refactor

llama_stack/providers/inline/scoring/basic/scoring_fn/equality_scoring_fn.py

@@ -8,7 +8,7 @@ from typing import Any, Dict, List, Optional
 
 from llama_stack.apis.scoring import ScoringResultRow
 
-from llama_stack.apis.scoring_functions import AggregationFunctionType, ScoringFnParams
+from llama_stack.apis.scoring_functions import ScoringFnParams
 from llama_stack.providers.utils.scoring.aggregation_utils import aggregate_metrics
 from llama_stack.providers.utils.scoring.base_scoring_fn import BaseScoringFn
 
@@ -54,7 +54,7 @@ class EqualityScoringFn(BaseScoringFn):
         if scoring_params is not None:
             params = scoring_params
 
-        aggregation_functions = [AggregationFunctionType.accuracy]
+        aggregation_functions = []
         if (
             params
             and hasattr(params, "aggregation_functions")

llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/equality.py

@@ -5,14 +5,20 @@
 # the root directory of this source tree.
 
 from llama_stack.apis.common.type_system import NumberType
-from llama_stack.apis.scoring_functions import ScoringFn
+from llama_stack.apis.scoring_functions import (
+    AggregationFunctionType,
+    BasicScoringFnParams,
+    ScoringFn,
+)
 
 
 equality = ScoringFn(
     identifier="basic::equality",
     description="Returns 1.0 if the input is equal to the target, 0.0 otherwise.",
-    params=None,
     provider_id="basic",
     provider_resource_id="equality",
     return_type=NumberType(),
+    params=BasicScoringFnParams(
+        aggregation_functions=[AggregationFunctionType.accuracy]
+    ),
 )

llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/regex_parser_multiple_choice_answer.py

@@ -4,9 +4,12 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from llama_stack.apis.scoring_functions import *  # noqa: F401, F403
-from llama_stack.apis.scoring import *  # noqa: F401, F403
 from llama_stack.apis.common.type_system import NumberType
+from llama_stack.apis.scoring_functions import (
+    AggregationFunctionType,
+    RegexParserScoringFnParams,
+    ScoringFn,
+)
 
 MULTILINGUAL_ANSWER_REGEXES = [
     r"Answer\s*:",
@@ -67,5 +70,6 @@ regex_parser_multiple_choice_answer = ScoringFn(
             MULTILINGUAL_ANSWER_PATTERN_TEMPLATE.format(x)
             for x in MULTILINGUAL_ANSWER_REGEXES
         ],
+        aggregation_functions=[AggregationFunctionType.accuracy],
     ),
 )

llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/subset_of.py

@@ -5,7 +5,11 @@
 # the root directory of this source tree.
 
 from llama_stack.apis.common.type_system import NumberType
-from llama_stack.apis.scoring_functions import ScoringFn
+from llama_stack.apis.scoring_functions import (
+    AggregationFunctionType,
+    BasicScoringFnParams,
+    ScoringFn,
+)
 
 
 subset_of = ScoringFn(
@@ -14,4 +18,7 @@ subset_of = ScoringFn(
     return_type=NumberType(),
     provider_id="basic",
     provider_resource_id="subset-of",
+    params=BasicScoringFnParams(
+        aggregation_functions=[AggregationFunctionType.accuracy]
+    ),
 )

llama_stack/providers/inline/scoring/basic/scoring_fn/regex_parser_scoring_fn.py

@@ -8,11 +8,7 @@ import re
 from typing import Any, Dict, List, Optional
 
 from llama_stack.apis.scoring import ScoringResultRow
-from llama_stack.apis.scoring_functions import (
-    AggregationFunctionType,
-    ScoringFnParams,
-    ScoringFnParamsType,
-)
+from llama_stack.apis.scoring_functions import ScoringFnParams, ScoringFnParamsType
 from llama_stack.providers.utils.scoring.aggregation_utils import aggregate_metrics
 from llama_stack.providers.utils.scoring.base_scoring_fn import BaseScoringFn
 
@@ -76,7 +72,7 @@ class RegexParserScoringFn(BaseScoringFn):
         if scoring_params is not None:
             params = scoring_params
 
-        aggregation_functions = [AggregationFunctionType.accuracy]
+        aggregation_functions = []
         if (
             params
             and hasattr(params, "aggregation_functions")

llama_stack/providers/inline/scoring/basic/scoring_fn/subset_of_scoring_fn.py

@@ -7,7 +7,7 @@
 from typing import Any, Dict, List, Optional
 
 from llama_stack.apis.scoring import ScoringResultRow
-from llama_stack.apis.scoring_functions import AggregationFunctionType, ScoringFnParams
+from llama_stack.apis.scoring_functions import ScoringFnParams
 from llama_stack.providers.utils.scoring.aggregation_utils import aggregate_metrics
 from llama_stack.providers.utils.scoring.base_scoring_fn import BaseScoringFn
 
@@ -48,7 +48,7 @@ class SubsetOfScoringFn(BaseScoringFn):
         if scoring_params is not None:
             params = scoring_params
 
-        aggregation_functions = [AggregationFunctionType.accuracy]
+        aggregation_functions = []
         if (
             params
             and hasattr(params, "aggregation_functions")

llama_stack/providers/inline/scoring/braintrust/braintrust.py

@@ -147,7 +147,7 @@ class BraintrustScoringImpl(
                 await self.score_row(input_row, scoring_fn_id)
                 for input_row in input_rows
             ]
-
+            aggregation_functions = [AggregationFunctionType.average]
             agg_results = aggregate_average(score_results)
             res[scoring_fn_id] = ScoringResult(
                 score_rows=score_results,

llama_stack/providers/utils/scoring/base_scoring_fn.py

@@ -12,7 +12,7 @@ from llama_stack.apis.scoring_functions import ScoringFn
 
 class BaseScoringFn(ABC):
     """
-    Base interface class for all meta-reference scoring_fns.
+    Base interface class for all native scoring_fns.
     Each scoring_fn needs to implement the following methods:
     - score_row(self, row)
     - aggregate(self, scoring_fn_results)
@@ -20,7 +20,6 @@ class BaseScoringFn(ABC):
 
     def __init__(self, *args, **kwargs) -> None:
         super().__init__(*args, **kwargs)
-        self.supported_fn_defs_registry = {}
 
     def __str__(self) -> str:
         return self.__class__.__name__