From 2505c771925383f2c63bc3b4ff3fd91ff93088a6 Mon Sep 17 00:00:00 2001
From: Stefano Zamboni <stefano.zamboni@radicalbit.ai>
Date: Mon, 28 Oct 2024 14:41:53 +0100
Subject: [PATCH] fix: fixed alerts when importing

---
 api/app/services/model_service.py | 55 ++++++++++++++++---------------
 1 file changed, 28 insertions(+), 27 deletions(-)

diff --git a/api/app/services/model_service.py b/api/app/services/model_service.py
index 710fcf4c..5793e5c5 100644
--- a/api/app/services/model_service.py
+++ b/api/app/services/model_service.py
@@ -137,34 +137,35 @@ def get_last_n_alerts(self, n_alerts) -> List[AlertDTO]:
             latest_reference_dataset, latest_current_dataset = self.get_latest_datasets(
                 model.uuid
             )
-            for perc in ['data_quality', 'model_quality', 'drift']:
-                if count_alerts == n_alerts:
-                    return res
-                if 0 <= metrics.percentages[perc]['value'] < 1:
-                    res.append(
-                        AlertDTO.from_dict(
-                            {
-                                'model_uuid': model.uuid,
-                                'reference_uuid': latest_reference_dataset.uuid
-                                if latest_reference_dataset
-                                else None,
-                                'current_uuid': latest_current_dataset.uuid
-                                if latest_current_dataset
-                                else None,
-                                'anomaly_type': AnomalyType[perc.upper()],
-                                'anomaly_features': [
-                                    x['feature_name']
-                                    for x in sorted(
-                                        metrics.percentages[perc]['details'],
-                                        key=lambda e: e['score'],
-                                        reverse=True,
-                                    )
-                                    if x['score'] > 0
-                                ],
-                            }
+            if metrics:
+                for perc in ['data_quality', 'model_quality', 'drift']:
+                    if count_alerts == n_alerts:
+                        return res
+                    if 0 <= metrics.percentages[perc]['value'] < 1:
+                        res.append(
+                            AlertDTO.from_dict(
+                                {
+                                    'model_uuid': model.uuid,
+                                    'reference_uuid': latest_reference_dataset.uuid
+                                    if latest_reference_dataset
+                                    else None,
+                                    'current_uuid': latest_current_dataset.uuid
+                                    if latest_current_dataset
+                                    else None,
+                                    'anomaly_type': AnomalyType[perc.upper()],
+                                    'anomaly_features': [
+                                        x['feature_name']
+                                        for x in sorted(
+                                            metrics.percentages[perc]['details'],
+                                            key=lambda e: e['score'],
+                                            reverse=True,
+                                        )
+                                        if x['score'] > 0
+                                    ],
+                                }
+                            )
                         )
-                    )
-                    count_alerts += 1
+                        count_alerts += 1
 
         return res