feat: add parameter max_workers to StudioBenchmark.execute

* add parameter max_workers to StudioBenchmark.execute
* to allow the control of parallel executions of various runs
   - needed when too many requests clog the inference API
* default set to 10 for simple extension of functionality
* apply linter

Author: AndreiComaneciAA

src/intelligence_layer/evaluation/benchmark/studio_benchmark.py

@@ -98,6 +98,7 @@ def execute(
         description: Optional[str] = None,
         labels: Optional[set[str]] = None,
         metadata: Optional[dict[str, Any]] = None,
+        max_workers: int = 10,
     ) -> str:
         start = datetime.now(timezone.utc)
 
@@ -108,7 +109,11 @@ def execute(
             f"benchmark-{self.id}-runner",
         )
         run_overview = runner.run_dataset(
-            self.dataset_id, description=description, labels=labels, metadata=metadata
+            self.dataset_id,
+            description=description,
+            labels=labels,
+            metadata=metadata,
+            max_workers=max_workers,
         )
 
         evaluation_overview = self.evaluator.evaluate_runs(