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feat: GenAI Client(evals) - Add support for inference_configs in create_evaluation_run. #6245

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feat: GenAI Client(evals) - Add support for inference_configs in create_evaluation_run. #6245

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95 changes: 85 additions & 10 deletions tests/unit/vertexai/genai/replays/test_create_evaluation_run.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,11 +20,11 @@
import pytest

GCS_DEST = "gs://lakeyk-limited-bucket/eval_run_output"
UNIVERSAL_AR_METRIC = types.EvaluationRunMetric(
metric="universal_ar_v1",
GENERAL_QUALITY_METRIC = types.EvaluationRunMetric(
metric="general_quality_v1",
metric_config=types.UnifiedMetric(
predefined_metric_spec=types.PredefinedMetricSpec(
metric_spec_name="universal_ar_v1",
metric_spec_name="general_quality_v1",
)
),
)
Expand Down Expand Up @@ -71,7 +71,7 @@ def test_create_eval_run_data_source_evaluation_set(client):
),
dest=GCS_DEST,
metrics=[
UNIVERSAL_AR_METRIC,
GENERAL_QUALITY_METRIC,
types.RubricMetric.FINAL_RESPONSE_QUALITY,
LLM_METRIC,
],
Expand All @@ -94,7 +94,7 @@ def test_create_eval_run_data_source_evaluation_set(client):
output_config=genai_types.OutputConfig(
gcs_destination=genai_types.GcsDestination(output_uri_prefix=GCS_DEST)
),
metrics=[UNIVERSAL_AR_METRIC, FINAL_RESPONSE_QUALITY_METRIC, LLM_METRIC],
metrics=[GENERAL_QUALITY_METRIC, FINAL_RESPONSE_QUALITY_METRIC, LLM_METRIC],
)
assert evaluation_run.inference_configs[
"agent-1"
Expand Down Expand Up @@ -131,7 +131,7 @@ def test_create_eval_run_data_source_bigquery_request_set(client):
),
labels={"label1": "value1"},
dest=GCS_DEST,
metrics=[UNIVERSAL_AR_METRIC],
metrics=[GENERAL_QUALITY_METRIC],
)
assert isinstance(evaluation_run, types.EvaluationRun)
assert evaluation_run.display_name == "test5"
Expand All @@ -152,7 +152,7 @@ def test_create_eval_run_data_source_bigquery_request_set(client):
output_config=genai_types.OutputConfig(
gcs_destination=genai_types.GcsDestination(output_uri_prefix=GCS_DEST)
),
metrics=[UNIVERSAL_AR_METRIC],
metrics=[GENERAL_QUALITY_METRIC],
)
assert evaluation_run.inference_configs is None
assert evaluation_run.labels == {
Expand All @@ -161,6 +161,43 @@ def test_create_eval_run_data_source_bigquery_request_set(client):
assert evaluation_run.error is None


def test_create_eval_run_with_inference_configs(client):
"""Tests that create_evaluation_run() creates a correctly structured EvaluationRun with inference_configs."""
client._api_client._http_options.api_version = "v1beta1"
inference_config = types.EvaluationRunInferenceConfig(
model="projects/503583131166/locations/us-central1/publishers/google/models/gemini-2.5-flash"
)
evaluation_run = client.evals.create_evaluation_run(
name="test_inference_config",
display_name="test_inference_config",
dataset=types.EvaluationRunDataSource(
evaluation_set="projects/503583131166/locations/us-central1/evaluationSets/6619939608513740800"
),
dest=GCS_DEST,
metrics=[GENERAL_QUALITY_METRIC],
inference_configs={"model_1": inference_config},
labels={"label1": "value1"},
)
assert isinstance(evaluation_run, types.EvaluationRun)
assert evaluation_run.display_name == "test_inference_config"
assert evaluation_run.state == types.EvaluationRunState.PENDING
assert isinstance(evaluation_run.data_source, types.EvaluationRunDataSource)
assert evaluation_run.data_source.evaluation_set == (
"projects/503583131166/locations/us-central1/evaluationSets/6619939608513740800"
)
assert evaluation_run.evaluation_config == types.EvaluationRunConfig(
output_config=genai_types.OutputConfig(
gcs_destination=genai_types.GcsDestination(output_uri_prefix=GCS_DEST)
),
metrics=[GENERAL_QUALITY_METRIC],
)
assert evaluation_run.inference_configs["model_1"] == inference_config
assert evaluation_run.labels == {
"label1": "value1",
}
assert evaluation_run.error is None


# Test fails in replay mode because of UUID generation mismatch.
# def test_create_eval_run_data_source_evaluation_dataset(client):
# """Tests that create_evaluation_run() creates a correctly structured EvaluationRun with EvaluationDataset."""
Expand Down Expand Up @@ -217,7 +254,7 @@ def test_create_eval_run_data_source_bigquery_request_set(client):
# eval_dataset_df=input_df,
# ),
# dest=GCS_DEST,
# metrics=[UNIVERSAL_AR_METRIC],
# metrics=[GENERAL_QUALITY_METRIC],
# )
# assert isinstance(evaluation_run, types.EvaluationRun)
# assert evaluation_run.display_name == "test6"
Expand Down Expand Up @@ -278,7 +315,7 @@ async def test_create_eval_run_async(client):
)
),
dest=GCS_DEST,
metrics=[UNIVERSAL_AR_METRIC],
metrics=[GENERAL_QUALITY_METRIC],
)
assert isinstance(evaluation_run, types.EvaluationRun)
assert evaluation_run.display_name == "test8"
Expand All @@ -295,7 +332,7 @@ async def test_create_eval_run_async(client):
output_config=genai_types.OutputConfig(
gcs_destination=genai_types.GcsDestination(output_uri_prefix=GCS_DEST)
),
metrics=[UNIVERSAL_AR_METRIC],
metrics=[GENERAL_QUALITY_METRIC],
)
assert evaluation_run.error is None
assert evaluation_run.inference_configs is None
Expand All @@ -304,6 +341,44 @@ async def test_create_eval_run_async(client):
assert evaluation_run.error is None


@pytest.mark.asyncio
async def test_create_eval_run_async_with_inference_configs(client):
"""Tests that create_evaluation_run() creates a correctly structured EvaluationRun with inference_configs asynchronously."""
client._api_client._http_options.api_version = "v1beta1"
inference_config = types.EvaluationRunInferenceConfig(
model="projects/503583131166/locations/us-central1/publishers/google/models/gemini-2.5-flash"
)
evaluation_run = await client.aio.evals.create_evaluation_run(
name="test_inference_config_async",
display_name="test_inference_config_async",
dataset=types.EvaluationRunDataSource(
evaluation_set="projects/503583131166/locations/us-central1/evaluationSets/6619939608513740800"
),
dest=GCS_DEST,
metrics=[GENERAL_QUALITY_METRIC],
inference_configs={"model_1": inference_config},
labels={"label1": "value1"},
)
assert isinstance(evaluation_run, types.EvaluationRun)
assert evaluation_run.display_name == "test_inference_config_async"
assert evaluation_run.state == types.EvaluationRunState.PENDING
assert isinstance(evaluation_run.data_source, types.EvaluationRunDataSource)
assert evaluation_run.data_source.evaluation_set == (
"projects/503583131166/locations/us-central1/evaluationSets/6619939608513740800"
)
assert evaluation_run.evaluation_config == types.EvaluationRunConfig(
output_config=genai_types.OutputConfig(
gcs_destination=genai_types.GcsDestination(output_uri_prefix=GCS_DEST)
),
metrics=[GENERAL_QUALITY_METRIC],
)
assert evaluation_run.inference_configs["model_1"] == inference_config
assert evaluation_run.labels == {
"label1": "value1",
}
assert evaluation_run.error is None


pytestmark = pytest_helper.setup(
file=__file__,
globals_for_file=globals(),
Expand Down
22 changes: 20 additions & 2 deletions vertexai/_genai/evals.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1581,6 +1581,9 @@ def create_evaluation_run(
name: Optional[str] = None,
display_name: Optional[str] = None,
agent_info: Optional[types.evals.AgentInfoOrDict] = None,
inference_configs: Optional[
dict[str, types.EvaluationRunInferenceConfigOrDict]
] = None,
labels: Optional[dict[str, str]] = None,
config: Optional[types.CreateEvaluationRunConfigOrDict] = None,
) -> types.EvaluationRun:
Expand All @@ -1593,12 +1596,18 @@ def create_evaluation_run(
name: The name of the evaluation run.
display_name: The display name of the evaluation run.
agent_info: The agent info to evaluate.
inference_configs: The candidate to inference config map for the evaluation run.
If provided, agent_info must be None.
labels: The labels to apply to the evaluation run.
config: The configuration for the evaluation run.

Returns:
The created evaluation run.
"""
if agent_info and inference_configs:
raise ValueError(
"At most one of agent_info or inference_configs can be provided."
)
if agent_info and isinstance(agent_info, dict):
agent_info = types.evals.AgentInfo.model_validate(agent_info)
if type(dataset).__name__ == "EvaluationDataset":
Expand Down Expand Up @@ -1630,8 +1639,8 @@ def create_evaluation_run(
evaluation_config = types.EvaluationRunConfig(
output_config=output_config, metrics=resolved_metrics
)
inference_configs = {}
if agent_info:
inference_configs = {}
inference_configs[agent_info.name] = types.EvaluationRunInferenceConfig(
agent_config=types.EvaluationRunAgentConfig(
developer_instruction=genai_types.Content(
Expand Down Expand Up @@ -2429,6 +2438,9 @@ async def create_evaluation_run(
name: Optional[str] = None,
display_name: Optional[str] = None,
agent_info: Optional[types.evals.AgentInfo] = None,
inference_configs: Optional[
dict[str, types.EvaluationRunInferenceConfigOrDict]
] = None,
labels: Optional[dict[str, str]] = None,
config: Optional[types.CreateEvaluationRunConfigOrDict] = None,
) -> types.EvaluationRun:
Expand All @@ -2441,12 +2453,18 @@ async def create_evaluation_run(
name: The name of the evaluation run.
display_name: The display name of the evaluation run.
agent_info: The agent info to evaluate.
inference_configs: The candidate to inference config map for the evaluation run.
If provided, agent_info must be None.
labels: The labels to apply to the evaluation run.
config: The configuration for the evaluation run.

Returns:
The created evaluation run.
"""
if agent_info and inference_configs:
raise ValueError(
"At most one of agent_info or inference_configs can be provided."
)
if agent_info and isinstance(agent_info, dict):
agent_info = types.evals.AgentInfo.model_validate(agent_info)
if type(dataset).__name__ == "EvaluationDataset":
Expand Down Expand Up @@ -2477,8 +2495,8 @@ async def create_evaluation_run(
evaluation_config = types.EvaluationRunConfig(
output_config=output_config, metrics=resolved_metrics
)
inference_configs = {}
if agent_info:
inference_configs = {}
inference_configs[agent_info.name] = types.EvaluationRunInferenceConfig(
agent_config=types.EvaluationRunAgentConfig(
developer_instruction=genai_types.Content(
Expand Down
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