added test cases and PR review comments

agrimk · agrimk · commit 83dc9fc9852f · 2025-07-05T21:51:12.000+05:30
diff --git a/ads/aqua/modeldeployment/deployment.py b/ads/aqua/modeldeployment/deployment.py
@@ -763,7 +763,6 @@ def _create_deployment(
             target=self.get_deployment_status,
             args=(
                 deployment,
-                deployment_id,
                 deployment.dsc_model_deployment.workflow_req_id,
                 model_type,
                 model_name,
@@ -1269,8 +1268,7 @@ def list_shapes(self, **kwargs) -> List[ComputeShapeSummary]:
 
     def get_deployment_status(
         self,
-        deployment,
-        model_deployment_id: str,
+        deployment: ModelDeployment,
         work_request_id: str,
         model_type: str,
         model_name: str,
@@ -1292,27 +1290,23 @@ def get_deployment_status(
         AquaDeployment
             An Aqua deployment instance.
         """
-        ocid = get_ocid_substring(model_deployment_id, key_len=8)
-
+        ocid = get_ocid_substring(deployment.id, key_len=8)
         data_science_work_request: DataScienceWorkRequest = DataScienceWorkRequest(
             work_request_id
         )
-
         try:
             data_science_work_request.wait_work_request(
                 progress_bar_description="Creating model deployment",
                 max_wait_time=DEFAULT_WAIT_TIME,
                 poll_interval=DEFAULT_POLL_INTERVAL,
             )
-        except Exception as e:
+        except Exception:
             status = ""
-            predict_logs = deployment.tail_logs("predict")
-            access_logs = deployment.tail_logs("access")
-            if access_logs and len(access_logs) > 0:
-                status = access_logs[0]["message"]
+            logs = deployment.show_logs().sort_values(by="time", ascending=False)
+
+            if logs and len(logs) > 0:
+                status = logs.iloc[0]["message"]
 
-            if predict_logs and len(predict_logs) > 0:
-                status += predict_logs[0]["message"]
             status = re.sub(r"[^a-zA-Z0-9]", " ", status)
 
             if data_science_work_request._error_message:
@@ -1324,7 +1318,8 @@ def get_deployment_status(
                 telemetry_kwargs = {
                     "ocid": ocid,
                     "model_name": model_name,
-                    "status": error_str + " " + status,
+                    "work_request_error": error_str,
+                    "status": status,
                 }
 
                 self.telemetry.record_event(
@@ -1333,7 +1328,6 @@ def get_deployment_status(
                     **telemetry_kwargs,
                 )
             else:
-                status = +" " + str(e)
                 telemetry_kwargs = {
                     "ocid": ocid,
                     "model_name": model_name,
diff --git a/ads/common/oci_logging.py b/ads/common/oci_logging.py
@@ -863,47 +863,6 @@ def tail(
         )
         self._print(sorted(tail_logs, key=lambda log: log["time"]))
 
-    def get_tail_logs(
-        self,
-        source: str = None,
-        limit: int = LOG_RECORDS_LIMIT,
-        time_start: datetime.datetime = None,
-        log_filter: str = None,
-    ) -> List[Union[oci.loggingsearch.models.SearchResult, dict]]:
-        """Returns the most recent consolidated log records.
-
-        Parameters
-        ----------
-        source : str, optional
-            Expression or OCID to filter the "source" field of the OCI log record.
-            Defaults to None.
-        limit : int, optional.
-            Maximum number of records to be returned.
-            If limit is set to None, all logs from time_start to now will be returned.
-            Defaults to 100.
-        time_start : datetime.datetime, optional
-            Starting time for the log query.
-            Defaults to None.
-        log_filter : str, optional
-            Expression for filtering the logs. This will be the WHERE clause of the query.
-            Defaults to None.
-
-        Returns
-        -------
-        list
-            A list of oci.loggingsearch.models.SearchResult objects or log records sorted in descending order by time
-            Each log record is a dictionary with the following keys: `annotation`, `id`, `time`,
-            `message` and `datetime`.
-        """
-        tail_logs = self._search_and_format(
-            source=source,
-            limit=limit,
-            sort_order=SortOrder.DESC,
-            time_start=time_start,
-            log_filter=log_filter,
-        )
-        return sorted(tail_logs, key=lambda log: log["time"])
-
     def head(
         self,
         source: str = None,
diff --git a/ads/model/deployment/model_deployment.py b/ads/model/deployment/model_deployment.py
@@ -729,44 +729,6 @@ def update(
 
         return self._update_from_oci_model(response)
 
-    def tail_logs(
-        self, log_type: str = None, time_start: datetime = None, log_filter: str = None
-    ) -> List[Union[oci.loggingsearch.models.SearchResult, dict]]:
-        """Returns the most recent consolidated log records for the model deployment
-
-        Parameters
-        ----------
-        source : str, optional
-            Expression or OCID to filter the "source" field of the OCI log record.
-            Defaults to None.
-        limit : int, optional.
-            Maximum number of records to be returned.
-            If limit is set to None, all logs from time_start to now will be returned.
-            Defaults to 100.
-        time_start : datetime.datetime, optional
-            Starting time for the log query.
-            Defaults to None.
-        log_filter : str, optional
-            Expression for filtering the logs. This will be the WHERE clause of the query.
-            Defaults to None.
-
-        Returns
-        -------
-        list
-            A list of oci.loggingsearch.models.SearchResult objects or log records sorted in descending order by time
-            Each log record is a dictionary with the following keys: `annotation`, `id`, `time`,
-            `message` and `datetime`.
-        """
-        try:
-            logs = self.logs(log_type).get_tail_logs(
-                source=self.model_deployment_id,
-                time_start=time_start,
-                log_filter=log_filter,
-            )
-            return logs
-        except LogNotConfiguredError:
-            return []
-
     def watch(
         self,
         log_type: str = None,
diff --git a/tests/unitary/with_extras/aqua/test_deployment.py b/tests/unitary/with_extras/aqua/test_deployment.py
@@ -2368,34 +2368,84 @@ def test_validate_multimodel_deployment_feasibility_positive_single(
             "test_data/deployment/aqua_summary_multi_model_single.json",
         )
 
-    def test_get_deployment_status(self):
+    def test_get_deployment_status_success(self):
         model_deployment = copy.deepcopy(TestDataset.model_deployment_object[0])
         deployment_id = "fakeid.datasciencemodeldeployment.oc1.iad.xxx"
         work_request_id = "fakeid.workrequest.oc1.iad.xxx"
         model_type = "custom"
         model_name = "model_name"
 
         with patch(
-            "ads.model.service.oci_datascience_model_deployment.DataScienceWorkRequest.__init__"
-        ) as mock_ds_work_request:
-            mock_ds_work_request.return_value = None
-            with patch(
-                "ads.model.service.oci_datascience_model_deployment.DataScienceWorkRequest.wait_work_request"
-            ) as mock_wait:
-                self.app.get_deployment_status(
-                    model_deployment,
-                    deployment_id,
-                    work_request_id,
-                    model_type,
-                    model_name,
-                )
+            "ads.model.service.oci_datascience_model_deployment.DataScienceWorkRequest.__init__",
+            return_value=None,
+        ) as mock_ds_work_request, patch(
+            "ads.model.service.oci_datascience_model_deployment.DataScienceWorkRequest.wait_work_request"
+        ) as mock_wait:
+            self.app.get_deployment_status(
+                oci.data_science.models.ModelDeploymentSummary(**model_deployment),
+                work_request_id,
+                model_type,
+                model_name,
+            )
 
-                mock_ds_work_request.assert_called_with(work_request_id)
-                mock_wait.assert_called_with(
-                    progress_bar_description="Creating model deployment",
-                    max_wait_time=DEFAULT_WAIT_TIME,
-                    poll_interval=DEFAULT_POLL_INTERVAL,
-                )
+            mock_ds_work_request.assert_called_once_with(work_request_id)
+            mock_wait.assert_called_once_with(
+                progress_bar_description="Creating model deployment",
+                max_wait_time=DEFAULT_WAIT_TIME,
+                poll_interval=DEFAULT_POLL_INTERVAL,
+            )
+
+    def raise_exception(*args, **kwargs):
+        raise Exception("Work request failed")
+
+    def test_get_deployment_status_failed(self):
+        model_deployment = copy.deepcopy(TestDataset.model_deployment_object[0])
+        deployment_id = "fakeid.datasciencemodeldeployment.oc1.iad.xxx"
+        work_request_id = "fakeid.workrequest.oc1.iad.xxx"
+        model_type = "custom"
+        model_name = "model_name"
+        with patch(
+            "ads.telemetry.client.TelemetryClient.record_event"
+        ) as mock_record_event, patch(
+            "ads.aqua.modeldeployment.deployment.DataScienceWorkRequest"
+        ) as mock_ds_work_request_class, patch(
+            "ads.model.deployment.model_deployment.ModelDeployment.show_logs"
+        ) as mock_show_log:
+            mock_ds_work_request_instance = MagicMock()
+            mock_ds_work_request_class.return_value = mock_ds_work_request_instance
+
+            mock_ds_work_request_instance._error_message = [
+                MagicMock(message="Some error occurred")
+            ]
+
+            mock_ds_work_request_instance.wait_work_request.side_effect = (
+                self.raise_exception
+            )
+
+            logs_df = MagicMock()
+            logs_df.sort_values.return_value = logs_df
+            logs_df.empty = False
+            logs_df.iloc.__getitem__.return_value = {
+                "message": "Error: deployment failed!"
+            }
+            mock_show_log.return_value = logs_df
+
+            self.app.get_deployment_status(
+                ModelDeployment(),
+                work_request_id,
+                model_type,
+                model_name,
+            )
+            mock_record_event.assert_called_once()
+            args, kwargs = mock_record_event.call_args
+            self.assertEqual(kwargs["category"], f"aqua/{model_type}/deployment/status")
+            self.assertEqual(kwargs["action"], "FAILED")
+            self.assertIn("work_request_error", kwargs)
+            self.assertIn("status", kwargs)
+            self.assertIn("ocid", kwargs)
+            self.assertIn("model_name", kwargs)
+
+            mock_ds_work_request_class.assert_called_once_with(work_request_id)
 
 
 class TestBaseModelSpec:
