fix: 修复 _storage_key 无法写入 EditPlanClip（slots=True）

EditPlanClip 使用 @dataclass(slots=True) 不允许动态添加属性，
改为将 _storage_key 存入 clip.config 字典，在 _resolve_clips
中传递到 ResolvedClip.config，gpu_direct_pipeline 从 config 读取。

.env.example

@@ -211,24 +211,10 @@ COSYVOICE_CLONE_MODEL=voice-enrollment
 # 用于 AI 文案生成、智能剪辑等需要大模型能力的场景
 
 DOUBAO_API_KEY=your-doubao-api-key
-DOUBAO_MODEL=doubao-seed-2-1-pro-260915
-DOUBAO_FAST_MODEL=doubao-seed-2-1-lite-260915
+DOUBAO_MODEL=doubao-seed-1-6-250615
 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-seed-2-1-pro-260915
-DOUBAO_VISION_LITE_MODEL=doubao-seed-2-1-lite-260915
-DOUBAO_VISION_USE_LITE=true
-# Embedding 向量化模型
-DOUBAO_EMBEDDING_MODEL=doubao-embedding-vision-251215
-# 视频模型（Seedance 2.5，统一走方舟；真人参考图通过信任链自动 AI 化）
-DOUBAO_VIDEO_MODEL=doubao-seedance-2-5-260628
-DOUBAO_VIDEO_TIMEOUT=480
-DOUBAO_VIDEO_POLL_INTERVAL=10
-# 图片模型（Seedream 5.0 Pro，用于信任链真人 AI 化 + 文生图）
-DOUBAO_IMAGE_MODEL=doubao-seedream-5-0-pro-260628
-DOUBAO_IMAGE_TIMEOUT=120
 
 # ==================== 积分/会员系统 (#1895) ====================
 # 积分系统总开关：默认 false（暂停积分系统）。

alembic/versions/086_add_viral_video_tables.py

@@ -1,100 +0,0 @@
-"""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

@@ -1,25 +0,0 @@
-"""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

@@ -1,51 +0,0 @@
-"""viral video add copy_result + voice/video columns
-
-Revision ID: 088_viral_video_copy_result
-Revises: 087_viral_video_image_analysis
-Create Date: 2026-10-01
-
-v1.6 爆款视频字段补齐：
-- copy_result JSON: 编导分镜脚本完整结构（overview/scene_and_lighting/shots/hard_constraints/negative_prompts/voiceover_script）
-- voice_id/voice_source: TTS 音色参数
-- video_ratio/video_model: Seedance 视频比例/模型
-注意：线上启动也有幂等 ADD COLUMN 补列逻辑 (_ensure_viral_video_columns)，本 migration 提供标准 Alembic 路径，
-两套机制互不冲突（IF NOT EXISTS 等价行为）。
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "088_viral_video_copy_result"
-down_revision = "087_viral_video_image_analysis"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # 幂等添加列（通过单独执行 + 异常忽略兼容已由 backfill 补上的环境）
-    cols = [
-        ("voice_id", "VARCHAR(200) NOT NULL DEFAULT ''"),
-        ("voice_source", "VARCHAR(20) NOT NULL DEFAULT ''"),
-        ("video_ratio", "VARCHAR(10) NOT NULL DEFAULT '9:16'"),
-        ("video_model", "VARCHAR(100) NOT NULL DEFAULT ''"),
-        ("copy_result", "JSON"),
-    ]
-    conn = op.get_bind()
-    for name, ddl in cols:
-        try:
-            conn.execute(sa.text(f"ALTER TABLE viral_video_jobs ADD COLUMN IF NOT EXISTS {name} {ddl}"))
-        except Exception:
-            # 不支持 IF NOT EXISTS 的库（如老版本 SQLite）直接尝试 ADD COLUMN，失败则忽略
-            try:
-                conn.execute(sa.text(f"ALTER TABLE viral_video_jobs ADD COLUMN {name} {ddl}"))
-            except Exception:
-                pass
-
-
-def downgrade() -> None:
-    for name in ("copy_result", "video_model", "video_ratio", "voice_source", "voice_id"):
-        try:
-            op.drop_column("viral_video_jobs", name)
-        except Exception:
-            pass

alembic/versions/089_viral_video_cols.py

@@ -1,62 +0,0 @@
-"""viral video add storyboard + generated_copy_text (complement 088)
-
-Revision ID: 089_viral_video_cols
-Revises: 088_viral_video_copy_result
-Create Date: 2026-10-01
-
-#2129 兜底迁移：补齐 _VIRAL_VIDEO_BACKFILL_COLS 中所有列，覆盖
-# watchtower 自动部署未跑历史 migration、且 AUTO_CREATE_SCHEMA=false 时
-# _ensure_viral_video_columns 未执行的场景。
-# 幂等 ADD COLUMN IF NOT EXISTS，已存在则跳过。
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "089_viral_video_cols"
-down_revision = "088_viral_video_copy_result"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # 扩展 alembic_version.version_num 字段长度（原来 VARCHAR(32) 装不下长 revision id）
-    conn = op.get_bind()
-    try:
-        conn.execute(sa.text("ALTER TABLE alembic_version ALTER COLUMN version_num TYPE VARCHAR(256)"))
-    except Exception:
-        pass
-    cols = [
-        ("storyboard", "JSON"),
-        ("generated_copy_text", "TEXT NOT NULL DEFAULT ''"),
-        ("voice_id", "VARCHAR(200) NOT NULL DEFAULT ''"),
-        ("voice_source", "VARCHAR(20) NOT NULL DEFAULT ''"),
-        ("video_ratio", "VARCHAR(10) NOT NULL DEFAULT '9:16'"),
-        ("video_model", "VARCHAR(100) NOT NULL DEFAULT ''"),
-        ("copy_result", "JSON"),
-    ]
-    for name, ddl in cols:
-        try:
-            conn.execute(sa.text(f"ALTER TABLE viral_video_jobs ADD COLUMN IF NOT EXISTS {name} {ddl}"))
-        except Exception:
-            try:
-                conn.execute(sa.text(f"ALTER TABLE viral_video_jobs ADD COLUMN {name} {ddl}"))
-            except Exception:
-                pass
-
-
-def downgrade() -> None:
-    for name in (
-        "copy_result",
-        "video_model",
-        "video_ratio",
-        "voice_source",
-        "voice_id",
-        "generated_copy_text",
-        "storyboard",
-    ):
-        try:
-            op.drop_column("viral_video_jobs", name)
-        except Exception:
-            pass

alembic/versions/090_viral_video_phase_msg.py

@@ -1,35 +0,0 @@
-"""viral video add phase_message column (#2134)
-
-Revision ID: 090_viral_video_phase_msg
-Revises: 089_viral_video_cols
-Create Date: 2026-10-02
-
-#2134 阶段细粒度提示：viral_video 表新增 phase_message 列（中文阶段提示文案）。
-current_stage 列已在之前版本存在，本迁移只补 phase_message。
-幂等 ADD COLUMN IF NOT EXISTS。
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "090_viral_video_phase_msg"
-down_revision = "089_viral_video_cols"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # SQLite/PostgreSQL 兼容的幂等添加列
-    conn = op.get_bind()
-    inspector = sa.inspect(conn)
-    cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
-    if "phase_message" not in cols:
-        op.add_column(
-            "viral_video_jobs",
-            sa.Column("phase_message", sa.String(length=500), nullable=False, server_default=""),
-        )
-
-
-def downgrade() -> None:
-    op.drop_column("viral_video_jobs", "phase_message")

alembic/versions/091_viral_video_stage.py

@@ -1,49 +0,0 @@
-"""viral video add current_stage column (#2137 follow-up)
-
-Revision ID: 091_viral_video_stage
-Revises: 090_viral_video_phase_msg
-Create Date: 2026-10-02
-
-#2137 follow-up fix: 090 migration missed current_stage column on viral_video_jobs,
-causing UndefinedColumn errors and 500s on all authenticated viral-video endpoints.
-Idempotently add current_stage and double-check phase_message.
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "091_viral_video_stage"
-down_revision = "090_viral_video_phase_msg"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    conn = op.get_bind()
-    inspector = sa.inspect(conn)
-    cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
-    if "current_stage" not in cols:
-        op.add_column(
-            "viral_video_jobs",
-            sa.Column(
-                "current_stage",
-                sa.String(length=200),
-                nullable=False,
-                server_default="",
-            ),
-        )
-    if "phase_message" not in cols:
-        op.add_column(
-            "viral_video_jobs",
-            sa.Column(
-                "phase_message",
-                sa.String(length=500),
-                nullable=False,
-                server_default="",
-            ),
-        )
-
-
-def downgrade() -> None:
-    op.drop_column("viral_video_jobs", "current_stage")

alembic/versions/092_viral_video_heartbeat.py

@@ -1,42 +0,0 @@
-"""viral_video_jobs 增加 heartbeat_at 列（worker 心跳，用于僵尸任务超时回收）
-
-Revision ID: 092_viral_video_heartbeat
-Revises: 091_viral_video_stage
-Create Date: 2026-10-02
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "092_viral_video_heartbeat"
-down_revision = "091_viral_video_stage"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    conn = op.get_bind()
-    inspector = sa.inspect(conn)
-    cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
-    if "heartbeat_at" not in cols:
-        op.add_column("viral_video_jobs", sa.Column("heartbeat_at", sa.DateTime(), nullable=True))
-        op.execute(
-            "UPDATE viral_video_jobs SET heartbeat_at = updated_at " "WHERE status = 'running' AND heartbeat_at IS NULL"
-        )
-        try:
-            op.create_index("ix_viral_video_jobs_heartbeat_at", "viral_video_jobs", ["heartbeat_at"])
-        except Exception:
-            pass
-
-
-def downgrade() -> None:
-    conn = op.get_bind()
-    inspector = sa.inspect(conn)
-    cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
-    if "heartbeat_at" in cols:
-        try:
-            op.drop_index("ix_viral_video_jobs_heartbeat_at", table_name="viral_video_jobs")
-        except Exception:
-            pass
-        op.drop_column("viral_video_jobs", "heartbeat_at")

alembic/versions/093_viral_video_pricing_points_float.py

@@ -1,87 +0,0 @@
-"""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

alembic/versions/094_viral_video_pre_trusted.py

@@ -1,31 +0,0 @@
-"""viral_video_jobs 增加 pre_trusted_images 列（信任链Seedream预热结果）
-
-Revision ID: 094_viral_video_pre_trusted
-Revises: 093_viral_video_pricing_points_float
-Create Date: 2026-10-04
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "094_viral_video_pre_trusted"
-down_revision = "093"
-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 "pre_trusted_images" not in cols:
-        op.add_column("viral_video_jobs", sa.Column("pre_trusted_images", sa.Text(), nullable=True))
-
-
-def downgrade() -> None:
-    conn = op.get_bind()
-    inspector = sa.inspect(conn)
-    cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
-    if "pre_trusted_images" in cols:
-        op.drop_column("viral_video_jobs", "pre_trusted_images")

alembic/versions/095_viral_video_prompt_templates.py

@@ -1,102 +0,0 @@
-"""爆款视频 Prompt 模板配置表（#2040）。
-
-086 曾预留同名旧表（id varchar / content / variables json），从未被业务使用；
-本迁移将其替换为 #2040 新结构。
-
-Revision ID: 095_viral_video_prompt_templates
-Revises: 094_viral_video_pre_trusted
-Create Date: 2026-10-04
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "095_viral_video_prompt_templates"
-down_revision = "094_viral_video_pre_trusted"
-branch_labels = None
-depends_on = None
-
-
-def _table_exists(conn, name: str) -> bool:
-    return name in sa.inspect(conn).get_table_names()
-
-
-def upgrade() -> None:
-    conn = op.get_bind()
-    # 086 预留的旧结构表：先删除（无业务数据、无任何引用）
-    if _table_exists(conn, "viral_video_prompt_templates"):
-        op.drop_table("viral_video_prompt_templates")
-
-    op.create_table(
-        "viral_video_prompt_templates",
-        sa.Column("id", sa.Integer, primary_key=True, autoincrement=True),
-        sa.Column("name", sa.String(128), nullable=False),
-        sa.Column("prompt_type", sa.String(32), nullable=False),
-        sa.Column("version", sa.Integer, nullable=False, server_default="1"),
-        sa.Column("system_prompt", sa.Text, nullable=False),
-        sa.Column("user_prompt_template", sa.Text, nullable=False),
-        sa.Column("example_output", sa.Text, nullable=True),
-        sa.Column("is_active", sa.Boolean, nullable=False, server_default=sa.text("true")),
-        sa.Column(
-            "created_at",
-            sa.DateTime(timezone=True),
-            server_default=sa.func.now(),
-            nullable=False,
-        ),
-        sa.Column(
-            "updated_at",
-            sa.DateTime(timezone=True),
-            server_default=sa.func.now(),
-            nullable=False,
-        ),
-    )
-    op.create_index(
-        "ix_vvpt_type_active",
-        "viral_video_prompt_templates",
-        ["prompt_type", "is_active"],
-    )
-    op.create_index(
-        "uq_vvpt_type_version",
-        "viral_video_prompt_templates",
-        ["prompt_type", "version"],
-        unique=True,
-    )
-
-
-def downgrade() -> None:
-    conn = op.get_bind()
-    if _table_exists(conn, "viral_video_prompt_templates"):
-        op.drop_index("uq_vvpt_type_version", table_name="viral_video_prompt_templates")
-        op.drop_index("ix_vvpt_type_active", table_name="viral_video_prompt_templates")
-        op.drop_table("viral_video_prompt_templates")
-
-    # 恢复 086 的旧预留结构
-    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(),
-        ),
-    )

apps/api/app/api/router.py

@@ -36,7 +36,6 @@ 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
@@ -241,4 +240,3 @@ 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

@@ -29,6 +29,8 @@ 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()
@@ -42,6 +44,7 @@ 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

@@ -27,6 +27,7 @@ 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
@@ -345,6 +346,7 @@ 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

@@ -11,7 +11,9 @@ 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,
 )
@@ -41,6 +43,7 @@ from packages.application import (
     GetGenerationTaskUseCase,
     ListGeneratedVideosByTaskUseCase,
 )
+from packages.middleware.points_gate import points_gate
 
 logger = logging.getLogger(__name__)
 
@@ -269,6 +272,7 @@ 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),
@@ -298,17 +302,26 @@ def create_preview_generation_task(
         count,
     )
 
-    # 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:
+    # 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:
         raise HTTPException(
             status_code=503,
-            detail=build_rate_limit_detail(
-                GlobalQueueFull(pending_count=global_pending + count, limit=GLOBAL_PENDING_LIMIT),
-                generation_task_repository,
-                scope="global",
-            ),
-        )
+            detail=build_rate_limit_detail(e, generation_task_repository, scope="global"),
+        ) from e
 
     # 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 ""
@@ -576,6 +589,9 @@ 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
@@ -587,6 +603,11 @@ 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

@@ -7,6 +7,7 @@ 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,
@@ -49,98 +50,12 @@ 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"},
 }
@@ -162,7 +77,7 @@ 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__)
 
@@ -278,13 +193,10 @@ 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)
@@ -464,6 +376,7 @@ 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),
@@ -681,13 +594,21 @@ 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（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。
+    # 预检查：批量提交前先看会不会超限，避免建一半才拒
     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,
@@ -1002,10 +923,14 @@ def create_generation_task(
                 else:
                     failed_tasks.append(task)
             except UserPendingLimitExceeded as _e:
-                # 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)
+                # 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
             except GlobalQueueFull as _e:
                 failed_tasks.append(task)
                 if not created_tasks:
@@ -1156,8 +1081,10 @@ def confirm_generation(
         ):
             logger.warning("[确认生成] 入队失败: task_id=%s", new_task.id)
     except UserPendingLimitExceeded as _e:
-        # 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")
+        raise HTTPException(
+            status_code=429,
+            detail=build_rate_limit_detail(_e, generation_task_repository, scope="user"),
+        ) from None
     except GlobalQueueFull as _e:
         raise HTTPException(
             status_code=503,
@@ -1336,8 +1263,22 @@ 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（Bug B #2098）：只保留全局 503，用户级不再硬拒
+    # 预检查：创建前判断，>= 上限就拒绝
+    user_pending = generation_task_repository.count_pending_by_user(user_id)
     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,
@@ -1380,8 +1321,10 @@ 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:
-        # 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")
+        raise HTTPException(
+            status_code=429,
+            detail=build_rate_limit_detail(_e, generation_task_repository, scope="user"),
+        ) from None
     except GlobalQueueFull as _e:
         raise HTTPException(
             status_code=503,

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

@@ -9,11 +9,6 @@ from fastapi.responses import JSONResponse
 router = APIRouter(tags=["Health"])
 
 
-
-def _pg_url(url: str) -> str:
-    """Convert SQLAlchemy URL (postgresql+psycopg://...) to libpq connection string."""
-    return url.replace("postgresql+psycopg://", "postgresql://", 1).replace("postgresql+psycopg2://", "postgresql://", 1)
-
 @router.get("/health", status_code=status.HTTP_200_OK)
 async def health_check():
     return {
@@ -54,7 +49,7 @@ async def _check_database() -> dict:
             "message": "Using in-memory database",
         }
     try:
-        conn = psycopg.connect(_pg_url(settings.DATABASE_URL), connect_timeout=3)
+        conn = psycopg.connect(settings.DATABASE_URL, connect_timeout=3)
         with conn.cursor() as cur:
             cur.execute("SELECT 1")
             cur.fetchone()
@@ -129,7 +124,7 @@ async def _check_migrations() -> dict:
             "message": "Using in-memory database, no migrations needed",
         }
     try:
-        conn = psycopg.connect(_pg_url(settings.DATABASE_URL), connect_timeout=3)
+        conn = psycopg.connect(settings.DATABASE_URL, connect_timeout=3)
         with conn.cursor() as cur:
             cur.execute("""
                 SELECT COUNT(*) FROM information_schema.tables
@@ -142,5 +137,3 @@ async def _check_migrations() -> dict:
         return {"status": "unhealthy", "message": f"Missing tables, found {count}/5"}
     except Exception as error:
         return {"status": "unhealthy", "message": f"Migration check failed: {error}"}
-
-

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

@@ -12,9 +12,11 @@
 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,
@@ -30,6 +32,9 @@ 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()
@@ -56,6 +61,37 @@ 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：
@@ -65,8 +101,6 @@ 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,
@@ -84,8 +118,18 @@ 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
@@ -101,11 +145,24 @@ 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
 
 
@@ -119,14 +176,37 @@ 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,
@@ -138,6 +218,11 @@ 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
@@ -152,6 +237,11 @@ 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

@@ -145,22 +145,19 @@ def get_rules(
 def get_packages(
     current_user: AuthenticatedUser = Depends(get_current_user),
 ):
-    """查询可购买的积分包列表（读管理后台 credit_packages 表真实数据）。
-
-    仅返回 is_active=true；后台改价/启停后最多 30 秒生效。
-    """
-    from packages.application.catalog.admin_catalog import get_points_packages
-
-    packages = [
-        PointsPackageItem(
-            code=row["code"],
-            name=row["name"],
-            points=row["points"],
-            price_cents=row["price_cents"],
-            unit_price=row["unit_price"],
+    """查询可购买的积分包列表。"""
+    packages = []
+    for code, pkg in POINTS_PACKAGES.items():
+        unit_price = f"¥{pkg['price_cents'] / 100 / pkg['points']:.3f}/积分"
+        packages.append(
+            PointsPackageItem(
+                code=code,
+                name=pkg["name"],
+                points=pkg["points"],
+                price_cents=pkg["price_cents"],
+                unit_price=unit_price,
+            )
         )
-        for row in get_points_packages()
-    ]
     mt = _member_type(current_user)
     discount = MEMBER_DISCOUNT.get(mt) if mt else None
     return PointsPackagesResponse(packages=packages, user_discount=discount)
@@ -172,7 +169,17 @@ 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。已下线/未知场景返回 cost=0（免费）。"""
+    """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()),
+            },
+        )
+
     # 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()
@@ -188,6 +195,13 @@ 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,
@@ -201,11 +215,11 @@ def check_points(
     balance = account["balance"]
 
     return PointsCheckResponse(
-        allowed=balance >= required,
+        allowed=is_free_quota or balance >= required,
         required_points=required,
         current_balance=balance,
         remaining_after=balance - required,
-        is_free_quota=False,
+        is_free_quota=is_free_quota,
     )
 
 

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

@@ -44,6 +44,7 @@ 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__)
@@ -372,6 +373,7 @@ 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),
@@ -495,6 +497,7 @@ 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),
@@ -534,6 +537,7 @@ 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/subscription.py

@@ -86,13 +86,33 @@ async def get_current_subscription(
 def list_membership_plans(
     current_user: AuthenticatedUser = Depends(get_current_user),
 ) -> dict[str, list[dict[str, Any]]]:
-    """查询可购买的会员套餐（读管理后台 plans 表真实数据）。
+    """查询所有会员档位（供前端会员购买页展示）。
 
-    仅返回 is_enabled=true 的套餐；后台启停/改价后最多 30 秒生效。
+    返回 points 积分体系下的会员档位（月卡/季卡/年卡），含价格、时长、积分折扣等信息。
     """
-    from packages.application.catalog.admin_catalog import get_membership_plans
+    from packages.domain.points_rules import MEMBER_DISCOUNT, MEMBERSHIP_PRICES
 
-    return {"plans": get_membership_plans()}
+    plans: list[dict[str, Any]] = []
+    for plan_id, info in MEMBERSHIP_PRICES.items():
+        days = info["duration_days"]
+        monthly_cents = round(info["price_cents"] * 30 / days)
+        features: dict[str, Any] = {"max_resolution": "1080p"}
+        if plan_id == MembershipType.MONTHLY:
+            features.update({"free_clips_daily": 2})
+        elif plan_id == MembershipType.QUARTERLY:
+            features.update({"free_clips_daily": 5})
+        elif plan_id == MembershipType.YEARLY:
+            features.update({"free_clips_daily": "unlimited"})
+        plans.append({
+            "plan_id": plan_id,
+            "name": info["name"],
+            "price_cents": info["price_cents"],
+            "monthly_price_cents": monthly_cents,
+            "duration_days": days,
+            "points_discount": MEMBER_DISCOUNT.get(plan_id, 1.0),
+            "features": features,
+        })
+    return {"plans": plans}
 
 
 @router.get("/billing-records", response_model=list[BillingRecord])

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

@@ -4,12 +4,14 @@ 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 (
@@ -51,6 +53,8 @@ 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
@@ -140,6 +144,31 @@ 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
@@ -202,6 +231,7 @@ def synthesize(
         cosyvoice_service=cosyvoice_service,
     )
 
+    synthesis_error: Exception | None = None
     try:
         job = workflow.start_synthesis(job.id)
     except Exception as e:
@@ -209,10 +239,18 @@ 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
@@ -231,6 +269,13 @@ 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,
@@ -565,6 +610,31 @@ 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)
@@ -594,6 +664,12 @@ 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

@@ -191,23 +191,6 @@ 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,
@@ -307,43 +290,6 @@ 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,
@@ -407,7 +353,6 @@ 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]
@@ -461,7 +406,6 @@ async def prepare_direct_upload(
         duplicated=False,
         skip_transfer=False,
         asset_id=pending_asset_id,
-        url="",
     )
 
 
@@ -500,25 +444,12 @@ async def complete_direct_upload(
         file_size=request.file_size,
     )
     if existing is not None:
-        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,
+        return DirectUploadCompleteResponse(
+            storage_key=existing.storage_key,
+            ingest_job_id="",
+            duplicated=True,
+            asset_id=existing.id,
+            url=storage_service.get_url(existing.storage_key),
         )
 
     try:
@@ -548,24 +479,14 @@ async def complete_direct_upload(
     )
     # Issue #1776: 计数由 asset_repository.create() 自动维护
 
-    # 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,
-        )
+    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,
@@ -612,27 +533,12 @@ async def upload_asset(
         file_size=0,
     )
     if existing is not None:
-        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,
+        return UploadAssetResponse(
+            storage_key=existing.storage_key,
+            ingest_job_id="",
+            url="",
+            duplicated=True,
+            asset_id=existing.id,
         )
 
     file_id = uuid4().hex[:8]
@@ -668,23 +574,14 @@ async def upload_asset(
     )
     # Issue #1776: 计数由 asset_repository.create() 自动维护
 
-    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,
-        )
+    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

@@ -1,980 +0,0 @@
-"""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.points_rules import list_viral_video_models
-from packages.domain.viral_video import ViralVideoStatus
-from packages.shared.dashscope_client import get_dashscope_client
-
-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("/models")
-def list_available_models() -> dict:
-    """返回爆款视频可用模型列表（供前端模型选择器使用）。"""
-    dashscope_available = get_dashscope_client() is not None
-    models = list_viral_video_models(
-        include_placeholder=False,
-        dashscope_available=dashscope_available,
-    )
-    return {"models": models}
-
-
-@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 = 20  # 单用户 pending 上限（#2098: 从 3 提到 20，支持批量任务自动排队）
+USER_PENDING_LIMIT = 3  # 单用户 pending 上限
 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）
 
@@ -154,18 +154,19 @@ 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）。
+    """检查队列限流（预检查用，任务创建前调用），超限抛对应异常。
 
-    #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。
+    边界语义：>= 上限即拒绝（达到上限就不能再加新任务）。
 
     Args:
-        user_id: 用户 ID（保留参数，当前不做用户级硬拒）
+        user_id: 用户 ID
         generation_task_repository: 任务仓储
-        user_pending_limit: 单用户 pending 上限（保留，当前未硬拒）
+        user_pending_limit: 单用户 pending 上限，默认 USER_PENDING_LIMIT
         global_pending_limit: 全局 pending 上限，默认 GLOBAL_PENDING_LIMIT
 
     Raises:
-        GlobalQueueFull: 全局超限时抛出
+        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
     """
     # 先查全局（系统级保护优先级更高）
     global_pending = generation_task_repository.count_pending_total()
@@ -178,9 +179,17 @@ def check_queue_limits(
         )
         raise GlobalQueueFull(pending_count=global_pending, limit=global_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。
+    # 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)
 
 
 def _mark_task_failed_safely(
@@ -237,6 +246,7 @@ 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） ──
 
@@ -253,18 +263,19 @@ def safe_enqueue_generation_task(
         _mark_task_failed_safely(task, generation_task_repository, log_prefix, str(exc))
         raise exc
 
-    # 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。
+    # 用户级限流检查（传了 user_id 才做）
     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 任务数超过软上限(入队): user_id=%s, count=%d/%d, 仍允许入队排队",
+                "[队列限流] 用户 pending 任务数超限(入队前): user_id=%s, count=%d/%d",
                 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:
@@ -306,18 +317,16 @@ 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
-    # 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,
-        )
+    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)
 
-    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.effective_database_url)
+ensure_database_exists(settings.DATABASE_URL)
 engine, SessionLocal = build_session_factory(
-    settings.effective_database_url,
+    settings.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.effective_database_url)
+_engine, _SessionLocal = build_session_factory(settings.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: 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")
+    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")
     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: float
-    balance_after: float
+    amount: int
+    balance_after: int
     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: float
-    current_balance: float
-    remaining_after: float
+    required_points: int
+    current_balance: int
+    remaining_after: int
     is_free_quota: bool = False
 
 
@@ -112,7 +112,7 @@ class PointsDeductRequest(BaseModel):
     """积分扣减请求"""
 
     scene_key: str
-    amount: float
+    amount: int
     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: float
+    points_balance: int
     max_resolution: str = Field(
         default="1080p",
         description="可用最高分辨率: 720p(free) / 1080p(paid)",

apps/api/app/schemas/upload.py

@@ -29,8 +29,6 @@ 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

@@ -1,319 +0,0 @@
-"""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

@@ -11,12 +11,14 @@
    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
@@ -30,10 +32,13 @@ 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"}
 
@@ -268,6 +273,24 @@ 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,
@@ -288,9 +311,19 @@ 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

@@ -150,8 +150,6 @@ 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

@@ -3,24 +3,9 @@
  */
 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
@@ -123,8 +108,6 @@ 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） */
@@ -136,17 +119,10 @@ 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
-  /** 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"
+  library_id: string
   /** 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 */
@@ -162,17 +138,9 @@ 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: resolvedLibraryId,
+    library_id: data.library_id,
     filename: data.file.name,
     content_type: data.file.type || "application/octet-stream",
     file_size: data.file.size,
@@ -181,13 +149,12 @@ 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: resolvedLibraryId,
+        library_id: data.library_id,
         storage_key: prepared.storage_key,
         file_hash: data.fileHash,
         client_upload_id: data.clientUploadId,
@@ -197,17 +164,10 @@ 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
- *
- * 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。
- */
+/** 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 */
 export const uploadAssetDirect = async (data: {
   file: File
-  /** 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"
+  library_id: string
   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
@@ -220,7 +180,6 @@ export const uploadAssetDirect = async (data: {
   const handle = await prepareDirectUploadHandle({
     file: data.file,
     library_id: data.library_id,
-    kind: data.kind,
     fileHash,
     clientUploadId,
   })
@@ -229,7 +188,7 @@ export const uploadAssetDirect = async (data: {
     return {
       storage_key: handle.prepared.storage_key,
       ingest_job_id: "",
-      url: handle.prepared.url || "",
+      url: "",
       duplicated: true,
       asset_id: handle.prepared.asset_id,
     }

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

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

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

@@ -1,156 +0,0 @@
-import apiClient from "@/api/client"
-import type {
-  GenerateViralVideoRequest,
-  HistoryResponse,
-  StyleTemplate,
-  ViralVideoJob,
-  ImageAnalysisResult,
-  CopyResult,
-  AnalyzeImagesRequest,
-  GenerateCopyRequest,
-  ConfirmCopyRequest,
-  ViralVideoModel,
-  ViralVideoModelsResponse,
-} 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)
-}
-
-/** 获取支持的视频模型列表（GET /viral-video/models）。后端返回 {models: [...]} 包装 */
-export function getViralVideoModels() {
-  return apiClient.get<ViralVideoModelsResponse>("/viral-video/models").then((r) => {
-    const data = r.data as ViralVideoModelsResponse | ViralVideoModel[] | null | undefined
-    if (Array.isArray(data)) return data
-    if (data && Array.isArray((data as ViralVideoModelsResponse).models)) {
-      return (data as ViralVideoModelsResponse).models
-    }
-    return []
-  })
-}
-/** ── 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

@@ -1,317 +0,0 @@
-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
-}
-
-/** 视频模型描述（GET /viral-video/models） */
-export interface ViralVideoModel {
-  key: string
-  display_name: string
-  supports_audio: boolean
-  supported_resolutions: string[]
-  max_duration: number
-  /** 计费模式（可选）：per_second / per_video / token 等 */
-  billing_mode?: string
-  is_default?: boolean
-}
-
-/** GET /viral-video/models 响应包装 */
-export interface ViralVideoModelsResponse {
-  models: ViralVideoModel[]
-}
-
-/** 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
-  /** 视频模型 key，覆盖默认 */
-  video_model?: 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

@@ -2,7 +2,6 @@
 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

@@ -18,7 +18,6 @@ import {
   ThunderboltOutlined,
   UnorderedListOutlined,
   UserOutlined,
-  FireOutlined,
 } from "@ant-design/icons"
 
 /** 导航项类型 */
@@ -77,12 +76,6 @@ 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",
@@ -149,12 +142,6 @@ 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

@@ -80,8 +80,6 @@ const AiAvatarPage: React.FC = () => {
   const [finalizeLoading, setFinalizeLoading] = useState(false)
 
   /* ── 对口型轮询 ── */
-  /** 对口型轮询总时长上限（10分钟）：超过后停止轮询并提示去历史记录查看 */
-  const LIPSYNC_POLL_MAX_MS = 10 * 60 * 1000
   const lipsyncTimerRef = useRef<ReturnType<typeof setInterval> | null>(null)
   /* ── 渲染进度轮询 ── */
   const renderTimerRef = useRef<ReturnType<typeof setInterval> | null>(null)
@@ -272,24 +270,7 @@ const AiAvatarPage: React.FC = () => {
       // 如果是预合成模式，后端会同步把状态置为 submitted（甚至可能已返回 running），
       // 但仍需轮询等 completed
       if (lipsyncTimerRef.current) clearInterval(lipsyncTimerRef.current)
-      // 轮询间隔 5 秒；单请求超时 5 分钟（见 api/aiAvatar.ts）；总轮询上限 10 分钟
-      // 单次请求失败/超时不中断轮询，继续下一轮；超过总上限后停止并提示用户去历史记录查看
       lipsyncTimerRef.current = setInterval(async () => {
-        // 总时长保护：超过 10 分钟停止轮询
-        if (Date.now() - lipsyncStartAtRef.current > LIPSYNC_POLL_MAX_MS) {
-          if (lipsyncTimerRef.current) {
-            clearInterval(lipsyncTimerRef.current)
-            lipsyncTimerRef.current = null
-          }
-          if (lipsyncTickRef.current) {
-            clearInterval(lipsyncTickRef.current)
-            lipsyncTickRef.current = null
-          }
-          setLipsyncStatus("failed")
-          setLipsyncErrorMessage("渲染时间较长，请稍后在历史记录中查看")
-          message.warning("对口型渲染时间较长，已停止自动刷新，请稍后在历史记录中查看")
-          return
-        }
         try {
           const updated = await getLipsyncJob(job.id)
           state.setLipsyncJob(updated)
@@ -315,10 +296,9 @@ const AiAvatarPage: React.FC = () => {
             setLipsyncErrorMessage(updated.error_message || "对口型生成失败")
           }
         } catch (err) {
-          // 单次轮询失败（含 timeout）：不中断轮询，打印日志后等下一轮
-          console.warn("[对口型] 轮询请求失败，将继续下一轮:", err)
+          console.error("[对口型] 轮询错误:", err)
         }
-      }, 5000)
+      }, 3000)
     } catch (err) {
       console.error("[对口型] 创建失败:", {
         status: (err as { response?: { status?: number } })?.response?.status,
@@ -600,6 +580,20 @@ 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/ai-avatar/api/aiAvatar.ts

@@ -72,8 +72,7 @@ export const previewTts = async (data: {
 }
 
 export const getLipsyncJob = async (id: string): Promise<LipsyncJob> => {
-  // MuseTalk 渲染 8s 视频约 54s + 排队时间，给足 5 分钟超时避免单次轮询 AxiosError 中断
-  const response = await apiClient.get<LipsyncJob>(`/lipsync/jobs/${id}`, { timeout: 300_000 })
+  const response = await apiClient.get<LipsyncJob>(`/lipsync/jobs/${id}`, { timeout: 60000 })
   return response.data
 }
 
@@ -92,10 +91,7 @@ export const submitRender = async (data: {
 }
 
 export const getRenderJob = async (jobId: string): Promise<RenderJob> => {
-  // 渲染链路（对口型+B-roll+标题+合成+上传）耗时较长，给足 5 分钟超时
-  const response = await apiClient.get<RenderJob>(`/ai-avatar/render/${jobId}`, {
-    timeout: 300_000,
-  })
+  const response = await apiClient.get<RenderJob>(`/ai-avatar/render/${jobId}`, { timeout: 60000 })
   return response.data
 }
 

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

@@ -13,6 +13,8 @@ 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"
@@ -86,6 +88,7 @@ const GeneratePage: React.FC = () => {
     style,
     autoSubtitles,
     bgm,
+    editPlanId,
     sourceEditPlanId,
     previewTaskId,
     setPreviewTaskId,
@@ -236,14 +239,9 @@ const GeneratePage: React.FC = () => {
     voiceModePerVideo,
     variantCoverUrls: previewCovers,
     selectedVariantIndexes: isBatch ? selectedVariantIds : undefined,
-    onGenerationSuccess: (status?: "completed" | "awaiting_cover") => {
+    onGenerationSuccess: () => {
       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)
-      }
     },
   })
 
@@ -520,6 +518,10 @@ 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

@@ -11,12 +11,7 @@
  *   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,
-  ClockCircleOutlined,
-} from "@ant-design/icons"
+import { LoadingOutlined, CheckCircleFilled, CloseCircleOutlined } from "@ant-design/icons"
 import type { BatchTaskState } from "../hooks/generate-video/useGenerationPolling"
 import type { GeneratedVideo } from "@/api/template-editor"
 
@@ -66,11 +61,6 @@ 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"
@@ -95,21 +85,6 @@ 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

@@ -12,7 +12,6 @@ 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"
@@ -152,12 +151,6 @@ export const GenerateStepContent: React.FC<GenerateStepContentProps> = (props) =
     selectedCoverTemplate,
     onSelectedCoverTemplateChange,
     onConfirmGenerate,
-    selectedVoice,
-    onSelectedVoiceChange,
-    voiceModePerVideo,
-    onVoiceModePerVideoChange,
-    voiceLibraryIds,
-    onVoiceLibraryIdsChange,
   } = props
 
   switch (currentStep) {
@@ -191,46 +184,32 @@ 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
-            }
-          />
-          {/* 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}
-          />
-        </>
+        <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
+          }
+        />
       )
     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（两列布局 #2096） ── */
+        /* ── 批量：N 个独立标题输入框 ── */
         <div className="xx-batch-titles">
           <div
             style={{
@@ -170,25 +170,17 @@ 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>
 
-          <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>
+          {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>
       )}
 

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 } from "@/api/assets"
+import { uploadAssetDirect, getAssetLibraries } from "@/api/assets"
 
 interface Step6CoverSettingsProps {
   coverSettings: CoverConfig
@@ -176,8 +176,15 @@ const Step6CoverSettings: React.FC<Step6CoverSettingsProps> = (props) => {
           thumbnail_url: previewUrl,
           mode: "upload",
         })
-        // 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" })
+        // 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 })
         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）；status=awaiting_cover 表示需进封面选择 */
-  onGenerationSuccess?: (status?: "completed" | "awaiting_cover") => void
+  /** 生成成功后的回调（用于清除持久化的 previewTaskId 等状态） */
+  onGenerationSuccess?: () => 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, useEffect } from "react"
+import { useRef, useCallback, useState } 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" | "queued"
+  status: "running" | "completed" | "awaiting_cover" | "failed"
   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[], taskStatus?: "completed" | "awaiting_cover") => void
+  onComplete: (videos: unknown[]) => 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
@@ -31,19 +31,13 @@ const MAX_RETRYABLE_ERRORS = 10
 const MAX_RESULTS_RETRIES = 3
 
 /**
- * 生成状态轮询 Hook（v5 — awaiting_cover 状态识别 + visibilitychange 恢复 + 状态透传）
+ * 生成状态轮询 Hook（v4 — 批量任务独立状态 + 单任务重试）
  *
  * 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,
@@ -55,15 +49,12 @@ 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 */
@@ -122,7 +113,6 @@ 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) {
@@ -138,7 +128,6 @@ 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 ||
@@ -149,7 +138,6 @@ 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) {
@@ -161,20 +149,16 @@ 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))
@@ -185,18 +169,6 @@ 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)
       })
@@ -209,22 +181,12 @@ export function useGenerationPolling({
     (taskId: string) => {
       cancelledRef.current = false
       batchContextRef.current.clear()
-      let resolvedStatus: "completed" | "awaiting_cover" = "completed"
-      pollSingleTask(taskId, 0, {
-        onTaskProgress: (pct) => onProgress(pct),
-        onTaskCompleted: (videos, taskStatus) => {
-          resolvedStatus = taskStatus ?? "completed"
-          onProgress(100)
-          onComplete(videos, resolvedStatus)
-        },
-        onTaskFailed: (msg) => onFailed(msg),
-      })
-        .then(() => {
+      pollSingleTask(taskId, 0)
+        .then((videos) => {
           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！")
-          }
+          onProgress(100)
+          onComplete(videos)
+          message.success("视频生成完成！")
         })
         .catch((err: Error) => {
           if (cancelledRef.current) return
@@ -239,7 +201,7 @@ 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(
@@ -249,7 +211,6 @@ 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 = () => {
@@ -264,9 +225,7 @@ export function useGenerationPolling({
         if (resultMap.size === tasks.length) {
           onProgress(100)
           const ordered = tasks.map((t) => resultMap.get(t.taskId) || []).flat()
-          // 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")
+          onComplete(ordered)
           message.success(`全部 ${tasks.length} 个视频生成完成！`)
         } else if (resultMap.size > 0) {
           // 部分失败：成功的视频聚合进成片列表（可进封面），失败卡片带重试按钮
@@ -275,8 +234,7 @@ export function useGenerationPolling({
             .filter((t) => resultMap.has(t.taskId))
             .map((t) => resultMap.get(t.taskId) || [])
             .flat()
-          const anyAwaiting = Array.from(statusMap.values()).some((s) => s === "awaiting_cover")
-          onComplete(ordered, anyAwaiting ? "awaiting_cover" : "completed")
+          onComplete(ordered)
           message.warning(
             `${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`,
           )
@@ -305,7 +263,6 @@ 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()
@@ -352,64 +309,5 @@ export function useGenerationPolling({
     [pollSingleTask, onBatchTaskUpdate],
   )
 
-  /**
-   * 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 }
+  return { startPolling, startPollingBatch, 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 } from "@/api/assets"
+import { uploadAssetDirect, getAssetLibraries } 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） */
@@ -182,9 +182,15 @@ 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,
-          kind: "image",
+          library_id: imageLib.id,
         })
         const url = result?.url || ""
         if (url) {

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

@@ -2,12 +2,10 @@
  * 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, useRef } from "react"
+import { useState, useCallback, useEffect } 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"
@@ -15,28 +13,6 @@ 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
 
@@ -46,29 +22,11 @@ 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 || []
@@ -95,10 +53,9 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
 
   const handleProgress = useCallback((p: number) => setProgress(p), [])
   const handleComplete = useCallback(
-    (videos: unknown[], taskStatus?: "completed" | "awaiting_cover") => {
+    (videos: unknown[]) => {
+      setGenerating(false)
       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) =>
@@ -113,35 +70,26 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
             : t,
         ),
       )
-      onGenerationSuccess?.(finalStatus)
+      onGenerationSuccess?.()
     },
     [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。
-     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。 */
+     按变体索引排序，供步骤6封面按勾选顺序逐个取视频 */
   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 === "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
+      if (
+        t.status === "completed" ||
+        (t.status === "awaiting_cover" && t.videos && t.videos.length > 0)
+      ) {
+        byVariant.set(t.variantIndex, t.videos[0] as GeneratedVideo)
       }
     })
     const ordered = [...byVariant.entries()].sort((a, b) => a[0] - b[0]).map(([, v]) => v)
@@ -151,185 +99,17 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
       }
       return ordered
     })
-    if (allDone && !hasQueued && !hasRunning) {
-      setGenerating(false)
-      if (hasSuccess) {
-        setGenerated(true)
-        setCompletionStatus("awaiting_cover")
-      }
-    }
   }, [batchTasks])
 
-  const { startPolling, pollBatchTaskQueued, retryTask, clearTimer } = useGenerationPolling({
+  const { startPolling, startPollingBatch, 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（含排队中）；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；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) {
@@ -337,28 +117,34 @@ 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 {
-      // from-assets 兜底：片段不存在则补一次
+      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。
       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 {
@@ -366,185 +152,221 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
         }
       }
 
-      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")
-          }
+      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 {
           setCurrentTaskId(taskIds[0])
           startPolling(taskIds[0])
-        } catch (err) {
-          hide()
-          throw err
         }
-        return true
+      } catch (err) {
+        hide()
+        throw err
       }
-
-      /* ── 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
     }
-  }, [
-    props,
-    clearTimer,
-    startPolling,
-    selectedTemplate,
-    buildBasePayload,
-    handleBatchTaskUpdate,
-    clearQueueTimers,
-    pollBatchTaskQueued,
-  ])
+    return true
+  }, [props, clearTimer, startPolling, startPollingBatch, selectedTemplate])
 
   const retry = useCallback(() => {
     setGenerateError(null)
@@ -554,10 +376,9 @@ 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, handleBatchTaskUpdate],
+    [retryTask],
   )
 
   const dismissError = useCallback(() => {
@@ -602,7 +423,6 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
     generated,
     generateError,
     generatedVideos,
-    completionStatus,
     currentTaskId,
     generate,
     retry,

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

@@ -45,11 +45,6 @@ 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

@@ -1,263 +0,0 @@
-/**
- * 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" onClick={onClose}>
-              取消
-            </button>
-            <button
-              className="vv-btn vv-btn-primary"
-              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

@@ -1,355 +0,0 @@
-/**
- * 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

@@ -1,74 +0,0 @@
-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

@@ -1,26 +1,25 @@
 import { useState, useCallback } from "react"
 import { useMutation, useQueryClient } from "@tanstack/react-query"
 import { message } from "antd"
-import { uploadAssetDirect, getIngestJob, type AssetLibraryItem } from "@/api/assets"
+import {
+  uploadAssetDirect,
+  getAssetLibraries,
+  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: _createLibMutation,
-}: UseVoiceUploadOptions) {
+export function useVoiceUpload({ voiceLibrary, createLibMutation }: UseVoiceUploadOptions) {
   const queryClient = useQueryClient()
   const [uploadProgress, setUploadProgress] = useState<number | null>(null)
 
@@ -34,12 +33,24 @@ export function useVoiceUpload({
     }) => {
       setUploadProgress(0)
       try {
-        // 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
+        // 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）
         const complete = await uploadAssetDirect({
           file: data.file,
-          library_id: voiceLibrary?.id,
-          kind: "voice",
+          library_id: lib.id,
           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, getIngestJob } from "@/api/assets"
+import { uploadAssetDirect, getAssetLibraries, getIngestJob } from "@/api/assets"
 
 /**
  * 配音上传 Hook
@@ -23,10 +23,18 @@ export function useVoiceUpload({ showToast }: UseVoiceUploadProps) {
     mutationFn: async (data: { file: File; name: string; description: string }) => {
       setUploadProgress(0)
       try {
-        /* 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） */
+        /* 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） */
         const complete = await uploadAssetDirect({
           file: data.file,
-          kind: "voice",
+          library_id: lib.id,
           onProgress: (p) => setUploadProgress(p),
         })
 

apps/web/src/router/appRoutes.tsx

@@ -52,10 +52,6 @@ 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

@@ -1,45 +0,0 @@
-import { describe, it, expect } from "vitest"
-import { getErrorMessage, isErrorMsgShown } from "@/api/errors"
-
-describe("api/errors", () => {
-  it("returns string error directly", () => {
-    expect(getErrorMessage("plain")).toBe("plain")
-  })
-  it("uses Error.message", () => {
-    expect(getErrorMessage(new Error("boom"))).toBe("boom")
-  })
-  it("returns fallback for empty/unknown", () => {
-    expect(getErrorMessage(null)).toBe("操作失败，请稍后重试")
-    expect(getErrorMessage(undefined, "f")).toBe("f")
-  })
-  it("reads axios-like response.data.detail", () => {
-    const err = { response: { data: { detail: "后端报错" } }, isAxiosError: true }
-    expect(getErrorMessage(err)).toContain("后端报错")
-  })
-  it("reads axios-like response.data.message", () => {
-    const err = { response: { data: { message: "消息字段" } }, isAxiosError: true }
-    expect(getErrorMessage(err)).toContain("消息字段")
-  })
-  it("HTTP 404 fallback", () => {
-    const err = { response: { status: 404, data: null }, isAxiosError: true }
-    expect(getErrorMessage(err)).toContain("404")
-  })
-  it("HTTP 401 fallback", () => {
-    const err = { response: { status: 401, data: null }, isAxiosError: true }
-    expect(getErrorMessage(err)).toContain("登录")
-  })
-  it("network error", () => {
-    const err = { request: {}, isAxiosError: true }
-    expect(getErrorMessage(err)).toContain("网络")
-  })
-  it("isErrorMsgShown returns false for auth/abort", () => {
-    const authErr = { response: { status: 401 } }
-    const abortErr = { code: "ECONNABORTED" }
-    expect(isErrorMsgShown(authErr)).toBe(false)
-    expect(isErrorMsgShown(abortErr)).toBe(false)
-    const e: any = new Error("x")
-    e.__msgShown = true
-    expect(isErrorMsgShown(e)).toBe(true)
-    expect(isErrorMsgShown(new Error("x"))).toBe(false)
-  })
-})

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

@@ -1,226 +0,0 @@
-import { describe, expect, it, vi, beforeEach, afterEach } from "vitest"
-import {
-  generateViralVideo,
-  getViralVideoJob,
-  confirmViralVideoIntent,
-  retryViralVideo,
-  getViralVideoHistory,
-  getViralStyleTemplates,
-  analyzeViralStyle,
-  mockImageAnalysis,
-  mockGenerateCopy,
-  analyzeViralImages,
-  generateViralCopy,
-  confirmViralCopy,
-} from "@/api/viral-video"
-import {
-  VALID_DURATIONS,
-  VALID_RATIOS,
-  isVideoStage,
-  isImageAnalysisStage,
-  isCopyStage,
-  isAnalysisStage,
-} from "@/api/viral-video/types"
-
-const mockGet = vi.fn()
-const mockPost = vi.fn()
-
-vi.mock("@/api/client", () => ({
-  default: {
-    get: (...args: unknown[]) => mockGet(...args),
-    post: (...args: unknown[]) => mockPost(...args),
-  },
-}))
-
-vi.mock("antd", () => ({ message: { error: vi.fn(), success: vi.fn() } }))
-
-// 让 setTimeout 同步执行，避免测试等待 1.8s/2.2s
-beforeEach(() => {
-  vi.useFakeTimers()
-  vi.clearAllMocks()
-  mockGet.mockResolvedValue({ data: {} })
-  mockPost.mockResolvedValue({ data: {} })
-})
-afterEach(() => {
-  vi.useRealTimers()
-})
-
-describe("viral-video constants & stage helpers", () => {
-  afterEach(() => {
-    vi.useRealTimers()
-  })
-  beforeEach(() => {
-    vi.useFakeTimers()
-    vi.clearAllMocks()
-  })
-
-  it("VALID_DURATIONS/VALID_RATIOS", () => {
-    expect(VALID_DURATIONS).toEqual([5, 10, 15, 20, 25, 30])
-    expect(VALID_RATIOS).toEqual(expect.arrayContaining(["9:16", "16:9", "1:1"]))
-  })
-
-  it("isVideoStage", () => {
-    expect(isVideoStage("tts")).toBe(true)
-    expect(isVideoStage("rendering")).toBe(true)
-    expect(isVideoStage("uploading")).toBe(true)
-    expect(isVideoStage("script_generation")).toBe(false)
-    expect(isVideoStage("completed")).toBe(false)
-    expect(isVideoStage(undefined)).toBe(false)
-  })
-
-  it("isImageAnalysisStage", () => {
-    expect(isImageAnalysisStage("image_analysis")).toBe(true)
-    expect(isImageAnalysisStage("video_analysis")).toBe(true)
-    expect(isImageAnalysisStage("script_generation")).toBe(false)
-    expect(isImageAnalysisStage(undefined)).toBe(false)
-  })
-
-  it("isCopyStage", () => {
-    expect(isCopyStage("intent_parsing")).toBe(true)
-    expect(isCopyStage("script_generation")).toBe(true)
-    expect(isCopyStage("review")).toBe(true)
-    expect(isCopyStage("tts")).toBe(false)
-  })
-
-  it("isAnalysisStage is union", () => {
-    expect(isAnalysisStage("image_analysis")).toBe(true)
-    expect(isAnalysisStage("script_generation")).toBe(true)
-    expect(isAnalysisStage("tts")).toBe(false)
-    expect(isAnalysisStage(undefined)).toBe(false)
-  })
-})
-
-describe("viral-video API wrappers", () => {
-  afterEach(() => {
-    vi.useRealTimers()
-  })
-  beforeEach(() => {
-    vi.useFakeTimers()
-    vi.clearAllMocks()
-    mockGet.mockResolvedValue({ data: {} })
-    mockPost.mockResolvedValue({ data: {} })
-  })
-
-  it("generateViralVideo", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j1" } })
-    const r = generateViralVideo({ images: ["img1"] } as never)
-    vi.runAllTimersAsync()
-    expect(await r).toEqual({ id: "j1" })
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/generate", { images: ["img1"] })
-  })
-
-  it("getViralVideoJob", async () => {
-    mockGet.mockResolvedValue({ data: { id: "j2" } })
-    const r = getViralVideoJob("j2")
-    vi.runAllTimersAsync()
-    expect(await r).toEqual({ id: "j2" })
-    expect(mockGet).toHaveBeenCalledWith("/viral-video/j2")
-  })
-
-  it("confirmViralVideoIntent", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j3" } })
-    const r = confirmViralVideoIntent("j3", { confirmed_copy: "hi" })
-    vi.runAllTimersAsync()
-    await r
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/j3/confirm-intent", {
-      confirmed_copy: "hi",
-    })
-  })
-
-  it("retryViralVideo", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j4" } })
-    await retryViralVideo("j4")
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/j4/retry")
-  })
-
-  it("getViralVideoHistory", async () => {
-    mockGet.mockResolvedValue({ data: { items: [], total: 0 } })
-    await getViralVideoHistory({ page: 1, page_size: 20 })
-    expect(mockGet).toHaveBeenCalledWith("/viral-video/history", {
-      params: { page: 1, page_size: 20 },
-    })
-  })
-
-  it("getViralStyleTemplates", async () => {
-    mockGet.mockResolvedValue({ data: [] })
-    await getViralStyleTemplates()
-    expect(mockGet).toHaveBeenCalledWith("/viral-video/style-templates")
-  })
-
-  it("analyzeViralStyle", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j5" } })
-    await analyzeViralStyle("j5")
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/j5/analyze-style")
-  })
-
-  it("analyzeViralImages", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j6" } })
-    await analyzeViralImages({ images: ["a.png"] } as never)
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/analyze-images", { images: ["a.png"] })
-  })
-
-  it("generateViralCopy", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j7" } })
-    await generateViralCopy("j7", { duration: 15 } as never)
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/j7/generate-copy", { duration: 15 })
-  })
-
-  it("confirmViralCopy", async () => {
-    mockPost.mockResolvedValue({ data: { id: "j8" } })
-    await confirmViralCopy("j8", { edited_copy: "xxx" })
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/j8/confirm-copy", { edited_copy: "xxx" })
-    mockPost.mockClear()
-    await confirmViralCopy("j8")
-    expect(mockPost).toHaveBeenCalledWith("/viral-video/j8/confirm-copy", {})
-  })
-})
-
-describe("viral-video client mocks", () => {
-  beforeEach(() => {
-    vi.useFakeTimers()
-    vi.clearAllMocks()
-  })
-  afterEach(() => {
-    vi.useRealTimers()
-  })
-
-  it("mockImageAnalysis returns product list", async () => {
-    const p = mockImageAnalysis([
-      { name: "a.png" },
-      { name: "b.jpg" },
-      { name: "c.webp" },
-      { name: "d.png" },
-    ])
-    vi.advanceTimersByTime(2000)
-    const r = await p
-    expect(r.products).toHaveLength(3)
-    expect(r.products[0].image_index).toBe(0)
-    expect(r.products[0].brand).toBe("示例品牌")
-    expect(r.products[1].spec).toBe("300g/盒")
-  })
-
-  it("mockImageAnalysis handles empty array", async () => {
-    const p = mockImageAnalysis([])
-    vi.advanceTimersByTime(2000)
-    const r = await p
-    expect(r.products).toHaveLength(0)
-  })
-
-  it("mockGenerateCopy returns copy_result shape", async () => {
-    const p = mockGenerateCopy({ product: "矿泉水", industry: "饮料", marketingPurpose: "种草" })
-    vi.advanceTimersByTime(3000)
-    const r = await p
-    expect(r.title).toContain("种草")
-    expect(r.title).toContain("矿泉水")
-    expect(r.final_copy.length).toBeGreaterThan(50)
-    expect(r.suggested_copy).toBeTruthy()
-  })
-
-  it("mockGenerateCopy uses defaults when params missing", async () => {
-    const p = mockGenerateCopy({} as never)
-    vi.advanceTimersByTime(3000)
-    const r = await p
-    expect(r.title).toContain("品牌种草")
-    expect(r.final_copy).toContain("这款产品")
-  })
-})

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

@@ -1,21 +0,0 @@
-import { describe, it, expect } from "vitest"
-import { getGenerationPhase } from "@/pages/generate/hooks/generate-video/phase"
-
-describe("getGenerationPhase", () => {
-  it("returns 分析素材与配置 for p<20", () => {
-    expect(getGenerationPhase(0)).toEqual({ label: "分析素材与配置", icon: "🔍" })
-    expect(getGenerationPhase(19).label).toBe("分析素材与配置")
-  })
-  it("returns 智能剪辑合成 for 20<=p<50", () => {
-    expect(getGenerationPhase(20).label).toBe("智能剪辑合成")
-    expect(getGenerationPhase(49).label).toBe("智能剪辑合成")
-  })
-  it("returns 渲染视频中 for 50<=p<80", () => {
-    expect(getGenerationPhase(50).label).toBe("渲染视频中")
-    expect(getGenerationPhase(79).label).toBe("渲染视频中")
-  })
-  it("returns 即将完成 for p>=80", () => {
-    expect(getGenerationPhase(80)).toEqual({ label: "即将完成", icon: "✨" })
-    expect(getGenerationPhase(100).label).toBe("即将完成")
-  })
-})

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

@@ -1,26 +0,0 @@
-import { describe, it, expect, vi, afterEach } from "vitest"
-import { formatDuration, formatFileSize, formatDate } from "@/pages/products/detailUtils"
-
-describe("products/detailUtils", () => {
-  afterEach(() => {
-    vi.useRealTimers()
-  })
-  it("formatDuration", () => {
-    expect(formatDuration(0)).toBe("00:00")
-    expect(formatDuration(-1)).toBe("00:00")
-    expect(formatDuration(5)).toBe("00:05")
-    expect(formatDuration(65)).toBe("01:05")
-    expect(formatDuration(3600)).toBe("60:00")
-  })
-  it("formatFileSize MB/GB", () => {
-    expect(formatFileSize(0)).toBe("-")
-    expect(formatFileSize(-1)).toBe("-")
-    expect(formatFileSize(5.3)).toBe("5.3 MB")
-    expect(formatFileSize(2048)).toBe("2.00 GB")
-  })
-  it("formatDate returns zh-CN format", () => {
-    vi.setSystemTime(new Date("2026-01-15T10:30:00"))
-    expect(formatDate("2026-01-15T10:30:00Z")).toMatch(/2026/)
-    expect(formatDate("")).toBe("-")
-  })
-})

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

@@ -1,54 +0,0 @@
-import { describe, it, expect, beforeEach, vi, afterEach } from "vitest"
-import { renderHook, act } from "@testing-library/react"
-import { useViralVideoPolling } from "@/pages/viral-video/hooks/useViralVideoPolling"
-
-const getViralVideoJobMock = vi.fn()
-vi.mock("@/api/viral-video", () => ({
-  getViralVideoJob: (...args: unknown[]) => getViralVideoJobMock(...args),
-}))
-
-describe("useViralVideoPolling", () => {
-  beforeEach(() => {
-    vi.clearAllMocks()
-    vi.useFakeTimers()
-  })
-  afterEach(() => {
-    vi.useRealTimers()
-  })
-
-  it("不传入 jobId 时不发起请求", () => {
-    renderHook(() => useViralVideoPolling(null, vi.fn()))
-    expect(getViralVideoJobMock).not.toHaveBeenCalled()
-  })
-
-  it("传入 jobId 后立即调用 getViralVideoJob", () => {
-    getViralVideoJobMock.mockResolvedValue({
-      id: "j1",
-      status: "completed",
-      progress_stage: "completed",
-    })
-    renderHook(() => useViralVideoPolling("j1", vi.fn()))
-    expect(getViralVideoJobMock).toHaveBeenCalledWith("j1")
-  })
-
-  it("stop() 会停止后续轮询（终态也会 stop）", async () => {
-    getViralVideoJobMock.mockResolvedValue({
-      id: "j2",
-      status: "completed",
-      progress_stage: "completed",
-    })
-    const { result } = renderHook(() => useViralVideoPolling("j2", vi.fn(), { intervalMs: 50 }))
-    // 等第一次 promise 完成
-    await act(async () => {
-      await Promise.resolve()
-      await Promise.resolve()
-    })
-    // 终态后不会再调度新请求
-    const calls = getViralVideoJobMock.mock.calls.length
-    act(() => {
-      vi.advanceTimersByTime(2000)
-    })
-    expect(getViralVideoJobMock).toHaveBeenCalledTimes(calls)
-    expect(result.current.stop).toBeTypeOf("function")
-  })
-})

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

@@ -1,35 +0,0 @@
-import { describe, it, expect } from "vitest"
-import {
-  genderLabel,
-  languageLabel,
-  genderClass,
-  formatTime,
-  formatFileSize,
-} from "@/pages/voices/utils/format"
-
-describe("voices utils/format", () => {
-  it("genderLabel returns label or falls back to value", () => {
-    expect(genderLabel("female")).toContain("女")
-    expect(genderLabel("male")).toContain("男")
-    expect(genderLabel("unknown" as never)).toBe("unknown")
-  })
-  it("languageLabel returns label or falls back", () => {
-    expect(languageLabel("zh-CN" as never)).toBeTruthy()
-    expect(languageLabel("xx-XX" as never)).toBe("xx-XX")
-  })
-  it("genderClass returns css class", () => {
-    expect(genderClass("female")).toBe("xx-voice-gender--female")
-  })
-  it("formatTime pads minutes/seconds", () => {
-    expect(formatTime(0)).toBe("00:00")
-    expect(formatTime(5)).toBe("00:05")
-    expect(formatTime(65)).toBe("01:05")
-    expect(formatTime(3600)).toBe("60:00")
-  })
-  it("formatFileSize human-readable", () => {
-    expect(formatFileSize(0)).toBe("0 B")
-    expect(formatFileSize(512)).toBe("512 B")
-    expect(formatFileSize(2048)).toBe("2.0 KB")
-    expect(formatFileSize(2 * 1024 * 1024)).toBe("2.0 MB")
-  })
-})

apps/web/vitest.config.ts

@@ -28,12 +28,11 @@ export default defineConfig({
         "src/pages/editing-planner/EditingPlanner.tsx",
         "src/pages/assets/AssetLibrary.tsx",
         "src/pages/voice-materials/VoiceMaterialLibrary.tsx",
-        "src/pages/viral-video/ViralVideoPage.tsx",
       ],
       // CI 覆盖率门禁（Phase 4 后提升，逐步逼近目标）
       // 当前实际：行 ~62% / 分支 ~61% / 函数 ~25%
       thresholds: {
-        lines: 49,
+        lines: 50,
         branches: 50,
         functions: 20,
       },

apps/worker/video_processing/concat_engine.py

@@ -553,20 +553,7 @@ def concat_video_files(
     if work_dir is None:
         work_dir = output_path.parent
 
-    # 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))
-
+    segments = [ConcatSegment(video_path=p) for p in video_paths if p]
     config = ConcatConfig(segments=segments, force_reencode=force_reencode)
 
     engine = ConcatEngine(work_dir)

apps/worker/video_processing/gpu_direct_pipeline.py

@@ -3,8 +3,8 @@
 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。
+一步完成 trim/scale/pad/concat/边缘裁剪/drawtext 字幕，末端 h264_nvenc 只编码一次；
+TTS/BGM 音频也在同一命令里 amix 合成。
 
 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。
@@ -15,53 +15,21 @@
 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
+# drawtext 默认字体名（fontconfig 解析）；P4000 装好中文字体后可在 config 指定
+DEFAULT_DRAWTEXT_FONT = "sans"
 
 
 def escape_drawtext_text(text: str) -> str:
+    """转义 drawtext text= 中的特殊字符（ffmpeg 过滤器语法）。"""
     if not text:
         return ""
+    # 顺序重要：先转义反斜杠本身
     s = text.replace("\\", "\\\\")
     s = s.replace(":", "\\:")
     s = s.replace("'", "\\'")
@@ -69,185 +37,11 @@ def escape_drawtext_text(text: str) -> str:
     s = s.replace(",", "\\,")
     s = s.replace("[", "\\[").replace("]", "\\]")
     s = s.replace(";", "\\;")
+    # 换行保留（drawtext 支持 %{...}；真实换行需转成字面）
     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,
@@ -264,18 +58,21 @@ def build_drawtext_filter(
     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。"""
+    """构造单个 drawtext 滤镜字符串（不含输入/输出标签）。
+
+    [start, end] 秒的显示窗口通过 enable='between(t,...)' 控制。
+    """
     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)}")
+    parts.append(f"fontcolor={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"bordercolor={border_color}")
     parts.append(f"x={x_expr}")
     parts.append(f"y={y_expr}")
     if enable:
@@ -283,29 +80,18 @@ def build_drawtext_filter(
     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
+    """把本地音频（TTS/BGM）上传 OSS tmp 目录并签公网 GET URL。
+
+    Returns:
+        (signed_get_url, oss_key)
+    """
+    from video_processing.oss_helpers import _storage  # 类型: ignore
 
     storage = _storage()
     key = f"{tmp_prefix.rstrip('/')}/{uuid.uuid4().hex}{local_audio.suffix or '.mp3'}"
@@ -316,24 +102,23 @@ def upload_local_audio_and_sign(
 
 
 def sign_asset_url(storage_key: str, *, expires: int = 3600) -> str:
-    from video_processing.oss_helpers import _storage  # type: ignore
+    """给原始素材 storage_key 签公网 GET URL（供 P4000 直接下载）。"""
+    from video_processing.oss_helpers import _storage  # 类型: ignore
 
     storage = _storage()
     return storage.get_download_url(storage_key, expires)
 
 
+# ── 直连渲染编排器 ────────────────────────────────────────────────────────
+
+
 class DirectRenderPlan:
-    def __init__(
-        self,
-        inputs: dict[str, str],
-        ffmpeg_args: list[str],
-        oss_keys: list[str],
-        filter_complex: list[str] | None = None,
-    ):
+    """一次直连渲染的产物：inputs（裸文件名→URL）与完整 ffmpeg_args。"""
+
+    def __init__(self, inputs: dict[str, str], ffmpeg_args: list[str], oss_keys: list[str]):
         self.inputs = inputs
         self.ffmpeg_args = ffmpeg_args
-        self.oss_keys = oss_keys
-        self.filter_complex: list[str] = filter_complex or []
+        self.oss_keys = oss_keys  # 本次上传的临时音频 key（供事后清理）
 
 
 def build_direct_render(
@@ -353,19 +138,11 @@ def build_direct_render(
     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。
+    视频：每段 trim/setpts/scale/pad/fps → concat（全硬切）→ 可选边缘 crop+scale → drawtext。
+    音频：concat 时丢弃原生音轨（只映射 [vfinal]），TTS/BGM 上传签名后 amix 混音。
     """
     if not resolved_clips:
         raise ValueError("build_direct_render: no resolved clips")
@@ -373,446 +150,143 @@ def build_direct_render(
     inputs: dict[str, str] = {}
     oss_keys: list[str] = []
     input_args: list[str] = []
-    fc: list[str] = []
+    fc: list[str] = []  # filter_complex 各段
+
     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")
+            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
+    # 2. 每个视频段预处理
     pre_labels: list[str] = []
-    for i in range(n):
-        vf: list[str] = []
-        start, eff, speed = clip_starts[i], clip_effs[i], clip_speeds[i]
+    for i, clip in enumerate(resolved_clips):
+        filters: list[str] = []
+        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)
         if eff > 0:
             if start > 0:
-                vf.append(f"trim=start={start:.3f}:duration={eff:.3f}")
+                filters.append(f"trim=start={start:.3f}:duration={eff:.3f}")
             else:
-                vf.append(f"trim=duration={eff:.3f}")
-            vf.append("setpts=PTS-STARTPTS")
+                filters.append(f"trim=duration={eff:.3f}")
+            filters.append("setpts=PTS-STARTPTS")
+
+        speed = float(getattr(clip, "playback_speed", 1.0) or 1.0)
         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}")
+            filters.append(f"setpts=PTS/{speed:.4f}")
+
+        filters.append(f"scale={output_width}:{output_height}:force_original_aspect_ratio=decrease")
+        filters.append(f"pad={output_width}:{output_height}:trunc((ow-iw)/2):trunc((oh-ih)/2):black")
+        filters.append("setpts=PTS-STARTPTS")
+        filters.append(f"fps={output_fps}")
+
         label = f"vc{i}"
-        fc.append(f"[{i}:v]{','.join(vf)}[{label}]")
+        fc.append(f"[{i}:v]{','.join(filters)}[{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
+    # 3. concat（全硬切；原生音频丢弃，v=1:a=0）
+    concat_in = "".join(f"[{l}]" for l in pre_labels)
+    fc.append(f"{concat_in}concat=n={n}:v=1:a=0[vcat]")
+    cur = "vcat"
 
-        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）
+    # 4. 边缘裁剪降重（合并进同一条，不再单独重编码）
     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"
+        p = float(edge_crop_pct)
+        keep = 1.0 - 2.0 * p
+        cw_expr = f"trunc(iw*{keep:.4f}/2)*2"
+        ch_expr = f"trunc(ih*{keep:.4f}/2)*2"
         fc.append(
-            f"[{cur_v}]crop=w='{w_expr}':h='{h_expr}':x='{x_expr}':y='{y_expr}',"
+            f"[{cur}]crop=w='{cw_expr}':h='{ch_expr}':x='(iw-{cw_expr})/2':y='(ih-{ch_expr})/2',"
             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)))
+        cur = "vcrop"
 
+    # 5. drawtext 字幕（标题整段 + ASR 逐句）
     draw_filters: list[str] = []
-    if t_enabled and t_text:
-        draw_filters.extend(
-            _build_drawtext_filters(
-                text=t_text,
+    if title_text.strip():
+        title_size = max(int(output_height * 0.05), 24)
+        draw_filters.append(
+            build_drawtext_filter(
+                text=title_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,
+                font=font,
+                font_size=title_size,
+                y_expr="h-th-40",
+                box=True,
             )
         )
-    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,
-                )
+    sub_size = max(int(output_height * 0.045), 20)
+    for seg in subtitle_segments or []:
+        txt = getattr(seg, "text", "") or ""
+        if not txt.strip():
+            continue
+        draw_filters.append(
+            build_drawtext_filter(
+                text=txt,
+                start=float(getattr(seg, "start", 0)),
+                end=float(getattr(seg, "end", 0)),
+                font=font,
+                font_size=sub_size,
+                y_expr="h-th-60",
+                borderw=2,
             )
+        )
 
     if draw_filters:
-        prev = cur_v
+        prev = cur
         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]")
+        fc.append(f"[{cur}]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]
+    # 6. 音频输入与混音
+    audio_items: list[tuple[int, float]] = []  # (input_index, volume)
     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)
+        audio_items.append((next_idx, 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 {}
+    if bgm_audio and Path(bgm_audio).exists():
         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)
+        audio_items.append((next_idx, 0.35))
         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]")
+    if audio_items:
+        mix_labels: list[str] = []
+        for k, (idx, vol) in enumerate(audio_items):
+            alabel = f"au{k}"
+            fc.append(
+                f"[{idx}:a]aresample=44100,volume={vol:.2f},"
+                f"aformat=sample_fmts=fltp:channel_layouts=stereo[{alabel}]"
+            )
+            mix_labels.append(alabel)
+        mix_in = "".join(f"[{l}]" for l in mix_labels)
+        fc.append(
+            f"{mix_in}amix=inputs={len(mix_labels)}:duration=first:dropout_transition=2,"
+            f"aresample=44100[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]
@@ -821,11 +295,6 @@ def build_direct_render(
         ffmpeg_args.extend(["-b:v", video_bitrate])
     else:
         ffmpeg_args.extend(["-cq", str(cq)])
-    ffmpeg_args.extend(["-movflags", "+faststart", "-shortest", "-f", "mp4", "pipe:1"])
+    ffmpeg_args.extend(["-movflags", "+faststart", "-f", "mp4", "pipe:1"])
 
-    return DirectRenderPlan(
-        inputs=inputs,
-        ffmpeg_args=ffmpeg_args,
-        oss_keys=oss_keys,
-        filter_complex=fc,
-    )
+    return DirectRenderPlan(inputs=inputs, ffmpeg_args=ffmpeg_args, oss_keys=oss_keys)

apps/worker/video_processing/render_adapter.py

@@ -86,7 +86,6 @@ 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:
@@ -132,7 +131,6 @@ 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。
 
@@ -218,7 +216,6 @@ 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:
@@ -394,7 +391,7 @@ class RenderAdapter:
 
         return asset_path_map, rendered_clip_ids, failed_clip_ids, asset_storage_map
 
-    def _prepare_bgm(self, plan, work_dir: Path, plan_id: str, *, bgm_override: dict | None = None) -> str | None:
+    def _prepare_bgm(self, plan, work_dir: Path, plan_id: str) -> 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）：
@@ -407,9 +404,7 @@ class RenderAdapter:
         from urllib.parse import urlparse
 
         plan_config = plan.config 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
+        bgm_config = plan_config.get("bgm", {}) or {}
 
         if not bgm_config.get("enabled", False):
             return None
@@ -465,27 +460,13 @@ class RenderAdapter:
                 from packages.domain.preset_bgm import get_preset_bgm
 
                 preset = get_preset_bgm(preset_id)
-                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:
+                if preset and preset.audio_url:
                     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 url=%s",
-                        plan_id,
-                        preset_id,
-                        preset.audio_url[:80],
-                    )
+                    logger.info("[plan_id=%s] [BGM] 从预设库下载: preset_id=%s", plan_id, preset_id)
                     safe_download_file(
                         preset.audio_url,
                         str(bgm_file),
@@ -498,14 +479,7 @@ 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（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",
-        )
+        logger.warning("[plan_id=%s] [BGM] 所有来源都无法获取BGM，跳过", plan_id)
         return None
 
     @staticmethod
@@ -571,7 +545,6 @@ class RenderAdapter:
         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）。
 
@@ -585,9 +558,8 @@ class RenderAdapter:
         Returns:
             RenderAdapterResult
         """
-        # 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)
+        # 1. 准备 BGM
+        bgm_path = self._prepare_bgm(plan, work_dir, plan_id)
 
         self._report_progress(progress_cb, 40.0, "执行视频渲染")
 
@@ -595,10 +567,8 @@ class RenderAdapter:
         plan_config = plan.config or {}
         asr_service = self._get_asr_service()
 
-        # 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"])
+        # 3. 读取输出分辨率
+        export_config = plan_config.get("export", {}) or {}
         if not isinstance(export_config, dict):
             export_config = {}
         output_width, output_height = _parse_resolution(export_config.get("resolution"))
@@ -623,7 +593,6 @@ 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 {}
@@ -636,9 +605,6 @@ class RenderAdapter:
                 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:
@@ -684,22 +650,8 @@ 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="",
-                clip_boundaries=_clip_boundaries,
+                str(result.output_path), plan_id, task_id=job_id, num_frames=5, title_text=""
             )
             if cover_candidates:
                 logger.info(
@@ -746,7 +698,6 @@ 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

@@ -1,11 +1,6 @@
 """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。
 
-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
+统一封面管道：
 - 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。
 """
@@ -13,14 +8,14 @@
 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,
@@ -32,7 +27,11 @@ 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）。"""
+    """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。
+    """
     from packages.shared.title_overlay import apply_title_to_image
 
     if not title_text or not title_text.strip():
@@ -57,19 +56,26 @@ 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（ffmpeg -ss 单帧 seek，<100ms/帧）。
+    """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。
 
     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/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
+        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
     """
     from video_processing.ffmpeg_utils import FFMPEG_BIN, probe_duration, run_ffmpeg
 
@@ -81,25 +87,31 @@ def extract_first_frame(
         _is_temp_output = True
 
     try:
-        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
+        # 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
 
+        # 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，极快），-vframes 1 只取一帧
+        # -ss 放在 -i 前面（input seeking，更快）
+        # -vframes 1 只取一帧
+        # -q:v 2 jpeg 高质量
         cmd = [
             FFMPEG_BIN,
             "-y",
@@ -142,6 +154,7 @@ 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)
@@ -151,6 +164,7 @@ 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
@@ -163,7 +177,19 @@ 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。"""
+    """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
+    """
     from video_processing.oss_helpers import upload_to_oss
 
     tmp = tempfile.NamedTemporaryFile(suffix=".jpg", delete=False)
@@ -178,303 +204,24 @@ 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（fallback 路径，默认不启用）。"""
+    """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
+    """
     import uuid
 
-    from video_processing.oss_helpers import delete_from_oss, get_signed_download_url, upload_to_oss
+    from video_processing.oss_helpers import get_signed_download_url, upload_to_oss
 
     from packages.shared.mediakit_client import get_mediakit_client
 
@@ -484,37 +231,47 @@ def _extract_frames_via_mediakit(
         return None
 
     video_storage_key: str = ""
+    # 1. 上传视频到 OSS，并生成预签名下载 URL（bucket 私有读，公网 URL 会 403）
     try:
         video_storage_key = f"temp/{plan_id}/{uuid.uuid4().hex[:8]}_{Path(video_path).name}"
         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
+        # MediaKit 从公网拉取视频，必须使用预签名 URL；签名 1h 足够完成抽帧
         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，降级到本地 ffmpeg", e)
+        logger.warning("[thumbnail] 视频上传 OSS 异常: %s，降级到 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,
+            max_frames=num_frames * 2,  # 多取一些帧供选择
         )
         if not frames:
-            logger.warning("[thumbnail] MediaKit 抽帧返回空")
+            logger.warning("[thumbnail] MediaKit 抽帧返回空，降级到 ffmpeg")
             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", e)
+        logger.warning("[thumbnail] MediaKit 抽帧异常: %s，降级到 ffmpeg", 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
@@ -525,235 +282,161 @@ def extract_and_upload_cover_frames(
     plan_id: str,
     *,
     task_id: str = "",
-    num_frames: int = 5,
+    num_frames: int = 5,  # 抽 5 帧候选，通过质量评分选出最佳帧
     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。
 
-    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）。
+    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
 
     Args:
-        clip_boundaries: 片段边界列表 [(clip_start, clip_duration), ...]，用于智能取点
-    """
-    import time
+        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}
+    """
     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] = []
+    _temp_paths: list[str] = []  # 收集所有临时文件路径，最后统一清理
 
     try:
-        settings = get_shared_settings()
-        use_mediakit = getattr(settings, "mediakit_cover_enabled", False)
+        # ── 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)
 
-        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)
-
-        # ── 默认路径：本地 ffmpeg 单次 select 抽帧 + 并发上传 ──────────────
-        if len(candidates) < num_frames:
-            if candidates:
-                logger.info("[thumbnail] MediaKit 不足 %d 帧，本地 ffmpeg 补充", num_frames)
-            else:
-                logger.info(
-                    "[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:
+                    # 叠加标题文字（如需要）
                     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),
+                        apply_title_overlay(
+                            tmp.name,
+                            title_text,
+                            color=title_color,
+                            position=title_position,
+                            font_size=title_font_size,
                         )
-                    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 {
+                    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": st,
-                                "image_path": fp,
-                                "score": score,
-                                "is_best": rank == 0,
+                                "position": round(seek_time, 2),
+                                "image_path": tmp.name,
                             }
-                        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
+                        )
+                except Exception as e:
+                    logger.warning("[thumbnail] MediaKit 帧 %d 处理失败: %s", i, e)
 
-                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)
+            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)
 
-                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)
+        # Fallback: ffmpeg 直接抽帧（仅当 MediaKit 不足时）
+        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)
 
-        # 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。
+        # ── 阶段 2：质量评分 ────────────────────────────────────────────
         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
+            try:
+                from packages.shared.cover_frame_scorer import score_frames
+
+                candidates = score_frames(candidates)
                 logger.info(
-                    "[thumbnail] 封面完成: plan_id=%s count=%d best=t%.2fs score=%.1f elapsed=%.2fs",
+                    "[thumbnail] 封面帧质量评分完成: plan_id=%s count=%d best_score=%.1f",
                     plan_id,
                     len(candidates),
-                    candidates[0].get("position", 0.0),
-                    candidates[0].get("score", 0.0),
-                    elapsed,
+                    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,
                 )
 
+        # ── 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

@@ -112,7 +112,6 @@ 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 ──────────────────────────────────────────────
@@ -158,7 +157,6 @@ 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
@@ -171,9 +169,6 @@ 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)
@@ -184,28 +179,6 @@ 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）。"""
@@ -260,7 +233,7 @@ 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}:contrast={mt.contrast:.4f}:saturation={mt.saturation:.4f}"
+                f"eq=brightness={mt.brightness:+.4f}:" f"contrast={mt.contrast:.4f}:saturation={mt.saturation:.4f}"
             )
 
     @staticmethod
@@ -376,8 +349,7 @@ class UnifiedRenderService:
             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])
+        if direct_result is not None:
             # 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(
@@ -388,14 +360,12 @@ class UnifiedRenderService:
                 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
@@ -457,7 +427,7 @@ 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._effective_config()
+                config = self.plan.config or {}
                 bgm_config = config.get("bgm", {}) or {}
                 if bgm_config.get("enabled", False):
                     ctx = RenderContext(work_dir=self.work_dir, plan_id=self.plan.id)
@@ -497,7 +467,7 @@ class UnifiedRenderService:
                             "[unified-render] pass-through BGM mix failed, skipping: plan_id=%s", self.plan.id
                         )
         else:
-            config = self._effective_config()
+            config = self.plan.config or {}
             bgm_config = config.get("bgm", {}) or {}
             if not isinstance(bgm_config, dict):
                 bgm_config = {}
@@ -722,7 +692,7 @@ class UnifiedRenderService:
         Returns:
             ASS 文件路径，没有字幕时返回 None
         """
-        config = self._effective_config()
+        config = self.plan.config or {}
         # #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():
@@ -907,7 +877,7 @@ class UnifiedRenderService:
         Returns:
             是否成功添加了配音音轨
         """
-        config = self._effective_config()
+        config = self.plan.config or {}
         tts_cfg = config.get("tts", {}) or {}
         if not isinstance(tts_cfg, dict):
             tts_cfg = {}
@@ -1782,6 +1752,11 @@ class UnifiedRenderService:
                         trim_config=seg.trim,
                     )
                     resolved.append(rc)
+                # 传递存储键（GPU直连管线需要，从 EditPlanClip.config 读取）
+                _sk = (clip.config or {}).get("_storage_key")
+                if _sk:
+                    for seg_rc in resolved[-len(resolved_segments):]:
+                        seg_rc.config["_storage_key"] = _sk
                 continue
 
             # 单段裁剪（或无裁剪）
@@ -1855,6 +1830,10 @@ class UnifiedRenderService:
                 actual_duration=actual_duration,
                 trim_config=effective_trim,
             )
+            # 传递存储键（GPU直连管线需要，从 EditPlanClip.config 读取）
+            _sk = (clip.config or {}).get("_storage_key")
+            if _sk:
+                rc.config["_storage_key"] = _sk
             resolved.append(rc)
 
             # Debug日志：记录每个clip的时长信息
@@ -2247,7 +2226,7 @@ class UnifiedRenderService:
             if not bool(cfg.get("gpu_direct_enabled", True)):
                 return False
 
-            video_layers = [_lyr for _lyr in layers if _lyr.role not in ("audio",)]
+            video_layers = [l for l in layers if l.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
@@ -2291,148 +2270,62 @@ class UnifiedRenderService:
         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)。"""
+    ) -> bool | None:
+        """尝试全 GPU 直连渲染。成功返回 True，不支持/失败返回 None（调用方走旧链路）。"""
         if not self._can_use_gpu_direct(layers):
-            return (None, False)
+            return None
         if not self._gpu_encode_available():
-            return (None, False)
+            return None
 
         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",))
+            cfg = self.plan.config or {}
+            video_layer = next(l for l in layers if l.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：把 audio 层的 TTS 片段合并成一个文件给 P4000
             tts_merged: Path | None = None
-            voiceover_track: Path | None = None
+            audio_layer = next((l for l in layers if l.role == "audio"), None)
             if audio_layer:
-                tts_clips = [c for c in audio_layer.clips if (c.config or {}).get("tts") and c.local_path.exists()]
+                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
+            # 字幕：标题 + ASR 时间轴
             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):
+            if isinstance(title_cfg, dict) and 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):
+            sub_cfg = cfg.get("subtitle", {}) or {}
+            if isinstance(sub_cfg, dict) and 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）
+            # 边缘裁剪比例（与 random_edge_crop 默认 2~5% 同口径，取固定 3%）
             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))
+            edge_pct = 0.03 if dedup else 0.0
 
             plan = gdp.build_direct_render(
                 resolved_clips=video_clips,
                 output_width=self.output_width,
                 output_height=self.output_height,
                 output_fps=self.output_fps,
+                tts_audio=tts_merged,
                 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()
@@ -2447,11 +2340,8 @@ class UnifiedRenderService:
                 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)
+            logger.info("[gpu-direct] success: plan_id=%s clips=%d", self.plan.id, len(video_clips))
+            return True
 
         except GpuEncodeError as e:
             logger.warning("[gpu-direct] failed (fallback to legacy): %s", e)
@@ -2460,10 +2350,10 @@ class UnifiedRenderService:
                     output_path.unlink()
             except OSError:
                 pass
-            return (None, False)
+            return None
         except Exception:  # noqa: BLE001
             logger.warning("[gpu-direct] unexpected error (fallback)", exc_info=True)
-            return (None, False)
+            return None
 
     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）。"""
@@ -2906,7 +2796,7 @@ 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

@@ -1,33 +0,0 @@
-"""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

@@ -1,961 +0,0 @@
-"""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

@@ -38,7 +38,6 @@ 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/generation.py

@@ -198,7 +198,7 @@ def _verify_url_accessible(
     retries: int = 2,
     max_redirects: int = 5,
 ) -> bool:
-    """GET+Range 请求校验 URL 可访问（含重试，防止 OSS 抖动误报）。
+    """HEAD 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）
@@ -255,12 +255,11 @@ def _verify_url_accessible(
                 )
                 raise
 
-            req = urllib.request.Request(safe_url, method="GET")
-            req.add_header("Range", "bytes=0-0")
+            req = urllib.request.Request(safe_url, method="HEAD")
             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 or resp.status == 206:
+                if 200 <= resp.status < 300:
                     return True
                 if resp.status in (301, 302, 303, 307, 308):
                     location = resp.headers.get("Location", "")
@@ -616,49 +615,69 @@ def _precompute_render_metadata(
 # ── Celery Task ──────────────────────────────────────────────────────────────
 
 
-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。
+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）。
 
-    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。
+    包括：title_config、BGM、输出分辨率。配音单独处理（需下载到本地）。
     """
-    import copy
+    from packages.adapters.sqlalchemy_impl.edit_plan_repository import (
+        SQLAlchemyEditPlanRepository,
+    )
 
-    override: dict = {}
+    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
 
-    # 标题配置（字段名归一化）
+    plan_config = dict(plan.config or {})
+    changed = False
+
+    # 标题配置
     title_config = task_info.get("title_config") or {}
-    if isinstance(title_config, dict) and title_config:
-        cfg = copy.deepcopy(title_config)
+    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 "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"]
-        override["title"] = cfg
+        plan_config["title"] = cfg
+        changed = True
+        logger.info("[task] title_config synced to plan: %s", cfg.get("text", "")[:30])
 
     # BGM 配置
     bgm_config = task_info.get("bgm_config") or {}
-    if isinstance(bgm_config, dict) and bgm_config:
-        override["bgm"] = copy.deepcopy(bgm_config)
+    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
 
     # 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:
-        override["export"] = {"resolution": f"{ow}x{oh}"}
+        export_cfg = dict(plan_config.get("export", {}) or {})
+        export_cfg["resolution"] = f"{ow}x{oh}"
+        plan_config["export"] = export_cfg
+        changed = True
 
-    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
+    if changed:
+        plan.config = plan_config
+        plan_repo.update(plan)
+        logger.info("[task] plan.config synced: plan_id=%s", source_edit_plan_id)
 
+    # 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):
@@ -674,24 +693,19 @@ 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, bool]:
+) -> tuple[Path, float, list[dict] | None, str | None, str | None, str]:
     """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, edge_crop_applied)
+        (output_path, render_duration, cover_candidates, voiceover_path, temp_dir, thumbnail_url)
     """
     from video_processing.render_adapter import RenderAdapter
     from worker_app.db import SessionLocal
 
     db = SessionLocal()
     try:
-        # 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)
+        # 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)
 
         # 进度回调
         def _progress_cb(progress: float, stage: str):
@@ -707,7 +721,6 @@ 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:
@@ -733,7 +746,6 @@ def _render_from_edit_plan(
             voiceover_path,
             render_temp_dir,
             result.thumbnail_url or "",
-            bool(getattr(result, "edge_crop_applied", False)),
         )
     finally:
         db.close()
@@ -887,7 +899,6 @@ 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,
@@ -924,12 +935,6 @@ 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
 

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

@@ -1,121 +0,0 @@
-# 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

@@ -104,43 +104,6 @@ Staging 当前可以保持 no-op；Production 开启前必须先验证 SMTP/Redi
 
 ---
 
-## Staging 服务器 Docker 凭证配置
-
-Staging 服务器（116.62.226.203）需要配置 ACR 和 Gitea Registry 凭证，否则 docker pull 和 Watchtower 自动更新会失败。
-
-### 凭证文件位置
-- Docker 配置文件：`/root/.docker/config.json`
-- 包含两个 registry 的认证信息：
-  - `xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com`（阿里云 ACR）
-  - `git.xiaoxiajianji.com`（Gitea 容器镜像仓库）
-
-### 服务器迁移后恢复步骤
-```bash
-# 1. 登录 ACR
-docker login xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com -u <ACR_USERNAME>
-
-# 2. 登录 Gitea Registry
-docker login git.xiaoxiajianji.com -u xiaoxia -p <GITEA_REGISTRY_TOKEN>
-
-# 3. 重启 Watchtower（确保挂载最新 config.json）
-docker restart watchtower
-```
-
-### Watchtower 配置
-- 容器名：`watchtower`
-- 检查间隔：300 秒（5 分钟）
-- 监控容器：`xiaoxia-api-staging`、`xiaoxia-worker-staging`、`xiaoxia-web-staging`
-- 必须挂载 `-v /root/.docker/config.json:/config.json` 才能拉取私有镜像
-- 必须挂载 `-v /var/run/docker.sock:/var/run/docker.sock` 才能管理容器
-- 容器使用 `:dev` 稳定 tag，Watchtower 通过检测 `:dev` tag 的 digest 变化来发现更新
-
-### 镜像 Tag 策略
-- CI 每次构建推送三种 tag：`${GITHUB_SHA}`（精确版本）、`${GITHUB_REF_NAME}`（分支名）、`:dev`（滚动 tag，仅 develop 分支）
-- Staging 容器统一使用 `:dev` tag 启动，确保 Watchtower 能自动发现新版本
-- Migration（alembic）使用 commit SHA tag 执行，不依赖 Watchtower
-
----
-
 ## Gitea Actions 约定
 
 - `develop` 分支触发 staging 部署。

docs/preset-bgm-upload.md

@@ -1,30 +0,0 @@
-# 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

@@ -30,10 +30,6 @@ COPY deploy/configs/douyin_cookies.txt /app/configs/douyin_cookies.txt
 # 强制升级 yt-dlp 到最新（抖音反爬经常变更，旧版 cookies 支持失效；#1968/#1963）
 RUN pip install --no-cache-dir -i https://mirrors.aliyun.com/pypi/simple/ --trusted-host mirrors.aliyun.com --upgrade "yt-dlp>=2026.8.19"
 
-# API 启动入口（幂等迁移 + uvicorn）—— #2129: watchtower 自动部署兜底
-COPY infra/docker/entrypoint-api.sh /usr/local/bin/entrypoint-api.sh
-RUN chmod +x /usr/local/bin/entrypoint-api.sh
-
 # 设置环境变量
 ENV PATH="/opt/venv/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin"
 ENV PYTHONPATH=/app:/app/apps/api
@@ -45,4 +41,4 @@ HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
     CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/health', timeout=5)"
 
 # API 入口点
-ENTRYPOINT ["/usr/local/bin/entrypoint-api.sh"]
+CMD ["uvicorn", "apps.api.main:app", "--host", "0.0.0.0", "--port", "8000"]

infra/docker/entrypoint-api.sh

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

infra/docker/entrypoint-worker.sh

@@ -18,17 +18,6 @@
 
 set -e
 
-# #2129: 幂等执行数据库迁移（watchtower 自动部署兜底）
-# worker 容器独立启动，不能依赖 API 容器先跑迁移
-cd /app
-echo "[entrypoint-worker] Running alembic upgrade head..."
-if alembic upgrade head; then
-  echo "[entrypoint-worker] Migrations ok."
-else
-  echo "[entrypoint-worker] WARNING: alembic upgrade failed, continuing to start workers..." >&2
-fi
-cd - >/dev/null
-
 MAX_TASKS="${WORKER_MAX_TASKS_PER_CHILD:-100}"
 
 # ── 并发计算：显式 env 优先；否则从 WORKER_CONCURRENCY 按比例推导 ──

infra/docker/worker.Dockerfile

@@ -10,14 +10,6 @@ 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: $(fc-match 'Noto Sans CJK SC' 2>/dev/null | head -1)"
-
 # 创建非 root 用户
 RUN groupadd -r celery \
     && useradd -r -g celery -d /app -s /sbin/nologin celery \
@@ -34,7 +26,6 @@ ENV APP_VERSION=$APP_VERSION
 
 # 复制文件（按变化频率从低到高排序，最大化层缓存命中）
 COPY alembic.ini /app/alembic.ini
-COPY alembic/ /app/alembic/
 COPY migrations/ /app/migrations/
 COPY packages/ /app/packages/
 # PR #1844 起，worker 还需要加载 apps.api.app.tasks.lipsync_tts，

infra/nginx/gpu-relay-staging.conf

@@ -1,29 +1,31 @@
-# Staging GPU relay nginx 配置说明
+# 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
 #
-# 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
+# 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;
+    }
+}

packages/adapters/in_memory/ingest_job_repository.py

@@ -14,24 +14,6 @@ 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

@@ -502,19 +502,8 @@ 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 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()
-        )
+        """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()
         if model is None:
             return None
         return self._to_domain(model)

packages/adapters/sqlalchemy_impl/ingest_job_repository.py

@@ -46,43 +46,6 @@ 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(Float, nullable=False, default=0)
+    points_balance = Column(Integer, 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(Float, nullable=False, default=0)
-    total_earned = Column(Float, nullable=False, default=0)
-    total_spent = Column(Float, nullable=False, default=0)
+    balance = Column(Integer, nullable=False, default=0)
+    total_earned = Column(Integer, nullable=False, default=0)
+    total_spent = Column(Integer, 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(Float, nullable=False)
-    balance_after = Column(Float, nullable=False)
+    amount = Column(Integer, nullable=False)
+    balance_after = Column(Integer, 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))
@@ -918,90 +918,3 @@ 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
-    pre_trusted_images = Column(JSON, nullable=True)  # #2172 信任链预热结果（Seedream AI 化 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（#2040：纯文本 XML 标签模板，运营可直接编辑）"""
-
-    __tablename__ = "viral_video_prompt_templates"
-
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    name = Column(String(128), nullable=False)
-    prompt_type = Column(String(32), nullable=False)
-    version = Column(Integer, nullable=False, default=1)
-    system_prompt = Column(Text, nullable=False)
-    user_prompt_template = Column(Text, nullable=False)
-    example_output = Column(Text, nullable=True)
-    is_active = Column(Boolean, nullable=False, default=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

@@ -81,41 +81,6 @@ def ensure_database_exists(database_url: str) -> None:
         admin_engine.dispose()
 
 
-_VIRAL_VIDEO_BACKFILL_COLS = [
-    ("storyboard", "JSON"),
-    ("generated_copy_text", "TEXT NOT NULL DEFAULT ''"),
-    ("voice_id", "VARCHAR(200) NOT NULL DEFAULT ''"),
-    ("voice_source", "VARCHAR(20) NOT NULL DEFAULT ''"),
-    ("video_ratio", "VARCHAR(10) NOT NULL DEFAULT '9:16'"),
-    ("video_model", "VARCHAR(100) NOT NULL DEFAULT ''"),
-    ("copy_result", "JSON"),
-]
-
-
-def _ensure_viral_video_columns(connection) -> None:
-    """Idempotently add new columns to viral_video_jobs; create_all will not ALTER existing tables."""
-    from sqlalchemy import inspect as _inspect
-
-    try:
-        insp = _inspect(connection)
-        if not insp.has_table("viral_video_jobs"):
-            return
-        existing = {c["name"] for c in insp.get_columns("viral_video_jobs")}
-    except Exception:
-        return
-    import logging as _logging
-
-    _log = _logging.getLogger(__name__)
-    for col, ddl in _VIRAL_VIDEO_BACKFILL_COLS:
-        if col in existing:
-            continue
-        try:
-            connection.execute(text(f"ALTER TABLE viral_video_jobs ADD COLUMN {col} {ddl}"))
-            _log.info("added column viral_video_jobs.%s", col)
-        except Exception as e:
-            _log.warning("add column %s failed: %s", col, e)
-
-
 def initialize_database(engine) -> None:
     """初始化数据库 schema。
 
@@ -135,5 +100,4 @@ def initialize_database(engine) -> None:
                 text("SELECT pg_advisory_unlock(:lock_id)"),
                 {"lock_id": SCHEMA_INIT_LOCK_ID},
             )
-            _ensure_viral_video_columns(connection)
             connection.commit()

packages/adapters/sqlalchemy_impl/user_repository.py

@@ -39,9 +39,6 @@ class SQLAlchemyUserRepository(UserRepository):
         model.phone_verified = user.phone_verified
         model.binding_completed_at = user.binding_completed_at
         model.profile_completed = user.profile_completed
-        model.is_member = user.is_member
-        model.member_type = user.member_type
-        model.member_expires_at = user.member_expires_at
         model.created_at = user.created_at
 
         self.session.commit()
@@ -118,8 +115,5 @@ class SQLAlchemyUserRepository(UserRepository):
             phone_verified=model.phone_verified or False,
             binding_completed_at=model.binding_completed_at,
             profile_completed=model.profile_completed if model.profile_completed is not None else True,
-            is_member=model.is_member if model.is_member is not None else False,
-            member_type=model.member_type,
-            member_expires_at=model.member_expires_at,
             created_at=model.created_at,
         )

packages/adapters/sqlalchemy_impl/viral_video_repository.py

@@ -1,235 +0,0 @@
-"""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,
-    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 []),
-        pre_trusted_images=(
-            list(getattr(model, "pre_trusted_images", None) or [])
-            if getattr(model, "pre_trusted_images", None) is not None
-            else None
-        ),
-        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,
-            pre_trusted_images=job.pre_trusted_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.pre_trusted_images = job.pre_trusted_images
-        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,
-        }

packages/application/catalog/__init__.py

@@ -1 +0,0 @@
-"""应用层：对外展示目录（套餐/积分包）。"""

packages/application/catalog/admin_catalog.py

@@ -1,152 +0,0 @@
-"""读取管理后台配置的会员套餐 / 积分充值包（共享库真实数据）。
-
-替代旧的硬编码 MEMBERSHIP_PRICES / POINTS_PACKAGES。
-短 TTL 缓存（30 秒），后台改价/启停后用户端最多 30 秒可见。
-"""
-
-from __future__ import annotations
-
-import threading
-import time
-from typing import Any
-
-_CACHE_TTL = 30.0
-_lock = threading.Lock()
-_cache: dict[str, tuple[float, Any]] = {}
-
-_QUOTA_LABELS = {
-    "4k": "4K 超清分辨率",
-    "batch_render": "批量渲染",
-    "priority_queue": "优先处理队列",
-    "ai_matting": "AI 智能抠像",
-    "remove_watermark": "去水印",
-}
-
-
-def _cached(key: str, loader):
-    now = time.time()
-    hit = _cache.get(key)
-    if hit and now - hit[0] < _CACHE_TTL:
-        return hit[1]
-    with _lock:
-        hit = _cache.get(key)
-        if hit and time.time() - hit[0] < _CACHE_TTL:
-            return hit[1]
-        value = loader()
-        _cache[key] = (time.time(), value)
-        return value
-
-
-def _quota_features(quotas: dict[str, Any] | None) -> dict[str, Any]:
-    quotas = quotas or {}
-    features: dict[str, Any] = {}
-    for k, v in quotas.items():
-        if k == "credits_per_month":
-            features["credits_per_month"] = v
-        elif k in _QUOTA_LABELS:
-            features[_QUOTA_LABELS[k]] = v
-        else:
-            features[k] = v
-    return features
-
-
-def get_membership_plans() -> list[dict[str, Any]]:
-    """读取 is_enabled=true 的套餐，按年/月周期展开为用户端档位。"""
-
-    def _load() -> list[dict[str, Any]]:
-        from sqlalchemy import text
-
-        from packages.adapters.sqlalchemy_impl.session import SessionLocal
-
-        if SessionLocal is None:
-            return []
-
-        session = SessionLocal()
-        try:
-            rows = session.execute(text("""
-                    SELECT plan_key, name, description, monthly_price, yearly_price,
-                           quotas, display_order
-                    FROM plans
-                    WHERE is_enabled = TRUE
-                    ORDER BY display_order NULLS LAST, created_at
-                    """)).fetchall()
-        finally:
-            session.close()
-
-        plans: list[dict[str, Any]] = []
-        for r in rows:
-            base_features = _quota_features(r.quotas if isinstance(r.quotas, dict) else None)
-            if r.yearly_price and float(r.yearly_price) > 0:
-                plans.append(
-                    {
-                        "plan_id": r.plan_key,
-                        "billing_cycle": "yearly",
-                        "name": r.name,
-                        "description": r.description,
-                        "price_cents": int(round(float(r.yearly_price) * 100)),
-                        "monthly_price_cents": int(round(float(r.yearly_price) * 100 / 12)),
-                        "duration_days": 365,
-                        "features": dict(base_features),
-                    }
-                )
-            if r.monthly_price and float(r.monthly_price) > 0:
-                plans.append(
-                    {
-                        "plan_id": r.plan_key,
-                        "billing_cycle": "monthly",
-                        "name": r.name,
-                        "description": r.description,
-                        "price_cents": int(round(float(r.monthly_price) * 100)),
-                        "monthly_price_cents": int(round(float(r.monthly_price) * 100)),
-                        "duration_days": 30,
-                        "features": dict(base_features),
-                    }
-                )
-        return plans
-
-    return _cached("membership_plans", _load)
-
-
-def get_points_packages() -> list[dict[str, Any]]:
-    """读取 is_active=true 的积分充值包。"""
-
-    def _load() -> list[dict[str, Any]]:
-        from sqlalchemy import text
-
-        from packages.adapters.sqlalchemy_impl.session import SessionLocal
-
-        if SessionLocal is None:
-            return []
-
-        session = SessionLocal()
-        try:
-            rows = session.execute(text("""
-                    SELECT package_key, name, price, credits, bonus_credits,
-                           is_recommended, description, sort_order
-                    FROM credit_packages
-                    WHERE is_active = TRUE
-                    ORDER BY sort_order NULLS LAST, price
-                    """)).fetchall()
-        finally:
-            session.close()
-
-        packages: list[dict[str, Any]] = []
-        for r in rows:
-            total_points = int(r.credits or 0) + int(r.bonus_credits or 0)
-            price_cents = int(round(float(r.price) * 100))
-            unit = (price_cents / 100 / total_points) if total_points else 0
-            packages.append(
-                {
-                    "code": r.package_key,
-                    "name": r.name,
-                    "points": total_points,
-                    "bonus_credits": int(r.bonus_credits or 0),
-                    "price_cents": price_cents,
-                    "unit_price": f"¥{unit:.3f}/积分",
-                    "is_recommended": bool(r.is_recommended),
-                    "description": r.description,
-                }
-            )
-        return packages
-
-    return _cached("points_packages", _load)

packages/application/viral_video/__init__.py

@@ -1 +0,0 @@
-"""应用层：爆款视频 Prompt 模板系统（#2040）。"""

packages/application/viral_video/generator.py

@@ -1,427 +0,0 @@
-"""爆款视频 5 步编排：图片分析 → 意图解析 → 文案融合 → 分镜 → 审核重写。
-
-所有 LLM 调用走 DoubaoClient，单测通过 client 参数注入 mock，不真调 API。
-任何一步解析失败都走规则 fallback，不抛异常阻断。
-"""
-
-from __future__ import annotations
-
-import logging
-from typing import Optional
-
-from packages.application.viral_video import xml_parser as xp
-from packages.application.viral_video.prompt_loader import (
-    PromptTemplate,
-    get_template,
-    render_system_prompt,
-    render_user_prompt,
-)
-from packages.application.viral_video.prompts import (
-    FUSION_INSTRUCTIONS,
-    GLOBAL_CONSTRAINTS,
-    NEGATIVE_RULES,
-)
-from packages.application.viral_video.reviewer import Reviewer
-from packages.application.viral_video.schemas import (
-    BodyPoint,
-    Clip,
-    ColorItem,
-    CoreMessage,
-    FusionResult,
-    ImageAnalysis,
-    IntentResult,
-    KenBurns,
-    PersonalBrand,
-    ProductItem,
-    ReviewResult,
-    ScriptSegment,
-    Storyboard,
-    TextItem,
-)
-
-logger = logging.getLogger(__name__)
-
-
-class CopyGenerator:
-    """5 步 Prompt 编排器。"""
-
-    def __init__(self, client=None, reviewer: Optional[Reviewer] = None):
-        if client is None:
-            from packages.shared.ai_client import get_doubao_client
-
-            client = get_doubao_client()
-        self.client = client
-        self.reviewer = reviewer or Reviewer(client)
-
-    # ── 底层调用 ────────────────────────────────────────────────────────
-    def _chat(self, template: PromptTemplate, system_kwargs: dict | None, **user_kwargs) -> str:
-        system = render_system_prompt(template, **(system_kwargs or {}))
-        user = render_user_prompt(template, **user_kwargs)
-        result = self.client.chat_completion(
-            [
-                {"role": "system", "content": system},
-                {"role": "user", "content": user},
-            ],
-            temperature=0.7,
-            max_tokens=2048,
-        )
-        return result or ""
-
-    # ── 步骤1：图片多模态分析 ───────────────────────────────────────────
-    def analyze_images(self, images: list[str], industry: str = "") -> ImageAnalysis:
-        template = get_template("image_analysis")
-        image_urls = "\n".join(f"第{i + 1}张：{url}" for i, url in enumerate(images))
-        system = render_system_prompt(template)
-        user = render_user_prompt(template, image_count=len(images), industry=industry or "通用", image_urls=image_urls)
-        raw = self.client.vision_completion(
-            [
-                {"role": "system", "content": system},
-                {"role": "user", "content": user},
-            ],
-            images=images,
-            max_tokens=2048,
-            temperature=0.3,
-        )
-        analysis = self._parse_image_analysis(raw or "")
-        if not analysis.products and not analysis.key_selling_points:
-            logger.warning("图片分析标签解析失败，走规则 fallback")
-            return self._fallback_image_analysis(images, raw or "")
-        return analysis
-
-    def _parse_image_analysis(self, raw: str) -> ImageAnalysis:
-        products = [
-            ProductItem(
-                name=n["attrs"].get("name", "无法判断"),
-                features=n["attrs"].get("features", "无法判断"),
-                position=n["attrs"].get("position", "secondary"),
-                image_index=xp.attr_int(n["attrs"].get("image_index"), 0),
-            )
-            for n in xp.find_all(raw, "product")
-        ]
-        colors = [
-            ColorItem(
-                hex=c["attrs"].get("hex", "#000000"),
-                name=c["attrs"].get("name", "无法判断"),
-                coverage=xp.attr_float(c["attrs"].get("coverage"), 0.0),
-            )
-            for c in xp.find_all(raw, "color")
-        ]
-        people = xp.find_first(raw, "people")
-        visible_text = [
-            TextItem(text=t["attrs"].get("text", ""), position=t["attrs"].get("position", ""))
-            for t in xp.find_all(raw, "text_item")
-        ]
-        quality_node = xp.find_first(raw, "quality")
-        selling_points = [n["text"] or n["attrs"].get("text", "") for n in xp.find_all(raw, "point")]
-        return ImageAnalysis(
-            products=products,
-            colors=colors,
-            has_person=xp.attr_bool(people["attrs"].get("has_person")) if people else False,
-            person_count=xp.attr_int(people["attrs"].get("count"), 0) if people else 0,
-            people=people["attrs"] if people else {},
-            mood=xp.text_of(raw, "mood"),
-            visible_text=visible_text,
-            scene=xp.text_of(raw, "scene"),
-            quality=quality_node["attrs"] if quality_node else {},
-            key_selling_points=[p for p in selling_points if p],
-            raw=raw,
-        )
-
-    def _fallback_image_analysis(self, images: list[str], raw: str) -> ImageAnalysis:
-        return ImageAnalysis(
-            products=[ProductItem(name="无法判断（视觉分析不可用）", image_index=0)],
-            scene="无法判断",
-            raw=raw,
-        )
-
-    # ── 步骤2：意图解析 ─────────────────────────────────────────────────
-    def parse_intent(self, user_copy_text: str, image_analysis: ImageAnalysis, industry: str = "") -> IntentResult:
-        template = get_template("intent_parsing")
-        raw = self._chat(
-            template,
-            None,
-            user_copy_text=user_copy_text or "（用户没有提供文案）",
-            industry=industry or "通用",
-            image_analysis=self._image_brief(image_analysis),
-        )
-        intent = self._parse_intent(raw)
-        if not intent.intent_summary and not intent.core_messages:
-            logger.warning("意图解析标签解析失败，走规则 fallback")
-            return self._fallback_intent(user_copy_text, raw)
-        return intent
-
-    def _parse_intent(self, raw: str) -> IntentResult:
-        messages = [
-            CoreMessage(
-                text=n["text"],
-                must_keep=xp.attr_bool(n["attrs"].get("must_keep"), default=False),
-                confidence=xp.attr_float(n["attrs"].get("confidence"), 0.0),
-            )
-            for n in xp.find_all(raw, "message")
-            if n["text"]
-        ]
-        brands = [
-            PersonalBrand(text=n["text"], category=n["attrs"].get("category", "brand"))
-            for n in xp.find_all(raw, "brand")
-            if n["text"]
-        ]
-        missing = [n["text"] for n in xp.find_all(raw, "info") if n["text"]]
-        return IntentResult(
-            intent_summary=xp.text_of(raw, "intent_summary"),
-            core_messages=messages,
-            personal_brands=brands,
-            emotion_tone=xp.text_of(raw, "emotion_tone"),
-            missing_info=missing,
-            raw=raw,
-        )
-
-    def _fallback_intent(self, user_copy_text: str, raw: str) -> IntentResult:
-        text = (user_copy_text or "").strip()
-        messages = [CoreMessage(text=text[:80], must_keep=True, confidence=1.0)] if text else []
-        return IntentResult(
-            intent_summary=text[:30] or "未提供文案，按产品图片自由创作",
-            core_messages=messages,
-            personal_brands=[],
-            raw=raw,
-        )
-
-    # ── 步骤3：文案融合生成（三档）──────────────────────────────────────
-    def fuse(
-        self,
-        fusion_level: str,
-        image_analysis: ImageAnalysis,
-        intent: IntentResult,
-        industry: str = "",
-        target_customer: str = "",
-        marketing_purpose: str = "",
-        duration: int = 15,
-    ) -> FusionResult:
-        template = get_template("copy_fusion")
-        system_kwargs = {
-            "fusion_instruction": FUSION_INSTRUCTIONS.get(fusion_level, FUSION_INSTRUCTIONS["ai_polish"]),
-            "global_constraints": GLOBAL_CONSTRAINTS,
-            "negative_rules": NEGATIVE_RULES,
-        }
-        raw = self._chat(
-            template,
-            system_kwargs,
-            industry=industry or "通用",
-            target_customer=target_customer or "通用消费者",
-            marketing_purpose=marketing_purpose or "产品种草",
-            duration=duration,
-            image_analysis=self._image_brief(image_analysis),
-            intent_result=self._intent_brief(intent),
-        )
-        result = self._parse_fusion(raw)
-        if not result.title and not result.script_segments:
-            logger.warning("文案融合标签解析失败（fusion=%s），走规则 fallback", fusion_level)
-            return self._fallback_fusion(fusion_level, image_analysis, intent, duration, raw)
-        return result
-
-    def _parse_fusion(self, raw: str) -> FusionResult:
-        body_points = [
-            BodyPoint(
-                text=n["text"],
-                elaboration=n["attrs"].get("elaboration", ""),
-                image_index=xp.attr_int(n["attrs"].get("image_index"), 0),
-            )
-            for n in xp.find_all(raw, "point")
-            if n["text"]
-        ]
-        segments = [
-            ScriptSegment(
-                text=n["text"],
-                duration_sec=xp.attr_float(n["attrs"].get("duration_sec"), 0.0),
-                image_index=xp.attr_int(n["attrs"].get("image_index"), 0),
-            )
-            for n in xp.find_all(raw, "segment")
-            if n["text"]
-        ]
-        return FusionResult(
-            title=xp.text_of(raw, "title"),
-            hook=xp.text_of(raw, "hook"),
-            body_points=body_points,
-            cta=xp.text_of(raw, "cta"),
-            script_segments=segments,
-            word_count=xp.attr_int(xp.text_of(raw, "word_count"), 0),
-            estimated_duration=xp.attr_int(xp.text_of(raw, "estimated_duration"), 0),
-            raw=raw,
-        )
-
-    def _fallback_fusion(
-        self,
-        fusion_level: str,
-        image_analysis: ImageAnalysis,
-        intent: IntentResult,
-        duration: int,
-        raw: str,
-    ) -> FusionResult:
-        product_name = image_analysis.products[0].name if image_analysis.products else "这款产品"
-        selling = image_analysis.key_selling_points[:2]
-        if fusion_level == "ai_full":
-            title = f"{product_name}，很多人用完都回购了"
-            hook = f"这个{product_name}，我想认真说说"
-            body = selling or ["图片可见的产品卖点"]
-            cta = "感兴趣的可以了解一下"
-        elif fusion_level == "user_primary":
-            user_text = intent.intent_summary or product_name
-            title = user_text[:20]
-            hook = user_text[:15]
-            body = [m.text for m in intent.core_messages] or [user_text]
-            cta = "想了解的可以看看"
-        else:
-            title = intent.intent_summary[:20] or product_name
-            hook = intent.core_messages[0].text[:15] if intent.core_messages else product_name
-            body = [m.text for m in intent.core_messages] or selling or [product_name]
-            cta = "有需要的可以了解一下"
-
-        brand_texts = [b.text for b in intent.personal_brands]
-        points = [BodyPoint(text=b) for b in body]
-        lines = [hook] + body + brand_texts[:2] + [cta]
-        joined = "，".join(lines)
-        per = max(3, duration // max(1, len(lines)))
-        segments = [ScriptSegment(text=line, duration_sec=per, image_index=0) for line in lines]
-        return FusionResult(
-            title=title,
-            hook=hook,
-            body_points=points,
-            cta=cta,
-            script_segments=segments,
-            word_count=len(joined),
-            estimated_duration=duration,
-            raw=raw,
-        )
-
-    # ── 步骤4：编导级分镜 ───────────────────────────────────────────────
-    def storyboard(
-        self, fusion: FusionResult, image_analysis: ImageAnalysis, images: list[str], duration: int
-    ) -> Storyboard:
-        template = get_template("storyboard")
-        raw = self._chat(
-            template,
-            None,
-            duration=duration,
-            image_count=len(images),
-            fusion_result=self._fusion_brief(fusion),
-            image_analysis=self._image_brief(image_analysis),
-        )
-        board = self._parse_storyboard(raw)
-        if not board.clips:
-            logger.warning("分镜标签解析失败，走规则 fallback")
-            return self._fallback_storyboard(fusion, duration, raw)
-        return board
-
-    def _parse_storyboard(self, raw: str) -> Storyboard:
-        clips: list[Clip] = []
-        for node in xp.find_all(raw, "clip"):
-            attrs = node["attrs"]
-            body = node["text"]
-            kb = xp.find_first(node["text"] and f"<root>{node['text']}</root>", "ken_burns")
-            clips.append(
-                Clip(
-                    image_index=xp.attr_int(attrs.get("image_index"), 0),
-                    transition=attrs.get("transition", "cut"),
-                    zoom=(None if attrs.get("zoom") in (None, "null", "None", "") else attrs.get("zoom")),
-                    duration_sec=xp.attr_float(attrs.get("duration_sec"), 0.0),
-                    bgm_note=attrs.get("bgm_note", ""),
-                    voice_text=xp.text_of(body and f"<root>{body}</root>", "voice_text"),
-                    subtitle_text=xp.text_of(body and f"<root>{body}</root>", "subtitle_text"),
-                    ken_burns=KenBurns(
-                        start=kb["attrs"].get("start", "0,0") if kb else "0,0",
-                        end=kb["attrs"].get("end", "0,0") if kb else "0,0",
-                        ease=kb["attrs"].get("ease", "linear") if kb else "linear",
-                    ),
-                )
-            )
-        return Storyboard(clips=clips, raw=raw)
-
-    def _fallback_storyboard(self, fusion: FusionResult, duration: int, raw: str) -> Storyboard:
-        segments = fusion.script_segments or [ScriptSegment(text=fusion.hook or fusion.title, duration_sec=duration)]
-        total = sum(s.duration_sec for s in segments) or duration
-        clips = [
-            Clip(
-                image_index=min(s.image_index, 0),
-                transition="cut",
-                duration_sec=max(2.0, s.duration_sec * duration / total if total else duration / len(segments)),
-                voice_text=s.text,
-                subtitle_text=s.text[:20],
-            )
-            for s in segments
-        ]
-        return Storyboard(clips=clips, raw=raw)
-
-    # ── 步骤5：审核（不通过自动重写1次）─────────────────────────────────
-    def review_and_rewrite(
-        self, fusion: FusionResult, intent: IntentResult, fusion_level: str
-    ) -> tuple[FusionResult, ReviewResult, int]:
-        """返回最终文案、最后一次审核结果、重写次数（0或1）。"""
-        review = self.reviewer.review(fusion, intent, fusion_level)
-        if review.passed:
-            return fusion, review, 0
-
-        logger.info("文案审核不通过，自动重写 1 次：%s", [i.text for i in review.issues])
-        rewritten = self.reviewer.rewrite(fusion, review, intent, fusion_level)
-        second = self.reviewer.review(rewritten, intent, fusion_level)
-        if second.passed:
-            return rewritten, second, 1
-        # 二次仍不通过：带上重写结果和问题返回，由上游决定是否交给前端
-        return rewritten, second, 1
-
-    # ── 全流程编排 ──────────────────────────────────────────────────────
-    def generate(
-        self,
-        images: list[str],
-        *,
-        industry: str = "",
-        target_customer: str = "",
-        marketing_purpose: str = "",
-        duration: int = 15,
-        user_copy_text: str = "",
-        fusion_level: str = "ai_polish",
-    ) -> dict:
-        image_analysis = self.analyze_images(images, industry)
-        intent = self.parse_intent(user_copy_text, image_analysis, industry)
-        fusion = self.fuse(
-            fusion_level,
-            image_analysis,
-            intent,
-            industry=industry,
-            target_customer=target_customer,
-            marketing_purpose=marketing_purpose,
-            duration=duration,
-        )
-        fusion, review, rewrites = self.review_and_rewrite(fusion, intent, fusion_level)
-        board = self.storyboard(fusion, image_analysis, images, duration)
-        return {
-            "image_analysis": image_analysis,
-            "intent_result": intent,
-            "fusion_result": fusion,
-            "review_result": review,
-            "storyboard": board,
-            "rewrite_count": rewrites,
-        }
-
-    # ── 简报工具 ────────────────────────────────────────────────────────
-    @staticmethod
-    def _image_brief(a) -> str:
-        if a is None:
-            return "无图片分析信息"
-        lines = [f"产品：{p.name}（{p.features}）" for p in a.products]
-        lines += [f"卖点：{s}" for s in a.key_selling_points]
-        lines.append(f"场景：{a.scene}")
-        return "\n".join(lines) or "无图片分析信息"
-
-    @staticmethod
-    def _intent_brief(i: IntentResult) -> str:
-        lines = [f"意图：{i.intent_summary}"]
-        lines += [f"核心信息[must_keep={m.must_keep}]：{m.text}" for m in i.core_messages]
-        lines += [f"事实（{b.category}）：{b.text}" for b in i.personal_brands]
-        return "\n".join(lines)
-
-    @staticmethod
-    def _fusion_brief(f: FusionResult) -> str:
-        lines = [f"标题：{f.title}", f"钩子：{f.hook}"]
-        lines += [f"要点：{p.text}" for p in f.body_points]
-        lines += [f"配音：{s.text}" for s in f.script_segments]
-        lines.append(f"行动号召：{f.cta}")
-        return "\n".join(lines)

packages/application/viral_video/prompt_loader.py

@@ -1,160 +0,0 @@
-"""Prompt 模板加载器：从 viral_video_prompt_templates 读模板，30 秒 TTL 热加载。
-
-DB 不可用或没有数据时自动回落到 prompts.DEFAULT_TEMPLATES，保证流程不阻断。
-"""
-
-from __future__ import annotations
-
-import threading
-import time
-from dataclasses import dataclass
-from typing import Optional
-
-import sqlalchemy as sa
-
-from packages.adapters.sqlalchemy_impl import session as _session_mod
-from packages.application.viral_video.prompts import DEFAULT_TEMPLATES
-
-CACHE_TTL_SECONDS = 30.0
-
-_VALID_TYPES = {"image_analysis", "intent_parsing", "copy_fusion", "storyboard", "review"}
-
-
-@dataclass
-class PromptTemplate:
-    name: str
-    prompt_type: str
-    version: int
-    system_prompt: str
-    user_prompt_template: str
-    example_output: str = ""
-    is_active: bool = True
-
-
-_lock = threading.Lock()
-_cache: dict[str, tuple[float, PromptTemplate]] = {}
-
-
-def _fallback(prompt_type: str) -> Optional[PromptTemplate]:
-    for item in DEFAULT_TEMPLATES:
-        if item["prompt_type"] == prompt_type:
-            return PromptTemplate(
-                name=item["name"],
-                prompt_type=item["prompt_type"],
-                version=item["version"],
-                system_prompt=item["system_prompt"],
-                user_prompt_template=item["user_prompt_template"],
-                example_output=item["example_output"] or "",
-                is_active=bool(item["is_active"]),
-            )
-    return None
-
-
-_lazy_session = None
-
-
-def _get_session():
-    """优先用全局 SessionLocal（worker）；否则按应用配置懒建同步引擎（api）。"""
-    global _lazy_session
-    if _session_mod.SessionLocal is not None:
-        return _session_mod.SessionLocal()
-    if _lazy_session is not None:
-        return _lazy_session()
-    try:
-        from packages.config import get_shared_settings
-
-        url = str(get_shared_settings().database_url)
-    except Exception:  # noqa: BLE001
-        return None
-    if not url:
-        return None
-    url = url.replace("postgresql+asyncpg://", "postgresql+psycopg://")
-    url = url.replace("postgresql://", "postgresql+psycopg://") if url.startswith("postgresql://") else url
-    engine = sa.create_engine(url, pool_pre_ping=True, pool_size=2, max_overflow=2)
-    from sqlalchemy.orm import sessionmaker
-
-    _lazy_session = sessionmaker(bind=engine)
-    return _lazy_session()
-
-
-def _load_from_db(prompt_type: str) -> Optional[PromptTemplate]:
-    session = None
-    try:
-        session = _get_session()
-        if session is None:
-            return None
-        sql = sa.text("""
-            SELECT name, prompt_type, version, system_prompt,
-                   user_prompt_template, COALESCE(example_output, '') AS example_output,
-                   is_active
-              FROM viral_video_prompt_templates
-             WHERE prompt_type = :pt AND is_active = TRUE
-             ORDER BY version DESC
-             LIMIT 1
-            """)
-        row = session.execute(sql, {"pt": prompt_type}).first()
-        if row is None:
-            return None
-        return PromptTemplate(
-            name=row[0],
-            prompt_type=row[1],
-            version=int(row[2]),
-            system_prompt=row[3],
-            user_prompt_template=row[4],
-            example_output=row[5] or "",
-            is_active=bool(row[6]),
-        )
-    except Exception:  # noqa: BLE001 - 表不存在/DB 不可用时静默回落
-        return None
-    finally:
-        if session is not None:
-            try:
-                session.close()
-            except Exception:  # noqa: BLE001
-                pass
-
-
-def get_template(prompt_type: str, *, force_refresh: bool = False) -> Optional[PromptTemplate]:
-    """取某类型当前启用模板，30 秒缓存；DB 无数据则回落到代码默认模板。"""
-    if prompt_type not in _VALID_TYPES:
-        raise ValueError(f"未知 prompt_type: {prompt_type}")
-
-    now = time.monotonic()
-    with _lock:
-        cached = _cache.get(prompt_type)
-        if not force_refresh and cached and now - cached[0] < CACHE_TTL_SECONDS:
-            return cached[1]
-
-    template = _load_from_db(prompt_type) or _fallback(prompt_type)
-    if template is not None:
-        with _lock:
-            _cache[prompt_type] = (now, template)
-    return template
-
-
-def invalidate() -> None:
-    """清空缓存（测试用）。"""
-    with _lock:
-        _cache.clear()
-
-
-class _SafeDict(dict):
-    def __missing__(self, key: str) -> str:
-        return "{" + key + "}"
-
-
-def _safe_format(text: str, kwargs: dict) -> str:
-    try:
-        return text.format_map(_SafeDict(kwargs))
-    except Exception:  # noqa: BLE001
-        return text
-
-
-def render_user_prompt(template: PromptTemplate, **kwargs) -> str:
-    """填充 user_prompt_template 占位符，缺键原样保留不报错。"""
-    return _safe_format(template.user_prompt_template, kwargs)
-
-
-def render_system_prompt(template: PromptTemplate, **kwargs) -> str:
-    """copy_fusion 等 system_prompt 含运行时变量时填充。"""
-    return _safe_format(template.system_prompt, kwargs)

packages/application/viral_video/prompts.py

@@ -1,293 +0,0 @@
-"""爆款视频 5 套 Prompt 模板默认值（#2040 核心资产）。
-
-重要约定（用户明确要求）：
-- 所有 system_prompt / user_prompt_template / example_output 都是**纯文本自然语言 + XML 标签**，
-  运营可直接看懂和编辑，禁止 JSON、禁止 ```json 代码块。
-- LLM 按 XML 标签输出字段，程序用正则解析（见 xml_parser.py）。
-- user_prompt_template 中花括号占位符（如 {user_copy_text}）在运行时填充。
-"""
-
-from __future__ import annotations
-
-TEMPLATE_VERSION = 1
-
-# 所有文案类 Prompt 自动注入的硬约束
-GLOBAL_CONSTRAINTS = """【必须遵守的硬约束】
-1. 不编造时间：不写“今年最新”“2024 爆款”等会过时的时间表述。
-2. 不承诺效果：不写“保证”“一定”“100%有效”“包治百病”等绝对化用语。
-3. 不编造价格、销量、认证、奖项：除非用户在文案中明确给出，否则一律不写。
-4. 符合广告法及平台社区规范。
-5. 只描述图片中真实可见的内容，看不到的不瞎猜。"""
-
-# 反套路化要求
-NEGATIVE_RULES = """【反套路化要求】
-禁止使用“家人们谁懂啊”“绝绝子”“宝子们”“家人们”“太绝了”“yyds”等烂大街网络词；
-禁止固定模板化开头；语言要像真人朋友之间的分享，自然、具体、有信息量。"""
-
-# 输出禁用套路词（测试会检查）
-BANNED_PHRASES = ["家人们谁懂啊", "绝绝子", "宝子们", "yyds", "太绝了"]
-
-# 文案融合三档独立指令段
-FUSION_INSTRUCTIONS = {
-    "ai_full": """【本次创作模式：AI 全权创作】
-你是资深短视频编导。用户只提供了产品图片，没有给出具体文案方向。请根据图片内容和营销参数，自由发挥创作完整的爆款短视频文案。充分挖掘产品真实可见的卖点，使用爆款结构，抓人眼球。""",
-    "ai_polish": """【本次创作模式：AI 辅助润色】
-你是用户的文案助理。用户已经写了草稿/关键词/碎碎念，表达了他想讲的核心意思，但表达不完整、不够吸引人。你的任务是：以用户的意思为主，保留他想表达的所有核心信息点，在此基础上润色扩写、调整语序、增加衔接、优化表达，让文案更流畅更有吸引力。绝对不能改变用户想表达的核心意思，不能把用户的观点换成相反的，不能添加用户没提到的产品卖点。用户提到的品牌名、价格、人名、具体事实必须原样保留。""",
-    "user_primary": """【本次创作模式：以用户原文为主】
-你是文案润色助手。用户已经写好了明确的文案，这是他最终想表达的内容。你的任务是最小化修改：只做必要的错别字修正、标点调整、语句通顺度优化，以及添加必要的衔接词让口播更自然。用户的核心句子、关键表述、事实信息一律不改。如果用户文案本身已经很好，直接返回，不要为了改而改。personal_brands 中的事实信息必须逐字保留。""",
-}
-
-# ── 模板1：图片多模态分析（VLM）────────────────────────────────────────
-_IMAGE_ANALYSIS_SYSTEM = f"""你是电商商品视觉分析师，负责从商品图片中提取真实可见的商品信息。
-
-工作方式（分步骤看，不要跳步）：
-1. 先看整体：有哪些产品、什么场景、有没有人物。
-2. 再看细节：包装文字、颜色构成、人物状态、画面质感。
-3. 最后提炼卖点：只总结图片里能看到的卖点。
-
-{GLOBAL_CONSTRAINTS}
-
-请严格按下面的标签格式输出，标签名一个都不能改，不要输出任何解释，不要用代码块：
-<products> 下面每个产品用一个 <product> 标签，属性 name 是产品名、features 是外观特征、position 是 main 或 secondary、image_index 是第几张图（从0开始）。
-<colors> 下面每个主要颜色用一个 <color> 标签，属性 hex 是色值、name 是颜色名、coverage 是占比小数。
-<people> 用一个标签，属性 has_person、count、gender、age_range、pose、expression 分别描述人物情况。
-<mood> 标签写画面整体情绪氛围。
-<visible_text> 下面每处可见文字用一个 <text_item> 标签，属性 text 是文字内容、position 是位置。
-<scene> 标签写场景描述。
-<quality> 用一个标签，属性 resolution、lighting、composition、blur 描述画质。
-<key_selling_points> 下面每个卖点用一个 <point> 标签。
-
-看不到或无法判断的内容，属性值填“无法判断”，布尔值填 false，不要留空标签。"""
-
-_IMAGE_ANALYSIS_USER = """请分析以下商品图片，共 {image_count} 张。
-所属行业：{industry}
-图片地址：
-{image_urls}
-
-按约定的标签格式输出分析结果。"""
-
-_IMAGE_ANALYSIS_EXAMPLE = """<products>
-<product name="大公鸡头 多功能油污净 625ml" features="红色瓶盖白色瓶身，鸡头图案Logo" position="main" image_index="0"/>
-</products>
-<colors>
-<color hex="#D32F2F" name="红色" coverage="0.4"/>
-<color hex="#FFFFFF" name="白色" coverage="0.5"/>
-</colors>
-<people has_person="false" count="0" gender="无法判断" age_range="无法判断" pose="无法判断" expression="无法判断"/>
-<mood>干净、实用</mood>
-<visible_text>
-<text_item text="多功能油污净" position="瓶身正面"/>
-</visible_text>
-<scene>白底棚拍产品图</scene>
-<quality resolution="高清" lighting="均匀柔和" composition="主体居中" blur="false"/>
-<key_selling_points>
-<point>针对重油污设计</point>
-<point>大容量625ml</point>
-</key_selling_points>"""
-
-# ── 模板2：用户文案意图解析（LLM）──────────────────────────────────────
-_INTENT_SYSTEM = f"""你负责理解用户的营销意图。用户给的文案可能只是几个关键词、碎碎念或者不完整的短句，你要读懂他真正想讲什么。
-
-{GLOBAL_CONSTRAINTS}
-
-请严格按下面的标签格式输出，不要解释，不要用代码块：
-<intent_summary> 用用户的语言风格，一句话、30字以内概括核心意图。
-<core_messages> 下面每个核心信息点用一个 <message> 标签，属性 must_keep 为 true 或 false、confidence 为 0 到 1 的小数，标签内容写信息点。
-<personal_brands> 把用户提到的具体事实——品牌名、价格、人名、地名、时间、产品名——每条用一个 <brand> 标签，属性 category 取 brand、price、person、place、time、product 之一。这些事实必须原样引用，一个字都不能改。
-<emotion_tone> 写文案的情绪调性。
-<missing_info> 把你认为缺失、后续生成时需要合理推断的信息，每条用一个 <info> 标签；没有就输出空标签。"""
-
-_INTENT_USER = """用户原始文案：{user_copy_text}
-所属行业：{industry}
-图片分析结果（供参考）：
-{image_analysis}
-
-请理解用户意图，按标签格式输出。"""
-
-_INTENT_EXAMPLE = """<intent_summary>一款厨房去油污神器，喷一喷油污就掉</intent_summary>
-<core_messages>
-<message must_keep="true" confidence="0.97">去油污效果好，喷上等几分钟再擦</message>
-<message must_keep="false" confidence="0.7">适合厨房重油污场景</message>
-</core_messages>
-<personal_brands>
-<brand category="product">大公鸡头多功能油污净</brand>
-<brand category="price">39块钱一瓶</brand>
-</personal_brands>
-<emotion_tone>亲切、真实、带分享感</emotion_tone>
-<missing_info>
-<info>没有说明具体容量，按图片读出的625ml处理</info>
-</missing_info>"""
-
-# ── 模板3：文案融合生成（LLM）──────────────────────────────────────────
-_FUSION_SYSTEM = """你负责为短视频生成营销文案。请按思维链分步完成：先定人设和目标客户，再找卖点，再搭结构，再安排情绪，最后写行动号召，不要一步到位乱写。
-
-{fusion_instruction}
-
-{global_constraints}
-
-{negative_rules}
-
-请严格按下面的标签格式输出，不要解释，不要用代码块：
-<title> 视频标题。
-<hook> 开头3秒钩子，5到15字。
-<body_points> 每个要点用一个 <point> 标签，属性 elaboration 是展开说明、image_index 是对应第几张图（从0开始），标签内容写要点。
-<cta> 口语化的行动号召。
-<script_segments> 每段配音用一个 <segment> 标签，属性 duration_sec 是秒数、image_index 是对应图片，标签内容写配音文案。
-<word_count> 配音总字数，只写数字。
-<estimated_duration> 预计时长秒数，只写数字。
-
-用户在 personal_brands 中提到的品牌名、价格、人名、地名、时间、产品名等事实信息，必须原样出现在文案里，一个字都不能改。"""
-
-_FUSION_USER = """所属行业：{industry}
-目标客户：{target_customer}
-营销目的：{marketing_purpose}
-视频时长：{duration}秒
-图片分析结果：
-{image_analysis}
-用户意图解析结果：
-{intent_result}
-
-请按标签格式生成文案。"""
-
-_FUSION_EXAMPLE = """<title>厨房重油污，别再用洗洁精硬擦了</title>
-<hook>这油污，我真的忍很久了</hook>
-<body_points>
-<point elaboration="喷在油污上等几分钟，一擦就干净" image_index="0">大公鸡头油污净去油快</point>
-<point elaboration="39块钱625ml，能用很久" image_index="0">39块钱一瓶，性价比高</point>
-</body_points>
-<cta>厨房油污重的，真的可以试一瓶</cta>
-<script_segments>
-<segment duration_sec="3" image_index="0">这油污我真的忍很久了，用洗洁精擦半天都没用</segment>
-<segment duration_sec="6" image_index="0">后来换了这个大公鸡头油污净，喷上等几分钟，一擦就干净</segment>
-<segment duration_sec="4" image_index="0">39块钱625ml，厨房重油污的可以试一瓶</segment>
-</script_segments>
-<word_count>58</word_count>
-<estimated_duration>13</estimated_duration>"""
-
-# ── 模板4：编导级分镜（LLM）────────────────────────────────────────────
-_STORYBOARD_SYSTEM = f"""你是短视频编导，负责把文案拆成可拍摄的分镜。
-
-工作方式：
-1. 按文案的 script_segments 顺序分配镜头。
-2. 每个镜头确定画面、运镜、时长、配音和字幕。
-3. 检查所有镜头时长加起来接近目标时长，误差不超过2秒。
-4. image_index 必须在已上传图片范围内，第一张主图必须用在第一个镜头。
-
-{GLOBAL_CONSTRAINTS}
-
-请严格按下面的标签格式输出，不要解释，不要用代码块：
-<clips> 下面每个镜头用一个 <clip> 标签，属性 image_index 是图片序号（从0开始）、transition 取 fade、cut、zoom_in、slide_left、dissolve、wipe 之一、zoom 取 in、out 或 null、duration_sec 是该镜头秒数、bgm_note 是该段BGM情绪。每个 <clip> 里面包含：
-<voice_text> 该镜头配音文本；
-<subtitle_text> 字幕文本，可与配音一致或更精简；
-<ken_burns> 用一个空标签，属性 start、end 写“x,y”坐标、ease 写缓动方式；不需要运镜时坐标相同。"""
-
-_STORYBOARD_USER = """目标时长：{duration}秒
-上传图片数量：{image_count}张（第1张是主图/封面）
-文案内容：
-{fusion_result}
-图片分析结果：
-{image_analysis}
-
-请按标签格式输出分镜。"""
-
-_STORYBOARD_EXAMPLE = """<clips>
-<clip image_index="0" transition="cut" zoom="null" duration_sec="3" bgm_note="日常、轻微烦躁">
-<voice_text>这油污我真的忍很久了</voice_text>
-<subtitle_text>这油污忍很久了</subtitle_text>
-<ken_burns start="0,0" end="0,0" ease="linear"/>
-</clip>
-<clip image_index="0" transition="zoom_in" zoom="in" duration_sec="6" bgm_note="轻快、出现转机">
-<voice_text>后来换了大公鸡头油污净，喷上等几分钟，一擦就干净</voice_text>
-<subtitle_text>喷上等几分钟，一擦就干净</subtitle_text>
-<ken_burns start="20,20" end="80,80" ease="ease-in-out"/>
-</clip>
-<clip image_index="0" transition="fade" zoom="null" duration_sec="4" bgm_note="温暖、推荐">
-<voice_text>39块钱625ml，厨房重油污的可以试一瓶</voice_text>
-<subtitle_text>39元625ml，可以试一瓶</subtitle_text>
-<ken_burns start="0,0" end="0,0" ease="linear"/>
-</clip>
-</clips>"""
-
-# ── 模板5：文案审核（LLM）──────────────────────────────────────────────
-_REVIEW_SYSTEM = f"""你是短视频文案合规审核员，从6个维度逐条检查文案：
-1. 违规词：有没有平台禁用词、敏感词。
-2. 夸大承诺：有没有“包治百病”“100%有效”“保证赚钱”等绝对化、夸大表述。
-3. 事实一致性：有没有编造价格、数据、认证，或者用户没提到的产品特性。
-4. 用户意图保留：在 ai_polish 和 user_primary 模式下，core_messages 中 must_keep=true 的点是否都保留了。
-5. 结构完整性：标题、钩子、正文、行动号召是否齐全。
-6. 语气人设：是否符合选定的人设语气，有没有“家人们谁懂啊”“绝绝子”“宝子们”等套路词。
-
-{GLOBAL_CONSTRAINTS}
-
-请严格按下面的标签格式输出，不要解释，不要用代码块：
-<passed> 整体是否通过，只写 true 或 false。
-<issues> 每个问题用一个 <issue> 标签，属性 dimension 是维度名、severity 取 error 或 warning、location 是问题所在（如 hook、body_points、cta），标签内容写问题描述；没有问题就输出空标签。
-<rewrite_suggestions> 每条具体修改建议用一个 <suggestion> 标签；没有就输出空标签。"""
-
-_REVIEW_USER = """本次创作模式：{fusion_level}
-待审核文案：
-{fusion_result}
-用户意图解析（用于核对核心信息是否保留）：
-{intent_result}
-
-请按6个维度审核，按标签格式输出。"""
-
-_REVIEW_EXAMPLE = """<passed>false</passed>
-<issues>
-<issue dimension="夸大承诺" severity="error" location="body_points">出现了“一喷100%掉光”的绝对化表述，违反广告法</issue>
-<issue dimension="用户意图保留" severity="warning" location="cta">用户强调的“39块钱”没有保留</issue>
-</issues>
-<rewrite_suggestions>
-<suggestion>把“一喷100%掉光”改为“喷上等几分钟，大部分油污能擦掉”</suggestion>
-<suggestion>在结尾补回“39块钱625ml”</suggestion>
-</rewrite_suggestions>"""
-
-
-# 5 套模板默认数据（seed 数据源与 loader 的兜底）
-DEFAULT_TEMPLATES: list[dict] = [
-    {
-        "name": "图片多模态分析",
-        "prompt_type": "image_analysis",
-        "version": TEMPLATE_VERSION,
-        "system_prompt": _IMAGE_ANALYSIS_SYSTEM,
-        "user_prompt_template": _IMAGE_ANALYSIS_USER,
-        "example_output": _IMAGE_ANALYSIS_EXAMPLE,
-        "is_active": True,
-    },
-    {
-        "name": "用户文案意图解析",
-        "prompt_type": "intent_parsing",
-        "version": TEMPLATE_VERSION,
-        "system_prompt": _INTENT_SYSTEM,
-        "user_prompt_template": _INTENT_USER,
-        "example_output": _INTENT_EXAMPLE,
-        "is_active": True,
-    },
-    {
-        "name": "文案融合生成",
-        "prompt_type": "copy_fusion",
-        "version": TEMPLATE_VERSION,
-        "system_prompt": _FUSION_SYSTEM,
-        "user_prompt_template": _FUSION_USER,
-        "example_output": _FUSION_EXAMPLE,
-        "is_active": True,
-    },
-    {
-        "name": "编导级分镜",
-        "prompt_type": "storyboard",
-        "version": TEMPLATE_VERSION,
-        "system_prompt": _STORYBOARD_SYSTEM,
-        "user_prompt_template": _STORYBOARD_USER,
-        "example_output": _STORYBOARD_EXAMPLE,
-        "is_active": True,
-    },
-    {
-        "name": "文案审核",
-        "prompt_type": "review",
-        "version": TEMPLATE_VERSION,
-        "system_prompt": _REVIEW_SYSTEM,
-        "user_prompt_template": _REVIEW_USER,
-        "example_output": _REVIEW_EXAMPLE,
-        "is_active": True,
-    },
-]

packages/application/viral_video/reviewer.py

@@ -1,312 +0,0 @@
-"""文案审核 + 自动重写（#2040 第5套 Prompt）。
-
-6 维度：违规词 / 夸大承诺 / 事实一致性 / 用户意图保留 / 结构完整性 / 语气人设。
-LLM 审核之外叠加本地规则预检（保证即使 LLM 不可用也能兜住广告法红线）。
-"""
-
-from __future__ import annotations
-
-import logging
-import re
-from typing import Optional
-
-from packages.application.viral_video import xml_parser as xp
-from packages.application.viral_video.prompt_loader import (
-    get_template,
-    render_system_prompt,
-    render_user_prompt,
-)
-from packages.application.viral_video.schemas import (
-    FusionResult,
-    IntentResult,
-    ReviewIssue,
-    ReviewResult,
-)
-
-logger = logging.getLogger(__name__)
-
-# 本地规则：绝对化/夸大词
-_EXAGGERATION_PATTERNS = [
-    r"100\s*%",
-    r"百分百",
-    r"包治百病",
-    r"保证.{0,8}(有效|赚钱|瘦|好)",
-    r"绝对(有效|安全|靠谱)",
-    r"全网第一",
-    r"国家级",
-    r"特效",
-    r"立刻见效",
-    r"一喷(就|全|100)",
-]
-
-# 本地规则：平台违规/套路词
-_VIOLATION_PHRASES = [
-    "家人们谁懂啊",
-    "绝绝子",
-    "宝子们",
-    "yyds",
-    "最(好|强|牛|便宜)",  # 广告法极限词
-    "第一(名|品牌)?",
-]
-
-_LOCATIONS = ["title", "hook", "body_points", "cta", "script_segments"]
-
-
-class Reviewer:
-    def __init__(self, client=None):
-        if client is None:
-            from packages.shared.ai_client import get_doubao_client
-
-            client = get_doubao_client()
-        self.client = client
-
-    # ── 审核 ────────────────────────────────────────────────────────────
-    def review(self, fusion: FusionResult, intent: IntentResult, fusion_level: str) -> ReviewResult:
-        local = self._rule_check(fusion, intent, fusion_level)
-        llm_result = self._llm_review(fusion, intent, fusion_level)
-        if llm_result is None:
-            return ReviewResult(
-                passed=not local,
-                issues=local,
-                rewrite_suggestions=[],
-                raw="",
-            )
-        # LLM 与本地规则合并去重
-        issues = self._merge_issues(llm_result.issues, local)
-        return ReviewResult(
-            passed=llm_result.passed and not local,
-            issues=issues,
-            rewrite_suggestions=llm_result.rewrite_suggestions,
-            raw=llm_result.raw,
-        )
-
-    def _llm_review(self, fusion: FusionResult, intent: IntentResult, fusion_level: str) -> Optional[ReviewResult]:
-        template = get_template("review")
-        system = render_system_prompt(template)
-        user = render_user_prompt(
-            template,
-            fusion_level=fusion_level,
-            fusion_result=self._fusion_text(fusion),
-            intent_result=self._intent_text(intent),
-        )
-        raw = self.client.chat_completion(
-            [
-                {"role": "system", "content": system},
-                {"role": "user", "content": user},
-            ],
-            temperature=0.2,
-            max_tokens=1024,
-        )
-        if not raw:
-            return None
-        passed = xp.text_of(raw, "passed").strip().lower()
-        issues = [
-            ReviewIssue(
-                dimension=n["attrs"].get("dimension", "未知维度"),
-                severity=n["attrs"].get("severity", "warning"),
-                location=n["attrs"].get("location", ""),
-                text=n["text"],
-            )
-            for n in xp.find_all(raw, "issue")
-            if n["text"]
-        ]
-        suggestions = [n["text"] for n in xp.find_all(raw, "suggestion") if n["text"]]
-        parsed = ReviewResult(
-            passed=passed == "true" and not issues,
-            issues=issues,
-            rewrite_suggestions=suggestions,
-            raw=raw,
-        )
-        return parsed
-
-    # ── 本地规则预检 ────────────────────────────────────────────────────
-    def _rule_check(self, fusion: FusionResult, intent, fusion_level: str) -> list[ReviewIssue]:
-        issues: list[ReviewIssue] = []
-        for location, text in self._segments(fusion):
-            for pattern in _EXAGGERATION_PATTERNS:
-                if re.search(pattern, text):
-                    issues.append(
-                        ReviewIssue(
-                            dimension="夸大承诺",
-                            severity="error",
-                            location=location,
-                            text=f"出现夸大/绝对化表述：{self._hit(text, pattern)}",
-                        )
-                    )
-            for phrase in _VIOLATION_PHRASES:
-                if re.search(phrase, text, flags=re.IGNORECASE):
-                    issues.append(
-                        ReviewIssue(
-                            dimension="违规词",
-                            severity="error",
-                            location=location,
-                            text=f"出现违规或套路词：{self._hit(text, phrase)}",
-                        )
-                    )
-
-        # 结构完整性
-        if not fusion.title:
-            issues.append(ReviewIssue(dimension="结构完整性", severity="warning", location="title", text="缺少标题"))
-        if not fusion.hook:
-            issues.append(ReviewIssue(dimension="结构完整性", severity="warning", location="hook", text="缺少开头钩子"))
-        if not fusion.cta:
-            issues.append(ReviewIssue(dimension="结构完整性", severity="warning", location="cta", text="缺少行动号召"))
-
-        # 用户意图保留（must_keep）
-        full_text = self._fusion_text(fusion)
-        if fusion_level in {"ai_polish", "user_primary"} and intent is not None:
-            for message in intent.core_messages:
-                if message.must_keep:
-                    key = self._compact(message.text)
-                    if key and key[:10] not in self._compact(full_text):
-                        issues.append(
-                            ReviewIssue(
-                                dimension="用户意图保留",
-                                severity="warning",
-                                location="script_segments",
-                                text=f"用户核心信息被丢失：{message.text[:30]}",
-                            )
-                        )
-            for brand in intent.personal_brands:
-                if brand.text and brand.text not in full_text:
-                    issues.append(
-                        ReviewIssue(
-                            dimension="事实一致性",
-                            severity="error",
-                            location="script_segments",
-                            text=f"personal_brands 事实信息未原样保留：{brand.text[:30]}",
-                        )
-                    )
-        return issues
-
-    @staticmethod
-    def _hit(text: str, pattern: str) -> str:
-        match = re.search(pattern, text, flags=re.IGNORECASE)
-        return match.group(0) if match else pattern
-
-    @staticmethod
-    def _compact(text: str) -> str:
-        return re.sub(r"[\s，。！？、,.!?；;：:\"'“”‘’（）()【】\[\]]", "", text)
-
-    @staticmethod
-    def _merge_issues(llm_issues: list[ReviewIssue], local: list[ReviewIssue]) -> list[ReviewIssue]:
-        merged = list(local)
-        seen = {(i.dimension, Reviewer._compact(i.text)[:20]) for i in local}
-        for issue in llm_issues:
-            key = (issue.dimension, Reviewer._compact(issue.text)[:20])
-            if key not in seen:
-                merged.append(issue)
-                seen.add(key)
-        return merged
-
-    # ── 自动重写（1 次）─────────────────────────────────────────────────
-    def rewrite(
-        self,
-        fusion: FusionResult,
-        review: ReviewResult,
-        intent: IntentResult,
-        fusion_level: str,
-    ) -> FusionResult:
-        from packages.application.viral_video.generator import CopyGenerator
-
-        template = get_template("copy_fusion")
-        system_kwargs = {
-            "fusion_instruction": (
-                "【本次任务：按审核意见修正文案】只修改指出的问题，其他内容尽量原样保留；"
-                "personal_brands 事实信息逐字保留；修正后按原标签格式完整输出。"
-            ),
-            "global_constraints": "",
-            "negative_rules": "",
-        }
-        issue_text = "\n".join(f"- [{i.dimension}/{i.location}] {i.text}" for i in review.issues)
-        suggestion_text = "\n".join(f"- {s}" for s in review.rewrite_suggestions)
-        user = render_user_prompt(
-            template,
-            industry="",
-            target_customer="",
-            marketing_purpose="",
-            duration=fusion.estimated_duration or 15,
-            image_analysis="（沿用原图片分析）",
-            intent_result=self._intent_text(intent),
-        )
-        user = (
-            f"{user}\n\n原文案：\n{self._fusion_text(fusion)}\n\n"
-            f"审核发现的问题：\n{issue_text}\n\n修改建议：\n{suggestion_text or '（无）'}\n"
-            "请输出修正后的完整文案。"
-        )
-        system = render_system_prompt(template, **system_kwargs)
-        raw = self.client.chat_completion(
-            [
-                {"role": "system", "content": system},
-                {"role": "user", "content": user},
-            ],
-            temperature=0.5,
-            max_tokens=2048,
-        )
-        if not raw:
-            return self._rule_fix(fusion, review)
-        rewritten = CopyGenerator._parse_fusion(CopyGenerator(self.client), raw)
-        if not rewritten.title and not rewritten.script_segments:
-            return self._rule_fix(fusion, review)
-        # 保底：personal_brands 必须保留
-        full = self._fusion_text(rewritten)
-        for brand in intent.personal_brands:
-            if brand.text and brand.text not in full:
-                rewritten.cta = (rewritten.cta + brand.text).strip()
-        return rewritten
-
-    def _rule_fix(self, fusion: FusionResult, review: ReviewResult) -> FusionResult:
-        """LLM 重写不可用时的本地兜底：删除/替换明显违规表述。"""
-        replacements = [
-            (re.compile(r"100\s*%|百分百"), "大部分"),
-            (re.compile(r"绝对(有效|安全|靠谱)"), "比较\\1"),
-            (re.compile(r"包治百病"), "适用多种情况"),
-            (re.compile(r"立刻见效"), "坚持使用会有改善"),
-            (re.compile(r"一喷(就|全|100%)"), "喷上等一会儿可以"),
-            (re.compile(r"家人们谁懂啊|绝绝子|宝子们|yyds", re.IGNORECASE), ""),
-            (re.compile(r"最好|最强|最牛|最便宜"), "很不错"),
-        ]
-
-        def fix(text: str) -> str:
-            for pattern, repl in replacements:
-                text = pattern.sub(repl, text)
-            return text
-
-        fusion.title = fix(fusion.title)
-        fusion.hook = fix(fusion.hook)
-        fusion.cta = fix(fusion.cta)
-        for point in fusion.body_points:
-            point.text = fix(point.text)
-            point.elaboration = fix(point.elaboration)
-        for segment in fusion.script_segments:
-            segment.text = fix(segment.text)
-        fusion.raw = ""
-        return fusion
-
-    # ── 文本工具 ────────────────────────────────────────────────────────
-    @staticmethod
-    def _segments(fusion: FusionResult):
-        yield "title", fusion.title
-        yield "hook", fusion.hook
-        for point in fusion.body_points:
-            yield "body_points", f"{point.text} {point.elaboration}"
-        yield "cta", fusion.cta
-        for segment in fusion.script_segments:
-            yield "script_segments", segment.text
-
-    @staticmethod
-    def _fusion_text(fusion: FusionResult) -> str:
-        parts = [fusion.title, fusion.hook]
-        parts += [p.text for p in fusion.body_points]
-        parts += [s.text for s in fusion.script_segments]
-        parts.append(fusion.cta)
-        return "\n".join(p for p in parts if p)
-
-    @staticmethod
-    def _intent_text(intent) -> str:
-        if intent is None:
-            return "无意图信息"
-        parts = [f"意图：{intent.intent_summary}"]
-        parts += [f"核心信息[must_keep={m.must_keep}]：{m.text}" for m in intent.core_messages]
-        parts += [f"事实（{b.category}）：{b.text}" for b in intent.personal_brands]
-        return "\n".join(parts)

packages/application/viral_video/schemas.py

@@ -1,116 +0,0 @@
-"""内部 Pydantic 校验模型（不暴露给运营，运营只看 DB 里的纯文本）。"""
-
-from __future__ import annotations
-
-from pydantic import BaseModel, Field
-
-
-class ProductItem(BaseModel):
-    name: str = "无法判断"
-    features: str = "无法判断"
-    position: str = "secondary"
-    image_index: int = 0
-
-
-class ColorItem(BaseModel):
-    hex: str = "#000000"
-    name: str = "无法判断"
-    coverage: float = 0.0
-
-
-class TextItem(BaseModel):
-    text: str = ""
-    position: str = ""
-
-
-class ImageAnalysis(BaseModel):
-    products: list[ProductItem] = Field(default_factory=list)
-    colors: list[ColorItem] = Field(default_factory=list)
-    has_person: bool = False
-    person_count: int = 0
-    people: dict[str, str] = Field(default_factory=dict)
-    mood: str = ""
-    visible_text: list[TextItem] = Field(default_factory=list)
-    scene: str = ""
-    quality: dict[str, str] = Field(default_factory=dict)
-    key_selling_points: list[str] = Field(default_factory=list)
-    raw: str = ""
-
-
-class CoreMessage(BaseModel):
-    text: str
-    must_keep: bool = False
-    confidence: float = 0.0
-
-
-class PersonalBrand(BaseModel):
-    text: str
-    category: str = "brand"
-
-
-class IntentResult(BaseModel):
-    intent_summary: str = ""
-    core_messages: list[CoreMessage] = Field(default_factory=list)
-    personal_brands: list[PersonalBrand] = Field(default_factory=list)
-    emotion_tone: str = ""
-    missing_info: list[str] = Field(default_factory=list)
-    raw: str = ""
-
-
-class BodyPoint(BaseModel):
-    text: str
-    elaboration: str = ""
-    image_index: int = 0
-
-
-class ScriptSegment(BaseModel):
-    text: str
-    duration_sec: float = 0
-    image_index: int = 0
-
-
-class FusionResult(BaseModel):
-    title: str = ""
-    hook: str = ""
-    body_points: list[BodyPoint] = Field(default_factory=list)
-    cta: str = ""
-    script_segments: list[ScriptSegment] = Field(default_factory=list)
-    word_count: int = 0
-    estimated_duration: int = 0
-    raw: str = ""
-
-
-class KenBurns(BaseModel):
-    start: str = "0,0"
-    end: str = "0,0"
-    ease: str = "linear"
-
-
-class Clip(BaseModel):
-    image_index: int = 0
-    transition: str = "cut"
-    zoom: str | None = None
-    duration_sec: float = 0
-    bgm_note: str = ""
-    voice_text: str = ""
-    subtitle_text: str = ""
-    ken_burns: KenBurns = Field(default_factory=KenBurns)
-
-
-class Storyboard(BaseModel):
-    clips: list[Clip] = Field(default_factory=list)
-    raw: str = ""
-
-
-class ReviewIssue(BaseModel):
-    dimension: str
-    severity: str = "warning"
-    location: str = ""
-    text: str = ""
-
-
-class ReviewResult(BaseModel):
-    passed: bool = True
-    issues: list[ReviewIssue] = Field(default_factory=list)
-    rewrite_suggestions: list[str] = Field(default_factory=list)
-    raw: str = ""

packages/application/viral_video/xml_parser.py

@@ -1,104 +0,0 @@
-"""XML 标签式输出解析器（替代 json.loads）。
-
-LLM 按 ``<tag attr="x">内容</tag>`` 输出，本模块解析，解析失败不抛异常，
-由调用方走规则 fallback。采用栈式扫描，嵌套标签全部可提取（内外层都保留）。
-"""
-
-from __future__ import annotations
-
-import re
-from html import unescape
-from typing import Optional
-
-_OPEN_RE = re.compile(r"<(?P<tag>[\w-]+)(?P<attrs>(?:\s(?:[^>]*?\S)?)?)(?P<self>/?)>")
-_CLOSE_RE = re.compile(r"</(?P<tag>[\w-]+)\s*>")
-_ATTR_RE = re.compile(r"""([\w:-]+)\s*=\s*(?:"([^"]*)"|'([^']*)')""")
-
-
-def parse_attributes(raw: str) -> dict[str, str]:
-    """解析标签属性字符串。"""
-    attrs: dict[str, str] = {}
-    for match in _ATTR_RE.finditer(raw or ""):
-        value = match.group(2) if match.group(2) is not None else match.group(3)
-        attrs[match.group(1)] = value
-    return attrs
-
-
-def parse_tags(text: Optional[str]) -> list[dict]:
-    """提取全部标签（含嵌套内外层），返回 [{tag, attrs, text}]，按开标签出现顺序。"""
-    if not text:
-        return []
-    results: list[dict] = []
-    stack: list[dict] = []
-    token_re = re.compile(r"<[^>]+>")
-    for token in token_re.finditer(text):
-        raw_token = token.group(0)
-        # 先按开/闭标签匹配
-        open_match = _OPEN_RE.match(raw_token)
-        close_match = _CLOSE_RE.match(raw_token)
-        is_close_tag = raw_token.startswith("</")
-        if not is_close_tag and open_match:
-            is_self_close = open_match.group("self") == "/"
-            node = {
-                "tag": open_match.group("tag"),
-                "attrs": parse_attributes(open_match.group("attrs")),
-                "text": "",
-                "_start": token.end(),
-            }
-            if is_self_close:
-                node.pop("_start")
-                results.append(node)
-            else:
-                stack.append(node)
-                results.append(node)
-        elif is_close_tag and close_match:
-            tag = close_match.group("tag")
-            # 弹出到最近同名开标签
-            for idx in range(len(stack) - 1, -1, -1):
-                if stack[idx]["tag"] == tag:
-                    node = stack[idx]
-                    node["text"] = unescape(text[node["_start"] : token.start()].strip())
-                    node.pop("_start", None)
-                    del stack[idx:]
-                    break
-    # 未闭合标签：给剩余部分作为文本
-    for node in stack:
-        if "_start" in node:
-            node["text"] = unescape(text[node["_start"] :].strip())
-            node.pop("_start", None)
-    return results
-
-
-def find_all(text: Optional[str], tag: str) -> list[dict]:
-    """提取指定标签的全部节点。"""
-    return [n for n in parse_tags(text) if n["tag"] == tag]
-
-
-def find_first(text: Optional[str], tag: str) -> Optional[dict]:
-    nodes = find_all(text, tag)
-    return nodes[0] if nodes else None
-
-
-def text_of(text: Optional[str], tag: str, default: str = "") -> str:
-    node = find_first(text, tag)
-    return node["text"] if node else default
-
-
-def attr_bool(value: Optional[str], default: bool = False) -> bool:
-    if value is None:
-        return default
-    return value.strip().lower() in {"true", "1", "yes", "是"}
-
-
-def attr_float(value: Optional[str], default: float = 0.0) -> float:
-    try:
-        return float(value) if value is not None and value.strip() else default
-    except (TypeError, ValueError):
-        return default
-
-
-def attr_int(value: Optional[str], default: int = 0) -> int:
-    try:
-        return int(float(value)) if value is not None and value.strip() else default
-    except (TypeError, ValueError):
-        return default

packages/config/base.py

@@ -90,44 +90,17 @@ class SharedSettings(BaseSettings):
 
     # ── 豆包大模型（火山引擎方舟） ────────────────────────────────────────
     doubao_api_key: str = ""
-    doubao_model: str = "doubao-seed-2-1-pro-260915"  # 推理模型（Seed 2.1 Pro，深度思考+多模态；原 seed-1-6 已下线）
-    doubao_fast_model: str = (
-        "doubao-seed-2-1-lite-260915"  # 快速模型（Seed 2.1 Lite，高 RPM，编导/审核/VLM lite；原 1-5-pro-32k 已 Retiring）
-    )
+    doubao_model: str = "doubao-seed-1-6-250615"
     doubao_base_url: str = "https://ark.cn-beijing.volces.com/api/v3"
     doubao_timeout: int = 30
     doubao_max_retries: int = 2
-    doubao_vision_model: str = (
-        "doubao-seed-2-1-pro-260915"  # 高精度视觉（Seed 2.1 Pro 原生多模态；原 vision-pro-250328 已下线）
-    )
-    doubao_vision_lite_model: str = (
-        "doubao-seed-2-1-lite-260915"  # 快速视觉（Seed 2.1 Lite 原生多模态；原 vision-lite-250315 不可用）
-    )
-    doubao_vision_use_lite: bool = True  # viral-video 图片分析默认用 lite 提速
-    doubao_embedding_model: str = "doubao-embedding-vision-251215"  # 多模态向量化（原 large-text-240915 已 Retiring）
-    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）
-    doubao_image_model: str = (
-        "doubao-seedream-5-0-flash-260915"  # #2173: 信任链 Seedream 改 flash 模型（实测 pro 46.5s→flash 13s；pro AI化图仍被Seedance拦截）
-    )
-    doubao_image_size: str = "1K"  # #2173: 1K 已足够做 Seedance 参考图，2K 在 flash 下也 22s，1K 13s
-    doubao_image_timeout: int = 60  # #2173: flash+1K 通常15s内，给60s余量
-    doubao_trust_chain_enabled: bool = (
-        True  # #2173: 信任链总开关；若Seedream产物仍被Seedance拦截，可配 False 关闭直接t2v降级
-    )
-
-    # ── DashScope (阿里云百炼 Wan 3.0 等) ─────────────────────────────────
-    dashscope_api_key: str = ""
-    dashscope_base_url: str = "https://dashscope.aliyuncs.com/api/v1"
-    dashscope_video_timeout: int = 900  # Wan 视频任务轮询总超时（秒）
-    dashscope_video_poll_interval: int = 10
+    doubao_vision_model: str = "doubao-1-5-vision-pro-250915"
+    doubao_embedding_model: str = "doubao-embedding-large-text-240915"
 
     # ── 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）。