fix tests after registration migration & rename meta-reference -> basic / llm_as_judge provider (#424)

* rename meta-reference -> basic

* config rename

* impl rename

* rename llm_as_judge, fix test

* util

* rebase

* naming fix

llama_stack/providers/utils/scoring/base_scoring_fn.py

@@ -0,0 +1,62 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+from abc import ABC, abstractmethod
+from typing import Any, Dict, List, Optional
+
+from llama_stack.apis.scoring import ScoringFnParams, ScoringResultRow
+from llama_stack.apis.scoring_functions import ScoringFn
+
+
+class BaseScoringFn(ABC):
+    """
+    Base interface class for all meta-reference scoring_fns.
+    Each scoring_fn needs to implement the following methods:
+    - score_row(self, row)
+    - aggregate(self, scoring_fn_results)
+    """
+
+    def __init__(self, *args, **kwargs) -> None:
+        super().__init__(*args, **kwargs)
+        self.supported_fn_defs_registry = {}
+
+    def __str__(self) -> str:
+        return self.__class__.__name__
+
+    def get_supported_scoring_fn_defs(self) -> List[ScoringFn]:
+        return [x for x in self.supported_fn_defs_registry.values()]
+
+    def register_scoring_fn_def(self, scoring_fn: ScoringFn) -> None:
+        if scoring_fn.identifier in self.supported_fn_defs_registry:
+            raise ValueError(
+                f"Scoring function def with identifier {scoring_fn.identifier} already exists."
+            )
+        self.supported_fn_defs_registry[scoring_fn.identifier] = scoring_fn
+
+    @abstractmethod
+    async def score_row(
+        self,
+        input_row: Dict[str, Any],
+        scoring_fn_identifier: Optional[str] = None,
+        scoring_params: Optional[ScoringFnParams] = None,
+    ) -> ScoringResultRow:
+        raise NotImplementedError()
+
+    @abstractmethod
+    async def aggregate(
+        self, scoring_results: List[ScoringResultRow]
+    ) -> Dict[str, Any]:
+        raise NotImplementedError()
+
+    async def score(
+        self,
+        input_rows: List[Dict[str, Any]],
+        scoring_fn_identifier: Optional[str] = None,
+        scoring_params: Optional[ScoringFnParams] = None,
+    ) -> List[ScoringResultRow]:
+        return [
+            await self.score_row(input_row, scoring_fn_identifier, scoring_params)
+            for input_row in input_rows
+        ]