Copybara import of the project:

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26df187 by Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>:

feat: Expose zone when creating a FeatureOnlineStore

PiperOrigin-RevId: 837256132

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Source-Link: googleapis/googleapis-gen@ab6c512
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ac65bf3 by Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>:

feat: A new field `min_gpu_driver_version` is added to message `.google.cloud.aiplatform.v1beta1.MachineSpec`

PiperOrigin-RevId: 838969898

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f2ffce6 by Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>:

docs: update `ReplicatedVoiceConfig.mime_type` comment

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19f6e28 by Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>:

docs: update `ReplicatedVoiceConfig.mime_type` comment

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1ea25e8 by Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>:

feat: Expose FullFineTunedResources for full fine tuned deployments

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9065bc2 by Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>:

feat: Introduce RagManagedVertexVectorSearch as a new vector db option
feat: add RagCorpus.satisfies_pzs and RagCorpus.satisfies_pzi
docs: A comment for field `rag_files_count` in message `.google.cloud.aiplatform.v1beta1.RagCorpus` is changed
docs: A comment for field `user_metadata` in message `.google.cloud.aiplatform.v1beta1.RagFile` is changed
docs: A comment for field `gcs_metadata_schema_source` in message `.google.cloud.aiplatform.v1beta1.RagFileMetadataConfig` is changed
docs: A comment for field `google_drive_metadata_schema_source` in message `.google.cloud.aiplatform.v1beta1.RagFileMetadataConfig` is changed
docs: A comment for field `gcs_metadata_source` in message `.google.cloud.aiplatform.v1beta1.RagFileMetadataConfig` is changed
docs: A comment for field `google_drive_metadata_source` in message `.google.cloud.aiplatform.v1beta1.RagFileMetadataConfig` is changed
docs: A comment for message `RagManagedDbConfig` is changed
docs: A comment for field `enterprise` in message `.google.cloud.aiplatform.v1beta1.RagManagedDbConfig` is changed
docs: A comment for field `scaled` in message `.google.cloud.aiplatform.v1beta1.RagManagedDbConfig` is changed

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COPYBARA_INTEGRATE_REVIEW=#6170 from googleapis:owl-bot-copy d471f76
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Author: gcf-owl-bot[bot]

google/cloud/aiplatform_v1/services/migration_service/client.py

@@ -265,40 +265,40 @@ def parse_dataset_path(path: str) -> Dict[str, str]:
     @staticmethod
     def dataset_path(
         project: str,
-        location: str,
         dataset: str,
     ) -> str:
         """Returns a fully-qualified dataset string."""
-        return "projects/{project}/locations/{location}/datasets/{dataset}".format(
+        return "projects/{project}/datasets/{dataset}".format(
             project=project,
-            location=location,
             dataset=dataset,
         )
 
     @staticmethod
     def parse_dataset_path(path: str) -> Dict[str, str]:
         """Parses a dataset path into its component segments."""
-        m = re.match(
-            r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/datasets/(?P<dataset>.+?)$",
-            path,
-        )
+        m = re.match(r"^projects/(?P<project>.+?)/datasets/(?P<dataset>.+?)$", path)
         return m.groupdict() if m else {}
 
     @staticmethod
     def dataset_path(
         project: str,
+        location: str,
         dataset: str,
     ) -> str:
         """Returns a fully-qualified dataset string."""
-        return "projects/{project}/datasets/{dataset}".format(
+        return "projects/{project}/locations/{location}/datasets/{dataset}".format(
             project=project,
+            location=location,
             dataset=dataset,
         )
 
     @staticmethod
     def parse_dataset_path(path: str) -> Dict[str, str]:
         """Parses a dataset path into its component segments."""
-        m = re.match(r"^projects/(?P<project>.+?)/datasets/(?P<dataset>.+?)$", path)
+        m = re.match(
+            r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/datasets/(?P<dataset>.+?)$",
+            path,
+        )
         return m.groupdict() if m else {}
 
     @staticmethod

google/cloud/aiplatform_v1/types/content.py

@@ -371,9 +371,11 @@ class ReplicatedVoiceConfig(proto.Message):
 
     Attributes:
         mime_type (str):
-            Optional. The mimetype of the voice sample. Currently only
-            mime_type=audio/pcm is supported, which is raw mono 16-bit
-            signed little-endian pcm data, with 24k sampling rate.
+            Optional. The mimetype of the voice sample. The only
+            currently supported value is ``audio/wav``. This represents
+            16-bit signed little-endian wav data, with a 24kHz sampling
+            rate. ``mime_type`` will default to ``audio/wav`` if not
+            set.
         voice_sample_audio (bytes):
             Optional. The sample of the custom voice.
     """

google/cloud/aiplatform_v1/types/feature_online_store.py

@@ -146,6 +146,12 @@ class Bigtable(proto.Message):
             bigtable_metadata (google.cloud.aiplatform_v1.types.FeatureOnlineStore.Bigtable.BigtableMetadata):
                 Output only. Metadata of the Bigtable
                 instance. Output only.
+            zone (str):
+                Optional. The zone where the underlying
+                Bigtable cluster for the primary Bigtable
+                instance will be provisioned. Only the zone must
+                be provided. For example, only "us-central1-a"
+                should be provided.
         """
 
         class AutoScaling(proto.Message):
@@ -223,6 +229,10 @@ class BigtableMetadata(proto.Message):
             number=4,
             message="FeatureOnlineStore.Bigtable.BigtableMetadata",
         )
+        zone: str = proto.Field(
+            proto.STRING,
+            number=5,
+        )
 
     class Optimized(proto.Message):
         r"""Optimized storage type"""

google/cloud/aiplatform_v1beta1/__init__.py

@@ -742,6 +742,7 @@
 from .types.machine_resources import DedicatedResources
 from .types.machine_resources import DiskSpec
 from .types.machine_resources import FlexStart
+from .types.machine_resources import FullFineTunedResources
 from .types.machine_resources import MachineSpec
 from .types.machine_resources import NfsMount
 from .types.machine_resources import PersistentDiskSpec
@@ -1767,6 +1768,7 @@
     "FulfillmentInstance",
     "FulfillmentResult",
     "FulfillmentSpec",
+    "FullFineTunedResources",
     "FunctionCall",
     "FunctionCallingConfig",
     "FunctionDeclaration",

google/cloud/aiplatform_v1beta1/types/__init__.py

@@ -769,6 +769,7 @@
     DedicatedResources,
     DiskSpec,
     FlexStart,
+    FullFineTunedResources,
     MachineSpec,
     NfsMount,
     PersistentDiskSpec,
@@ -2100,6 +2101,7 @@
     "DedicatedResources",
     "DiskSpec",
     "FlexStart",
+    "FullFineTunedResources",
     "MachineSpec",
     "NfsMount",
     "PersistentDiskSpec",

google/cloud/aiplatform_v1beta1/types/content.py

@@ -371,9 +371,11 @@ class ReplicatedVoiceConfig(proto.Message):
 
     Attributes:
         mime_type (str):
-            Optional. The mimetype of the voice sample. Currently only
-            mime_type=audio/pcm is supported, which is raw mono 16-bit
-            signed little-endian pcm data, with 24k sampling rate.
+            Optional. The mimetype of the voice sample. The only
+            currently supported value is ``audio/wav``. This represents
+            16-bit signed little-endian wav data, with a 24kHz sampling
+            rate. ``mime_type`` will default to ``audio/wav`` if not
+            set.
         voice_sample_audio (bytes):
             Optional. The sample of the custom voice.
     """

google/cloud/aiplatform_v1beta1/types/endpoint.py

@@ -315,6 +315,11 @@ class DeployedModel(proto.Message):
             deploy on. Format:
             ``projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}``
 
+            This field is a member of `oneof`_ ``prediction_resources``.
+        full_fine_tuned_resources (google.cloud.aiplatform_v1beta1.types.FullFineTunedResources):
+            Optional. Resources for a full fine tuned
+            model.
+
             This field is a member of `oneof`_ ``prediction_resources``.
         id (str):
             Immutable. The ID of the DeployedModel. If not provided upon
@@ -475,6 +480,12 @@ class Status(proto.Message):
         number=17,
         oneof="prediction_resources",
     )
+    full_fine_tuned_resources: machine_resources.FullFineTunedResources = proto.Field(
+        proto.MESSAGE,
+        number=36,
+        oneof="prediction_resources",
+        message=machine_resources.FullFineTunedResources,
+    )
     id: str = proto.Field(
         proto.STRING,
         number=1,

google/cloud/aiplatform_v1beta1/types/feature_online_store.py

@@ -151,6 +151,12 @@ class Bigtable(proto.Message):
             bigtable_metadata (google.cloud.aiplatform_v1beta1.types.FeatureOnlineStore.Bigtable.BigtableMetadata):
                 Metadata of the Bigtable instance. Output
                 only.
+            zone (str):
+                Optional. The zone where the underlying
+                Bigtable cluster for the primary Bigtable
+                instance will be provisioned. Only the zone must
+                be provided. For example, only "us-central1-a"
+                should be provided.
         """
 
         class AutoScaling(proto.Message):
@@ -228,6 +234,10 @@ class BigtableMetadata(proto.Message):
             number=4,
             message="FeatureOnlineStore.Bigtable.BigtableMetadata",
         )
+        zone: str = proto.Field(
+            proto.STRING,
+            number=5,
+        )
 
     class Optimized(proto.Message):
         r"""Optimized storage type"""

google/cloud/aiplatform_v1beta1/types/machine_resources.py

@@ -35,6 +35,7 @@
         "DedicatedResources",
         "AutomaticResources",
         "BatchDedicatedResources",
+        "FullFineTunedResources",
         "ResourcesConsumed",
         "DiskSpec",
         "PersistentDiskSpec",
@@ -100,6 +101,12 @@ class MachineSpec(proto.Message):
             Optional. Immutable. Configuration
             controlling how this resource pool consumes
             reservation.
+        min_gpu_driver_version (str):
+            Optional. Immutable. The minimum GPU driver
+            version that this machine requires. For example,
+            "535.104.06". If not specified, the default GPU
+            driver version will be used by the underlying
+            infrastructure.
     """
 
     machine_type: str = proto.Field(
@@ -132,6 +139,10 @@ class MachineSpec(proto.Message):
         number=5,
         message=gca_reservation_affinity.ReservationAffinity,
     )
+    min_gpu_driver_version: str = proto.Field(
+        proto.STRING,
+        number=9,
+    )
 
 
 class DedicatedResources(proto.Message):
@@ -397,6 +408,66 @@ class BatchDedicatedResources(proto.Message):
     )
 
 
+class FullFineTunedResources(proto.Message):
+    r"""Resources for an fft model.
+
+    Attributes:
+        deployment_type (google.cloud.aiplatform_v1beta1.types.FullFineTunedResources.DeploymentType):
+            Required. The kind of deployment.
+        model_inference_unit_count (int):
+            Optional. The number of model inference units to use for
+            this deployment. This can only be specified for
+            DEPLOYMENT_TYPE_PROD. The following table lists the number
+            of model inference units for different model types:
+
+            - Gemini 2.5 Flash
+
+              - Foundation FMIU: 25
+              - Expansion FMIU: 4
+
+            - Gemini 2.5 Pro
+
+              - Foundation FMIU: 32
+              - Expansion FMIU: 16
+
+            - Veo 3.0 (undistilled)
+
+              - Foundation FMIU: 63
+              - Expansion FMIU: 7
+
+            - Veo 3.0 (distilled)
+
+              - Foundation FMIU: 30
+              - Expansion FMIU: 10
+    """
+
+    class DeploymentType(proto.Enum):
+        r"""The type of deployment.
+
+        Values:
+            DEPLOYMENT_TYPE_UNSPECIFIED (0):
+                Unspecified deployment type.
+            DEPLOYMENT_TYPE_EVAL (1):
+                Eval deployment type.
+            DEPLOYMENT_TYPE_PROD (2):
+                Prod deployment type.
+        """
+
+        DEPLOYMENT_TYPE_UNSPECIFIED = 0
+        DEPLOYMENT_TYPE_EVAL = 1
+        DEPLOYMENT_TYPE_PROD = 2
+
+    deployment_type: DeploymentType = proto.Field(
+        proto.ENUM,
+        number=1,
+        enum=DeploymentType,
+    )
+    model_inference_unit_count: int = proto.Field(
+        proto.INT32,
+        number=2,
+    )
+
+
 class ResourcesConsumed(proto.Message):
     r"""Statistics information about resource consumption.