clean up error messaging

Author: ahosler

ads/opctl/operator/lowcode/common/utils.py

@@ -142,6 +142,11 @@ def write_data(data, filename, format, storage_options=None, index=False, **kwar
     )
 
 
+def write_json(json_dict, filename, storage_options=None):
+    with fsspec.open(filename, mode="w", **storage_options) as f:
+        f.write(json.dumps(json_dict))
+
+
 def write_simple_json(data, path):
     if ObjectStorageDetails.is_oci_path(path):
         storage_options = default_signer()

ads/opctl/operator/lowcode/forecast/model/arima.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python
 
-# Copyright (c) 2023, 2024 Oracle and/or its affiliates.
+# Copyright (c) 2023, 2025 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
 import logging
@@ -132,11 +132,12 @@ def _train_model(self, i, s_id, df, model_kwargs):
 
             logger.debug("===========Done===========")
         except Exception as e:
-            self.errors_dict[s_id] = {
+            new_error = {
                 "model_name": self.spec.model,
                 "error": str(e),
                 "error_trace": traceback.format_exc(),
             }
+            self.errors_dict[s_id] = new_error
             logger.warning(f"Encountered Error: {e}. Skipping.")
             logger.warning(traceback.format_exc())
 

ads/opctl/operator/lowcode/forecast/model/automlx.py

@@ -184,12 +184,17 @@ def _build_model(self) -> pd.DataFrame:
                     "selected_model_params": model.selected_model_params_,
                 }
             except Exception as e:
-                self.errors_dict[s_id] = {
+                new_error = {
                     "model_name": self.spec.model,
                     "error": str(e),
                     "error_trace": traceback.format_exc(),
                 }
+                if s_id in self.errors_dict:
+                    self.errors_dict[s_id]["model_fitting"] = new_error
+                else:
+                    self.errors_dict[s_id] = {"model_fitting": new_error}
                 logger.warning(f"Encountered Error: {e}. Skipping.")
+                logger.warning(f"self.errors_dict[s_id]: {self.errors_dict[s_id]}")
                 logger.warning(traceback.format_exc())
 
         logger.debug("===========Forecast Generated===========")

ads/opctl/operator/lowcode/forecast/model/base_model.py

@@ -28,6 +28,7 @@
     merged_category_column_name,
     seconds_to_datetime,
     write_data,
+    write_json,
 )
 from ads.opctl.operator.lowcode.forecast.utils import (
     _build_metrics_df,
@@ -634,17 +635,12 @@ def _save_report(
             f"The outputs have been successfully generated and placed into the directory: {unique_output_dir}."
         )
         if self.errors_dict:
-            write_data(
-                data=pd.DataFrame(
-                    self.errors_dict, index=np.arange(len(self.errors_dict.keys()))
-                ),
+            write_json(
+                json_dict=self.errors_dict,
                 filename=os.path.join(
                     unique_output_dir, self.spec.errors_dict_filename
                 ),
-                format="json",
                 storage_options=storage_options,
-                index=True,
-                indent=4,
             )
             results.set_errors_dict(self.errors_dict)
         else:

ads/opctl/operator/lowcode/forecast/model/neuralprophet.py

@@ -229,7 +229,6 @@ def _build_model(self) -> pd.DataFrame:
         self.models = {}
         self.trainers = {}
         self.outputs = {}
-        self.errors_dict = {}
         self.explanations_info = {}
         self.accepted_regressors = {}
         self.additional_regressors = self.datasets.get_additional_data_column_names()

tests/operators/forecast/test_errors.py

@@ -255,7 +255,7 @@ def setup_rossman():
 
 def setup_faulty_rossman():
     curr_dir = pathlib.Path(__file__).parent.resolve()
-    data_folder = f"{curr_dir}/../data/"
+    data_folder = f"{curr_dir}/../data"
     historical_data_path = f"{data_folder}/rs_2_prim.csv"
     additional_data_path = f"{data_folder}/rs_2_add_encoded.csv"
     return historical_data_path, additional_data_path
@@ -707,10 +707,10 @@ def test_arima_automlx_errors(operator_setup, model):
             error_content = json.load(error_file)
             assert (
                 "Input data does not have a consistent (in terms of diff) DatetimeIndex."
-                in error_content["13"]["error"]
-            ), "Error message mismatch"
+                in error_content["13"]["model_fitting"]["error"]
+            ), f"Error message mismatch: {error_content}"
 
-    if model not in ["autots"]:  # , "lgbforecast"
+    if model not in ["autots", "automlx"]:  # , "lgbforecast"
         if yaml_i["spec"].get("explanations_accuracy_mode") != "AUTOMLX":
             global_fn = f"{tmpdirname}/results/global_explanation.csv"
             assert os.path.exists(