tests w/ eval params

llama_stack/providers/tests/eval/constants.py

@@ -0,0 +1,20 @@
+# 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.
+
+JUDGE_PROMPT = """
+You will be given a question, a expected_answer, and a system_answer.
+Your task is to provide a 'total rating' scoring how well the system_answer answers compared with ground truth in expected_answer in terms of factual correctness to the question.
+Give your answer as a integer on a scale of 0 to 5, where 0 means that the system_answer is not correct at all compared with expected_answer, and 5 means that the answer completely and correctly answers the question.
+Provide your feedback as follows:
+Feedback:::
+Total rating: (your rating, as a int between 0 and 5)
+Now here are the question, expected_answer, system_answer.
+Question: {input_query}
+Expected Answer: {expected_answer}
+System Answer: {generated_answer}
+Feedback:::
+Total rating:
+"""

llama_stack/providers/tests/eval/test_eval.py

@@ -19,9 +19,10 @@ from llama_stack.apis.eval.eval import (
     EvalTaskDefWithProvider,
     ModelCandidate,
 )
+from llama_stack.apis.scoring_functions import LLMAsJudgeScoringFnParams
 from llama_stack.distribution.datatypes import Api
 from llama_stack.providers.tests.datasetio.test_datasetio import register_dataset
-
+from .constants import JUDGE_PROMPT
 
 # How to run this test:
 #
@@ -65,6 +66,7 @@ class Testeval:
         assert len(rows.rows) == 3
 
         scoring_functions = [
+            "meta-reference::llm_as_judge_base",
             "meta-reference::equality",
         ]
         task_id = "meta-reference::app_eval"
@@ -84,10 +86,22 @@ class Testeval:
                     model="Llama3.2-3B-Instruct",
                     sampling_params=SamplingParams(),
                 ),
+                scoring_params={
+                    "meta-reference::llm_as_judge_base": LLMAsJudgeScoringFnParams(
+                        judge_model="Llama3.1-8B-Instruct",
+                        prompt_template=JUDGE_PROMPT,
+                        judge_score_regexes=[
+                            r"Total rating: (\d+)",
+                            r"rating: (\d+)",
+                            r"Rating: (\d+)",
+                        ],
+                    )
+                },
             ),
         )
         assert len(response.generations) == 3
         assert "meta-reference::equality" in response.scores
+        assert "meta-reference::llm_as_judge_base" in response.scores
 
     @pytest.mark.asyncio
     async def test_eval_run_eval(self, eval_stack):