Add custom error reporting to labeling service

Author: Val Brodsky

libs/labelbox/src/labelbox/client.py

@@ -164,6 +164,13 @@ def execute(
             files (dict): file arguments for request
             timeout (float): Max allowed time for query execution,
                 in seconds.
+            raise_return_resource_not_found: By default the client relies on the caller to raise the correct exception when a resource is not found.
+                If this is set to True, the client will raise a ResourceNotFoundError exception automatically.
+                This simplifies processing.
+                We recommend to use it only of api returns a clear and well-formed error when a resource not found for a given query.
+            error_handlers (dict): A dictionary mapping graphql error code to handler functions.
+                Allows a caller to handle specific errors reporting in a custom way or produce more user-friendly readable messages.
+
         Returns:
             dict, parsed JSON response.
         Raises:

libs/labelbox/src/labelbox/schema/labeling_service.py

@@ -1,9 +1,10 @@
 from datetime import datetime
 from enum import Enum
+import json
 from typing import Any
 from typing_extensions import Annotated
 
-from labelbox.exceptions import ResourceNotFoundError
+from labelbox.exceptions import LabelboxError, ResourceNotFoundError
 
 from labelbox.pydantic_compat import BaseModel, Field
 from labelbox.utils import _CamelCaseMixin
@@ -87,12 +88,29 @@ def request(self) -> 'LabelingService':
         }
         """
         result = self.client.execute(query_str, {"projectId": self.project_id},
-                                     raise_return_resource_not_found=True)
+                                     raise_return_resource_not_found=True,
+                                     error_handlers={
+                                         "INTERNAL_SERVER_ERROR":
+                                             self._raise_readable_errors
+                                     })
         success = result["validateAndRequestProjectBoostWorkforce"]["success"]
         if not success:
             raise Exception("Failed to start labeling service")
         return LabelingService.get(self.client, self.project_id)
 
+    def _raise_readable_errors(self, response):
+        errors = response.json().get('errors', [])
+        if errors:
+            message = errors[0].get(
+                'message', json.dumps([{
+                    "errorMessage": "Unknown error"
+                }]))
+            errors = json.loads(message)
+            error_messages = [error['errorMessage'] for error in errors]
+        else:
+            error_messages = ["Uknown error"]
+        raise LabelboxError(". ".join(error_messages))
+
     @classmethod
     def getOrCreate(cls, client, project_id: Cuid) -> 'LabelingService':
         """

libs/labelbox/tests/integration/test_labeling_service.py

@@ -42,11 +42,8 @@ def test_request_labeling_service_moe_project(
     project.upsert_instructions('tests/integration/media/sample_pdf.pdf')
 
     labeling_service = project.get_labeling_service()
-    with pytest.raises(
-            LabelboxError,
-            match=
-            '[{"errorType":"PROJECT_MODEL_CONFIG","errorMessage":"Project model config is not completed"}]'
-    ):
+    with pytest.raises(LabelboxError,
+                       match='Project model config is not completed'):
         labeling_service.request()
     project.add_model_config(model_config.uid)
     project.set_project_model_setup_complete()
@@ -64,5 +61,8 @@ def test_request_labeling_service_incomplete_requirements(ontology, project):
                       ):  # No labeling service by default
         labeling_service.request()
     project.connect_ontology(ontology)
-    with pytest.raises(LabelboxError):
+    with pytest.raises(
+            LabelboxError,
+            match=
+            "['Data is missing', 'Ontology instructions are not completed']"):
         labeling_service.request()