feat: GenAI Client(evals) - Add get_evaluation_run method to Vertex AI GenAI SDK evals

tests/unit/vertexai/genai/replays/test_get_evaluation_run.py

@@ -0,0 +1,129 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# pylint: disable=protected-access,bad-continuation,missing-function-docstring
+
+from tests.unit.vertexai.genai.replays import pytest_helper
+from vertexai import types
+import datetime
+import pytest
+
+
+def test_get_eval_run(client):
+    """Tests that get_evaluation_run() returns a correctly structured EvaluationRun."""
+    evaluation_run_name = (
+        "projects/503583131166/locations/us-central1/evaluationRuns/1957799200510967808"
+    )
+    evaluation_run = client.evals.get_evaluation_run(name=evaluation_run_name)
+    assert isinstance(evaluation_run, types.EvaluationRun)
+    assert evaluation_run.name == evaluation_run_name
+    assert evaluation_run.display_name == "test2"
+    assert evaluation_run.metadata == {"pipeline_id": "4460531348888616960"}
+    assert evaluation_run.create_time == datetime.datetime(
+        2025, 9, 8, 20, 55, 41, 833176, tzinfo=datetime.timezone.utc
+    )
+    assert evaluation_run.completion_time == datetime.datetime(
+        2025, 9, 8, 20, 56, 13, 492971, tzinfo=datetime.timezone.utc
+    )
+    assert evaluation_run.state == types.EvaluationRunState.SUCCEEDED
+    assert evaluation_run.evaluation_set_snapshot == (
+        "projects/503583131166/locations/us-central1/evaluationSets/8069535738573619200"
+    )
+    assert evaluation_run.data_source.bigquery_request_set == types.BigQueryRequestSet(
+        uri="bq://lakeyk-test-limited.inference_batch_prediction_input.1317387725199900672_1b",
+        prompt_column="request",
+        candidate_response_columns={
+            "baseline_model_response": "baseline_model_response",
+            "checkpoint_1": "checkpoint_1",
+            "checkpoint_2": "checkpoint_2",
+        },
+    )
+    assert evaluation_run.error is None
+
+
+def test_get_eval_run_bq_source(client):
+    """Tests that get_evaluation_run() returns a correctly structured EvaluationRun."""
+    evaluation_run_name = (
+        "projects/503583131166/locations/us-central1/evaluationRuns/1968424880881795072"
+    )
+    evaluation_run = client.evals.get_evaluation_run(name=evaluation_run_name)
+    assert isinstance(evaluation_run, types.EvaluationRun)
+    assert evaluation_run.name == evaluation_run_name
+    assert evaluation_run.display_name == "test1"
+    assert evaluation_run.data_source.bigquery_request_set == types.BigQueryRequestSet(
+        uri="bq://lakeyk-test-limited.inference_batch_prediction_input.1317387725199900672_1b",
+        prompt_column="request",
+        rubrics_column="rubric",
+        candidate_response_columns={
+            "baseline_model_response": "baseline_model_response",
+            "checkpoint_1": "checkpoint_1",
+            "checkpoint_2": "checkpoint_2",
+        },
+        sampling_config=types.SamplingConfig(
+            sampling_count=100,
+            sampling_method=types.SamplingMethod.RANDOM,
+            sampling_duration="60s",
+        ),
+    )
+
+
+def test_get_eval_run_eval_set_source(client):
+    """Tests that get_evaluation_run() returns a correctly structured EvaluationRun."""
+    evaluation_run_name = (
+        "projects/503583131166/locations/us-central1/evaluationRuns/6903525647549726720"
+    )
+    evaluation_run = client.evals.get_evaluation_run(name=evaluation_run_name)
+    assert isinstance(evaluation_run, types.EvaluationRun)
+    assert evaluation_run.name == evaluation_run_name
+    assert evaluation_run.display_name == "test3"
+    assert evaluation_run.data_source.evaluation_set == (
+        "projects/503583131166/locations/us-central1/evaluationSets/6619939608513740800"
+    )
+    assert evaluation_run.state == types.EvaluationRunState.FAILED
+    assert evaluation_run.error.message == (
+        "code=INVALID_ARGUMENT, message=EvaluationRun 6903525647549726720 has no "
+        "items, cause=null"
+    )
+
+
+pytest_plugins = ("pytest_asyncio",)
+
+
+@pytest.mark.asyncio
+async def test_get_eval_run_async(client):
+    """Tests that get_evaluation_run() returns a correctly structured EvaluationRun."""
+    eval_run_id = "1957799200510967808"
+    eval_run_name = (
+        f"projects/503583131166/locations/us-central1/evaluationRuns/{eval_run_id}"
+    )
+    evaluation_run = await client.aio.evals.get_evaluation_run(name=eval_run_id)
+    assert isinstance(evaluation_run, types.EvaluationRun)
+    assert evaluation_run.name == eval_run_name
+    assert evaluation_run.display_name == "test2"
+    assert evaluation_run.data_source.bigquery_request_set == types.BigQueryRequestSet(
+        uri="bq://lakeyk-test-limited.inference_batch_prediction_input.1317387725199900672_1b",
+        prompt_column="request",
+        candidate_response_columns={
+            "baseline_model_response": "baseline_model_response",
+            "checkpoint_1": "checkpoint_1",
+            "checkpoint_2": "checkpoint_2",
+        },
+    )
+
+
+pytestmark = pytest_helper.setup(
+    file=__file__,
+    globals_for_file=globals(),
+    test_method="evals.get_evaluation_run",
+)