feat: GenAI Client(evals) - Add allow_cross_region_model support for create_evaluation_run

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

@@ -294,6 +294,31 @@ def test_create_eval_run_with_inference_configs(client):
     assert evaluation_run.error is None
 
 
+def test_create_eval_run_with_allow_cross_region_model(client):
+    """Tests that create_evaluation_run() works with allow_cross_region_model in config."""
+    client._api_client._http_options.api_version = "v1beta1"
+    inference_config = types.EvaluationRunInferenceConfig(
+        model=MODEL_NAME,
+        prompt_template=types.EvaluationRunPromptTemplate(
+            prompt_template="test prompt template"
+        ),
+    )
+    evaluation_run = client.evals.create_evaluation_run(
+        name="test_inference_config",
+        display_name="test_inference_config",
+        dataset=types.EvaluationRunDataSource(evaluation_set=EVAL_SET_NAME),
+        dest=GCS_DEST,
+        metrics=[GENERAL_QUALITY_METRIC],
+        inference_configs={"model_1": inference_config},
+        labels={"label1": "value1"},
+        config={"allow_cross_region_model": True},
+    )
+    assert isinstance(evaluation_run, types.EvaluationRun)
+    assert evaluation_run.display_name == "test_inference_config"
+    assert evaluation_run.state == types.EvaluationRunState.PENDING
+    assert evaluation_run.error is None
+
+
 @mock.patch("uuid.uuid4")
 def test_create_eval_run_with_metric_resource_name(mock_uuid4, client):
     """Tests create_evaluation_run with metric_resource_name."""

tests/unit/vertexai/genai/test_evals.py

@@ -9136,3 +9136,104 @@ def test_computation_metric_retry_on_resource_exhausted(
         summary_metric = result.summary_metrics[0]
         assert summary_metric.metric_name == "bleu"
         assert summary_metric.mean_score == 0.85
+
+
+class TestAllowCrossRegionModel:
+    """Tests for allow_cross_region_model flag for create_evaluation_run."""
+
+    def setup_method(self, method):
+        self.mock_api_client = mock.MagicMock()
+        self.mock_api_client.vertexai = True
+
+        self.mock_response = mock.MagicMock()
+        self.mock_response.body = json.dumps(
+            {
+                "name": "projects/123/locations/us-central1/evaluationRuns/456",
+                "displayName": "test_run",
+                "state": "PENDING",
+            }
+        )
+        self.mock_api_client.request.return_value = self.mock_response
+
+    def test_create_evaluation_run_config_has_allow_cross_region_model(self):
+        """Verifies allow_cross_region_model field exists on CreateEvaluationRunConfig."""
+        config = vertexai_genai_types.CreateEvaluationRunConfig(
+            allow_cross_region_model=True,
+        )
+        assert config.allow_cross_region_model is True
+
+    def test_create_evaluation_run_config_from_dict(self):
+        """Verifies allow_cross_region_model can be set via dict on CreateEvaluationRunConfig."""
+        config = vertexai_genai_types.CreateEvaluationRunConfig.model_validate(
+            {"allow_cross_region_model": True}
+        )
+        assert config.allow_cross_region_model is True
+
+    def test_create_evaluation_run_config_default_is_none(self):
+        """Verifies the default value of allow_cross_region_model is None."""
+        config = vertexai_genai_types.CreateEvaluationRunConfig()
+        assert config.allow_cross_region_model is None
+
+    def test_create_evaluation_run_passes_allow_cross_region_model(self):
+        """Verifies allow_cross_region_model is sent inside evaluationConfig in the API request."""
+        evals_module = evals.Evals(api_client_=self.mock_api_client)
+
+        evals_module.create_evaluation_run(
+            dataset=vertexai_genai_types.EvaluationRunDataSource(
+                evaluation_set="projects/123/locations/us-central1/evaluationSets/789"
+            ),
+            metrics=[
+                vertexai_genai_types.EvaluationRunMetric(
+                    metric="general_quality_v1",
+                    metric_config=vertexai_genai_types.UnifiedMetric(
+                        predefined_metric_spec=genai_types.PredefinedMetricSpec(
+                            metric_spec_name="general_quality_v1",
+                        )
+                    ),
+                )
+            ],
+            dest="gs://test-bucket/output",
+            config={"allow_cross_region_model": True},
+        )
+
+        self.mock_api_client.request.assert_called_once()
+        call_args = self.mock_api_client.request.call_args
+        request_body = call_args[0][2]  # Third positional arg is the request dict
+        assert (
+            request_body.get("evaluationConfig", {}).get("allowCrossRegionModel")
+            is True
+        )
+
+    @pytest.mark.asyncio
+    async def test_create_evaluation_run_async_passes_allow_cross_region_model(self):
+        """Verifies allow_cross_region_model is sent inside evaluationConfig in the async API request."""
+        self.mock_api_client.async_request = mock.AsyncMock(
+            return_value=self.mock_response
+        )
+        async_evals_module = evals.AsyncEvals(api_client_=self.mock_api_client)
+
+        await async_evals_module.create_evaluation_run(
+            dataset=vertexai_genai_types.EvaluationRunDataSource(
+                evaluation_set="projects/123/locations/us-central1/evaluationSets/789"
+            ),
+            metrics=[
+                vertexai_genai_types.EvaluationRunMetric(
+                    metric="general_quality_v1",
+                    metric_config=vertexai_genai_types.UnifiedMetric(
+                        predefined_metric_spec=genai_types.PredefinedMetricSpec(
+                            metric_spec_name="general_quality_v1",
+                        )
+                    ),
+                )
+            ],
+            dest="gs://test-bucket/output",
+            config={"allow_cross_region_model": True},
+        )
+
+        self.mock_api_client.async_request.assert_called_once()
+        call_args = self.mock_api_client.async_request.call_args
+        request_body = call_args[0][2]  # Third positional arg is the request dict
+        assert (
+            request_body.get("evaluationConfig", {}).get("allowCrossRegionModel")
+            is True
+        )

vertexai/_genai/evals.py

@@ -391,6 +391,13 @@ def _EvaluationRunConfig_from_vertex(
             [item for item in getv(from_object, ["lossAnalysisConfig"])],
         )
 
+    if getv(from_object, ["allowCrossRegionModel"]) is not None:
+        setv(
+            to_object,
+            ["allow_cross_region_model"],
+            getv(from_object, ["allowCrossRegionModel"]),
+        )
+
     return to_object
 
 
@@ -425,6 +432,13 @@ def _EvaluationRunConfig_to_vertex(
             [item for item in getv(from_object, ["loss_analysis_config"])],
         )
 
+    if getv(from_object, ["allow_cross_region_model"]) is not None:
+        setv(
+            to_object,
+            ["allowCrossRegionModel"],
+            getv(from_object, ["allow_cross_region_model"]),
+        )
+
     return to_object
 
 
@@ -2653,6 +2667,8 @@ def create_evaluation_run(
               ``max_top_cluster_count``. Mutually exclusive with
               ``loss_analysis_metrics``.
           config: The configuration for the evaluation run.
+            - allow_cross_region_model: Opt-in flag to authorize cross-region
+              routing for model inference. Applies to both scraping and evaluation.
 
         Returns:
             The created evaluation run.
@@ -2672,6 +2688,11 @@ def create_evaluation_run(
             else (agent_info or evals_types.AgentInfo())
         )
 
+        if not config:
+            config = types.CreateEvaluationRunConfig()
+        if isinstance(config, dict):
+            config = types.CreateEvaluationRunConfig.model_validate(config)
+
         if agent_info and not inference_configs:
             parsed_user_simulator_config = (
                 evals_types.UserSimulatorConfig.model_validate(user_simulator_config)
@@ -2712,6 +2733,7 @@ def create_evaluation_run(
             output_config=output_config,
             metrics=resolved_metrics,
             loss_analysis_config=resolved_loss_configs,
+            allow_cross_region_model=getattr(config, "allow_cross_region_model", None),
         )
         resolved_inference_configs = _evals_common._resolve_inference_configs(
             self._api_client, resolved_dataset, inference_configs, parsed_agent_info
@@ -4422,6 +4444,8 @@ async def create_evaluation_run(
               ``max_top_cluster_count``. Mutually exclusive with
               ``loss_analysis_metrics``.
           config: The configuration for the evaluation run.
+            - allow_cross_region_model: Opt-in flag to authorize cross-region
+              routing for model inference. Applies to both scraping and evaluation.
 
         Returns:
             The created evaluation run.
@@ -4441,6 +4465,11 @@ async def create_evaluation_run(
             else (agent_info or evals_types.AgentInfo())
         )
 
+        if not config:
+            config = types.CreateEvaluationRunConfig()
+        if isinstance(config, dict):
+            config = types.CreateEvaluationRunConfig.model_validate(config)
+
         if agent_info and not inference_configs:
             parsed_user_simulator_config = (
                 evals_types.UserSimulatorConfig.model_validate(user_simulator_config)
@@ -4481,6 +4510,7 @@ async def create_evaluation_run(
             output_config=output_config,
             metrics=resolved_metrics,
             loss_analysis_config=resolved_loss_configs,
+            allow_cross_region_model=getattr(config, "allow_cross_region_model", None),
         )
         resolved_inference_configs = _evals_common._resolve_inference_configs(
             self._api_client, resolved_dataset, inference_configs, parsed_agent_info

vertexai/_genai/types/common.py

@@ -2386,6 +2386,11 @@ class EvaluationRunConfig(_common.BaseModel):
         default=None,
         description="""Specifications for loss analysis. Each config specifies a metric and candidate to analyze for loss patterns.""",
     )
+    allow_cross_region_model: Optional[bool] = Field(
+        default=None,
+        description="""Opt-in flag to authorize cross-region routing for model inference.
+    Applies to both scraping and evaluation.""",
+    )
 
 
 class EvaluationRunConfigDict(TypedDict, total=False):
@@ -2406,6 +2411,10 @@ class EvaluationRunConfigDict(TypedDict, total=False):
     loss_analysis_config: Optional[list[LossAnalysisConfigDict]]
     """Specifications for loss analysis. Each config specifies a metric and candidate to analyze for loss patterns."""
 
+    allow_cross_region_model: Optional[bool]
+    """Opt-in flag to authorize cross-region routing for model inference.
+    Applies to both scraping and evaluation."""
+
 
 EvaluationRunConfigOrDict = Union[EvaluationRunConfig, EvaluationRunConfigDict]
 
@@ -2536,6 +2545,11 @@ class CreateEvaluationRunConfig(_common.BaseModel):
     http_options: Optional[genai_types.HttpOptions] = Field(
         default=None, description="""Used to override HTTP request options."""
     )
+    allow_cross_region_model: Optional[bool] = Field(
+        default=None,
+        description="""Opt-in flag to authorize cross-region routing for model inference.
+      Applies to both scraping and evaluation.""",
+    )
 
 
 class CreateEvaluationRunConfigDict(TypedDict, total=False):
@@ -2544,6 +2558,10 @@ class CreateEvaluationRunConfigDict(TypedDict, total=False):
     http_options: Optional[genai_types.HttpOptionsDict]
     """Used to override HTTP request options."""
 
+    allow_cross_region_model: Optional[bool]
+    """Opt-in flag to authorize cross-region routing for model inference.
+      Applies to both scraping and evaluation."""
+
 
 CreateEvaluationRunConfigOrDict = Union[
     CreateEvaluationRunConfig, CreateEvaluationRunConfigDict