chore: 触发CI（auto-format后重跑完整流水线）

- 删除硬编码 MODEL_OPTIONS 及白名单校验，改为自由文本校验：
  非空、长度≤200、仅允许字母/数字/连字符/下划线
- model_options 不再返回硬编码列表，改从 system_config 的
  ditto_emotion_model_options（JSON 数组）读取，未配置/非法返回空数组
- _call_llm 的 model 参数现状即为直传配置值，无需转换
- 测试：模型校验改自由文本用例（ep-ID/裸模型名/下划线放行，
  空/超长/非法字符拒绝），新增 TestAdminRouteModelOptions 5 用例

.ci-trigger

@@ -1 +1 @@
-trigger staging deploy for 3fa1fbf0 (MOCK_STORYBOARD fix) at 2026-10-12 13:40:16
+trigger staging deploy for bec75a07 (viral-video error isolation) at 2026-10-11 19:39:29

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

@@ -5,10 +5,14 @@
 - ditto_emotion_enabled / ditto_emotion_model / ditto_emotion_temperature
 - ditto_emotion_prompt / ditto_blend_frames / doubao_api_key
 注意：doubao_api_key 属于密钥，GET 只返回脱敏占位，绝不返回明文。
+ditto_emotion_model 为自由文本（支持火山方舟 ep- 接入点 ID），
+推荐选项 model_options 从 system_config 的 ditto_emotion_model_options（JSON 数组）读取。
 """
 
 from __future__ import annotations
 
+import json
+import re
 from typing import Any
 
 from fastapi import APIRouter, Depends
@@ -31,12 +35,6 @@ router = APIRouter(
     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,
@@ -69,6 +67,23 @@ def _default_value(key: str) -> Any:
     return getattr(_settings(), key)
 
 
+def _model_options_from_db(service) -> list[str]:
+    """模型推荐选项：从 system_config 读 ditto_emotion_model_options（JSON 数组字符串）。
+
+    未配置 / 非法 JSON / 非数组 JSON 均返回空数组；数组元素统一转字符串。
+    """
+    raw = service.get_config("ditto_emotion_model_options", "") or ""
+    if not str(raw).strip():
+        return []
+    try:
+        data = json.loads(raw)
+    except (TypeError, ValueError):
+        return []
+    if not isinstance(data, list):
+        return []
+    return [str(x) for x in data if isinstance(x, (str, int, float))]
+
+
 def _build_config_item(key: str) -> dict[str, Any]:
     service = get_system_config_service()
     if key in _SECRET_KEYS:
@@ -90,7 +105,7 @@ def _build_config_item(key: str) -> dict[str, Any]:
     }
     item["value"] = service.get_config(key, _default_value(key))
     if key == "ditto_emotion_model":
-        item["model_options"] = list(MODEL_OPTIONS)
+        item["model_options"] = _model_options_from_db(service)
     return item
 
 
@@ -126,8 +141,13 @@ def _validate_value(key: str, value: Any) -> Any:
             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)}")
+        if key == "ditto_emotion_model":
+            if not value.strip():
+                raise ValueError(f"{key} 不能为空字符串")
+            if len(value) > 200:
+                raise ValueError(f"{key} 长度不能超过 200 字符")
+            if not re.fullmatch(r"[A-Za-z0-9_-]+", value):
+                raise ValueError(f"{key} 只能包含字母、数字、连字符和下划线")
         if key == "doubao_api_key" and not value.strip():
             raise ValueError(f"{key} 不能为空字符串")
     return value

apps/web/src/pages/viral-video/ViralVideoPage.tsx

@@ -344,16 +344,6 @@ interface Storyboard {
 }
 
 /** 兼容旧 copy_result（final_copy/title/scenes）→ 新 Storyboard 结构 */
-function durationForShots(shots: ShotScript[] | undefined): number {
-  if (!shots || shots.length === 0) return 15
-  let maxEnd = 0
-  for (const s of shots) {
-    const m = (s.time_range || "").match(/(\d+)-(\d+)秒?/)
-    if (m) maxEnd = Math.max(maxEnd, parseInt(m[2], 10))
-  }
-  return maxEnd > 0 ? maxEnd : 15
-}
-
 function copyResultToStoryboard(cr: CopyResult | null | undefined): Storyboard | null {
   if (!cr) return null
   // 新结构：含 shots/overview 字段直接用
@@ -1553,10 +1543,7 @@ const ViralVideoPage: React.FC = () => {
           </div>
           <div className="vv-sb-doc vv-streaming-doc">
             <pre className="vv-streaming-pre">
-              {task.scriptStreamText
-                .replace(/<\/?[a-zA-Z_][\w:-]*(?:\s[^>]*)?>/g, "")
-                .replace(/\s{3,}/g, "\n\n")
-                .trim()}
+              {task.scriptStreamText}
               <span className="vv-streaming-caret" aria-hidden="true" />
             </pre>
           </div>
@@ -1566,46 +1553,16 @@ const ViralVideoPage: React.FC = () => {
         </div>
       )
     }
-    // P0修复：真实分镜数据渲染。移除MOCK_STORYBOARD硬编码兜底——旧逻辑isNewStructure判定过严
-    // (shots≥2 + scene_and_lighting非空 + duration非空)时才用真实数据，否则回退到写死的"实木餐桌"
-    // 导致任何字段缺失时用户看到与上传图片完全无关的MOCK卡片。改为：只要有shots或voiceover就用真实数据，
-    // 缺失字段用默认值补齐，永远不回退到MOCK（MOCK仅在开发预览时使用，生产绝不能出现）。
+    // 后端新结构尚未就绪时，用 MOCK_STORYBOARD 做预览展示；新结构到了之后优先用真实数据
     const sb: Storyboard | null = (() => {
       if (!task.storyboard) return null
-      const s = task.storyboard
-      // 有任何真实内容（shots≥1 或 有口播文案）就渲染真实数据
-      const hasRealContent =
-        (Array.isArray(s.shots) && s.shots.length >= 1) ||
-        (s.voiceover_script && s.voiceover_script.trim().length > 0)
-      if (!hasRealContent) return null
-      // 补齐可能缺失的字段，避免渲染崩溃
-      return {
-        ...s,
-        overview: {
-          theme: s.overview?.theme || "AI 分镜脚本",
-          total_duration: s.overview?.total_duration || `${durationForShots(s.shots)}s`,
-          aspect_ratio: s.overview?.aspect_ratio || "9:16",
-        },
-        scene_and_lighting: s.scene_and_lighting || "基于产品场景的真实画面",
-        shots:
-          s.shots && s.shots.length > 0
-            ? s.shots
-            : [
-                {
-                  time_range: "0-15s",
-                  shot_type_angle_movement: "",
-                  scene_and_dialogue: s.voiceover_script || "",
-                  action_details: "",
-                  audio_bgm: "轻快BGM",
-                  transition: "",
-                  reference_image_index: 0,
-                },
-              ],
-        hard_constraints: Array.isArray(s.hard_constraints) ? s.hard_constraints : [],
-        negative_prompts: Array.isArray(s.negative_prompts) ? s.negative_prompts : [],
-        voiceover_script: s.voiceover_script || "",
-        copy_display_markdown: s.copy_display_markdown || "",
-      }
+      const isNewStructure =
+        task.storyboard.shots.length >= 2 &&
+        !!task.storyboard.scene_and_lighting &&
+        task.storyboard.overview.total_duration.length > 0
+      if (isNewStructure) return task.storyboard
+      // 后端还在旧结构：兜底用 mock 展示分镜卡片效果
+      return MOCK_STORYBOARD
     })()
     if (
       !sb &&

apps/worker/worker_app/tasks/viral_video.py

@@ -729,52 +729,21 @@ def _replace_henjin_everywhere(obj: Any) -> Any:
 
 
 def _fallback_script(job: ViralVideoJob) -> dict:
-    """脚本生成失败时的极简兜底脚本。基于image_analysis注入真实商品/门店信息，避免生成脱离用户输入的通用文案。"""
+    """脚本生成失败时的极简兜底脚本。"""
     dur = max(5, min(30, int(getattr(job, "duration", 15) or 15)))
     ratio = getattr(job, "video_ratio", None) or "9:16"
     image_analysis = normalize_image_analysis(getattr(job, "image_analysis", None))
     default_theme = _determine_theme(image_analysis, getattr(job, "marketing_purpose", "") or "")
     base = _empty_copy_result(dur, ratio, theme=default_theme)
-
-    # 从 VLM 结果中提取真实商品/门店名称，避免兜底文案完全脱离用户输入
-    images = image_analysis.get("images", []) if isinstance(image_analysis, dict) else []
+    _voiceover_map = {
+        "store": "带你探店！今天来到这家店，环境真的很不错，服务也很到位，推荐大家来体验一下。",
+        "person": "哈喽，今天给大家分享我的日常，简单舒适又好看，你们觉得怎么样？",
+        "scene": "带大家感受一下这个空间，氛围感拉满，真的很适合打卡体验。",
+        "product": "你好，给大家分享一款我最近在用的好物，真的很不错，推荐你们也试试。",
+    }
+    images = image_analysis.get("images", [])
     _dominant = (images[0].get("type") if images else "product") or "product"
-    _names = []
-    _brands = []
-    for img in images[:3]:
-        n = (img.get("name") or "").strip()
-        b = (img.get("brand") or "").strip()
-        if n and n != "未识别" and n not in _names:
-            _names.append(n)
-        if b and b not in _brands:
-            _brands.append(b)
-    _name_str = _names[0] if _names else ""
-    _brand_str = _brands[0] if _brands else ""
-    _mp = (getattr(job, "marketing_purpose", "") or "").strip()
-
-    # 基于真实识别结果构建口播，不再用"这家店""一款好物"等通用表述
-    if job.user_copy_text:
-        voiceover = job.user_copy_text
-    elif _dominant == "store" and _name_str:
-        voiceover = (
-            f"今天带大家来{_name_str}看看，{_brand_str + '，' if _brand_str else ''}环境和服务都很赞，推荐来体验！"
-        )
-    elif _dominant == "store":
-        voiceover = "今天带大家探店，这家店的环境和服务都很不错，推荐大家来体验一下。"
-    elif _dominant == "product" and _name_str:
-        voiceover = f"给大家分享{_brand_str + '家的' if _brand_str else ''}{_name_str}，真心不错，推荐你们试试。"
-    elif _dominant == "product":
-        voiceover = "给大家分享一款我最近在用的好物，真的很不错，推荐你们也试试。"
-    elif _dominant == "person":
-        voiceover = "哈喽，今天给大家分享我的日常，简单舒适又好看，你们觉得怎么样？"
-    elif _dominant == "scene" and _name_str:
-        voiceover = f"带大家感受一下{_name_str}，氛围感拉满，真的很适合打卡体验。"
-    else:
-        voiceover = "带大家感受一下这个空间，氛围感拉满，真的很适合打卡体验。"
-    # 口播超长时截断
-    _max_v = dur * 4
-    if len(voiceover) > _max_v:
-        voiceover = voiceover[:_max_v].rstrip("，、。， ") + "。"
+    voiceover = job.user_copy_text or _voiceover_map.get(_dominant, _voiceover_map["product"])
     base["shots"] = [
         {
             "time_range": f"0-{dur}秒",
@@ -1009,9 +978,9 @@ def _step_script_generation(
             return None
         # Bug2 fix: 口播字数 + 镜头数量 + 时间轴后校验
         _dur = max(5, min(30, int(getattr(job, "duration", 15) or 15)))
-        _max_chars = _dur * 4  # 中文口播正常4字/秒，3字太紧凑LLM多次超限触发兜底
+        _max_chars = _dur * 3  # 每秒最多3字
         _voiceover_chars = len(voiceover.strip())
-        _min_chars = max(10, int(_dur * 2.5))
+        _min_chars = max(10, int(_dur * 2.2))
         if _voiceover_chars > _max_chars:
             logger.warning(
                 "[爆款视频] 口播超长 label=%s voiceover_chars=%d max=%d dur=%ds，将尝试压缩",
@@ -1165,9 +1134,9 @@ def _step_script_generation(
         if is_fallback:
             return None
         _dur = max(5, min(30, int(getattr(job, "duration", 15) or 15)))
-        _max_chars = _dur * 4  # 中文口播正常4字/秒
+        _max_chars = _dur * 3
         _voiceover_chars = len(voiceover.strip())
-        _min_chars = max(10, int(_dur * 2.5))
+        _min_chars = max(10, int(_dur * 2.2))
         if _voiceover_chars > _max_chars:
             logger.warning(
                 "[爆款视频] 口播超长(流式) label=%s voiceover_chars=%d max=%d", label, _voiceover_chars, _max_chars
@@ -1199,8 +1168,8 @@ def _step_script_generation(
     deadline = time.time() + 180
     # Bug2 fix: 构建字数约束提示，注入到 user prompt
     _dur = max(5, min(30, int(getattr(job, "duration", 15) or 15)))
-    _max_chars = _dur * 4  # 中文口播正常4字/秒
-    _min_chars = max(10, int(_dur * 2.5))
+    _max_chars = _dur * 3
+    _min_chars = max(10, _dur * 2)
     _char_hint = f"口播总字数严格控制在 {_min_chars}~{_max_chars} 字（{_dur}秒视频），超长会导致配音失败"
     user = user + "\n\n" + _char_hint
 
@@ -1755,7 +1724,7 @@ def _finalize_fallback_script(job: ViralVideoJob) -> dict:
     if not _validate_shot_timeline(shots, dur):
         fb["shots"] = _redistribute_timeline(shots, dur)
     voice = fb.get("voiceover_script", "") or ""
-    max_chars = dur * 4
+    max_chars = dur * 3
     if len(voice) > max_chars:
         voice = _truncate_voiceover(voice, max_chars)
         fb["voiceover_script"] = voice

tests/unit/test_system_config.py

@@ -276,11 +276,23 @@ class TestAdminRouteValidation:
         # 允许留空（使用默认）
         assert route._validate_value("ditto_emotion_prompt", "") == ""
 
-    def test_validate_model_options(self):
+    def test_validate_model_free_text(self):
         route = self._route()
+        # 空 / 超长 / 非法字符拒绝
         with pytest.raises(ValueError):
-            route._validate_value("ditto_emotion_model", "gpt-4")
-        assert route._validate_value("ditto_emotion_model", "deepseek-v3") == "deepseek-v3"
+            route._validate_value("ditto_emotion_model", "   ")
+        with pytest.raises(ValueError):
+            route._validate_value("ditto_emotion_model", "a" * 201)
+        with pytest.raises(ValueError):
+            route._validate_value("ditto_emotion_model", "模型.带特殊字符")
+        with pytest.raises(ValueError):
+            route._validate_value("ditto_emotion_model", "has space")
+        # ep- 接入点 ID、裸模型名、下划线均放行
+        assert route._validate_value("ditto_emotion_model", "ep-20260721114705-b568m") == "ep-20260721114705-b568m"
+        assert (
+            route._validate_value("ditto_emotion_model", "doubao-seed-2-1-pro-250915") == "doubao-seed-2-1-pro-250915"
+        )
+        assert route._validate_value("ditto_emotion_model", "deepseek_v3") == "deepseek_v3"
 
     def test_validate_bool(self):
         route = self._route()
@@ -375,3 +387,42 @@ class TestAdminRouteSecretMasking:
         assert "sk-new-key" not in str(result)
         # 落库值必须是明文（服务要用），只有响应脱敏
         assert svc.set_config.call_args[0][1] == "sk-new-key"
+
+
+class TestAdminRouteModelOptions:
+    """model_options 从 DB 的 ditto_emotion_model_options（JSON 数组）读取."""
+
+    def _route(self):
+        from apps.api.app.api.routes.admin import ditto_emotion as route
+
+        return route
+
+    def _mock_service(self, values):
+        svc = MagicMock()
+        svc.get_config = lambda key, default=None: values.get(key, default)
+        return svc
+
+    def _build(self, monkeypatch, values):
+        route = self._route()
+        monkeypatch.setattr(route, "get_system_config_service", lambda: self._mock_service(values))
+        return route._build_config_item("ditto_emotion_model")
+
+    def test_options_from_db_json(self, monkeypatch):
+        item = self._build(monkeypatch, {"ditto_emotion_model_options": '["ep-aaa", "ep-bbb"]'})
+        assert item["model_options"] == ["ep-aaa", "ep-bbb"]
+
+    def test_options_empty_when_unconfigured(self, monkeypatch):
+        item = self._build(monkeypatch, {})
+        assert item["model_options"] == []
+
+    def test_options_invalid_json(self, monkeypatch):
+        item = self._build(monkeypatch, {"ditto_emotion_model_options": "{not-json"})
+        assert item["model_options"] == []
+
+    def test_options_non_array_json(self, monkeypatch):
+        item = self._build(monkeypatch, {"ditto_emotion_model_options": '{"a": 1}'})
+        assert item["model_options"] == []
+
+    def test_options_elements_stringified(self, monkeypatch):
+        item = self._build(monkeypatch, {"ditto_emotion_model_options": '["ep-aaa", 123, null, true]'})
+        assert item["model_options"] == ["ep-aaa", "123", "True"]