Merge branch 'dev' of http://192.168.0.3:3000/CRBC-MaaS-Platform-Project/LQAgentPlatform into dev

core/construction_review/component/ai_review_engine.py

@@ -788,7 +788,7 @@ class AIReviewEngine(BaseReviewer):
             logger.info("\n[5/5] 生成规范要点覆盖汇总表...")
             analyzer = ResultAnalyzer(str(csv_path))
             processed_results = analyzer.process_results(review_results)
-            spec_summary_csv_path = Path('temp') / 'document_temp' / '3_spec_review_summary.csv'
+            spec_summary_csv_path = Path('temp') / 'document_temp' / 'review_summary.csv'
             summary_rows = analyzer.build_spec_summary(processed_results)
             # logger.info(f"  规范覆盖汇总结果已保存至: {spec_summary_csv_path}")
             summary_rows = pd.DataFrame(summary_rows)
@@ -798,6 +798,8 @@ class AIReviewEngine(BaseReviewer):
             # 生成缺失要点 JSON 列表，便于前端消费
 
             issues = analyzer.build_missing_issue_list(summary_rows)
+            # with open(r'temp\document_temp\2_spec_review_missing_issues.json', 'w', encoding='utf-8') as f:
+            #     json.dump(issues, f, ensure_ascii=False, indent=4)
             # issues["response"] += outline_review_result
             # issues["response"].extend(outline_review_result)
             # 包装成外层格式化期望的结构

core/construction_review/component/reviewers/check_completeness/components/result_analyzer.py

@@ -271,7 +271,7 @@ class ResultAnalyzer(IResultAnalyzer):
             requirement_list = requirement.split('：')[-1].split('；')
             requirement_text = '；'.join([requirement_list[i-1] for i in missing_points])
             issue_point = (
-                f"{row.get('section_label', '')}下缺失{suorces_eum[row.get('标签', '')]}中的【{level2}】内容"
+                f"{row.get('section_label', '')}下缺失{suorces_eum[row.get('标签', '')]}中的【{level2}】内容: {'；'.join([str(index+1)+'.'+str(i.split('.')[-1]) for index, i in enumerate(requirement_list[:-1])])}" if requirement else "补充缺失要点内容"
             )
             suggestion = f"建议补充：{requirement_text}" if requirement else "补充缺失要点内容"
             risk_level = self._map_risk_level(len(missing_points))