fix(step8): 修复外部模型字典透传断链 + 规范化 loaded_model_data 防 Ridge subscriptable 崩溃

src/core/steps/prediction_step.py

@@ -118,6 +118,8 @@ class PredictionStep:
         print("\n" + "=" * 80)
         print("步骤8: 预测水质参数")
         print("=" * 80)
+        print(f"[PredictionStep] 准备执行预测，字典状态: {'Yes' if _external_models_dict else 'No'}"
+              f", 单模型状态: {'Yes' if _external_model else 'No'}")
 
         step_start_time = time.time()
 
@@ -153,8 +155,10 @@ class PredictionStep:
                 else:
                     print(f"检测到部分预测结果文件，缺少: {missing_targets}，将继续生成...")
 
+        all_results = {}
+
         if _external_models_dict:
-            # 外部模型字典优先：每个 {subdir_name: model_obj} 对应一个水质参数，
+            # 外部模型字典优先：直接用字典的 keys 作为 targets 列表，
             # 手动为每个模型创建 inference 实例并调用 inference_pipeline。
             print(f"\n使用外部导入模型字典（{len(_external_models_dict)} 个模型）...")
             for target_name, model_obj in _external_models_dict.items():
@@ -172,11 +176,18 @@ class PredictionStep:
                         prediction_column=prediction_column,
                     )
                     prediction_files[target_name] = str(output_file)
+                    all_results[target_name] = {
+                        "status": "success",
+                        "output_file": str(output_file),
+                        "sample_count": len(predictions),
+                    }
                     print(f"  ✓ {target_name}: {len(predictions)} 个预测值")
                 except Exception as e:
                     print(f"  ✗ {target_name}: 失败 — {type(e).__name__}: {e}")
                     prediction_files[target_name] = None
+                    all_results[target_name] = {"status": "error", "error": str(e)}
         else:
+            # 字典为空或不存在：回退到扫描 models_dir 子目录的传统逻辑
             inferencer = WaterQualityInference(
                 models_dir,
                 external_model=_external_model,
@@ -191,10 +202,13 @@ class PredictionStep:
                 output_format="csv",
                 external_model=_external_model,
                 external_model_path=_external_model_path,
+                external_models_dict=_external_models_dict,
             )
-            for target_name, result in all_results.items():
-                if result.get("status") == "success":
-                    prediction_files[target_name] = result["output_file"]
+            # batch_inference_multi_models 已确保返回字典，永不返回 None
+            if all_results:
+                for target_name, result in all_results.items():
+                    if result.get("status") == "success":
+                        prediction_files[target_name] = result["output_file"]
 
         print(f"预测完成，结果保存在: {ml_prediction_dir}")