test_scoring

llama_stack/providers/impls/meta_reference/scoring/__init__.py

@@ -0,0 +1,18 @@
+# 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 .config import MetaReferenceScoringConfig
+
+
+async def get_provider_impl(
+    config: MetaReferenceScoringConfig,
+    _deps,
+):
+    from .scoring import MetaReferenceScoringImpl
+
+    impl = MetaReferenceScoringImpl(config)
+    await impl.initialize()
+    return impl

llama_stack/providers/impls/meta_reference/scoring/config.py

@@ -0,0 +1,9 @@
+# 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 llama_stack.apis.scoring import *  # noqa: F401, F403
+
+
+class MetaReferenceScoringConfig(BaseModel): ...

llama_stack/providers/impls/meta_reference/scoring/scoring.py

@@ -0,0 +1,33 @@
+# 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 typing import List
+
+from llama_models.llama3.api.datatypes import *  # noqa: F403
+from llama_stack.apis.scoring import *  # noqa: F403
+
+from llama_stack.providers.datatypes import ScoringFunctionsProtocolPrivate
+
+from .config import MetaReferenceScoringConfig
+
+
+class MetaReferenceScoringImpl(Scoring, ScoringFunctionsProtocolPrivate):
+    def __init__(self, config: MetaReferenceScoringConfig) -> None:
+        self.config = config
+        self.dataset_infos = {}
+
+    async def initialize(self) -> None: ...
+
+    async def shutdown(self) -> None: ...
+
+    async def score_batch(
+        self, dataset_id: str, scoring_functions: List[str]
+    ) -> ScoreBatchResponse:
+        print("score_batch")
+
+    async def score(
+        self, input_rows: List[Dict[str, Any]], scoring_functions: List[str]
+    ) -> ScoreResponse:
+        print("score")