feat: migrate model garden to agentplatform

PiperOrigin-RevId: 910885525

Author: yyyu-google

.kokoro/docker/docs/Dockerfile

@@ -21,7 +21,10 @@ ENV PATH /usr/local/bin:$PATH
 
 # Install dependencies.
 RUN apt-get update \
-  && apt-get install -y --no-install-recommends \
+  && apt-get install -y ca-certificates --fix-missing \
+  && update-ca-certificates
+
+RUN apt-get install -y --no-install-recommends \
     apt-transport-https \
     build-essential \
     ca-certificates \

agentplatform/__init__.py

@@ -14,11 +14,26 @@
 #
 """The agentplatform module."""
 
+import importlib
 from google.cloud.aiplatform import init
 from google.cloud.aiplatform import version as aiplatform_version
 
 __version__ = aiplatform_version.__version__
 
+
+def __getattr__(name):  # type: ignore[no-untyped-def]
+    if name == "preview":
+        # We need to import carefully to avoid `RecursionError`.
+        # This won't work since it causes `RecursionError`:
+        # `from agentplatform import preview`
+        # This won't work due to Copybara lacking a transform:
+        # `import google.cloud.aiplatform.agentplatform.preview as`
+        #    `agentplatform_preview`
+        return importlib.import_module(".preview", __name__)
+    raise AttributeError(f"module '{__name__}' has no attribute '{name}'")
+
+
 __all__ = [
     "init",
+    "preview",
 ]

agentplatform/model_garden/README.md

@@ -0,0 +1,214 @@
+# Gemini Enterprise Agent Platform Model Garden SDK for Python
+
+The Gemini Enterprise Agent Platform Model Garden SDK helps developers use [Model Garden](https://cloud.google.com/model-garden) open models to build AI-powered features and applications.
+The SDKs support use cases like the following:
+
+- Deploy an open model
+- Export open model weights
+
+## Installation
+
+To install the
+[google-cloud-aiplatform](https://pypi.org/project/google-cloud-aiplatform/)
+Python package, run the following command:
+
+```shell
+pip3 install --upgrade --user "google-cloud-aiplatform>=1.84"
+```
+
+## Usage
+
+For detailed instructions, see [deploy an open model](https://cloud.google.com/vertex-ai/generative-ai/docs/model-garden/use-models#deploy_an_open_model) and [deploy notebook tutorial](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/community/model_garden/model_garden_deployment_tutorial.ipynb).
+
+## Quick Start: Default Deployment
+
+This is the simplest way to deploy a model. If you provide just a model name, the SDK will use the default deployment configuration.
+
+```python
+from agentplatform import model_garden
+
+model = model_garden.OpenModel("google/paligemma@paligemma-224-float32")
+endpoint = model.deploy()
+```
+
+**Use case:** Fast prototyping, first-time users evaluating model outputs.
+
+## List Deployable Models
+
+You can list all models that are currently deployable via Model Garden:
+
+```python
+from agentplatform import model_garden
+
+models = model_garden.list_deployable_models()
+```
+
+To filter only Hugging Face models or by keyword:
+
+```python
+models = model_garden.list_deployable_models(list_hf_models=True, model_filter="stable-diffusion")
+```
+
+**Use case:** Discover available models before deciding which one to deploy.
+
+## Hugging Face Model Deployment
+
+Deploy a model directly from Hugging Face using the model ID.
+
+```python
+model = model_garden.OpenModel("Qwen/Qwen2-1.5B-Instruct")
+endpoint = model.deploy()
+```
+
+**Use case:** Leverage community or third-party models without custom container setup. If the model is gated, you may need to provide a Hugging Face access token:
+
+```python
+endpoint = model.deploy(hugging_face_access_token="your_hf_token")
+```
+
+**Use case:** Deploy gated Hugging Face models requiring authentication.
+
+## List Deployment Configurations
+
+You can inspect available deployment configurations for a model:
+
+```python
+model = model_garden.OpenModel("google/paligemma@paligemma-224-float32")
+deploy_options = model.list_deploy_options()
+```
+
+**Use case:** Evaluate compatible machine specs and containers before deployment.
+
+## Select a Verified Deployment: By Container Image
+
+Specify a container image from the list of verified deployment configurations.
+
+```python
+endpoint = model.deploy(
+    serving_container_image_uri="us-docker.pkg.dev/vertex-ai/vertex-vision-model-garden-dockers/pytorch-vllm-serve:20250430_0916_RC00_maas",
+)
+```
+
+## Select a Verified Deployment: By Hardware
+
+Specify a hardware configuration from the list of verified deployment configurations.
+
+```python
+endpoints = model.deploy(
+    machine_type="a3-highgpu-1g",
+    accelerator_type="NVIDIA_H100_80GB",
+    accelerator_count=1,
+)
+```
+
+## Select a Verified Deployment: By Container and Hardware
+
+Specify both a container image and a hardware configuration from the list of verified deployment configurations.
+
+```python
+endpoint = model.deploy(
+    serving_container_image_uri="us-docker.pkg.dev/vertex-ai/vertex-vision-model-garden-dockers/pytorch-vllm-serve:20250430_0916_RC00_maas",
+    machine_type="a3-highgpu-1g",
+    accelerator_type="NVIDIA_H100_80GB",
+    accelerator_count=1,
+)
+```
+
+**Use case:** Production configuration, performance tuning, scaling.
+
+## EULA Acceptance
+
+Some models require acceptance of a license agreement. Pass `eula=True` if prompted.
+
+```python
+model = model_garden.OpenModel("google/gemma2@gemma-2-27b-it")
+endpoint = model.deploy(eula=True)
+```
+
+**Use case:** First-time deployment of EULA-protected models.
+
+## Spot VM Deployment
+
+Schedule workloads on Spot VMs for lower cost.
+
+```python
+endpoint = model.deploy(spot=True)
+```
+
+**Use case:** Cost-sensitive development and batch workloads.
+
+## Fast Tryout Deployment
+
+Enable experimental fast-deploy path for popular models.
+
+```python
+endpoint = model.deploy(fast_tryout_enabled=True)
+```
+
+**Use case:** Interactive experimentation without full production setup.
+
+## Dedicated Endpoints
+
+Create a dedicated DNS-isolated endpoint.
+
+```python
+endpoint = model.deploy(use_dedicated_endpoint=True)
+```
+
+**Use case:** Traffic isolation for enterprise or regulated workloads.
+
+## Reservation Affinity
+
+Use shared or specific Compute Engine reservations.
+
+```python
+endpoint = model.deploy(
+    reservation_affinity_type="SPECIFIC_RESERVATION",
+    reservation_affinity_key="compute.googleapis.com/reservation-name",
+    reservation_affinity_values="projects/YOUR_PROJECT/zones/YOUR_ZONE/reservations/YOUR_RESERVATION"
+)
+```
+
+**Use case:** Optimized resource usage with pre-reserved capacity.
+
+## Custom Container Image
+
+Override the default container with a custom image.
+
+```python
+endpoint = model.deploy(
+    serving_container_image_uri="us-docker.pkg.dev/vertex-ai/custom-container:latest"
+)
+```
+
+**Use case:** Use of custom inference servers or fine-tuned environments.
+
+## Advanced Full Container Configuration
+
+Further customize startup probes, health checks, shared memory, and gRPC ports.
+
+```python
+endpoint = model.deploy(
+    serving_container_image_uri="us-docker.pkg.dev/vertex-ai/custom-container:latest",
+    container_command=["python3"],
+    container_args=["serve.py"],
+    container_ports=[8888],
+    container_env_vars={"ENV": "prod"},
+    container_predict_route="/predict",
+    container_health_route="/health",
+    serving_container_shared_memory_size_mb=512,
+    serving_container_grpc_ports=[9000],
+    serving_container_startup_probe_exec=["/bin/check-start.sh"],
+    serving_container_health_probe_exec=["/bin/health-check.sh"]
+)
+```
+
+**Use case:** Production-grade deployments requiring deep customization of runtime behavior and monitoring.
+
+## Contributing
+
+See [Contributing](https://github.com/googleapis/python-aiplatform/blob/main/CONTRIBUTING.rst) for more information on contributing to the Gemini Enterprise Agent Platform Python SDK.
+
+## License
+
+The contents of this repository are licensed under the [Apache License, version 2.0](http://www.apache.org/licenses/LICENSE-2.0).

agentplatform/model_garden/__init__.py

@@ -0,0 +1,27 @@
+# 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
+#
+#     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.
+#
+
+"""Classes and functions for working with Model Garden."""
+
+# We just want to re-export certain classes
+# pylint: disable=g-multiple-import,g-importing-member
+from agentplatform.model_garden import _model_garden
+
+OpenModel = _model_garden.OpenModel
+PartnerModel = _model_garden.PartnerModel
+list_deployable_models = _model_garden.list_deployable_models
+list_models = _model_garden.list_models
+
+__all__ = ("OpenModel", "PartnerModel", "list_deployable_models", "list_models")