perf(#2172): 信任链 Seedream i2i 预热与文案生成并行，缩短有参考图场景等待时间

问题：
- #2170 信任链方案在视频渲染阶段同步串行跑 Seedream AI 化（每张约5-15s）
- 用户提交到出片要多等一个 Seedream i2i 耗时
- 主人反馈「分析图片很慢」「生成文案也很慢」

方案：
- 抽取 ai_client.preheat_trust_chain() 独立方法
- 在阶段1（图片VLM分析）开始时，用 daemon 线程后台并行启动 Seedream i2i 预热
- 预热结果持久化到 job.pre_trusted_images 字段（新增 094 migration）
- 阶段3渲染时，若预热完成直接使用 pre_trusted_images，跳过现场 Seedream i2i
- 预热失败/未完成不影响主流程，自动回退到现场跑信任链兜底
- VLM分析(~5-15s) + 文案生成(~10-20s) + 用户编辑确认(~30s+)期间，Seedream i2i 在后台已完成

改动文件：
- packages/shared/ai_client.py: 抽取 preheat_trust_chain() 方法；video_generation 加 pre_trusted_images 参数支持预热结果
- packages/shared/ai_service.py: 新增 preheat_trust_chain() 入口；call_video_generation 透传 pre_trusted_images
- packages/domain/viral_video.py: ViralVideoJob 加 pre_trusted_images 字段
- packages/adapters/sqlalchemy_impl/models.py: ViralVideoJobModel 加 pre_trusted_images 列
- packages/adapters/sqlalchemy_impl/viral_video_repository.py: _to_domain/save/update 映射新字段
- alembic/versions/094_viral_video_pre_trusted.py: 新增列 migration
- apps/worker/worker_app/tasks/viral_video.py: _start_trust_chain_preheat() 后台预热启动函数；阶段1启动预热；_step_render 使用预热结果

测试：16513 passed（2个musetalk pre-existing失败，无关）

alembic/versions/094_viral_video_pre_trusted.py

@@ -0,0 +1,31 @@
+"""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_viral_video_pricing_points_float"
+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")

apps/worker/worker_app/tasks/viral_video.py

@@ -92,6 +92,62 @@ def _save_job(repo, job, session):
     session.commit()
 
 
+def _start_trust_chain_preheat(job_id: str, portrait_urls: list[str]) -> None:
+    """#2172 后台启动信任链预热（Seedream AI 化人像），不阻塞调用方。
+
+    预热成功后把结果写入 job.pre_trusted_images，阶段3 渲染直接使用，省掉串行等待。
+    预热失败静默（pre_trusted_images 保持 None），阶段3 会现场跑信任链兜底。
+    """
+    if not portrait_urls:
+        return
+    # 判断是否是 doubao provider（DashScope/Wan 不需要信任链）
+    try:
+        from packages.domain.points_rules import get_viral_video_model_config
+        from packages.shared.ai_service import preheat_trust_chain
+    except ImportError:
+        return
+
+    def _run_preheat():
+        sess = None
+        try:
+            # 只有 doubao provider 的模型需要信任链
+            try:
+                _s = get_shared_settings()
+                job_sess, job_repo, job_obj = _get_repo_and_job(job_id)
+                model = getattr(job_obj, "video_model", "") or ""
+                _mcfg = get_viral_video_model_config(model)
+                if _mcfg.get("provider", "doubao") != "doubao":
+                    job_sess.close()
+                    return
+                job_sess.close()
+            except Exception:
+                pass
+
+            logger.info("[trust-chain][preheat] 后台预热启动 job=%s n=%d", job_id, len(portrait_urls))
+            result = preheat_trust_chain(portrait_urls, timeout=120)
+            if result and len(result) == len(portrait_urls):
+                sess2, repo2, job2 = _get_repo_and_job(job_id)
+                try:
+                    job2.pre_trusted_images = result
+                    repo2.update(job2)
+                    sess2.commit()
+                    logger.info(
+                        "[trust-chain][preheat] 预热完成并持久化 job=%s n=%d",
+                        job_id, len(result),
+                    )
+                finally:
+                    sess2.close()
+            else:
+                logger.info("[trust-chain][preheat] 预热失败 job=%s，阶段3现场跑兜底", job_id)
+        except Exception as e:
+            logger.warning("[trust-chain][preheat] 预热异常 job=%s err=%s", job_id, e, exc_info=True)
+
+    # 用 daemon 线程启动，不阻塞 celery task 返回
+    import threading
+    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。
 
@@ -1162,6 +1218,21 @@ def _step_render(job: ViralVideoJob, copy_result: dict, tts_audio_url: str | Non
     )
     logger.info("[爆款视频] Seedance prompt (前300字): %s", prompt[:300])
 
+    # #2172: 使用信任链预热结果（阶段1已在后台并行 Seedream AI 化）
+    pre_trusted = None
+    all_portrait_urls = []
+    if first_image:
+        all_portrait_urls.append(first_image)
+    for u in rest_images:
+        if u not in all_portrait_urls:
+            all_portrait_urls.append(u)
+    pti = getattr(job, "pre_trusted_images", None)
+    if pti and len(pti) == len(all_portrait_urls):
+        pre_trusted = list(pti)
+        logger.info("[爆款视频] 使用信任链预热结果 n=%d，跳过现场 Seedream AI 化", len(pre_trusted))
+    elif all_portrait_urls and _mcfg.get("provider", "doubao") == "doubao":
+        logger.info("[爆款视频] 预热结果不可用(%s/%d张)，将现场跑信任链", "缺失" if not pti else f"{len(pti)}/{len(all_portrait_urls)}", len(all_portrait_urls))
+
     # 第一次调用：带参考图/首帧/音频/参考视频
     result = call_video_generation(
         prompt=prompt,
@@ -1175,6 +1246,7 @@ def _step_render(job: ViralVideoJob, copy_result: dict, tts_audio_url: str | Non
         reference_images=rest_images,
         reference_audios=ref_audios,
         reference_videos=ref_videos,
+        pre_trusted_images=pre_trusted,
     )
 
     # #2170: 真人/肖像拦截由 ai_client 内部信任链自动处理（Seedream AI 化后再调 Seedance）；
@@ -1274,6 +1346,13 @@ def run_viral_video_pipeline(self: Task, job_id: str) -> dict:
         _hb_stop, _hb_thread = _start_heartbeat_thread(job_id)
         _set_stage(job, repo, session, ViralVideoStage.IMAGE_ANALYSIS, "正在分析商品特征...")
 
+        # #2172: 信任链预热与 VLM 分析并行启动（不阻塞）
+        if job.images:
+            try:
+                _start_trust_chain_preheat(job.id, list(job.images))
+            except Exception as _e:
+                logger.warning("[爆款视频][阶段1] 启动信任链预热失败: %s", _e)
+
         image_analysis = _step_image_analysis(job)
         job.image_analysis = image_analysis
         _save_job(repo, job, session)

packages/adapters/sqlalchemy_impl/models.py

@@ -928,6 +928,7 @@ class ViralVideoJobModel(Base):
     id = Column(String(36), primary_key=True)
     user_id = Column(String(36), nullable=False, index=True)
     images = Column(JSON, nullable=False, default=list)  # 产品图片 URL 列表
+    pre_trusted_images = Column(JSON, nullable=True)  # #2172 信任链预热结果（Seedream AI 化 URL 列表）
     industry = Column(String(100), nullable=False, default="")
     target_customer = Column(String(500), nullable=False, default="")
     persona_id = Column(String(36), nullable=False, default="")

packages/adapters/sqlalchemy_impl/viral_video_repository.py

@@ -18,6 +18,7 @@ def _to_domain(model: ViralVideoJobModel) -> ViralVideoJob:
         id=model.id,
         user_id=model.user_id,
         images=list(model.images or []),
+        pre_trusted_images=list(getattr(model, "pre_trusted_images", None) or []) if getattr(model, "pre_trusted_images", None) is not None else None,
         industry=model.industry or "",
         target_customer=model.target_customer or "",
         persona_id=model.persona_id or "",
@@ -70,6 +71,7 @@ class SQLAlchemyViralVideoJobRepository:
             id=job.id,
             user_id=job.user_id,
             images=job.images,
+            pre_trusted_images=job.pre_trusted_images,
             industry=job.industry,
             target_customer=job.target_customer,
             persona_id=job.persona_id,
@@ -126,6 +128,7 @@ class SQLAlchemyViralVideoJobRepository:
         model.storyboard = job.storyboard
         model.generated_copy_text = job.generated_copy_text or ""
         model.copy_result = job.copy_result
+        model.pre_trusted_images = job.pre_trusted_images
         model.result_video_url = job.result_video_url
         model.video_resolution = getattr(job, "video_resolution", "720p") or "720p"
         model.credits_prepaid = float(getattr(job, "credits_prepaid", 0) or 0)

packages/domain/viral_video.py

@@ -87,6 +87,7 @@ class ViralVideoJob:
 
     user_id: str
     images: list[str] = field(default_factory=list)
+    pre_trusted_images: list[str] | None = None  # #2172 信任链预热结果（Seedream AI 化后的 URL 列表），与 images 顺序对应
     industry: str = ""
     target_customer: str = ""
     persona_id: str = ""

packages/shared/ai_client.py

@@ -413,6 +413,47 @@ class DoubaoClient:
 
     # ── 视频生成（Seedance 2.5，异步任务）────────────────────────────
 
+    def preheat_trust_chain(
+        self,
+        portrait_urls: list[str],
+        *,
+        timeout: int = 120,
+    ) -> list[str] | None:
+        """#2172 信任链预热：对一组人像 URL 执行 Seedream AI 化，返回 AI 化后的 URL 列表。
+
+        - 全部成功返回 list[str]（顺序与输入一致）
+        - 任何一张失败返回 None（保留上层回退原图直传的路径）
+        - 供 worker 在视频生成前并行预热使用；video_generation 内部若收到 preheated 结果会直接使用，不再现场跑。
+        """
+        if not portrait_urls or not self.is_available:
+            return None
+        seedream_prompt = (
+            "保持此人五官特征、发型、肤色、面部轮廓、年龄感，生成一张高清写实人像照片，"
+            "人物外貌特征与参考图完全一致，皮肤自然，光线柔和，高清细节，不要过度美化。"
+        )
+        trusted: list[str] = []
+        _t0 = time.time()
+        for idx, raw_url in enumerate(portrait_urls):
+            sd_prompt = seedream_prompt if len(portrait_urls) == 1 else f"{seedream_prompt}（这是参考图{idx + 1}）"
+            sd_result = self.image_generation(
+                prompt=sd_prompt,
+                reference_images=[raw_url],
+                size="2K",
+                timeout=timeout,
+            )
+            if not sd_result:
+                logger.warning(
+                    "[trust-chain][preheat] Seedream 第 %d/%d 张失败: %s，预热整体失败",
+                    idx + 1, len(portrait_urls), getattr(self, "last_image_error", None),
+                )
+                return None
+            trusted.append(sd_result["url"])
+        logger.info(
+            "[trust-chain][preheat] Seedream AI 化预热完成 %d 张，总耗时 %.1fs",
+            len(trusted), time.time() - _t0,
+        )
+        return trusted
+
     def video_generation(
         self,
         prompt: str,
@@ -428,6 +469,7 @@ class DoubaoClient:
         reference_images: list[str] | None = None,
         reference_audios: list[str] | None = None,
         reference_videos: list[str] | None = None,
+        pre_trusted_images: list[str] | None = None,
     ) -> dict | None:
         """调用 Seedance 2.5 生视频（异步任务→轮询→下载）。
 
@@ -511,66 +553,55 @@ class DoubaoClient:
         ref_videos = [u for u in (reference_videos or [])[:3] if u and isinstance(u, str)]
         ref_imgs = [u for u in (reference_images or [])[:9] if u and isinstance(u, str)]
 
-        # ── #2170 方舟信任链（Trust Chain）────────────────────────────────────
+        # ── #2170/#2172 方舟信任链（Trust Chain）────────────────────────────────
         # 真人照片直接传给 Seedance 会触发 50411 肖像审核拦截。
         # 解决：先通过同账号的 Seedream 5.0 Pro 图生图 AI 化（保持五官特征），
         # 得到的 AI 产物图属于"模型信任产物"，再作为 reference_image 传给 Seedance 即可通过审核。
+        # #2172: 支持预热结果 pre_trusted_images（worker 在文案阶段并行预热，省掉串行等待）；
+        #       预热结果有效则直接使用，否则现场跑一次 Seedream AI 化。
         # 信任链只作用于 doubao provider；DashScope(Wan) 保持原行为。
         trust_chain_applied = False
         if provider == "doubao":
-            seedream_prompt = (
-                "保持此人五官特征、发型、肤色、面部轮廓、年龄感，生成一张高清写实人像照片，"
-                "人物外貌特征与参考图完全一致，皮肤自然，光线柔和，高清细节，不要过度美化。"
-            )
             raw_portrait_urls: list[str] = []
             if image_url:
                 raw_portrait_urls.append(image_url)
             for u in ref_imgs:
                 if u not in raw_portrait_urls:
                     raw_portrait_urls.append(u)
-            if raw_portrait_urls:
-                trusted_urls: list[str] = []
+            trusted_urls: list[str] = []
+            if pre_trusted_images and len(pre_trusted_images) == len(raw_portrait_urls):
+                # #2172: 使用预热结果
+                trusted_urls = list(pre_trusted_images)
+                trust_chain_applied = True
+                logger.info(
+                    "[trust-chain] 使用预热结果 %d 张，替换为 reference_image 模式",
+                    len(trusted_urls),
+                )
+            elif raw_portrait_urls:
+                # 现场跑信任链
                 _tc_t0 = time.time()
-                for idx, raw_url in enumerate(raw_portrait_urls):
-                    sd_prompt = (
-                        seedream_prompt if len(raw_portrait_urls) == 1 else f"{seedream_prompt}（这是参考图{idx + 1}）"
-                    )
-                    sd_result = self.image_generation(
-                        prompt=sd_prompt,
-                        reference_images=[raw_url],
-                        size="2K",
-                        timeout=120,
-                    )
-                    if not sd_result:
-                        logger.warning(
-                            "[trust-chain] Seedream 第 %d/%d 张失败: %s，回退直传原图",
-                            idx + 1,
-                            len(raw_portrait_urls),
-                            self.last_image_error,
-                        )
-                        break
-                    trusted_urls.append(sd_result["url"])
+                trusted_urls = self.preheat_trust_chain(raw_portrait_urls) or []
                 if trusted_urls and len(trusted_urls) == len(raw_portrait_urls):
                     trust_chain_applied = True
-                    # 替换：原 image_url 用第一张 AI 图，ref_imgs 用剩余
-                    if image_url and trusted_urls:
-                        image_url = trusted_urls[0]
-                        ref_imgs = trusted_urls[1:] if len(trusted_urls) > 1 else []
-                    else:
-                        ref_imgs = trusted_urls
                     logger.info(
                         "[trust-chain] Seedream AI 化完成 %d 张，总耗时 %.1fs，替换为 reference_image 模式",
                         len(trusted_urls),
                         time.time() - _tc_t0,
                     )
                 else:
-                    # Seedream 部分失败 → 回退原图直传（仍可能被 50411 拦截，但保留降级路径）
                     logger.warning(
                         "[trust-chain] Seedream AI 化不完整(%d/%d)，总耗时 %.1fs，回退原图直传",
                         len(trusted_urls),
                         len(raw_portrait_urls),
                         time.time() - _tc_t0,
                     )
+            if trust_chain_applied and trusted_urls:
+                # 替换：原 image_url 用第一张 AI 图，ref_imgs 用剩余
+                if image_url and trusted_urls:
+                    image_url = trusted_urls[0]
+                    ref_imgs = trusted_urls[1:] if len(trusted_urls) > 1 else []
+                else:
+                    ref_imgs = trusted_urls
         # ─────────────────────────────────────────────────────────────────
 
         # 判断任务模式：

packages/shared/ai_service.py

@@ -604,6 +604,22 @@ def call_vision(
         return raw
 
 
+
+def preheat_trust_chain(portrait_urls: list[str], *, timeout: int = 120) -> list[str] | None:
+    """#2172 信任链预热：提前把人像图跑 Seedream AI 化，结果可传给 call_video_generation(pre_trusted_images=...)。
+
+    成功返回与输入同序的 AI 化 URL 列表；任意一张失败返回 None（调用方回退到现场跑信任链）。
+    """
+    client = get_doubao_client()
+    if not client.is_available:
+        return None
+    try:
+        return client.preheat_trust_chain(portrait_urls, timeout=timeout)
+    except Exception as e:
+        logger.error("[ai_service] preheat_trust_chain 异常: %s", e, exc_info=True)
+        return None
+
+
 def call_video_generation(
     prompt: str,
     *,
@@ -617,8 +633,9 @@ def call_video_generation(
     reference_images: list[str] | None = None,
     reference_audios: list[str] | None = None,
     reference_videos: list[str] | None = None,
+    pre_trusted_images: list[str] | None = None,
 ) -> dict | None:
-    """调用 Seedance / Wan 视频生成（v1.6.2 多模型版）。
+    """调用 Seedance / Wan 视频生成（v1.6.2 多模型版 + #2172 信任链预热）。
 
     成功返回 {"video_path": str, "usage": dict | None}（usage 含 completion_tokens），失败返回 None。
     失败时错误详情会写入 client.last_video_error，可通过 get_last_video_error() 读取：
@@ -650,6 +667,7 @@ def call_video_generation(
             reference_images=reference_images,
             reference_audios=reference_audios,
             reference_videos=reference_videos,
+            pre_trusted_images=pre_trusted_images,
         )
         if effective_ratio:
             kwargs["ratio"] = effective_ratio