feat(model_garden): add new samples to list models and deploy a model (#13236)

* feat(generative-ai): add samples for the new Model Garden SDK

* chore: move Model Garden SDK samples from generative_ai/model_garden/sdk to model_garden/sdk.

* refactor: clean up the code to address lint errors

* refactor: clean up the code to address more lint errors

* feature: remove sdk/ folder, add deploy/ folder and add test with mock.

* chore: delete files in sdk/ folder

* fix lint issues

* fix lint issues

* address comments

* add some comments

* remove trailing whitespace

* fixing a few more things

* fixing a few more things

* fix import names

* fix import names

* fix import names

Author: wuliang229

model_garden/gemma/gemma3_deploy.py

@@ -0,0 +1,52 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Google Cloud Vertex AI sample for deploying Gemma 3 in Model Garden.
+"""
+import os
+
+from google.cloud import aiplatform
+
+
+PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
+
+
+def deploy() -> aiplatform.Endpoint:
+    # [START aiplatform_modelgarden_gemma3_deploy]
+
+    import vertexai
+    from vertexai.preview import model_garden
+
+    # TODO(developer): Update and un-comment below lines
+    # PROJECT_ID = "your-project-id"
+    vertexai.init(project=PROJECT_ID, location="us-central1")
+
+    open_model = model_garden.OpenModel("google/gemma3@gemma-3-12b-it")
+    endpoint = open_model.deploy(
+        machine_type="g2-standard-48",
+        accelerator_type="NVIDIA_L4",
+        accelerator_count=4,
+        accept_eula=True,
+    )
+
+    # Optional. Run predictions on the deployed endoint.
+    # endpoint.predict(instances=[{"prompt": "What is Generative AI?"}])
+
+    # [END aiplatform_modelgarden_gemma3_deploy]
+
+    return endpoint
+
+
+if __name__ == "__main__":
+    deploy()

model_garden/gemma/models_deploy_options_list.py

@@ -0,0 +1,67 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Google Cloud Vertex AI sample for listing verified deploy
+    options for models in Model Garden.
+"""
+import os
+from typing import List
+
+from google.cloud.aiplatform_v1beta1 import types
+
+
+PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
+
+
+def list_deploy_options(model : str) -> List[types.PublisherModel.CallToAction.Deploy]:
+    # [START aiplatform_modelgarden_models_deployables_options_list]
+
+    import vertexai
+    from vertexai.preview import model_garden
+
+    # TODO(developer): Update and un-comment below lines
+    # PROJECT_ID = "your-project-id"
+    # model = "google/gemma3@gemma-3-1b-it"
+    vertexai.init(project=PROJECT_ID, location="us-central1")
+
+    # For Hugging Face modelsm the format is the Hugging Face model name, as in
+    # "meta-llama/Llama-3.3-70B-Instruct".
+    # Go to https://console.cloud.google.com/vertex-ai/model-garden to find all deployable
+    # model names.
+
+    model = model_garden.OpenModel(model)
+    deploy_options = model.list_deploy_options()
+    print(deploy_options)
+    # Example response:
+    # [
+    #   dedicated_resources {
+    #     machine_spec {
+    #       machine_type: "g2-standard-12"
+    #       accelerator_type: NVIDIA_L4
+    #       accelerator_count: 1
+    #     }
+    #   }
+    #   container_spec {
+    #     ...
+    #   }
+    #   ...
+    # ]
+
+    # [END aiplatform_modelgarden_models_deployables_options_list]
+
+    return deploy_options
+
+
+if __name__ == "__main__":
+    list_deploy_options("google/gemma3@gemma-3-1b-it")

model_garden/gemma/models_deployable_list.py

@@ -0,0 +1,47 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Google Cloud Vertex AI sample for listing deployable models in
+    Model Garden.
+"""
+import os
+from typing import List
+
+
+PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
+
+
+def list_deployable_models() -> List[str]:
+    # [START aiplatform_modelgarden_models_deployables_list]
+
+    import vertexai
+    from vertexai.preview import model_garden
+
+    # TODO(developer): Update and un-comment below lines
+    # PROJECT_ID = "your-project-id"
+    vertexai.init(project=PROJECT_ID, location="us-central1")
+
+    # List deployable models, optionally list Hugging Face models only or filter by model name.
+    deployable_models = model_garden.list_deployable_models(list_hf_models=False, model_filter="gemma")
+    print(deployable_models)
+    # Example response:
+    # ['google/gemma2@gemma-2-27b','google/gemma2@gemma-2-27b-it', ...]
+
+    # [END aiplatform_modelgarden_models_deployables_list]
+
+    return deployable_models
+
+
+if __name__ == "__main__":
+    list_deployable_models()

model_garden/gemma/noxfile_config.py

@@ -0,0 +1,42 @@
+# Copyright 2021 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Default TEST_CONFIG_OVERRIDE for python repos.
+
+# You can copy this file into your directory, then it will be imported from
+# the noxfile.py.
+
+# The source of truth:
+# https://github.com/GoogleCloudPlatform/python-docs-samples/blob/main/noxfile_config.py
+
+TEST_CONFIG_OVERRIDE = {
+    # You can opt out from the test for specific Python versions.
+    "ignored_versions": ["2.7", "3.7", "3.8", "3.10", "3.11", "3.13"],
+    # Old samples are opted out of enforcing Python type hints
+    # All new samples should feature them
+    "enforce_type_hints": True,
+    # An envvar key for determining the project id to use. Change it
+    # to 'BUILD_SPECIFIC_GCLOUD_PROJECT' if you want to opt in using a
+    # build specific Cloud project. You can also use your own string
+    # to use your own Cloud project.
+    "gcloud_project_env": "GOOGLE_CLOUD_PROJECT",
+    # 'gcloud_project_env': 'BUILD_SPECIFIC_GCLOUD_PROJECT',
+    # If you need to use a specific version of pip,
+    # change pip_version_override to the string representation
+    # of the version number, for example, "20.2.4"
+    "pip_version_override": None,
+    # A dictionary you want to inject into your test. Don't put any
+    # secrets here. These values will override predefined values.
+    "envs": {},
+}

model_garden/gemma/requirements-test.txt

@@ -0,0 +1,4 @@
+backoff==2.2.1
+google-api-core==2.19.0
+pytest==8.2.0
+pytest-asyncio==0.23.6

model_garden/gemma/requirements.txt

@@ -0,0 +1 @@
+google-cloud-aiplatform[all]==1.84.0

model_garden/gemma/test_model_garden_examples.py

@@ -0,0 +1,50 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from unittest.mock import MagicMock, patch
+
+from google.cloud import aiplatform
+
+import gemma3_deploy
+import models_deploy_options_list
+import models_deployable_list
+
+
+def test_list_deployable_models() -> None:
+    models = models_deployable_list.list_deployable_models()
+    assert len(models) > 0
+    assert "gemma" in models[0]
+
+
+def test_list_deploy_options() -> None:
+    deploy_options = models_deploy_options_list.list_deploy_options(
+        model="google/gemma3@gemma-3-1b-it"
+    )
+    assert len(deploy_options) > 0
+
+
+@patch("vertexai.preview.model_garden.OpenModel")
+def test_gemma3_deploy(mock_open_model: MagicMock) -> None:
+    # Mock the deploy response.
+    mock_endpoint = aiplatform.Endpoint(endpoint_name="test-endpoint-name")
+    mock_open_model.return_value.deploy.return_value = mock_endpoint
+    endpoint = gemma3_deploy.deploy()
+    assert endpoint
+    mock_open_model.assert_called_once_with("google/gemma3@gemma-3-12b-it")
+    mock_open_model.return_value.deploy.assert_called_once_with(
+        machine_type="g2-standard-48",
+        accelerator_type="NVIDIA_L4",
+        accelerator_count=4,
+        accept_eula=True,
+    )