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feat: GenAI SDK client(multimodal) - Support Assess Tuning Validity for multimodal dataset. #6298

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feat: GenAI SDK client(multimodal) - Support Assess Tuning Validity for multimodal dataset. #6298

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19 changes: 19 additions & 0 deletions tests/unit/vertexai/genai/replays/test_assess_multimodal_dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -66,6 +66,25 @@ def test_assess_tuning_resources(client):
assert isinstance(response, types.TuningResourceUsageAssessmentResult)


def test_assess_tuning_validity(client):
response = client.datasets.assess_tuning_validity(
dataset_name=DATASET,
dataset_usage="SFT_VALIDATION",
model_name="gemini-2.5-flash-001",
template_config=types.GeminiTemplateConfig(
gemini_example=types.GeminiExample(
contents=[
{
"role": "user",
"parts": [{"text": "What is the capital of {name}?"}],
}
],
),
),
)
assert isinstance(response, types.TuningValidationAssessmentResult)


pytestmark = pytest_helper.setup(
file=__file__,
globals_for_file=globals(),
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49 changes: 49 additions & 0 deletions vertexai/_genai/datasets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1054,6 +1054,55 @@ def assess_tuning_resources(
response["tuningResourceUsageAssessmentResult"],
)

def assess_tuning_validity(
self,
*,
dataset_name: str,
model_name: str,
dataset_usage: str,
template_config: Optional[types.GeminiTemplateConfigOrDict] = None,
config: Optional[types.AssessDatasetConfigOrDict] = None,
) -> types.TuningValidationAssessmentResult:
if isinstance(config, dict):
config = types.AssessDatasetConfig(**config)
elif not config:
config = types.AssessDatasetConfig()

operation = self._assess_multimodal_dataset(
name=dataset_name,
tuning_validation_assessment_config=types.TuningValidationAssessmentConfig(
model_name=model_name,
dataset_usage=dataset_usage,
),
gemini_request_read_config=types.GeminiRequestReadConfig(
template_config=template_config,
),
config=config,
)
response = self._wait_for_operation(
operation=operation,
timeout_seconds=config.timeout,
)
return _datasets_utils.create_from_response(
types.TuningValidationAssessmentResult,
response["tuningValidationAssessmentResult"],
)

# request = self._build_assess_data_request(template_config)
# request.tuning_validation_assessment_config = (
# types.TuningValidationAssessmentConfig(
# model_name=model_name,
# dataset_usage=dataset_usage,
# )
# )
# assess_lro = self.api_client.assess_data(
# request=request, timeout=assess_request_timeout
# )
# assessment_result = assess_lro.result(timeout=None)
# return TuningValidationAssessmentResult(
# errors=assessment_result.tuning_validation_assessment_result.errors
# )


class AsyncDatasets(_api_module.BaseModule):

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