baseline: Clover 独立仓库首次基线提交

将 Clover 从上层产品包旧仓库中独立出来,建立专属版本控制。
当前状态=纵切片端到端已打通(登录→选品→出文出图→审核→下载包),
M1文案质量去套路化已验收。此提交作为后续按核销清单逐条修复的基线。

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

backend/app/services/ai_engine/banned_word_checker.py

@@ -0,0 +1,125 @@
+"""
+违禁词三级处理（扒 copy.js sanitizePlanningText 扩展为三级）
+🟢 auto_fix  = 自动改写（replacement 字段给出替换词）
+🟡 soft_warn = 软提示（返回建议词，不阻塞）
+🔴 hard_block= 硬拦截（直接返回 None，拦住发布）
+
+词库来自数据库 banned_words 表（level + replacement 字段），
+DB 未配时用本模块内置默认词库作冷启动。
+"""
+from __future__ import annotations
+import re
+from dataclasses import dataclass, field
+from typing import Literal
+
+BannedLevel = Literal["auto_fix", "soft_warn", "hard_block"]
+
+
+@dataclass
+class BannedWordEntry:
+    word: str
+    level: BannedLevel
+    replacement: str | None = None  # auto_fix 时提供替换词
+
+
+# ── 默认词库（北哥回填解读与落点 §4.3，数据库未配时使用）─
+DEFAULT_BANNED_WORDS: list[BannedWordEntry] = [
+    # 功效违禁（auto_fix：改写成合规表达，对应北哥"提亮肤色感/改善暗沉观感"）
+    BannedWordEntry("美白", "auto_fix", "提亮肤色感"),
+    BannedWordEntry("祛斑", "auto_fix", "改善暗沉观感"),
+    # 功效违禁（hard_block：无法合规改写，直接拦截）
+    BannedWordEntry("速效", "hard_block"),
+    BannedWordEntry("医用", "hard_block"),
+    BannedWordEntry("药妆", "hard_block"),
+    BannedWordEntry("强效焕白", "hard_block"),
+    # 保证性词（soft_warn）
+    BannedWordEntry("绝对", "soft_warn"),
+    BannedWordEntry("第一名", "soft_warn"),
+    BannedWordEntry("再也不", "soft_warn"),
+    # 夸张词（soft_warn）
+    BannedWordEntry("杀疯了", "soft_warn"),
+    BannedWordEntry("秒杀", "soft_warn"),
+    BannedWordEntry("震撼", "soft_warn"),
+    # AI 味词（auto_fix，置换为口语表达；同时在 _NEGATIVE_WORDS prompt负向约束里已禁止AI写进正文）
+    BannedWordEntry("神器", "auto_fix", "好用的"),
+    BannedWordEntry("福音", "auto_fix", "适合的"),
+    BannedWordEntry("救急单品", "auto_fix", "随手备用的"),
+    BannedWordEntry("遮羞布", "auto_fix", "底妆感"),          # 北哥原文补录
+    BannedWordEntry("不仅而且", "auto_fix", "，另外"),
+    BannedWordEntry("焕发", "auto_fix", "呈现"),
+    BannedWordEntry("守护", "auto_fix", ""),
+    BannedWordEntry("尽享", "auto_fix", "使用"),
+    BannedWordEntry("日常维稳", "auto_fix", "日常保养"),
+    BannedWordEntry("精简底妆", "auto_fix", "轻便底妆"),
+    # 视觉违禁（hard_block，文案含这些词不许过）
+    BannedWordEntry("前后对比", "hard_block"),
+    BannedWordEntry("使用前后", "hard_block"),
+    BannedWordEntry("变白", "auto_fix", "自然光泽感"),
+    BannedWordEntry("瑕疵消失", "auto_fix", "妆感更服帖"),
+]
+
+
+@dataclass
+class CheckResult:
+    text: str                        # 原文（soft_warn/hard_block 场景下保持原文）
+    fixed_text: str | None           # auto_fix 后的文本；其他级别为 None
+    status: Literal["pass", "auto_fixed", "soft_warn", "hard_block"]
+    found: list[dict] = field(default_factory=list)
+    # found 每项: {"word": str, "level": BannedLevel, "replacement": str|None}
+
+
+def check_and_fix(
+    text: str,
+    entries: list[BannedWordEntry] | None = None,
+) -> CheckResult:
+    """
+    对一段文本做三级违禁词扫描。
+    entries：优先用 DB 词条，为 None 时用默认词库。
+    """
+    word_list = entries if entries is not None else DEFAULT_BANNED_WORDS
+    found: list[dict] = []
+    working = text
+
+    # 先扫描所有命中
+    for entry in word_list:
+        if entry.word.lower() in working.lower():
+            found.append({
+                "word": entry.word,
+                "level": entry.level,
+                "replacement": entry.replacement,
+            })
+
+    if not found:
+        return CheckResult(text=text, fixed_text=None, status="pass", found=[])
+
+    # 有 hard_block → 直接拦截
+    if any(f["level"] == "hard_block" for f in found):
+        return CheckResult(text=text, fixed_text=None, status="hard_block", found=found)
+
+    # 只有 soft_warn → 软提示，不改文字
+    if any(f["level"] == "soft_warn" for f in found) and \
+            all(f["level"] in ("soft_warn", "auto_fix") for f in found):
+        # 仍执行 auto_fix 改写，但结果状态是 soft_warn（优先级高）
+        for f in found:
+            if f["level"] == "auto_fix" and f["replacement"] is not None:
+                working = re.sub(re.escape(f["word"]), f["replacement"], working, flags=re.IGNORECASE)
+        return CheckResult(text=text, fixed_text=working, status="soft_warn", found=found)
+
+    # 只有 auto_fix → 自动改写，返回 fixed_text
+    for f in found:
+        if f["level"] == "auto_fix" and f["replacement"] is not None:
+            working = re.sub(re.escape(f["word"]), f["replacement"], working, flags=re.IGNORECASE)
+    return CheckResult(text=text, fixed_text=working, status="auto_fixed", found=found)
+
+
+def build_entries_from_db(rows: list[dict]) -> list[BannedWordEntry]:
+    """把 DB banned_words 行转成 BannedWordEntry 列表"""
+    return [
+        BannedWordEntry(
+            word=r["word"],
+            level=r["level"],
+            replacement=r.get("replacement"),
+        )
+        for r in rows
+        if r.get("word") and r.get("level") in ("auto_fix", "soft_warn", "hard_block")
+    ]