fix: Enhance robustness of issue and quality score processing in the scanner service by adding defensive checks and error handling.

backend/app/services/llm/service.py

@@ -333,16 +333,13 @@ Please analyze the following code:
             # 尝试从响应中提取JSON
             result = self._parse_json(content)
             
+            # 验证和清理结果
+            result = self._validate_analysis_result(result)
+            
             # 记录解析后的问题数量
             issues_count = len(result.get("issues", []))
             logger.info(f"📊 LLM 分析结果: 发现 {issues_count} 个问题, 质量评分: {result.get('quality_score', 'N/A')}")
             
-            # 检查解析结果是否有效（不是默认响应）
-            if result == self._get_default_response():
-                error_msg = f"无法解析LLM响应为有效的分析结果 - Provider: {self.config.provider.value}"
-                logger.error(error_msg)
-                raise Exception(error_msg)
-            
             return result
             
         except Exception as e:
@@ -763,6 +760,54 @@ Please analyze the following code:
         
         raise ValueError(f"json-repair returned unexpected type: {type(repaired)}")
     
+    def _validate_analysis_result(self, result: Dict[str, Any]) -> Dict[str, Any]:
+        """验证和清理分析结果"""
+        if not isinstance(result, dict):
+            logger.warning(f"分析结果不是字典类型: {type(result)}")
+            return self._get_default_response()
+        
+        # 确保 issues 是列表，且每个元素都是字典
+        raw_issues = result.get("issues", [])
+        if not isinstance(raw_issues, list):
+            logger.warning(f"issues 字段不是列表类型: {type(raw_issues)}")
+            raw_issues = []
+            
+        valid_issues = []
+        for i, issue in enumerate(raw_issues):
+            if isinstance(issue, dict):
+                valid_issues.append(issue)
+            else:
+                logger.warning(f"忽略无效的问题格式 (index {i}): {type(issue)}")
+        
+        result["issues"] = valid_issues
+        
+        # 确保 quality_score 是数字
+        score = result.get("quality_score")
+        if score is None or not isinstance(score, (int, float)):
+            try:
+                if score is not None:
+                    result["quality_score"] = int(float(str(score)))
+                else:
+                    result["quality_score"] = 80
+            except (ValueError, TypeError):
+                result["quality_score"] = 80
+                
+        # 确保 summary 和 metrics 存在
+        if "summary" not in result or not isinstance(result["summary"], dict):
+            num_issues = len(valid_issues)
+            result["summary"] = {
+                "total_issues": num_issues,
+                "critical_issues": sum(1 for iss in valid_issues if iss.get("severity") == "critical"),
+                "high_issues": sum(1 for iss in valid_issues if iss.get("severity") == "high"),
+                "medium_issues": sum(1 for iss in valid_issues if iss.get("severity") == "medium"),
+                "low_issues": sum(1 for iss in valid_issues if iss.get("severity") == "low")
+            }
+            
+        if "metrics" not in result or not isinstance(result["metrics"], dict):
+            result["metrics"] = self._get_default_response()["metrics"]
+            
+        return result
+
     def _get_default_response(self) -> Dict[str, Any]:
         """返回默认响应"""
         return {
@@ -915,6 +960,8 @@ Please analyze the following code:
                 raise Exception("LLM返回空响应")
             
             result = self._parse_json(content)
+            # 验证和清理结果
+            result = self._validate_analysis_result(result)
             return result
             
         except Exception as e:

backend/app/services/scanner.py

@@ -680,6 +680,12 @@ async def scan_repo_task(task_id: str, db_session_factory, user_config: dict = N
                         # 保存问题
                         issues = analysis.get("issues", [])
                         for issue in issues:
+                            try:
+                                # 防御性检查：确保 issue 是字典
+                                if not isinstance(issue, dict):
+                                    print(f"⚠️ 警告: 任务 {task_id} 中文件 {f_path} 的分析结果包含无效的问题格式: {issue}")
+                                    continue
+
                                 line_num = issue.get("line", 1)
                                 code_snippet = issue.get("code_snippet")
                                 if not code_snippet or len(code_snippet.strip()) < 5:
@@ -707,9 +713,16 @@ async def scan_repo_task(task_id: str, db_session_factory, user_config: dict = N
                                 )
                                 db.add(audit_issue)
                                 total_issues += 1
+                            except Exception as e:
+                                print(f"⚠️ 处理单个问题时出错 (文件 {f_path}): {e}")
+                                continue
                         
                         if "quality_score" in analysis:
-                            quality_scores.append(analysis["quality_score"])
+                            try:
+                                quality_score = float(analysis["quality_score"])
+                                quality_scores.append(quality_score)
+                            except (ValueError, TypeError):
+                                pass
 
                     # 更新主任务进度
                     processed_count = scanned_files + failed_files