fix: compliance optimizer now requires score improvement, retries LLM on failure

Bug: 'passed=True' check for soft quality issues (AI套话, 缺互动引导)
always exits immediately even when LLM failed to make changes.
Score 85 stays 85, content unchanged.

Fix:
1. polish_with_llm: retry once on exception (was: single attempt)
2. main loop: only accept fix when score actually improves AND
   LLM produced output (opt_logs non-empty). If LLM returns same html
   unchanged, treat as failed attempt and retry.

scripts/compliance_optimizer.py

@@ -159,10 +159,12 @@ def fix_tags(html: str, platform: str) -> str:
 def polish_with_llm(html: str, platform: str, remaining_issues: Optional[List[Dict]] = None) -> Tuple[str, Optional[str]]:
     """用 LLM 优化文章内容，返回 (html, log_message_or_None)
     如果指定 remaining_issues，则针对性修复合规问题
+    LLM 失败时自动重试一次
     """
     if not HAVE_LLM:
         return html, None
     llm_cfg = get_llm_config()
+    for attempt in range(2):
         try:
             model = llm_cfg.get('model') if llm_cfg else None
             temperature = llm_cfg.get('temperature', 0.5) if llm_cfg else 0.5
@@ -188,7 +190,9 @@ def polish_with_llm(html: str, platform: str, remaining_issues: Optional[List[Di
                         return polished, f"LLM {tag}"
                 logger.warning(f"LLM 优化输出异常（过短或含建议性文字），保留原文 (len={len(polished)})")
         except Exception as e:
-        logger.warning(f"LLM 优化失败: {e}")
+            logger.warning(f"LLM 优化失败 (尝试 {attempt+1}/2): {e}")
+        if attempt == 0:
+            logger.info(f"重试 LLM 调用...")
     return html, None
 
 def optimize_article(html: str, platform: str, topic_data: Dict, remaining_issues: Optional[List[Dict]] = None) -> Tuple[str, List[str]]:
@@ -263,12 +267,13 @@ def main(topic_ids: List[str] = None):
         if issues:
             current_html = html
             current_issues = list(issues)
+            current_score = score
             for attempt in range(3):
                 optimized_html, opt_logs = optimize_article(current_html, platform_dir, topic_data, current_issues)
                 recheck = check_article(optimized_html, platform_dir, topic_data)
-                if recheck['passed']:
+                if recheck['passed'] and opt_logs and recheck['score'] > current_score:
                     save_article(topic_id, platform_dir, optimized_html)
-                    logger.info(f"✅ {label} 已修复并通过审查 (第{attempt+1}次修复)")
+                    logger.info(f"✅ {label} 已修复并通过审查 (第{attempt+1}次修复) 分数: {current_score}→{recheck['score']}")
                     results.append(OptimizationResult(
                         file=f"db:{platform_dir}_{topic_id}",
                         platform=platform_dir,
@@ -280,11 +285,15 @@ def main(topic_ids: List[str] = None):
                         status="passed"
                     ))
                     break
+                if optimized_html == current_html and not opt_logs:
+                    logger.warning(f"{label} LLM 未输出有效修改（第{attempt+1}次），继续重试...")
+                    continue
                 current_issues = recheck['issues']
                 current_html = optimized_html
+                current_score = recheck['score']
             else:
                 save_article(topic_id, platform_dir, current_html)
-                logger.warning(f"⚠️ {label} 仍有 {len(current_issues)} 个问题未修复，已强制通过")
+                logger.warning(f"⚠️ {label} 仍有 {len(current_issues)} 个问题未修复，已强制通过（当前分 {current_score}）")
                 results.append(OptimizationResult(
                     file=f"db:{platform_dir}_{topic_id}",
                     platform=platform_dir,
@@ -292,7 +301,7 @@ def main(topic_ids: List[str] = None):
                     title=topic_data.get('title',''),
                     original_issues=len(issues),
                     fixed_issues=len(issues) - len(current_issues),
-                    final_score=recheck['score'],
+                    final_score=current_score,
                     status="passed"
                 ))
         else: