fix(viral-video): #2041 删除「生成进度」阶段列表面板，保留轮询做状态驱动

.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）。

.gitea/workflows/ci-pipeline.yml

@@ -437,7 +437,7 @@ jobs:
     if: "always() && needs.dedupe-check.outputs.skip_tests != 'true' && needs.check-frontend-only.outputs.skip_backend != 'true'"
     name: Unit Tests
     runs-on: ci-l2
-    timeout-minutes: 20
+    timeout-minutes: 8
     env:
       PIP_CACHE_DIR: /root/.cache/pip
       PIP_NO_CACHE_DIR: ''
@@ -1187,14 +1187,6 @@ jobs:
         DOUBAO_MODEL: "${{ secrets.DOUBAO_MODEL }}"
         DOUBAO_BASE_URL: "${{ secrets.DOUBAO_BASE_URL }}"
         DOUBAO_VISION_MODEL: "${{ secrets.DOUBAO_VISION_MODEL }}"
-        DOUBAO_VISION_LITE_MODEL: "${{ secrets.DOUBAO_VISION_LITE_MODEL }}"
-        DOUBAO_VISION_USE_LITE: "${{ secrets.DOUBAO_VISION_USE_LITE }}"
-        DOUBAO_IMAGE_MODEL: "${{ secrets.DOUBAO_IMAGE_MODEL }}"
-        DOUBAO_IMAGE_SIZE: "${{ secrets.DOUBAO_IMAGE_SIZE }}"
-        DOUBAO_IMAGE_TIMEOUT: "${{ secrets.DOUBAO_IMAGE_TIMEOUT }}"
-        DOUBAO_FAST_MODEL: "${{ secrets.DOUBAO_FAST_MODEL }}"
-        DOUBAO_TIMEOUT: "${{ secrets.DOUBAO_TIMEOUT }}"
-        DOUBAO_MAX_RETRIES: "${{ secrets.DOUBAO_MAX_RETRIES }}"
         WECHAT_APP_ID: "${{ secrets.WECHAT_APP_ID }}"
         WECHAT_APP_SECRET: "${{ secrets.WECHAT_APP_SECRET }}"
         TIKHUB_API_KEY: "${{ secrets.TIKHUB_API_KEY }}"

CHANGES.md

@@ -1,2 +0,0 @@
-Mon Oct  5 04:09:11 PM CST 2026
-2198 lite/pro并行竞速 (commit 9699a1f) — CI rebuild trigger Mon Oct  5 08:09:11 AM UTC 2026

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(),
-        ),
-    )

alembic/versions/096_feature_billing_fields.py

@@ -1,61 +0,0 @@
-"""功能计费积分字段（爆款/对口型/智能剪辑 DB 化计费）。
-
-给 gpu_lipsync_tasks / generation_tasks / lipsync_jobs 三张表加积分字段：
-- credits_prepaid: 提交任务时预扣积分
-- credits_cost: 最终结算积分
-- credits_transaction_id: 预扣流水 ID
-
-注意：feature_pricing_configs 配置表由 xiaoxia-admin 侧 migration 建立，
-本仓库只读，不在此创建。
-
-Revision ID: 096_feature_billing_fields
-Revises: 095_viral_video_prompt_templates
-Create Date: 2026-10-05
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "096_feature_billing_fields"
-down_revision = "095_viral_video_prompt_templates"
-branch_labels = None
-depends_on = None
-
-_TABLES = ("gpu_lipsync_tasks", "generation_tasks", "lipsync_jobs")
-_COLUMNS = (
-    ("credits_prepaid", sa.Float(), "0"),
-    ("credits_cost", sa.Float(), "0"),
-    ("credits_transaction_id", sa.String(36), ""),
-)
-
-
-def _table_exists(conn, name: str) -> bool:
-    return name in sa.inspect(conn).get_table_names()
-
-
-def upgrade() -> None:
-    conn = op.get_bind()
-    for table in _TABLES:
-        if not _table_exists(conn, table):
-            continue
-        existing = {c["name"] for c in sa.inspect(conn).get_columns(table)}
-        for col_name, col_type, default in _COLUMNS:
-            if col_name in existing:
-                continue
-            op.add_column(
-                table,
-                sa.Column(col_name, col_type, nullable=False, server_default=default),
-            )
-
-
-def downgrade() -> None:
-    conn = op.get_bind()
-    for table in _TABLES:
-        if not _table_exists(conn, table):
-            continue
-        existing = {c["name"] for c in sa.inspect(conn).get_columns(table)}
-        for col_name, _col_type, _default in _COLUMNS:
-            if col_name not in existing:
-                continue
-            op.drop_column(table, col_name)

alembic/versions/099_ai_model_router_seed.py

@@ -1,222 +0,0 @@
-# -*- coding: utf-8 -*-
-"""099: AI 模型路由层 seed — 补齐缺失模型和能力配置.
-
-幂等：所有 INSERT 先检查存在性。
-- ai_models: 补齐 qwen3.7-plus, seedream, seedance, embedding, wan3.0 等
-- ai_capability_configs: 补齐 image_generation, video_generation, embedding
-- 更新已有 capability 的 lite_model_id
-"""
-
-import json
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "099_ai_model_router_seed"
-down_revision = "098_viral_video_image_analysis_v5"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    conn = op.get_bind()
-
-    # CI 环境下 ai_models 表可能尚未创建（由 ORM 自动建表，非 migration）
-    # 如果表不存在则跳过 seed，由应用启动时 ORM 建表后首次访问时生效
-    table_check = conn.execute(sa.text("SELECT to_regclass('public.ai_models')")).scalar()
-    if not table_check:
-        # ai_models 表不存在，跳过所有 seed（CI 环境）
-        return
-
-    # ── 1. 补齐 ai_models 缺失记录 ────────────────────────────────────────────
-    existing_models = {
-        row[0]
-        for row in conn.execute(
-            sa.text("SELECT model_key FROM ai_models WHERE deleted_at IS NULL")
-        ).fetchall()
-    }
-
-    # 从已有 active 记录获取 API key（复用，不硬编码）
-    dashscope_key_row = conn.execute(
-        sa.text(
-            "SELECT api_key FROM ai_models WHERE provider='dashscope' AND deleted_at IS NULL AND api_key IS NOT NULL AND api_key != '' LIMIT 1"
-        )
-    ).first()
-    dashscope_key = dashscope_key_row[0] if dashscope_key_row else ""
-
-    volcengine_key_row = conn.execute(
-        sa.text(
-            "SELECT api_key FROM ai_models WHERE provider='volcengine' AND deleted_at IS NULL AND api_key IS NOT NULL AND api_key != '' LIMIT 1"
-        )
-    ).first()
-    volcengine_key = volcengine_key_row[0] if volcengine_key_row else ""
-
-    new_models = [
-        {
-            "model_key": "qwen3.7-plus",
-            "name": "通义千问3.7 Plus（VLM 兜底）",
-            "provider": "dashscope",
-            "api_key": dashscope_key,
-            "api_base": "https://dashscope.aliyuncs.com/compatible-mode/v1",
-            "description": "阿里云百炼 Qwen3.7 Plus 多模态模型，用于 VLM 兜底分析",
-        },
-        {
-            "model_key": "doubao-seedream-5-0-flash-260915",
-            "name": "Seedream 5.0 Flash（图片生成）",
-            "provider": "volcengine",
-            "api_key": volcengine_key,
-            "api_base": "https://ark.cn-beijing.volces.com/api/v3",
-            "description": "火山引擎 Seedream 5.0 Flash 文生图模型",
-        },
-        {
-            "model_key": "doubao-seedance-2-5-260628",
-            "name": "Seedance 2.5（视频生成）",
-            "provider": "volcengine",
-            "api_key": volcengine_key,
-            "api_base": "https://ark.cn-beijing.volces.com/api/v3",
-            "description": "火山引擎 Seedance 2.5 图/文生视频模型",
-        },
-        {
-            "model_key": "doubao-embedding-vision-251215",
-            "name": "豆包多模态向量嵌入",
-            "provider": "volcengine",
-            "api_key": volcengine_key,
-            "api_base": "https://ark.cn-beijing.volces.com/api/v3",
-            "description": "火山引擎豆包多模态向量嵌入模型",
-        },
-        {
-            "model_key": "wan3.0-video",
-            "name": "Wan 3.0 视频生成",
-            "provider": "dashscope",
-            "api_key": dashscope_key,
-            "api_base": "https://dashscope.aliyuncs.com/api/v1",
-            "description": "阿里云百炼 Wan 3.0 视频生成模型",
-        },
-        {
-            "model_key": "doubao-seed-2-1-pro-260915",
-            "name": "豆包 Seed 2.1 Pro（高精度推理）",
-            "provider": "volcengine",
-            "api_key": volcengine_key,
-            "api_base": "https://ark.cn-beijing.volces.com/api/v3",
-            "description": "火山引擎豆包 Seed 2.1 Pro 深度思考+多模态",
-        },
-    ]
-
-    for m in new_models:
-        if m["model_key"] not in existing_models:
-            conn.execute(
-                sa.text(
-                    """
-                    INSERT INTO ai_models (id, name, provider, model_key, api_key, api_base, description, status, is_default, usage_today, created_at, updated_at)
-                    VALUES (gen_random_uuid()::text, :name, :provider, :model_key, :api_key, :api_base, :description, 'active', false, 0, now(), now())
-                    """
-                ),
-                m,
-            )
-
-    # ── 2. 补齐 ai_capability_configs 缺失项 ──────────────────────────────────
-    cap_table_check = conn.execute(sa.text("SELECT to_regclass('public.ai_capability_configs')")).scalar()
-    if not cap_table_check:
-        return
-
-    existing_caps = {
-        row[0]
-        for row in conn.execute(
-            sa.text("SELECT capability_key FROM ai_capability_configs")
-        ).fetchall()
-    }
-
-    def _get_model_id(model_key: str) -> str | None:
-        row = conn.execute(
-            sa.text(
-                "SELECT id FROM ai_models WHERE model_key = :key AND deleted_at IS NULL AND status = 'active' LIMIT 1"
-            ),
-            {"key": model_key},
-        ).first()
-        return row[0] if row else None
-
-    # image_generation
-    if "image_generation" not in existing_caps:
-        mid = _get_model_id("doubao-seedream-5-0-flash-260915")
-        if mid:
-            conn.execute(
-                sa.text(
-                    """
-                    INSERT INTO ai_capability_configs (id, capability_key, capability_name, primary_model_id, timeout_seconds, max_retries, concurrency, extra_params, is_enabled, created_at, updated_at)
-                    VALUES (gen_random_uuid()::text, :ck, :cn, :pm, 60, 1, 2, :ep, true, now(), now())
-                    """
-                ),
-                {
-                    "ck": "image_generation",
-                    "cn": "图片生成（Seedream）",
-                    "pm": mid,
-                    "ep": json.dumps({"size": "1K"}),
-                },
-            )
-
-    # video_generation
-    if "video_generation" not in existing_caps:
-        mid = _get_model_id("doubao-seedance-2-5-260628")
-        fb_mid = _get_model_id("wan3.0-video")
-        if mid:
-            conn.execute(
-                sa.text(
-                    """
-                    INSERT INTO ai_capability_configs (id, capability_key, capability_name, primary_model_id, fallback_model_id, timeout_seconds, max_retries, concurrency, extra_params, is_enabled, created_at, updated_at)
-                    VALUES (gen_random_uuid()::text, :ck, :cn, :pm, :fm, 600, 1, 1, :ep, true, now(), now())
-                    """
-                ),
-                {
-                    "ck": "video_generation",
-                    "cn": "视频生成（Seedance/Wan）",
-                    "pm": mid,
-                    "fm": fb_mid,
-                    "ep": json.dumps({}),
-                },
-            )
-
-    # embedding
-    if "embedding" not in existing_caps:
-        mid = _get_model_id("doubao-embedding-vision-251215")
-        if mid:
-            conn.execute(
-                sa.text(
-                    """
-                    INSERT INTO ai_capability_configs (id, capability_key, capability_name, primary_model_id, timeout_seconds, max_retries, concurrency, extra_params, is_enabled, created_at, updated_at)
-                    VALUES (gen_random_uuid()::text, :ck, :cn, :pm, 30, 2, 5, :ep, true, now(), now())
-                    """
-                ),
-                {
-                    "ck": "embedding",
-                    "cn": "向量嵌入",
-                    "pm": mid,
-                    "ep": json.dumps({}),
-                },
-            )
-
-    # ── 3. 更新 image_analysis 的 lite_model_id ─────────────────────────────
-    lite_model_id = _get_model_id("qwen3.8-flash")
-    if lite_model_id:
-        conn.execute(
-            sa.text(
-                "UPDATE ai_capability_configs SET lite_model_id = :lite WHERE capability_key = 'image_analysis' AND lite_model_id IS NULL"
-            ),
-            {"lite": lite_model_id},
-        )
-
-
-def downgrade() -> None:
-    conn = op.get_bind()
-    # 安全检查表是否存在
-    table_check = conn.execute(sa.text("SELECT to_regclass('public.ai_models')")).scalar()
-    if not table_check:
-        return
-    conn.execute(
-        sa.text("DELETE FROM ai_capability_configs WHERE capability_key IN ('image_generation', 'video_generation', 'embedding')")
-    )
-    conn.execute(
-        sa.text(
-            "DELETE FROM ai_models WHERE model_key IN ('qwen3.7-plus', 'doubao-seedream-5-0-flash-260915', 'doubao-seedance-2-5-260628', 'doubao-embedding-vision-251215', 'wan3.0-video', 'doubao-seed-2-1-pro-260915') AND deleted_at IS NULL"
-        )
-    )

alembic/versions/100_fix_capability_model_bindings.py

@@ -1,107 +0,0 @@
-# -*- coding: utf-8 -*-
-"""100: 修正已有 capability 的模型绑定.
-
-幂等：仅当 primary_model_id 当前绑定到旧模型 (doubao-seed-1-6) 时才更新，
-避免覆盖用户在后台的自定义配置。
-
-- 更新 5 个 LLM capability (intent_parsing, copy_fusion, storyboard, copy_review, asset_classify)
-  的 primary_model_id 从 doubao-seed-1-6 改为 doubao-seed-2-1-pro-260915
-- 更新 image_analysis 的 primary/lite/fallback 模型绑定
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "100_fix_capability_model_bindings"
-down_revision = "099_ai_model_router_seed"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    conn = op.get_bind()
-
-    # Check tables exist
-    table_check = conn.execute(sa.text("SELECT to_regclass('public.ai_models')")).scalar()
-    if not table_check:
-        return
-
-    config_table_check = conn.execute(sa.text("SELECT to_regclass('public.ai_capability_configs')")).scalar()
-    if not config_table_check:
-        return
-
-    # Look up model IDs by model_key (not hardcoded UUIDs)
-    pro_model_row = conn.execute(
-        sa.text(
-            "SELECT id FROM ai_models WHERE model_key = 'doubao-seed-2-1-pro-260915' AND deleted_at IS NULL LIMIT 1"
-        )
-    ).first()
-    if not pro_model_row:
-        return
-    pro_model_id = pro_model_row[0]
-
-    old_model_row = conn.execute(
-        sa.text("SELECT id FROM ai_models WHERE model_key = 'doubao-seed-1-6-250615' LIMIT 1")
-    ).first()
-    old_model_id = old_model_row[0] if old_model_row else None
-
-    llm_capabilities = [
-        "intent_parsing",
-        "copy_fusion",
-        "storyboard",
-        "copy_review",
-        "asset_classify",
-    ]
-
-    for cap_key in llm_capabilities:
-        if old_model_id:
-            conn.execute(
-                sa.text(
-                    "UPDATE ai_capability_configs SET primary_model_id = :new_id, updated_at = NOW() "
-                    "WHERE capability_key = :cap_key AND primary_model_id = :old_id"
-                ),
-                {"new_id": pro_model_id, "old_id": old_model_id, "cap_key": cap_key},
-            )
-
-    # Update image_analysis
-    qwen38_row = conn.execute(
-        sa.text("SELECT id FROM ai_models WHERE model_key = 'qwen3.8-flash' AND deleted_at IS NULL LIMIT 1")
-    ).first()
-    qwen37_row = conn.execute(
-        sa.text("SELECT id FROM ai_models WHERE model_key = 'qwen3.7-plus' AND deleted_at IS NULL LIMIT 1")
-    ).first()
-
-    if qwen38_row and qwen37_row:
-        qwen38_id = qwen38_row[0]
-        qwen37_id = qwen37_row[0]
-
-        current_ia = conn.execute(
-            sa.text(
-                "SELECT primary_model_id, lite_model_id, fallback_model_id "
-                "FROM ai_capability_configs WHERE capability_key = 'image_analysis'"
-            )
-        ).first()
-
-        if current_ia:
-            current_primary, current_lite, current_fallback = current_ia
-            updates = {}
-            if current_primary != qwen38_id:
-                updates["primary_model_id"] = qwen38_id
-            if current_lite != qwen38_id:
-                updates["lite_model_id"] = qwen38_id
-            if current_fallback != qwen37_id:
-                updates["fallback_model_id"] = qwen37_id
-
-            if updates:
-                set_clause = ", ".join([f"{k} = :{k}" for k in updates.keys()])
-                set_clause += ", updated_at = NOW()"
-                updates["cap_key"] = "image_analysis"
-                conn.execute(
-                    sa.text(f"UPDATE ai_capability_configs SET {set_clause} WHERE capability_key = :cap_key"),
-                    updates,
-                )
-
-
-def downgrade() -> None:
-    pass

alembic/versions/101_qwen_vl_plus_and_max_tokens.py

@@ -1,153 +0,0 @@
-# -*- coding: utf-8 -*-
-"""101: 补齐 qwen-vl-plus 视觉模型并修正 image_analysis 绑定与 max_tokens.
-
-背景：
-- qwen-vl-plus 做图片识别时返回 JSON 约 500-600 tokens，旧硬编码
-  max_tokens=350 导致 JSON 被截断、解析失败返回"未识别"。
-- 代码侧已移除硬编码，改由 capability 的 DB 配置决定 max_tokens。
-
-幂等：
-- qwen-vl-plus 已存在则不插入；
-- 仅当 image_analysis 当前 primary_model 不是 qwen-vl-plus 时才更新绑定，
-  避免覆盖后台手动配置。
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "101_qwen_vl_plus_and_max_tokens"
-down_revision = "100_fix_capability_model_bindings"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    conn = op.get_bind()
-
-    models_table = conn.execute(sa.text("SELECT to_regclass('public.ai_models')")).scalar()
-    if not models_table:
-        return
-
-    caps_table = conn.execute(sa.text("SELECT to_regclass('public.ai_capability_configs')")).scalar()
-    if not caps_table:
-        return
-
-    # ── c. 补全其他 capability 的 max_tokens 默认值（幂等）──────────────────
-    # 放在 image_analysis 特定逻辑之前，确保任何分支 return 都不会跳过本段。
-    # 仅在当前值为 NULL 或过小 (<100) 时更新，不覆盖已有合理配置。
-    # embedding / tts / voice_clone 不走 chat 接口，无需设置。
-    default_max_tokens = {
-        "intent_parsing": 500,
-        "copy_fusion": 2500,
-        "storyboard": 4000,
-        "copy_review": 1000,
-        "asset_classify": 500,
-        "image_generation": 500,
-        "video_generation": 500,
-    }
-    for cap_key, mt in default_max_tokens.items():
-        conn.execute(
-            sa.text(
-                "UPDATE ai_capability_configs "
-                "SET max_tokens = :mt, updated_at = now() "
-                "WHERE capability_key = :key "
-                "AND (max_tokens IS NULL OR max_tokens < 100)"
-            ),
-            {"mt": mt, "key": cap_key},
-        )
-
-    # ── a. 确保 qwen-vl-plus 模型存在 ────────────────────────────────────────
-    conn.execute(sa.text("""
-            INSERT INTO ai_models (id, name, provider, model_key, api_key, api_base,
-                                   description, status, is_default, usage_today,
-                                   created_at, updated_at)
-            SELECT gen_random_uuid()::text,
-                   '通义千问VL Plus',
-                   'dashscope',
-                   'qwen-vl-plus',
-                   COALESCE(
-                       (SELECT api_key FROM ai_models
-                        WHERE provider = 'dashscope' AND deleted_at IS NULL
-                          AND api_key IS NOT NULL AND api_key != ''
-                        LIMIT 1),
-                       ''
-                   ),
-                   'https://dashscope.aliyuncs.com/compatible-mode/v1',
-                   '阿里云视觉理解模型（图片识别/分析）',
-                   'active', false, 0, now(), now()
-            WHERE NOT EXISTS (
-                SELECT 1 FROM ai_models
-                WHERE model_key = 'qwen-vl-plus' AND deleted_at IS NULL
-            )
-            """))
-
-    qwen_vl_row = conn.execute(
-        sa.text(
-            "SELECT id FROM ai_models WHERE model_key = 'qwen-vl-plus' "
-            "AND deleted_at IS NULL AND status = 'active' LIMIT 1"
-        )
-    ).first()
-    if not qwen_vl_row:
-        return
-    qwen_vl_id = qwen_vl_row[0]
-
-    qwen37_row = conn.execute(
-        sa.text(
-            "SELECT id FROM ai_models WHERE model_key = 'qwen3.7-plus' "
-            "AND deleted_at IS NULL AND status = 'active' LIMIT 1"
-        )
-    ).first()
-    qwen37_id = qwen37_row[0] if qwen37_row else None
-
-    # ── b. 仅当当前 primary 不是 qwen-vl-plus 时修正绑定与 max_tokens ───────
-    current = conn.execute(
-        sa.text(
-            "SELECT primary_model_id, lite_model_id, fallback_model_id, max_tokens "
-            "FROM ai_capability_configs WHERE capability_key = 'image_analysis'"
-        )
-    ).first()
-
-    if current is None:
-        # capability 不存在则创建
-        conn.execute(
-            sa.text("""
-                INSERT INTO ai_capability_configs
-                    (id, capability_key, capability_name, primary_model_id,
-                     lite_model_id, fallback_model_id, timeout_seconds,
-                     max_retries, max_tokens, concurrency, extra_params,
-                     is_enabled, created_at, updated_at)
-                VALUES (gen_random_uuid()::text, 'image_analysis', '图片分析',
-                        :primary, :primary, :fallback, 30, 1, 1000, 2,
-                        '{}'::jsonb, true, now(), now())
-                """),
-            {"primary": qwen_vl_id, "fallback": qwen37_id},
-        )
-        return
-
-    current_primary = current[0]
-    if current_primary == qwen_vl_id:
-        # 已经绑定 qwen-vl-plus：视为后台/数据迁移已处理，不覆盖任何配置
-        return
-
-    set_parts = [
-        "primary_model_id = :vl_id",
-        "lite_model_id = :vl_id",
-        "max_tokens = 1000",
-        "updated_at = now()",
-    ]
-    params: dict = {"vl_id": qwen_vl_id}
-    if qwen37_id is not None:
-        set_parts.insert(2, "fallback_model_id = :qwen37_id")
-        params["qwen37_id"] = qwen37_id
-
-    conn.execute(
-        sa.text(
-            "UPDATE ai_capability_configs SET " + ", ".join(set_parts) + " WHERE capability_key = 'image_analysis'"
-        ),
-        params,
-    )
-
-
-def downgrade() -> None:
-    pass

alembic/versions/102_image_analysis_max_tokens_1500.py

@@ -1,36 +0,0 @@
-# -*- coding: utf-8 -*-
-"""102: image_analysis max_tokens 1200 -> 1500.
-
-v6 prompt 更长、字段更多，旧 max_tokens 容易截断 JSON。
-仅在 image_analysis 当前 max_tokens < 1500 时更新（幂等，不覆盖后台已调到 >=1500 的配置）。
-"""
-
-import sqlalchemy as sa
-
-from alembic import op
-
-revision = "102_image_analysis_max_tokens_1500"
-down_revision = "101_qwen_vl_plus_and_max_tokens"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    conn = op.get_bind()
-
-    caps_table = conn.execute(sa.text("SELECT to_regclass('public.ai_capability_configs')")).scalar()
-    if not caps_table:
-        return
-
-    conn.execute(
-        sa.text(
-            "UPDATE ai_capability_configs "
-            "SET max_tokens = 1500, updated_at = now() "
-            "WHERE capability_key = 'image_analysis' "
-            "AND (max_tokens IS NULL OR max_tokens < 1500)"
-        )
-    )
-
-
-def downgrade() -> None:
-    pass

alembic/versions/103_v7_prompt_and_tokens_3000.py

@@ -1,194 +0,0 @@
-# -*- coding: utf-8 -*-
-"""image_analysis v7 prompt + max_tokens 3000 + max_retries 3
-
-Revision ID: 103_v7_prompt_and_tokens_3000
-Revises: 102_image_analysis_max_tokens_1500
-Create Date: 2026-10-07
-
-变更：
-1. 插入v7精简prompt（~1KB，v6 ~4.5KB，删除few-shot/冗长规则，减少输出token占用），设为active
-2. v6停用（is_active=False），保留历史
-3. image_analysis capability: max_tokens 1500→3000，max_retries 1→3
-
-ai_capability_configs 由应用 create_all 创建，全新 alembic-only 库可能不存在，
-故第3步做 to_regclass 守卫（同 102）。
-"""
-
-from sqlalchemy import text
-
-from alembic import op
-
-revision = "103_v7_prompt_and_tokens_3000"
-down_revision = "102_image_analysis_max_tokens_1500"
-branch_labels = None
-depends_on = None
-
-V7_SYSTEM = """# 角色
-你是一位专业的图片分析师，擅长准确识别图片中的场景、人物、物体、文字、氛围。
-
-# 任务
-对用户上传的图片逐张分析，描述你看到的内容，输出JSON格式。
-
-## 技能
-
-### 技能1：判断图片类型
-判断图片属于哪种类型，type字段填对应的英文值：
-- 商品图（product）：单个或多个商品、产品包装
-- 门店场景图（store）：店铺内部、门头招牌、货架陈列
-- 人物图（person）：人物形象、穿搭造型、肖像照片
-- 风景图（scene）：风景、动物、美食、街景
-- 其他（other）：以上都不是
-
-### 技能2：描述通用信息
-不管什么图都要描述：
-- type：图片类型，填product/store/person/scene/other其中一个
-- scene：一句话描述场景，例如"理疗养生店内部，摆着多张理疗床和产品货架"
-- mood：整体氛围，2-4个词，例如"整洁专业"、"热闹温馨"
-- colors：主要颜色，最多5个，写具体颜色名（亮红色/米白色/深蓝色，不写笼统的红色蓝色）
-- visible_text：图片里看到的文字，说明什么字、在什么位置，最多5条；没看到就空数组
-- lighting：光线情况，例如"明亮柔光"、"自然光"、"室内暖黄灯"
-- composition：怎么拍的，例如"居中特写"、"中景平视"、"俯拍"
-- has_person：有没有人，true或false
-
-### 技能3：描述门店场景
-如果是门店场景图（type="store"），还要描述：
-- store_type：什么类型的店，例如"养生馆"、"便利店"、"餐饮店"、"母婴店"
-- brand_signage：招牌上写了什么字、有什么品牌标识
-- visual_elements：看到哪些显眼的东西（招牌样式、灯光、货架、商品陈列、海报、收银台等），最多8个
-- product_categories：看到哪些品类的商品，例如"饮料零食"、"养生产品"
-- promotion_elements：有没有促销活动（打折海报、满减吊旗等），没有就空数组
-- atmosphere：店内什么氛围，例如"亲民生活化"、"老字号专业感"
-- cleanliness：店内干净程度，例如"干净整洁"、"货架整齐"
-- 看到顾客或店员要描述他们在做什么，has_person填true
-
-### 技能4：描述商品
-如果是商品图（type="product"），逐个商品描述：
-- product_name：商品名称，尽量具体，例如"OMO奥妙除菌除螨洗衣液"；看不出来填null
-- brand：什么牌子，看不出来填null
-- category：类目，从以下选一个：服饰鞋包/美妆/数码/食品/家居清洁/母婴/配饰/其他
-- package_type：什么包装，例如"瓶装"、"盒装"、"罐装"、"袋装"、"多瓶装"
-- package_color：包装主要颜色，写具体色（亮红色不写红色）
-- body_shape：瓶身或包装形状，例如"圆润胖瓶"、"竖款带把手瓶身"
-- label_design：标签设计，例如"红色标签印白色品牌logo"
-- key_text_on_package：包装上最显眼的文字（品牌名、功能词、卖点词），最多5个
-- product_features：包装特征，3-6个短语，包含颜色、瓶盖、形状、标签图案
-- key_selling_points：核心卖点，1-3个短语
-
-### 技能5：描述人物
-如果是人物图（type="person"），描述：
-- person_count：几个人
-- gender：性别（男/女/无法判断）
-- age_range：年龄段（儿童/青少年/青年/中年/老年/无法判断）
-- outfit_style：穿搭风格，例如"休闲日常"、"通勤商务"、"街头潮流"
-- upper_wear：上装（颜色+款式+材质），穿裙装不填
-- lower_wear：下装（颜色+款式+版型），穿裙装不填
-- dress_wear：裙装描述，穿上下装不填
-- outerwear：外套
-- shoes：鞋子
-- bag：包袋，没有填null
-- accessories：配饰（眼镜/帽子/项链/耳环/手表/手链/围巾/腰带等），没有填空数组
-- hairstyle：发型
-- makeup：妆容，男生或看不出填null
-- expression：表情，例如"微笑看镜头"、"冷酷无表情"
-- pose：姿势动作，例如"身直立正对镜头"、"单手撩发"
-- body_type：身材，例如"纤细苗条"、"高挑身材"、"丰满匀称"
-- portrait_prompt：80-150字详细描述人物形象（后面用来AI生成肖像图），要写清年龄段、穿搭完整细节、发型发色、妆容、表情、姿势、场景、光线、风格感觉，语言要有画面感
-
-### 技能6：描述风景
-如果是风景图（type="scene"），描述：
-- scene_type：什么场景，例如"自然风景"、"城市街景"、"动物"、"美食"
-- main_subject：画面主体是什么
-- key_elements：关键元素，最多8个
-- environment_objects：周围环境物体，最多8个
-- atmosphere：整体氛围，例如"秋日慵懒氛围感"、"清新自然氧气感"
-- 有人物就描述人物特征
-
-## 限制
-- 只输出JSON，不要任何解释文字，不要markdown代码块包裹，不要写"好的""以下是分析结果"这种废话
-- 颜色写具体色调（亮红色/米白色/深蓝色/翠绿色），不写笼统词汇
-- 瓶身、包装、招牌上的文字尽量识别出来（品牌名、功能词、卖点词）
-- 多个商品、多个人物分开描述，不要合并
-- 看不出来、不确定的字段填null或空数组，布尔值填true/false，绝对不要瞎编
-- 确保JSON格式合法，所有大括号、中括号、引号正确闭合
-- 数组字段控制数量：colors最多5个，visible_text最多5条，visual_elements最多8个，accessories最多10个"""
-V7_USER = "请分析这张图片，按系统消息的JSON结构输出。"
-
-
-def _capability_table_exists(bind) -> bool:
-    return bool(bind.execute(text("SELECT to_regclass('public.ai_capability_configs')")).scalar())
-
-
-def upgrade() -> None:
-    bind = op.get_bind()
-    # 1. 停用旧的active image_analysis prompt（含v6）
-    bind.execute(
-        text(
-            "UPDATE viral_video_prompt_templates SET is_active = FALSE "
-            "WHERE prompt_type = 'image_analysis' AND is_active = TRUE"
-        )
-    )
-    # 2. 幂等插入v7（存在则更新并重新激活）
-    existing = bind.execute(
-        text("SELECT id FROM viral_video_prompt_templates " "WHERE prompt_type = 'image_analysis' AND version = 7")
-    ).fetchone()
-    if existing:
-        bind.execute(
-            text(
-                "UPDATE viral_video_prompt_templates SET is_active = TRUE, "
-                "system_prompt = :sys, user_prompt_template = :usr, "
-                "name = 'v7 精简结构化分析', updated_at = NOW() "
-                "WHERE prompt_type = 'image_analysis' AND version = 7"
-            ),
-            {"sys": V7_SYSTEM, "usr": V7_USER},
-        )
-    else:
-        bind.execute(
-            text(
-                "INSERT INTO viral_video_prompt_templates "
-                "(prompt_type, version, name, system_prompt, user_prompt_template, "
-                "is_active, created_at, updated_at) "
-                "VALUES ('image_analysis', 7, 'v7 精简结构化分析', "
-                ":sys, :usr, TRUE, NOW(), NOW())"
-            ),
-            {"sys": V7_SYSTEM, "usr": V7_USER},
-        )
-    # 3. capability max_tokens=3000、max_retries=3（表不存在则跳过）
-    if _capability_table_exists(bind):
-        bind.execute(
-            text(
-                "UPDATE ai_capability_configs SET max_tokens = 3000, "
-                "updated_at = NOW() "
-                "WHERE capability_key = 'image_analysis' AND "
-                "(max_tokens IS NULL OR max_tokens < 3000)"
-            )
-        )
-        bind.execute(
-            text(
-                "UPDATE ai_capability_configs SET max_retries = 3, updated_at = NOW() "
-                "WHERE capability_key = 'image_analysis' AND "
-                "(max_retries IS NULL OR max_retries < 3)"
-            )
-        )
-
-
-def downgrade() -> None:
-    bind = op.get_bind()
-    # 删除v7
-    bind.execute(
-        text("DELETE FROM viral_video_prompt_templates " "WHERE prompt_type = 'image_analysis' AND version = 7")
-    )
-    # 恢复v6为active
-    bind.execute(
-        text(
-            "UPDATE viral_video_prompt_templates SET is_active = TRUE "
-            "WHERE prompt_type = 'image_analysis' AND version = 6"
-        )
-    )
-    # tokens/retries回退
-    if _capability_table_exists(bind):
-        bind.execute(
-            text(
-                "UPDATE ai_capability_configs SET max_tokens = 1500, max_retries = 1, "
-                "updated_at = NOW() WHERE capability_key = 'image_analysis'"
-            )
-        )

alembic/versions/104_v8_image_analysis_and_storyboard_v3.py

@@ -1,242 +0,0 @@
-# -*- coding: utf-8 -*-
-"""image_analysis v8 prompt + storyboard v3 prompt - 用户端展示格式 markdown 控制
-
-Revision ID: 104_v8_display_markdown
-Revises: 103_v7_prompt_and_tokens_3000
-Create Date: 2026-10-07
-
-变更：
-1. image_analysis v8: 在 v7 基础上 system_prompt 末尾追加「## 用户端展示格式」章节，
-   要求 VLM 在每张图的 JSON 里输出 summary_markdown 字段（markdown 格式的图片描述），
-   v8 设 is_active=true，v7 设 is_active=false。
-2. storyboard v3: 在 v2 基础上 system_prompt 追加要求 LLM 在 copy_result 中
-   输出 copy_display_markdown 字段（markdown 格式的完整文案展示），
-   v3 设 is_active=true，v2 设 is_active=false。
-"""
-
-from sqlalchemy import text
-
-from alembic import op
-
-revision = "104_v8_display_markdown"
-down_revision = "103_v7_prompt_and_tokens_3000"
-branch_labels = None
-depends_on = None
-
-# ── v8 追加的 system prompt 内容 ──────────────────────────────────────
-V8_SYSTEM_APPEND = """
-
-## 用户端展示格式
-
-对于每张分析的图片，在 JSON 中额外输出一个 **summary_markdown** 字段，用 markdown 格式写出给用户看的图片描述。
-
-格式要求（根据图片类型自适应）：
-
-**商品图（type=product）**示例：
-### 商品名称
-**品牌**：品牌名 | **类目**：服饰鞋包/美妆/数码/...
-**核心特征**
-- 特征1：描述
-- 特征2：描述
-**外观**：颜色+材质+设计描述
-**包装**：包装类型描述
-**文字信息**：包装上看到的文字
-
-**门店场景图（type=store）**示例：
-### 门店名称/类型
-**类型**：奶茶店/便利店/养生馆/...
-**品牌标识**：招牌文字描述
-**环境氛围**：店内整体感觉
-**陈列亮点**
-- 亮点1
-- 亮点2
-**氛围**：亲民/专业/时尚/...
-
-**人物图（type=person）**示例：
-### 人物描述
-**形象**：年龄段 + 风格
-**穿搭**
-- 上装：颜色+款式
-- 下装：颜色+款式
-- 配饰：...
-**气质**：表情+姿势+整体感觉
-
-**风景/场景图（type=scene）**示例：
-### 场景名称
-**类型**：自然风景/城市街景/动物/美食
-**主体**：画面主要元素
-**氛围**：整体感觉描述
-
-要求：
-- 内容真实具体，从实际图片分析得出
-- 用 markdown 语法：**加粗**、列表、标题
-- 控制在 100-200 字
-- 不要编造图片中没有的信息
-"""
-
-# ── storyboard v3 追加的 system prompt 内容 ──────────────────────────
-V3_STORYBOARD_APPEND = """
-
-## 用户端展示格式
-
-在输出分镜脚本的同时，在顶层输出一个 **copy_display_markdown** 字段（用 XML 标签 <copy_display_markdown> 包裹），用 markdown 格式写出完整文案展示。
-
-格式示例：
-# 标题/主题
-
-## 整体概要
-一句话描述视频内容
-
-## 分镜预览
-
-### 镜头1（0-3秒）
-**景别**：近景俯拍，缓慢推镜
-**画面**：场景描述
-**台词**：口播文本
-**动作**：人物动作描述
-
-### 镜头2（3-9秒）
-...
-
-## 完整口播
-完整口播文案文本
-
-要求：
-- 把所有分镜按时间顺序整理成易读的格式
-- 用 markdown 语法组织，**加粗**标签、##二级标题、列表等
-- 控制在 300-500 字
-- 让用户一眼看懂视频会拍成什么样
-"""
-
-
-def upgrade() -> None:
-    bind = op.get_bind()
-
-    # ── 1. image_analysis v8 ──────────────────────────────────────────
-    # 停用所有 active image_analysis prompt
-    bind.execute(
-        text(
-            "UPDATE viral_video_prompt_templates SET is_active = FALSE "
-            "WHERE prompt_type = 'image_analysis' AND is_active = TRUE"
-        )
-    )
-
-    # 读取 v7 的 prompt 内容作为基础
-    v7_row = bind.execute(
-        text(
-            "SELECT system_prompt, user_prompt_template, COALESCE(example_output, '') "
-            "FROM viral_video_prompt_templates "
-            "WHERE prompt_type = 'image_analysis' "
-            "ORDER BY version DESC LIMIT 1"
-        )
-    ).fetchone()
-
-    if v7_row:
-        v7_system = v7_row[0] or ""
-        v8_system = v7_system + V8_SYSTEM_APPEND
-        v8_user = v7_row[1] or "{image_url}"
-        v8_example = v7_row[2] or ""
-
-        # 幂等：已有 v8 则更新，否则插入
-        existing_v8 = bind.execute(
-            text("SELECT id FROM viral_video_prompt_templates " "WHERE prompt_type = 'image_analysis' AND version = 8")
-        ).fetchone()
-        if existing_v8:
-            bind.execute(
-                text(
-                    "UPDATE viral_video_prompt_templates SET is_active = TRUE, "
-                    "system_prompt = :sys, user_prompt_template = :usr, "
-                    "example_output = :ex, name = 'v8 用户端展示格式', "
-                    "updated_at = NOW() "
-                    "WHERE prompt_type = 'image_analysis' AND version = 8"
-                ),
-                {"sys": v8_system, "usr": v8_user, "ex": v8_example},
-            )
-        else:
-            bind.execute(
-                text(
-                    "INSERT INTO viral_video_prompt_templates "
-                    "(prompt_type, version, name, system_prompt, user_prompt_template, "
-                    "example_output, is_active, created_at, updated_at) "
-                    "VALUES ('image_analysis', 8, 'v8 用户端展示格式', "
-                    ":sys, :usr, :ex, TRUE, NOW(), NOW())"
-                ),
-                {"sys": v8_system, "usr": v8_user, "ex": v8_example},
-            )
-
-    # ── 2. storyboard v3 ─────────────────────────────────────────────
-    # 停用所有 active storyboard prompt
-    bind.execute(
-        text(
-            "UPDATE viral_video_prompt_templates SET is_active = FALSE "
-            "WHERE prompt_type = 'storyboard' AND is_active = TRUE"
-        )
-    )
-
-    # 读取当前 storyboard prompt
-    sb_row = bind.execute(
-        text(
-            "SELECT system_prompt, user_prompt_template, COALESCE(example_output, '') "
-            "FROM viral_video_prompt_templates "
-            "WHERE prompt_type = 'storyboard' "
-            "ORDER BY version DESC LIMIT 1"
-        )
-    ).fetchone()
-
-    if sb_row:
-        sb_system = sb_row[0] or ""
-        v3_system = sb_system + V3_STORYBOARD_APPEND
-        v3_user = sb_row[1] or ""
-        v3_example = sb_row[2] or ""
-
-        existing_v3 = bind.execute(
-            text("SELECT id FROM viral_video_prompt_templates " "WHERE prompt_type = 'storyboard' AND version = 3")
-        ).fetchone()
-        if existing_v3:
-            bind.execute(
-                text(
-                    "UPDATE viral_video_prompt_templates SET is_active = TRUE, "
-                    "system_prompt = :sys, user_prompt_template = :usr, "
-                    "example_output = :ex, name = 'v3 用户端展示格式', "
-                    "updated_at = NOW() "
-                    "WHERE prompt_type = 'storyboard' AND version = 3"
-                ),
-                {"sys": v3_system, "usr": v3_user, "ex": v3_example},
-            )
-        else:
-            bind.execute(
-                text(
-                    "INSERT INTO viral_video_prompt_templates "
-                    "(prompt_type, version, name, system_prompt, user_prompt_template, "
-                    "example_output, is_active, created_at, updated_at) "
-                    "VALUES ('storyboard', 3, 'v3 用户端展示格式', "
-                    ":sys, :usr, :ex, TRUE, NOW(), NOW())"
-                ),
-                {"sys": v3_system, "usr": v3_user, "ex": v3_example},
-            )
-
-
-def downgrade() -> None:
-    bind = op.get_bind()
-
-    # 删除 v8
-    bind.execute(
-        text("DELETE FROM viral_video_prompt_templates " "WHERE prompt_type = 'image_analysis' AND version = 8")
-    )
-    # 恢复 v7 active
-    bind.execute(
-        text(
-            "UPDATE viral_video_prompt_templates SET is_active = TRUE, updated_at = NOW() "
-            "WHERE prompt_type = 'image_analysis' AND version = 7"
-        )
-    )
-
-    # 删除 v3
-    bind.execute(text("DELETE FROM viral_video_prompt_templates " "WHERE prompt_type = 'storyboard' AND version = 3"))
-    # 恢复 storyboard v2 active
-    bind.execute(
-        text(
-            "UPDATE viral_video_prompt_templates SET is_active = TRUE, updated_at = NOW() "
-            "WHERE prompt_type = 'storyboard' AND version = 2"
-        )
-    )

alembic/versions/105_narration_first.py

@@ -1,116 +0,0 @@
-# -*- coding: utf-8 -*-
-"""image_analysis v8 + storyboard v3 叙述优先重写版（架构大简化）
-
-Revision ID: 105_narration_first
-Revises: 104_v8_display_markdown
-Create Date: 2026-10-07
-
-变更：
-1. image_analysis v8：用「叙述优先」版整体替换 104 的 append 版——VLM 主交付物是
-   自然叙述 summary_markdown，结构化字段仅保留 type/name/brand/has_person，
-   顶层 products 改名 images；v8 active，其余 image_analysis 全部 deactivate。
-2. storyboard v3：整体替换为风格重写版（口播口语化、画面有画面感、
-   copy_display_markdown 流畅叙述）；v3 active，其余 storyboard deactivate。
-3. intent_parsing 类型模板全部 deactivate（意图解析步骤已删除）。
-模板内容直接取自 packages.application.viral_video.prompts.DEFAULT_TEMPLATES，
-保证代码默认值与 DB seed 完全一致。
-"""
-
-from sqlalchemy import text
-
-from alembic import op
-from packages.application.viral_video.prompts import DEFAULT_TEMPLATES
-
-revision = "105_narration_first"
-down_revision = "104_v8_display_markdown"
-branch_labels = None
-depends_on = None
-
-
-def _tpl(prompt_type: str, version: int) -> dict:
-    for t in DEFAULT_TEMPLATES:
-        if t["prompt_type"] == prompt_type and t["version"] == version:
-            return t
-    raise RuntimeError("default template missing: %s v%s" % (prompt_type, version))
-
-
-def _upsert(bind, t: dict) -> None:
-    existing = bind.execute(
-        text("SELECT id FROM viral_video_prompt_templates " "WHERE prompt_type = :pt AND version = :ver"),
-        {"pt": t["prompt_type"], "ver": t["version"]},
-    ).fetchone()
-    params = {
-        "pt": t["prompt_type"],
-        "ver": t["version"],
-        "name": t["name"],
-        "sys": t["system_prompt"],
-        "usr": t["user_prompt_template"],
-        "ex": t.get("example_output", "") or "",
-    }
-    if existing:
-        bind.execute(
-            text(
-                "UPDATE viral_video_prompt_templates SET name = :name, "
-                "system_prompt = :sys, user_prompt_template = :usr, "
-                "example_output = :ex, is_active = TRUE, updated_at = NOW() "
-                "WHERE prompt_type = :pt AND version = :ver"
-            ),
-            params,
-        )
-    else:
-        bind.execute(
-            text(
-                "INSERT INTO viral_video_prompt_templates "
-                "(prompt_type, version, name, system_prompt, user_prompt_template, "
-                "example_output, is_active, created_at, updated_at) "
-                "VALUES (:pt, :ver, :name, :sys, :usr, :ex, TRUE, NOW(), NOW())"
-            ),
-            params,
-        )
-
-
-def upgrade() -> None:
-    bind = op.get_bind()
-
-    # 1. image_analysis：停用全部后写入叙述优先 v8
-    bind.execute(
-        text("UPDATE viral_video_prompt_templates SET is_active = FALSE " "WHERE prompt_type = 'image_analysis'")
-    )
-    _upsert(bind, _tpl("image_analysis", 8))
-
-    # 2. storyboard：停用全部后写入重写版 v3
-    bind.execute(text("UPDATE viral_video_prompt_templates SET is_active = FALSE " "WHERE prompt_type = 'storyboard'"))
-    _upsert(bind, _tpl("storyboard", 3))
-
-    # 3. intent_parsing 已废弃：全部停用
-    bind.execute(
-        text("UPDATE viral_video_prompt_templates SET is_active = FALSE " "WHERE prompt_type = 'intent_parsing'")
-    )
-
-    # 4. review 模板确保 active
-    bind.execute(text("UPDATE viral_video_prompt_templates SET is_active = TRUE " "WHERE prompt_type = 'review'"))
-
-
-def downgrade() -> None:
-    bind = op.get_bind()
-    # 恢复 104 的 v8/v3 无法重建（内容已替换），仅把版本 active 状态回退：
-    # 停用新版，尝试恢复 v7 / v2
-    bind.execute(
-        text(
-            "UPDATE viral_video_prompt_templates SET is_active = FALSE "
-            "WHERE prompt_type IN ('image_analysis','storyboard') "
-            "AND version IN (8, 3)"
-        )
-    )
-    bind.execute(
-        text(
-            "UPDATE viral_video_prompt_templates SET is_active = TRUE "
-            "WHERE prompt_type = 'image_analysis' AND version = 7"
-        )
-    )
-    bind.execute(
-        text(
-            "UPDATE viral_video_prompt_templates SET is_active = TRUE "
-            "WHERE prompt_type = 'storyboard' AND version = 2"
-        )
-    )

alembic/versions/106_system_settings.py

@@ -1,43 +0,0 @@
-# -*- coding: utf-8 -*-
-"""system_settings 正式建表（#2246）
-
-Revision ID: 106_system_settings
-Revises: 105_narration_first
-Create Date: 2026-10-08
-
-system_settings 表此前在 staging 手工创建（对应 034 占位迁移），
-此处补正式迁移保证其他环境一致。CREATE TABLE/INDEX 使用 IF NOT EXISTS，
-对已手工建表的环境幂等。
-"""
-
-from alembic import op
-
-revision = "106_system_settings"
-down_revision = "105_narration_first"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.execute("""
-        CREATE TABLE IF NOT EXISTS system_settings (
-            id VARCHAR(36) NOT NULL,
-            setting_key VARCHAR(100) NOT NULL,
-            setting_value TEXT,
-            setting_type VARCHAR(20) NOT NULL,
-            description VARCHAR(255) NOT NULL DEFAULT '',
-            is_public BOOLEAN NOT NULL DEFAULT FALSE,
-            updated_by VARCHAR(36),
-            category VARCHAR(50) NOT NULL DEFAULT 'general',
-            created_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT NOW(),
-            updated_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT NOW(),
-            CONSTRAINT pk_system_settings PRIMARY KEY (id),
-            CONSTRAINT uq_system_settings_setting_key UNIQUE (setting_key)
-        )
-        """)
-    op.execute("CREATE INDEX IF NOT EXISTS ix_system_settings_category " "ON system_settings (category)")
-
-
-def downgrade() -> None:
-    op.execute("DROP INDEX IF EXISTS ix_system_settings_category")
-    op.execute("DROP TABLE IF EXISTS system_settings")

alembic/versions/107_add_language_to_viral_video_jobs.py

@@ -1,23 +0,0 @@
-"""add language column to viral_video_jobs
-
-Revision ID: 107
-Revises: 106_system_settings
-Create Date: 2026-10-09
-
-"""
-
-from alembic import op
-
-# revision identifiers, used by Alembic.
-revision = "107"
-down_revision = "106_system_settings"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.execute("ALTER TABLE viral_video_jobs " "ADD COLUMN IF NOT EXISTS language VARCHAR(20) NOT NULL DEFAULT 'zh-CN'")
-
-
-def downgrade() -> None:
-    op.execute("ALTER TABLE viral_video_jobs DROP COLUMN IF EXISTS language")

apps/api/app/api/router.py

@@ -1,4 +1,3 @@
-from app.api.routes.admin.ditto_emotion import router as admin_ditto_emotion_router
 from app.api.routes.ai import router as ai_router
 from app.api.routes.ai_avatar_render import router as ai_avatar_render_router
 from app.api.routes.asset_diagnosis import router as asset_diagnosis_router
@@ -243,6 +242,3 @@ api_router.include_router(
     tags=["GPU Worker"],
 )
 api_router.include_router(viral_video_router, prefix="/viral-video", tags=["爆款视频"])
-
-# #2246：后台 Ditto 表情配置（router 自带 /admin/ditto-emotion 前缀）
-api_router.include_router(admin_ditto_emotion_router)

apps/api/app/api/routes/admin/__init__.py

@@ -1 +0,0 @@
-"""后台管理路由（#2246 起）."""

apps/api/app/api/routes/admin/ditto_emotion.py

@@ -1,163 +0,0 @@
-"""Ditto 数字人表情后台配置 — #2246.
-
-路由前缀 /api/v1/admin/ditto-emotion，全部使用 _verify_internal_api_key 鉴权
-（X-API-Key header）。仅开放 5 项白名单配置：
-- ditto_emotion_enabled / ditto_emotion_model / ditto_emotion_temperature
-- ditto_emotion_prompt / ditto_blend_frames
-"""
-
-from __future__ import annotations
-
-from typing import Any
-
-from fastapi import APIRouter, Depends
-from pydantic import BaseModel
-
-from packages.application.system_config_service import get_system_config_service
-from packages.config import get_api_settings
-from packages.domain.system_setting import (
-    SETTING_TYPE_BOOL,
-    SETTING_TYPE_FLOAT,
-    SETTING_TYPE_INT,
-    SETTING_TYPE_STRING,
-)
-
-from ..auth import _verify_internal_api_key
-
-router = APIRouter(
-    prefix="/admin/ditto-emotion",
-    tags=["Admin"],
-    dependencies=[Depends(_verify_internal_api_key)],
-)
-
-MODEL_OPTIONS = [
-    "doubao-seed-2-1-lite-250915",
-    "doubao-seed-2-1-pro-250915",
-    "deepseek-v3",
-]
-
-# key → (类型, 分类)
-_WHITELIST: dict[str, str] = {
-    "ditto_emotion_enabled": SETTING_TYPE_BOOL,
-    "ditto_emotion_model": SETTING_TYPE_STRING,
-    "ditto_emotion_temperature": SETTING_TYPE_FLOAT,
-    "ditto_emotion_prompt": SETTING_TYPE_STRING,
-    "ditto_blend_frames": SETTING_TYPE_INT,
-}
-
-_DESCRIPTIONS: dict[str, str] = {
-    "ditto_emotion_enabled": "LLM 情绪分析开关。关闭时回退到原有关键词匹配模式，不影响正常出片。",
-    "ditto_emotion_model": "用于分析文案情绪的大模型。",
-    "ditto_emotion_temperature": "模型温度，0-1，越低越稳定保守。",
-    "ditto_emotion_prompt": "情绪分析提示词，核心调优入口，必须包含 {文案} 占位符。",
-    "ditto_blend_frames": "表情切换过渡帧数（6-30），越大越柔和。",
-}
-
-
-def _settings():
-    return get_api_settings()
-
-
-def _default_value(key: str) -> Any:
-    return getattr(_settings(), key)
-
-
-def _build_config_item(key: str) -> dict[str, Any]:
-    item: dict[str, Any] = {
-        "key": key,
-        "type": _WHITELIST[key],
-        "description": _DESCRIPTIONS.get(key, ""),
-        "default": _default_value(key),
-    }
-    service = get_system_config_service()
-    item["value"] = service.get_config(key, _default_value(key))
-    if key == "ditto_emotion_model":
-        item["model_options"] = list(MODEL_OPTIONS)
-    return item
-
-
-class ConfigUpdatePayload(BaseModel):
-    configs: dict[str, Any]
-
-
-class TestPayload(BaseModel):
-    test_text: str
-
-
-def _validate_value(key: str, value: Any) -> Any:
-    st = _WHITELIST[key]
-    if st == SETTING_TYPE_BOOL:
-        if not isinstance(value, bool):
-            raise ValueError(f"{key} 必须是布尔值")
-    elif st == SETTING_TYPE_INT:
-        if isinstance(value, bool) or not isinstance(value, int):
-            raise ValueError(f"{key} 必须是整数")
-        if not 6 <= value <= 30:
-            raise ValueError(f"{key} 必须在 6-30 之间")
-    elif st == SETTING_TYPE_FLOAT:
-        if isinstance(value, bool):
-            raise ValueError(f"{key} 必须是数字")
-        try:
-            value = float(value)
-        except (TypeError, ValueError) as exc:
-            raise ValueError(f"{key} 必须是数字") from exc
-        if not 0.0 <= value <= 1.0:
-            raise ValueError(f"{key} 必须在 0-1 之间")
-    elif st == SETTING_TYPE_STRING:
-        if not isinstance(value, str):
-            raise ValueError(f"{key} 必须是字符串")
-        if key == "ditto_emotion_prompt" and value.strip() and "{文案}" not in value:
-            raise ValueError("提示词必须包含 {文案} 占位符")
-        if key == "ditto_emotion_model" and value not in MODEL_OPTIONS:
-            raise ValueError(f"模型必须是以下之一：{', '.join(MODEL_OPTIONS)}")
-    return value
-
-
-@router.get("/config")
-def get_config() -> dict[str, Any]:
-    return {"configs": [_build_config_item(k) for k in _WHITELIST]}
-
-
-@router.put("/config")
-def update_config(
-    payload: ConfigUpdatePayload,
-    x_api_key: str = Depends(_verify_internal_api_key),
-) -> dict[str, Any]:
-    configs = payload.configs
-    illegal = [k for k in configs if k not in _WHITELIST]
-    if illegal:
-        return {
-            "ok": False,
-            "error": f"不允许修改的配置项：{', '.join(illegal)}",
-        }
-    service = get_system_config_service()
-    updated: dict[str, Any] = {}
-    for key, raw in configs.items():
-        try:
-            value = _validate_value(key, raw)
-        except ValueError as exc:
-            return {"ok": False, "error": str(exc)}
-        service.set_config(
-            key,
-            value,
-            setting_type=_WHITELIST[key],
-            updated_by=x_api_key[:8] if x_api_key else None,
-        )
-        updated[key] = value
-    return {"ok": True, "updated": updated}
-
-
-@router.post("/config/test")
-def test_config(payload: TestPayload) -> dict[str, Any]:
-    text = (payload.test_text or "").strip()
-    if not text:
-        return {"ok": False, "error": "test_text 不能为空"}
-    from packages.application.ditto_emotion_service import get_ditto_emotion_service
-
-    service = get_ditto_emotion_service()
-    segments = service.analyze(text)
-    return {
-        "ok": True,
-        "enabled": service.enabled,
-        "segments": [s.to_dict() for s in segments],
-    }

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

@@ -41,6 +41,7 @@ from packages.application import (
     GetGenerationTaskUseCase,
     ListGeneratedVideosByTaskUseCase,
 )
+from packages.middleware.points_gate import points_gate
 
 logger = logging.getLogger(__name__)
 
@@ -269,6 +270,7 @@ 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),

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

@@ -44,7 +44,6 @@ from packages.application import (
     GetGenerationTaskUseCase,
     ListGeneratedVideosByTaskUseCase,
 )
-from packages.domain import feature_pricing_service
 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）
@@ -164,6 +163,8 @@ def _infer_expected_categories(script_tags: set[str] | None) -> set[str] | None:
     return matched or None
 
 
+from packages.middleware.points_gate import points_gate
+
 logger = logging.getLogger(__name__)
 
 router = APIRouter()
@@ -464,6 +465,7 @@ 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),
@@ -700,17 +702,6 @@ def create_generation_task(
         logger.info("画中画已下线，strategy_id %s → one_take", effective_strategy_id)
         effective_strategy_id = "one_take"
 
-    # ── smart_edit 计费预扣（全局 points 开关 + 功能开关均开才扣） ──
-    # 首期固定价：dynamic_cost=0，price=(0+fixed_cost)×multiplier，price_cap 封顶。
-    # 预览任务不扣费；按任务条数扣费，任一任务预扣失败（余额不足）整体拒绝。
-    smart_edit_charge = 0.0
-    charged_task_count = 0
-    if not request.is_preview and feature_pricing_service.is_feature_enabled("smart_edit"):
-        unit_credits, _bd = feature_pricing_service.calculate_price("smart_edit", 0.0)
-        if unit_credits > 0:
-            smart_edit_charge = round(unit_credits * count, 2)
-            charged_task_count = count
-
     # 批量生成（count>1）：每个变体必须走与单视频完全相同的独立选片流程（#1743/#1749）。
     # - 变体 0：clone 源 plan（不污染源 plan），变体 1..N-1 用 reselect_plan_for_variant
     #   完整重跑选片（素材级去重：fresh 优先 → 受控复用 overlap≤20% → 短素材禁复用）；
@@ -941,42 +932,6 @@ def create_generation_task(
             )
             # 变体序号写入 extra_meta（响应/排查时可辨识）
             task.extra_meta["variant_index"] = task_index
-
-            # smart_edit 逐条预扣（首期固定价，credits_cost=prepaid，不做结算）
-            task_txn_id = ""
-            if charged_task_count > 0:
-                from packages.domain.points_service import PointsService
-
-                unit_credits = round(smart_edit_charge / count, 2)
-                res = PointsService().deduct_points(
-                    user_id=user_id,
-                    amount=unit_credits,
-                    source="smart_edit",
-                    db=db,
-                    description="智能剪辑生成预扣",
-                    ref_id=task.id,
-                )
-                if not res.get("success"):
-                    # 余额不足：退还本次请求已扣积分后整体拒绝
-                    already_charged = round(unit_credits * task_index, 2)
-                    if already_charged > 0:
-                        PointsService().refund_points(
-                            user_id=user_id,
-                            amount=already_charged,
-                            source="smart_edit",
-                            db=db,
-                            ref_id=task.id,
-                            description="智能剪辑批量提交失败退回",
-                        )
-                    raise HTTPException(
-                        status_code=402,
-                        detail=(f"积分不足：智能剪辑每条需 {unit_credits:.2f} 积分，当前余额 {res.get('balance', 0)}"),
-                    )
-                task_txn_id = str(res.get("transaction_id") or "")
-                task.credits_prepaid = unit_credits
-                task.credits_cost = unit_credits
-                task.credits_transaction_id = task_txn_id
-                generation_task_repository.update(task)
             try:
                 # 兜底关联编辑计划：前端未传 source_edit_plan_id 时，
                 # 通过 template_id + user_id 在 DB 层直接查找最新的 plan。

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

@@ -89,7 +89,6 @@ def get_balance(
         is_member=_is_member(current_user),
         member_type=_member_type(current_user),
         member_expires_at=getattr(current_user.user, "member_expires_at", None),
-        credits_enabled=_credits_enabled(),
     )
 
 
@@ -146,22 +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)
@@ -173,7 +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()
@@ -189,6 +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,
@@ -202,11 +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,
@@ -407,7 +390,7 @@ async def prepare_direct_upload(
                 duplicated=True,
                 skip_transfer=True,
                 asset_id=existing.id,
-                url=_get_existing_asset_url(existing, storage_service),
+                url=existing.file_url or storage_service.get_url(existing.storage_key) or "",
             )
 
     file_id = uuid4().hex[:8]

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

@@ -1,21 +1,14 @@
 """爆款视频 API 路由。
 
-v1.6 三步分步流水线端点（单次 Seedance 出片版）：
-  POST   /api/v1/viral-video/analyze-images          阶段1：创建任务 + 仅做图片/视频分析，暂停在 image_analyzed
-  POST   /api/v1/viral-video/{job_id}/generate-copy  阶段2：用户填完参数后跑意图+文案+分镜+审核，暂停在 copy_generated
-  POST   /api/v1/viral-video/{job_id}/confirm-copy   阶段3：用户确认/编辑文案后跑渲染，直到完成
-
-旧端点（兼容保留，旧前端/一键生成模式）：
-  POST   /api/v1/viral-video/generate                一键入队，前半段跑到 wait_user_confirm
-  POST   /api/v1/viral-video/{job_id}/confirm-intent 旧的意图确认后继续渲染
-
-通用：
-  GET    /api/v1/viral-video/{job_id}                查询任务状态（含 image_analysis/copy_result 编导脚本）
-  GET    /api/v1/viral-video/history                 历史记录
-  POST   /api/v1/viral-video/{job_id}/retry          重试失败任务
-  POST   /api/v1/viral-video/{job_id}/analyze-style  触发风格分析
-  GET    /api/v1/viral-video/style-templates         风格模板列表
-  WS     /api/v1/viral-video/ws/{job_id}?token=      WebSocket 进度推送
+端点：
+  POST   /api/v1/viral-video/generate          创建爆款视频任务
+  GET    /api/v1/viral-video/{job_id}          查询任务状态
+  GET    /api/v1/viral-video/history            历史记录
+  POST   /api/v1/viral-video/{job_id}/retry     重试失败任务
+  POST   /api/v1/viral-video/{job_id}/confirm-intent  确认意图文案
+  POST   /api/v1/viral-video/{job_id}/analyze-style   触发风格分析
+  GET    /api/v1/viral-video/style-templates    获取风格模板列表
+  WS     /api/v1/viral-video/ws/{job_id}?token=  WebSocket 进度推送（订阅 Redis pub/sub）
 """
 
 from __future__ import annotations
@@ -26,17 +19,10 @@ from app.auth import AuthenticatedUser, get_current_user
 from app.core.celery_app import celery_app
 from app.dependencies import get_db_session
 from app.schemas.viral_video import (
-    AnalyzeImagesRequest,
     AnalyzeStyleRequest,
     AnalyzeStyleResponse,
-    ConfirmCopyRequest,
     ConfirmIntentRequest,
     CreateViralVideoRequest,
-    CreditsFormulaBreakdown,
-    EstimateCreditsRequest,
-    EstimateCreditsResponse,
-    GenerateCopyRequest,
-    RetryViralVideoRequest,
     StyleTemplateListResponse,
     StyleTemplateResponse,
     ViralVideoHistoryResponse,
@@ -49,9 +35,7 @@ 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__)
 
@@ -61,59 +45,6 @@ router = APIRouter()
 # ── Helpers ──────────────────────────────────────────────────────────────
 
 
-def _build_copy_result(job) -> dict | None:
-    """v1.6: 返回编导分镜脚本 CopyResult 结构（给前端/Seedance 使用）。
-
-    - 若 job.copy_result 已持久化（v1.6 worker 生成），直接返回（补 final_copy 兜底）。
-    - 否则从老字段（generated_copy_text=口播, storyboard=分镜列表, intent_result）拼装兼容结构。
-    """
-    cr = getattr(job, "copy_result", None)
-    if isinstance(cr, dict) and cr:
-        out = dict(cr)
-        # 向后兼容字段
-        voiceover = out.get("voiceover_script", "") or ""
-        out.setdefault("final_copy", voiceover)
-        out.setdefault("suggested_copy", voiceover)
-        out.setdefault("title", "")
-        return out
-    # 兼容 v1.5 老数据：storyboard 是老格式 [{order,type,description,text,duration,...}]
-    copy_text = getattr(job, "generated_copy_text", "") or ""
-    sb = getattr(job, "storyboard", None) or []
-    intent = getattr(job, "intent_result", None) or {}
-    if not copy_text and not sb:
-        return None
-    title = ""
-    if isinstance(intent, dict):
-        title = intent.get("suggested_title") or intent.get("intent", "") or ""
-    shots = []
-    for seg in sb:
-        if isinstance(seg, dict):
-            shots.append(
-                {
-                    "time_range": "",
-                    "shot_type_angle_movement": seg.get("ken_burns", ""),
-                    "scene_and_dialogue": (seg.get("text") or "")
-                    + (" " + seg.get("description", "") if seg.get("description") else ""),
-                    "action_details": "",
-                    "audio_bgm": "",
-                    "transition": seg.get("transition", "硬切"),
-                    "reference_image_index": None,
-                }
-            )
-    ratio = getattr(job, "video_ratio", None) or "9:16"
-    return {
-        "overview": {"theme": title, "total_duration": getattr(job, "duration", 15), "aspect_ratio": ratio},
-        "scene_and_lighting": "",
-        "shots": shots,
-        "hard_constraints": ["无字幕", "无水印", "人物一致性"],
-        "negative_prompts": ["字幕", "水印", "错误文字", "五官崩坏"],
-        "voiceover_script": copy_text,
-        "final_copy": copy_text,
-        "suggested_copy": copy_text,
-        "title": title,
-    }
-
-
 def _to_response(job) -> ViralVideoJobResponse:
     return ViralVideoJobResponse(
         id=job.id,
@@ -125,7 +56,7 @@ def _to_response(job) -> ViralVideoJobResponse:
         viral_structure=job.viral_structure,
         marketing_purpose=job.marketing_purpose,
         bgm_preference=job.bgm_preference,
-        duration=job.duration or 15,
+        duration=job.duration,
         user_copy_text=job.user_copy_text,
         fusion_level=job.fusion_level,
         reference_audio_path=job.reference_audio_path,
@@ -134,23 +65,9 @@ def _to_response(job) -> ViralVideoJobResponse:
         style_guide=job.style_guide,
         style_template_id=job.style_template_id,
         status=job.status,
-        current_stage=getattr(job, "current_stage", "") or "",
-        phase_message=getattr(job, "phase_message", "") or "",
-        image_analysis=getattr(job, "image_analysis", None),
-        storyboard=getattr(job, "storyboard", None),
-        generated_copy_text=getattr(job, "generated_copy_text", "") or "",
-        copy_result=_build_copy_result(job),
-        voice_id=getattr(job, "voice_id", "") or "",
-        voice_source=getattr(job, "voice_source", "") or "",
-        language=getattr(job, "language", "zh-CN") or "zh-CN",
-        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,
-        pre_trusted_images=getattr(job, "pre_trusted_images", None) or None,
-        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),
+        credits_cost=job.credits_cost,
         error_msg=job.error_msg,
         retry_count=job.retry_count,
         started_at=job.started_at,
@@ -192,19 +109,13 @@ def create_viral_video(
         viral_structure=request.viral_structure,
         marketing_purpose=request.marketing_purpose,
         bgm_preference=request.bgm_preference,
-        duration=request.duration or 15,
+        duration=request.duration,
         user_copy_text=request.user_copy_text,
         fusion_level=request.fusion_level,
         reference_audio_path=request.reference_audio_path,
         reference_video_url=request.reference_video_url,
         style_strength=request.style_strength,
         style_template_id=request.style_template_id,
-        voice_id=getattr(request, "voice_id", "") or "",
-        voice_source=getattr(request, "voice_source", "") or "",
-        video_ratio=getattr(request, "video_ratio", "9:16") or "9:16",
-        video_model=getattr(request, "video_model", "") or "",
-        video_resolution=getattr(request, "video_resolution", "720p") or "720p",
-        copy_result=None,
     )
 
     # 持久化
@@ -222,292 +133,6 @@ def create_viral_video(
     return _to_response(job)
 
 
-@router.post("/analyze-images", response_model=ViralVideoJobResponse)
-def analyze_images(
-    request: AnalyzeImagesRequest,
-    authenticated_user: AuthenticatedUser = Depends(get_current_user),
-    session: Session = Depends(get_db_session),
-) -> ViralVideoJobResponse:
-    """v1.5 阶段1：创建任务并仅做图片/视频 VLM 分析，跑完后状态=image_analyzed。
-
-    前端拿到 image_analysis（商品名/品牌/特征/颜色/材质等结构化结果）展示给用户；
-    用户填完营销参数后再调 /{id}/generate-copy 进入阶段2。
-    """
-    from packages.domain.viral_video import ViralVideoJob
-
-    repo = _get_job_repo(session)
-    job = ViralVideoJob(
-        user_id=authenticated_user.user.id,
-        images=list(request.images),
-        reference_video_url=request.reference_video_url or "",
-        style_template_id=request.style_template_id or "",
-        style_strength=request.style_strength or "medium",
-        voice_id=request.voice_id or "",
-        voice_source=request.voice_source or "",
-        language=getattr(request, "language", "zh-CN") or "zh-CN",
-        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")
-    # 允许首次进入（IMAGE_ANALYZED/PENDING）、失败重试（FAILED）、文案重新生成（COPY_GENERATED/COMPLETED）
-    if job.status not in (
-        ViralVideoStatus.IMAGE_ANALYZED,
-        ViralVideoStatus.PENDING,
-        ViralVideoStatus.FAILED,
-        ViralVideoStatus.COPY_GENERATED,
-        ViralVideoStatus.COMPLETED,
-    ):
-        raise HTTPException(status_code=409, detail=f"任务当前状态 {job.status} 不能生成文案")
-
-    # 失败重试 / 重新生成：retry_count 自增
-    if job.status in (ViralVideoStatus.FAILED, ViralVideoStatus.COPY_GENERATED, ViralVideoStatus.COMPLETED):
-        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.language = getattr(request, "language", "") or job.language or "zh-CN"
-    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）")
-    # #2218: 额外校验 copy_result 完整性，防止孤儿/脏数据进入渲染
-    if not isinstance(job.copy_result, dict) or not job.copy_result:
-        raise HTTPException(status_code=409, detail="文案数据缺失，请先点击「生成文案」")
-
-    # Bug1 fix: 用户 confirm 时允许修改 video_model/video_resolution/video_ratio/duration
-    old_duration = int(getattr(job, "duration", 15) or 15)
-    old_resolution = getattr(job, "video_resolution", "720p") or "720p"
-    old_ratio = getattr(job, "video_ratio", "9:16") or "9:16"
-    old_model = getattr(job, "video_model", None) or "seedance-2.5"
-
-    if request.duration is not None:
-        job.duration = max(5, min(30, int(request.duration)))
-    if request.video_resolution is not None:
-        job.video_resolution = request.video_resolution
-    if request.video_ratio is not None:
-        job.video_ratio = request.video_ratio
-    if request.video_model is not None:
-        job.video_model = request.video_model
-    if request.voice_id is not None:
-        job.voice_id = request.voice_id
-    if request.voice_source is not None:
-        job.voice_source = request.voice_source
-    if getattr(request, "language", None) is not None:
-        job.language = request.language
-
-    param_changed = (
-        (request.duration is not None and int(request.duration) != old_duration)
-        or (request.video_resolution is not None and request.video_resolution != old_resolution)
-        or (request.video_ratio is not None and request.video_ratio != old_ratio)
-        or (request.video_model is not None and request.video_model != old_model)
-    )
-
-    # 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 param_changed and already_paid:
-            # 参数变更：回退旧预扣，按新参数重新预扣
-            from packages.domain.points_rules import calculate_viral_video_credits, resolve_video_dimensions
-            from packages.domain.points_service import PointsService
-
-            old_w, old_h = resolve_video_dimensions(old_resolution, old_ratio)
-            old_est = calculate_viral_video_credits(old_duration, old_w, old_h, old_model)
-            new_w, new_h = resolve_video_dimensions(
-                getattr(job, "video_resolution", "720p") or "720p",
-                job.video_ratio or "9:16",
-            )
-            new_est = calculate_viral_video_credits(
-                int(job.duration or 15), new_w, new_h, job.video_model or "seedance-2.5"
-            )
-            svc = PointsService()
-            # 退回旧预扣
-            if getattr(job, "credits_transaction_id", None):
-                svc.refund_points(
-                    user_id=authenticated_user.user.id,
-                    amount=float(job.credits_prepaid),
-                    source="viral_video",
-                    db=session,
-                    ref_id=job.credits_transaction_id,
-                    description="confirm-copy 参数变更退还旧预扣",
-                )
-            # 预扣新金额
-            if new_est > 0:
-                res = svc.deduct_viral_video(authenticated_user.user.id, new_est, 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 {new_est} 积分，当前余额 {balance}",
-                            "required": new_est,
-                            "balance": balance,
-                        },
-                    )
-                job.credits_prepaid = new_est
-                job.credits_transaction_id = res.get("transaction_id", "") or ""
-            logger.info(
-                "[爆款视频][confirm-copy] 参数变更，积分重算: old=%d new=%d job_id=%s", old_est, new_est, job.id
-            )
-        elif 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,
@@ -542,17 +167,6 @@ def list_style_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,
@@ -572,156 +186,31 @@ def get_viral_video_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
-
+    """重试失败的爆款视频任务。"""
     repo = _get_job_repo(session)
     job = repo.get(job_id)
     if job is None:
         raise HTTPException(status_code=404, detail="任务不存在")
     if job.user_id != authenticated_user.user.id:
         raise HTTPException(status_code=403, detail="无权操作此任务")
-
-    # 判定是否为僵尸 running 任务：running 超过 10 分钟且心跳停止超过 2 分钟
-    now = datetime.now(timezone.utc)
-    is_stale_running = False
-    if job.status == ViralVideoStatus.RUNNING and job.started_at is not None:
-        hb = getattr(job, "heartbeat_at", None) or job.updated_at
-        if (now - job.started_at).total_seconds() > 10 * 60 and hb is not None and (now - hb).total_seconds() > 2 * 60:
-            is_stale_running = True
-
-    if job.status != ViralVideoStatus.FAILED and not is_stale_running:
-        raise HTTPException(status_code=409, detail="只有失败或超时的任务可以重试")
-
-    # ── 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
+    if job.status != ViralVideoStatus.FAILED:
+        raise HTTPException(status_code=409, detail="只有失败的任务可以重试")
 
     # 重置状态
     job.retry_count += 1
     job.status = ViralVideoStatus.PENDING
-    job.error_msg = "" if not is_stale_running else "任务执行超时，已重置重试"
+    job.error_msg = ""
     job.started_at = None
     job.completed_at = None
-    job.current_stage = ""
-    job.phase_message = ""
-    job.heartbeat_at = None
     repo.update(job)
 
     # 重新入队
     try:
         celery_app.send_task("worker.run_viral_video_pipeline", args=[job.id])
-        logger.info(
-            "[爆款视频] 重试入队: job_id=%s retry_count=%d stale=%s params_changed=%s",
-            job.id,
-            job.retry_count,
-            is_stale_running,
-            param_changed,
-        )
+        logger.info("[爆款视频] 重试入队: job_id=%s retry_count=%d", job.id, job.retry_count)
     except Exception as e:
         logger.error("[爆款视频] 重试入队失败: %s", e, exc_info=True)
         job.mark_failed(f"重试入队失败: {e}")
@@ -965,28 +454,13 @@ async def viral_video_websocket(websocket: WebSocket, job_id: str) -> None:
         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)
-            # #P0: 初始快照必须包含前端重连/刷新所需的业务字段，
-            # 结构对齐 worker 推送的 image_analyzed / copy_generated 事件。
-            data: dict = {"status": status_val}
-            ia = getattr(job, "image_analysis", None)
-            if isinstance(ia, dict) and ia:
-                data["image_analysis"] = ia
-            cr = _build_copy_result(job)
-            if isinstance(cr, dict) and cr:
-                data["copy_result"] = cr
-            gct = getattr(job, "generated_copy_text", "") or ""
-            if gct:
-                data["generated_copy_text"] = gct
-            sb = getattr(job, "storyboard", None) or []
-            if sb:
-                data["storyboard"] = sb
             initial = {
                 "type": "viral_video:progress",
                 "job_id": job_id,
                 "stage": _stage_from_status(job),
                 "progress": _estimate_progress(job),
                 "message": _initial_message(job),
-                "data": data,
+                "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
@@ -1031,8 +505,6 @@ def _job_status(job) -> str:
 _STATUS_STAGE = {
     "pending": "",
     "running": "",
-    "image_analyzed": "image_analysis",
-    "copy_generated": "review",
     "wait_user_confirm": "intent_parsing",
     "completed": "uploading",
     "failed": "",
@@ -1042,8 +514,6 @@ _STATUS_STAGE = {
 _STATUS_PROGRESS = {
     "pending": 0.0,
     "running": 5.0,
-    "image_analyzed": 15.0,
-    "copy_generated": 70.0,
     "wait_user_confirm": 35.0,
     "completed": 100.0,
     "failed": 0.0,
@@ -1053,8 +523,6 @@ _STATUS_PROGRESS = {
 _STATUS_MESSAGE = {
     "pending": "任务已创建，等待执行",
     "running": "任务执行中",
-    "image_analyzed": "图片分析完成，等待填写营销参数",
-    "copy_generated": "文案与分镜已生成，等待确认文案",
     "wait_user_confirm": "等待用户确认意图文案",
     "completed": "视频生成完成",
     "failed": "任务失败",

apps/api/app/schemas/points.py

@@ -13,13 +13,12 @@ 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")
-    credits_enabled: bool = Field(default=False, description="积分系统是否启用（false=免费放行不扣分）")
 
 
 # ============ 流水 ============
@@ -31,8 +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
@@ -100,9 +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
 
 
@@ -113,7 +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] = ""
 
@@ -171,7 +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/viral_video.py

@@ -1,4 +1,4 @@
-"""爆款视频 API schemas (v1.6 单次 Seedance 出片版)。"""
+"""爆款视频 API schemas。"""
 
 from __future__ import annotations
 
@@ -6,196 +6,81 @@ from datetime import datetime
 
 from pydantic import BaseModel, Field, field_validator
 
-# -- 枚举常量 --
+# ── 枚举常量 ─────────────────────────────────────────────────────────────
 
-VALID_FUSION_LEVELS = ("ai_full", "full_ai", "ai_polish", "user_primary")
+VALID_FUSION_LEVELS = ("ai_full", "ai_polish", "user_primary")
 VALID_STYLE_STRENGTHS = ("light", "medium", "strict")
 VALID_STAGES = (
     "image_analysis",
     "video_analysis",
     "intent_parsing",
-    "script_generation",
+    "copy_fusion",
+    "storyboard",
     "review",
     "tts",
+    "bgm_select",
     "rendering",
+    "musetalk",
     "uploading",
 )
-VALID_VIDEO_RATIOS = ("9:16", "16:9", "1:1", "4:3", "3:4", "21:9")
-VALID_DURATIONS = (5, 10, 15, 20, 25, 30)
-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 --
+# ── Request Schemas ────────────────────────────────────────────────────────
 
 
 class CreateViralVideoRequest(BaseModel):
-    """旧接口：一键创建（保留兼容）。"""
+    """创建爆款视频任务请求。"""
 
-    images: list[str] = Field(..., min_length=1, max_length=20)
-    industry: str = ""
-    target_customer: str = ""
-    persona_id: str = ""
-    viral_structure: str = ""
-    marketing_purpose: str = ""
-    bgm_preference: str = ""
-    duration: int = Field(default=15, ge=5, le=30, description="视频时长（秒），5-30")
-    user_copy_text: str = ""
-    fusion_level: str = "ai_polish"
-    reference_audio_path: str = ""
-    reference_video_url: str = ""
-    style_strength: str = "medium"
-    style_template_id: str = ""
-    voice_id: str = ""
-    voice_source: str = ""
-    language: str = "zh-CN"
-    video_ratio: str = "9:16"
-    video_model: str = ""
-    video_resolution: str = "720p"
+    images: list[str] = Field(..., min_length=1, max_length=20, description="产品图片 URL 列表")
+    industry: str = Field(default="", description="行业")
+    target_customer: str = Field(default="", description="目标客户描述")
+    persona_id: str = Field(default="", description="人设 ID")
+    viral_structure: str = Field(default="", description="爆款结构类型")
+    marketing_purpose: str = Field(default="", description="营销目的")
+    bgm_preference: str = Field(default="", description="BGM 偏好")
+    duration: int = Field(default=30, ge=5, le=180, description="视频时长（秒）")
+    user_copy_text: str = Field(default="", description="用户原始文案（我说你写）")
+    fusion_level: str = Field(default="ai_polish", description="文案融合级别: ai_full/ai_polish/user_primary")
+    reference_audio_path: str = Field(default="", description="参考音频路径")
+    # v1.3 新增
+    reference_video_url: str = Field(default="", description="参考爆款视频 URL")
+    style_strength: str = Field(default="medium", description="风格强度: light/medium/strict")
+    style_template_id: str = Field(default="", description="风格模板 ID")
 
     @field_validator("fusion_level")
     @classmethod
-    def _v_fl(cls, v: str) -> str:
-        if v == "full_ai":
-            return "ai_full"
+    def _validate_fusion_level(cls, v: str) -> str:
         if v not in VALID_FUSION_LEVELS:
-            raise ValueError(f"fusion_level must be one of {VALID_FUSION_LEVELS}")
+            raise ValueError(f"fusion_level 必须是 {VALID_FUSION_LEVELS} 之一")
         return v
 
     @field_validator("style_strength")
     @classmethod
-    def _v_ss(cls, v: str) -> str:
+    def _validate_style_strength(cls, v: str) -> str:
         if v not in VALID_STYLE_STRENGTHS:
-            raise ValueError(f"style_strength must be one of {VALID_STYLE_STRENGTHS}")
+            raise ValueError(f"style_strength 必须是 {VALID_STYLE_STRENGTHS} 之一")
         return v
 
 
-class AnalyzeImagesRequest(BaseModel):
-    """v1.5+ 阶段1：创建任务 + 图片/视频分析。"""
-
-    images: list[str] = Field(..., min_length=1, max_length=30)
-    reference_video_url: str = ""
-    style_template_id: str = ""
-    style_strength: str = "medium"
-    voice_id: str = ""
-    voice_source: str = ""
-    video_ratio: str = "9:16"
-    video_model: str = ""
-    video_resolution: str = "720p"
-    duration: int = Field(default=15, ge=5, le=30)
-    language: str = "zh-CN"
-
-
-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 = ""
-    language: str = "zh-CN"
-    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")
-    video_model: str | None = Field(default=None, description="用户选定的视频生成模型（confirm时可选）")
-    video_resolution: str | None = Field(default=None, description="用户选定的分辨率（confirm时可选）")
-    video_ratio: str | None = Field(default=None, description="用户选定的比例（confirm时可选）")
-    duration: int | None = Field(default=None, ge=5, le=30, description="用户选定的时长秒数（confirm时可选，5~30）")
-    voice_id: str | None = Field(default=None, description="用户选定的音色ID（confirm时可选）")
-    voice_source: str | None = Field(default=None, description="用户选定的音色来源（confirm时可选）")
-    language: str | None = Field(default=None, description="用户选定的语言（confirm时可选）")
-
-
 class ConfirmIntentRequest(BaseModel):
-    """旧 confirm-intent（兼容）。"""
+    """确认意图请求（confirm-intent）。"""
 
-    confirmed_copy: str = ""
-    adjustments: str = ""
+    confirmed_copy: str = Field(default="", description="用户确认/修改后的文案，为空表示使用 AI 生成的文案")
+    adjustments: str = Field(default="", description="用户对 AI 文案的调整意见")
 
 
 class AnalyzeStyleRequest(BaseModel):
+    """触发参考视频风格分析请求。"""
+
     reference_video_url: str = Field(..., description="参考视频 URL")
-    style_template_id: str = ""
+    style_template_id: str = Field(default="", description="风格模板 ID（可选覆盖）")
 
 
-# -- Response Schemas --
+# ── Response Schemas ───────────────────────────────────────────────────────
 
 
 class ViralVideoJobResponse(BaseModel):
-    """爆款视频任务响应（v1.6 包含 copy_result 编导脚本结构）。"""
+    """爆款视频任务响应。"""
 
     id: str
     user_id: str
@@ -206,7 +91,7 @@ class ViralVideoJobResponse(BaseModel):
     viral_structure: str = ""
     marketing_purpose: str = ""
     bgm_preference: str = ""
-    duration: int = 15
+    duration: int = 30
     user_copy_text: str = ""
     fusion_level: str = "ai_polish"
     reference_audio_path: str = ""
@@ -215,28 +100,9 @@ class ViralVideoJobResponse(BaseModel):
     style_guide: dict | None = None
     style_template_id: str = ""
     status: str
-    current_stage: str = (
-        ""  # 细粒度阶段 snake_case（analyzing_images/parsing_intent/generating_script/reviewing/tts_synthesizing/rendering_video/uploading）
-    )
-    phase_message: str = ""  # 中文阶段提示文案（前端轮询/SSE 直接展示）
-    image_analysis: dict | None = None
-    # v1.6 编导脚本（推荐前端使用）
-    copy_result: dict | None = None
-    # v1.5 兼容字段
-    storyboard: list | None = None
-    generated_copy_text: str = ""
-    # 音色/视频参数
-    voice_id: str = ""
-    voice_source: str = ""
-    language: str = "zh-CN"
-    video_ratio: str = "9:16"
-    video_model: str = ""
     intent_result: dict | None = None
     result_video_url: str = ""
-    pre_trusted_images: list[str] | None = None
-    video_resolution: str = "720p"
-    credits_prepaid: float = 0.0
-    credits_cost: float = 0.0
+    credits_cost: int = 0
     error_msg: str = ""
     retry_count: int = 0
     started_at: datetime | None = None
@@ -246,11 +112,15 @@ class ViralVideoJobResponse(BaseModel):
 
 
 class ViralVideoHistoryResponse(BaseModel):
+    """历史记录列表响应。"""
+
     items: list[ViralVideoJobResponse]
     total: int
 
 
 class StyleTemplateResponse(BaseModel):
+    """风格模板响应。"""
+
     id: str
     name: str
     description: str = ""
@@ -259,70 +129,25 @@ class StyleTemplateResponse(BaseModel):
 
 
 class StyleTemplateListResponse(BaseModel):
+    """风格模板列表响应。"""
+
     items: list[StyleTemplateResponse]
 
 
 class AnalyzeStyleResponse(BaseModel):
+    """风格分析结果响应。"""
+
     job_id: str
     status: str
     style_guide: dict | None = None
 
 
-# -- 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 --
+# ── WebSocket 事件 Schema ──────────────────────────────────────────────────
 
 
 class WSProgressEvent(BaseModel):
+    """WebSocket 进度推送事件。"""
+
     type: str = "viral_video:progress"
     job_id: str
     stage: str

apps/api/app/services/gpu_lipsync_service.py

@@ -228,8 +228,6 @@ class GpuLipsyncService:
         lipsync_job_id: str = "",
         user_id: str = "",
         project_id: str = "",
-        credits_prepaid: float = 0.0,
-        credits_transaction_id: str = "",
     ) -> GpuLipsyncTaskModel:
         task_id = str(uuid.uuid4())
         now = datetime.now(UTC)
@@ -242,8 +240,6 @@ class GpuLipsyncService:
             audio_url=audio_url,
             status="pending",
             attempt=0,
-            credits_prepaid=float(credits_prepaid or 0.0),
-            credits_transaction_id=str(credits_transaction_id or ""),
             created_at=now,
             updated_at=now,
         )

apps/api/app/services/lipsync_service.py

@@ -38,7 +38,6 @@ from sqlalchemy.orm import Session
 from packages.adapters.sqlalchemy_impl.models import LipsyncJobModel
 from packages.application.cosyvoice_service import CosyVoiceError
 from packages.config import get_api_settings
-from packages.domain import feature_pricing_service
 from packages.domain.sentence_timings import (
     compute_sentence_timings,
     probe_audio_duration,
@@ -223,47 +222,7 @@ class LipsyncService:
         if timings:
             job.sentence_timings = timings
 
-        # 4. 检查是否走 Ditto（蚂蚁数字人，#2076）：开关 + 配置完整
-        use_ditto = False
-        if self.settings.use_ditto_lipsync:
-            try:
-                from packages.application.ditto_service import get_ditto_client
-
-                ditto = get_ditto_client()
-                if ditto.is_configured:
-                    use_ditto = True
-                    logger.info("[lipsync] 优先走 Ditto 蚂蚁数字人: job_id=%s", job.id)
-                else:
-                    logger.info(
-                        "[lipsync] Ditto 开关已开但配置不完整（base_url=%s, template=%s），继续判断 GPU: job_id=%s",
-                        bool(ditto.base_url),
-                        bool(ditto.default_video_url),
-                        job.id,
-                    )
-            except Exception as exc:
-                logger.warning("[lipsync] Ditto 初始化失败，继续判断 GPU: job_id=%s err=%s", job.id, exc)
-
-        if use_ditto:
-            try:
-                # Ditto 使用预置人物模板视频，不用用户上传的 video_url；
-                # 但保留用户 video_url 以便失败回退到 GPU/MediaKit。
-                job.status = "processing"
-                job.mediakit_task_id = "ditto:submitted"
-                job.updated_at = datetime.now(UTC)
-                self.db.commit()
-                from app.tasks.lipsync_ditto import lipsync_ditto_process_async
-
-                lipsync_ditto_process_async.apply_async(args=(job.id, job.user_id))
-                logger.info("[lipsync] Ditto 任务已异步派发: job_id=%s", job.id)
-                return
-            except Exception as exc:
-                logger.warning("[lipsync] Ditto 派发失败，回退 GPU/MediaKit: job_id=%s err=%s", job.id, exc)
-                try:
-                    self.db.rollback()
-                except Exception:
-                    pass
-
-        # 5. 检查是否走 GPU 路径：开关打开 + 有可用 Worker
+        # 4. 检查是否走 GPU 路径：开关打开 + 有可用 Worker
         use_gpu = False
         if self.settings.use_gpu_lipsync:
             try:
@@ -409,8 +368,6 @@ class LipsyncService:
             lipsync_job_id=job.id,
             user_id=job.user_id,
             project_id=job.project_id,
-            credits_prepaid=float(getattr(job, "credits_prepaid", 0) or 0),
-            credits_transaction_id=str(getattr(job, "credits_transaction_id", "") or ""),
         )
         logger.info(
             "[lipsync] 已创建 GPU 任务（异步）: job_id=%s gpu_task=%s",
@@ -458,121 +415,6 @@ class LipsyncService:
             job.output_duration,
         )
 
-    # ── lip_sync 计费辅助 ────────────────────────────────────────────────
-
-    @staticmethod
-    def _estimate_duration(
-        *,
-        audio_duration: Optional[float] = None,
-        sentence_timings: Optional[list] = None,
-        script_text: str = "",
-    ) -> float:
-        """预估音频/成片秒数。
-
-        优先级：audio_duration（预合成前端已 ffprobe）> timings 末句 end_time >
-        脚本字数 / 5 字每秒 > 默认 10 秒。
-        """
-        if audio_duration and float(audio_duration) > 0:
-            return float(audio_duration)
-        if sentence_timings:
-            max_end = 0.0
-            for item in sentence_timings:
-                if isinstance(item, dict):
-                    end = item.get("end_time") or item.get("end") or 0.0
-                else:
-                    end = 0.0
-                try:
-                    max_end = max(max_end, float(end))
-                except (TypeError, ValueError):
-                    continue
-            if max_end > 0:
-                return max_end
-        text = (script_text or "").strip()
-        if text:
-            return max(1.0, len(text) / 5.0)
-        return 10.0
-
-    def _settle_lip_sync(self, job: LipsyncJobModel, actual_duration: float) -> None:
-        """按实际时长结算（首期只退不补：final < prepaid 退差额，> 不补）。
-
-        幂等：credits_cost 已 > 0 说明结算过，直接跳过。
-        结算失败不阻塞业务（结果已产出），仅记录日志。
-        """
-        try:
-            prepaid = float(getattr(job, "credits_prepaid", 0) or 0)
-            if prepaid <= 0:
-                return
-            if float(getattr(job, "credits_cost", 0) or 0) > 0:
-                return
-            feature_cfg = feature_pricing_service.get_feature_config("lip_sync")
-            unit_cost = float(feature_cfg.dynamic_unit_cost) if feature_cfg is not None else 0.0
-            duration = float(actual_duration or 0.0)
-            if duration <= 0:
-                duration = self._estimate_duration(
-                    sentence_timings=job.sentence_timings,
-                    script_text=job.script_text,
-                )
-            final_price, _bd = feature_pricing_service.calculate_price("lip_sync", duration * unit_cost)
-            final_price = round(float(final_price), 2)
-            job.credits_cost = final_price
-            if final_price < prepaid - 0.009:
-                refund = round(prepaid - final_price, 2)
-                from packages.domain.points_service import PointsService
-
-                res = PointsService().refund_points(
-                    user_id=job.user_id,
-                    amount=refund,
-                    source="lip_sync",
-                    db=self.db,
-                    ref_id=str(job.credits_transaction_id or job.id),
-                    description="对口型结算退费",
-                )
-                if not res.get("success"):
-                    logger.warning(
-                        "[lip_sync] 结算退费失败 job_id=%s refund=%.2f（不阻塞）",
-                        job.id,
-                        refund,
-                    )
-            # final > prepaid：首期只退不补，不补扣
-            self.db.commit()
-        except Exception:  # noqa: BLE001
-            logger.exception("[lip_sync] 结算异常 job_id=%s（不阻塞结果）", job.id)
-            try:
-                self.db.rollback()
-            except Exception:  # noqa: BLE001
-                pass
-
-    def _refund_lip_sync(self, job: LipsyncJobModel) -> None:
-        """任务失败/取消时全额退还预扣积分（credits_cost 已结算则退实际未消耗部分）。"""
-        try:
-            prepaid = float(getattr(job, "credits_prepaid", 0) or 0)
-            if prepaid <= 0:
-                return
-            txn_id = str(getattr(job, "credits_transaction_id", "") or "")
-            cost = float(getattr(job, "credits_cost", 0) or 0)
-            refund = round(prepaid - cost, 2) if cost > 0 else round(prepaid, 2)
-            if refund <= 0:
-                return
-            from packages.domain.points_service import PointsService
-
-            res = PointsService().refund_points(
-                user_id=job.user_id,
-                amount=refund,
-                source="lip_sync",
-                db=self.db,
-                ref_id=txn_id or job.id,
-                description="对口型失败/取消退款",
-            )
-            if res.get("success"):
-                job.credits_cost = prepaid  # 标记已全额退回，防重复退
-                self.db.commit()
-        except Exception:  # noqa: BLE001
-            logger.exception("[lip_sync] 退款异常 job_id=%s", job.id)
-            try:
-                self.db.rollback()
-            except Exception:  # noqa: BLE001
-                pass
-
     # ── 创建任务 ──────────────────────────────────────────────────────────
 
     def create_job(
@@ -624,35 +466,6 @@ class LipsyncService:
             if not isinstance(sentence_timings, list) or len(sentence_timings) == 0:
                 raise MediaKitError("预合成模式 sentence_timings 不能为空", code="InvalidInput")
 
-        # 0.5 lip_sync 计费预扣（全局 points 开关 + 功能开关均开才扣）
-        prepaid_credits = 0.0
-        prepaid_txn_id = ""
-        if feature_pricing_service.is_feature_enabled("lip_sync"):
-            est_duration = self._estimate_duration(
-                audio_duration=audio_duration,
-                sentence_timings=sentence_timings,
-                script_text=script_text,
-            )
-            feature_cfg = feature_pricing_service.get_feature_config("lip_sync")
-            unit_cost = float(feature_cfg.dynamic_unit_cost) if feature_cfg is not None else 0.0
-            dynamic_cost = est_duration * unit_cost
-            prepaid_credits, _bd = feature_pricing_service.calculate_price("lip_sync", dynamic_cost)
-            if prepaid_credits > 0:
-                from packages.domain.points_service import PointsService
-
-                res = PointsService().deduct_points(
-                    user_id=user_id,
-                    amount=prepaid_credits,
-                    source="lip_sync",
-                    db=self.db,
-                    description="对口型生成预扣",
-                )
-                if not res.get("success"):
-                    raise ValueError(
-                        f"积分不足：本次对口型需 {prepaid_credits:.2f} 积分，当前余额 {res.get('balance', 0)}"
-                    )
-                prepaid_txn_id = str(res.get("transaction_id") or "")
-
         # 1. 创建数据库记录
         job_id = str(uuid.uuid4())
         job = LipsyncJobModel(
@@ -669,8 +482,6 @@ class LipsyncService:
             emotion=emotion or "",
             # 音频直传（含预合成）直接进入 pending（后续同步改为 submitted）；TTS 模式进入 tts_processing
             status="tts_processing" if is_tts_mode else "pending",
-            credits_prepaid=prepaid_credits,
-            credits_transaction_id=prepaid_txn_id,
         )
         self.db.add(job)
         self.db.flush()
@@ -845,30 +656,6 @@ class LipsyncService:
         if job.status in (STATUS_COMPLETED, "failed"):
             return job
 
-        # Ditto 异步路径：mediakit_task_id 以 "ditto:" 开头，由 Celery 任务异步更新
-        # 不做 MediaKit 轮询，只检查是否卡住太久（>10 分钟）则标失败
-        if job.mediakit_task_id and job.mediakit_task_id.startswith("ditto:"):
-            if job.status in ("processing", "submitted"):
-                _now = datetime.now(UTC)
-                _upd = job.updated_at
-                if _upd is not None and _upd.tzinfo is None:
-                    _upd = _upd.replace(tzinfo=UTC)
-                stale_minutes = 10
-                if _upd and (_now - _upd).total_seconds() > stale_minutes * 60:
-                    logger.warning(
-                        "Ditto 异步任务超时（>%d 分钟），标记失败: job_id=%s",
-                        stale_minutes,
-                        job_id,
-                    )
-                    job.status = "failed"
-                    job.error_message = f"Ditto 处理超时（>{stale_minutes} 分钟）"
-                    job.error_code = "DittoTimeout"
-                    job.completed_at = _now
-                    job.updated_at = _now
-                    self.db.commit()
-                    self._refund_lip_sync(job)
-            return job
-
         # GPU 异步路径：mediakit_task_id 以 "gpu:" 开头，由 Celery 任务异步更新
         # 不做 MediaKit 轮询，只检查是否卡住太久（>30 分钟）则标失败
         if job.mediakit_task_id and job.mediakit_task_id.startswith("gpu:"):
@@ -890,8 +677,6 @@ class LipsyncService:
                     job.completed_at = _now
                     job.updated_at = _now
                     self.db.commit()
-                    # lip_sync 超时全额退款
-                    self._refund_lip_sync(job)
             return job
 
         # 未提交的任务不轮询
@@ -917,8 +702,6 @@ class LipsyncService:
                 job.completed_at = datetime.now(UTC)
                 job.updated_at = datetime.now(UTC)
                 self.db.commit()
-                # lip_sync 结算（只退不补）
-                self._settle_lip_sync(job, float(job.output_duration or 0.0))
                 # 异步转存自家 OSS
                 try:
                     from app.tasks.lipsync_tts import persist_output_video_task
@@ -936,8 +719,6 @@ class LipsyncService:
                 job.error_message = error.get("message", "任务执行失败")
                 job.error_code = error.get("code", "TaskFailed")
                 job.completed_at = datetime.now(UTC)
-                # lip_sync 失败全额退款（先退款再统一 commit）
-                self._refund_lip_sync(job)
             else:
                 # 中间状态（running/processing/queued 等）同步到 DB，避免前端永远卡在 submitted
                 if isinstance(mk_status, str) and mk_status:
@@ -1031,8 +812,6 @@ class LipsyncService:
             job.status = "cancelled"
             job.updated_at = datetime.now(UTC)
             self.db.commit()
-            # lip_sync 取消全额退款
-            self._refund_lip_sync(job)
             self.db.refresh(job)
 
         return job

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/api/app/tasks/lipsync_ditto.py

@@ -1,552 +0,0 @@
-"""Ditto 蚂蚁数字人口型异步任务 — #2076.
-
-把 Ditto 同步 HTTP 调用（30-120s）从 API 请求移到 Celery 后台执行：
-1. 加载 LipsyncJob
-2. 确定驱动视频：用户上传的 video_url 优先，无则用 settings.ditto_default_video_url 兜底
-3. 视频时长对齐：若视频 < 音频+2s，用 ffmpeg 循环视频到足够长度后上传临时文件
-4. 调 DittoClient.generate_and_persist
-5. 成功：标记 completed，写入 output_video_url（Ditto 输出自带音频，无需二次混流/超分）
-6. 失败：回退 GPU MuseTalk → 再失败回退 MediaKit
-
-注意：
-- 保留 MuseTalk 代码不动；Ditto 优先，失败按原链路兜底
-- Ditto 默认使用用户上传的视频作为驱动模板，default_video_url 仅作兜底
-- 用户视频短于音频时，ffmpeg stream_loop 循环到音频时长+2s余量
-- 不传 GFPGAN 超分，不需要 ffmpeg 音视频混流（Ditto 输出已带音视频）
-"""
-
-from __future__ import annotations
-
-import logging
-import os
-import subprocess
-import tempfile
-from datetime import UTC, datetime
-from typing import TYPE_CHECKING, Optional
-
-from celery import shared_task
-from sqlalchemy.orm import Session
-
-if TYPE_CHECKING:
-    from packages.adapters.sqlalchemy_impl.models import LipsyncJobModel
-
-logger = logging.getLogger(__name__)
-
-_DITTO_URL_TTL_SECONDS = 7 * 24 * 3600  # Ditto 结果 OSS URL 7 天有效
-_VIDEO_LOOP_MARGIN_SECONDS = 2.0  # 循环视频时比音频多留 2 秒余量
-_MAX_VIDEO_PREPROCESS_SIZE = 200 * 1024 * 1024  # 用户视频最大 200MB
-
-
-def _get_db_session() -> Session:
-    try:
-        from worker_app.db import SessionLocal  # type: ignore
-    except ImportError:
-        from app.db import SessionLocal  # type: ignore
-    return SessionLocal()
-
-
-def _sign_media_url(url: str) -> str:
-    """对自家 OSS URL 签 7 天预签名。"""
-    if not url:
-        return url
-    try:
-        from urllib.parse import urlparse
-
-        from packages.shared.storage import get_shared_storage_service
-
-        storage = get_shared_storage_service()
-        public_base = getattr(storage, "public_url", "")
-        if not isinstance(public_base, str) or not public_base:
-            return url
-        own_host = urlparse(public_base).netloc.lower()
-        host = urlparse(url).netloc.lower()
-        if not own_host or host != own_host:
-            return url
-        return storage.get_download_url(url, expires_seconds=_DITTO_URL_TTL_SECONDS)
-    except Exception:
-        return url
-
-
-def _probe_media_duration(path_or_bytes, *, is_bytes: bool = False) -> float:
-    """用 ffprobe 探测视频/音频时长（秒）；失败返回 0。
-
-    Args:
-        path_or_bytes: 文件路径(str) 或 字节数据(bytes)
-        is_bytes: 传入的是 bytes 还是文件路径
-    """
-    tmp_path = None
-    try:
-        if is_bytes:
-            with tempfile.NamedTemporaryFile(suffix=".bin", delete=False) as tmp:
-                tmp.write(path_or_bytes)
-                tmp_path = tmp.name
-            target = tmp_path
-        else:
-            target = path_or_bytes
-        out = subprocess.check_output(
-            [
-                "ffprobe",
-                "-v",
-                "error",
-                "-show_entries",
-                "format=duration",
-                "-of",
-                "default=noprint_wrappers=1:nokey=1",
-                target,
-            ],
-            stderr=subprocess.STDOUT,
-            timeout=15,
-        )
-        return float(out.decode().strip() or 0)
-    except Exception as exc:
-        logger.warning("[ditto_task] ffprobe 失败: %s", exc)
-        return 0.0
-    finally:
-        if tmp_path and os.path.exists(tmp_path):
-            try:
-                os.unlink(tmp_path)
-            except Exception:
-                pass
-
-
-def _probe_video_duration(video_bytes: bytes) -> float:
-    """用 ffprobe 探测视频时长（秒）；失败返回 0。"""
-    return _probe_media_duration(video_bytes, is_bytes=True)
-
-
-def _prepare_driver_video(
-    *,
-    user_video_url: str,
-    default_video_url: str,
-    audio_duration: float,
-    job_id: str,
-    user_id: str,
-) -> tuple[str, bool]:
-    """准备传给 Ditto 的驱动视频 URL。
-
-    逻辑：
-    1. 优先使用用户上传的视频（user_video_url），无则用 default_video_url 兜底
-    2. 下载视频，探测时长
-    3. 若视频时长 >= 音频时长+2s 余量：直接用原 URL（签名后）
-    4. 若视频时长 < 音频时长+2s：ffmpeg stream_loop 循环到目标时长，上传临时 OSS，返回临时 URL
-    5. 任何异常：回退到 default_video_url（兜底）
-
-    Returns:
-        (video_url_for_ditto, is_temporary) — is_temporary=True 表示 URL 是本次临时生成的
-    """
-    from packages.shared.storage import get_shared_storage_service
-    from packages.shared.url_security import safe_download_bytes
-
-    storage = get_shared_storage_service()
-
-    # 1. 选择源 URL（用户视频优先）
-    source_url = user_video_url or default_video_url
-    source_label = "user" if user_video_url else "default"
-    if not source_url:
-        raise RuntimeError("无可用驱动视频（用户视频和默认模板都为空）")
-
-    # 2. 下载视频
-    try:
-        # 用户视频需要签名才能下载
-        signed_source = _sign_media_url(source_url) if user_video_url else source_url
-        video_bytes = safe_download_bytes(
-            signed_source,
-            purpose="ditto-driver-video",
-            max_size=_MAX_VIDEO_PREPROCESS_SIZE,
-            allowed_mime_types=("video/mp4", "video/quicktime", "video/x-msvideo", "video/webm"),
-            timeout=60,
-        )
-    except Exception as dl_exc:
-        logger.warning(
-            "[ditto_task] 下载驱动视频失败（%s），回退默认模板: job=%s err=%s",
-            source_label,
-            job_id,
-            dl_exc,
-        )
-        if user_video_url and default_video_url:
-            return default_video_url, False
-        raise
-
-    # 3. 探测视频时长
-    video_duration = _probe_media_duration(video_bytes, is_bytes=True)
-    target_duration = audio_duration + _VIDEO_LOOP_MARGIN_SECONDS
-
-    # 4. 视频足够长：直接用签名后的原 URL
-    if video_duration >= target_duration:
-        logger.info(
-            "[ditto_task] 驱动视频足够长（%.2fs >= %.2fs），直接使用: job=%s source=%s",
-            video_duration,
-            target_duration,
-            job_id,
-            source_label,
-        )
-        return _sign_media_url(source_url) if user_video_url else source_url, False
-
-    # 5. 视频不够长：ffmpeg 循环到目标时长
-    logger.info(
-        "[ditto_task] 驱动视频不够长（%.2fs < %.2fs），ffmpeg 循环延长: job=%s",
-        video_duration,
-        target_duration,
-        job_id,
-    )
-    looped_path = None
-    try:
-        # 写临时文件
-        with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as src_tmp:
-            src_tmp.write(video_bytes)
-            src_path = src_tmp.name
-        looped_fd, looped_path = tempfile.mkstemp(suffix=".mp4")
-        os.close(looped_fd)
-
-        # ffmpeg: stream_loop -1 循环输入，-t 截到目标时长
-        # 使用 -c copy 快速复制流（不重编码），速度快无画质损失
-        cmd = [
-            "ffmpeg",
-            "-y",
-            "-stream_loop",
-            "-1",
-            "-i",
-            src_path,
-            "-t",
-            str(target_duration),
-            "-c",
-            "copy",
-            "-movflags",
-            "+faststart",
-            looped_path,
-        ]
-        try:
-            subprocess.run(cmd, check=True, capture_output=True, timeout=60)
-        except subprocess.CalledProcessError:
-            # copy 模式失败（编码不兼容），回退重编码
-            logger.warning("[ditto_task] stream_loop copy 失败，回退重编码: job=%s", job_id)
-            cmd = [
-                "ffmpeg",
-                "-y",
-                "-stream_loop",
-                "-1",
-                "-i",
-                src_path,
-                "-t",
-                str(target_duration),
-                "-c:v",
-                "libx264",
-                "-preset",
-                "veryfast",
-                "-crf",
-                "23",
-                "-c:a",
-                "aac",
-                "-movflags",
-                "+faststart",
-                looped_path,
-            ]
-            subprocess.run(cmd, check=True, capture_output=True, timeout=120)
-
-        # 上传临时 OSS
-        looped_key = f"ditto-tmp/{user_id}/{job_id}_looped.mp4"
-        with open(looped_path, "rb") as f:
-            tmp_url = storage.upload_file(
-                f,
-                looped_key,
-                content_type="video/mp4",
-            )
-        # 临时文件需要签名（private bucket）
-        signed_tmp_url = _sign_media_url(tmp_url)
-        logger.info(
-            "[ditto_task] 循环视频已上传: job=%s key=%s dur=%.2fs",
-            job_id,
-            looped_key,
-            target_duration,
-        )
-        return signed_tmp_url, True
-
-    except Exception as loop_exc:
-        logger.warning(
-            "[ditto_task] 视频循环处理失败，回退直接使用（Ditto 侧处理）: job=%s err=%s",
-            job_id,
-            loop_exc,
-        )
-        # 兜底：直接用原视频（交给 Ditto 侧处理时长不一致）
-        return _sign_media_url(source_url) if user_video_url else source_url, False
-    finally:
-        for p in (locals().get("src_path"), looped_path):
-            if p and os.path.exists(p):
-                try:
-                    os.unlink(p)
-                except Exception:
-                    pass
-
-
-def _refund_lip_sync(db: Session, job: "LipsyncJobModel") -> None:
-    """Ditto 失败/取消时全额退款（复用 lipsync_service 的退款逻辑）。"""
-    try:
-        from app.services.lipsync_service import LipsyncService
-
-        LipsyncService(db)._refund_lip_sync(job)
-    except Exception:
-        logger.exception("[ditto_task] lip_sync 退款异常 job_id=%s", job.id)
-
-
-def _settle_lip_sync(db: Session, job: "LipsyncJobModel", duration: float) -> None:
-    """Ditto 成功后按实际时长结算。"""
-    try:
-        from app.services.lipsync_service import LipsyncService
-
-        LipsyncService(db)._settle_lip_sync(job, duration)
-    except Exception:
-        logger.exception("[ditto_task] lip_sync 结算异常 job_id=%s（不阻塞）", job.id)
-
-
-def _fallback_to_gpu_then_mediakit(db: Session, job: "LipsyncJobModel") -> None:
-    """Ditto 失败后：优先回退 GPU MuseTalk，再回退 MediaKit 云端。
-
-    复用 lipsync_service 现有路径逻辑以保证兜底一致性。
-    """
-    # 先尝试走 GPU MuseTalk（若可用）
-    try:
-        from app.services.gpu_lipsync_service import GpuLipsyncService
-        from app.tasks.lipsync_gpu import lipsync_gpu_process_async
-
-        gpu_svc = GpuLipsyncService(db)
-        if gpu_svc.has_available_worker():
-            logger.info("[ditto_task] 回退 GPU MuseTalk: job_id=%s", job.id)
-            from app.services.lipsync_service import LipsyncService
-
-            svc = LipsyncService(db)
-            storage = _shared_storage()
-            persisted_audio = None
-            try:
-                persisted_audio = svc._persist_external_audio_for_gpu(job=job, storage=storage)
-            except Exception as exc:
-                logger.warning("[ditto_task] GPU 外部音频转存失败: %s", exc)
-            audio_url_for_task = persisted_audio or job.audio_url
-            gpu_task = gpu_svc.create_task(
-                video_url=job.video_url,
-                audio_url=audio_url_for_task,
-                lipsync_job_id=job.id,
-                user_id=job.user_id,
-            )
-            if gpu_task is not None:
-                job.mediakit_task_id = f"gpu:{gpu_task.id}"
-                job.status = "processing"
-                job.updated_at = datetime.now(UTC)
-                db.commit()
-                lipsync_gpu_process_async.apply_async(args=(job.id, job.user_id, gpu_task.id))
-                return
-            db.rollback()
-    except Exception as exc:
-        logger.warning("[ditto_task] GPU MuseTalk 回退失败，转 MediaKit: %s", exc)
-        try:
-            db.rollback()
-        except Exception:
-            pass
-
-    # 最后兜底：MediaKit 云端
-    try:
-        from app.services.mediakit_client import get_mediakit_client
-
-        client = get_mediakit_client()
-        video_url = _sign_media_url(job.video_url)
-        signed_audio_url = _sign_media_url(job.audio_url)
-        result = client.submit_lipsync(
-            video_url=video_url,
-            audio_url=signed_audio_url,
-            enable_video_loop=job.enable_video_loop,
-            client_token=job.id,
-        )
-        job.mediakit_task_id = result["task_id"]
-        job.status = "submitted"
-        job.submitted_at = datetime.now(UTC)
-        job.updated_at = datetime.now(UTC)
-        db.commit()
-        logger.info("[ditto_task] 已回退 MediaKit: job_id=%s task_id=%s", job.id, result["task_id"])
-    except Exception as exc:
-        job.status = "failed"
-        job.error_message = f"Ditto/GPU/MediaKit 均失败: {exc}"
-        job.error_code = "AllBackendsFailed"
-        job.updated_at = datetime.now(UTC)
-        db.commit()
-        logger.error("[ditto_task] 所有兜底均失败: job_id=%s err=%s", job.id, exc)
-
-
-def _shared_storage():
-    from packages.shared.storage import get_shared_storage_service
-
-    return get_shared_storage_service()
-
-
-@shared_task(
-    name="lipsync_ditto_process_async",
-    bind=True,
-    max_retries=0,
-    acks_late=True,
-    time_limit=600,
-    soft_time_limit=540,
-)
-def lipsync_ditto_process_async(self, job_id: str, user_id: str) -> None:
-    """异步调用 Ditto 生成口型视频。
-
-    Args:
-        job_id: LipsyncJob ID
-        user_id: 用户 ID
-    """
-    from packages.application.ditto_emotion_service import get_ditto_emotion_service
-    from packages.application.ditto_service import DittoError, get_ditto_client
-    from packages.config import get_api_settings
-    from packages.domain.sentence_timings import probe_audio_duration
-    from packages.shared.url_security import safe_download_bytes
-
-    db: Session = _get_db_session()
-    job: Optional[LipsyncJobModel] = None
-    prepared_video_url: str = ""
-    try:
-        from packages.adapters.sqlalchemy_impl.models import LipsyncJobModel
-
-        job = db.query(LipsyncJobModel).filter_by(id=job_id, user_id=user_id).first()
-        if job is None:
-            logger.error("[ditto_task] job 不存在: job_id=%s", job_id)
-            return
-
-        if job.status != "processing":
-            logger.warning(
-                "[ditto_task] job 状态异常（非 processing），跳过: job_id=%s status=%s",
-                job_id,
-                job.status,
-            )
-            return
-
-        audio_url = job.audio_url or ""
-        script = job.script_text or ""
-        user_video_url = job.video_url or ""
-        if not audio_url:
-            raise DittoError("job.audio_url 为空，无法调用 Ditto", code="InvalidParam")
-
-        settings = get_api_settings()
-        default_video_url = settings.ditto_default_video_url or ""
-
-        logger.info(
-            "[ditto_task] 开始 Ditto 生成: job_id=%s has_user_video=%s script_len=%d",
-            job_id,
-            bool(user_video_url),
-            len(script),
-        )
-
-        # ── 0. 探测音频时长（情绪分析 + 视频循环都需要）──
-        audio_duration = 0.0
-        audio_bytes_for_probe = None
-        try:
-            audio_bytes_for_probe = safe_download_bytes(
-                audio_url,
-                allowed_mime_types=("audio/mpeg", "audio/wav", "audio/x-wav", "audio/mp3"),
-                timeout=30,
-            )
-            audio_duration = probe_audio_duration(audio_bytes_for_probe)
-            logger.info("[ditto_task] 音频时长: %.2fs", audio_duration)
-        except Exception as audio_exc:
-            logger.warning("[ditto_task] 音频时长探测失败: %s", audio_exc)
-            audio_duration = 0.0
-
-        # ── 1. LLM 情绪分析（生成 emo_timeline）──
-        emo_timeline = ""
-        try:
-            emo_svc = get_ditto_emotion_service()
-            if emo_svc.enabled and script and audio_duration > 0:
-                sentence_timings = getattr(job, "sentence_timings", None)
-                emo_timeline = emo_svc.build_timeline(
-                    text=script,
-                    audio_duration=audio_duration,
-                    sentence_timings=sentence_timings,
-                )
-                if emo_timeline:
-                    logger.info("[ditto_task] 情绪时间线已生成: segments≈%d", len(emo_timeline) // 50)
-        except Exception as emo_exc:
-            logger.warning("[ditto_task] 情绪分析异常（降级中性）: %s", emo_exc)
-            emo_timeline = ""
-
-        # ── 2. 准备驱动视频（用户视频优先，必要时循环延长）──
-        prepared_video_url, _is_tmp = _prepare_driver_video(
-            user_video_url=user_video_url,
-            default_video_url=default_video_url,
-            audio_duration=audio_duration if audio_duration > 0 else 10.0,  # 探测失败时按10s估
-            job_id=job_id,
-            user_id=user_id,
-        )
-
-        # ── 3. 调用 Ditto ──
-        client = get_ditto_client()
-        result = client.generate_and_persist(
-            job_id=job_id,
-            user_id=user_id,
-            audio_url=audio_url,
-            script=script,
-            video_url=prepared_video_url,
-            emo_timeline=emo_timeline,
-        )
-
-        # Ditto 返回的 MP4 自带音频，签名 OSS URL（7天有效）后标记完成
-        job.output_video_url = _sign_media_url(result.video_url)
-        # 探测时长（用于计费）
-        duration = _probe_video_duration(result.video_bytes)
-        if duration <= 0:
-            # 兜底：按音频时长估算
-            if audio_bytes_for_probe is not None:
-                try:
-                    duration = probe_audio_duration(audio_bytes_for_probe)
-                except Exception:
-                    duration = 0.0
-            if duration <= 0 and audio_duration > 0:
-                duration = audio_duration
-        job.output_duration = duration
-        job.status = "completed"
-        job.completed_at = datetime.now(UTC)
-        job.updated_at = datetime.now(UTC)
-        db.commit()
-        logger.info(
-            "[ditto_task] Ditto 完成: job_id=%s url=%s duration=%.2fs rtf=%.2f frames=%d",
-            job_id,
-            result.video_url[:100],
-            duration,
-            result.rtf,
-            result.frames,
-        )
-        _settle_lip_sync(db, job, duration)
-
-    except DittoError as exc:
-        logger.error("[ditto_task] Ditto 失败，回退: job_id=%s code=%s err=%s", job_id, exc.code, exc)
-        if job is not None:
-            try:
-                db.rollback()
-                job = db.query(type(job)).filter_by(id=job_id).first() if hasattr(job, "id") else job
-                _fallback_to_gpu_then_mediakit(db, job)
-            except Exception as fallback_exc:
-                logger.exception("[ditto_task] 回退也失败 job_id=%s err=%s", job_id, fallback_exc)
-                try:
-                    if job:
-                        job.status = "failed"
-                        job.error_message = f"Ditto 失败且回退异常: {exc}; fallback: {fallback_exc}"
-                        job.error_code = "FallbackError"
-                        job.updated_at = datetime.now(UTC)
-                        db.commit()
-                except Exception:
-                    pass
-    except Exception as exc:
-        logger.exception("[ditto_task] 未预期异常: job_id=%s err=%s", job_id, exc)
-        if job is not None:
-            try:
-                db.rollback()
-                job = db.query(type(job)).filter_by(id=job_id).first()
-                _fallback_to_gpu_then_mediakit(db, job)
-            except Exception as fallback_exc:
-                logger.exception("[ditto_task] 回退也失败 job_id=%s err=%s", job_id, fallback_exc)
-                try:
-                    if job:
-                        job.status = "failed"
-                        job.error_message = f"Ditto 异常: {exc}"
-                        job.error_code = "DittoAsyncError"
-                        job.updated_at = datetime.now(UTC)
-                        db.commit()
-                except Exception:
-                    pass
-    finally:
-        db.close()

apps/api/app/tasks/lipsync_gpu.py

@@ -104,7 +104,6 @@ def lipsync_gpu_process_async(self, job_id: str, user_id: str, gpu_task_id: str)
             job.updated_at = datetime.now(UTC)
             db.commit()
             logger.info("[lipsync_gpu_async] GPU 任务已被用户取消: job_id=%s", job_id)
-            _refund_lip_sync(db, job)
             return
 
         if final_task.status != "done":
@@ -142,7 +141,6 @@ def lipsync_gpu_process_async(self, job_id: str, user_id: str, gpu_task_id: str)
             job_id,
             job.output_duration,
         )
-        _settle_lip_sync(db, job, final_task)
     except Exception as exc:
         logger.exception("[lipsync_gpu_async] 异常: job_id=%s err=%s", job_id, exc)
         try:
@@ -159,33 +157,6 @@ def lipsync_gpu_process_async(self, job_id: str, user_id: str, gpu_task_id: str)
         db.close()
 
 
-def _settle_lip_sync(db: Session, job: LipsyncJobModel, gpu_task) -> None:
-    """GPU 成功后结算：同步 credits_cost 到 gpu 任务并按实际时长多退少不补。"""
-    try:
-        from app.services.lipsync_service import LipsyncService
-
-        # GPU 任务表先同步结算结果（标记用）
-        LipsyncService._settle_lip_sync(job, float(getattr(gpu_task, "result_duration", 0) or 0.0))
-        gpu_task.credits_cost = float(job.credits_cost or 0.0)
-        db.commit()
-    except Exception:  # noqa: BLE001
-        logger.exception("[lipsync_gpu_async] lip_sync 结算异常 job_id=%s（不阻塞）", job.id)
-        try:
-            db.rollback()
-        except Exception:  # noqa: BLE001
-            pass
-
-
-def _refund_lip_sync(db: Session, job: LipsyncJobModel) -> None:
-    """GPU 取消/失败路径全额退款。"""
-    try:
-        from app.services.lipsync_service import LipsyncService
-
-        LipsyncService(db)._refund_lip_sync(job)
-    except Exception:  # noqa: BLE001
-        logger.exception("[lipsync_gpu_async] lip_sync 退款异常 job_id=%s", job.id)
-
-
 def _fallback_to_mediakit(db: Session, job: LipsyncJobModel) -> None:
     """GPU 失败时回退到 MediaKit 云端渲染。"""
     try:

apps/api/app/tasks/lipsync_tts.py

@@ -261,33 +261,7 @@ def tts_synthesize_and_submit(
                 "[lipsync_tts] 句子时间戳计算失败（不影响主流程）: job_id=%s err=%s", job_id, _st_err, exc_info=True
             )
 
-        # 3. 优先走 Ditto（#2076）：开关打开且配置完整时，派发 Ditto 异步任务，不再走 MediaKit
-        ditto_dispatched = False
-        try:
-            from packages.config import get_api_settings as _get_settings
-
-            _settings = _get_settings()
-            if _settings.use_ditto_lipsync and _settings.ditto_api_base_url and _settings.ditto_default_video_url:
-                from app.tasks.lipsync_ditto import lipsync_ditto_process_async
-
-                job.status = "processing"
-                job.mediakit_task_id = "ditto:tts-submitted"
-                job.updated_at = datetime.now(UTC)
-                db.commit()
-                lipsync_ditto_process_async.apply_async(args=(job_id, user_id))
-                logger.info("[lipsync_tts] TTS 完成，已派发 Ditto 任务: job_id=%s", job_id)
-                ditto_dispatched = True
-        except Exception as _ditto_err:
-            logger.warning("[lipsync_tts] Ditto 派发失败，回退 MediaKit: job_id=%s err=%s", job_id, _ditto_err)
-            try:
-                db.rollback()
-            except Exception:
-                pass
-
-        if ditto_dispatched:
-            return
-
-        # 4. 签名 URL 并提交到 MediaKit（复用模块内 _sign_media_url，避免对 LipsyncService 的耦合）
+        # 3. 签名 URL 并提交到 MediaKit（复用模块内 _sign_media_url，避免对 LipsyncService 的耦合）
         audio_url = _sign_media_url(job.audio_url)
         video_url = _sign_media_url(job.video_url)
 

apps/web/e2e/core-generation.spec.ts

@@ -11,34 +11,12 @@ const apiOrigin = apiBase.endsWith("/api/v1") ? apiBase.slice(0, -"/api/v1".leng
 /** 将浏览器侧 /api/v1 请求路由到 Playwright request 源（支持跨域） */
 async function routeBrowserApiToTestApi(page: Page) {
   if (!apiOrigin) return
-  // 单一通用路由（Playwright 按注册逆序匹配，故不拆分多个 glob 以免相互遮蔽）
   await page.route("**/api/v1/**", async (route) => {
-    try {
-      const sourceUrl = new URL(route.request().url())
-      const response = await route.fetch({
-        url: `${apiOrigin}${sourceUrl.pathname}${sourceUrl.search}`,
-      })
-      // /points/balance：Staging 后端积分总开关关闭（credits_enabled=false，免费放行）。
-      // 旧 bundle 部署的接口暂未返回该字段、且预校验只看余额，这里同时补开关与余额，
-      // 以验证“免费期不拦截生成”；新后端+新前端部署后读 credits_enabled=false 直接放行，
-      // 余额被忽略，此补丁随之成为 no-op。
-      if (sourceUrl.pathname.endsWith("/points/balance")) {
-        const body = await response.json().catch(() => ({}))
-        await route.fulfill({
-          response,
-          json: { ...body, credits_enabled: false, balance: 999999 },
-        })
-        return
-      }
-      await route.fulfill({ response })
-    } catch {
-      // 测试收尾时页面/上下文可能已关闭，忽略仍在途的请求，避免误判为失败
-      try {
-        await route.abort()
-      } catch {
-        /* noop */
-      }
-    }
+    const sourceUrl = new URL(route.request().url())
+    const response = await route.fetch({
+      url: `${apiOrigin}${sourceUrl.pathname}${sourceUrl.search}`,
+    })
+    await route.fulfill({ response })
   })
 }
 
@@ -67,13 +45,7 @@ async function loginWithRetry(
 async function setupFreshUser(
   request: APIRequestContext,
   label: string,
-): Promise<{
-  token: string
-  user: Record<string, unknown>
-  libraryId: string
-  assetId: string
-  suffix: string
-}> {
+): Promise<{ token: string; libraryId: string; assetId: string; suffix: string }> {
   const suffix = Math.random().toString(36).slice(2, 8)
   const email = `e2e-${label}-${suffix}@example.com`
   await request.post(`${apiBase}/auth/register`, {
@@ -81,19 +53,7 @@ async function setupFreshUser(
   })
   const token = await loginWithRetry(request, email, PASSWORD)
   const auth = { Authorization: `Bearer ${token}` }
-  const me = await request.get(`${apiBase}/auth/me`, { headers: auth })
-  expect(me.ok(), `fetch profile: ${await me.text()}`).toBeTruthy()
-  const user = (await me.json()) as Record<string, unknown>
 
-  // 预置一条文案：标题下拉候选来自文案库，新用户为空会导致无法选中标题
-  await request.post(`${apiBase}/scripts`, {
-    headers: auth,
-    data: {
-      title: `测试标题 ${suffix}`,
-      content: `测试文案内容 ${suffix}`,
-      tags: ["e2e"],
-    },
-  })
   const proj = await request.post(`${apiBase}/projects`, {
     headers: auth,
     data: { name: `Smoke ${label} ${suffix}` },
@@ -133,7 +93,7 @@ async function setupFreshUser(
       { timeout: 90_000, intervals: [3000, 3000, 5000] },
     )
     .toBe("ready")
-  return { token, user, libraryId, assetId, suffix }
+  return { token, libraryId, assetId, suffix }
 }
 
 /**
@@ -152,7 +112,7 @@ test.describe("Core Smart-Edit Flow (#1970)", () => {
   test("random mode: 5-step wizard creates generation task", async ({ page, request }) => {
     test.setTimeout(600_000)
     await page.setViewportSize({ width: 1440, height: 1000 })
-    const { token, user, suffix } = await setupFreshUser(request, "random")
+    const { token, suffix } = await setupFreshUser(request, "random")
     const authHeader = { Authorization: `Bearer ${token}` }
 
     // 确保默认模板存在（智能剪辑页依赖模板）
@@ -166,24 +126,13 @@ test.describe("Core Smart-Edit Flow (#1970)", () => {
     expect(templates.length).toBeGreaterThan(0)
 
     // 注入登录态 + 路由 API
-    await page.addInitScript(
-      ({ token, user }) => {
-        window.localStorage.setItem("access_token", token)
-        window.localStorage.setItem(
-          "auth-storage",
-          JSON.stringify({
-            state: {
-              user,
-              isAuthenticated: true,
-              accessToken: token,
-              refreshToken: null,
-            },
-            version: 0,
-          }),
-        )
-      },
-      { token, user },
-    )
+    await page.addInitScript((t: string) => {
+      window.localStorage.setItem("access_token", t)
+      window.localStorage.setItem(
+        "auth-storage",
+        JSON.stringify({ state: { token: t, user: null } }),
+      )
+    }, token)
     await routeBrowserApiToTestApi(page)
 
     // ── 提前 mock 配音列表（VoiceSelectModal 查询 /assets?kind=voice） ──
@@ -229,28 +178,16 @@ test.describe("Core Smart-Edit Flow (#1970)", () => {
     await expect(page.getByText("🎙️ 选择配音")).not.toBeVisible()
 
     // ── Step 2：选择素材 ──────────────────────────────────────────
-    await expect(page.getByText(/选择素材/).first()).toBeVisible({ timeout: 10000 })
-    // 卡片中心是播放按钮（stopPropagation 仅播放不选中），点右上角空白处完成选中
-    await page
-      .getByTestId("material-card")
-      .first()
-      .click({ position: { x: 70, y: 12 } })
-    await expect(page.getByText(/已选 1 个素材|已选[^0]*[1-9]/)).toBeVisible({ timeout: 5000 })
+    await expect(page.getByText("选择素材", { exact: true })).toBeVisible({ timeout: 10000 })
+    await page.getByTestId("material-card").first().click()
     await page.getByRole("button", { name: /下一步/ }).click()
 
     // ── Step 3：填写标题 ──────────────────────────────────────────
     // (#2048: PreviewCountModal 已移除，生成数量在 Step1 内设置)
-    await expect(page.getByText(/选择标题/).first()).toBeVisible({ timeout: 10000 })
-    // 标题为 antd AutoComplete（combobox），真实 input 带 placeholder
-    // antd AutoComplete combobox：真实可输入元素是 .ant-select-selection-search-input，
-    // 灰色提示语是单独的 placeholder span（input 自身无 placeholder 属性）
-    // 标题候选来自文案库（setupFreshUser 已预置一条文案）。
-    // combobox 的自由输入会在失焦时被 rc-select 重置，必须从下拉选中才提交，
-    // 因此聚焦输入框 → 点击候选选项
-    const seededTitle = `测试标题 ${suffix}`
-    const titleBox = page.locator(".ant-select-selection-search-input:visible").first()
-    await titleBox.click()
-    await page.locator(".ant-select-item-option", { hasText: seededTitle }).first().click()
+    await expect(page.getByText("选择标题", { exact: true })).toBeVisible({ timeout: 10000 })
+    const titleInput = page.getByPlaceholder("输入或从标题库选择")
+    await expect(titleInput).toBeVisible({ timeout: 5000 })
+    await titleInput.fill(`测试随机剪辑 ${suffix}`)
     await page.getByRole("button", { name: /下一步/ }).click()
 
     // ── Step 4：确认生成 ──────────────────────────────────────────
@@ -267,11 +204,9 @@ test.describe("Core Smart-Edit Flow (#1970)", () => {
     await confirmBtn.click()
     const taskResp = await createTask
     expect(taskResp.ok(), `Create task: ${await taskResp.text()}`).toBeTruthy()
-    const taskBody = await taskResp.json()
-    const taskId = taskBody.items?.[0]?.id ?? taskBody.id ?? taskBody.task_id
-    expect(taskId, "created task should return an id").toBeTruthy()
+    const taskId = (await taskResp.json()).id ?? (await taskResp.json()).task_id
     console.log("[random] Generation task created:", taskId)
-    await expect(page.getByText(/正在生成|提交/).first()).toBeVisible({ timeout: 15000 })
+    await expect(page.getByText(/正在生成|提交/)).toBeVisible({ timeout: 15000 })
     console.log("[random] Wizard flow completed ✓")
   })
 
@@ -281,28 +216,113 @@ test.describe("Core Smart-Edit Flow (#1970)", () => {
   }) => {
     test.setTimeout(600_000)
     await page.setViewportSize({ width: 1440, height: 1000 })
-    const { token, user, suffix } = await setupFreshUser(request, "narrative")
+    const { token, suffix } = await setupFreshUser(request, "narrative")
 
-    await page.addInitScript(
-      ({ token, user }) => {
-        window.localStorage.setItem("access_token", token)
-        window.localStorage.setItem(
-          "auth-storage",
-          JSON.stringify({
-            state: {
-              user,
-              isAuthenticated: true,
-              accessToken: token,
-              refreshToken: null,
-            },
-            version: 0,
-          }),
-        )
-      },
-      { token, user },
-    )
+    await page.addInitScript((t: string) => {
+      window.localStorage.setItem("access_token", t)
+      window.localStorage.setItem(
+        "auth-storage",
+        JSON.stringify({ state: { token: t, user: null } }),
+      )
+    }, token)
     await routeBrowserApiToTestApi(page)
 
+    // ── Mock 文案列表、音色、TTS 合成（避免真实合成） ──────────────
+    const mockScriptId = `script-mock-${suffix}`
+    const mockVoiceId = `preset-voice-${suffix}`
+    const mockJobId = `tts-job-${suffix}`
+
+    // 文案列表（ScriptSelectModal 查询 /scripts）
+    await page.route("**/api/v1/scripts**", (route) => {
+      const url = new URL(route.request().url())
+      if (url.pathname.includes("/extract-from-douyin")) {
+        route.continue()
+        return
+      }
+      route.fulfill({
+        status: 200,
+        contentType: "application/json",
+        body: JSON.stringify({
+          items: [
+            {
+              id: mockScriptId,
+              title: "测试带货文案",
+              content: "这是一段测试用的带货文案内容，用于 E2E 冒烟测试。",
+              tags: ["带货"],
+              title_category: "daihuo",
+              created_at: new Date().toISOString(),
+              updated_at: new Date().toISOString(),
+            },
+          ],
+          total: 1,
+          page: 1,
+          page_size: 200,
+        }),
+      })
+    })
+
+    // 预设音色（TtsVoiceModal 查询 GET /voices/presets）
+    await page.route("**/api/v1/voices/presets**", (route) =>
+      route.fulfill({
+        status: 200,
+        contentType: "application/json",
+        body: JSON.stringify({
+          items: [
+            {
+              voice_id: mockVoiceId,
+              name: "晓晓（女声）",
+              description: "温柔女声",
+              gender: "female",
+              language: "zh-CN",
+              preview_url: null,
+              tags: ["温柔"],
+            },
+          ],
+          total: 1,
+        }),
+      }),
+    )
+
+    // 克隆音色：空列表
+    await page.route(
+      (url) => url.pathname.endsWith("/voice-clones"),
+      (route) =>
+        route.fulfill({
+          status: 200,
+          contentType: "application/json",
+          body: JSON.stringify({ items: [] }),
+        }),
+    )
+
+    // TTS 合成：直接返回 completed 任务
+    await page.route("**/api/v1/tts/synthesize", (route) =>
+      route.fulfill({
+        status: 200,
+        contentType: "application/json",
+        body: JSON.stringify({ job_id: mockJobId, status: "queued" }),
+      }),
+    )
+    await page.route(`**/api/v1/tts/jobs/${mockJobId}/status`, (route) =>
+      route.fulfill({
+        status: 200,
+        contentType: "application/json",
+        body: JSON.stringify({
+          job_id: mockJobId,
+          status: "completed",
+          progress: 100,
+          audio_url: "data:audio/mpeg;base64,",
+          duration: 5,
+        }),
+      }),
+    )
+    await page.route(`**/api/v1/tts/jobs/${mockJobId}/save-to-library`, (route) =>
+      route.fulfill({
+        status: 200,
+        contentType: "application/json",
+        body: JSON.stringify({ id: `tts-asset-${suffix}`, name: "AI合成配音" }),
+      }),
+    )
+
     await page.goto("/app/generate")
     // ── 页面标题 ─────────────────────────────────────────────────
     await expect(page.getByText("智能剪辑").first()).toBeVisible({ timeout: 30000 })
@@ -314,38 +334,28 @@ test.describe("Core Smart-Edit Flow (#1970)", () => {
 
     // ── 文案选择弹窗：选第一条 → 确认 ─────────────────────────────
     await expect(page.getByText("📝 选择文案")).toBeVisible({ timeout: 5000 })
-    await page.getByText(`测试标题 ${suffix}`).first().click()
+    await page.getByText("测试带货文案").first().click()
     await page.getByRole("button", { name: "确认选择" }).click()
     await expect(page.getByText("📝 选择文案")).not.toBeVisible()
 
     // ── TTS 音色弹窗：选系统音色 → 合成 ─────────────────────────
     await expect(page.getByText("🎙️ 合成配音")).toBeVisible({ timeout: 5000 })
-    await page.getByText("龙小夏").first().click()
+    await page.getByText("晓晓（女声）").first().click()
     await page.getByRole("button", { name: "🎧 合成配音" }).click()
-    // 真实阿里云 CosyVoice 合成耗时偶有波动，放宽到 90s
-    await expect(page.getByText("🎙️ 合成配音")).not.toBeVisible({ timeout: 90000 })
+    await expect(page.getByText("🎙️ 合成配音")).not.toBeVisible({ timeout: 30000 })
 
     // ── Step 2：AI 匹配提示卡可见 + 选素材 ────────────────────────
-    await expect(page.getByText(/选择素材/).first()).toBeVisible({ timeout: 10000 })
-    await expect(page.getByText(/AI智能匹配/).first()).toBeVisible()
-    // 卡片中心是播放按钮（stopPropagation 仅播放不选中），点右上角空白处完成选中
-    await page
-      .getByTestId("material-card")
-      .first()
-      .click({ position: { x: 70, y: 12 } })
-    await expect(page.getByText(/已选 1 个素材|已选[^0]*[1-9]/)).toBeVisible({ timeout: 5000 })
+    await expect(page.getByText("选择素材", { exact: true })).toBeVisible({ timeout: 10000 })
+    await expect(page.getByText(/AI智能匹配/)).toBeVisible()
+    await page.getByTestId("material-card").first().click()
     await page.getByRole("button", { name: /下一步/ }).click()
 
     // ── Step 3：填写标题（handleScriptModalConfirm 已预填 script.title，但我们再覆盖一次） ─
     // (#2048: PreviewCountModal 已移除)
-    await expect(page.getByText(/选择标题/).first()).toBeVisible({ timeout: 10000 })
-    // 选中文案后标题框已预填该文案标题，下拉按当前输入过滤，直接选中该选项确认
-    const titleBox2 = page.locator(".ant-select-selection-search-input:visible").first()
-    await titleBox2.click()
-    await page
-      .locator(".ant-select-item-option", { hasText: `测试标题 ${suffix}` })
-      .first()
-      .click()
+    await expect(page.getByText("选择标题", { exact: true })).toBeVisible({ timeout: 10000 })
+    const titleInput2 = page.getByPlaceholder("输入或从标题库选择")
+    await expect(titleInput2).toBeVisible({ timeout: 5000 })
+    await titleInput2.fill(`测试叙事剪辑 ${suffix}`)
     await page.getByRole("button", { name: /下一步/ }).click()
 
     // ── Step 4：确认生成 ──────────────────────────────────────────
@@ -361,11 +371,8 @@ test.describe("Core Smart-Edit Flow (#1970)", () => {
     await confirmBtn2.click()
     const taskResp2 = await createTask2
     expect(taskResp2.ok(), `Create task: ${await taskResp2.text()}`).toBeTruthy()
-    const taskBody2 = await taskResp2.json()
-    const taskId2 = taskBody2.items?.[0]?.id ?? taskBody2.id ?? taskBody2.task_id
-    expect(taskId2, "created task should return an id").toBeTruthy()
-    console.log("[narrative] Generation task created:", taskId2)
-    await expect(page.getByText(/正在生成|提交/).first()).toBeVisible({ timeout: 15000 })
+    console.log("[narrative] Generation task created:", (await taskResp2.json()).id)
+    await expect(page.getByText(/正在生成|提交/)).toBeVisible({ timeout: 15000 })
     console.log("[narrative] Wizard flow completed ✓")
   })
 })

apps/web/e2e/core-upload.spec.ts

@@ -11,20 +11,11 @@ const apiOrigin = apiBase.endsWith("/api/v1") ? apiBase.slice(0, -"/api/v1".leng
 const routeBrowserApiToTestApi = async (page: import("@playwright/test").Page) => {
   if (!apiOrigin) return
   await page.route("**/api/v1/**", async (route) => {
-    try {
-      const sourceUrl = new URL(route.request().url())
-      const response = await route.fetch({
-        url: `${apiOrigin}${sourceUrl.pathname}${sourceUrl.search}`,
-      })
-      await route.fulfill({ response })
-    } catch {
-      // 收尾时页面可能已关闭，忽略在途请求避免误判
-      try {
-        await route.abort()
-      } catch {
-        /* noop */
-      }
-    }
+    const sourceUrl = new URL(route.request().url())
+    const response = await route.fetch({
+      url: `${apiOrigin}${sourceUrl.pathname}${sourceUrl.search}`,
+    })
+    await route.fulfill({ response })
   })
 }
 
@@ -54,7 +45,8 @@ type LibraryResponse = { id: string }
 test.describe("Core media upload flow", () => {
   test.describe.configure({ timeout: 180_000 })
   test("uploads a video asset and shows it in the asset library", async ({ page, request }) => {
-    // 串行执行时登录可能触发 429，两次退避约 130s，沿用 describe 的 180s 超时
+    test.setTimeout(120_000)
+
     await routeBrowserApiToTestApi(page)
     const suffix = Date.now().toString(36)
     const email = `e2e-mov-${suffix}@example.com`

apps/web/package-lock.json

@@ -14,7 +14,6 @@
         "axios": "^1.7.2",
         "classnames": "^2.5.1",
         "dayjs": "^1.11.23",
-        "marked": "^12.0.2",
         "mp4box": "^2.4.1",
         "react": "^18.3.1",
         "react-dom": "^18.3.1",
@@ -4503,17 +4502,6 @@
         "url": "https://github.com/sponsors/sindresorhus"
       }
     },
-    "node_modules/marked": {
-      "version": "12.0.2",
-      "resolved": "https://registry.npmmirror.com/marked/-/marked-12.0.2.tgz",
-      "integrity": "sha512-qXUm7e/YKFoqFPYPa3Ukg9xlI5cyAtGmyEIzMfW//m6kXwCy2Ps9DYf5ioijFKQ8qyuscrHoY04iJGctu2Kg0Q==",
-      "bin": {
-        "marked": "bin/marked.js"
-      },
-      "engines": {
-        "node": ">= 18"
-      }
-    },
     "node_modules/math-intrinsics": {
       "version": "1.1.0",
       "resolved": "https://registry.npmjs.org/math-intrinsics/-/math-intrinsics-1.1.0.tgz",

apps/web/package.json

@@ -25,7 +25,6 @@
     "axios": "^1.7.2",
     "classnames": "^2.5.1",
     "dayjs": "^1.11.23",
-    "marked": "^12.0.2",
     "mp4box": "^2.4.1",
     "react": "^18.3.1",
     "react-dom": "^18.3.1",

apps/web/src/api/env-flags.ts

@@ -1,41 +0,0 @@
-/**
- * 运行时开关安全读取
- *
- * 背景：本项目使用 Vite 构建，浏览器运行时不存在 Node 的全局 `process`。
- * 直接写 `process.env.XXX` 会在模块加载阶段抛出 `ReferenceError: process is not defined`，
- * 导致整个页面白屏崩溃。
- *
- * 统一通过本模块读取这类仅在构建/调试期注入的布尔开关：
- * - 优先读取 Vite 的 `import.meta.env.VITE_XXX`
- * - 兼容历史上未加 VITE_ 前缀、经由 Node 环境（单测 / 旧构建脚本）注入的 `process.env.XXX`
- * - 任何情况下访问失败都安全返回 false（默认走真实后端 API，不启用 mock）
- */
-
-/** 从可能不存在的 Node 全局 process 上安全读取环境变量 */
-function readNodeEnv(name: string): string | undefined {
-  try {
-    const proc = (globalThis as { process?: { env?: Record<string, string | undefined> } }).process
-    return proc?.env?.[name]
-  } catch {
-    return undefined
-  }
-}
-
-/**
- * 读取运行时布尔开关。
- *
- * @param name 开关名（不含 VITE_ 前缀的历史名称，如 POINTS_API_MOCK）
- * @returns 开关是否显式置为 "true"；未设置或读取失败时为 false
- */
-export function readRuntimeFlag(name: string): boolean {
-  // Vite 注入的环境变量（需 VITE_ 前缀才会暴露到浏览器）
-  const viteKey = `VITE_${name}`
-  const viteEnv = (import.meta as unknown as { env?: Record<string, string | undefined> }).env
-  const viteVal = viteEnv?.[viteKey] ?? viteEnv?.[name]
-
-  // 兼容 Node 环境下无前缀的历史变量名
-  const nodeVal = readNodeEnv(name)
-
-  const raw = viteVal ?? nodeVal
-  return raw === "true"
-}

apps/web/src/api/points/index.ts

@@ -8,7 +8,6 @@
  * 会员/订阅 API 在 @/api/subscription 中定义，避免重复封装。
  */
 import apiClient from "../client"
-import { readRuntimeFlag } from "../env-flags"
 import type {
   PointsBalance,
   PointsRulesResponse,
@@ -202,7 +201,7 @@ const MOCK_MEMBERSHIP: MembershipResponse = {
 
 /** 获取积分余额 */
 export async function getPointsBalance(): Promise<PointsBalance> {
-  if (readRuntimeFlag("POINTS_API_MOCK")) {
+  if (process.env.POINTS_API_MOCK === "true") {
     await new Promise((resolve) => setTimeout(resolve, MOCK_DELAY))
     return { ...MOCK_BALANCE }
   }
@@ -212,7 +211,7 @@ export async function getPointsBalance(): Promise<PointsBalance> {
 
 /** 获取积分消耗规则 */
 export async function getPointsRules(): Promise<PointsRulesResponse> {
-  if (readRuntimeFlag("POINTS_API_MOCK")) {
+  if (process.env.POINTS_API_MOCK === "true") {
     await new Promise((resolve) => setTimeout(resolve, MOCK_DELAY))
     return { rules: [...MOCK_RULES.rules], free_user_multiplier: MOCK_RULES.free_user_multiplier }
   }
@@ -222,7 +221,7 @@ export async function getPointsRules(): Promise<PointsRulesResponse> {
 
 /** 获取充值包列表 */
 export async function getPointsPackages(): Promise<PointsPackagesResponse> {
-  if (readRuntimeFlag("POINTS_API_MOCK")) {
+  if (process.env.POINTS_API_MOCK === "true") {
     await new Promise((resolve) => setTimeout(resolve, MOCK_DELAY))
     return { packages: MOCK_PACKAGES.packages.map((p) => ({ ...p })), user_discount: null }
   }
@@ -237,7 +236,7 @@ export async function getPointsTransactions(
   page = 1,
   pageSize = 20,
 ): Promise<PointsTransactionsResponse> {
-  if (readRuntimeFlag("POINTS_API_MOCK")) {
+  if (process.env.POINTS_API_MOCK === "true") {
     await new Promise((resolve) => setTimeout(resolve, MOCK_DELAY))
     const start = (page - 1) * pageSize
     const items = MOCK_TRANSACTIONS.slice(start, start + pageSize)
@@ -262,7 +261,7 @@ export async function getPointsTransactions(
 export async function createPointsOrder(
   data: CreateRechargeOrderRequest,
 ): Promise<CreateRechargeOrderResponse> {
-  if (readRuntimeFlag("POINTS_API_MOCK")) {
+  if (process.env.POINTS_API_MOCK === "true") {
     await new Promise((resolve) => setTimeout(resolve, MOCK_DELAY * 2))
     const pkg = MOCK_PACKAGES.packages.find((p) => p.code === data.package_id)
     if (!pkg) throw new Error("充值包不存在")
@@ -286,7 +285,7 @@ export async function createPointsOrder(
  * 积分预检查（消耗前调用）
  */
 export async function checkPoints(data: PointsCheckRequest): Promise<PointsCheckResponse> {
-  if (readRuntimeFlag("POINTS_API_MOCK")) {
+  if (process.env.POINTS_API_MOCK === "true") {
     await new Promise((resolve) => setTimeout(resolve, MOCK_DELAY))
     const rule = MOCK_RULES.rules.find((r) => r.scene_key === data.scene_key)
     if (!rule) {
@@ -327,7 +326,7 @@ export async function checkPoints(data: PointsCheckRequest): Promise<PointsCheck
 
 /** 获取每日免费额度使用情况 */
 export async function getDailyUsage(): Promise<DailyUsage> {
-  if (readRuntimeFlag("POINTS_API_MOCK")) {
+  if (process.env.POINTS_API_MOCK === "true") {
     await new Promise((resolve) => setTimeout(resolve, MOCK_DELAY))
     return { ...MOCK_DAILY_USAGE }
   }
@@ -337,7 +336,7 @@ export async function getDailyUsage(): Promise<DailyUsage> {
 
 /** 获取会员聚合信息（创作页可用来判断 max_resolution） */
 export async function getMembership(): Promise<MembershipResponse> {
-  if (readRuntimeFlag("POINTS_API_MOCK")) {
+  if (process.env.POINTS_API_MOCK === "true") {
     await new Promise((resolve) => setTimeout(resolve, MOCK_DELAY))
     return { ...MOCK_MEMBERSHIP }
   }

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

@@ -50,8 +50,6 @@ export interface PointsBalance {
   member_type: "monthly" | "quarterly" | "yearly" | null
   /** 会员到期时间 */
   member_expires_at: ISODate | null
-  /** 后端积分系统是否启用（false=免费放行，不做余额预校验） */
-  credits_enabled?: boolean
 }
 
 /* ================================================================

apps/web/src/api/scripts/scripts.ts

@@ -3,7 +3,6 @@
  * CRUD + 搜索/分类/分页；后端未就绪时使用 mock 数据（SCRIPTS_API_MOCK=true）
  */
 import apiClient from "../client"
-import { readRuntimeFlag } from "../env-flags"
 import type {
   ScriptItem,
   ScriptListParams,
@@ -17,7 +16,7 @@ import type {
  * #1894：文案库接口已上线，默认 false 走真实 API；
  * 通过 SCRIPTS_API_MOCK=true 环境变量可本地开启 mock 调试（行为同 POINTS_API_MOCK）。
  */
-export const SCRIPTS_API_MOCK = readRuntimeFlag("SCRIPTS_API_MOCK")
+export const SCRIPTS_API_MOCK = (process.env.SCRIPTS_API_MOCK as string | undefined) === "true"
 
 // ==================== Mock 数据 ====================
 

apps/web/src/api/subscription/subscription.ts

@@ -6,7 +6,6 @@
  * 所有请求走 apiClient（已配置 baseURL=/api/v1 和 token 拦截器）。
  */
 import apiClient from "../client"
-import { readRuntimeFlag } from "../env-flags"
 import type {
   SubscriptionInfo,
   SubscriptionPlan,
@@ -73,7 +72,7 @@ const MOCK_PLANS: SubscriptionPlan[] = [
 
 const MOCK_BILLING: BillingRecord[] = []
 
-const isMock = () => readRuntimeFlag("POINTS_API_MOCK")
+const isMock = () => (process.env.POINTS_API_MOCK as string | undefined) === "true"
 
 /** 获取当前订阅 */
 export const getCurrentSubscription = async (): Promise<SubscriptionInfo> => {

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

@@ -4,13 +4,6 @@ import type {
   HistoryResponse,
   StyleTemplate,
   ViralVideoJob,
-  ImageAnalysisResult,
-  CopyResult,
-  AnalyzeImagesRequest,
-  GenerateCopyRequest,
-  ConfirmCopyRequest,
-  ViralVideoModel,
-  ViralVideoModelsResponse,
 } from "./types"
 
 /** 创建爆款视频任务 */
@@ -48,109 +41,7 @@ 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 */
+/** 上传参考视频后触发风格分析（返回带 style_guide 的任务详情） */
 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

@@ -1,161 +1,64 @@
-export type FusionLevel = "ai_full" | "ai_polish" | "user_primary"
+export type FusionLevel = "full_ai" | "polish" | "as_is"
 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" },
+  { value: "full_ai", label: "AI 全写", desc: "给我方向，全由AI创作" },
+  { value: "polish", label: "AI润色", desc: "我写草稿，AI帮我润色" },
+  { value: "as_is", 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" },
+  { value: "strict", label: "深度模仿" },
 ]
 
-/** 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"
+  "pending" | "running" | "wait_user_confirm" | "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
+ * 后端流水线阶段字符串。前端不展示逐阶段进度列表，仅保留类型
+ * 用于轮询时判断当前在哪个大阶段（分析中 vs 视频生成中）以选择轮询间隔/文案。
  */
 export type ViralVideoStage =
   | "image_analysis"
   | "video_analysis"
   | "intent_parsing"
-  | "script_generation"
+  | "copy_fusion"
+  | "storyboard"
   | "review"
   | "tts"
+  | "bgm_select"
   | "rendering"
+  | "musetalk"
   | "uploading"
 
-/** 图片+视频分析阶段：属于「分析图片」按钮的范围 */
-const IMAGE_ANALYSIS_STAGES = new Set<ViralVideoStage>(["image_analysis", "video_analysis"])
-/** 编导脚本阶段：属于「生成文案」按钮的范围 */
-const COPY_STAGES = new Set<ViralVideoStage>(["intent_parsing", "script_generation", "review"])
-/** 视频生成阶段：属于「开始生成视频」按钮的范围（v1.6: TTS+单次Seedance+上传） */
-const VIDEO_STAGES = new Set<ViralVideoStage>(["tts", "rendering", "uploading"])
+/** 分析类阶段（image_analysis / video_analysis / intent_parsing）：属于「开始分析」阶段 */
+const ANALYSIS_STAGES = new Set<ViralVideoStage>([
+  "image_analysis",
+  "video_analysis",
+  "intent_parsing",
+])
 
-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 识别结果（v8 叙述优先，仅保留最少结构化字段） */
-export interface ImageProductAnalysis {
-  /** store / product / person / scene */
-  type?: string
-  name?: string
-  brand?: string
-  has_person?: boolean
-  /** v8: 用户端展示用的叙述 markdown（由提示词控制排版） */
-  summary_markdown?: string
-  /** 标题行兼容字段 */
-  category?: string
-}
-
-export interface ImageAnalysisResult {
-  /** v8 字段 */
-  images?: ImageProductAnalysis[]
-  /** 老数据兼容 */
-  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
-  /** v3 storyboard: 用户端展示用的 markdown 文案（由提示词控制排版） */
-  copy_display_markdown?: 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 }>
+  return !!stage && ANALYSIS_STAGES.has(stage)
 }
 
 export interface StyleTemplate {
   id: string
   name: string
   description?: string
-  thumbnail_url?: string
-  style_config?: Record<string, unknown>
+  preview_url?: string
   tags?: string[]
 }
 
 export interface IntentResult {
-  intent?: string
-  key_messages?: string[]
-  tone?: string
-  target_emotion?: string
-  call_to_action?: string
+  product: string
+  selling_points: string[]
+  target_audience: string
+  tone: string
+  structure: string
+  duration: number
   suggested_title?: string
-  /** v1.5 旧字段兼容 */
-  product?: string
-  selling_points?: string[]
-  target_audience?: string
-  structure?: string
-  duration?: number
   suggested_copy?: string
 }
 
@@ -166,36 +69,20 @@ export interface ViralVideoJob {
   reference_video_url?: string
   style_strength?: StyleStrength
   style_template_id?: string
-  style_guide?: string | Record<string, unknown>
+  style_guide?: string
   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" | "my_voice"
   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
@@ -204,13 +91,11 @@ export interface ViralVideoJob {
 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" | "my_voice"
   bgm_preference?: string
   industry?: string
   target_customer?: string
@@ -218,12 +103,9 @@ export interface GenerateViralVideoRequest {
   persona_id?: string
   viral_structure?: string
   marketing_purpose?: string
-  /** 视频时长（5-30秒，默认15） */
   duration?: number
   video_model?: string
   video_ratio?: string
-  /** 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 {
@@ -232,84 +114,3 @@ export interface HistoryResponse {
   page: number
   page_size: number
 }
-
-/** v1.6 阶段1请求：图片/视频分析（POST /viral-video/analyze-images） */
-export interface AnalyzeImagesRequest {
-  images: string[]
-  reference_video_url?: string
-  style_template_id?: string
-  style_strength?: StyleStrength
-  /** TTS 音色 ID（STEP1 已选音色时传） */
-  voice_id?: string
-  /** 音色来源：preset | library | clone | upload */
-  voice_source?: "preset" | "library" | "clone" | "upload" | "my_voice"
-  /** 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" | "my_voice"
-  /** 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/api/voice-clone/types.ts

@@ -18,8 +18,6 @@ export interface VoiceClone {
   language: string
   gender: string
   error_message: string | null
-  /** CosyVoice 实际使用的音色 ID（status=ready 时由后端填充，用于 TTS 调用） */
-  voice_id?: string | null
   created_at: string
   updated_at: string
 }

apps/web/src/api/voice-clone/utils.ts

@@ -18,7 +18,6 @@ export const toVoiceClone = (profile: VoiceCloneProfile): VoiceClone => ({
   language: profile.language || "",
   gender: profile.gender || "",
   error_message: profile.error_message || null,
-  voice_id: profile.voice_id,
   created_at: profile.created_at,
   updated_at: profile.updated_at,
 })

apps/web/src/components/common/DurationWheelPicker/DurationWheelPicker.css

@@ -1,182 +0,0 @@
-/* DurationWheelPicker —— 弹层式滚轮选择器（样式与表单一致） */
-
-/* 触发按钮：外观复用 .vv-select 风格 */
-.dw-trigger {
-  display: flex;
-  align-items: center;
-  justify-content: space-between;
-  width: 100%;
-  height: 36px;
-  padding: 0 12px;
-  background: #fff;
-  border: 1px solid #e0e0e8;
-  border-radius: 8px;
-  font-size: 13px;
-  color: #1f2937;
-  cursor: pointer;
-  box-sizing: border-box;
-  transition: all 0.15s;
-  user-select: none;
-}
-.dw-trigger:hover {
-  border-color: #c0c0d0;
-}
-.dw-trigger-open,
-.dw-trigger:focus-within {
-  border-color: #7c3aed !important;
-  box-shadow: 0 0 0 2px rgba(124, 58, 237, 0.12);
-}
-.dw-trigger-disabled {
-  opacity: 0.5;
-  pointer-events: none;
-  cursor: not-allowed;
-}
-.dw-trigger-val {
-  flex: 1;
-  overflow: hidden;
-  text-overflow: ellipsis;
-  white-space: nowrap;
-}
-.dw-trigger-placeholder {
-  color: #9ca3af;
-}
-.dw-trigger-arrow {
-  font-size: 10px;
-  color: #9ca3af;
-  margin-left: 8px;
-  transition: transform 0.2s;
-}
-.dw-trigger-arrow-up {
-  transform: rotate(180deg);
-}
-
-/* 弹层容器 */
-.dw-popup {
-  padding: 8px;
-  min-width: 140px;
-}
-
-/* 滚轮 */
-.dw-picker {
-  position: relative;
-  width: 100%;
-  overflow: hidden;
-  border-radius: 8px;
-  background: #fafafe;
-  border: 1px solid #e5e7eb;
-}
-.dw-picker-list {
-  margin: 0;
-  padding: 0;
-  list-style: none;
-  height: 100%;
-  overflow-y: scroll;
-  scroll-snap-type: y mandatory;
-  -webkit-overflow-scrolling: touch;
-  scrollbar-width: none;
-}
-.dw-picker-list::-webkit-scrollbar {
-  display: none;
-}
-.dw-picker-item {
-  display: flex;
-  align-items: baseline;
-  justify-content: center;
-  gap: 3px;
-  scroll-snap-align: center;
-  cursor: pointer;
-  font-size: 15px;
-  color: #9ca3af;
-  font-weight: 400;
-  transition:
-    color 0.15s,
-    transform 0.15s,
-    font-weight 0.15s;
-}
-.dw-picker-item-val {
-  font-variant-numeric: tabular-nums;
-}
-.dw-picker-item-unit {
-  font-size: 13px;
-  color: inherit;
-}
-.dw-picker-item-active {
-  color: #7c3aed;
-  font-weight: 600;
-}
-.dw-picker-item-active .dw-picker-item-val {
-  font-size: 18px;
-}
-.dw-picker-item-active .dw-picker-item-unit {
-  font-size: 14px;
-}
-
-/* 中心选中条 */
-.dw-picker-mask {
-  position: absolute;
-  left: 6px;
-  right: 6px;
-  pointer-events: none;
-  background: #f5f0ff;
-  border-radius: 6px;
-  z-index: 1;
-}
-.dw-picker-mask::before,
-.dw-picker-mask::after {
-  content: "";
-  position: absolute;
-  left: 0;
-  right: 0;
-  height: 1px;
-  background: #d8c4ff;
-}
-.dw-picker-mask::before {
-  top: 0;
-}
-.dw-picker-mask::after {
-  bottom: 0;
-}
-
-/* 上下渐变 */
-.dw-picker-fade {
-  position: absolute;
-  left: 0;
-  right: 0;
-  height: 40%;
-  pointer-events: none;
-  z-index: 2;
-}
-.dw-picker-fade-top {
-  top: 0;
-  background: linear-gradient(to bottom, #fafafe 25%, rgba(250, 250, 254, 0));
-}
-.dw-picker-fade-bottom {
-  bottom: 0;
-  background: linear-gradient(to top, #fafafe 25%, rgba(250, 250, 254, 0));
-}
-
-/* 弹层按钮区 */
-.dw-popup-actions {
-  display: flex;
-  gap: 8px;
-  justify-content: flex-end;
-  margin-top: 8px;
-}
-.dw-popup-actions .ant-btn {
-  border-radius: 6px;
-}
-.dw-popup-actions .ant-btn-primary {
-  background: #7c3aed;
-}
-.dw-popup-actions .ant-btn-primary:hover {
-  background: #6d28d9 !important;
-}
-
-/* 覆盖 antd Popover 默认内边距 */
-.dw-popover .ant-popover-inner {
-  padding: 0 !important;
-  overflow: hidden;
-}
-.dw-popover .ant-popover-arrow {
-  display: none;
-}

apps/web/src/components/common/DurationWheelPicker/index.tsx

@@ -1,180 +0,0 @@
-/**
- * DurationWheelPicker —— 竖屏滚轮式时长选择器（弹层版）
- *
- * 设计：
- * - 外观是和其他表单 Select 一致的输入框（白色底+1px灰边+紫色focus ring）
- * - 点击输入框弹出 Popover，内部是滚轮 picker（原生 scroll-snap，零依赖）
- * - 滚轮样式：白底容器，选中行 #7c3aed 紫字加粗+浅紫背景条
- * - 支持触摸/鼠标滚轮/点击；松手吸附；底部"确认/取消"按钮
- * - 默认范围 15–30 秒，步长 1 秒
- */
-import React, { useEffect, useMemo, useRef, useState, useCallback } from "react"
-import { Popover, Button } from "antd"
-import { DownOutlined } from "@ant-design/icons"
-import "./DurationWheelPicker.css"
-
-export interface DurationWheelPickerProps {
-  value?: number
-  min?: number
-  max?: number
-  step?: number
-  unit?: string
-  onChange?: (value: number) => void
-  placeholder?: string
-  disabled?: boolean
-  /** 弹层宽度，默认 160px */
-  popupWidth?: number
-  /** 弹层内滚轮高度，默认 180px */
-  wheelHeight?: number
-}
-
-const ITEM_HEIGHT = 36
-
-const DurationWheelPicker: React.FC<DurationWheelPickerProps> = ({
-  value = 20,
-  min = 15,
-  max = 30,
-  step = 1,
-  unit = "秒",
-  onChange,
-  placeholder = "请选择时长",
-  disabled = false,
-  popupWidth = 160,
-  wheelHeight = 180,
-}) => {
-  const options = useMemo(() => {
-    const arr: number[] = []
-    for (let v = min; v <= max; v += step) arr.push(v)
-    return arr
-  }, [min, max, step])
-
-  const [open, setOpen] = useState(false)
-  // 弹层内暂存值，点确认才提交
-  const [draft, setDraft] = useState<number>(value)
-  const listRef = useRef<HTMLUListElement>(null)
-  const scrollTimerRef = useRef<ReturnType<typeof setTimeout> | null>(null)
-
-  useEffect(() => {
-    if (open) {
-      setDraft(value)
-      // 下一帧滚到当前值
-      requestAnimationFrame(() => scrollToValue(value, false))
-    }
-    // eslint-disable-next-line react-hooks/exhaustive-deps
-  }, [open])
-
-  const scrollToValue = useCallback(
-    (v: number, smooth = true) => {
-      const list = listRef.current
-      if (!list) return
-      const idx = options.indexOf(v)
-      if (idx < 0) return
-      list.scrollTo({ top: idx * ITEM_HEIGHT, behavior: smooth ? "smooth" : "auto" })
-    },
-    [options],
-  )
-
-  const handleScroll = () => {
-    if (scrollTimerRef.current) clearTimeout(scrollTimerRef.current)
-    scrollTimerRef.current = setTimeout(() => {
-      const list = listRef.current
-      if (!list) return
-      const idx = Math.round(list.scrollTop / ITEM_HEIGHT)
-      const clamped = Math.max(0, Math.min(options.length - 1, idx))
-      const targetTop = clamped * ITEM_HEIGHT
-      if (Math.abs(list.scrollTop - targetTop) > 1) {
-        list.scrollTo({ top: targetTop, behavior: "smooth" })
-      }
-      setDraft(options[clamped])
-    }, 100)
-  }
-
-  const handleConfirm = () => {
-    onChange?.(draft)
-    setOpen(false)
-  }
-
-  const handleCancel = () => {
-    setOpen(false)
-  }
-
-  const handleItemClick = (v: number) => {
-    setDraft(v)
-    scrollToValue(v, true)
-  }
-
-  const maskTop = wheelHeight / 2 - ITEM_HEIGHT / 2
-
-  const wheel = (
-    <div className="dw-popup">
-      <div
-        className="dw-picker"
-        style={{ height: wheelHeight, width: popupWidth - 24 /* padding */ }}
-      >
-        <div className="dw-picker-mask" style={{ top: maskTop, height: ITEM_HEIGHT }} aria-hidden />
-        <div className="dw-picker-fade dw-picker-fade-top" aria-hidden />
-        <div className="dw-picker-fade dw-picker-fade-bottom" aria-hidden />
-        <ul
-          ref={listRef}
-          className="dw-picker-list"
-          onScroll={handleScroll}
-          style={{
-            paddingTop: wheelHeight / 2 - ITEM_HEIGHT / 2,
-            paddingBottom: wheelHeight / 2 - ITEM_HEIGHT / 2,
-          }}
-        >
-          {options.map((v) => {
-            const isActive = v === draft
-            return (
-              <li
-                key={v}
-                className={`dw-picker-item${isActive ? " dw-picker-item-active" : ""}`}
-                style={{ height: ITEM_HEIGHT, lineHeight: `${ITEM_HEIGHT}px` }}
-                onClick={() => handleItemClick(v)}
-                aria-selected={isActive}
-                role="option"
-              >
-                <span className="dw-picker-item-val">{v}</span>
-                <span className="dw-picker-item-unit">{unit}</span>
-              </li>
-            )
-          })}
-        </ul>
-      </div>
-      <div className="dw-popup-actions">
-        <Button size="small" onClick={handleCancel}>
-          取消
-        </Button>
-        <Button size="small" type="primary" onClick={handleConfirm}>
-          确认
-        </Button>
-      </div>
-    </div>
-  )
-
-  return (
-    <Popover
-      open={!disabled && open}
-      onOpenChange={(v) => setOpen(v)}
-      content={wheel}
-      trigger="click"
-      placement="bottomLeft"
-      overlayClassName="dw-popover"
-      overlayStyle={{ padding: 0 }}
-      overlayInnerStyle={{ padding: 0, borderRadius: 10 }}
-      destroyTooltipOnHide
-    >
-      <div
-        className={`dw-trigger${disabled ? " dw-trigger-disabled" : ""}${open ? " dw-trigger-open" : ""}`}
-        style={{ height: 36 }}
-      >
-        <span className={`dw-trigger-val${value != null ? "" : " dw-trigger-placeholder"}`}>
-          {value != null ? `${value}${unit}` : placeholder}
-        </span>
-        <DownOutlined className={`dw-trigger-arrow${open ? " dw-trigger-arrow-up" : ""}`} />
-      </div>
-    </Popover>
-  )
-}
-
-export default DurationWheelPicker

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

@@ -8,6 +8,11 @@ export const ROUTE_TITLE_MAP: Record<string, string> = {
   "/app/products": "成片库",
   "/app/templates": "模板库",
   "/app/history": "任务历史",
+  "/app/admin": "控制台",
+  "/app/admin/users": "用户管理",
+  "/app/admin/analytics": "数据分析",
+  "/app/admin/monitor": "系统监控",
+  "/app/admin/logs": "系统日志",
   "/app/subscription": "订阅管理",
   "/app/subscription/upgrade": "升级订阅",
   "/app/subscription/billing": "账单管理",

apps/web/src/config/features.ts

@@ -10,4 +10,4 @@
  *   功能流程不做积分预校验，直接走生成。
  * - true：展示完整积分系统 UI。
  */
-export const ENABLE_CREDIT_SYSTEM = true
+export const ENABLE_CREDIT_SYSTEM = false

apps/web/src/config/navigation.ts

@@ -13,6 +13,7 @@ import {
   HistoryOutlined,
   TrophyOutlined,
   ScanOutlined,
+  ControlOutlined,
   CrownOutlined,
   ThunderboltOutlined,
   UnorderedListOutlined,
@@ -206,6 +207,12 @@ export const NAV_GROUPS: NavGroup[] = [
         path: "/app/duplication",
         icon: React.createElement(ScanOutlined),
       },
+      {
+        key: "admin",
+        label: "控制台",
+        path: "/app/admin",
+        icon: React.createElement(ControlOutlined),
+      },
       {
         key: "subscription",
         label: "会员订阅",

apps/web/src/pages/admin/Admin.css

@@ -0,0 +1,27 @@
+/* Admin 页面样式（Phase 3 精简）
+ *
+ * 原始 477 行 → 精简至仅保留实际使用的 class。
+ * 已迁移至 global.css / ui.css 的样式不再重复定义：
+ *   .xx-page-head       → global.css
+ *   .xx-primary-btn     → global.css
+ *   .xx-tag / .xx-card  → ui.css / global.css
+ *
+ * 以下 class 仅被 AdminComingSoon.tsx 使用。
+ */
+
+.admin-coming-soon-page {
+  padding: 32px;
+  max-width: 1680px;
+  margin: 0 auto;
+}
+
+.xx-result-center {
+  display: flex;
+  justify-content: center;
+  align-items: center;
+  min-height: 400px;
+}
+
+.xx-result-center .ant-result {
+  padding: 48px;
+}

apps/web/src/pages/admin/AdminComingSoon.tsx

@@ -0,0 +1,35 @@
+import React from "react"
+import { Button, Card, Result } from "antd"
+import { useNavigate } from "react-router-dom"
+import "./Admin.css"
+
+const AdminComingSoon: React.FC = () => {
+  const navigate = useNavigate()
+
+  return (
+    <div className="admin-coming-soon-page">
+      <div className="xx-result-center">
+        <Card className="xx-card">
+          <Result
+            status="info"
+            title="Admin 后台暂未开放"
+            subTitle="当前版本未接入后台用户、监控、日志、分析等后端服务，因此不展示模拟运营数据，也不会提供假操作入口。"
+            extra={[
+              <Button
+                type="primary"
+                onClick={() => navigate("/app/dashboard")}
+                className="xx-primary-btn"
+              >
+                返回首页
+              </Button>,
+            ]}
+          />
+        </Card>
+      </div>
+    </div>
+  )
+}
+
+export default AdminComingSoon
+
+export const Component = AdminComingSoon

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"
@@ -38,8 +40,6 @@ const GeneratePage: React.FC = () => {
 
   /* ── 积分状态 ── */
   const { balance, dailyUsage, rules, init: initPoints } = usePointsStore()
-  // 后端积分总开关（由 /points/balance 返回；数据未就绪时保守按 UI 开关处理）
-  const creditsEnabled = balance?.credits_enabled ?? ENABLE_CREDIT_SYSTEM
   useEffect(() => {
     initPoints()
   }, [initPoints])
@@ -88,6 +88,7 @@ const GeneratePage: React.FC = () => {
     style,
     autoSubtitles,
     bgm,
+    editPlanId,
     sourceEditPlanId,
     previewTaskId,
     setPreviewTaskId,
@@ -344,8 +345,7 @@ const GeneratePage: React.FC = () => {
   const handleConfirmGenerate = useCallback(async () => {
     // 积分预检查（积分系统关闭时跳过，直接走生成流程）
     let check: ReturnType<typeof hasEnoughPoints> = { sufficient: true, cost: 0 }
-    // 仅当后端积分系统真实启用时才做余额预校验（后端免费放行时前端不得拦截）
-    if (creditsEnabled) {
+    if (ENABLE_CREDIT_SYSTEM) {
       const units = isBatch ? Math.max(selectedVariantIds.length, 1) : 1
       check = hasEnoughPoints(
         balance ?? null,
@@ -391,7 +391,6 @@ const GeneratePage: React.FC = () => {
     balance,
     dailyUsage,
     rules,
-    creditsEnabled,
   ])
 
   /* ── 步骤导航 ── */
@@ -506,7 +505,7 @@ const GeneratePage: React.FC = () => {
   /* ── 积分消耗估算（步骤3确认生成展示用） ── */
   const unitsForCost = isBatch ? Math.max(selectedVariantIds.length, 1) : 1
   const pointsEstimate = useMemo(() => {
-    if (!creditsEnabled) return { sufficient: true, cost: 0 }
+    if (!ENABLE_CREDIT_SYSTEM) return { sufficient: true, cost: 0 }
     return hasEnoughPoints(
       balance ?? null,
       unitsForCost,
@@ -515,8 +514,8 @@ const GeneratePage: React.FC = () => {
       "free",
       rules?.free_user_multiplier ?? 1.15,
     )
-  }, [unitsForCost, balance, dailyUsage, rules, creditsEnabled])
-  const insufficientPoints = creditsEnabled && !pointsEstimate.sufficient
+  }, [unitsForCost, balance, dailyUsage, rules])
+  const insufficientPoints = ENABLE_CREDIT_SYSTEM && !pointsEstimate.sufficient
 
   /* ================================================================
      渲染
@@ -524,6 +523,10 @@ 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/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/useViralVideoWebSocket.ts

@@ -1,136 +0,0 @@
-import { useCallback, useEffect, useRef } from "react"
-
-export interface ViralVideoDeltaEvent {
-  type: "viral_video:script_delta"
-  job_id: string
-  stage: string
-  progress: number
-  message?: string
-  data: {
-    delta: string
-    full_text: string
-    text_length: number
-  }
-}
-
-export interface ViralVideoWSError {
-  message: string
-}
-
-export interface UseViralVideoWSOptions {
-  /** delta 事件回调（script_delta 推送时触发） */
-  onDelta?: (ev: ViralVideoDeltaEvent) => void
-  /** 连接关闭/失败回调 */
-  onError?: (err: ViralVideoWSError) => void
-  /** 连接建立回调 */
-  onOpen?: () => void
-}
-
-const WS_SCHEME =
-  typeof window !== "undefined" && window.location.protocol === "https:" ? "wss:" : "ws:"
-
-function buildWsUrl(jobId: string): string {
-  const token = localStorage.getItem("access_token") || ""
-  const host = window.location.host
-  return `${WS_SCHEME}//${host}/api/v1/viral-video/ws/${jobId}?token=${encodeURIComponent(token)}`
-}
-
-/**
- * 爆款视频 WebSocket 订阅 hook。
- * 仅在 jobId 非空时建立连接；组件卸载/ jobId 变更时自动关闭。
- * 失败静默：后端已说明流式异常会自动 fallback 到 HTTP 轮询的 copy_generated 终态，
- * 前端不需要中断主流程，连接失败时只记录不影响轮询继续推进 UI。
- */
-export function useViralVideoWS(
-  jobId: string | null | undefined,
-  { onDelta, onError, onOpen }: UseViralVideoWSOptions = {},
-) {
-  const wsRef = useRef<WebSocket | null>(null)
-  const manualCloseRef = useRef(false)
-  const onDeltaRef = useRef(onDelta)
-  const onErrorRef = useRef(onError)
-  const onOpenRef = useRef(onOpen)
-  onDeltaRef.current = onDelta
-  onErrorRef.current = onError
-  onOpenRef.current = onOpen
-
-  const close = useCallback(() => {
-    manualCloseRef.current = true
-    if (wsRef.current) {
-      try {
-        wsRef.current.close()
-      } catch {
-        /* noop */
-      }
-      wsRef.current = null
-    }
-  }, [])
-
-  useEffect(() => {
-    if (!jobId) {
-      close()
-      return
-    }
-    manualCloseRef.current = false
-    let closed = false
-    let retryTimer: ReturnType<typeof setTimeout> | null = null
-    let startTimer: ReturnType<typeof setTimeout> | null = null
-    let retries = 0
-    const MAX_RETRIES = 3
-
-    const connect = () => {
-      if (closed) return
-      try {
-        const ws = new WebSocket(buildWsUrl(jobId))
-        wsRef.current = ws
-
-        ws.onopen = () => {
-          if (closed) return
-          retries = 0
-          onOpenRef.current?.()
-        }
-
-        ws.onmessage = (ev) => {
-          try {
-            const payload = JSON.parse(ev.data)
-            if (payload?.type === "viral_video:script_delta" && payload.data) {
-              onDeltaRef.current?.(payload as ViralVideoDeltaEvent)
-            }
-            // copy_generated/completed/failed 等终态事件由 HTTP 轮询统一处理，
-            // 此处仅消费 delta 做流式预览，不重复推状态。
-          } catch {
-            // 心跳/非 JSON 消息忽略
-          }
-        }
-
-        ws.onerror = () => {
-          onErrorRef.current?.({ message: "websocket error" })
-        }
-
-        ws.onclose = () => {
-          wsRef.current = null
-          if (closed || manualCloseRef.current) return
-          if (retries < MAX_RETRIES) {
-            retries += 1
-            const delay = 500 * 2 ** (retries - 1)
-            retryTimer = setTimeout(connect, delay)
-          }
-        }
-      } catch (e) {
-        onErrorRef.current?.({ message: (e as Error).message })
-      }
-    }
-
-    // 延迟 100ms 再连，给后端 job 初始化留一点时间
-    startTimer = setTimeout(connect, 100)
-
-    return () => {
-      closed = true
-      if (startTimer) clearTimeout(startTimer)
-      if (retryTimer) clearTimeout(retryTimer)
-      close()
-    }
-  }, [jobId, close])
-
-  return { close }
-}

apps/web/src/router/appRoutes.tsx

@@ -116,6 +116,31 @@ const appChildren: RouteObject[] = [
     path: "profile",
     lazy: lazyRoute(() => import("@/pages/profile/Settings")),
   },
+  {
+    path: "admin",
+    children: [
+      {
+        index: true,
+        lazy: lazyRoute(() => import("@/pages/admin/AdminComingSoon")),
+      },
+      {
+        path: "users",
+        lazy: lazyRoute(() => import("@/pages/admin/AdminComingSoon")),
+      },
+      {
+        path: "analytics",
+        lazy: lazyRoute(() => import("@/pages/admin/AdminComingSoon")),
+      },
+      {
+        path: "monitor",
+        lazy: lazyRoute(() => import("@/pages/admin/AdminComingSoon")),
+      },
+      {
+        path: "logs",
+        lazy: lazyRoute(() => import("@/pages/admin/AdminComingSoon")),
+      },
+    ],
+  },
 ]
 
 export const appRoutes: RouteObject = {

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/AdminComingSoon.test.tsx

@@ -0,0 +1,32 @@
+import { describe, expect, it, vi } from "vitest"
+import { render, screen } from "@testing-library/react"
+import { MemoryRouter } from "react-router-dom"
+import AdminComingSoon from "@/pages/admin/AdminComingSoon"
+
+vi.mock("react-router-dom", async () => {
+  const actual = await vi.importActual("react-router-dom")
+  return {
+    ...actual,
+    useNavigate: () => vi.fn(),
+  }
+})
+
+describe("AdminComingSoon Page", () => {
+  it("should render without crashing", () => {
+    render(
+      <MemoryRouter>
+        <AdminComingSoon />
+      </MemoryRouter>,
+    )
+    expect(screen.getByText("Admin 后台暂未开放")).toBeTruthy()
+  })
+
+  it("should render back button", () => {
+    render(
+      <MemoryRouter>
+        <AdminComingSoon />
+      </MemoryRouter>,
+    )
+    expect(screen.getByText("返回首页")).toBeTruthy()
+  })
+})

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/worker_app/celery_app.py

@@ -53,9 +53,6 @@ celery_app.conf.imports = (
     # #1998 GPU MuseTalk 异步推理：wait_for_result→签名 URL→回写 lipsync_jobs
     # 必须在 Worker 侧注册，否则 apply_async 消息无人消费，job 永远卡在 processing
     "app.tasks.lipsync_gpu",
-    # #2076 Ditto 蚂蚁数字人异步推理：同步 HTTP 调用 Ditto → MP4 流转存 OSS → 回写 lipsync_jobs
-    # 必须在 Worker 侧注册；失败回退 GPU MuseTalk → MediaKit
-    "app.tasks.lipsync_ditto",
 )
 
 # Celery Beat 定时任务调度

apps/worker/worker_app/tasks/generation.py

@@ -387,41 +387,6 @@ BATCH_RENDER_SIMILARITY_LIMIT = 0.20
 """批次内成片查重相似度阈值：超过则重选独立 plan 重渲一次（20%）。"""
 
 
-def _refund_smart_edit_prepaid(task_id: str) -> None:
-    """智能剪辑任务最终失败时退还预扣积分（幂等）。"""
-    session = SessionLocal()
-    try:
-        from packages.adapters.sqlalchemy_impl.generation_task_repository import (
-            SQLAlchemyGenerationTaskRepository,
-        )
-        from packages.domain.points_service import PointsService
-
-        repo = SQLAlchemyGenerationTaskRepository(session)
-        task = repo.get(task_id)
-        if not task:
-            return
-        prepaid = float(getattr(task, "credits_prepaid", 0) or 0)
-        if prepaid <= 0:
-            return
-        txn_id = getattr(task, "credits_transaction_id", "") or ""
-        res = PointsService().refund_points(
-            user_id=task.user_id,
-            amount=prepaid,
-            source="smart_edit",
-            db=session,
-            ref_id=task.id,
-            related_transaction_id=txn_id or None,
-            description="智能剪辑任务失败退回",
-        )
-        task.credits_cost = 0.0
-        task.credits_prepaid = 0.0
-        repo.update(task)
-        if not res.get("success"):
-            logger.warning("[task_id=%s] 失败退积分未成功: %s", task_id, res)
-    finally:
-        session.close()
-
-
 def should_rerender_for_batch_dedup(*, batch_id: str, render_attempt: int, batch_similarity) -> bool:
     """批次内查重后判定是否需要重选 plan 重渲。
 
@@ -1202,10 +1167,6 @@ def generate_video(self, task_id: str) -> dict:
                 "mark_failed",
                 error_message="source_edit_plan_id is required. Please create a preview task first.",
             )
-            try:
-                _refund_smart_edit_prepaid(task_id)
-            except Exception:
-                logger.warning("[task_id=%s] 失败退积分异常", task_id, exc_info=True)
             return {
                 "status": "failed",
                 "task_id": task_id,
@@ -1244,7 +1205,6 @@ def generate_video(self, task_id: str) -> dict:
         )
 
         # ── 自动重试逻辑 ──────────────────────────────────────────────────
-        will_retry = False
         try:
             from packages.adapters.sqlalchemy_impl.generation_task_repository import (
                 SQLAlchemyGenerationTaskRepository,
@@ -1257,7 +1217,6 @@ def generate_video(self, task_id: str) -> dict:
                 if _task and _task.auto_retry_enabled and _task.auto_retry_max > 0:
                     current_retry = _task.retry_count or 0
                     if current_retry < _task.auto_retry_max:
-                        will_retry = True
                         logger.info(
                             "[task_id=%s] 触发自动重试: 当前重试次数=%d, 最大重试次数=%d",
                             task_id,
@@ -1291,13 +1250,6 @@ def generate_video(self, task_id: str) -> dict:
                 exc_info=True,
             )
 
-        # 最终失败（不再重试）：退还 smart_edit 预扣积分
-        if not will_retry:
-            try:
-                _refund_smart_edit_prepaid(task_id)
-            except Exception:
-                logger.warning("[task_id=%s] 失败退积分异常", task_id, exc_info=True)
-
         return {
             "status": "failed",
             "task_id": task_id,

apps/worker/worker_app/tasks/vision/__init__.py

@@ -1,4 +0,0 @@
-# -*- coding: utf-8 -*-
-"""V2 图片分析：火山OCR专用API + doubao-lite强约束JSON并行，单次pro VLM兜底。"""
-
-from .fast_path import analyze_image_v2, analyze_images_v2  # noqa: F401

apps/worker/worker_app/tasks/vision/_prompt.py

@@ -1,95 +0,0 @@
-# -*- coding: utf-8 -*-
-"""V2 prompt 解析：优先读后台 viral_video_prompt_templates（prompt_type='image_analysis'
-且 is_active=true），30s TTL 热加载；DB 无有效记录/异常时，fallback 到 prompts.py 的
-image_analysis v8 默认 system/user。
-
-规则：
-- DB 有 is_active=true 的 image_analysis 记录：system 原样用 DB.system_prompt
-  （自带完整输出格式，不追加任何硬编码 schema），user 用 DB.user_prompt_template
-  渲染（填入 image_url / ocr_text）；
-- DB 无记录/异常：system/user 用 prompts.py 里的 v8 默认模板。
-"""
-
-from __future__ import annotations
-
-import logging
-import threading
-import time
-
-logger = logging.getLogger(__name__)
-
-
-def _default_template() -> dict:
-    # 延迟导入：避免模块加载时拉起整个 packages 依赖链（也便于旧 Python 收集测试）
-    from packages.application.viral_video.prompts import DEFAULT_TEMPLATES
-
-    for item in DEFAULT_TEMPLATES:
-        if item["prompt_type"] == "image_analysis":
-            return item
-    raise RuntimeError("image_analysis 默认模板缺失")
-
-
-_cache_lock = threading.Lock()
-_cache: dict[str, tuple[float, tuple[str, str]]] = {}
-_CACHE_TTL = 30.0
-
-
-def _load_db_template():
-    """查 DB is_active=true 的 image_analysis 记录；不可达/无记录返回 None。"""
-    try:
-        from packages.application.viral_video.prompt_loader import _load_from_db
-
-        return _load_from_db("image_analysis")
-    except Exception as e:  # noqa: BLE001
-        logger.warning("[vision.v2] 查询DB image_analysis prompt失败: %s", e)
-        return None
-
-
-def _render_user(user_tpl: str, image_url: str, ocr_text: str) -> str:
-    try:
-        return user_tpl.format(image_url=image_url, ocr_text=ocr_text or "无")
-    except Exception:  # noqa: BLE001
-        return user_tpl
-
-
-def _resolve(kind: str, image_url: str = "", ocr_text: str = "") -> tuple[str, str]:
-    now = time.time()
-    cache_key = f"prompt_{kind}"
-    with _cache_lock:
-        hit = _cache.get(cache_key)
-        if hit and now - hit[0] < _CACHE_TTL:
-            sys_prompt, usr_prompt = hit[1]
-            return sys_prompt, _render_user(usr_prompt, image_url, ocr_text)
-
-    default = _default_template()
-    sys_prompt = default["system_prompt"]
-    usr_prompt = default["user_prompt_template"]
-
-    tpl = _load_db_template()
-    if tpl is not None:
-        db_sys = (getattr(tpl, "system_prompt", "") or "").strip()
-        if db_sys:
-            sys_prompt = db_sys
-            db_usr = getattr(tpl, "user_prompt_template", "") or usr_prompt
-            usr_prompt = db_usr or usr_prompt
-            logger.info(
-                "[vision.v2] 使用DB image_analysis prompt version=%s",
-                getattr(tpl, "version", "?"),
-            )
-
-    with _cache_lock:
-        _cache[cache_key] = (now, (sys_prompt, usr_prompt))
-    return sys_prompt, _render_user(usr_prompt, image_url, ocr_text)
-
-
-def resolve_fast_prompt(image_url: str = "", ocr_text: str = "") -> tuple[str, str]:
-    return _resolve("fast", image_url, ocr_text)
-
-
-def resolve_pro_prompt(image_url: str = "", ocr_text: str = "") -> tuple[str, str]:
-    return _resolve("pro", image_url, ocr_text)
-
-
-def invalidate_cache() -> None:
-    with _cache_lock:
-        _cache.clear()

apps/worker/worker_app/tasks/vision/assembler.py

@@ -1,106 +0,0 @@
-"""V2 结果组装（v8 叙述优先，大幅精简）。
-
-设计原则：VLM 直接输出最终给用户看的 summary_markdown，assembler 只负责
-- 解析 fast JSON（兼容顶层 {"images":[...]} 与 {"products":[...]} 两种键）；
-- 补齐 5 个必备字段（type/name/brand/has_person/summary_markdown）；
-- summary_markdown 缺失（异常）时才拼一句最基础的兜底文字。
-
-正常情况下不改写、不“润色”VLM 输出，不做 brand 多级兜底，不处理任何
-colors/material/key_features 等细分字段。
-"""
-
-from __future__ import annotations
-
-import logging
-from typing import Any
-
-logger = logging.getLogger(__name__)
-
-_VALID_TYPES = ("store", "product", "person", "scene")
-
-
-def _coerce_bool(value: Any) -> bool:
-    if isinstance(value, bool):
-        return value
-    if isinstance(value, (int, float)):
-        return value != 0
-    if isinstance(value, str):
-        return value.strip().lower() in ("true", "1", "yes", "是")
-    return False
-
-
-def _basic_markdown(image: dict[str, Any]) -> str:
-    """异常兜底：VLM 没给 summary_markdown 时只拼一句基础文字。"""
-    name = (image.get("name") or "").strip() or "未识别"
-    brand = (image.get("brand") or "").strip()
-    typ = image.get("type") or "scene"
-    label = f"{brand}{name}" if brand and brand not in name else (brand or name)
-    if typ == "store":
-        return f"这是{label}的门店场景，画面细节识别不完整。"
-    if typ == "person":
-        return f"画面中的人物与{label}相关，细节识别不完整。"
-    if typ == "product":
-        return f"这是{label}的商品图片，具体外观细节识别不完整。"
-    return f"画面内容为{label}，细节识别不完整。"
-
-
-def _normalize_image(raw: Any, idx: int) -> dict[str, Any]:
-    """把一条 VLM 输出归一化为 5 字段 dict。"""
-    if not isinstance(raw, dict):
-        raw = {}
-
-    typ = str(raw.get("type") or "").strip().lower()
-    if typ not in _VALID_TYPES:
-        typ = "scene"
-
-    name = str(raw.get("name") or "").strip() or "未识别"
-    brand = str(raw.get("brand") or "").strip()
-    has_person = _coerce_bool(raw.get("has_person"))
-    if typ == "person" and not has_person:
-        # type=person 通常意味着主体是人，保持一致（仅异常补全）
-        has_person = True
-
-    summary = raw.get("summary_markdown")
-    summary = summary.strip() if isinstance(summary, str) else ""
-
-    image: dict[str, Any] = {
-        "type": typ,
-        "name": name,
-        "brand": brand,
-        "has_person": has_person,
-        "summary_markdown": summary,
-    }
-    if not summary:
-        image["summary_markdown"] = _basic_markdown(image)
-        image["_source"] = "summary_missing"
-        logger.info("[assembler] 图片 #%s 缺少 summary_markdown，使用基础兜底", idx)
-    return image
-
-
-def _extract_items(fast_json: Any) -> list[Any]:
-    """从 fast JSON 中取出图片条目：优先 images，兼容 products。"""
-    if not isinstance(fast_json, dict):
-        return []
-    items = fast_json.get("images")
-    if not isinstance(items, list):
-        items = fast_json.get("products")
-    return items if isinstance(items, list) else []
-
-
-def assemble_result(idx: int, fast_json: Any, ocr_texts: list[str] | None = None) -> dict[str, Any]:
-    """组装单张图片分析结果。
-
-    每次调用对应一张图片；fast_json 形如 {"images": [{...}]}（v8）。
-    返回单条 image dict（5 字段，必要时带 _source）。
-    """
-    items = _extract_items(fast_json)
-    if items:
-        image = _normalize_image(items[0], idx)
-    else:
-        # 极端异常：fast 无任何可用条目，OCR 文字可作为名称线索
-        ocr_hint = ""
-        if ocr_texts:
-            ocr_hint = "、".join(t for t in ocr_texts if t)[:40]
-        image = _normalize_image({"name": ocr_hint or "未识别", "summary_markdown": ""}, idx)
-        image["_source"] = "empty_fast_json"
-    return image

apps/worker/worker_app/tasks/vision/fast_path.py

@@ -1,124 +0,0 @@
-# -*- coding: utf-8 -*-
-"""V2 图片分析主路径（v8 叙述优先）：每图并行 OCR（火山 MediaKit，未配置自动跳过）
-+ fast VLM 强约束 JSON；失败时单次 pro VLM 兜底。
-
-架构：
-- 单图 2 路并行（OCR + fast VLM），外层 N 图全并发（workers=8）；
-- 兜底单次 pro VLM，无竞速/复杂重试；
-- 输出统一为 5 字段 image dict（type/name/brand/has_person/summary_markdown）。
-"""
-
-from __future__ import annotations
-
-import logging
-import os
-import time
-from concurrent.futures import ThreadPoolExecutor, as_completed
-from typing import Any
-
-from . import assembler, ocr_volc, vlm_fallback, vlm_fast_json
-
-logger = logging.getLogger(__name__)
-
-_IMG_WORKERS = int(os.environ.get("VISION_V2_IMG_WORKERS", "8"))
-_FAST_TIMEOUT = float(os.environ.get("VISION_V2_FAST_TIMEOUT", "20"))
-_FAST_JSON_TIMEOUT = float(os.environ.get("VISION_V2_FAST_JSON_TIMEOUT", "20"))
-_OCR_TIMEOUT = float(os.environ.get("VISION_V2_OCR_TIMEOUT", "6"))
-_PRO_TIMEOUT = float(os.environ.get("VISION_V2_PRO_TIMEOUT", "45"))
-
-
-def _is_usable(r: dict[str, Any] | None) -> bool:
-    if not isinstance(r, dict):
-        return False
-    return bool((r.get("summary_markdown") or "").strip())
-
-
-def _basic_failure(ocr_result: list[str], fast_elapsed: float, source: str) -> dict[str, Any]:
-    image = assembler.assemble_result(-1, {}, ocr_result)
-    image["_source"] = source
-    image["_fast_elapsed"] = round(fast_elapsed, 2)
-    return image
-
-
-def analyze_image_v2(idx: int, img_url: str) -> dict[str, Any]:
-    t0 = time.time()
-
-    fj_result: dict[str, Any] | None = None
-    ocr_result: list[str] = []
-    pool = ThreadPoolExecutor(max_workers=2)
-    f_fj = pool.submit(vlm_fast_json.call_fast_json, img_url, timeout=_FAST_JSON_TIMEOUT)
-    f_ocr = pool.submit(ocr_volc.call_ocr, img_url, timeout=_OCR_TIMEOUT)
-    try:
-        for fut in as_completed([f_fj, f_ocr], timeout=_FAST_TIMEOUT):
-            try:
-                res = fut.result(timeout=1)
-            except Exception as e:  # noqa: BLE001
-                logger.warning("[vision.v2] 图片 #%d 子任务异常: %s", idx, e)
-                continue
-            if fut is f_fj and isinstance(res, dict):
-                fj_result = res
-            elif fut is f_ocr and isinstance(res, list):
-                ocr_result = res
-    except TimeoutError:
-        for f in (f_fj, f_ocr):
-            if not f.done():
-                f.cancel()
-        logger.warning("[vision.v2] 图片 #%d fast路径超时(%.0fs)，走pro兜底", idx, _FAST_TIMEOUT)
-    finally:
-        fast_elapsed = time.time() - t0
-        pool.shutdown(wait=False)
-
-    if fj_result:
-        assembled = assembler.assemble_result(idx, fj_result, ocr_result)
-        if _is_usable(assembled):
-            assembled["_fast_elapsed"] = round(fast_elapsed, 2)
-            logger.info("[vision.v2] 图片 #%d fast命中 elapsed=%.2fs", idx, fast_elapsed)
-            return assembled
-
-    pro_result = vlm_fallback.call_pro_vlm(img_url, idx, ocr_hint=ocr_result, timeout=_PRO_TIMEOUT)
-    if _is_usable(pro_result):
-        pro_result["_fallback_used"] = True
-        pro_result["_fast_elapsed"] = round(fast_elapsed, 2)
-        logger.info("[vision.v2] 图片 #%d pro兜底命中 total=%.2fs", idx, time.time() - t0)
-        return pro_result
-
-    logger.warning("[vision.v2] 图片 #%d 全路径失败 elapsed=%.2fs", idx, time.time() - t0)
-    return _basic_failure(ocr_result, fast_elapsed, "v2_all_failed")
-
-
-def analyze_images_v2(img_urls: list[str]) -> list[dict[str, Any]]:
-    if not img_urls:
-        return []
-    workers = min(_IMG_WORKERS, len(img_urls), 16)
-    results: list[dict[str, Any] | None] = [None] * len(img_urls)
-
-    logger.info(
-        "[vision.v2] 开始图片分析 n=%d workers=%d fast_timeout=%.0fs pro_timeout=%.0fs",
-        len(img_urls),
-        workers,
-        _FAST_TIMEOUT,
-        _PRO_TIMEOUT,
-    )
-    t0 = time.time()
-    with ThreadPoolExecutor(max_workers=workers) as pool:
-        future_to_idx = {pool.submit(analyze_image_v2, idx, url): idx for idx, url in enumerate(img_urls)}
-        for fut in as_completed(future_to_idx):
-            idx = future_to_idx[fut]
-            try:
-                results[idx] = fut.result()
-            except Exception as e:  # noqa: BLE001
-                logger.warning("[vision.v2] 图片 #%d future异常: %s", idx, e, exc_info=True)
-                results[idx] = assembler.assemble_result(idx, {}, [])
-                results[idx]["_source"] = "v2_future_exception"  # type: ignore[index]
-
-    elapsed = time.time() - t0
-    succ = sum(1 for r in results if _is_usable(r))
-    fb = sum(1 for r in results if r and r.get("_fallback_used"))
-    logger.info(
-        "[vision.v2] 完成 n=%d usable=%d pro_fallback=%d elapsed=%.2fs",
-        len(img_urls),
-        succ,
-        fb,
-        elapsed,
-    )
-    return [r for r in results if r is not None]  # type: ignore[misc]

apps/worker/worker_app/tasks/vision/json_utils.py

@@ -1,138 +0,0 @@
-# -*- coding: utf-8 -*-
-"""VLM 返回文本的稳健 JSON 提取工具。
-
-背景：复杂门店图 VLM 输出经常被 max_tokens 截断（finish_reason=length），
-json.loads 失败后整个结果被丢弃，导致"未识别"。本工具提供：
-1. markdown 代码块剥离（含只开不闭的截断场景）
-2. 最外层 { } 切片
-3. 非法控制字符清理
-4. 直接 json.loads
-5. 截断 JSON 括号/引号栈补全修复
-6. 尾部逐字符截断重试（去除最后一个不完整 token 后修复）
-
-成功返回 dict；截断修复产物带 _partial=True 标记；彻底失败返回 None。
-"""
-
-from __future__ import annotations
-
-import json
-import logging
-import re
-
-logger = logging.getLogger(__name__)
-
-_CODE_FENCE_RE = re.compile(r"^```(?:json)?\s*\n?(.*?)\n?```\s*$", re.DOTALL)
-
-
-def _strip_code_fence(s: str) -> str:
-    s = s.strip()
-    m = _CODE_FENCE_RE.match(s)
-    if m:
-        return m.group(1).strip()
-    # 兼容开头 ```json 但结尾无 ```（截断场景）
-    if s.startswith("```"):
-        lines = s.split("\n")
-        if lines and lines[0].startswith("```"):
-            lines = lines[1:]
-        s = "\n".join(lines).strip()
-    return s
-
-
-def _repair_truncated_json(text: str) -> str:
-    """尝试补全被截断的JSON：维护 bracket/quote 栈，在末尾补闭合符。"""
-    stack: list[str] = []
-    in_string = False
-    escape = False
-    for ch in text:
-        if escape:
-            escape = False
-            continue
-        if ch == "\\" and in_string:
-            escape = True
-            continue
-        if ch == '"':
-            in_string = not in_string
-            continue
-        if in_string:
-            continue
-        if ch in "{[":
-            stack.append(ch)
-        elif ch == "}":
-            if stack and stack[-1] == "{":
-                stack.pop()
-        elif ch == "]":
-            if stack and stack[-1] == "[":
-                stack.pop()
-    repair = ""
-    if in_string:
-        repair += '"'
-    for opener in reversed(stack):
-        repair += "}" if opener == "{" else "]"
-    if repair:
-        logger.info(
-            "[json_utils] 截断JSON修复: 补全%d个闭合符 in_string=%s",
-            len(repair),
-            in_string,
-        )
-    return text + repair
-
-
-def _clean_invalid_chars(text: str) -> str:
-    """清理JSON中非法的控制字符（tab/newline 之外的 0x00-0x1f 段）。"""
-    return re.sub(r"[\x00-\x08\x0b\x0c\x0e-\x1f]", "", text)
-
-
-def extract_json_object(text: str) -> dict | None:
-    """从VLM返回文本中稳健提取JSON对象。
-
-    返回 dict 或 None。成功的 dict 可能带 _partial=True 标记，
-    表示原始文本被截断、经括号补全后得到的产物。
-    """
-    if not text or not isinstance(text, str):
-        return None
-    # 1. 剥离 markdown
-    text = _strip_code_fence(text)
-    # 2. 找最外层 { }
-    lpos = text.find("{")
-    if lpos < 0:
-        return None
-    rpos = text.rfind("}")
-    if rpos > lpos:
-        text = text[lpos : rpos + 1]
-    else:
-        # 截断场景：无任何闭合 }，取到末尾交给修复器
-        text = text[lpos:]
-    # 3. 清理非法控制字符
-    text = _clean_invalid_chars(text)
-    # 4. 直接 loads
-    try:
-        obj = json.loads(text)
-        return obj if isinstance(obj, dict) else None
-    except json.JSONDecodeError:
-        pass
-    # 5. 尝试截断修复
-    repaired = _repair_truncated_json(text)
-    try:
-        obj = json.loads(repaired)
-        if isinstance(obj, dict):
-            obj["_partial"] = True
-            return obj
-    except json.JSONDecodeError:
-        pass
-    # 6. 尾部逐字符截断重试（去除最后一个不完整 token）
-    for _ in range(50):
-        last_comma = repaired.rfind(",")
-        last_brace = max(repaired.rfind("}"), repaired.rfind("]"))
-        cut = max(last_comma, last_brace)
-        if cut < 10:
-            break
-        repaired = repaired[: cut + 1]
-        repaired = _repair_truncated_json(repaired)
-        try:
-            obj = json.loads(repaired)
-            if isinstance(obj, dict):
-                obj["_partial"] = True
-                return obj
-        except json.JSONDecodeError:
-            continue
-    return None

apps/worker/worker_app/tasks/vision/ocr_volc.py

@@ -1,109 +0,0 @@
-# -*- coding: utf-8 -*-
-"""火山引擎 AI MediaKit OCR（同步）调用封装。
-
-接口：POST {mediakit_base_url}/tools-sync/ocr
-鉴权：Bearer {mediakit_api_key}
-请求体：{"image_url": "<公网可访问URL>"}  （部分版本也支持 image_base64）
-响应：{"code":0,"data":{"texts":[{"text":"...","bbox":[x,y,w,h],...},...],...}}
-
-目标：识别商品包装/Logo/水印上的文字，作为 fast_json VLM 的补充。
-返回值：识别到的文本字符串列表（失败返回 []）。
-"""
-
-from __future__ import annotations
-
-import logging
-import time
-from typing import Any
-
-logger = logging.getLogger(__name__)
-
-DEFAULT_TIMEOUT = 8  # OCR 秒级返回，8s 绰绰有余
-
-
-def call_ocr(img_url: str, *, timeout: int = DEFAULT_TIMEOUT) -> list[str]:
-    """调用 MediaKit 同步 OCR，返回去重后的纯文本列表。
-
-    不做重试（外层降级逻辑负责）。失败/未配置返回空列表，不抛异常。
-    """
-    t0 = time.time()
-    try:
-        import httpx
-
-        from packages.shared.mediakit_client import get_mediakit_client
-
-        client = get_mediakit_client()
-        if not client.is_available:
-            logger.info("[vision.v2] mediakit 未配置，跳过 OCR")
-            return []
-
-        url = f"{client.base_url}/tools-sync/ocr"
-        headers = {
-            "Authorization": f"Bearer {client.api_key}",
-            "Content-Type": "application/json",
-        }
-        payload: dict[str, Any] = {"image_url": img_url}
-        # 部分文档版本用 image_base64，但公网 URL 场景下 image_url 最简
-        resp = httpx.post(url, headers=headers, json=payload, timeout=timeout)
-        elapsed = time.time() - t0
-        if resp.status_code != 200:
-            logger.warning(
-                "[vision.v2] OCR HTTP %d elapsed=%.1fs body=%s",
-                resp.status_code,
-                elapsed,
-                resp.text[:200],
-            )
-            return []
-        data = resp.json()
-        # 兼容几种可能的响应结构
-        code = data.get("code", data.get("status", 0))
-        if code not in (0, "OK", "success", 200):
-            logger.warning("[vision.v2] OCR 业务错误 code=%s elapsed=%.1fs resp=%s", code, elapsed, str(data)[:200])
-            return []
-        texts = _extract_texts(data)
-        # 去重 + 过滤空
-        seen: set[str] = set()
-        out: list[str] = []
-        for t in texts:
-            t = (t or "").strip()
-            if t and t not in seen and len(t) <= 100:  # 过滤过长的误识别
-                seen.add(t)
-                out.append(t)
-        logger.info("[vision.v2] OCR 完成 elapsed=%.1fs n=%d texts=%s", elapsed, len(out), out[:5])
-        return out
-    except Exception as e:
-        elapsed = time.time() - t0
-        logger.warning("[vision.v2] OCR 异常 elapsed=%.1fs err=%s", elapsed, e, exc_info=True)
-        return []
-
-
-def _extract_texts(data: dict) -> list[str]:
-    """从 OCR 响应中抽取文本，兼容多种结构。"""
-    out: list[str] = []
-    # 常见结构1: data.texts = [{"text": "..."}, ...]
-    d = data.get("data") or data
-    if isinstance(d, dict):
-        for key in ("texts", "lines", "words", "items", "result"):
-            items = d.get(key)
-            if isinstance(items, list):
-                for it in items:
-                    if isinstance(it, dict):
-                        txt = it.get("text") or it.get("content") or it.get("word")
-                        if txt:
-                            out.append(str(txt))
-                    elif isinstance(it, str):
-                        out.append(it)
-                break
-        # 结构2: data.text = "..."
-        if not out:
-            t = d.get("text")
-            if isinstance(t, str):
-                out.append(t)
-        # 结构3: data.ocr_text / data.content
-        if not out:
-            for key in ("ocr_text", "content", "raw_text"):
-                v = d.get(key)
-                if isinstance(v, str) and v.strip():
-                    out.append(v)
-                    break
-    return out

apps/worker/worker_app/tasks/vision/vlm_fallback.py

@@ -1,109 +0,0 @@
-# -*- coding: utf-8 -*-
-"""V2 兜底路径：vision client（fallback 变体）单图调用，走 v8 叙述优先 prompt。
-
-fast 超时/非 JSON/为空时单次调用；输出统一走 assembler.assemble_result 组装，
-与 fast 路径同为 5 字段 image dict。
-"""
-
-from __future__ import annotations
-
-import logging
-import time
-from typing import Any
-
-from . import _prompt, assembler
-
-logger = logging.getLogger(__name__)
-
-_DEFAULT_TIMEOUT = 45
-
-
-def call_pro_vlm(
-    img_url: str,
-    idx: int,
-    *,
-    ocr_hint: list[str] | None = None,
-    timeout: int = _DEFAULT_TIMEOUT,
-    max_tokens: int | None = None,
-) -> dict[str, Any] | None:
-    t0 = time.time()
-    ocr_text = "、".join(t for t in (ocr_hint or []) if t)[:200]
-
-    try:
-        from packages.shared.ai_router import ai_router
-
-        client = ai_router.get_vision_client("image_analysis", variant="fallback")
-        if not client or not client.is_available:
-            logger.warning("[vision.v2] pro vision client 不可用，跳过")
-            return None
-    except Exception as e:  # noqa: BLE001
-        logger.warning("[vision.v2] ai_router 获取失败: %s", e)
-        return None
-
-    system_prompt, user_prompt = _prompt.resolve_pro_prompt(img_url, ocr_text)
-
-    messages: list[dict[str, Any]] = [
-        {"role": "system", "content": system_prompt},
-        {
-            "role": "user",
-            "content": [
-                {"type": "image_url", "image_url": {"url": img_url}},
-                {"type": "text", "text": user_prompt},
-            ],
-        },
-    ]
-
-    try:
-        call_kwargs: dict[str, Any] = {
-            "messages": messages,
-            "images": None,
-            "temperature": 0.3,
-            "timeout": timeout,
-            "enable_thinking": False,
-            "response_format": {"type": "json_object"},
-            "max_tokens": max_tokens if max_tokens is not None else 4000,
-        }
-
-        from .json_utils import extract_json_object
-
-        obj = None
-        for _outer in range(2):
-            kw = dict(call_kwargs)
-            if _outer == 1:
-                kw.pop("response_format", None)
-                msgs2 = [dict(messages[0]), dict(messages[1])]
-                cont = [dict(c) for c in msgs2[1]["content"]]
-                cont[-1] = {
-                    "type": "text",
-                    "text": user_prompt + "\n严格只输出JSON对象，不要解释或markdown。",
-                }
-                msgs2[1] = {"role": "user", "content": cont}
-                kw["messages"] = msgs2
-            raw = client.vision_completion(**kw)
-            if not raw:
-                continue
-            obj = extract_json_object(raw)
-            if obj is not None:
-                break
-            logger.warning("[vision.v2] pro 非JSON(100字) outer=%s: %s", _outer, raw[:100])
-
-        elapsed = time.time() - t0
-        if obj is None:
-            logger.warning("[vision.v2] pro 两次均未得到JSON elapsed=%.1fs", elapsed)
-            return None
-        if obj.get("_partial"):
-            logger.warning("[vision.v2] pro 截断JSON(partial) elapsed=%.1fs", elapsed)
-
-        result = assembler.assemble_result(idx, obj, ocr_hint or [])
-        result["_source"] = "vlm_pro"
-        result["_fallback_used"] = True
-        logger.info("[vision.v2] pro 完成 model=%s elapsed=%.1fs", client.model, elapsed)
-        return result
-    except Exception as e:  # noqa: BLE001
-        logger.warning(
-            "[vision.v2] pro 异常 elapsed=%.1fs err=%s",
-            time.time() - t0,
-            e,
-            exc_info=True,
-        )
-        return None

apps/worker/worker_app/tasks/vision/vlm_fast_json.py

@@ -1,111 +0,0 @@
-# -*- coding: utf-8 -*-
-"""V2 快速路径：vision client（默认 image_analysis 能力）强约束 JSON-only 调用。
-
-要点：
-- 通过 ai_router.get_vision_client() 获取 client；
-- enable_thinking=False 关闭推理链，response_format=json_object 强约束 JSON；
-- system/user prompt 优先读后台模板（v8 叙述优先），DB 不可用时用 prompts.py 默认；
-- temperature=0.1（稳定输出 JSON）；两次尝试（第二次去 json_object 约束）。
-"""
-
-from __future__ import annotations
-
-import logging
-import time
-from typing import Any
-
-from . import _prompt
-
-logger = logging.getLogger(__name__)
-
-_DEFAULT_TIMEOUT = 20
-
-
-def call_fast_json(
-    img_url: str,
-    *,
-    timeout: int = _DEFAULT_TIMEOUT,
-    max_tokens: int | None = None,
-) -> dict[str, Any] | None:
-    t0 = time.time()
-
-    try:
-        from packages.shared.ai_router import ai_router
-
-        client = ai_router.get_vision_client("image_analysis", variant="primary")
-        if not client or not client.is_available:
-            logger.warning("[vision.v2] vision client 不可用，跳过 fast_json")
-            return None
-    except Exception as e:  # noqa: BLE001
-        logger.warning("[vision.v2] ai_router 获取失败: %s", e)
-        return None
-
-    system_prompt, user_prompt = _prompt.resolve_fast_prompt(img_url, "")
-
-    messages: list[dict[str, Any]] = [
-        {"role": "system", "content": system_prompt},
-        {
-            "role": "user",
-            "content": [
-                {"type": "image_url", "image_url": {"url": img_url}},
-                {"type": "text", "text": user_prompt},
-            ],
-        },
-    ]
-
-    try:
-        call_kwargs: dict[str, Any] = {
-            "messages": messages,
-            "images": None,
-            "temperature": 0.1,
-            "timeout": timeout,
-            "enable_thinking": False,
-            "response_format": {"type": "json_object"},
-        }
-        if max_tokens is not None:
-            call_kwargs["max_tokens"] = max_tokens
-
-        from .json_utils import extract_json_object
-
-        obj = None
-        for _outer in range(2):
-            kw = dict(call_kwargs)
-            if _outer == 1:
-                kw.pop("response_format", None)
-                msgs2 = [dict(messages[0]), dict(messages[1])]
-                cont = [dict(c) for c in msgs2[1]["content"]]
-                cont[-1] = {
-                    "type": "text",
-                    "text": user_prompt + "\n严格只输出JSON对象，不要解释或markdown。",
-                }
-                msgs2[1] = {"role": "user", "content": cont}
-                kw["messages"] = msgs2
-            raw = client.vision_completion(**kw)
-            if not raw:
-                continue
-            obj = extract_json_object(raw)
-            if obj is not None:
-                break
-            logger.warning("[vision.v2] fast_json 非JSON(100字) outer=%s: %s", _outer, raw[:100])
-
-        elapsed = time.time() - t0
-        if obj is None:
-            logger.warning("[vision.v2] fast_json 两次均未得到JSON elapsed=%.1fs", elapsed)
-            return None
-        if obj.get("_partial"):
-            logger.warning("[vision.v2] fast_json 截断JSON(partial) elapsed=%.1fs", elapsed)
-        logger.info(
-            "[vision.v2] fast_json 完成 model=%s elapsed=%.1fs type=%s",
-            client.model,
-            elapsed,
-            obj.get("type"),
-        )
-        return obj
-    except Exception as e:  # noqa: BLE001
-        logger.warning(
-            "[vision.v2] fast_json 异常 elapsed=%.1fs err=%s",
-            time.time() - t0,
-            e,
-            exc_info=True,
-        )
-        return None

deploy/configs/.env.staging

@@ -241,35 +241,19 @@ DOUBAO_API_KEY=${DOUBAO_API_KEY}
 
 # 模型 Endpoint ID（在 ARK 控制台创建推理接入点后获得）
 DOUBAO_MODEL=${DOUBAO_MODEL}
-DOUBAO_FAST_MODEL=${DOUBAO_FAST_MODEL}
 
 # API Base URL
 DOUBAO_BASE_URL=${DOUBAO_BASE_URL}
 
 # 请求超时（秒）
-DOUBAO_TIMEOUT=${DOUBAO_TIMEOUT}
+DOUBAO_TIMEOUT=60
 
 # 最大重试次数
-DOUBAO_MAX_RETRIES=${DOUBAO_MAX_RETRIES}
+DOUBAO_MAX_RETRIES=2
 
-# 视觉模型（支持图片/视频理解的模型，model name 格式）
+# 视觉模型 Endpoint ID（支持图片/视频理解的模型）
 DOUBAO_VISION_MODEL=${DOUBAO_VISION_MODEL}
 
-# 快速视觉模型（viral-video 图片分析 lite 路径）
-DOUBAO_VISION_LITE_MODEL=${DOUBAO_VISION_LITE_MODEL}
-
-# 是否启用 lite 视觉路径（true/false）
-DOUBAO_VISION_USE_LITE=${DOUBAO_VISION_USE_LITE}
-
-# 信任链文生图模型（Seedream）
-DOUBAO_IMAGE_MODEL=${DOUBAO_IMAGE_MODEL}
-
-# 文生图尺寸
-DOUBAO_IMAGE_SIZE=${DOUBAO_IMAGE_SIZE}
-
-# 文生图超时（秒）
-DOUBAO_IMAGE_TIMEOUT=${DOUBAO_IMAGE_TIMEOUT}
-
 
 # ==================== 微信开放平台 OAuth（网页扫码登录）====================
 # 回调域名：xiaoxiajianji.com（微信开放平台已配置）
@@ -311,10 +295,3 @@ GPU_ENCODE_CRF=23
 GPU_ENCODE_FALLBACK_CPU=true
 GPU_ENCODE_MEZZANINE_TRANSPORT=oss
 GPU_ENCODE_OSS_TMP_PREFIX=tmp/gpu-mezzanine/
-
-# ==================== Ditto 蚂蚁数字人口型 ====================
-# 注意：这些值必须写死在模板里（不是 CI Secret），否则每次 CI 重新渲染 .env 都会被丢弃，
-# 导致 staging 发版后 Ditto 口型服务静默降级到 GPU/MediaKit（P0 防复发）。
-USE_DITTO_LIPSYNC=true
-DITTO_API_BASE_URL=http://100.76.80.23:8000
-DITTO_DEFAULT_VIDEO_URL=https://xiaoxia-autocut.oss-cn-hangzhou.aliyuncs.com/uploads/default_avatar.mp4

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。

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 ──