存量积累：生图素人感约束+评图分+幂等防重跑+审核回路

- 015-017迁移：image_candidate 文案复审/AI视觉分/重生标记
- constants C7素人感约束(反电商摆拍对齐真实笔记)+C3叠字口子
- celery visibility_timeout=2h 防长任务被误判重投重复烧钱(task75教训)
- image_scorer 评图分(只筛选+展示,真实信号才进飞轮权重)
- storyboard/image_gen/pipeline_io 生图存量
- task_actions/tasks/task_service/flywheel 审核回路+飞轮存量

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

backend/app/workers/celery_app.py

@@ -29,6 +29,11 @@ celery_app.conf.update(
     task_track_started=True,
     task_acks_late=True,          # 任务处理完才 ACK，防丢失
     worker_prefetch_multiplier=1,  # 一次只取1条，防长任务堆积
+    # 🔴 visibility_timeout 必须 > 单任务最长耗时。生图(gpt-image-2)单张可达 270s+，
+    # 整条流水线(多图+评图重试)可能十几分钟。默认仅 1h 时，长任务超时会被 Redis broker
+    # 误判丢失而重新投递给另一 worker → 同一 task 被反复重跑、重复烧钱(task75 教训)。
+    # 设 2h 留足余量；配合 pipeline 入口幂等检查双保险。
+    broker_transport_options={"visibility_timeout": 7200},
     task_routes={
         "app.workers.tasks.run_generation_pipeline": {"queue": "generation"},
         "app.workers.tasks.build_delivery_package": {"queue": "packaging"},

backend/app/workers/pipeline_io.py

@@ -145,10 +145,16 @@ def run_text_generation(db, clients, task, product_dict: dict, flywheel_fragment
 
 def run_image_generation(db, clients, task, product_dict: dict,
                          push_fn, workspace_id: int, seq_start: int,
-                         first_copy: dict, upload_base_path: str) -> int:
+                         first_copy: dict, upload_base_path: str,
+                         regen_strategy: str | None = None,
+                         regen_role: str | None = None,
+                         custom_prompt: str | None = None) -> int:
     """
     Step6+7+8(image): 调 generate_storyboard_images → 后处理 → 存 ImageCandidate → 推 SSE。
     返回 next_seq。
+
+    R2 局部重生(均 None=全量A/B/C)：regen_strategy 限定只跑该套；regen_role 配合限定该套该张；
+    custom_prompt 人工追加提示词。重生产出 is_regen=True 新增不删旧。
     """
     import time
     from app.services.ai_engine.image_gen import generate_storyboard_images
@@ -197,8 +203,17 @@ def run_image_generation(db, clients, task, product_dict: dict,
         )
 
     seq = seq_start
-    # 3套正交叙事 A/B/C，每套各 image_count 张独立生图
-    for strategy in ("A", "B", "C"):
+    # R2: 限定重生套别(regen_strategy)则只跑该套，否则全量 A/B/C 三套正交叙事
+    _strategies = (regen_strategy,) if regen_strategy else ("A", "B", "C")
+    _is_regen = bool(regen_strategy or regen_role)
+    # 进度总数：单张重生=1，单套=image_count，全量=image_count×3
+    if regen_role:
+        _img_total = 1
+    elif regen_strategy:
+        _img_total = task.image_count
+    else:
+        _img_total = task.image_count * 3
+    for si, strategy in enumerate(_strategies):
         t0 = time.monotonic()
         img_success = True
         img_error_code = None
@@ -210,6 +225,8 @@ def run_image_generation(db, clients, task, product_dict: dict,
                 image_count=task.image_count,
                 reference_images=reference_images or None,
                 strategy=strategy,
+                target_role=regen_role,
+                custom_prompt=custom_prompt,
             ))
         except Exception as exc:
             img_success = False
@@ -261,17 +278,25 @@ def run_image_generation(db, clients, task, product_dict: dict,
                 url=img_url,
                 seq=i + 1,
                 strategy=strategy,    # 写入 A/B/C（非 hardcode）
+                is_regen=_is_regen,   # R2 重生标记：新增不删旧，前端同strategy+role默认展示最新
+                # E12 AI评图分：只落展示分,绝不碰 eval_score(留 NULL)；AI 分不进飞轮权重
+                ai_visual_score=img_result.get("ai_visual_score"),
+                ai_visual_note=img_result.get("ai_visual_note"),
             )
             db.add(ic)
             db.flush()
             seq += 1
             push_fn(task.id, workspace_id, "image_candidate", {
-                "candidate_id": ic.id, "strategy": strategy,
+                "candidate_id": ic.id, "strategy": strategy, "seq": i + 1,
                 "url": img_url, "role": img_result["role"],
+                "is_regen": _is_regen,
+                "ai_visual_score": img_result.get("ai_visual_score"),
+                "ai_visual_note": img_result.get("ai_visual_note"),
             }, seq)
             seq += 1
             push_fn(task.id, workspace_id, "image_progress", {
-                "done": i + 1, "total": task.image_count, "strategy": strategy,
+                "done": si * task.image_count + (i + 1),
+                "total": _img_total, "strategy": strategy,
             }, seq)
 
         # 写 ai_call_logs（每套一条，失败不阻断）