Merge branch 'googleapis:main' into fix/option-to-set-fps-in-video-metadata

Author: philipshurpik

.kokoro/build.sh

@@ -36,6 +36,9 @@ export PROJECT_ID=$(cat "${KOKORO_GFILE_DIR}/project-id.json")
 # Remove old nox
 python3 -m pip uninstall --yes --quiet nox-automation
 
+# Match the docker version to the one used by the test runner for CPR
+export DOCKER_API_VERSION=1.39
+
 # Install nox
 python3 -m pip install --upgrade --quiet uv nox
 python3 -m nox --version

.kokoro/test-samples-impl.sh

@@ -34,7 +34,7 @@ env | grep KOKORO
 
 # Install nox
 # `virtualenv==20.26.6` is added for Python 3.7 compatibility
-python3 -m pip install --upgrade --quiet nox uv virtualenv==20.26.6
+python3 -m pip install --upgrade --quiet nox virtualenv==20.26.6
 
 # Use secrets acessor service account to get secrets
 if [[ -f "${KOKORO_GFILE_DIR}/secrets_viewer_service_account.json" ]]; then

.release-please-manifest.json

@@ -1,3 +1,3 @@
 {
-    ".": "1.124.0"
+    ".": "1.132.0"
 }

CHANGELOG.md

@@ -6,6 +6,8 @@ Vertex AI SDK
     :show-inheritance:
     :inherited-members:
 
+    .. autoattribute:: types
+
 .. autoclass:: vertexai.Client
     :members:
     :undoc-members:
@@ -37,6 +39,11 @@ Vertex AI SDK
     :undoc-members:
     :show-inheritance:
 
+.. automodule:: vertexai._genai.types
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
 .. automodule:: vertexai.generative_models
     :members:
     :show-inheritance:

gemini_docs/vertexai/vertexai.rst

@@ -13,4 +13,4 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
-__version__ = "1.124.0"  # {x-release-please-version}
+__version__ = "1.132.0"  # {x-release-please-version}

google/cloud/aiplatform/gapic_version.py

@@ -722,7 +722,7 @@ def _set_async_rest_credentials(credentials: AsyncCredentials):
             + "google-auth >= 2.35.0.\n\n"
             + "Install the following dependencies:\n"
             + "pip install google-api-core[grpc, async_rest] >= 2.21.0\n"
-            + "pip install google-auth[aiohttp] >= 2.35.0\n\n"
+            + "pip install google-auth[aiohttp] >= 2.45.0\n\n"
             + "Example usage:\n"
             + "from google.auth.aio.credentials import StaticCredentials\n"
             + "async_credentials = StaticCredentials(token=YOUR_TOKEN_HERE)\n"

google/cloud/aiplatform/initializer.py

@@ -319,7 +319,7 @@ def cancel(self) -> None:
         getattr(self.api_client, self._cancel_method)(name=self.resource_name)
 
 
-class BatchPredictionJob(_Job):
+class BatchPredictionJob(_Job, base.PreviewMixin):
 
     _resource_noun = "batchPredictionJobs"
     _getter_method = "get_batch_prediction_job"
@@ -329,6 +329,9 @@ class BatchPredictionJob(_Job):
     _job_type = "batch-predictions"
     _parse_resource_name_method = "parse_batch_prediction_job_path"
     _format_resource_name_method = "batch_prediction_job_path"
+    _preview_class = (
+        "google.cloud.aiplatform.aiplatform.preview.jobs.BatchPredictionJob"
+    )
 
     def __init__(
         self,
@@ -949,6 +952,9 @@ def _submit_impl(
         ] = None,
         analysis_instance_schema_uri: Optional[str] = None,
         service_account: Optional[str] = None,
+        reservation_affinity_type: Optional[str] = None,
+        reservation_affinity_key: Optional[str] = None,
+        reservation_affinity_values: Optional[Sequence[str]] = None,
         wait_for_completion: bool = False,
     ) -> "BatchPredictionJob":
         """Create a batch prediction job.
@@ -1136,6 +1142,18 @@ def _submit_impl(
             service_account (str):
                 Optional. Specifies the service account for workload run-as account.
                 Users submitting jobs must have act-as permission on this run-as account.
+            reservation_affinity_type (str):
+                Optional. The type of reservation affinity.
+                One of NO_RESERVATION, ANY_RESERVATION, SPECIFIC_RESERVATION,
+                SPECIFIC_THEN_ANY_RESERVATION, SPECIFIC_THEN_NO_RESERVATION
+            reservation_affinity_key (str):
+                Optional. Corresponds to the label key of a reservation resource.
+                To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key
+                and specify the name of your reservation as its value.
+            reservation_affinity_values (List[str]):
+                Optional. Corresponds to the label values of a reservation resource.
+                This must be the full resource name of the reservation.
+                Format: 'projects/{project_id_or_number}/zones/{zone}/reservations/{reservation_name}'
             wait_for_completion (bool):
                 Whether to wait for the job completion.
         Returns:
@@ -1268,6 +1286,13 @@ def _submit_impl(
             machine_spec.accelerator_type = accelerator_type
             machine_spec.accelerator_count = accelerator_count
 
+            if reservation_affinity_type:
+                machine_spec.reservation_affinity = utils.get_reservation_affinity(
+                    reservation_affinity_type,
+                    reservation_affinity_key,
+                    reservation_affinity_values,
+                )
+
             dedicated_resources = gca_machine_resources_compat.BatchDedicatedResources()
 
             dedicated_resources.machine_spec = machine_spec

google/cloud/aiplatform/jobs.py

@@ -16,7 +16,7 @@
 #
 
 from dataclasses import dataclass, field
-from typing import Dict, List, Optional, Sequence, Tuple, Union
+from typing import Dict, List, Optional, Sequence, Tuple, Union, Any, Mapping
 
 from google.auth import credentials as auth_credentials
 from google.cloud.aiplatform import base
@@ -208,6 +208,8 @@ class MatchNeighbor:
             For example, values [1,2,3] with dimensions [4,5,6] means value 1 is
             of the 4th dimension, value 2 is of the 4th dimension, and value 3 is
             of the 6th dimension.
+        embedding_metadata (Mapping[str, Any]):
+            Optional. The corresponding embedding metadata of the matching datapoint.
 
     """
 
@@ -220,6 +222,7 @@ class MatchNeighbor:
     numeric_restricts: Optional[List[NumericNamespace]] = None
     sparse_embedding_values: Optional[List[float]] = None
     sparse_embedding_dimensions: Optional[List[int]] = None
+    embedding_metadata: Optional[Mapping[str, Any]] = None
 
     def from_index_datapoint(
         self, index_datapoint: gca_index_v1beta1.IndexDatapoint
@@ -276,6 +279,9 @@ def from_index_datapoint(
             self.sparse_embedding_dimensions = (
                 index_datapoint.sparse_embedding.dimensions
             )
+        # retrieve embedding metadata
+        if index_datapoint.embedding_metadata is not None:
+            self.embedding_metadata = index_datapoint.embedding_metadata
         return self
 
     def from_embedding(self, embedding: match_service_pb2.Embedding) -> "MatchNeighbor":
@@ -702,10 +708,10 @@ def _get_psc_automated_deployed_index_ip_address(
         psc_network: Optional[str] = None,
     ) -> str:
         """Helper method to get the ip address for a psc automated endpoint.
-        Returns:
+        Args:
             deployed_index_id (str):
-                    Optional. Required for private service access endpoint.
-                    The user specified ID of the DeployedIndex.
+                Optional. Required for private service access endpoint.
+                The user specified ID of the DeployedIndex.
             deployed_index (gca_matching_engine_index_endpoint.DeployedIndex):
                 Optional. Required for private service access endpoint.
                 The DeployedIndex resource.
@@ -722,6 +728,9 @@ def _get_psc_automated_deployed_index_ip_address(
                 MatchingEngineIndexEndpoint instance, if the ip address is
                 already known.
 
+        Returns:
+            str: The IP address for the PSC automated endpoint.
+
         Raises:
             RuntimeError: No valid ip found for deployed index with id
                 deployed_index_id within network psc_network, invalid PSC