Pin JS model integ test to 4.* version

src/sagemaker/serve/builder/jumpstart_builder.py

@@ -142,7 +142,11 @@ def _is_jumpstart_model_id(self) -> bool:
             return False
 
         try:
-            model_uris.retrieve(model_id=self.model, model_version="*", model_scope=_JS_SCOPE)
+            model_uris.retrieve(
+                model_id=self.model,
+                model_version=getattr(self, "model_version", None) or "*",
+                model_scope=_JS_SCOPE,
+            )
         except KeyError:
             logger.warning(_NO_JS_MODEL_EX)
             return False
@@ -154,6 +158,7 @@ def _create_pre_trained_js_model(self) -> Type[Model]:
         """Placeholder docstring"""
         pysdk_model = JumpStartModel(
             self.model,
+            model_version=getattr(self, "model_version", None) or "*",
             vpc_config=self.vpc_config,
             sagemaker_session=self.sagemaker_session,
             name=self.name,

src/sagemaker/serve/builder/model_builder.py

@@ -225,6 +225,8 @@ class ModelBuilder(Triton, DJL, JumpStart, TGI, Transformers, TensorflowServing,
             available for providing s3 path to fine-tuned model artifacts. ``FINE_TUNING_JOB_NAME``
             is available for providing fine-tuned job name. Both ``FINE_TUNING_MODEL_PATH`` and
             ``FINE_TUNING_JOB_NAME`` are mutually exclusive.
+        model_version (Optional[str]): Override the JumpStart model version to resolve.
+            Defaults to ``"*"`` (latest) when not set. Ignored for non-JumpStart models.
         inference_component_name (Optional[str]): The name for an inference component
             created from this ModelBuilder instance. This or ``resource_requirements`` must be set
             to denote that this instance refers to an inference component.
@@ -337,6 +339,13 @@ class ModelBuilder(Triton, DJL, JumpStart, TGI, Transformers, TensorflowServing,
             "in the Hub, Adding unsupported task types will throw an exception."
         },
     )
+    model_version: Optional[str] = field(
+        default=None,
+        metadata={
+            "help": "Override the JumpStart model version to resolve. Defaults to the "
+            "latest version ('*') when not set. Ignored for non-JumpStart models."
+        },
+    )
     inference_component_name: Optional[str] = field(
         default=None,
         metadata={

tests/integ/sagemaker/jumpstart/model/test_jumpstart_model.py

@@ -197,12 +197,11 @@ def test_jumpstart_gated_model_inference_component_enabled(setup):
 
     model = JumpStartModel(
         model_id=model_id,
-        model_version="*",  # version >=3.0.0 stores artifacts in jumpstart-private-cache-* buckets
+        model_version="4.*",  # pin: v5.0.0 default image fails to start
         role=get_sm_session().get_caller_identity_arn(),
         sagemaker_session=get_sm_session(),
     )
 
-    # uses ml.g5.2xlarge instance
     model.deploy(
         tags=[{"Key": JUMPSTART_TAG, "Value": os.environ[ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID]}],
         accept_eula=True,

tests/integ/sagemaker/serve/test_serve_model_builder_inference_component_happy.py

@@ -48,6 +48,8 @@
 def model_builder_llama_inference_component():
     return ModelBuilder(
         model=LLAMA_2_7B_JS_ID,
+        # Pin: JumpStart v5.0.0 default image fails to start for this model.
+        model_version="4.*",
         schema_builder=SchemaBuilder(sample_input, sample_output),
         resource_requirements=ResourceRequirements(
             requests={"memory": 98304, "num_accelerators": 4, "copies": 1, "num_cpus": 40}

tests/unit/sagemaker/serve/builder/test_js_builder.py

@@ -1957,3 +1957,38 @@ def test_optimize_on_js_model_test_image_defaulting_scenarios(
             optimization_args["OptimizationConfigs"][0]["ModelQuantizationConfig"]["Image"],
             "763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.29.0-lmi13.0.1-cu124",
         )
+
+
+class TestModelBuilderJumpStartModelVersion(unittest.TestCase):
+    """``ModelBuilder.model_version`` should be threaded into JumpStart resolution."""
+
+    @patch("sagemaker.serve.builder.jumpstart_builder.model_uris.retrieve")
+    def test_is_jumpstart_model_id_defaults_to_star(self, mock_retrieve):
+        mb = ModelBuilder(model=mock_model_id, schema_builder=mock_schema_builder)
+        self.assertTrue(mb._is_jumpstart_model_id())
+        mock_retrieve.assert_called_once()
+        self.assertEqual(mock_retrieve.call_args.kwargs["model_version"], "*")
+
+    @patch("sagemaker.serve.builder.jumpstart_builder.model_uris.retrieve")
+    def test_is_jumpstart_model_id_uses_override(self, mock_retrieve):
+        mb = ModelBuilder(
+            model=mock_model_id, schema_builder=mock_schema_builder, model_version="4.*"
+        )
+        self.assertTrue(mb._is_jumpstart_model_id())
+        self.assertEqual(mock_retrieve.call_args.kwargs["model_version"], "4.*")
+
+    @patch("sagemaker.serve.builder.jumpstart_builder.JumpStartModel")
+    def test_create_pre_trained_js_model_defaults_to_star(self, mock_js_model_cls):
+        mock_js_model_cls.return_value = MagicMock(deploy=MagicMock())
+        mb = ModelBuilder(model=mock_model_id, schema_builder=mock_schema_builder)
+        mb._create_pre_trained_js_model()
+        self.assertEqual(mock_js_model_cls.call_args.kwargs["model_version"], "*")
+
+    @patch("sagemaker.serve.builder.jumpstart_builder.JumpStartModel")
+    def test_create_pre_trained_js_model_uses_override(self, mock_js_model_cls):
+        mock_js_model_cls.return_value = MagicMock(deploy=MagicMock())
+        mb = ModelBuilder(
+            model=mock_model_id, schema_builder=mock_schema_builder, model_version="4.*"
+        )
+        mb._create_pre_trained_js_model()
+        self.assertEqual(mock_js_model_cls.call_args.kwargs["model_version"], "4.*")