上线版: 产品表单统一+form嵌套修复+用户管理+部署+三套叙事

- 产品编辑入口统一走 ProductFormFull(卖点/风格/人群/品牌词全字段); 修复开任务页 <form> 套 <form> 致"编辑产品"报错、改不了、跳回首个产品 - dashboard 入口卡片对齐实际路由: 系统管理(/config) 与工作配置(/settings) 分开; settings ?tab=products 直达改用挂载后读 URL, 消除 hydration mismatch - 新增用户管理(users API/admin service/改密页) + alembic 022/023/024 - 上线部署: Dockerfile / docker-compose.prod+https / nginx https / .env.example - A8 三套正交叙事(痛点/场景/成分背书) + beige 调色去AI化 + 飞轮 text_import 高权重信号 Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-30 18:08:13 +08:00
parent a77212781c
commit df1856d793
150 changed files with 8616 additions and 1765 deletions
--- a/backend/app/workers/pipeline_io.py
+++ b/backend/app/workers/pipeline_io.py
@@ -32,15 +32,17 @@ def _resolve_image_path(img_path: str) -> str:


 def run_text_generation(db, clients, task, product_dict: dict, flywheel_fragment: str,
-                        push_fn, workspace_id: int, seq_start: int) -> tuple[list, int, bool]:
+                        push_fn, workspace_id: int, seq_start: int) -> tuple[list, int, bool, str | None, int]:
    """
    Step5: 调 generate_text_variants → 存 TextCandidate → 推 SSE → 写 ai_call_logs。
    S1: 存库前过滤——只存 passed且score>=QUALITY_PASS_SCORE(80,红线)且banned_word_status!='hard_block' 的文案。
    合格数 < task.text_count 时 needs_replenish=True（由主任务发起后台补充子任务）。
-    返回 (candidates_raw, next_seq, needs_replenish)。
+    返回 (candidates_raw, next_seq, needs_replenish, text_fail_reason, saved_count)。
+    text_fail_reason: None|scoring_unavailable|generation_failed|quality_filtered|replenishing(B1透传0条原因)。
    """
    import time
    from app.services.ai_engine.text_variants import generate_text_variants
+    from app.services.ai_engine.llm_scorer import ScoringUnavailableError
    from app.models.product import BannedWord
    from app.models.task import TextCandidate
    from app.models.flywheel import AiCallLog
@@ -70,6 +72,7 @@ def run_text_generation(db, clients, task, product_dict: dict, flywheel_fragment

    t0 = time.monotonic()
    llm_success = True
+    scoring_unavailable = False  # B1：评分通道(apiports+codeproxy)整套都挂，用于区分"评分不可用"vs"质量不合格"
    candidates_raw: list = []
    for s in _strategies:
        n = _per[s]
@@ -85,6 +88,12 @@ def run_text_generation(db, clients, task, product_dict: dict, flywheel_fragment
                flywheel_context=flywheel_fragment,
                strategy_narrative=TEXT_NARRATIVE_BY_STRATEGY.get(s, ""),
            ))
+        except ScoringUnavailableError as exc:
+            # B1：评分两通道均不可用——明确记号，绝不当"质量不合格"糊弄用户
+            scoring_unavailable = True
+            llm_success = False
+            logger.error("generate_text_variants(套%s) 评分通道不可用: %s", s, exc)
+            part = []
        except Exception as exc:
            llm_success = False
            logger.error("generate_text_variants(套%s) 失败: %s", s, exc)
@@ -115,10 +124,13 @@ def run_text_generation(db, clients, task, product_dict: dict, flywheel_fragment
    # S1: 存库前过滤——只存合格文案（passed + score>=QUALITY_PASS_SCORE(80) + 非hard_block）
    seq = seq_start
    saved_count = 0
+    partial_scoring_unavailable = False  # 部分条目评分通道挂(整套没全挂故没抛异常),用于精确归因
    for i, c in enumerate(candidates_raw):
        score = c.get("score", 0)
        passed = c.get("passed", False)
        bw_status = c.get("banned_word_status", "pass")
+        if c.get("scoring_unavailable"):
+            partial_scoring_unavailable = True
        if not (passed and score >= QUALITY_PASS_SCORE and bw_status != "hard_block"):
            logger.info(
                "文案[%d] 过滤丢弃: passed=%s score=%s banned=%s",
@@ -159,22 +171,40 @@ def run_text_generation(db, clients, task, product_dict: dict, flywheel_fragment
            "文案合格数不足: task_id=%s 目标=%s 实得=%s，将后台异步补充",
            task.id, task.text_count, saved_count,
        )
-    return candidates_raw, seq, needs_replenish
+    # 整套全挂(scoring_unavailable)或部分条目评分挂(partial)都按"评分不可用"归因，
+    # 不被 quality_filtered 掩盖——评分通道问题≠文案质量问题(B1红线)
+    scoring_unavailable = scoring_unavailable or partial_scoring_unavailable
+    # B1：透传 0 条的真实原因，前端据此区分提示，不再把"评分挂了"显示成"没有合格文案"
+    if saved_count == 0 and scoring_unavailable:
+        text_fail_reason = "scoring_unavailable"   # 评分服务不可用
+    elif saved_count == 0 and not llm_success:
+        text_fail_reason = "generation_failed"     # 文案生成本身失败(非评分)
+    elif saved_count == 0:
+        text_fail_reason = "quality_filtered"      # 生成成功但全部未达标
+    elif needs_replenish:
+        text_fail_reason = "replenishing"          # 有产出但不足，补充中
+    else:
+        text_fail_reason = None                     # 正常足量
+    return candidates_raw, seq, needs_replenish, text_fail_reason, saved_count


 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,
+                         notes_by_strategy: dict[str, dict], upload_base_path: str,
                         regen_strategy: str | None = None,
                         regen_role: str | None = None,
                         custom_prompt: str | None = None,
-                         flywheel_fragment: str | None = None) -> int:
+                         flywheel_fragment: str | None = None,
+                         reuse_text: bool = False) -> 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。
+
+    reuse_text=True(导入轨)：只遍历库内真有导入文案的套(notes_by_strategy 的键)，
+    导入几套出几套，未导入的套不刷 batch_failed 噪声。
    """
    import time
    from app.services.ai_engine.image_gen import generate_storyboard_images
@@ -236,28 +266,66 @@ def run_image_generation(db, clients, task, product_dict: dict,
    # 主图始终保底进 primary（多图表为空或主图未入表时仍可用）
    if reference_images and not images_by_scene.get("primary"):
        images_by_scene.setdefault("primary", []).extend(reference_images)
+    # 主图缺失告警：无 scene=primary 入表时，所有 primary 角色只能靠 image_path 兜底，
+    # 若用户把瓶身误标成 texture，主图角色会取不到真瓶身 → 提前暴露在日志（不硬拦，纯测试场景仍放行）
+    if not images_by_scene.get("primary"):
+        logger.warning(
+            "task_id=%s 无 scene=primary 产品图，主图角色将无瓶身锚点，"
+            "请确认产品已正确标注主图(瓶身本体)。", task.id
+        )
    if images_by_scene:
        logger.info("R5多图已加载：%s", {k: len(v) for k, v in images_by_scene.items()})

    seq = seq_start
-    # 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")
+    # R2: 限定重生套别(regen_strategy)则只跑该套；
+    # reuse_text(导入轨): 只跑库内真有导入文案的套(按 A/B/C 顺序)，导入几套出几套；
+    # 否则全量 A/B/C 三套正交叙事。
+    if regen_strategy:
+        _strategies = (regen_strategy,)
+    elif reuse_text:
+        _strategies = tuple(s for s in ("A", "B", "C") if notes_by_strategy.get(s))
+        # 存量导入文案 strategy 可能为 NULL(归到键"_")，A/B/C 全匹配不上→_strategies 空。
+        # 必须显式报错，否则循环静默跳过=零图产出但任务不报错，极难排查。
+        if not _strategies:
+            logger.error(
+                "导入文案均未分配套别(A/B/C)，无法生图: task_id=%s keys=%s",
+                task.id, list(notes_by_strategy.keys()),
+            )
+            push_fn(task.id, workspace_id, "error", {
+                "code": 40003,
+                "message": "导入文案未分配套别(A/B/C)，请重新导入文案后再去生图",
+            }, seq + 1)
+            return seq + 1
+    else:
+        _strategies = ("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
+    # 进度总数：单张重生=1，单套=image_count，全量/导入=image_count×实际套数
    if regen_role:
        _img_total = 1
    elif regen_strategy:
        _img_total = task.image_count
    else:
-        _img_total = task.image_count * 3
+        _img_total = task.image_count * len(_strategies)
    for si, strategy in enumerate(_strategies):
        t0 = time.monotonic()
        img_success = True
        img_error_code = None
        try:
+            note_for_strategy = notes_by_strategy.get(strategy)
+            if not note_for_strategy:
+                logger.error("套%s缺少合格文案，拒绝复用其他套文案生图: task_id=%s", strategy, task.id)
+                seq += 1
+                push_fn(task.id, workspace_id, "batch_failed", {
+                    "batch": f"{strategy}_missing_text",
+                    "reason": f"套{strategy}缺少合格文案，未生成该套图片",
+                    "strategy": strategy,
+                    "retryable": False,
+                }, seq)
+                continue
+
            image_results = asyncio.run(generate_storyboard_images(
                client=clients,
-                note=first_copy,
+                note=note_for_strategy,
                product=product_dict,
                image_count=task.image_count,
                reference_images=reference_images or None,