ci: Enable black check for evaluation SDK (#37305)

* chore: set black=true

* style: Run black

Author: kdestin

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/_common/constants.py

@@ -62,4 +62,4 @@ class _InternalEvaluationMetrics:
     enum over time.
     """
 
-    ECI = "eci"
+    ECI = "eci"

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/_common/rai_service.py

@@ -447,4 +447,4 @@ async def evaluate_with_rai_service(
     annotation_response = await fetch_result(operation_id, rai_svc_url, credential, token)
     result = parse_response(annotation_response, metric_name)
 
-    return result
+    return result

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/_common/utils.py

@@ -52,4 +52,4 @@ def nltk_tokenize(text: str) -> List[str]:
         # By default, use NLTK word tokenizer
         tokens = nltk.word_tokenize(text)
 
-    return list(tokens)
+    return list(tokens)

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/_constants.py

@@ -46,4 +46,4 @@ class Prefixes:
 PF_BATCH_TIMEOUT_SEC = "PF_BATCH_TIMEOUT_SEC"
 
 OTEL_EXPORTER_OTLP_TRACES_TIMEOUT = "OTEL_EXPORTER_OTLP_TRACES_TIMEOUT"
-OTEL_EXPORTER_OTLP_TRACES_TIMEOUT_DEFAULT = 60
+OTEL_EXPORTER_OTLP_TRACES_TIMEOUT_DEFAULT = 60

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/evaluate/_eval_run.py

@@ -380,7 +380,7 @@ def log_artifact(self, artifact_folder: str, artifact_name: str = EVALUATION_ART
         remote_paths = {"paths": []}
         local_paths = []
         # Go over the artifact folder and upload all artifacts.
-        for (root, _, filenames) in os.walk(artifact_folder):
+        for root, _, filenames in os.walk(artifact_folder):
             upload_path = root_upload_path
             if root != artifact_folder:
                 rel_path = os.path.relpath(root, artifact_folder)

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/evaluate/_evaluate.py

@@ -481,9 +481,9 @@ def _evaluate(  # pylint: disable=too-many-locals
 
     # Target Run
     pf_client = PFClient(
-        config={"trace.destination": _trace_destination_from_project_scope(azure_ai_project)}
-        if azure_ai_project
-        else None,
+        config=(
+            {"trace.destination": _trace_destination_from_project_scope(azure_ai_project)} if azure_ai_project else None
+        ),
         user_agent=USER_AGENT,
     )
 
@@ -601,4 +601,4 @@ def _evaluate(  # pylint: disable=too-many-locals
     if output_path:
         _write_output(output_path, result)
 
-    return result
+    return result

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/evaluate/_telemetry/__init__.py

@@ -111,9 +111,11 @@ def wrapper(*args, **kwargs) -> Callable:
         azure_ai_project = kwargs.get("azure_ai_project", None)
 
         pf_client = PFClient(
-            config={"trace.destination": _trace_destination_from_project_scope(azure_ai_project)}
-            if azure_ai_project
-            else None,
+            config=(
+                {"trace.destination": _trace_destination_from_project_scope(azure_ai_project)}
+                if azure_ai_project
+                else None
+            ),
             user_agent=USER_AGENT,
         )
 

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/evaluators/__init__.py

@@ -46,4 +46,4 @@
     "RougeScoreEvaluator",
     "RougeType",
     "ProtectedMaterialEvaluator",
-]
+]

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/evaluators/_eci/_eci.py

@@ -87,4 +87,4 @@ def __call__(self, *, question: str, answer: str, **kwargs):
         return async_run_allowing_running_loop(self._async_evaluator, question=question, answer=answer, **kwargs)
 
     def _to_async(self):
-        return self._async_evaluator
+        return self._async_evaluator

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/evaluators/_xpia/xpia.py

@@ -122,4 +122,4 @@ def __call__(self, *, question: str, answer: str, **kwargs):
         return async_run_allowing_running_loop(self._async_evaluator, question=question, answer=answer, **kwargs)
 
     def _to_async(self):
-        return self._async_evaluator
+        return self._async_evaluator