feat: [New Eval Benchamark] IfEval (#1708)

# What does this PR do?
In this PR, we added a new eval open benchmark IfEval based on paper
https://arxiv.org/abs/2311.07911 to measure the model capability of
instruction following.


## Test Plan
spin up a llama stack server with open-benchmark template

run `llama-stack-client --endpoint xxx eval run-benchmark
"meta-reference-ifeval" --model-id "meta-llama/Llama-3.3-70B-Instruct"
--output-dir "/home/markchen1015/" --num-examples 20` on client side and
get the eval aggregate results

llama_stack/providers/utils/scoring/aggregation_utils.py

@@ -28,6 +28,17 @@ def aggregate_average(scoring_results: List[ScoringResultRow]) -> Dict[str, Any]
     }
 
 
+def aggregate_weighted_average(scoring_results: List[ScoringResultRow]) -> Dict[str, Any]:
+    return {
+        "weighted_average": sum(
+            result["score"] * result["weight"]
+            for result in scoring_results
+            if result["score"] is not None and result["weight"] is not None
+        )
+        / sum(result["weight"] for result in scoring_results if result["weight"] is not None),
+    }
+
+
 def aggregate_categorical_count(
     scoring_results: List[ScoringResultRow],
 ) -> Dict[str, Any]:
@@ -46,6 +57,7 @@ def aggregate_median(scoring_results: List[ScoringResultRow]) -> Dict[str, Any]:
 AGGREGATION_FUNCTIONS = {
     AggregationFunctionType.accuracy: aggregate_accuracy,
     AggregationFunctionType.average: aggregate_average,
+    AggregationFunctionType.weighted_average: aggregate_weighted_average,
     AggregationFunctionType.categorical_count: aggregate_categorical_count,
     AggregationFunctionType.median: aggregate_median,
 }