fixed CI errors

Signed-off-by: dafnapension <dafnashein@yahoo.com>

src/unitxt/metrics.py

@@ -429,7 +429,7 @@ def metric(sample: List[Dict[str, Any]]):
 
             # resample the instance scores, and then return the global score each time
             scores = numpy.apply_along_axis(
-                lambda x: metric(x),
+                lambda x: metric(sample=[instances[i] for i in x]),
                 axis=axis,
                 arr=arr,
             )
@@ -566,6 +566,8 @@ def compute_stream_score(
     def compute_stream_score_version_for_ci(
         self, instances: List[Dict[str, Any]], score_name: str
     ) -> dict:
+        if score_name is None or not isinstance(score_name, str):
+            score_name = self.main_score
         full_score = self.compute_stream_score(instances, [score_name])
         return full_score[score_name]
 
@@ -886,6 +888,8 @@ def process(self, stream: Stream, stream_name: Optional[str] = None) -> Generato
         global_score.update(
             self.compute_stream_score(instances=instances, score_names=self.score_names)
         )
+        global_score["score"] = global_score[self.main_score]
+        global_score["score_name"] = self.main_score
 
         ci_fields = (
             list(set(self.ci_scores))

tests/library/test_metrics.py

@@ -217,7 +217,7 @@ def test_accuracy_max_aggregation(self):
             for key, value in global_result.items()
             if key in expected_global_result
         }
-        self.assertDictEqual(expected_global_result, global_result)
+        self.assertDictEqual(global_result, expected_global_result)
 
         instance_targets = [
             {"accuracy": 0.0, "score": 0.0, "score_name": "accuracy"},