From 85c0ef1b68ec5d5d2f7df8419d6e9c34bbfadc75 Mon Sep 17 00:00:00 2001
From: Ben Kazemi <benkazemi@google.com>
Date: Tue, 27 Jan 2026 16:15:30 -0800
Subject: [PATCH] feat: GenAI SDK client(multimodal) - Support Assess Tuning
 Validity for multimodal dataset.

PiperOrigin-RevId: 861928934
---
 .../replays/test_assess_multimodal_dataset.py | 19 +++++++
 vertexai/_genai/datasets.py                   | 49 +++++++++++++++++++
 2 files changed, 68 insertions(+)

diff --git a/tests/unit/vertexai/genai/replays/test_assess_multimodal_dataset.py b/tests/unit/vertexai/genai/replays/test_assess_multimodal_dataset.py
index 673a3b5b68..5a8d7bfdc9 100644
--- a/tests/unit/vertexai/genai/replays/test_assess_multimodal_dataset.py
+++ b/tests/unit/vertexai/genai/replays/test_assess_multimodal_dataset.py
@@ -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(),
diff --git a/vertexai/_genai/datasets.py b/vertexai/_genai/datasets.py
index 68a5367bdf..db5ade15c9 100644
--- a/vertexai/_genai/datasets.py
+++ b/vertexai/_genai/datasets.py
@@ -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):