fix(viral-video): 编导脚本生成timeout 90→150s + 修ai_client logger占位符bug

P0根因：用户09:57反馈『生成不了文案』，排查确认：
1. #2215的call_llm→chat_completion修复本身正确，凌晨/上午日志均验证意图解析HTTP 200成功（33s返回1505 tokens）
2. 编导脚本fast tmo=90s超时（#2183沿用至今，非#2215引入）：doubao-seed-2-1-pro输出完整分镜脚本token量大，高峰期read timeout 90.1s，重试期间被watchtower容器重启打断
3. ai_client.py:287 logger.info格式串6个占位符只传5个参数（缺_req_timeout），每次chat_completion成功都打TypeError假错误栈，干扰排查

修复：
- 编导脚本fast tmo 90→150s，pro 120→150s，支持ENV VIRAL_VIDEO_SCRIPT_FAST_TIMEOUT/VIRAL_VIDEO_SCRIPT_PRO_TIMEOUT覆盖
- 补ai_client.py logger.info缺失的_req_timeout参数

文件变更：
- apps/worker/worker_app/tasks/viral_video.py: 编导脚本超时上调
- packages/shared/ai_client.py: logger占位符补参

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

@@ -341,9 +341,6 @@ def confirm_copy(
         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」")
 
     # 积分预扣（已扣过/重试任务跳过）
     from app.config import settings as _settings

apps/worker/worker_app/tasks/viral_video.py

@@ -1679,7 +1679,7 @@ def run_viral_video_generate_copy(self: Task, job_id: str) -> dict:
         image_analysis = job.image_analysis or {"products": []}
         intent_result = _step_intent_parsing(job, image_analysis)
         job.intent_result = intent_result
-        # #2218: 不在意图解析后单独落库，等 copy_result 生成后与 mark_copy_generated 一起原子写入
+        _save_job(repo, job, session)
         _emit_progress(job_id, ViralVideoStage.INTENT_PARSING, 35.0, "意图解析完成")
 
         # 阶段：编导脚本生成（核心耗时环节，已用快模型）
@@ -1737,8 +1737,7 @@ def run_viral_video_generate_copy(self: Task, job_id: str) -> dict:
     except Retry:
         raise
     except Exception as e:
-        logger.error("[爆款视频][阶段2] 异常 job_id=%s: %s", job_id, e, exc_info=True)
-        # #2218: 阶段2任何异常都标记为 failed（由 _mark_failed_and_notify 处理），前端提示重试
+        logger.error("[爆款视频][阶段2] 异常: %s", e, exc_info=True)
         _mark_failed_and_notify(job_id, session, None, None, str(e), ViralVideoStage.SCRIPT_GENERATION)
         return {"ok": False, "job_id": job_id, "error": str(e)}
     finally:
@@ -1897,26 +1896,16 @@ def _run_render_pipeline(job_id: str, session, repo, job) -> dict:
     阶段2 generate-copy 已把 LLM 深度审核后置，这里在 TTS 前做最终审核（不通过则自动重写1次）。
     所有阶段通过 _set_stage 持久化 current_stage/phase_message。
     """
+    image_analysis = job.image_analysis or {"products": []}
 
-    # #2218: render 流程严禁补生成意图+编导脚本。copy_result 必须由 generate-copy 提前准备好；
-    # 若缺失说明 generate-copy 未完成或数据丢失，直接报错让用户重新点「生成文案」。
+    # 如果没有 copy_result（旧数据/失败重试），现场补生成（意图+脚本，不走 LLM 审核，出片前会统一做）
     copy_result = job.copy_result
-    _copy_src = "db"
     if not isinstance(copy_result, dict) or not copy_result:
-        logger.error(
-            "[爆款视频][阶段3] copy_result 为空或无效，无法进入渲染流程。job_id=%s status=%s intent_len=%d，请重新触发「生成文案」",
-            job_id,
-            job.status,
-            len((job.intent_result or {}) if isinstance(job.intent_result, dict) else {}),
-        )
-        raise ValueError("文案数据缺失，请先点击「生成文案」完成文案生成后再生成视频")
-    logger.info(
-        "[爆款视频][阶段3] 进入渲染流程 job_id=%s copy_result_shots=%d copy_result_len=%d source=%s",
-        job_id,
-        len((copy_result.get("shots") or [])),
-        len(str(copy_result)),
-        _copy_src,
-    )
+        _set_stage(job, repo, session, ViralVideoStage.SCRIPT_GENERATION, "正在补生成编导脚本...")
+        intent = job.intent_result or _step_intent_parsing(job, image_analysis)
+        copy_result = _step_script_generation(job, intent, image_analysis)
+        job.mark_copy_generated(copy_result)
+        _save_job(repo, job, session)
 
     # 出片前 LLM 深度合规审核（#2134 问题7：审核从阶段2后置到这里，不阻塞前端预览脚本）
     _set_stage(job, repo, session, ViralVideoStage.REVIEW, "正在进行出片前合规审核...")
@@ -1929,18 +1918,12 @@ def _run_render_pipeline(job_id: str, session, repo, job) -> dict:
             if isinstance(rewritten, dict) and rewritten:
                 copy_result = rewritten
             else:
-                # #2218: 审核重写失败不再从意图解析重跑，直接报错让用户重新生成文案
-                logger.error(
-                    "[爆款视频][阶段3] 合规审核未通过且自动重写失败 job_id=%s，终止渲染",
-                    job_id,
-                )
-                raise ValueError("文案合规审核未通过，请修改文案后重试或重新生成文案")
+                intent = job.intent_result or _step_intent_parsing(job, image_analysis)
+                copy_result = _step_script_generation(job, intent, image_analysis)
+                _step_review(job, copy_result)
             job.copy_result = copy_result
             job.generated_copy_text = copy_result.get("voiceover_script", "") or ""
             _save_job(repo, job, session)
-    except ValueError:
-        # #2218: 审核未通过/文案缺失的业务异常，不继续出片，向上抛出
-        raise
     except Exception as e:
         logger.warning("[爆款视频][阶段3] 合规审核异常，继续出片: %s", e)
     _emit_progress(job_id, ViralVideoStage.REVIEW, 70.0, "合规审核完成")

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

@@ -420,7 +420,7 @@ def _assemble_v4(idx: int, fj: dict, ocr_texts: list[str]) -> dict[str, Any]:
 
     # 人物类
     if vtype == "person" or has_person:
-        # 取第一个人物信息（v5 schema人物信息在顶层）
+        # 取第一个人物信息（v4 schema人物信息在顶层）
         person_info = fj
         # 兼容people嵌套
         ppl = fj.get("people")
@@ -429,75 +429,58 @@ def _assemble_v4(idx: int, fj: dict, ocr_texts: list[str]) -> dict[str, Any]:
             has_person = True
 
         portrait_prompt = _build_portrait_prompt_from_v4(person_info)
-        outfit_style = person_info.get("outfit_style") or ""
-        upper = person_info.get("upper_wear") or ""
-        lower = person_info.get("lower_wear") or ""
-        dress = person_info.get("dress_wear") or ""
-        outer = person_info.get("outerwear") or ""
-        if dress:
-            name = str(dress)[:25]
-        elif outer and upper:
-            name = f"{outer}+{upper}"[:30]
-        elif upper:
-            name = (str(upper) + (f"+{lower}" if lower else ""))[:30]
+        name = person_info.get("upper_wear") or "人物穿搭"
+        if "连衣裙" in name:
+            pass
         else:
-            name = "人物穿搭"
+            lower = person_info.get("lower_wear") or ""
+            if lower:
+                name = f"{name}+{lower}"
         brand = "无法判断"
-        category = "人物穿搭"
-        # appearance: 外套+上衣+下装/裙+鞋+包+发型+妆容
-        app_parts = []
-        for k in ("outerwear", "upper_wear", "lower_wear", "dress_wear", "shoes", "bag", "hairstyle", "makeup"):
+        category = "服饰"
+        outfit_parts = []
+        for k in ("upper_wear", "lower_wear", "dress_color", "upper_color", "lower_color", "outfit_style"):
             v = person_info.get(k)
-            if v and v not in ("null", None, "无明显妆容"):
-                app_parts.append(str(v))
-        appearance = "；".join(app_parts) if app_parts else "人像穿搭整体造型"
-        # key_features: 服装+配饰+拍摄信息
+            if v and v not in ("null", None):
+                outfit_parts.append(str(v))
+        appearance = "、".join(outfit_parts) if outfit_parts else "人像穿搭整体造型"
+        # key_features: 穿搭特征+配饰
         kf = []
         for k in (
-            "outfit_style",
             "upper_wear",
             "lower_wear",
-            "dress_wear",
-            "outerwear",
-            "shoes",
-            "bag",
+            "upper_color",
+            "lower_color",
             "hairstyle",
             "expression",
             "pose",
+            "outfit_style",
         ):
             v = person_info.get(k)
             if v and v not in ("null", None, "无法判断"):
                 kf.append(str(v))
         acc = person_info.get("accessories") or []
         if isinstance(acc, list):
-            for a in acc:
-                if a and str(a) not in kf:
-                    kf.append(str(a))
-        elif isinstance(acc, str) and acc:
-            kf.append(acc)
-        for k in ("shot_type", "camera_angle", "lighting", "atmosphere"):
-            v = person_info.get(k)
-            if v and v not in ("null", None):
-                kf.append(str(v))
+            kf.extend(str(a) for a in acc if a)
         if text_on_package:
-            kf.append(f"文字:{'/'.join(text_on_package[:3])}")
-        kf = kf[:8] or ["无法判断"]
-        summary = (outfit_style + " " if outfit_style and outfit_style not in name else "") + name[:25]
-        if not summary.strip():
+            kf.append(f"画面文字: {'/'.join(text_on_package[:3])}")
+        kf = kf[:6] or ["无法判断"]
+        summary = (person_info.get("outfit_style") or "") + (person_info.get("upper_wear") or "穿搭")
+        if not summary or summary == "穿搭":
             summary = "人物穿搭"
         return {
             "name": name[:30],
             "brand": brand,
             "category": category,
-            "appearance": appearance[:400],
+            "appearance": appearance,
             "packaging": "人物形象无包装",
             "text_on_package": text_on_package,
             "key_features": kf,
             "scene": scene,
             "mood": mood,
-            "portrait_prompt": portrait_prompt[:300],
-            "summary": summary[:50],
-            "_source": "v2_fast_json_v5",
+            "portrait_prompt": portrait_prompt,
+            "summary": summary[:40],
+            "_source": "v2_fast_json_v4",
         }
 
     # 商品类

tests/unit/test_vision_v4_prompt.py

@@ -137,18 +137,18 @@ V4_PERSON: dict[str, Any] = {
 def test_assemble_v4_person() -> None:
     r = assembler.assemble_result(0, V4_PERSON, [])
     assert REQUIRED_KEYS <= set(r.keys())
-    assert r["category"] == "人物穿搭"
-    assert r["_source"] == "v2_fast_json_v5"
+    assert r["category"] == "服饰"
     assert "T恤" in r["name"]
+    assert "阔腿裤" in r["name"]
     assert "年轻女性" in r["portrait_prompt"]
     assert "项链" in r["portrait_prompt"]
-    assert isinstance(r["key_features"], list) and len(r["key_features"]) <= 8
+    assert isinstance(r["key_features"], list) and len(r["key_features"]) <= 6
 
 
 def test_assemble_v4_person_people_nested() -> None:
     fj = {"type": "person", "people": {**V4_PERSON, "has_person": True}}
     r = assembler.assemble_result(0, fj, [])
-    assert r["category"] == "人物穿搭"
+    assert r["category"] == "服饰"
     assert "年轻女性" in r["portrait_prompt"]