
+GPU_ENCODE_RELAY_INTERNAL_BASE_URL=http://xiaoxia-api-staging:8000
+GPU_ENCODE_RELAY_SECRET=0e1a8f0626438564a8b3fa92f3f2aac29e3c69bc02f2f85c
+GPU_ENCODE_VCODEC=h264_nvenc
+GPU_ENCODE_PRESET=p4
+GPU_ENCODE_CRF=23
+GPU_ENCODE_FALLBACK_CPU=true
+GPU_ENCODE_MEZZANINE_TRANSPORT=oss
+GPU_ENCODE_OSS_TMP_PREFIX=tmp/gpu-mezzanine/

deploy/configs/host-nginx-cms-staging.conf

@@ -0,0 +1,121 @@
+# Host nginx config for staging server: /etc/nginx/sites-available/05-xiaoxia-cms
+# Xiaoxia CMS - cms.xiaoxiajianji.com
+# 
+# 注意：此文件是宿主机 nginx 配置的备份/参考，不是 Docker 容器内的 nginx。
+# Docker 容器内的 nginx 配置见 nginx-staging.conf。
+#
+# GPU relay 路由说明：
+# P4000 编码完成后通过 http://100.69.73.60:8092/api/v1/internal/gpu-relay/{key} PUT 上传
+# Worker 容器通过 http://xiaoxia-api-staging:8000/api/v1/internal/gpu-relay/{key} GET 下载
+# 8092 端口由 CMS 宿主机 nginx 承载，GPU relay 路由通过最长前缀匹配优先代理到 staging API (8000)
+
+# 80 端口：ACME 验证 + 重定向到 HTTPS
+server {
+    listen 80;
+    server_name cms.xiaoxiajianji.com;
+
+    # Let's Encrypt ACME 验证
+    location /.well-known/acme-challenge/ {
+        root /var/www/certbot;
+    }
+
+    location / {
+        return 301 https://$host$request_uri;
+    }
+}
+
+# 443 端口：CMS 主站
+server {
+    listen 443 ssl http2;
+    server_name cms.xiaoxiajianji.com;
+
+    ssl_certificate /etc/letsencrypt/live/cms.xiaoxiajianji.com/fullchain.pem;
+    ssl_certificate_key /etc/letsencrypt/live/cms.xiaoxiajianji.com/privkey.pem;
+    include /etc/letsencrypt/options-ssl-nginx.conf;
+    ssl_dhparam /etc/letsencrypt/ssl-dhparams.pem;
+
+    client_max_body_size 50m;
+
+    # Security headers
+    add_header X-Content-Type-Options "nosniff" always;
+    add_header X-Frame-Options "SAMEORIGIN" always;
+    add_header X-XSS-Protection "1; mode=block" always;
+    add_header Referrer-Policy "strict-origin-when-cross-origin" always;
+    add_header Strict-Transport-Security "max-age=31536000; includeSubDomains" always;
+
+    root /data/www/cms/current;
+    index index.html;
+
+    gzip on;
+    gzip_types text/plain text/css application/json application/javascript text/xml application/xml application/xml+rss text/javascript image/svg+xml;
+    gzip_min_length 1024;
+
+    location / {
+        try_files $uri $uri/ /index.html;
+    }
+
+    location /api/ {
+        proxy_pass http://127.0.0.1:8091/api/;
+        proxy_http_version 1.1;
+        proxy_set_header Host $host;
+        proxy_set_header X-Real-IP $remote_addr;
+        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+        proxy_set_header X-Forwarded-Proto $scheme;
+    }
+
+    location = /health {
+        proxy_pass http://127.0.0.1:8091/health;
+    }
+}
+
+# 临时访问：8092 端口（IP直接访问，后续可关闭）
+server {
+    listen 8092;
+    server_name _;
+
+    root /data/www/cms/current;
+    index index.html;
+
+    client_max_body_size 50m;
+
+    add_header X-Content-Type-Options "nosniff" always;
+    add_header X-Frame-Options "SAMEORIGIN" always;
+    add_header X-XSS-Protection "1; mode=block" always;
+    add_header Referrer-Policy "strict-origin-when-cross-origin" always;
+    add_header Strict-Transport-Security "max-age=31536000; includeSubDomains" always;
+
+    gzip on;
+    gzip_types text/plain text/css application/json application/javascript text/xml application/xml application/xml+rss text/javascript image/svg+xml;
+    gzip_min_length 1024;
+
+    location / {
+        try_files $uri $uri/ /index.html;
+    }
+
+    # GPU relay endpoints - proxy to staging API (port 8000) instead of CMS
+    # 此 location 必须在 location /api/ 之前，利用 nginx 最长前缀匹配优先路由
+    location /api/v1/internal/gpu-relay/ {
+        proxy_pass http://127.0.0.1:8000/api/v1/internal/gpu-relay/;
+        proxy_http_version 1.1;
+        proxy_set_header Host $host;
+        proxy_set_header X-Real-IP $remote_addr;
+        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+        proxy_set_header X-Forwarded-Proto $scheme;
+        proxy_request_buffering off;
+        proxy_read_timeout 600s;
+        proxy_send_timeout 600s;
+    }
+
+    location /api/ {
+        proxy_pass http://127.0.0.1:8091/api/;
+        proxy_http_version 1.1;
+        proxy_set_header Host $host;
+        proxy_set_header X-Real-IP $remote_addr;
+        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+        proxy_set_header X-Forwarded-Proto $scheme;
+    }
+
+    location = /health {
+        proxy_pass http://127.0.0.1:8091/health;
+    }
+}

docs/DEPLOYMENT.md

@@ -104,6 +104,43 @@ 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。

docs/preset-bgm-upload.md

@@ -0,0 +1,30 @@
+# 预设 BGM 音频文件放置目录
+
+将下列 10 首免费可商用 BGM 的 mp3/m4a 文件按 `{preset_id}.mp3` 命名放到本目录：
+
+| preset_id         | 名称     | 风格     | 时长(s) | 标签                       |
+|-------------------|----------|----------|---------|----------------------------|
+| bgm_upbeat_001    | 阳光清晨 | upbeat   | 120     | 轻快 阳光 吉他 vlog         |
+| bgm_upbeat_002    | 活力节拍 | upbeat   | 95      | 轻快 电子 活力 运动         |
+| bgm_upbeat_003    | 夏日漫步 | upbeat   | 110     | 轻快 夏日 ukulele 旅行      |
+| bgm_relax_001     | 静谧时光 | relax    | 180     | 治愈 钢琴 安静 冥想         |
+| bgm_relax_002     | 雨后森林 | relax    | 150     | 治愈 自然 放松 环境音       |
+| bgm_relax_003     | 月光奏鸣曲 | relax  | 200     | 治愈 古典 钢琴 优雅（公版） |
+| bgm_tech_001      | 未来科技 | tech     | 85      | 科技 电子 未来感 数码       |
+| bgm_tech_002      | 数据脉冲 | tech     | 100     | 科技 极简 数据 AI           |
+| bgm_commerce_001  | 心动时刻 | commerce | 75      | 电商 时尚 动感 带货         |
+| bgm_commerce_002  | 品质生活 | commerce | 90      | 电商 高端 品牌 品质         |
+
+放好后执行（需要在有 OSS 凭证的机器上）：
+```bash
+export OSS_ENDPOINT=oss-cn-hangzhou.aliyuncs.com
+export OSS_ACCESS_KEY_ID=xxx
+export OSS_ACCESS_KEY_SECRET=xxx
+export OSS_BUCKET_NAME=xiaoxia-autocut
+python scripts/upload_preset_bgm.py
+```
+
+脚本会：
+1. 上传文件到 OSS `preset/bgm/<preset_id>.mp3`，设置公共读 ACL
+2. 自动改写 `packages/domain/preset_bgm.py` 把对应 `audio_url=""` 回填成公网 URL
+3. 提示 `git commit & push`

infra/docker/api.Dockerfile

@@ -30,6 +30,10 @@ 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
@@ -41,4 +45,4 @@ 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
-CMD ["uvicorn", "apps.api.main:app", "--host", "0.0.0.0", "--port", "8000"]
+ENTRYPOINT ["/usr/local/bin/entrypoint-api.sh"]

infra/docker/compose.yml

@@ -10,20 +10,25 @@
 #   API_IMAGE        - API 镜像名称 (默认: xiaoxia-saas-api:dev)
 #   WORKER_IMAGE     - Worker 镜像名称 (默认: xiaoxia-saas-worker:dev)
 #   WEB_IMAGE        - Web 镜像名称 (默认: xiaoxia-saas-web:dev)
-#   WEB_DOCKERFILE   - Web Dockerfile 路径
-#   WEB_NGINX_CONF   - Nginx 配置文件路径
 #   API_PORT         - API 端口映射 (staging: 8000, production: 8001)
 #   WEB_PORT         - Web 端口映射 (staging: 3001, production: 3002)
 #   GENERATED_FILES_HOST_DIR - 生成文件的主机目录
-#   WORKER_CONCURRENCY        - Worker 并发数 (默认: 4)
+#   GENERATION_CONCURRENCY    - Generation worker 并发（用户实时任务，默认 2）
+#   TRANSCODE_CONCURRENCY     - Transcode worker 并发（后台/转码/AI，默认 2）
 #   WORKER_MAX_TASKS_PER_CHILD - Worker 每个子进程最大任务数 (默认: 100)
+#   BEAT_ENABLED              - 容器内启动 celery beat（默认 1；独立 beat 容器部署设为 0）
+#   WORKER_CONCURRENCY        - 兼容旧变量：未显式设置上面两个并发时按此总数分配
 #
-# 重要: 
+# 重要:
 #   - 生产环境不要挂载 web-dist volume，否则会导致 403
 #   - 确保环境隔离网络已创建: docker network create xiaoxia-net-${ENV}
-#   - ENV=staging  → xiaoxia-net-staging
-#   - ENV=production → xiaoxia-net-production
+#   - ENV=staging  -> xiaoxia-net-staging
+#   - ENV=production -> xiaoxia-net-production
 #
+# #2073 队列分流：worker 容器内跑三个独立进程——beat(只发定时任务)、
+# generation worker(只消费 generation 队列，实时高优)、transcode worker(消费
+# transcode + celery 队列，后台任务)。beat 不再嵌入 generation worker，
+# 不占实时任务槽位；TRANSCODE_CONCURRENCY 独立伸缩，不再依赖 WORKER_CONCURRENCY 差值。
 
 # ===========================================
 # 日志轮转配置（所有服务共享）
@@ -40,53 +45,39 @@ services:
   # =========================================
   api:
     image: ${API_IMAGE:-xiaoxia-saas-api:dev}
-    # 不在生产环境构建镜像，使用预构建的镜像
-    # build:
-    #   context: ../..
-    #   dockerfile: infra/docker/api.Dockerfile
-    
     container_name: xiaoxia-api-${ENV:-staging}
     restart: unless-stopped
     stop_grace_period: 30s
     stop_signal: SIGTERM
-    
-    # 环境变量文件（包含数据库密码等敏感信息）
+
     env_file:
       - ../../.env
-    
+
     environment:
       APP_ENV: ${APP_ENV:-staging}
       GENERATED_FILES_DIR: /app/generated
       GENERATED_FILES_URL_PREFIX: /generated-files
       PUBLIC_API_BASE_URL: ${PUBLIC_API_BASE_URL:-https://api.xiaoxiajianji.com}
-    
-    # 端口映射
-    # Staging: 8000 -> 8000
-    # Production: 8001 -> 8000
+
     ports:
       - "127.0.0.1:${API_PORT:-8000}:8000"
-    
-    # 共享生成文件目录 + 抖音 cookies 等运行时配置
+
     volumes:
       - generated-files:/app/generated
       - ../../deploy/configs:/app/configs:ro
-    
+
     networks:
       - xiaoxia-net
-    
-    # 健康检查配置
+
     healthcheck:
       test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health', timeout=5)"]
       interval: 30s
       timeout: 10s
       retries: 3
       start_period: 40s
-    
+
     logging: *default-logging
 
-    # =========================================
-    # 资源限制建议（生产环境建议启用）
-    # =========================================
     deploy:
       resources:
         limits:
@@ -97,39 +88,48 @@ services:
           memory: 512M
 
   # =========================================
-  # Worker 服务（Celery 任务队列）
+  # Worker 服务（#2073 队列分流：beat + generation + transcode 同容器三进程）
   # =========================================
+  # 三个进程独立启动，任一退出则容器整体退出由 docker restart 拉起；
+  # 各自的并发与资源占用通过环境变量控制：
+  #   - generation：GENERATION_CONCURRENCY（默认 2），消费 generation 队列
+  #   - transcode： TRANSCODE_CONCURRENCY（默认 2），消费 transcode,celery 队列
+  #   - beat：      不消费任务，只发定时任务到 celery 默认队列
   worker:
     image: ${WORKER_IMAGE:-xiaoxia-saas-worker:dev}
-    
+
     container_name: xiaoxia-worker-${ENV:-staging}
     restart: unless-stopped
+    # 长任务（ingest HEVC 转码最长 30min、生成硬超时 11min）给足优雅关闭窗口
     stop_grace_period: 300s
     stop_signal: SIGTERM
-    
+
     env_file:
       - ../../.env
-    
+
     environment:
       APP_ENV: ${APP_ENV:-staging}
+      # 兼容旧变量：若两个 *_CONCURRENCY 均未显式设置，entrypoint 会按此总数分配
       WORKER_CONCURRENCY: ${WORKER_CONCURRENCY:-4}
       WORKER_MAX_TASKS_PER_CHILD: ${WORKER_MAX_TASKS_PER_CHILD:-100}
-      # #1714 队列隔离：generation 队列独占 worker（默认并发 2），其余并发给转码
+      # #2073 队列独立伸缩：generation 默认 2，transcode 默认 2（不再差值计算）
       GENERATION_CONCURRENCY: ${GENERATION_CONCURRENCY:-2}
+      TRANSCODE_CONCURRENCY: ${TRANSCODE_CONCURRENCY:-2}
+      # beat 默认在本容器启动；独立 beat 容器部署时设为 0
+      BEAT_ENABLED: ${BEAT_ENABLED:-1}
       GENERATED_FILES_DIR: /app/generated
       GENERATED_FILES_URL_PREFIX: /generated-files
       PUBLIC_API_BASE_URL: ${PUBLIC_API_BASE_URL:-https://api.xiaoxiajianji.com}
-    
+
     volumes:
       - generated-files:/app/generated
-    
+
     networks:
       - xiaoxia-net
 
-    # 健康检查配置
-    # 注：容器内无 pgrep/ps，扫描 /proc 所有进程的 cmdline 查找 celery 进程
+    # 健康检查：至少有一个 celery worker 进程在跑（beat 本身不作为存活依据）
     healthcheck:
-      test: ["CMD-SHELL", "grep -lq celery /proc/[0-9]*/cmdline 2>/dev/null || exit 1"]
+      test: ["CMD-SHELL", "grep -q 'celery.*worker' /proc/[0-9]*/cmdline 2>/dev/null || exit 1"]
       interval: 30s
       timeout: 10s
       retries: 3
@@ -137,12 +137,8 @@ services:
 
     logging: *default-logging
 
-    # =========================================
-    # 资源限制建议（生产环境建议启用）
-    # =========================================
-    # 注意: Worker 需要处理视频，建议分配更多资源
-    # #1714 队列隔离后容器内运行 generation + transcode 两个 worker 进程，
-    # 总并发 = WORKER_CONCURRENCY（默认 4），4C8G 以上确保视频渲染不 OOM
+    # 资源限制：容器总资源 = gen + trans + beat，按 2+2 并发场景建议 4C8G；
+    # 后续如需独立扩容/重启，可拆为 worker-generation / worker-transcode / worker-beat 三个 service。
     deploy:
       resources:
         limits:
@@ -157,35 +153,21 @@ services:
   # =========================================
   web:
     image: ${WEB_IMAGE:-xiaoxia-saas-web:dev}
-    # 不在生产环境构建镜像，使用 web-artifact.Dockerfile
-    # build:
-    #   context: ../..
-    #   dockerfile: ${WEB_DOCKERFILE:-infra/docker/web.Dockerfile}
-    #   args:
-    #     (NGINX_CONF no longer needed - all configs baked into image)
-    
+
     container_name: xiaoxia-web-${ENV:-staging}
     restart: unless-stopped
-    
-    # 端口映射
-    # Staging: 3001 -> 80
-    # Production: 3002 -> 80 (通过 Nginx 反向代理)
+
     ports:
       - "127.0.0.1:${WEB_PORT:-3001}:80"
-    
+
     networks:
       - xiaoxia-net
-    
-    # =========================================
-    # Nginx 配置运行时覆盖（双保险：entrypoint 也按 APP_ENV 选择配置）
-    # 确保容器使用正确环境的 nginx 配置，即使镜像构建时使用了默认配置
-    # 注意: 只覆盖 /etc/nginx/conf.d/default.conf，不挂载 /usr/share/nginx/html
-    # =========================================
+
     environment:
       - APP_ENV=${ENV:-staging}
     volumes:
       - ./nginx-${ENV:-staging}.conf:/etc/nginx/conf.d/default.conf:ro
-    
+
     healthcheck:
       test: ["CMD", "wget", "--spider", "-q", "http://127.0.0.1:80"]
       interval: 30s
@@ -194,9 +176,6 @@ services:
 
     logging: *default-logging
 
-    # =========================================
-    # 资源限制建议
-    # =========================================
     deploy:
       resources:
         limits:
@@ -212,9 +191,6 @@ volumes:
     driver_opts:
       type: none
       o: bind
-      # 重要: 确保主机目录存在且有正确权限
-      # Staging: /var/lib/xiaoxia-saas-staging/generated
-      # Production: /var/lib/xiaoxia-saas-production/generated
       device: ${GENERATED_FILES_HOST_DIR:?GENERATED_FILES_HOST_DIR must be set in .env}
 
 # ===========================================
@@ -223,8 +199,4 @@ volumes:
 networks:
   xiaoxia-net:
     external: true
-    # 网络名根据 ENV 变量区分，实现 staging/production 环境隔离
-    # staging:     xiaoxia-net-staging
-    # production:  xiaoxia-net-production
     name: xiaoxia-net-${ENV:-staging}
-

infra/docker/entrypoint-api.sh

@@ -0,0 +1,22 @@
+#!/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

infra/docker/entrypoint-worker.sh

@@ -1,48 +1,88 @@
 #!/bin/bash
-# Worker 启动脚本 — #1714 队列隔离
+# Worker 启动脚本 — #1714 + #2073 队列分流
 #
-# 部署约束：worker 容器单实例（replicas=1），容器内启动两个 celery 进程：
-#   1. generation-worker：独占消费 generation 队列（用户视频生成，高优先级），
-#      内嵌 celery beat（-B），定时清理任务只在一个进程里跑，避免重复执行；
-#   2. transcode-worker：消费 transcode + celery 默认队列（素材转码/分类/查重/
-#      配音/下载等后台任务）。
-# 转码队列积压时，generation 队列仍有独立 worker 立即领取视频生成任务。
+# 容器内启动三个独立进程（任一退出则整体退出由 docker restart 拉起）：
+#   1. beat：celery beat 调度器，不消费任何任务，只发定时任务到 celery 默认队列
+#   2. generation-worker：独占消费 generation 队列（用户实时任务，高优先级）
+#   3. transcode-worker：消费 transcode + celery 默认队列（后台/清理任务）
 #
 # 环境变量：
-#   WORKER_CONCURRENCY            总并发槽参考（默认 4）；生成 worker 并发默认 2，
-#                                 可用 GENERATION_CONCURRENCY 覆盖
 #   GENERATION_CONCURRENCY        generation worker 并发（默认 2）
-#   TRANSCODE_CONCURRENCY         transcode worker 并发（默认 = WORKER_CONCURRENCY - 2，最小 1）
+#   TRANSCODE_CONCURRENCY         transcode worker 并发（默认 2）
 #   WORKER_MAX_TASKS_PER_CHILD    每个子进程最大任务数（默认 100）
+#   WORKER_CONCURRENCY            兼容旧变量：若未显式设置 GENERATION_CONCURRENCY /
+#                                 TRANSCODE_CONCURRENCY，则按比例分配（gen=ceil(total*1/2)，
+#                                 trans=剩余，各至少 1）；已显式设置时忽略此变量。
+#   BEAT_ENABLED                  是否在本容器内启动 beat 进程（默认 1）；
+#                                 若独立 beat 容器部署设为 0。
 
 set -e
 
-CONCURRENCY="${WORKER_CONCURRENCY:-4}"
+# #2129: 幂等执行数据库迁移（watchtower 自动部署兜底）
+# worker 容器独立启动，不能依赖 API 容器先跑迁移
+cd /app
+echo "[entrypoint-worker] Running alembic upgrade head..."
+if alembic upgrade head; then
+  echo "[entrypoint-worker] Migrations ok."
+else
+  echo "[entrypoint-worker] WARNING: alembic upgrade failed, continuing to start workers..." >&2
+fi
+cd - >/dev/null
+
 MAX_TASKS="${WORKER_MAX_TASKS_PER_CHILD:-100}"
 
-GEN_CONCURRENCY="${GENERATION_CONCURRENCY:-2}"
-if [ -z "$TRANSCODE_CONCURRENCY" ]; then
-  TRANS_CONCURRENCY=$((CONCURRENCY - GEN_CONCURRENCY))
-  if [ "$TRANS_CONCURRENCY" -lt 1 ]; then
-    TRANS_CONCURRENCY=1
-  fi
+# ── 并发计算：显式 env 优先；否则从 WORKER_CONCURRENCY 按比例推导 ──
+if [ -n "$GENERATION_CONCURRENCY" ]; then
+  GEN_CONCURRENCY="$GENERATION_CONCURRENCY"
 else
-  TRANS_CONCURRENCY="$TRANSCODE_CONCURRENCY"
+  TOTAL="${WORKER_CONCURRENCY:-4}"
+  GEN_CONCURRENCY=$(( (TOTAL + 1) / 2 ))
+  if [ "$GEN_CONCURRENCY" -lt 1 ]; then GEN_CONCURRENCY=1; fi
 fi
 
-echo "Starting generation worker (queue=generation, concurrency=$GEN_CONCURRENCY, beat embedded)"
+if [ -n "$TRANSCODE_CONCURRENCY" ]; then
+  TRANS_CONCURRENCY="$TRANSCODE_CONCURRENCY"
+else
+  if [ -n "$WORKER_CONCURRENCY" ] && [ -z "$GENERATION_CONCURRENCY" ]; then
+    # 两个都没显式设置，按 WORKER_CONCURRENCY 分配剩余
+    TOTAL="$WORKER_CONCURRENCY"
+    TRANS_CONCURRENCY=$(( TOTAL - GEN_CONCURRENCY ))
+    if [ "$TRANS_CONCURRENCY" -lt 1 ]; then TRANS_CONCURRENCY=1; fi
+  else
+    # 默认 2（#2073：独立伸缩，不再依赖 WORKER_CONCURRENCY 差值）
+    TRANS_CONCURRENCY=2
+  fi
+fi
+
+BEAT_ENABLED="${BEAT_ENABLED:-1}"
+
+PIDS=()
+
+# ── 1. Beat 调度器（独立进程，不消费任务）──
+if [ "$BEAT_ENABLED" = "1" ] || [ "$BEAT_ENABLED" = "true" ]; then
+  echo "Starting beat scheduler (schedule file=/tmp/celerybeat-schedule)"
+  celery \
+    -A worker_app.celery_app \
+    beat \
+    --loglevel=info \
+    -s /tmp/celerybeat-schedule &
+  PIDS+=($!)
+fi
+
+# ── 2. Generation worker（实时高优队列）──
+echo "Starting generation worker (queue=generation, concurrency=$GEN_CONCURRENCY)"
 celery \
   -A worker_app.celery_app \
   worker \
   --loglevel=info \
-  "-B" \
-  -s /tmp/celerybeat-schedule \
   -Q generation \
   "--concurrency=${GEN_CONCURRENCY}" \
   "--max-tasks-per-child=${MAX_TASKS}" \
   -n generation@%h &
-GEN_PID=$!
+PIDS+=($!)
+GEN_PID=${PIDS[1]:-${PIDS[0]}}
 
+# ── 3. Transcode worker（后台 + 清理队列）──
 echo "Starting transcode worker (queues=transcode,celery, concurrency=$TRANS_CONCURRENCY)"
 celery \
   -A worker_app.celery_app \
@@ -52,13 +92,22 @@ celery \
   "--concurrency=${TRANS_CONCURRENCY}" \
   "--max-tasks-per-child=${MAX_TASKS}" \
   -n transcode@%h &
-TRANS_PID=$!
+PIDS+=($!)
+TRANS_PID=${PIDS[2]:-${PIDS[1]}}
 
-# 任一进程退出则终止另一个，让容器整体重启（restart: unless-stopped）
-trap 'echo "Shutting down workers..."; kill -TERM $GEN_PID $TRANS_PID 2>/dev/null || true' TERM INT
+# 任一进程退出则终止其他进程，让容器整体重启
+cleanup() {
+  echo "Shutting down all celery processes..."
+  for pid in "${PIDS[@]}"; do
+    kill -TERM "$pid" 2>/dev/null || true
+  done
+}
+trap cleanup TERM INT
 
-wait -n $GEN_PID $TRANS_PID
+# wait -n 等待任意一个子进程退出（bash 4.3+）
+# 容器镜像基础为 python:3.11-slim，bash 版本满足
+wait -n "${PIDS[@]}"
 EXIT_CODE=$?
-echo "One worker exited (code=$EXIT_CODE), stopping the other..."
-kill -TERM $GEN_PID $TRANS_PID 2>/dev/null || true
-exit $EXIT_CODE
+echo "One celery process exited (code=$EXIT_CODE), stopping the rest..."
+cleanup
+exit "$EXIT_CODE"

infra/docker/worker.Dockerfile

@@ -10,6 +10,14 @@ FROM xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com/xiaoxiakeji/saas-worker-base:l
 # 构建参数：版本号（CI 传入 commit hash）
 ARG APP_VERSION=dev
 
+# CJK 字体保障：确保 fonts-noto-cjk 已安装（base 镜像漂移兜底）+ 重建字体缓存
+# fc-cache 非致命；fc-match 结果只打日志用于排查，不阻断构建
+RUN apt-get update && (apt-get install -y --no-install-recommends fonts-noto-cjk fontconfig || true) \
+    && rm -rf /var/lib/apt/lists/* \
+    && (fc-cache -fv || true) \
+    && echo "[font] fc-match sans:zh: $(fc-match -f '%{family}\n' sans:zh 2>/dev/null | head -1)" \
+    && echo "[font] fc-match Noto Sans CJK SC: $(fc-match 'Noto Sans CJK SC' 2>/dev/null | head -1)"
+
 # 创建非 root 用户
 RUN groupadd -r celery \
     && useradd -r -g celery -d /app -s /sbin/nologin celery \
@@ -26,6 +34,7 @@ ENV APP_VERSION=$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，

infra/nginx/gpu-relay-staging.conf

@@ -1,31 +1,29 @@
-# Staging GPU relay plain-HTTP vhost (P4000 NVENC 编码回传入口)
-# - 监听 8092 端口纯 HTTP（绕开 HTTPS 证书与 P4000 httpx SSL 问题）
-# - 代理到本机 staging API 的 /api/ 路径（127.0.0.1:8000 是 docker 映射端口）
-# - P4000 通过 Tailscale 直连宿主机 100.69.73.60:8092 PUT 编码结果
-# - Worker 通过 Docker DNS (xiaoxia-api-staging:8000) 直接 GET/DELETE，
-#   不经宿主机 nginx，避免 UFW FORWARD DROP 阻断
+# Staging GPU relay nginx 配置说明
 #
-# 部署：cp infra/nginx/gpu-relay-staging.conf /etc/nginx/conf.d/ && nginx -t && systemctl reload nginx
-
-server {
-    listen 8092;
-    server_name _;
-
-    client_max_body_size 2048m;
-
-    location /api/ {
-        proxy_pass http://127.0.0.1:8000/api/;
-        proxy_http_version 1.1;
-        proxy_set_header Host $host;
-        proxy_set_header X-Real-IP $remote_addr;
-        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
-        proxy_set_header X-Forwarded-Proto $scheme;
-        proxy_request_buffering off;
-        proxy_read_timeout 600s;
-        proxy_send_timeout 600s;
-    }
-
-    location = /health {
-        proxy_pass http://127.0.0.1:8000/health;
-    }
-}
+# GPU relay 并没有独立的 nginx vhost，而是集成在宿主机 CMS nginx 的 8092 server block 中。
+# 完整宿主机 nginx 配置备份见: deploy/configs/host-nginx-cms-staging.conf
+#
+# 核心 location 块（添加到 8092 server block，位于 location /api/ 之前）：
+#
+#     # GPU relay endpoints - proxy to staging API (port 8000) instead of CMS
+#     location /api/v1/internal/gpu-relay/ {
+#         proxy_pass http://127.0.0.1:8000/api/v1/internal/gpu-relay/;
+#         proxy_http_version 1.1;
+#         proxy_set_header Host $host;
+#         proxy_set_header X-Real-IP $remote_addr;
+#         proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+#         proxy_set_header X-Forwarded-Proto $scheme;
+#         proxy_request_buffering off;
+#         proxy_read_timeout 600s;
+#         proxy_send_timeout 600s;
+#     }
+#
+# 部署方式：手动将上述 location 块添加到 /etc/nginx/sites-available/05-xiaoxia-cms 的 8092 server block 中
+# 然后 nginx -t && systemctl reload nginx
+#
+# 原理说明：
+# - 8092 端口由 CMS 宿主机 nginx 承载（与 CMS 共享端口）
+# - GPU relay 路由 /api/v1/internal/gpu-relay/ 比 CMS 的 /api/ 更具体
+# - nginx 最长前缀匹配确保 relay 请求路由到 staging API (port 8000) 而非 CMS (port 8091)
+# - P4000 通过 Tailscale IP 100.69.73.60:8092 访问 relay
+# - Worker 容器通过 Docker DNS xiaoxia-api-staging:8000 直接访问 relay

packages/adapters/in_memory/ingest_job_repository.py

@@ -14,6 +14,24 @@ class InMemoryIngestJobRepository:
     def get(self, job_id: str) -> IngestJob | None:
         return self._items.get(job_id)
 
+    def find_by_asset_id(self, asset_id: str) -> IngestJob | None:
+        if not asset_id:
+            return None
+        from packages.domain.classification import IngestJobStatus
+
+        running: IngestJob | None = None
+        completed: IngestJob | None = None
+        for job in self._items.values():
+            if getattr(job, "asset_id", "") != asset_id:
+                continue
+            if job.status in (IngestJobStatus.PENDING, IngestJobStatus.PROCESSING):
+                if running is None or job.created_at > running.created_at:
+                    running = job
+            elif job.status == IngestJobStatus.COMPLETED:
+                if completed is None or job.created_at > completed.created_at:
+                    completed = job
+        return running or completed
+
     def update(self, job: IngestJob) -> IngestJob:
         self._items[job.id] = job
         return job

packages/adapters/sqlalchemy_impl/asset_repository.py

@@ -128,8 +128,12 @@ class SQLAlchemyAssetRepository:
             height=asset.height,
             fps=asset.fps,
             codec=asset.codec,
-            status=asset.status.value,
-            classification_status=asset.classification_status.value,
+            status=(asset.status.value if hasattr(asset.status, "value") else str(asset.status)),
+            classification_status=(
+                asset.classification_status.value
+                if hasattr(asset.classification_status, "value")
+                else str(asset.classification_status)
+            ),
             classification_result=(json.dumps(asset.metadata) if asset.metadata else None),
             quality_score=asset.quality_score,
             uploaded_by_user_id=asset.uploaded_by_user_id or "system",
@@ -142,7 +146,7 @@ class SQLAlchemyAssetRepository:
         self.session.flush()
         self._sync_asset_tags(asset.id, asset.tag_ids)
         # Issue #1776: 自动维护素材库计数（同事务内原子更新）
-        if asset.library_id and asset.status.value != "deleted":
+        if asset.library_id and (getattr(asset.status, "value", str(asset.status)) != "deleted"):
             from sqlalchemy import func
 
             self.session.query(AssetLibraryModel).filter(AssetLibraryModel.id == asset.library_id).update(
@@ -168,8 +172,12 @@ class SQLAlchemyAssetRepository:
         model.height = asset.height
         model.fps = asset.fps
         model.codec = asset.codec
-        model.status = asset.status.value
-        model.classification_status = asset.classification_status.value
+        model.status = asset.status.value if hasattr(asset.status, "value") else str(asset.status)
+        model.classification_status = (
+            asset.classification_status.value
+            if hasattr(asset.classification_status, "value")
+            else str(asset.classification_status)
+        )
         model.classification_result = json.dumps(asset.metadata) if asset.metadata else None
         model.quality_score = asset.quality_score
         model.uploaded_by_user_id = asset.uploaded_by_user_id or model.uploaded_by_user_id
@@ -494,8 +502,19 @@ class SQLAlchemyAssetRepository:
         return [self._to_domain(m) for m in models]
 
     def find_by_storage_key(self, storage_key: str) -> Asset | None:
-        """按 storage_key（对应 DB 中的 file_url）查找素材。"""
-        model = self.session.query(AssetModel).filter(AssetModel.file_url == storage_key).first()
+        """按 storage_key 查找素材。
+
+        Bug #2110: 历史数据 file_url 列可能是旧路径（assets/...），新代码统一写入
+        storage_key 列。双列 OR 查询，避免占位 asset 因路径错配导致 ingest 兜底新建
+        第二条 READY 记录，原占位卡 PROCESSING → 前端缩略图出现后消失。
+        """
+        if not storage_key:
+            return None
+        model = (
+            self.session.query(AssetModel)
+            .filter((AssetModel.storage_key == storage_key) | (AssetModel.file_url == storage_key))
+            .first()
+        )
         if model is None:
             return None
         return self._to_domain(model)

packages/adapters/sqlalchemy_impl/generation_task_repository.py

@@ -43,6 +43,7 @@ def _to_domain(model: GenerationTaskModel) -> GenerationTask:
         output_height=getattr(model, "output_height", 720) or 720,
         cover_url=getattr(model, "cover_url", "") or "",
         title_config=dict(getattr(model, "title_config", {}) or {}),
+        extra_meta=dict(getattr(model, "extra_meta", {}) or {}),
         logs=model.logs or "[]",
         created_at=model.created_at,
         updated_at=model.updated_at,
@@ -88,6 +89,7 @@ class SQLAlchemyGenerationTaskRepository:
             output_height=task.output_height,
             cover_url=task.cover_url or "",
             title_config=dict(task.title_config) if task.title_config else {},
+            extra_meta=dict(task.extra_meta) if task.extra_meta else {},
             logs=task.logs,
             created_at=task.created_at,
             updated_at=task.updated_at,
@@ -322,6 +324,7 @@ class SQLAlchemyGenerationTaskRepository:
         model.output_height = task.output_height
         model.cover_url = task.cover_url or ""
         model.title_config = dict(task.title_config) if task.title_config else {}
+        model.extra_meta = dict(task.extra_meta) if task.extra_meta else {}
         model.logs = task.logs
         self.session.commit()
         return task

packages/adapters/sqlalchemy_impl/ingest_job_repository.py

@@ -46,6 +46,43 @@ class SQLAlchemyIngestJobRepository:
             updated_at=model.updated_at,
         )
 
+    def find_by_asset_id(self, asset_id: str) -> IngestJob | None:
+        """返回 asset 最近一条未失败的 ingest job（PENDING/PROCESSING/COMPLETED 均算存在，用于幂等判断）。"""
+        if not asset_id:
+            return None
+        # 优先返回仍在跑的 (PENDING/PROCESSING)，否则返回最新一条 COMPLETED
+        model = (
+            self.session.query(IngestJobModel)
+            .filter(IngestJobModel.asset_id == asset_id)
+            .filter(IngestJobModel.status.in_([IngestJobStatus.PENDING.value, IngestJobStatus.PROCESSING.value]))
+            .order_by(IngestJobModel.created_at.desc())
+            .first()
+        )
+        if model is None:
+            model = (
+                self.session.query(IngestJobModel)
+                .filter(IngestJobModel.asset_id == asset_id)
+                .filter(IngestJobModel.status == IngestJobStatus.COMPLETED.value)
+                .order_by(IngestJobModel.created_at.desc())
+                .first()
+            )
+        if model is None:
+            return None
+        return IngestJob(
+            id=model.id,
+            project_id=model.project_id,
+            library_id=model.library_id,
+            storage_key=model.storage_key,
+            status=IngestJobStatus(model.status),
+            error_message=model.error_message,
+            result_asset_id=model.result_asset_id,
+            file_hash=model.file_hash or "",
+            asset_id=getattr(model, "asset_id", "") or "",
+            celery_task_id=getattr(model, "celery_task_id", "") or "",
+            created_at=model.created_at,
+            updated_at=model.updated_at,
+        )
+
     def list_by_project(self, project_id: str) -> list[IngestJob]:
         models = self.session.query(IngestJobModel).filter(IngestJobModel.project_id == project_id).all()
         return [self.get(model.id) for model in models if self.get(model.id) is not None]

packages/adapters/sqlalchemy_impl/models.py

@@ -56,7 +56,7 @@ class UserModel(Base):
     is_member = Column(Boolean, nullable=False, default=False)
     member_type = Column(String(20), nullable=True)
     member_expires_at = Column(DateTime, nullable=True)
-    points_balance = Column(Integer, nullable=False, default=0)
+    points_balance = Column(Float, nullable=False, default=0)
     created_at = Column(DateTime, nullable=False, default=lambda: datetime.now(UTC))
 
 
@@ -775,9 +775,9 @@ class PointsAccountModel(Base):
 
     id = Column(String(36), primary_key=True)
     user_id = Column(String(36), nullable=False, unique=True, index=True)
-    balance = Column(Integer, nullable=False, default=0)
-    total_earned = Column(Integer, nullable=False, default=0)
-    total_spent = Column(Integer, nullable=False, default=0)
+    balance = Column(Float, nullable=False, default=0)
+    total_earned = Column(Float, nullable=False, default=0)
+    total_spent = Column(Float, nullable=False, default=0)
     created_at = Column(DateTime, nullable=False, default=lambda: datetime.now(UTC))
     updated_at = Column(DateTime, nullable=False, default=lambda: datetime.now(UTC))
 
@@ -792,8 +792,8 @@ class PointsTransactionModel(Base):
     account_id = Column(String(36), nullable=False, index=True)
     type = Column(String(20), nullable=False, index=True)  # earn / spend / refund
     source = Column(String(50), nullable=False, index=True)
-    amount = Column(Integer, nullable=False)
-    balance_after = Column(Integer, nullable=False)
+    amount = Column(Float, nullable=False)
+    balance_after = Column(Float, nullable=False)
     description = Column(String(255), nullable=False, default="")
     ref_id = Column(String(100), nullable=False, default="")
     created_at = Column(DateTime, nullable=False, default=lambda: datetime.now(UTC))
@@ -918,3 +918,88 @@ class GpuWorkerModel(Base):
     capabilities = Column(String(500), nullable=False, default="")  # 逗号分隔，如 "musetalk"
     last_heartbeat_at = Column(DateTime, nullable=True, index=True)
     created_at = Column(DateTime, nullable=False, default=lambda: datetime.now(UTC))
+
+
+class ViralVideoJobModel(Base):
+    """爆款视频任务"""
+
+    __tablename__ = "viral_video_jobs"
+
+    id = Column(String(36), primary_key=True)
+    user_id = Column(String(36), nullable=False, index=True)
+    images = Column(JSON, nullable=False, default=list)  # 产品图片 URL 列表
+    industry = Column(String(100), nullable=False, default="")
+    target_customer = Column(String(500), nullable=False, default="")
+    persona_id = Column(String(36), nullable=False, default="")
+    viral_structure = Column(String(50), nullable=False, default="")
+    marketing_purpose = Column(String(100), nullable=False, default="")
+    bgm_preference = Column(String(50), nullable=False, default="")
+    duration = Column(Integer, nullable=False, default=30)
+    user_copy_text = Column(Text, nullable=False, default="")
+    fusion_level = Column(String(20), nullable=False, default="ai_polish")
+    reference_audio_path = Column(String(1000), nullable=False, default="")
+    # v1.3 新增字段
+    reference_video_url = Column(String(1000), nullable=False, default="")
+    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(Float, nullable=False, default=0)
+    video_resolution = Column(String(20), nullable=False, default="720p")
+    credits_prepaid = Column(Float, nullable=False, default=0.0)
+    credits_transaction_id = Column(String(36), nullable=False, default="")
+    error_msg = Column(Text, nullable=False, default="")
+    retry_count = Column(Integer, nullable=False, default=0)
+    started_at = Column(DateTime(timezone=True), nullable=True)
+    completed_at = Column(DateTime(timezone=True), nullable=True)
+    created_at = Column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(UTC))
+    updated_at = Column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(UTC))
+
+
+class ViralVideoStyleTemplateModel(Base):
+    """爆款视频风格模板配置表"""
+
+    __tablename__ = "viral_video_style_templates"
+
+    id = Column(String(36), primary_key=True)
+    name = Column(String(200), nullable=False)
+    description = Column(Text, nullable=False, default="")
+    thumbnail_url = Column(String(1000), nullable=False, default="")
+    style_config = Column(JSON, nullable=False, default=dict)
+    is_system = Column(Boolean, nullable=False, default=True, index=True)
+    sort_order = Column(Integer, nullable=False, default=0)
+    created_at = Column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(UTC))
+    updated_at = Column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(UTC))
+
+
+class ViralVideoPromptTemplateModel(Base):
+    """爆款视频 Prompt 模板表（由 #2040 seed）"""
+
+    __tablename__ = "viral_video_prompt_templates"
+
+    id = Column(String(36), primary_key=True)
+    prompt_type = Column(String(50), nullable=False, index=True)
+    name = Column(String(200), nullable=False)
+    content = Column(Text, nullable=False, default="")
+    variables = Column(JSON, nullable=False, default=list)
+    version = Column(Integer, nullable=False, default=1)
+    is_active = Column(Boolean, nullable=False, default=True, index=True)
+    created_at = Column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(UTC))
+    updated_at = Column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(UTC))

packages/adapters/sqlalchemy_impl/session.py

@@ -81,6 +81,41 @@ 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。
 
@@ -100,4 +135,5 @@ 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()

packages/adapters/sqlalchemy_impl/viral_video_repository.py

@@ -0,0 +1,257 @@
+"""爆款视频任务 SQLAlchemy 仓储实现。"""
+
+from datetime import datetime, timezone
+
+from sqlalchemy.orm import Session
+
+from packages.adapters.sqlalchemy_impl.models import (
+    ViralVideoJobModel,
+    ViralVideoPromptTemplateModel,
+    ViralVideoStyleTemplateModel,
+)
+from packages.domain.viral_video import ViralVideoJob, ViralVideoStatus
+
+
+def _to_domain(model: ViralVideoJobModel) -> ViralVideoJob:
+    """ORM → 领域实体。"""
+    return ViralVideoJob(
+        id=model.id,
+        user_id=model.user_id,
+        images=list(model.images or []),
+        industry=model.industry or "",
+        target_customer=model.target_customer or "",
+        persona_id=model.persona_id or "",
+        viral_structure=model.viral_structure or "",
+        marketing_purpose=model.marketing_purpose or "",
+        bgm_preference=model.bgm_preference or "",
+        duration=model.duration or 15,
+        user_copy_text=model.user_copy_text or "",
+        fusion_level=model.fusion_level or "ai_polish",
+        reference_audio_path=model.reference_audio_path or "",
+        reference_video_url=getattr(model, "reference_video_url", "") or "",
+        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 "",
+        video_resolution=getattr(model, "video_resolution", "720p") or "720p",
+        credits_prepaid=float(getattr(model, "credits_prepaid", 0) or 0),
+        credits_transaction_id=getattr(model, "credits_transaction_id", "") or "",
+        credits_cost=float(model.credits_cost or 0),
+        error_msg=model.error_msg or "",
+        retry_count=model.retry_count or 0,
+        started_at=model.started_at,
+        completed_at=model.completed_at,
+        created_at=model.created_at,
+        updated_at=model.updated_at,
+    )
+
+
+class SQLAlchemyViralVideoJobRepository:
+    """爆款视频任务仓储。"""
+
+    def __init__(self, session: Session):
+        self.session = session
+
+    def save(self, job: ViralVideoJob) -> ViralVideoJob:
+        model = ViralVideoJobModel(
+            id=job.id,
+            user_id=job.user_id,
+            images=job.images,
+            industry=job.industry,
+            target_customer=job.target_customer,
+            persona_id=job.persona_id,
+            viral_structure=job.viral_structure,
+            marketing_purpose=job.marketing_purpose,
+            bgm_preference=job.bgm_preference,
+            duration=job.duration,
+            user_copy_text=job.user_copy_text,
+            fusion_level=job.fusion_level,
+            reference_audio_path=job.reference_audio_path,
+            reference_video_url=job.reference_video_url,
+            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,
+            video_resolution=getattr(job, "video_resolution", "720p") or "720p",
+            credits_prepaid=float(getattr(job, "credits_prepaid", 0) or 0),
+            credits_transaction_id=getattr(job, "credits_transaction_id", "") or "",
+            credits_cost=float(getattr(job, "credits_cost", 0) or 0),
+            error_msg=job.error_msg,
+            retry_count=job.retry_count,
+            started_at=job.started_at,
+            completed_at=job.completed_at,
+            created_at=job.created_at,
+            updated_at=job.updated_at,
+        )
+        self.session.add(model)
+        self.session.commit()
+        return job
+
+    def update(self, job: ViralVideoJob) -> None:
+        model = self.session.query(ViralVideoJobModel).filter(ViralVideoJobModel.id == job.id).first()
+        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.video_resolution = getattr(job, "video_resolution", "720p") or "720p"
+        model.credits_prepaid = float(getattr(job, "credits_prepaid", 0) or 0)
+        model.credits_transaction_id = getattr(job, "credits_transaction_id", "") or ""
+        model.credits_cost = float(getattr(job, "credits_cost", 0) or 0)
+        model.error_msg = job.error_msg
+        model.retry_count = job.retry_count
+        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()
+
+    def get(self, job_id: str) -> ViralVideoJob | None:
+        model = self.session.query(ViralVideoJobModel).filter(ViralVideoJobModel.id == job_id).first()
+        if model is None:
+            return None
+        return _to_domain(model)
+
+    def list_by_user(self, user_id: str, limit: int = 50, offset: int = 0) -> list[ViralVideoJob]:
+        models = (
+            self.session.query(ViralVideoJobModel)
+            .filter(ViralVideoJobModel.user_id == user_id)
+            .order_by(ViralVideoJobModel.created_at.desc())
+            .offset(offset)
+            .limit(limit)
+            .all()
+        )
+        return [_to_domain(m) for m in models]
+
+    def count_pending_by_user(self, user_id: str) -> int:
+        return (
+            self.session.query(ViralVideoJobModel)
+            .filter(
+                ViralVideoJobModel.user_id == user_id,
+                ViralVideoJobModel.status.in_(
+                    ["pending", "running", "wait_user_confirm", "image_analyzed", "copy_generated"]
+                ),
+            )
+            .count()
+        )
+
+
+class SQLAlchemyViralVideoStyleTemplateRepository:
+    """风格模板仓储。"""
+
+    def __init__(self, session: Session):
+        self.session = session
+
+    def list_all(self) -> list[dict]:
+        models = (
+            self.session.query(ViralVideoStyleTemplateModel)
+            .order_by(ViralVideoStyleTemplateModel.sort_order.asc())
+            .all()
+        )
+        return [
+            {
+                "id": m.id,
+                "name": m.name,
+                "description": m.description or "",
+                "thumbnail_url": m.thumbnail_url or "",
+                "style_config": dict(m.style_config) if m.style_config else {},
+                "is_system": m.is_system,
+            }
+            for m in models
+        ]
+
+    def get(self, template_id: str) -> dict | None:
+        model = (
+            self.session.query(ViralVideoStyleTemplateModel)
+            .filter(ViralVideoStyleTemplateModel.id == template_id)
+            .first()
+        )
+        if model is None:
+            return None
+        return {
+            "id": model.id,
+            "name": model.name,
+            "description": model.description or "",
+            "thumbnail_url": model.thumbnail_url or "",
+            "style_config": dict(model.style_config) if model.style_config else {},
+            "is_system": model.is_system,
+        }
+
+
+class SQLAlchemyViralVideoPromptTemplateRepository:
+    """Prompt 模板仓储（由 #2040 seed，这里只读取）。"""
+
+    def __init__(self, session: Session):
+        self.session = session
+
+    def get_active_by_type(self, prompt_type: str) -> dict | None:
+        model = (
+            self.session.query(ViralVideoPromptTemplateModel)
+            .filter(
+                ViralVideoPromptTemplateModel.prompt_type == prompt_type,
+                ViralVideoPromptTemplateModel.is_active.is_(True),
+            )
+            .order_by(ViralVideoPromptTemplateModel.version.desc())
+            .first()
+        )
+        if model is None:
+            return None
+        return {
+            "id": model.id,
+            "prompt_type": model.prompt_type,
+            "name": model.name,
+            "content": model.content,
+            "variables": list(model.variables or []),
+            "version": model.version,
+        }

packages/application/generated_video_finalize.py

@@ -52,6 +52,18 @@ class RenderedOutput:
     def from_dict(cls, data: dict[str, Any]) -> "RenderedOutput":
         if not isinstance(data, dict):
             raise ValueError("rendered_output must be a dict")
+        # fingerprint_chunks 历史上有两种位置：
+        #   1) 顶层 ``fingerprint_chunks``（由 compute_render_fingerprint_and_dedup 直接返回）
+        #   2) 嵌套在 ``fingerprint_dict["chunks"]``（VideoFingerprint.to_dict() 序列化的结构）
+        # 顶层优先；顶层为空时回退到嵌套位置，兼容旧数据。
+        fp_dict = data.get("fingerprint_dict") or {}
+        chunks_raw = data.get("fingerprint_chunks")
+        if not chunks_raw and isinstance(fp_dict, dict):
+            chunks_raw = fp_dict.get("chunks")
+        # md5 同样可能在顶层或嵌套在 fingerprint_dict 内（历史数据兼容）
+        md5_value = data.get("video_fingerprint_md5")
+        if not md5_value and isinstance(fp_dict, dict):
+            md5_value = fp_dict.get("md5")
         return cls(
             file_url=str(data.get("file_url") or ""),
             file_size=int(data.get("file_size") or 0),
@@ -65,14 +77,14 @@ class RenderedOutput:
             batch_id=str(data.get("batch_id") or ""),
             project_id=str(data.get("project_id") or ""),
             user_id=str(data.get("user_id") or ""),
-            fingerprint_dict=data.get("fingerprint_dict"),
-            fingerprint_chunks=data.get("fingerprint_chunks"),
+            fingerprint_dict=fp_dict or None,
+            fingerprint_chunks=chunks_raw if isinstance(chunks_raw, list) else None,
             is_duplicate=bool(data.get("is_duplicate", False)),
             duplicate_of=data.get("duplicate_of"),
             duplicate_rate=_safe_float(data.get("duplicate_rate")),
             match_count=_safe_int(data.get("match_count")),
             visual_similarity=_safe_float(data.get("visual_similarity")),
-            video_fingerprint_md5=str(data.get("video_fingerprint_md5") or ""),
+            video_fingerprint_md5=str(md5_value or ""),
         )
 
 

packages/config/api_settings.py

@@ -51,7 +51,7 @@ class APISettings(SharedSettings):
     def validate_jwt_secret_key(cls, v):
         if v is None or v == "":
             raise ValueError(
-                "JWT_SECRET_KEY must be set via environment variable. " "Do not use default value in production!"
+                "JWT_SECRET_KEY must be set via environment variable. Do not use default value in production!"
             )
         # Block known insecure default values
         insecure_defaults = [
@@ -63,7 +63,7 @@ class APISettings(SharedSettings):
         ]
         if v.lower() in [d.lower() for d in insecure_defaults]:
             raise ValueError(
-                f"JWT_SECRET_KEY '{v}' is insecure. " "Please set a strong random secret via environment variable."
+                f"JWT_SECRET_KEY '{v}' is insecure. Please set a strong random secret via environment variable."
             )
         return v
 
@@ -248,6 +248,10 @@ class APISettings(SharedSettings):
     def OSS_ENDPOINT(self) -> str:
         return self.oss_endpoint
 
+    @property
+    def OSS_INTERNAL_ENDPOINT(self) -> str:
+        return self.effective_oss_internal_endpoint
+
     @property
     def OSS_ACCESS_KEY_ID(self) -> str:
         return self.oss_access_key_id

packages/config/base.py

@@ -47,12 +47,37 @@ class SharedSettings(BaseSettings):
 
     # ── OSS 阿里云 ──────────────────────────────────────────────────────
     oss_endpoint: str = "oss-cn-hangzhou.aliyuncs.com"
+    # 内网 endpoint：ECS VPC 内访问 OSS 用（千兆带宽、免公网流量费）。
+    # 为空时自动从 oss_endpoint 推导：若 oss_endpoint 是阿里云公网域名（形如
+    # oss-cn-<region>.aliyuncs.com），自动加 -internal 得到内网域名；其他情况
+    # （自定义域名/本地 MinIO/非阿里云）回退使用 oss_endpoint。
+    # 显式填同值可以覆盖自动推导、强制所有流量都走公网。
+    oss_internal_endpoint: str = ""
     oss_access_key_id: str = ""
     oss_access_key_secret: str = ""
     oss_bucket_name: str = "xiaoxia-autocut"
     oss_direct_upload_max_mb: int = 2000
     oss_direct_upload_expire_seconds: int = 900
 
+    @property
+    def effective_oss_internal_endpoint(self) -> str:
+        """实际用于 SDK 内网访问的 endpoint（带 -internal 自动推导）。"""
+        if self.oss_internal_endpoint:
+            return self.oss_internal_endpoint
+        ep = self.oss_endpoint.strip()
+        scheme = ""
+        host = ep
+        if ep.startswith("https://"):
+            scheme = "https://"
+            host = ep[len("https://") :]
+        elif ep.startswith("http://"):
+            scheme = "http://"
+            host = ep[len("http://") :]
+        # 阿里云公网域名自动推导：oss-cn-<region>.aliyuncs.com → oss-cn-<region>-internal.aliyuncs.com
+        if host.endswith(".aliyuncs.com") and "-internal" not in host and host.startswith("oss-cn-"):
+            host = host[: -len(".aliyuncs.com")] + "-internal.aliyuncs.com"
+        return f"{scheme}{host}" if scheme else host
+
     # ── CosyVoice (阿里云百炼语音合成) ───────────────────────────────────
     cosyvoice_api_key: str = ""
     cosyvoice_base_url: str = "https://dashscope.aliyuncs.com/api/v1"
@@ -65,17 +90,24 @@ 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"
+    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_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-250915"
+    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_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）
+    doubao_video_poll_interval: int = 10  # 轮询间隔（秒）
 
     # ── MediaKit (火山引擎 AI 媒体工具) ──────────────────────────────────
     mediakit_api_key: str = ""
     mediakit_base_url: str = "https://mediakit.cn-beijing.volces.com/api/v1"
     mediakit_timeout: int = 60
+    mediakit_cover_enabled: bool = False  # 封面抽帧是否走MediaKit(默认false走本地ffmpeg+cv2，<2s完成)
 
     # ── 积分/会员系统 (#1895) ────────────────────────────────────────────
     # 积分系统总开关（产品要求 #1895：暂停积分系统但保留全部代码/表/接口）。

packages/domain/points_account.py

@@ -9,9 +9,9 @@ from uuid import uuid4
 class PointsAccount:
     id: str
     user_id: str
-    balance: int = 0
-    total_earned: int = 0
-    total_spent: int = 0
+    balance: float = 0.0
+    total_earned: float = 0.0
+    total_spent: float = 0.0
     created_at: datetime = field(default_factory=lambda: datetime.now(UTC))
     updated_at: datetime = field(default_factory=lambda: datetime.now(UTC))
 

packages/domain/points_rules.py

@@ -1,32 +1,198 @@
-"""积分消耗规则配置 (#1895)"""
+"""积分消耗规则配置 (#1895)
+
+v1.6.1: 按产品决策，智能混剪/AI数字人/AI配音/抖音解析/改写/标题/封面 全部免费，
+仅保留声音克隆合成（voice_clone_synth）的扣点逻辑；声音克隆训练保持免费。
+爆款视频（viral_video）走动态定价，见本文件 VIRAL_VIDEO_MODEL_PRICES + calculate_viral_video_credits。
+"""
 
 from __future__ import annotations
 
 import math
 
+# ============ 爆款视频动态定价 (#2151) ============
+# key = (model_id, resolution, has_video_input)，单位：元/百万token
+VIRAL_VIDEO_MODEL_PRICES: dict[tuple[str, str, bool], float] = {
+    ("seedance-2.5", "480p", False): 70.0,
+    ("seedance-2.5", "720p", False): 70.0,
+    ("seedance-2.5", "1080p", False): 77.0,
+    ("seedance-2.5", "480p", True): 42.0,
+    ("seedance-2.5", "720p", True): 42.0,
+    ("seedance-2.5", "1080p", True): 46.0,
+    ("seedance-2.0", "480p", False): 46.0,
+    ("seedance-2.0", "720p", False): 46.0,
+    ("seedance-2.0", "1080p", False): 51.0,
+}
+
+# 固定成本（元）：VLM 分析 + LLM 文案 + TTS + OSS + 服务器
+VIRAL_VIDEO_FIXED_COST = 0.15
+# 利润系数
+VIRAL_VIDEO_PROFIT_MULTIPLIER = 1.3
+# Seedance 输出帧率
+VIRAL_VIDEO_FPS = 24
+
+# 分辨率别名映射 -> 标准 key
+_RESOLUTION_ALIASES: dict[str, str] = {
+    "480p": "480p",
+    "普清": "480p",
+    "default": "480p",
+    "low": "480p",
+    "sd": "480p",
+    "720p": "720p",
+    "高清": "720p",
+    "medium": "720p",
+    "hd": "720p",
+    "1080p": "1080p",
+    "超清": "1080p",
+    "high": "1080p",
+    "ultra": "1080p",
+    "全能": "1080p",
+    "fhd": "1080p",
+}
+# 分辨率 -> 短边像素数（p 值代表短边，不是 height）
+_RESOLUTION_SHORT_SIDE: dict[str, int] = {"480p": 480, "720p": 720, "1080p": 1080}
+
+
+def resolve_video_dimensions(resolution: str, ratio: str) -> tuple[int, int]:
+    """把 (resolution, ratio) 解析为 (width, height)。
+
+    resolution 数字代表短边像素数（480p/720p/1080p 等）：
+    - 横屏 16:9：短边是 height，width = short * 16/9
+    - 竖屏 9:16：短边是 width，height = short * 16/9
+    - 方屏 1:1：width = height = short
+    """
+    key = str(resolution or "").strip()
+    key_l = key.lower()
+    res_key = _RESOLUTION_ALIASES.get(key_l) or _RESOLUTION_ALIASES.get(key) or "720p"
+    short = _RESOLUTION_SHORT_SIDE.get(res_key, 720)
+    r = str(ratio or "").strip().lower()
+    if r == "16:9":
+        # 横屏：短边是 height，width 向上取整并对齐偶数
+        w = math.ceil(short * 16 / 9)
+        h = short
+    elif r == "1:1":
+        w, h = short, short
+    else:
+        # 9:16 竖屏（默认）：短边是 width，height 向上取整并对齐偶数
+        w = short
+        h = math.ceil(short * 16 / 9)
+    # 对齐到偶数（视频编码要求）
+    w = w + (w % 2)
+    h = h + (h % 2)
+    return int(w), int(h)
+
+
+def _match_model_prefix(model: str) -> str:
+    """匹配 model 前缀。"""
+    m = (model or "").strip().lower()
+    for prefix in ("seedance-2.5", "seedance-2.0"):
+        if m.startswith(prefix):
+            return prefix
+    return "seedance-2.5"
+
+
+def _infer_resolution_key(width: int, height: int) -> str:
+    """从实际 (width, height) 用短边推断 resolution key。"""
+    short = min(int(width or 720), int(height or 720))
+    if short >= 1000:
+        return "1080p"
+    if short >= 650:
+        return "720p"
+    return "480p"
+
+
+def calculate_viral_video_credits_with_breakdown(
+    duration_seconds: int,
+    width: int,
+    height: int,
+    model: str = "seedance-2.5",
+    has_video_input: bool = False,
+    actual_tokens: int | None = None,
+    fps: int = VIRAL_VIDEO_FPS,
+) -> tuple[float, dict]:
+    """计算爆款视频所需积分（1 积分 = 1 元），并返回计费公式明细。
+
+    公式:
+        tokens = duration * width * height * fps / 1024
+        video_cost = tokens / 1_000_000 * model_token_price
+        total = round((video_cost + fixed_cost) * profit_multiplier, 2)
+    若传入 actual_tokens 则用它替代计算值。
+
+    Returns:
+        (credits, breakdown) 二元组：
+        - credits: 四舍五入保留两位小数的最终积分
+        - breakdown: dict，包含 tokens / video_cost / fixed_cost / profit_multiplier /
+          model_price / width / height / fps 字段，便于前端展示计费明细。
+    """
+    w = max(1, int(width or 1))
+    h = max(1, int(height or 1))
+    effective_fps = int(fps or VIRAL_VIDEO_FPS)
+
+    prefix = _match_model_prefix(model)
+    res_key = _infer_resolution_key(w, h)
+    key = (prefix, res_key, bool(has_video_input))
+    price = VIRAL_VIDEO_MODEL_PRICES.get(key)
+    if price is None:
+        price = VIRAL_VIDEO_MODEL_PRICES.get(("seedance-2.5", res_key, False), 70.0)
+    if actual_tokens is not None and actual_tokens > 0:
+        tokens = float(actual_tokens)
+    else:
+        dur = max(1, int(duration_seconds or 15))
+        tokens = dur * w * h * effective_fps / 1024.0
+
+    video_cost = tokens / 1_000_000.0 * float(price)
+    total = (video_cost + VIRAL_VIDEO_FIXED_COST) * VIRAL_VIDEO_PROFIT_MULTIPLIER
+    credits = round(float(total), 2)
+    breakdown = {
+        "tokens": float(tokens),
+        "video_cost": float(video_cost),
+        "fixed_cost": float(VIRAL_VIDEO_FIXED_COST),
+        "profit_multiplier": float(VIRAL_VIDEO_PROFIT_MULTIPLIER),
+        "model_price": float(price),
+        "width": int(w),
+        "height": int(h),
+        "fps": int(effective_fps),
+    }
+    return credits, breakdown
+
+
+def calculate_viral_video_credits(
+    duration_seconds: int,
+    width: int,
+    height: int,
+    model: str = "seedance-2.5",
+    has_video_input: bool = False,
+    actual_tokens: int | None = None,
+    fps: int = VIRAL_VIDEO_FPS,
+) -> float:
+    """计算爆款视频所需积分（1 积分 = 1 元），仅返回积分值（向后兼容包装器）。
+
+    内部调用 calculate_viral_video_credits_with_breakdown，仅返回 credits 部分，
+    保持旧调用方签名与返回值类型不变。
+
+    公式:
+        tokens = duration * width * height * fps / 1024
+        video_cost = tokens / 1_000_000 * model_token_price
+        total = round((video_cost + fixed_cost) * profit_multiplier, 2)
+    若传入 actual_tokens 则用它替代计算值。
+    """
+    credits, _ = calculate_viral_video_credits_with_breakdown(
+        duration_seconds=duration_seconds,
+        width=width,
+        height=height,
+        model=model,
+        has_video_input=has_video_input,
+        actual_tokens=actual_tokens,
+        fps=fps,
+    )
+    return credits
+
+
 # ============ 场景定义 ============
-# 每个场景: base_points(基础积分), unit(计费单位), name(显示名称)
+# 每个场景: base_points(基础积分), unit(计费单位), name(显示名称), dynamic(是否动态定价)
+# 说明：爆款视频（viral_video）走动态定价（预扣→结算多退少补），因此不使用 @points_gate
+# 装饰器，base_points=0，dynamic=True；前端展示场景列表时仍可看到。
 
 POINTS_SCENES: dict[str, dict] = {
-    "ai_voice": {
-        "base_points": 1,
-        "unit": "分钟",
-        "name": "AI 配音",
-        "description": "AI 配音每分钟消耗 1 积分（免费用户上浮 15%，会员 8~9 折）",
-    },
-    "ai_video": {
-        "base_points": 3,
-        "unit": "条",
-        "name": "智能混剪",
-        "extra_per_30s": 1,
-        "description": "智能混剪每条 3 积分起，视频超过 30 秒后每 30 秒加 1 积分；免费用户每日 2 条免费额度",
-    },
-    "ai_digital_human": {
-        "base_points": 15,
-        "unit": "分钟",
-        "name": "AI 数字人",
-        "description": "AI 数字人每分钟消耗 15 积分",
-    },
     "voice_clone_train": {
         "base_points": 0,
         "unit": "次",
@@ -39,23 +205,16 @@ POINTS_SCENES: dict[str, dict] = {
         "name": "声音克隆合成",
         "description": "克隆音色合成每分钟消耗 1 积分",
     },
-    "douyin_extract": {
-        "base_points": 1,
+    "viral_video": {
+        "base_points": 0,
         "unit": "次",
-        "name": "抖音链接提取",
-        "description": "抖音文案提取每次 1 积分",
+        "name": "爆款视频",
+        "dynamic": True,
+        "description": "爆款视频动态定价（按视频时长/分辨率/模型计算，预扣→结算多退少补）",
     },
-    "ai_rewrite": {"base_points": 1, "unit": "次", "name": "AI 改写文案", "description": "AI 改写文案每次 1 积分"},
-    "ai_title": {
-        "base_points": 1,
-        "unit": "次",
-        "name": "AI 标题生成",
-        "description": "AI 生成标题每次 1 积分（免费用户实际上浮后 2 积分/次）",
-    },
-    "ai_cover": {"base_points": 1, "unit": "张", "name": "AI 封面生成", "description": "AI 封面生成每张 1 积分"},
 }
 
-# 免费用户积分消耗上浮系数
+# 免费用户积分消耗上浮系数（仅对 voice_clone_synth 生效）
 FREE_USER_MULTIPLIER = 1.15
 
 # ============ 积分包定义 ============
@@ -81,9 +240,6 @@ MEMBER_DISCOUNT: dict[str, float] = {
     "yearly": 0.8,
 }
 
-# 每日免费混剪次数（免费用户）
-DAILY_FREE_CLIP_LIMIT = 2
-
 
 def calculate_points_cost(
     scene_key: str,
@@ -91,48 +247,45 @@ def calculate_points_cost(
     quantity: int = 1,
     duration_minutes: float = 0,
     member_type: str | None = None,
-) -> int:
+) -> float:
     """计算指定场景的积分消耗。
 
     Args:
-        scene_key: 场景标识，如 "ai_voice"、"ai_video"
+        scene_key: 场景标识（当前支持 voice_clone_train/voice_clone_synth/viral_video；
+                   viral_video 为动态定价场景，此处返回 0，由业务侧调用
+                   calculate_viral_video_credits 手动计算）
         is_member: 是否付费会员
         quantity: 数量（按次计费场景）
         duration_minutes: 时长分钟数（按时长计费场景）
         member_type: 会员类型 (monthly/quarterly/yearly)，用于折扣
 
     Returns:
-        实际消耗积分（已含免费用户 ×1.15 上浮或会员折扣）
-
-    Raises:
-        ValueError: 未知场景标识
+        实际消耗积分（float；已含免费用户 ×1.15 上浮或会员折扣）；免费/动态/已下线场景统一返回 0。
     """
     scene = POINTS_SCENES.get(scene_key)
     if not scene:
-        raise ValueError(f"Unknown points scene: {scene_key}")
+        # 已下线/未注册的场景统一返回 0（免费），保持向后兼容
+        return 0.0
+
+    # 动态定价场景（如 viral_video）由业务侧手动计算，这里统一返回 0
+    if scene.get("dynamic"):
+        return 0.0
 
     base = scene["base_points"]
     if base == 0:
-        return 0
+        return 0.0
 
-    # —— 计算基础消耗 ——
     unit = scene["unit"]
     if unit == "分钟":
         total_base = base * max(1, math.ceil(duration_minutes))
-    elif unit in ("条", "次", "张"):
+    elif unit in ("次", "张"):
         total_base = base * quantity
-        # 混剪特殊逻辑：视频超过 30s 后每 +30s 额外加 1 积分
-        if scene_key == "ai_video" and duration_minutes > 0.5:
-            extra_segments = math.ceil((duration_minutes * 60 - 30) / 30)
-            if extra_segments > 0:
-                total_base += scene.get("extra_per_30s", 1) * extra_segments
     else:
         total_base = base
 
-    # —— 会员折扣 / 免费用户上浮 ——
     if is_member and member_type and member_type in MEMBER_DISCOUNT:
         total_base = max(1, math.floor(total_base * MEMBER_DISCOUNT[member_type]))
     elif not is_member:
         total_base = math.ceil(total_base * FREE_USER_MULTIPLIER)
 
-    return total_base
+    return float(total_base)

packages/domain/points_service.py

@@ -13,7 +13,6 @@ from typing import Any
 from sqlalchemy.orm import Session
 
 from packages.domain.points_rules import (
-    DAILY_FREE_CLIP_LIMIT,
     POINTS_PACKAGES,
 )
 
@@ -84,7 +83,7 @@ class PointsService:
 
     # ──────────────── 余额检查 ────────────────
 
-    def check_balance(self, user_id: str, amount: int, db: Session) -> dict[str, Any]:
+    def check_balance(self, user_id: str, amount: float, db: Session) -> dict[str, Any]:
         """检查余额是否足够。"""
         account_data = self.get_or_create_account(user_id, db)
         balance = account_data["balance"]
@@ -100,7 +99,7 @@ class PointsService:
     def deduct_points(
         self,
         user_id: str,
-        amount: int,
+        amount: float,
         source: str,
         db: Session,
         description: str = "",
@@ -109,7 +108,7 @@ class PointsService:
         """扣减积分（事务性：SELECT FOR UPDATE → 检查余额 → 扣减 → 流水 → 同步用户表）。
 
         Returns:
-            {"success": True/False, "balance": int, "transaction_id": str|None}
+            {"success": True/False, "balance": float, "transaction_id": str|None}
         """
         PointsAccountModel, PointsTransactionModel, _, _, UserModel = _get_models()
 
@@ -173,7 +172,7 @@ class PointsService:
         except Exception:
             db.rollback()
             logger.exception(
-                "积分扣减失败: user_id=%s, amount=%d, source=%s",
+                "积分扣减失败: user_id=%s, amount=%.2f, source=%s",
                 user_id,
                 amount,
                 source,
@@ -185,7 +184,7 @@ class PointsService:
     def add_points(
         self,
         user_id: str,
-        amount: int,
+        amount: float,
         source: str,
         db: Session,
         description: str = "",
@@ -242,7 +241,7 @@ class PointsService:
         except Exception:
             db.rollback()
             logger.exception(
-                "积分增加失败: user_id=%s, amount=%d, source=%s",
+                "积分增加失败: user_id=%s, amount=%.2f, source=%s",
                 user_id,
                 amount,
                 source,
@@ -254,7 +253,7 @@ class PointsService:
     def refund_points(
         self,
         user_id: str,
-        amount: int,
+        amount: float,
         source: str,
         db: Session,
         ref_id: str = "",
@@ -270,6 +269,92 @@ class PointsService:
             ref_id=ref_id,
         )
 
+    # ──────────────── 爆款视频（viral_video）动态定价 ────────────────
+
+    def deduct_viral_video(self, user_id: str, credits: float, job_id: str, db: Session) -> dict[str, Any]:
+        """爆款视频预扣积分（confirm-copy 阶段）。"""
+        return self.deduct_points(
+            user_id=user_id,
+            amount=float(credits or 0),
+            source="viral_video",
+            db=db,
+            description="爆款视频生成",
+            ref_id=job_id,
+        )
+
+    def settle_viral_video(
+        self,
+        user_id: str,
+        estimated: float,
+        actual: float,
+        txn_id: str,
+        db: Session,
+    ) -> dict[str, Any]:
+        """爆款视频完成后按实际 tokens 结算（多退少补）。
+
+        - actual < estimated: 退差额
+        - actual > estimated: 补扣差额（余额不足时记 warning，不阻塞完成）
+        - |diff| < 0.01: 不动
+        """
+        diff = round(float(actual or 0) - float(estimated or 0), 2)
+        if abs(diff) < 0.01:
+            return {"success": True, "action": "none", "diff": 0.0}
+        if diff < 0:
+            refund = round(-diff, 2)
+            try:
+                res = self.refund_points(
+                    user_id=user_id,
+                    amount=refund,
+                    source="viral_video",
+                    db=db,
+                    ref_id=txn_id,
+                    description="爆款视频结算退费",
+                )
+                return {"success": bool(res.get("success")), "action": "refund", "diff": -refund, "amount": refund}
+            except Exception:
+                logger.exception("[viral_video] 结算退费异常 user_id=%s refund=%.2f", user_id, refund)
+                return {"success": False, "action": "refund", "diff": -refund}
+        else:
+            extra = round(diff, 2)
+            try:
+                res = self.deduct_points(
+                    user_id=user_id,
+                    amount=extra,
+                    source="viral_video",
+                    db=db,
+                    description="爆款视频结算补扣",
+                    ref_id=txn_id,
+                )
+                if not res.get("success"):
+                    logger.warning(
+                        "[viral_video] 结算补扣余额不足 user_id=%s extra=%.2f balance=%s (不阻塞任务完成)",
+                        user_id,
+                        extra,
+                        res.get("balance"),
+                    )
+                return {"success": bool(res.get("success")), "action": "deduct", "diff": extra, "amount": extra}
+            except Exception:
+                logger.exception("[viral_video] 结算补扣异常 user_id=%s extra=%.2f", user_id, extra)
+                return {"success": False, "action": "deduct", "diff": extra}
+
+    def refund_viral_video(self, user_id: str, credits: float, txn_id: str, db: Session) -> dict[str, Any]:
+        """爆款视频失败全额退款。"""
+        amount = float(credits or 0)
+        if amount <= 0:
+            return {"success": True, "action": "none", "amount": 0.0}
+        try:
+            return self.refund_points(
+                user_id=user_id,
+                amount=amount,
+                source="viral_video",
+                db=db,
+                ref_id=txn_id,
+                description="爆款视频失败退款",
+            )
+        except Exception:
+            logger.exception("[viral_video] 失败退款异常 user_id=%s amount=%.2f", user_id, amount)
+            return {"success": False, "action": "refund", "amount": amount}
+
     # ──────────────── 流水查询 ────────────────
 
     def get_transactions(
@@ -324,132 +409,16 @@ class PointsService:
             "page_size": page_size,
         }
 
-    # ──────────────── 每日免费混剪额度 ────────────────
-
-    def _daily_key(self, user_id: str) -> str:
-        """生成 Redis 每日额度 key。格式: daily_usage:{user_id}:{YYYYMMDD}:free_clip"""
-        today = datetime.now(UTC).strftime("%Y%m%d")
-        return f"daily_usage:{user_id}:{today}:free_clip"
-
-    def check_daily_free_clip(self, user_id: str, db: Session) -> bool:
-        """检查今日是否还有免费混剪额度。
-
-        优先查 Redis，Redis 不可用时降级到 DB。
-        """
-        redis_client = _get_redis_client()
-        if redis_client:
-            try:
-                key = self._daily_key(user_id)
-                current = redis_client.get(key)
-                if current is None:
-                    return True
-                return int(current) < DAILY_FREE_CLIP_LIMIT
-            except Exception:
-                logger.warning("Redis 不可用，降级到 DB 查询每日额度")
-
-        # 降级到 DB
-        _, _, _, DailyUsageRecordModel, _ = _get_models()
-        today_start = datetime.now(UTC).replace(hour=0, minute=0, second=0, microsecond=0)
-        record = (
-            db.query(DailyUsageRecordModel)
-            .filter(
-                DailyUsageRecordModel.user_id == user_id,
-                DailyUsageRecordModel.usage_type == "free_clip",
-                DailyUsageRecordModel.usage_date >= today_start,
-            )
-            .first()
-        )
-        if record is None:
-            return True
-        return record.count < DAILY_FREE_CLIP_LIMIT
-
-    def record_daily_free_clip(self, user_id: str, db: Session) -> bool:
-        """记录使用一次免费混剪。
-
-        先 INCR Redis；如果超限回退 Redis。DB 使用 upsert 语义（唯一约束）。
-        """
-        redis_client = _get_redis_client()
-        if redis_client:
-            try:
-                key = self._daily_key(user_id)
-                new_count = redis_client.incr(key)
-                if new_count == 1:
-                    redis_client.expire(key, 48 * 3600)  # TTL 48h
-                if new_count <= DAILY_FREE_CLIP_LIMIT:
-                    return True
-                # 超限，回退 Redis
-                redis_client.decr(key)
-            except Exception:
-                logger.warning("Redis 不可用，降级到 DB 记录每日额度")
-
-        # 降级/兜底到 DB（upsert 语义）
-        _, _, _, DailyUsageRecordModel, _ = _get_models()
-        today_start = datetime.now(UTC).replace(hour=0, minute=0, second=0, microsecond=0)
-
-        record = (
-            db.query(DailyUsageRecordModel)
-            .filter(
-                DailyUsageRecordModel.user_id == user_id,
-                DailyUsageRecordModel.usage_type == "free_clip",
-                DailyUsageRecordModel.usage_date >= today_start,
-            )
-            .first()
-        )
-
-        if record is None:
-            if DAILY_FREE_CLIP_LIMIT <= 0:
-                return False
-            record = DailyUsageRecordModel(
-                id=uuid.uuid4().hex,
-                user_id=user_id,
-                usage_type="free_clip",
-                usage_date=datetime.now(UTC),
-                count=1,
-            )
-            db.add(record)
-        else:
-            if record.count >= DAILY_FREE_CLIP_LIMIT:
-                return False
-            record.count += 1
-
-        db.commit()
-        return True
+    # ──────────────── 每日免费混剪额度（已下线：智能混剪全免费） ────────────────
 
     def get_daily_usage(self, user_id: str, db: Session) -> dict[str, Any]:
-        """查询今日免费额度使用情况。"""
-        redis_client = _get_redis_client()
-        used = 0
-
-        if redis_client:
-            try:
-                key = self._daily_key(user_id)
-                val = redis_client.get(key)
-                used = int(val) if val else 0
-            except Exception:
-                pass
-
-        if used == 0:
-            # 从 DB 查
-            _, _, _, DailyUsageRecordModel, _ = _get_models()
-            today_start = datetime.now(UTC).replace(hour=0, minute=0, second=0, microsecond=0)
-            record = (
-                db.query(DailyUsageRecordModel)
-                .filter(
-                    DailyUsageRecordModel.user_id == user_id,
-                    DailyUsageRecordModel.usage_type == "free_clip",
-                    DailyUsageRecordModel.usage_date >= today_start,
-                )
-                .first()
-            )
-            used = record.count if record else 0
-
+        """查询今日免费额度使用情况（智能混剪已全免费，返回 unlimited）。"""
         now = datetime.now(UTC)
         tomorrow = (now + timedelta(days=1)).replace(hour=0, minute=0, second=0, microsecond=0)
-
         return {
-            "free_clips_used": used,
-            "free_clips_limit": DAILY_FREE_CLIP_LIMIT,
-            "free_clips_remaining": max(0, DAILY_FREE_CLIP_LIMIT - used),
+            "free_clips_used": 0,
+            "free_clips_limit": -1,  # -1 表示 unlimited
+            "free_clips_remaining": -1,
             "reset_at": tomorrow.isoformat(),
         }
 

packages/domain/viral_video.py

@@ -0,0 +1,251 @@
+"""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)。
+"""
+
+from __future__ import annotations
+
+import sys
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+
+if sys.version_info >= (3, 11):
+    from enum import StrEnum
+else:
+    from enum import Enum
+
+    class StrEnum(str, Enum):
+        pass
+
+
+from uuid import uuid4
+
+
+class ViralVideoStatus(StrEnum):
+    PENDING = "pending"
+    RUNNING = "running"
+    IMAGE_ANALYZED = "image_analyzed"
+    COPY_GENERATED = "copy_generated"
+    WAIT_USER_CONFIRM = "wait_user_confirm"
+    COMPLETED = "completed"
+    FAILED = "failed"
+    CANCELLED = "cancelled"
+
+
+class ViralVideoStage(StrEnum):
+    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）
+    REVIEW = "review"
+    TTS = "tts"
+    RENDERING = "rendering"  # v1.6: 单次 Seedance 生成（BGM/音效/画面一次出片）
+    UPLOADING = "uploading"
+
+
+class FusionLevel(StrEnum):
+    AI_FULL = "ai_full"
+    AI_POLISH = "ai_polish"
+    USER_PRIMARY = "user_primary"
+
+
+class StyleStrength(StrEnum):
+    LIGHT = "light"
+    MEDIUM = "medium"
+    STRICT = "strict"
+
+
+class PromptType(StrEnum):
+    IMAGE_ANALYSIS = "image_analysis"
+    INTENT_PARSING = "intent_parsing"
+    SCRIPT_GENERATION = "script_generation"
+    REVIEW = "review"
+    VIDEO_STYLE_INTEGRATION = "video_style_integration"
+    STYLE_CONSTRAINT = "style_constraint"
+
+
+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.REVIEW: "合规审核",
+    ViralVideoStage.TTS: "AI 配音",
+    ViralVideoStage.RENDERING: "视频生成",
+    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）。"""
+
+    user_id: str
+    images: list[str] = field(default_factory=list)
+    industry: str = ""
+    target_customer: str = ""
+    persona_id: str = ""
+    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）
+    user_copy_text: str = ""
+    fusion_level: str = FusionLevel.AI_POLISH
+    reference_audio_path: str = ""
+    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
+    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
+    result_video_url: str = ""
+    video_resolution: str = "720p"
+    credits_prepaid: float = 0.0
+    credits_transaction_id: str = ""
+    credits_cost: float = 0.0
+    error_msg: str = ""
+    retry_count: int = 0
+    started_at: datetime | None = None
+    completed_at: datetime | None = None
+    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 --
+
+    def mark_running(self) -> None:
+        if self.status not in (
+            ViralVideoStatus.PENDING,
+            ViralVideoStatus.IMAGE_ANALYZED,
+            ViralVideoStatus.COPY_GENERATED,
+            ViralVideoStatus.WAIT_USER_CONFIRM,
+            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.updated_at = datetime.now(timezone.utc)
+
+    def mark_wait_user_confirm(self, intent_result: dict) -> None:
+        if self.status != ViralVideoStatus.RUNNING:
+            raise ValueError(f"Cannot transition from {self.status} to wait_user_confirm")
+        self.status = ViralVideoStatus.WAIT_USER_CONFIRM
+        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}")
+        self.status = ViralVideoStatus.RUNNING
+        self.updated_at = datetime.now(timezone.utc)
+
+    def mark_completed(self, video_url: str) -> None:
+        self.status = ViralVideoStatus.COMPLETED
+        self.result_video_url = video_url
+        self.completed_at = datetime.now(timezone.utc)
+        self.updated_at = datetime.now(timezone.utc)
+
+    def mark_failed(self, error_msg: str) -> None:
+        self.status = ViralVideoStatus.FAILED
+        self.error_msg = error_msg
+        self.completed_at = datetime.now(timezone.utc)
+        self.updated_at = datetime.now(timezone.utc)
+
+    def mark_cancelled(self) -> None:
+        if self.status in (ViralVideoStatus.COMPLETED, ViralVideoStatus.FAILED, ViralVideoStatus.CANCELLED):
+            raise ValueError(f"Cannot cancel task in {self.status} status")
+        self.status = ViralVideoStatus.CANCELLED
+        self.completed_at = datetime.now(timezone.utc)
+        self.updated_at = datetime.now(timezone.utc)
+
+    @property
+    def is_terminal(self) -> bool:
+        return self.status in (
+            ViralVideoStatus.COMPLETED,
+            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