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feat: GenAI SDK client - Add batch_evaluate method for asynchronous batch eval. Add transformation support for consistent interface parameters with the evaluate method #5464

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feat: GenAI SDK client - Add batch_evaluate method for asynchronous batch eval. Add transformation support for consistent interface parameters with the evaluate method #5464

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39 changes: 21 additions & 18 deletions tests/unit/vertexai/genai/test_evals.py
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Original file line number Diff line number Diff line change
Expand Up @@ -158,14 +158,13 @@ def test_eval_run(self):

@pytest.mark.usefixtures("google_auth_mock")
@mock.patch.object(client.Client, "_get_api_client")
@mock.patch.object(evals.Evals, "batch_eval")
def test_eval_batch_eval(self, mock_evaluate, mock_get_api_client):
@mock.patch.object(evals.Evals, "batch_evaluate")
def test_eval_batch_evaluate(self, mock_evaluate, mock_get_api_client):
test_client = vertexai.Client(project=_TEST_PROJECT, location=_TEST_LOCATION)
test_client.evals.batch_eval(
test_client.evals.batch_evaluate(
dataset=vertexai_genai_types.EvaluationDataset(),
metrics=[vertexai_genai_types.Metric(name="test")],
output_config=vertexai_genai_types.OutputConfig(),
autorater_config=vertexai_genai_types.AutoraterConfig(),
dest="gs://bucket/output",
config=vertexai_genai_types.EvaluateDatasetConfig(),
)
mock_evaluate.assert_called_once()
Expand Down Expand Up @@ -376,13 +375,14 @@ def test_inference_with_gcs_destination(
mock_generate_content_response
)

gcs_dest_path = "gs://bucket/output.jsonl"
config = vertexai_genai_types.EvalRunInferenceConfig(dest=gcs_dest_path)
gcs_dest_dir = "gs://bucket/output"
config = vertexai_genai_types.EvalRunInferenceConfig(dest=gcs_dest_dir)

inference_result = self.client.evals.run_inference(
model="gemini-pro", src=mock_df, config=config
)

expected_gcs_path = os.path.join(gcs_dest_dir, "inference_results.jsonl")
expected_df_to_save = pd.DataFrame(
{
"prompt": ["test prompt"],
Expand All @@ -393,15 +393,15 @@ def test_inference_with_gcs_destination(
pd.testing.assert_frame_equal(saved_df, expected_df_to_save)
mock_gcs_utils.return_value.upload_dataframe.assert_called_once_with(
df=mock.ANY,
gcs_destination_blob_path=gcs_dest_path,
gcs_destination_blob_path=expected_gcs_path,
file_type="jsonl",
)
pd.testing.assert_frame_equal(
inference_result.eval_dataset_df, expected_df_to_save
)
assert inference_result.candidate_name == "gemini-pro"
assert inference_result.gcs_source == vertexai_genai_types.GcsSource(
uris=[gcs_dest_path]
uris=[expected_gcs_path]
)

@mock.patch.object(_evals_common, "Models")
Expand Down Expand Up @@ -434,16 +434,17 @@ def test_inference_with_local_destination(
mock_generate_content_response
)

local_dest_path = "/tmp/test/output_dir/results.jsonl"
config = vertexai_genai_types.EvalRunInferenceConfig(dest=local_dest_path)
local_dest_dir = "/tmp/test/output_dir"
config = vertexai_genai_types.EvalRunInferenceConfig(dest=local_dest_dir)

inference_result = self.client.evals.run_inference(
model="gemini-pro", src=mock_df, config=config
)

mock_makedirs.assert_called_once_with("/tmp/test/output_dir", exist_ok=True)
mock_makedirs.assert_called_once_with(local_dest_dir, exist_ok=True)
expected_save_path = os.path.join(local_dest_dir, "inference_results.jsonl")
mock_df_to_json.assert_called_once_with(
local_dest_path, orient="records", lines=True
expected_save_path, orient="records", lines=True
)
expected_df = pd.DataFrame(
{
Expand All @@ -457,7 +458,7 @@ def test_inference_with_local_destination(

@mock.patch.object(_evals_common, "Models")
@mock.patch.object(_evals_utils, "EvalDatasetLoader")
def test_inference_from_request_column_save_locally(
def test_inference_from_request_column_save_to_local_dir(
self, mock_eval_dataset_loader, mock_models
):
mock_df = pd.DataFrame(
Expand Down Expand Up @@ -494,8 +495,8 @@ def test_inference_from_request_column_save_locally(
mock_generate_content_responses
)

local_dest_path = "/tmp/output.jsonl"
config = vertexai_genai_types.EvalRunInferenceConfig(dest=local_dest_path)
local_dest_dir = "/tmp/test_output_dir"
config = vertexai_genai_types.EvalRunInferenceConfig(dest=local_dest_dir)

inference_result = self.client.evals.run_inference(
model="gemini-pro", src=mock_df, config=config
Expand Down Expand Up @@ -530,13 +531,15 @@ def test_inference_from_request_column_save_locally(
expected_df.sort_values(by="request").reset_index(drop=True),
)

with open(local_dest_path, "r") as f:
saved_file_path = os.path.join(local_dest_dir, "inference_results.jsonl")
with open(saved_file_path, "r") as f:
saved_records = [json.loads(line) for line in f]
expected_records = expected_df.to_dict(orient="records")
assert sorted(saved_records, key=lambda x: x["request"]) == sorted(
expected_records, key=lambda x: x["request"]
)
os.remove(local_dest_path)
os.remove(saved_file_path)
os.rmdir(local_dest_dir)
assert inference_result.candidate_name == "gemini-pro"
assert inference_result.gcs_source is None

Expand Down
12 changes: 3 additions & 9 deletions vertexai/_genai/_evals_common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -617,19 +617,13 @@ def _execute_inference(

if dest:
file_name = "inference_results.jsonl"
full_dest_path = dest
is_gcs_path = dest.startswith(_evals_utils.GCS_PREFIX)

if is_gcs_path:
if not dest.endswith("/"):
pass
else:
full_dest_path = os.path.join(dest, file_name)
full_dest_path = os.path.join(dest, file_name)
else:
if os.path.isdir(dest):
full_dest_path = os.path.join(dest, file_name)

os.makedirs(os.path.dirname(full_dest_path), exist_ok=True)
os.makedirs(dest, exist_ok=True)
full_dest_path = os.path.join(dest, file_name)

logger.info("Saving inference results to: %s", full_dest_path)
try:
Expand Down
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