From fb10393f3df1881d091e90475e19e1b77c8ba92e Mon Sep 17 00:00:00 2001
From: xiaoxia-saas-bot <bot@xiaoxiajianji.com>
Date: Sun, 4 Oct 2026 19:24:00 +0800
Subject: [PATCH] =?UTF-8?q?fix(viral=5Fvideo):=20#2040=20rebase=20?=
 =?UTF-8?q?=E5=90=8E=E6=B8=85=E7=90=86F841=E6=AD=BB=E4=BB=A3=E7=A0=81+?=
 =?UTF-8?q?=E4=BF=9D=E7=95=99#2180=20timeout=E4=BF=AE=E5=A4=8D?=
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- 删除 script_generation 中旧prompt遗留的未使用变量(style_hint/ratio/viral_structure_block/persona_hint)
- 冲突解决保留 #2180 全部修复: VLM/LLM timeout 15/25→45, pro 25→60, max_retries 2→1
- black/isort/ruff 全绿；viral 相关71测试全过
---
 apps/worker/worker_app/tasks/viral_video.py | 193 +++++++++++++++-----
 1 file changed, 145 insertions(+), 48 deletions(-)

diff --git a/apps/worker/worker_app/tasks/viral_video.py b/apps/worker/worker_app/tasks/viral_video.py
index 4e7c572b7..54dbc16ae 100644
--- a/apps/worker/worker_app/tasks/viral_video.py
+++ b/apps/worker/worker_app/tasks/viral_video.py
@@ -50,6 +50,7 @@ logger = logging.getLogger(__name__)
 
 # ── WS 进度推送 ──────────────────────────────────────────────────────────
 
+
 def _emit_progress(
     job_id: str,
     stage: str,
@@ -75,18 +76,22 @@ def _emit_progress(
     except Exception as e:
         logger.warning("[爆款视频] WS 进度推送失败: %s", e)
 
+
 # ── 仓储辅助 ────────────────────────────────────────────────────────────
 
+
 def _get_repo_and_job(job_id: str):
     session = SessionLocal()
     repo = SQLAlchemyViralVideoJobRepository(session)
     job = repo.get(job_id)
     return session, repo, job
 
+
 def _save_job(repo, job, session):
     repo.update(job)
     session.commit()
 
+
 def _start_trust_chain_preheat(job_id: str, portrait_descriptions: list[str]) -> None:
     """#2172/#2174 后台启动信任链预热（Seedream t2i 文生图人像），不阻塞调用方。
 
@@ -152,6 +157,7 @@ def _start_trust_chain_preheat(job_id: str, portrait_descriptions: list[str]) ->
     t = threading.Thread(target=_run_preheat, name=f"tc-preheat-{job_id[:8]}", daemon=True)
     t.start()
 
+
 def _set_stage(job, repo, session, stage: str, message: str, persist: bool = True) -> None:
     """更新细粒度阶段并持久化到 DB，同时通过 Redis 推送进度事件。
 
@@ -167,6 +173,7 @@ def _set_stage(job, repo, session, stage: str, message: str, persist: bool = Tru
         except Exception as e:  # 阶段持久化失败不阻塞主流程
             logger.warning("[爆款视频] 阶段持久化失败 stage=%s err=%s", stage, e)
 
+
 # ── worker 心跳（僵尸任务检测） ─────────────────────────────────────────
 
 # 心跳间隔（秒）；超过此时间未更新 heartbeat_at 视为 worker 异常
@@ -176,6 +183,7 @@ _STALE_RUNNING_TIMEOUT_SEC = 10 * 60  # 10 分钟
 # 心跳过期窗口：heartbeat_at 距 now 超过此时长视为失效
 _HEARTBEAT_EXPIRE_SEC = 2 * 60  # 2 分钟
 
+
 def _heartbeat_once(job_id: str) -> None:
     """在独立 session 中更新一次 heartbeat_at（不捕获主流程事务状态）。"""
     ssn = None
@@ -200,6 +208,7 @@ def _heartbeat_once(job_id: str) -> None:
             except Exception:
                 pass
 
+
 def _start_heartbeat_thread(job_id: str) -> tuple[threading.Event, threading.Thread]:
     """启动后台心跳线程，每 _HEARTBEAT_INTERVAL_SEC 秒更新一次 heartbeat_at。
     返回 (stop_event, thread)；任务结束时调用 stop_event.set() 停止心跳。
@@ -216,6 +225,7 @@ def _start_heartbeat_thread(job_id: str) -> tuple[threading.Event, threading.Thr
     t.start()
     return stop, t
 
+
 def _recover_stale_jobs() -> int:
     """启动/定时扫描：把僵尸任务（running 超时且心跳停止）标记为 failed。
     返回本次回收的任务数。可由 celery beat 周期性调用，也可在任务启动前顺带扫一次。
@@ -253,6 +263,7 @@ def _recover_stale_jobs() -> int:
             except Exception:
                 pass
 
+
 # ── 默认结构 ─────────────────────────────────────────────────────────────
 
 _DEFAULT_HARD_CONSTRAINTS = [
@@ -283,6 +294,7 @@ _DEFAULT_NEGATIVE_PROMPTS = [
     "低分辨率",
 ]
 
+
 def _empty_copy_result(duration: int = 15, ratio: str = "9:16") -> dict:
     return {
         "overview": {"theme": "好物推荐", "total_duration": duration, "aspect_ratio": ratio},
@@ -296,8 +308,10 @@ def _empty_copy_result(duration: int = 15, ratio: str = "9:16") -> dict:
         "title": "",
     }
 
+
 # ── 流水线各步骤 ────────────────────────────────────────────────────────
 
+
 def _vision_fallback(idx: int, reason: str, extra: dict | None = None) -> dict:
     d = {
         "name": "未识别",
@@ -315,6 +329,7 @@ def _vision_fallback(idx: int, reason: str, extra: dict | None = None) -> dict:
         d.update(extra)
     return d
 
+
 def _is_vision_result_usable(result: dict) -> bool:
     """判断 VLM 返回是否有效：name/summary 不能为未识别/无法判断/空，summary 要够长。"""
     if not isinstance(result, dict):
@@ -333,6 +348,7 @@ def _is_vision_result_usable(result: dict) -> bool:
         return False
     return True
 
+
 def _analyze_single_image(
     idx: int,
     img_url: str,
@@ -346,11 +362,13 @@ def _analyze_single_image(
     lite 失败/不可用时用 pro 降级重试 1 次。失败/None 最终返回含默认字段的 dict。
     """
     try:
-        from packages.shared.ai_service import call_vision
-        from packages.application.viral_video.prompt_loader import (
-            get_template, render_system_prompt, render_user_prompt,
-        )
         from packages.application.viral_video import xml_parser as xp
+        from packages.application.viral_video.prompt_loader import (
+            get_template,
+            render_system_prompt,
+            render_user_prompt,
+        )
+        from packages.shared.ai_service import call_vision
     except ImportError as e:
         logger.warning("[爆款视频] prompt 模板/解析模块不可用: %s", e)
         return _vision_fallback(idx, f"fallback_import_error:{e}")
@@ -361,15 +379,21 @@ def _analyze_single_image(
     template = get_template("image_analysis")
     system = render_system_prompt(template)
     user = render_user_prompt(
-        template, image_count=1, industry="通用",
+        template,
+        image_count=1,
+        industry="通用",
         image_urls=f"第1张：{img_url}",
     )
 
     def _call(model: str, tmo: int):
         try:
             return call_vision(
-                image_url=img_url, prompt=user, model=model,
-                max_tokens=2048, temperature=0.3, timeout=tmo,
+                image_url=img_url,
+                prompt=user,
+                model=model,
+                max_tokens=2048,
+                temperature=0.3,
+                timeout=tmo,
                 system_prompt=system,
             )
         except Exception as e:
@@ -396,13 +420,18 @@ def _analyze_single_image(
             packaging = a.get("packaging", "") or "无法判断"
             summary = a.get("summary", "") or f"{brand} {name}"
             return {
-                "name": name, "brand": brand, "category": category,
-                "appearance": appearance, "packaging": packaging,
+                "name": name,
+                "brand": brand,
+                "category": category,
+                "appearance": appearance,
+                "packaging": packaging,
                 "text_on_package": text_list,
                 "key_features": feat_list or [features] if features else ["无法判断"],
-                "scene": scene, "mood": mood,
+                "scene": scene,
+                "mood": mood,
                 "portrait_prompt": a.get("portrait_prompt", "无人像"),
-                "summary": summary, "_source": "xml",
+                "summary": summary,
+                "_source": "xml",
             }
         return _vision_fallback(idx, "no_product_tag")
 
@@ -435,6 +464,7 @@ def _analyze_single_image(
         return pro_result
     return first_result
 
+
 def _step_image_analysis(job: ViralVideoJob) -> dict:
     """步骤 1: 图片 VLM 分析 — 识别产品特征（v1.6 优化：并行 + lite 模型提速）。"""
     try:
@@ -490,6 +520,7 @@ def _step_image_analysis(job: ViralVideoJob) -> dict:
 
     return {"products": results}
 
+
 def _step_video_analysis(job: ViralVideoJob) -> dict | None:
     """步骤 1.5: 参考视频风格分析（可选）。"""
     if not job.reference_video_url:
@@ -513,14 +544,17 @@ def _step_video_analysis(job: ViralVideoJob) -> dict | None:
         logger.error("[爆款视频] 视频风格分析失败: %s", e)
         return {"error": str(e), "source": "failed"}
 
+
 def _step_intent_parsing(job: ViralVideoJob, image_analysis: dict) -> dict:
     """步骤 2: 用户文案意图解析（#2040：改为模板 + XML 解析）。"""
     try:
-        from packages.shared.ai_service import call_llm
-        from packages.application.viral_video.prompt_loader import (
-            get_template, render_system_prompt, render_user_prompt,
-        )
         from packages.application.viral_video import xml_parser as xp
+        from packages.application.viral_video.prompt_loader import (
+            get_template,
+            render_system_prompt,
+            render_user_prompt,
+        )
+        from packages.shared.ai_service import call_llm
     except ImportError:
         return {"intent": "推广产品", "key_messages": ["产品亮点"], "tone": "专业", "suggested_title": ""}
 
@@ -556,11 +590,21 @@ def _step_intent_parsing(job: ViralVideoJob, image_analysis: dict) -> dict:
         msgs = [n["text"] for n in xp.find_all(raw, "message") if n["text"]]
         tone = xp.text_of(raw, "emotion_tone") or "亲切自然"
         title = xp.text_of(raw, "suggested_title") or xp.text_of(raw, "title")
-        return {"intent": summary or "推广产品", "key_messages": msgs or ["产品亮点"], "tone": tone, "suggested_title": title}
+        return {
+            "intent": summary or "推广产品",
+            "key_messages": msgs or ["产品亮点"],
+            "tone": tone,
+            "suggested_title": title,
+        }
 
     def _fallback(raw: str) -> dict:
         t = (job.user_copy_text or "").strip()
-        return {"intent": t[:30] or "推广产品", "key_messages": [t[:80]] if t else ["产品亮点"], "tone": "专业", "suggested_title": ""}
+        return {
+            "intent": t[:30] or "推广产品",
+            "key_messages": [t[:80]] if t else ["产品亮点"],
+            "tone": "专业",
+            "suggested_title": "",
+        }
 
     _s = get_shared_settings()
     _fast = _s.doubao_fast_model
@@ -568,8 +612,13 @@ def _step_intent_parsing(job: ViralVideoJob, image_analysis: dict) -> dict:
     for _m, _lbl in [(_fast, "fast"), (_pro, "pro-fallback")]:
         try:
             logger.info("[爆款视频] 意图解析 model=%s label=%s", _m, _lbl)
-            raw = call_llm([{"role": "system", "content": system}, {"role": "user", "content": user}],
-                           temperature=0.4, max_tokens=1024, model=_m, timeout=45)  # #2180: 意图解析 LLM 实测需更长响应，原25s太紧
+            raw = call_llm(
+                [{"role": "system", "content": system}, {"role": "user", "content": user}],
+                temperature=0.4,
+                max_tokens=1024,
+                model=_m,
+                timeout=45,
+            )  # #2180: 意图解析 LLM 实测需更长响应，原25s太紧
             if not raw:
                 continue
             parsed = _parse(raw)
@@ -579,6 +628,7 @@ def _step_intent_parsing(job: ViralVideoJob, image_analysis: dict) -> dict:
             logger.warning("[爆款视频] 意图解析失败 label=%s err=%s", _lbl, e)
     return _fallback("")
 
+
 _PERSONA_STYLE_GUIDE = {
     "通用个人IP": "亲切自然、像朋友分享好物，第一人称口语化，不端着",
     "老板型IP": "沉稳大气、有行业格局感，适度使用『我做了XX年』『我一直坚持』等老板视角，语气自信不夸张",
@@ -592,6 +642,7 @@ _PERSONA_STYLE_GUIDE = {
     "测评种草型": "真实测评感、讲使用体验和优缺点对比，带『亲测』『我用了XX天』『实测下来』真实感词汇",
 }
 
+
 def _persona_style_hint(persona_id: str) -> str:
     """根据 persona_id 查文案风格指导；未命中/空值返回通用提示。"""
     pid = (persona_id or "").strip()
@@ -602,6 +653,7 @@ def _persona_style_hint(persona_id: str) -> str:
         return f"【人设风格：{pid}】按该人设的口吻、话术习惯组织口播和出镜动作"
     return "【人设风格：未指定】亲切自然、像朋友分享好物"
 
+
 def _build_products_summary(image_analysis: dict) -> str:
     """把 VLM 返回的商品分析结果拼给文案/分镜生成 prompt 用。
     优先用 summary（自然段落）；没有时用结构化字段兜底拼一段。"""
@@ -670,6 +722,7 @@ def _build_products_summary(image_analysis: dict) -> str:
         lines.append("- " + "，".join(parts))
     return "\n".join(lines)
 
+
 def _safe_json_loads(raw: str | dict | list | None):
     if raw is None:
         return None
@@ -696,6 +749,7 @@ def _safe_json_loads(raw: str | dict | list | None):
             pass
     return None
 
+
 def _replace_henjin_everywhere(obj: Any) -> Any:
     """递归遍历 copy_result 里所有字符串值，把'很近'替换成'最近'。
     覆盖 overview.theme、scene_and_lighting、voiceover_script、
@@ -711,6 +765,7 @@ def _replace_henjin_everywhere(obj: Any) -> Any:
         return {k: _replace_henjin_everywhere(v) for k, v in obj.items()}
     return obj
 
+
 def _fallback_script(job: ViralVideoJob) -> dict:
     """脚本生成失败时的兜底脚本（极简但可用）。"""
     dur = max(5, min(30, int(getattr(job, "duration", 15) or 15)))
@@ -735,6 +790,7 @@ def _fallback_script(job: ViralVideoJob) -> dict:
     base["title"] = "好物分享"
     return base
 
+
 def _validate_and_normalize_script(raw, job: ViralVideoJob) -> dict:
     """把 LLM 返回的脚本规范化、补默认、校验结构。"""
     dur = max(5, min(30, int(getattr(job, "duration", 15) or 15)))
@@ -831,9 +887,11 @@ def _validate_and_normalize_script(raw, job: ViralVideoJob) -> dict:
     base["title"] = base["overview"]["theme"]
     return base
 
+
 def _script_from_xml(raw: str, job: ViralVideoJob) -> dict | None:
     """把 LLM 返回的 XML 分镜规范化为旧 copy_result 结构（供 Seedance 使用）。"""
     from packages.application.viral_video import xml_parser as xp
+
     dur = max(5, min(30, int(getattr(job, "duration", 15) or 15)))
     ratio = getattr(job, "video_ratio", None) or "9:16"
     base = _empty_copy_result(dur, ratio)
@@ -860,14 +918,18 @@ def _script_from_xml(raw: str, job: ViralVideoJob) -> dict | None:
             ref_idx = xp.attr_int(ref_idx_raw, 0)
         shot = {
             "time_range": a.get("time_range") or f"{i * 3}-{(i + 1) * 3}秒",
-            "shot_type_angle_movement": (xp.text_of(body, "shot_type_angle_movement") if body else "") or a.get("shot_type_angle_movement", "") or "中景平视，固定镜头",
+            "shot_type_angle_movement": (xp.text_of(body, "shot_type_angle_movement") if body else "")
+            or a.get("shot_type_angle_movement", "")
+            or "中景平视，固定镜头",
             "scene_and_dialogue": (xp.text_of(body, "scene_and_dialogue") if body else "") or "",
             "action_details": (xp.text_of(body, "action_details") if body else "") or "",
             "audio_bgm": (xp.text_of(body, "audio_bgm") if body else "") or a.get("bgm_note", "") or "轻快BGM",
-            "transition": (xp.text_of(body, "transition") if body else "") or a.get("transition", "") or ("硬切" if i < len(clips) - 1 else "结束"),
+            "transition": (xp.text_of(body, "transition") if body else "")
+            or a.get("transition", "")
+            or ("硬切" if i < len(clips) - 1 else "结束"),
             "reference_image_index": ref_idx,
         }
-        voice = (xp.text_of(body, "voice_text") if body else "")
+        voice = xp.text_of(body, "voice_text") if body else ""
         if voice:
             voice_parts.append(voice)
             if not shot["scene_and_dialogue"]:
@@ -883,30 +945,25 @@ def _script_from_xml(raw: str, job: ViralVideoJob) -> dict | None:
     base["title"] = base["overview"]["theme"]
     return base
 
+
 def _step_script_generation(job: ViralVideoJob, intent: dict, image_analysis: dict) -> dict:
     """步骤 3: 编导分镜脚本生成（#2040：模板 + XML 解析；输出 copy_result 结构）。"""
     try:
-        from packages.shared.ai_service import call_llm
         from packages.application.viral_video.prompt_loader import (
             get_template,
             render_user_prompt,
         )
         from packages.application.viral_video.prompts import (
-            FUSION_INSTRUCTIONS, GLOBAL_CONSTRAINTS, NEGATIVE_RULES,
+            FUSION_INSTRUCTIONS,
+            GLOBAL_CONSTRAINTS,
+            NEGATIVE_RULES,
         )
+        from packages.shared.ai_service import call_llm
     except ImportError:
         return _fallback_script(job)
 
     products_summary = _build_products_summary(image_analysis)
-    style_hint = "无"
-    if isinstance(job.style_guide, dict):
-        style_hint = (
-            f"节奏{job.style_guide.get('cut_speed', '')}、转场{job.style_guide.get('transition', '')}、"
-            f"色调{job.style_guide.get('color_grade', '')}、能量{job.style_guide.get('energy', '')}"
-        )
-
     dur = max(5, min(30, int(getattr(job, "duration", 15) or 15)))
-    ratio = getattr(job, "video_ratio", None) or "9:16"
 
     intent_str = "推广产品"
     key_msgs = "产品亮点"
@@ -916,13 +973,6 @@ def _step_script_generation(job: ViralVideoJob, intent: dict, image_analysis: di
         key_msgs = "、".join(intent.get("key_messages") or []) or key_msgs
         tone = intent.get("tone") or tone
 
-    _vs = (job.viral_structure or "").strip()
-    if _vs:
-        viral_structure_block = f"【{_vs}】—— 请严格按照这个爆款结构的节奏/段落顺序编排镜头、台词和情绪节点（开场钩子、痛点、反转、案例、行动号召等按结构走），不要打乱顺序"
-    else:
-        viral_structure_block = "未指定（自由编排，但仍需有钩子开头+产品展示+行动号召的基本节奏）"
-
-    persona_hint = _persona_style_hint(getattr(job, "persona_id", ""))
     fusion_level = getattr(job, "fusion_level", "ai_polish") or "ai_polish"
     fusion_instruction = FUSION_INSTRUCTIONS.get(fusion_level, FUSION_INSTRUCTIONS["ai_polish"])
 
@@ -939,15 +989,21 @@ def _step_script_generation(job: ViralVideoJob, intent: dict, image_analysis: di
     )
     user = render_user_prompt(
         template,
-        duration=dur, image_count=len(job.images or []),
+        duration=dur,
+        image_count=len(job.images or []),
         fusion_result=fusion_brief,
         image_analysis=products_summary,
     )
 
     def _try_gen(model: str, temp: float, max_tok: int, label: str, tmo: int = 25):
         logger.info("[爆款视频] 编导脚本生成 model=%s label=%s timeout=%d", model, label, tmo)
-        raw = call_llm([{"role": "system", "content": system_tpl}, {"role": "user", "content": user}],
-                       temperature=temp, max_tokens=max_tok, model=model, timeout=tmo)
+        raw = call_llm(
+            [{"role": "system", "content": system_tpl}, {"role": "user", "content": user}],
+            temperature=temp,
+            max_tokens=max_tok,
+            model=model,
+            timeout=tmo,
+        )
         if not raw:
             return None
         normalized = _script_from_xml(raw, job)
@@ -967,7 +1023,13 @@ def _step_script_generation(job: ViralVideoJob, intent: dict, image_analysis: di
         fallback_marker = "我最近在用的好物" in voiceover
         has_typo_henjin = "很近" in json.dumps(normalized, ensure_ascii=False)
         is_fallback = fallback_marker or shots_cnt < 1 or len(voiceover) < 20 or has_typo_henjin
-        logger.info("[爆款视频] 编导脚本结果 label=%s voiceover_len=%d shots=%d fallback=%s", label, len(voiceover), shots_cnt, is_fallback)
+        logger.info(
+            "[爆款视频] 编导脚本结果 label=%s voiceover_len=%d shots=%d fallback=%s",
+            label,
+            len(voiceover),
+            shots_cnt,
+            is_fallback,
+        )
         return None if is_fallback else normalized
 
     _s = get_shared_settings()
@@ -992,6 +1054,7 @@ def _step_script_generation(job: ViralVideoJob, intent: dict, image_analysis: di
         logger.warning("[爆款视频] 编导脚本生成异常: %s，使用兜底脚本", e, exc_info=True)
         return _fallback_script(job)
 
+
 def _step_review(job: ViralVideoJob, copy_result: dict) -> dict:
     """步骤 4: 合规审核（#2040：使用 Reviewer + review 模板，6 维度 + 自动重写 1 次）。
 
@@ -1000,7 +1063,11 @@ def _step_review(job: ViralVideoJob, copy_result: dict) -> dict:
     try:
         from packages.application.viral_video.reviewer import Reviewer
         from packages.application.viral_video.schemas import (
-            FusionResult, IntentResult, CoreMessage, PersonalBrand, ScriptSegment,
+            CoreMessage,
+            FusionResult,
+            IntentResult,
+            PersonalBrand,
+            ScriptSegment,
         )
     except ImportError as e:
         logger.warning("[爆款视频] reviewer 模块不可用，跳过审核: %s", e)
@@ -1010,14 +1077,17 @@ def _step_review(job: ViralVideoJob, copy_result: dict) -> dict:
     title = (copy_result or {}).get("title") or (copy_result or {}).get("overview", {}).get("theme", "")
 
     intent_data = job.intent_result or {}
-    core_msgs = [CoreMessage(text=str(m), must_keep=True, confidence=0.9) for m in (intent_data.get("key_messages") or [])]
+    core_msgs = [
+        CoreMessage(text=str(m), must_keep=True, confidence=0.9) for m in (intent_data.get("key_messages") or [])
+    ]
     brands: list[PersonalBrand] = []
     brand_text = intent_data.get("brand_text") or intent_data.get("suggested_title") or ""
     if brand_text:
         brands.append(PersonalBrand(text=str(brand_text), category="brand"))
     intent_obj = IntentResult(
         intent_summary=intent_data.get("intent", "") or "推广产品",
-        core_messages=core_msgs, personal_brands=brands,
+        core_messages=core_msgs,
+        personal_brands=brands,
     )
     fusion_obj = FusionResult(
         title=title or "",
@@ -1041,7 +1111,11 @@ def _step_review(job: ViralVideoJob, copy_result: dict) -> dict:
             try:
                 rewritten = reviewer.rewrite(fusion_obj, review_res, intent_obj, fusion_level)
                 if rewritten and (rewritten.title or rewritten.script_segments):
-                    new_voice = rewritten.script_segments[0].text if rewritten.script_segments else (rewritten.hook or voiceover)
+                    new_voice = (
+                        rewritten.script_segments[0].text
+                        if rewritten.script_segments
+                        else (rewritten.hook or voiceover)
+                    )
                     new_copy = dict(copy_result)
                     new_copy["voiceover_script"] = new_voice
                     new_copy["final_copy"] = new_voice
@@ -1057,7 +1131,10 @@ def _step_review(job: ViralVideoJob, copy_result: dict) -> dict:
             "passed": review_res.passed,
             "score": 90 if review_res.passed else 60,
             "details": {i.dimension: i.text for i in review_res.issues},
-            "issues": [{"dimension": i.dimension, "severity": i.severity, "location": i.location, "text": i.text} for i in review_res.issues],
+            "issues": [
+                {"dimension": i.dimension, "severity": i.severity, "location": i.location, "text": i.text}
+                for i in review_res.issues
+            ],
         }
         if rewritten_voice is not None:
             result["rewritten_copy"] = new_copy
@@ -1068,6 +1145,7 @@ def _step_review(job: ViralVideoJob, copy_result: dict) -> dict:
         logger.warning("[爆款视频] 审核异常，跳过: %s", e, exc_info=True)
         return {"passed": True, "score": 75, "details": {}, "issues": []}
 
+
 def _step_tts(job: ViralVideoJob, voiceover_script: str):
     """步骤 5: CosyVoice 整段配音 → 返回本地 MP3 Path；失败返回 None。"""
     try:
@@ -1106,6 +1184,7 @@ def _step_tts(job: ViralVideoJob, voiceover_script: str):
         logger.warning("[爆款视频] TTS 配音失败: %s", e, exc_info=True)
         return None
 
+
 def _upload_tts_to_oss(job: ViralVideoJob, tts_path) -> str | None:
     """把 TTS 本地 mp3 上传到 OSS，返回公网 URL（供 Seedance 做 reference_audios 口型驱动用）。"""
     if tts_path is None:
@@ -1125,6 +1204,7 @@ def _upload_tts_to_oss(job: ViralVideoJob, tts_path) -> str | None:
         logger.warning("[爆款视频] TTS 上传 OSS 失败: %s", e, exc_info=True)
         return None
 
+
 def _assemble_seedance_prompt(copy_result: dict, job: ViralVideoJob) -> str:
     """把编导脚本拼成 Seedance 长 prompt。"""
     if not isinstance(copy_result, dict) or not copy_result:
@@ -1175,6 +1255,7 @@ def _assemble_seedance_prompt(copy_result: dict, job: ViralVideoJob) -> str:
     lines.append("，".join([str(x) for x in np if x]))
     return "\n".join(lines)
 
+
 def _step_render(job: ViralVideoJob, copy_result: dict, tts_audio_url: str | None) -> tuple[str, dict | None]:
     """步骤 6: v1.6 单次 Seedance 生成（不再分段/拼接）。
 
@@ -1288,6 +1369,7 @@ def _step_render(job: ViralVideoJob, copy_result: dict, tts_audio_url: str | Non
     logger.info("[爆款视频] 单次生成完成: path=%s size=%d usage=%s", video_path, size, usage)
     return str(video_path), (usage if isinstance(usage, dict) else None)
 
+
 def _step_upload(job: ViralVideoJob, video_path: str) -> str:
     """步骤 7: OSS 上传。"""
     from video_processing.oss_helpers import upload_to_oss
@@ -1300,6 +1382,7 @@ def _step_upload(job: ViralVideoJob, video_path: str) -> str:
         raise RuntimeError(f"OSS 上传失败: storage_key={storage_key}")
     return video_url
 
+
 def _wait_oss_ready(url: str, timeout_sec: int = 10) -> bool:
     """轮询 OSS 公网 URL，直到 HEAD 返回 200 或超时。
     用于缓解 OSS 上传后 1-5s 公网 eventual consistency 导致的 NoSuchKey。
@@ -1320,8 +1403,10 @@ def _wait_oss_ready(url: str, timeout_sec: int = 10) -> bool:
     logger.warning("[爆款视频] OSS 成片在 %ds 内未就绪 last_status=%s url=%s", timeout_sec, last_status, url[:120])
     return False
 
+
 # ── 主编排器 ────────────────────────────────────────────────────────────
 
+
 @shared_task(
     bind=True,
     max_retries=2,
@@ -1406,6 +1491,7 @@ def run_viral_video_pipeline(self: Task, job_id: str) -> dict:
         if session:
             session.close()
 
+
 @shared_task(bind=True, max_retries=2, name="worker.resume_viral_video_pipeline")
 def resume_viral_video_pipeline(self: Task, job_id: str) -> dict:
     """旧 confirm-intent 路径兼容：从 WAIT_USER_CONFIRM 跑完整个渲染。"""
@@ -1427,6 +1513,7 @@ def resume_viral_video_pipeline(self: Task, job_id: str) -> dict:
         if session:
             session.close()
 
+
 @shared_task(bind=True, max_retries=1, name="worker.run_video_style_analysis")
 def run_video_style_analysis(self: Task, job_id: str) -> dict:
     """独立的视频风格分析任务。"""
@@ -1450,8 +1537,10 @@ def run_video_style_analysis(self: Task, job_id: str) -> dict:
         if session:
             session.close()
 
+
 # ── 失败处理 ────────────────────────────────────────────────────────────
 
+
 def _mark_failed_and_notify(job_id: str, session, repo, job, err_msg: str, stage: str = "") -> None:
     """标记任务失败并通知。若传入的 session 已失效（因前面异常导致 rollback 状态），
     会自动 fallback 到新建 SessionLocal 重新标记，确保状态一定落库。"""
@@ -1492,8 +1581,10 @@ def _mark_failed_and_notify(job_id: str, session, repo, job, err_msg: str, stage
         event_type="viral_video:failed",
     )
 
+
 # ── v1.5/v1.6 三步分步流水线 Celery 任务 ─────────────────────────────────
 
+
 @shared_task(
     bind=True,
     max_retries=1,
@@ -1561,6 +1652,7 @@ def run_viral_video_analyze(self: Task, job_id: str) -> dict:
         if session:
             session.close()
 
+
 @shared_task(
     bind=True,
     max_retries=1,
@@ -1663,6 +1755,7 @@ def run_viral_video_generate_copy(self: Task, job_id: str) -> dict:
         if session:
             session.close()
 
+
 def _quick_compliance_blacklist_check(copy_result: dict) -> None:
     """阶段2快速黑名单检查：不调用 LLM，只扫描高风险关键词；命中则在 voiceover 中就地替换。
 
@@ -1704,6 +1797,7 @@ def _quick_compliance_blacklist_check(copy_result: dict) -> None:
                 for bk, bv in BLACKLIST.items():
                     copy_result[k] = copy_result[k].replace(bk, bv)
 
+
 def _try_refund_viral_video(job: ViralVideoJob) -> None:
     """爆款视频生成失败：若已预扣积分则全额退款。"""
     try:
@@ -1733,6 +1827,7 @@ def _try_refund_viral_video(job: ViralVideoJob) -> None:
     except Exception:
         logger.exception("[爆款视频] 失败退款异常 job_id=%s", job.id)
 
+
 def _settle_viral_video(job: ViralVideoJob, usage: dict | None) -> None:
     """爆款视频生成成功：按实际 usage 结算，多退少补，写 credits_cost。"""
     try:
@@ -1803,6 +1898,7 @@ def _settle_viral_video(job: ViralVideoJob, usage: dict | None) -> None:
         job.credits_cost = float(getattr(job, "credits_prepaid", 0) or 0)
         job.credits_prepaid = 0.0
 
+
 def _run_render_pipeline(job_id: str, session, repo, job) -> dict:
     """v1.6.1 阶段3：出片前合规审核（LLM 深度）→ TTS → Seedance → Upload → Completed。
 
@@ -1889,6 +1985,7 @@ def _run_render_pipeline(job_id: str, session, repo, job) -> dict:
     logger.info("[爆款视频] 任务完成: job_id=%s video_url=%s", job_id, video_url)
     return {"ok": True, "job_id": job_id, "video_url": video_url}
 
+
 @shared_task(bind=True, max_retries=2, name="worker.run_viral_video_render")
 def run_viral_video_render(self: Task, job_id: str) -> dict:
     """v1.6 阶段3：TTS + 单次 Seedance 生成 + 上传。"""