[Evals API][3/n] scoring_functions / scoring meta-reference implementations (#296)

* wip

* dataset validation

* test_scoring

* cleanup

* clean up test

* comments

* error checking

* dataset client

* test client:

* datasetio client

* clean up

* basic scoring function works

* scorer wip

* equality scorer

* score batch impl

* score batch

* update scoring test

* refactor

* validate scorer input

* address comments

* add all rows scores to ScoringResult

* bugfix

* scoring function def rename

llama_stack/providers/tests/scoring/__init__.py

@@ -0,0 +1,5 @@
+# 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.

llama_stack/providers/tests/scoring/provider_config_example.yaml

@@ -0,0 +1,9 @@
+providers:
+  datasetio:
+  - provider_id: test-meta
+    provider_type: meta-reference
+    config: {}
+  scoring:
+    - provider_id: test-meta
+      provider_type: meta-reference
+      config: {}

llama_stack/providers/tests/scoring/test_scoring.py

@@ -0,0 +1,69 @@
+# 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.
+import pytest
+import pytest_asyncio
+
+from llama_stack.apis.common.type_system import *  # noqa: F403
+from llama_stack.apis.datasetio import *  # noqa: F403
+from llama_stack.distribution.datatypes import *  # noqa: F403
+
+from llama_stack.providers.tests.datasetio.test_datasetio import register_dataset
+from llama_stack.providers.tests.resolver import resolve_impls_for_test
+
+# How to run this test:
+#
+# 1. Ensure you have a conda with the right dependencies installed. This is a bit tricky
+#    since it depends on the provider you are testing. On top of that you need
+#    `pytest` and `pytest-asyncio` installed.
+#
+# 2. Copy and modify the provider_config_example.yaml depending on the provider you are testing.
+#
+# 3. Run:
+#
+# ```bash
+# PROVIDER_ID=<your_provider> \
+#   PROVIDER_CONFIG=provider_config.yaml \
+#   pytest -s llama_stack/providers/tests/scoring/test_scoring.py \
+#   --tb=short --disable-warnings
+# ```
+
+
+@pytest_asyncio.fixture(scope="session")
+async def scoring_settings():
+    impls = await resolve_impls_for_test(Api.scoring, deps=[Api.datasetio])
+    return {
+        "scoring_impl": impls[Api.scoring],
+        "scoring_functions_impl": impls[Api.scoring_functions],
+        "datasets_impl": impls[Api.datasets],
+    }
+
+
+@pytest.mark.asyncio
+async def test_scoring_functions_list(scoring_settings):
+    scoring_functions_impl = scoring_settings["scoring_functions_impl"]
+    scoring_functions = await scoring_functions_impl.list_scoring_functions()
+    assert isinstance(scoring_functions, list)
+    assert len(scoring_functions) > 0
+    function_ids = [f.identifier for f in scoring_functions]
+    assert "equality" in function_ids
+
+
+@pytest.mark.asyncio
+async def test_scoring_score(scoring_settings):
+    scoring_impl = scoring_settings["scoring_impl"]
+    datasets_impl = scoring_settings["datasets_impl"]
+    await register_dataset(datasets_impl)
+
+    response = await datasets_impl.list_datasets()
+    assert len(response) == 1
+
+    response = await scoring_impl.score_batch(
+        dataset_id=response[0].identifier,
+        scoring_functions=["equality"],
+    )
+
+    assert len(response.results) == 1
+    assert "equality" in response.results