scoring updates

llama_stack/apis/scoring_functions/scoring_functions.py

@@ -67,7 +67,7 @@ class AggregationFunctionType(Enum):
     accuracy = "accuracy"
 
 
-class BasicScoringFnParamsFields(BaseModel):
+class BasicScoringFnParams(BaseModel):
     """
     :param aggregation_functions: (Optional) Aggregation functions to apply to the scores of each row. If not provided, no aggregation will be performed.
     """
@@ -78,7 +78,7 @@ class BasicScoringFnParamsFields(BaseModel):
     )
 
 
-class RegexParserScoringFnParamsFields(BaseModel):
+class RegexParserScoringFnParams(BaseModel):
     """
     :param parsing_regexes: (Optional) Regexes to extract the answer from generated response.
     :param aggregation_functions: (Optional) Aggregation functions to apply to the scores of each row. If not provided, no aggregation will be performed.
@@ -93,7 +93,7 @@ class RegexParserScoringFnParamsFields(BaseModel):
         default_factory=list,
     )
 
-class CustomLLMAsJudgeScoringFnParamsFields(BaseModel):
+class CustomLLMAsJudgeScoringFnParams(BaseModel):
     type: Literal["custom_llm_as_judge"] = "custom_llm_as_judge"
     judge_model: str
     prompt_template: Optional[str] = None
@@ -103,103 +103,103 @@ class CustomLLMAsJudgeScoringFnParamsFields(BaseModel):
     )
 
 @json_schema_type
-class RegexParserScoringFnParams(BaseModel):
+class RegexParserScoringFn(BaseModel):
     type: Literal["regex_parser"] = "regex_parser"
-    regex_parser: RegexParserScoringFnParamsFields
+    regex_parser: RegexParserScoringFnParams
 
 
 @json_schema_type
-class RegexParserMathScoringFnParams(BaseModel):
+class RegexParserMathScoringFn(BaseModel):
     type: Literal["regex_parser_math_response"] = "regex_parser_math_response"
-    regex_parser_math_response: RegexParserScoringFnParamsFields
+    regex_parser_math_response: RegexParserScoringFnParams
 
 @json_schema_type
-class EqualityScoringFnParams(BaseModel):
+class EqualityScoringFn(BaseModel):
     type: Literal["equality"] = "equality"
-    equality: BasicScoringFnParamsFields
+    equality: BasicScoringFnParams
 
 @json_schema_type
-class SubsetOfcoringFnParams(BaseModel):
+class SubsetOfScoringFn(BaseModel):
     type: Literal["subset_of"] = "subset_of"
-    subset_of: BasicScoringFnParamsFields
+    subset_of: BasicScoringFnParams
 
 @json_schema_type
-class FactualityScoringFnParams(BaseModel):
+class FactualityScoringFn(BaseModel):
     type: Literal["factuality"] = "factuality"
-    factuality: BasicScoringFnParamsFields
+    factuality: BasicScoringFnParams
 
 @json_schema_type
-class FaithfulnessScoringFnParams(BaseModel):
+class FaithfulnessScoringFn(BaseModel):
     type: Literal["faithfulness"] = "faithfulness"
-    faithfulness: BasicScoringFnParamsFields
+    faithfulness: BasicScoringFnParams
 
 @json_schema_type
-class AnswerCorrectnessScoringFnParams(BaseModel):
+class AnswerCorrectnessScoringFn(BaseModel):
     type: Literal["answer_correctness"] = "answer_correctness"
-    answer_correctness: BasicScoringFnParamsFields
+    answer_correctness: BasicScoringFnParams
 
 @json_schema_type
-class AnswerRelevancyScoringFnParams(BaseModel):
+class AnswerRelevancyScoringFn(BaseModel):
     type: Literal["answer_relevancy"] = "answer_relevancy"
-    answer_relevancy: BasicScoringFnParamsFields
+    answer_relevancy: BasicScoringFnParams
 
 @json_schema_type
-class AnswerSimilarityScoringFnParams(BaseModel):
+class AnswerSimilarityScoringFn(BaseModel):
     type: Literal["answer_similarity"] = "answer_similarity"
-    answer_similarity: BasicScoringFnParamsFields
+    answer_similarity: BasicScoringFnParams
 
 
 @json_schema_type
-class ContextEntityRecallScoringFnParams(BaseModel):
+class ContextEntityRecallScoringFn(BaseModel):
     type: Literal["context_entity_recall"] = "context_entity_recall"
-    context_entity_recall: BasicScoringFnParamsFields
+    context_entity_recall: BasicScoringFnParams
 
 
 @json_schema_type
-class ContextPrecisionScoringFnParams(BaseModel):
+class ContextPrecisionScoringFn(BaseModel):
     type: Literal["context_precision"] = "context_precision"
-    context_precision: BasicScoringFnParamsFields
+    context_precision: BasicScoringFnParams
 
 
 @json_schema_type
-class ContextRecallScoringFnParams(BaseModel):
+class ContextRecallScoringFn(BaseModel):
     type: Literal["context_recall"] = "context_recall"
-    context_recall: BasicScoringFnParamsFields
+    context_recall: BasicScoringFnParams
 
 
 @json_schema_type
-class ContextRelevancyScoringFnParams(BaseModel):
+class ContextRelevancyScoringFn(BaseModel):
     type: Literal["context_relevancy"] = "context_relevancy"
-    context_relevancy: BasicScoringFnParamsFields
+    context_relevancy: BasicScoringFnParams
 
 
 @json_schema_type
-class CustomLLMAsJudgeScoringFnParams(BaseModel):
+class CustomLLMAsJudgeScoringFn(BaseModel):
     type: Literal["custom_llm_as_judge"] = "custom_llm_as_judge"
-    custom_llm_as_judge: CustomLLMAsJudgeScoringFnParamsFields
+    custom_llm_as_judge: CustomLLMAsJudgeScoringFnParams
 
 
-ScoringFnParams = register_schema(
+ScoringFnDefinition = register_schema(
     Annotated[
         Union[
-            CustomLLMAsJudgeScoringFnParams,
-            RegexParserScoringFnParams,
-            RegexParserMathScoringFnParams,
-            EqualityScoringFnParams,
-            SubsetOfcoringFnParams,
-            FactualityScoringFnParams,
-            FaithfulnessScoringFnParams,
-            AnswerCorrectnessScoringFnParams,
-            AnswerRelevancyScoringFnParams,
-            AnswerSimilarityScoringFnParams,
-            ContextEntityRecallScoringFnParams,
-            ContextPrecisionScoringFnParams,
-            ContextRecallScoringFnParams,
-            ContextRelevancyScoringFnParams,
+            CustomLLMAsJudgeScoringFn,
+            RegexParserScoringFn,
+            RegexParserMathScoringFn,
+            EqualityScoringFn,
+            SubsetOfScoringFn,
+            FactualityScoringFn,
+            FaithfulnessScoringFn,
+            AnswerCorrectnessScoringFn,
+            AnswerRelevancyScoringFn,
+            AnswerSimilarityScoringFn,
+            ContextEntityRecallScoringFn,
+            ContextPrecisionScoringFn,
+            ContextRecallScoringFn,
+            ContextRelevancyScoringFn,
         ],
         Field(discriminator="type"),
     ],
-    name="ScoringFnParams",
+    name="ScoringFnDefinition",
 )
 
 
@@ -208,7 +208,7 @@ class CommonScoringFnFields(BaseModel):
     :param fn: The scoring function type and parameters. 
     :param metadata: (Optional) Any additional metadata for this definition (e.g. description).
     """
-    fn: ScoringFnParams
+    fn: ScoringFnDefinition
     metadata: Dict[str, Any] = Field(
         default_factory=dict,
         description="Any additional metadata for this definition (e.g. description)",
@@ -288,7 +288,7 @@ class ScoringFunctions(Protocol):
     @webmethod(route="/scoring-functions", method="POST")
     async def register_scoring_function(
         self,
-        fn: ScoringFnParams,
+        fn: ScoringFnDefinition,
         scoring_fn_id: Optional[str] = None,
         metadata: Optional[Dict[str, Any]] = None,
     ) -> ScoringFn: