[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/datasetio/test_datasetio.py

@@ -8,8 +8,13 @@ import os
 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
+import base64
+import mimetypes
+from pathlib import Path
+
 from llama_stack.providers.tests.resolver import resolve_impls_for_test
 
 # How to run this test:
@@ -41,14 +46,35 @@ async def datasetio_settings():
     }
 
 
+def data_url_from_file(file_path: str) -> str:
+    if not os.path.exists(file_path):
+        raise FileNotFoundError(f"File not found: {file_path}")
+
+    with open(file_path, "rb") as file:
+        file_content = file.read()
+
+    base64_content = base64.b64encode(file_content).decode("utf-8")
+    mime_type, _ = mimetypes.guess_type(file_path)
+
+    data_url = f"data:{mime_type};base64,{base64_content}"
+
+    return data_url
+
+
 async def register_dataset(datasets_impl: Datasets):
+    test_file = Path(os.path.abspath(__file__)).parent / "test_dataset.csv"
+    test_url = data_url_from_file(str(test_file))
     dataset = DatasetDefWithProvider(
         identifier="test_dataset",
         provider_id=os.environ["PROVIDER_ID"],
         url=URL(
-            uri="https://openaipublic.blob.core.windows.net/simple-evals/mmlu.csv",
+            uri=test_url,
         ),
-        columns_schema={},
+        dataset_schema={
+            "generated_answer": StringType(),
+            "expected_answer": StringType(),
+            "input_query": StringType(),
+        },
     )
     await datasets_impl.register_dataset(dataset)
 
@@ -100,10 +126,10 @@ async def test_get_rows_paginated(datasetio_settings):
     # iterate over all rows
     response = await datasetio_impl.get_rows_paginated(
         dataset_id="test_dataset",
-        rows_in_page=10,
+        rows_in_page=2,
         page_token=response.next_page_token,
     )
 
     assert isinstance(response.rows, list)
-    assert len(response.rows) == 10
-    assert response.next_page_token == "13"
+    assert len(response.rows) == 2
+    assert response.next_page_token == "5"