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a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/custom_job.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/custom_job.py new file mode 100644 index 0000000000000000000000000000000000000000..67200dc8cde78b504bdb1e1fe22b4026f0df0992 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/custom_job.py @@ -0,0 +1,644 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import encryption_spec as gca_encryption_spec +from google.cloud.aiplatform_v1beta1.types import env_var +from google.cloud.aiplatform_v1beta1.types import io +from google.cloud.aiplatform_v1beta1.types import job_state +from google.cloud.aiplatform_v1beta1.types import machine_resources +from google.cloud.aiplatform_v1beta1.types import service_networking +import google.protobuf.duration_pb2 as duration_pb2 # type: ignore +import google.protobuf.timestamp_pb2 as timestamp_pb2 # type: ignore +import google.rpc.status_pb2 as status_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "CustomJob", + "CustomJobSpec", + "WorkerPoolSpec", + "ContainerSpec", + "PythonPackageSpec", + "Scheduling", + }, +) + + +class CustomJob(proto.Message): + r"""Represents a job that runs custom workloads such as a Docker + container or a Python package. A CustomJob can have multiple + worker pools and each worker pool can have its own machine and + input spec. A CustomJob will be cleaned up once the job enters + terminal state (failed or succeeded). + + Attributes: + name (str): + Output only. Resource name of a CustomJob. + display_name (str): + Required. The display name of the CustomJob. + The name can be up to 128 characters long and + can consist of any UTF-8 characters. + job_spec (google.cloud.aiplatform_v1beta1.types.CustomJobSpec): + Required. Job spec. + state (google.cloud.aiplatform_v1beta1.types.JobState): + Output only. The detailed state of the job. + create_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Time when the CustomJob was + created. + start_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Time when the CustomJob for the first time + entered the ``JOB_STATE_RUNNING`` state. + end_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Time when the CustomJob entered any of the + following states: ``JOB_STATE_SUCCEEDED``, + ``JOB_STATE_FAILED``, ``JOB_STATE_CANCELLED``. + update_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Time when the CustomJob was most + recently updated. + error (google.rpc.status_pb2.Status): + Output only. Only populated when job's state is + ``JOB_STATE_FAILED`` or ``JOB_STATE_CANCELLED``. + labels (MutableMapping[str, str]): + The labels with user-defined metadata to + organize CustomJobs. + Label keys and values can be no longer than 64 + characters (Unicode codepoints), can only + contain lowercase letters, numeric characters, + underscores and dashes. International characters + are allowed. + + See https://goo.gl/xmQnxf for more information + and examples of labels. + encryption_spec (google.cloud.aiplatform_v1beta1.types.EncryptionSpec): + Customer-managed encryption key options for a + CustomJob. If this is set, then all resources + created by the CustomJob will be encrypted with + the provided encryption key. + web_access_uris (MutableMapping[str, str]): + Output only. URIs for accessing `interactive + shells `__ + (one URI for each training node). Only available if + [job_spec.enable_web_access][google.cloud.aiplatform.v1beta1.CustomJobSpec.enable_web_access] + is ``true``. + + The keys are names of each node in the training job; for + example, ``workerpool0-0`` for the primary node, + ``workerpool1-0`` for the first node in the second worker + pool, and ``workerpool1-1`` for the second node in the + second worker pool. + + The values are the URIs for each node's interactive shell. + satisfies_pzs (bool): + Output only. Reserved for future use. + satisfies_pzi (bool): + Output only. Reserved for future use. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + display_name: str = proto.Field( + proto.STRING, + number=2, + ) + job_spec: "CustomJobSpec" = proto.Field( + proto.MESSAGE, + number=4, + message="CustomJobSpec", + ) + state: job_state.JobState = proto.Field( + proto.ENUM, + number=5, + enum=job_state.JobState, + ) + create_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=6, + message=timestamp_pb2.Timestamp, + ) + start_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=7, + message=timestamp_pb2.Timestamp, + ) + end_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=8, + message=timestamp_pb2.Timestamp, + ) + update_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=9, + message=timestamp_pb2.Timestamp, + ) + error: status_pb2.Status = proto.Field( + proto.MESSAGE, + number=10, + message=status_pb2.Status, + ) + labels: MutableMapping[str, str] = proto.MapField( + proto.STRING, + proto.STRING, + number=11, + ) + encryption_spec: gca_encryption_spec.EncryptionSpec = proto.Field( + proto.MESSAGE, + number=12, + message=gca_encryption_spec.EncryptionSpec, + ) + web_access_uris: MutableMapping[str, str] = proto.MapField( + proto.STRING, + proto.STRING, + number=16, + ) + satisfies_pzs: bool = proto.Field( + proto.BOOL, + number=18, + ) + satisfies_pzi: bool = proto.Field( + proto.BOOL, + number=19, + ) + + +class CustomJobSpec(proto.Message): + r"""Represents the spec of a CustomJob. + + Attributes: + persistent_resource_id (str): + Optional. The ID of the PersistentResource in + the same Project and Location which to run + + If this is specified, the job will be run on + existing machines held by the PersistentResource + instead of on-demand short-live machines. The + network and CMEK configs on the job should be + consistent with those on the PersistentResource, + otherwise, the job will be rejected. + worker_pool_specs (MutableSequence[google.cloud.aiplatform_v1beta1.types.WorkerPoolSpec]): + Required. The spec of the worker pools + including machine type and Docker image. All + worker pools except the first one are optional + and can be skipped by providing an empty value. + scheduling (google.cloud.aiplatform_v1beta1.types.Scheduling): + Scheduling options for a CustomJob. + service_account (str): + Specifies the service account for workload run-as account. + Users submitting jobs must have act-as permission on this + run-as account. If unspecified, the `Vertex AI Custom Code + Service + Agent `__ + for the CustomJob's project is used. + network (str): + Optional. The full name of the Compute Engine + `network `__ + to which the Job should be peered. For example, + ``projects/12345/global/networks/myVPC``. + `Format `__ + is of the form + ``projects/{project}/global/networks/{network}``. Where + {project} is a project number, as in ``12345``, and + {network} is a network name. + + To specify this field, you must have already `configured VPC + Network Peering for Vertex + AI `__. + + If this field is left unspecified, the job is not peered + with any network. + reserved_ip_ranges (MutableSequence[str]): + Optional. A list of names for the reserved ip ranges under + the VPC network that can be used for this job. + + If set, we will deploy the job within the provided ip + ranges. Otherwise, the job will be deployed to any ip ranges + under the provided VPC network. + + Example: ['vertex-ai-ip-range']. + psc_interface_config (google.cloud.aiplatform_v1beta1.types.PscInterfaceConfig): + Optional. Configuration for PSC-I for + CustomJob. + base_output_directory (google.cloud.aiplatform_v1beta1.types.GcsDestination): + The Cloud Storage location to store the output of this + CustomJob or HyperparameterTuningJob. For + HyperparameterTuningJob, the baseOutputDirectory of each + child CustomJob backing a Trial is set to a subdirectory of + name [id][google.cloud.aiplatform.v1beta1.Trial.id] under + its parent HyperparameterTuningJob's baseOutputDirectory. + + The following Vertex AI environment variables will be passed + to containers or python modules when this field is set: + + For CustomJob: + + - AIP_MODEL_DIR = ``/model/`` + - AIP_CHECKPOINT_DIR = + ``/checkpoints/`` + - AIP_TENSORBOARD_LOG_DIR = + ``/logs/`` + + For CustomJob backing a Trial of HyperparameterTuningJob: + + - AIP_MODEL_DIR = + ``//model/`` + - AIP_CHECKPOINT_DIR = + ``//checkpoints/`` + - AIP_TENSORBOARD_LOG_DIR = + ``//logs/`` + protected_artifact_location_id (str): + The ID of the location to store protected + artifacts. e.g. us-central1. Populate only when + the location is different than CustomJob + location. List of supported locations: + + https://cloud.google.com/vertex-ai/docs/general/locations + tensorboard (str): + Optional. The name of a Vertex AI + [Tensorboard][google.cloud.aiplatform.v1beta1.Tensorboard] + resource to which this CustomJob will upload Tensorboard + logs. Format: + ``projects/{project}/locations/{location}/tensorboards/{tensorboard}`` + enable_web_access (bool): + Optional. Whether you want Vertex AI to enable `interactive + shell + access `__ + to training containers. + + If set to ``true``, you can access interactive shells at the + URIs given by + [CustomJob.web_access_uris][google.cloud.aiplatform.v1beta1.CustomJob.web_access_uris] + or + [Trial.web_access_uris][google.cloud.aiplatform.v1beta1.Trial.web_access_uris] + (within + [HyperparameterTuningJob.trials][google.cloud.aiplatform.v1beta1.HyperparameterTuningJob.trials]). + enable_dashboard_access (bool): + Optional. Whether you want Vertex AI to enable access to the + customized dashboard in training chief container. + + If set to ``true``, you can access the dashboard at the URIs + given by + [CustomJob.web_access_uris][google.cloud.aiplatform.v1beta1.CustomJob.web_access_uris] + or + [Trial.web_access_uris][google.cloud.aiplatform.v1beta1.Trial.web_access_uris] + (within + [HyperparameterTuningJob.trials][google.cloud.aiplatform.v1beta1.HyperparameterTuningJob.trials]). + experiment (str): + Optional. The Experiment associated with this job. Format: + ``projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}`` + experiment_run (str): + Optional. The Experiment Run associated with this job. + Format: + ``projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}`` + models (MutableSequence[str]): + Optional. The name of the Model resources for which to + generate a mapping to artifact URIs. Applicable only to some + of the Google-provided custom jobs. Format: + ``projects/{project}/locations/{location}/models/{model}`` + + In order to retrieve a specific version of the model, also + provide the version ID or version alias. Example: + ``projects/{project}/locations/{location}/models/{model}@2`` + or + ``projects/{project}/locations/{location}/models/{model}@golden`` + If no version ID or alias is specified, the "default" + version will be returned. The "default" version alias is + created for the first version of the model, and can be moved + to other versions later on. There will be exactly one + default version. + """ + + persistent_resource_id: str = proto.Field( + proto.STRING, + number=14, + ) + worker_pool_specs: MutableSequence["WorkerPoolSpec"] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message="WorkerPoolSpec", + ) + scheduling: "Scheduling" = proto.Field( + proto.MESSAGE, + number=3, + message="Scheduling", + ) + service_account: str = proto.Field( + proto.STRING, + number=4, + ) + network: str = proto.Field( + proto.STRING, + number=5, + ) + reserved_ip_ranges: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=13, + ) + psc_interface_config: service_networking.PscInterfaceConfig = proto.Field( + proto.MESSAGE, + number=21, + message=service_networking.PscInterfaceConfig, + ) + base_output_directory: io.GcsDestination = proto.Field( + proto.MESSAGE, + number=6, + message=io.GcsDestination, + ) + protected_artifact_location_id: str = proto.Field( + proto.STRING, + number=19, + ) + tensorboard: str = proto.Field( + proto.STRING, + number=7, + ) + enable_web_access: bool = proto.Field( + proto.BOOL, + number=10, + ) + enable_dashboard_access: bool = proto.Field( + proto.BOOL, + number=16, + ) + experiment: str = proto.Field( + proto.STRING, + number=17, + ) + experiment_run: str = proto.Field( + proto.STRING, + number=18, + ) + models: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=20, + ) + + +class WorkerPoolSpec(proto.Message): + r"""Represents the spec of a worker pool in a job. + + This message has `oneof`_ fields (mutually exclusive fields). + For each oneof, at most one member field can be set at the same time. + Setting any member of the oneof automatically clears all other + members. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + container_spec (google.cloud.aiplatform_v1beta1.types.ContainerSpec): + The custom container task. + + This field is a member of `oneof`_ ``task``. + python_package_spec (google.cloud.aiplatform_v1beta1.types.PythonPackageSpec): + The Python packaged task. + + This field is a member of `oneof`_ ``task``. + machine_spec (google.cloud.aiplatform_v1beta1.types.MachineSpec): + Optional. Immutable. The specification of a + single machine. + replica_count (int): + Optional. The number of worker replicas to + use for this worker pool. + nfs_mounts (MutableSequence[google.cloud.aiplatform_v1beta1.types.NfsMount]): + Optional. List of NFS mount spec. + lustre_mounts (MutableSequence[google.cloud.aiplatform_v1beta1.types.LustreMount]): + Optional. List of Lustre mounts. + disk_spec (google.cloud.aiplatform_v1beta1.types.DiskSpec): + Disk spec. + """ + + container_spec: "ContainerSpec" = proto.Field( + proto.MESSAGE, + number=6, + oneof="task", + message="ContainerSpec", + ) + python_package_spec: "PythonPackageSpec" = proto.Field( + proto.MESSAGE, + number=7, + oneof="task", + message="PythonPackageSpec", + ) + machine_spec: machine_resources.MachineSpec = proto.Field( + proto.MESSAGE, + number=1, + message=machine_resources.MachineSpec, + ) + replica_count: int = proto.Field( + proto.INT64, + number=2, + ) + nfs_mounts: MutableSequence[machine_resources.NfsMount] = proto.RepeatedField( + proto.MESSAGE, + number=4, + message=machine_resources.NfsMount, + ) + lustre_mounts: MutableSequence[machine_resources.LustreMount] = proto.RepeatedField( + proto.MESSAGE, + number=9, + message=machine_resources.LustreMount, + ) + disk_spec: machine_resources.DiskSpec = proto.Field( + proto.MESSAGE, + number=5, + message=machine_resources.DiskSpec, + ) + + +class ContainerSpec(proto.Message): + r"""The spec of a Container. + + Attributes: + image_uri (str): + Required. The URI of a container image in the + Container Registry that is to be run on each + worker replica. + command (MutableSequence[str]): + The command to be invoked when the container + is started. It overrides the entrypoint + instruction in Dockerfile when provided. + args (MutableSequence[str]): + The arguments to be passed when starting the + container. + env (MutableSequence[google.cloud.aiplatform_v1beta1.types.EnvVar]): + Environment variables to be passed to the + container. Maximum limit is 100. + """ + + image_uri: str = proto.Field( + proto.STRING, + number=1, + ) + command: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=2, + ) + args: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=3, + ) + env: MutableSequence[env_var.EnvVar] = proto.RepeatedField( + proto.MESSAGE, + number=4, + message=env_var.EnvVar, + ) + + +class PythonPackageSpec(proto.Message): + r"""The spec of a Python packaged code. + + Attributes: + executor_image_uri (str): + Required. The URI of a container image in Artifact Registry + that will run the provided Python package. Vertex AI + provides a wide range of executor images with pre-installed + packages to meet users' various use cases. See the list of + `pre-built containers for + training `__. + You must use an image from this list. + package_uris (MutableSequence[str]): + Required. The Google Cloud Storage location + of the Python package files which are the + training program and its dependent packages. The + maximum number of package URIs is 100. + python_module (str): + Required. The Python module name to run after + installing the packages. + args (MutableSequence[str]): + Command line arguments to be passed to the + Python task. + env (MutableSequence[google.cloud.aiplatform_v1beta1.types.EnvVar]): + Environment variables to be passed to the + python module. Maximum limit is 100. + """ + + executor_image_uri: str = proto.Field( + proto.STRING, + number=1, + ) + package_uris: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=2, + ) + python_module: str = proto.Field( + proto.STRING, + number=3, + ) + args: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=4, + ) + env: MutableSequence[env_var.EnvVar] = proto.RepeatedField( + proto.MESSAGE, + number=5, + message=env_var.EnvVar, + ) + + +class Scheduling(proto.Message): + r"""All parameters related to queuing and scheduling of custom + jobs. + + Attributes: + timeout (google.protobuf.duration_pb2.Duration): + Optional. The maximum job running time. The + default is 7 days. + restart_job_on_worker_restart (bool): + Optional. Restarts the entire CustomJob if a + worker gets restarted. This feature can be used + by distributed training jobs that are not + resilient to workers leaving and joining a job. + strategy (google.cloud.aiplatform_v1beta1.types.Scheduling.Strategy): + Optional. This determines which type of + scheduling strategy to use. + disable_retries (bool): + Optional. Indicates if the job should retry for internal + errors after the job starts running. If true, overrides + ``Scheduling.restart_job_on_worker_restart`` to false. + max_wait_duration (google.protobuf.duration_pb2.Duration): + Optional. This is the maximum duration that a job will wait + for the requested resources to be provisioned if the + scheduling strategy is set to [Strategy.DWS_FLEX_START]. If + set to 0, the job will wait indefinitely. The default is 24 + hours. + """ + + class Strategy(proto.Enum): + r"""Optional. This determines which type of scheduling strategy + to use. Right now users have two options such as STANDARD which + will use regular on demand resources to schedule the job, the + other is SPOT which would leverage spot resources alongwith + regular resources to schedule the job. + + Values: + STRATEGY_UNSPECIFIED (0): + Strategy will default to STANDARD. + ON_DEMAND (1): + Deprecated. Regular on-demand provisioning + strategy. + LOW_COST (2): + Deprecated. Low cost by making potential use + of spot resources. + STANDARD (3): + Standard provisioning strategy uses regular + on-demand resources. + SPOT (4): + Spot provisioning strategy uses spot + resources. + FLEX_START (6): + Flex Start strategy uses DWS to queue for + resources. + """ + + STRATEGY_UNSPECIFIED = 0 + ON_DEMAND = 1 + LOW_COST = 2 + STANDARD = 3 + SPOT = 4 + FLEX_START = 6 + + timeout: duration_pb2.Duration = proto.Field( + proto.MESSAGE, + number=1, + message=duration_pb2.Duration, + ) + restart_job_on_worker_restart: bool = proto.Field( + proto.BOOL, + number=3, + ) + strategy: Strategy = proto.Field( + proto.ENUM, + number=4, + enum=Strategy, + ) + disable_retries: bool = proto.Field( + proto.BOOL, + number=5, + ) + max_wait_duration: duration_pb2.Duration = proto.Field( + proto.MESSAGE, + number=6, + message=duration_pb2.Duration, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/deployment_resource_pool_service.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/deployment_resource_pool_service.py new file mode 100644 index 0000000000000000000000000000000000000000..64bcc8c576ddbd515e138d0146578f8a414b1af2 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/deployment_resource_pool_service.py @@ -0,0 +1,330 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import deployed_model_ref +from google.cloud.aiplatform_v1beta1.types import ( + deployment_resource_pool as gca_deployment_resource_pool, +) +from google.cloud.aiplatform_v1beta1.types import endpoint +from google.cloud.aiplatform_v1beta1.types import operation +import google.protobuf.field_mask_pb2 as field_mask_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "CreateDeploymentResourcePoolRequest", + "CreateDeploymentResourcePoolOperationMetadata", + "GetDeploymentResourcePoolRequest", + "ListDeploymentResourcePoolsRequest", + "ListDeploymentResourcePoolsResponse", + "UpdateDeploymentResourcePoolRequest", + "UpdateDeploymentResourcePoolOperationMetadata", + "DeleteDeploymentResourcePoolRequest", + "QueryDeployedModelsRequest", + "QueryDeployedModelsResponse", + }, +) + + +class CreateDeploymentResourcePoolRequest(proto.Message): + r"""Request message for CreateDeploymentResourcePool method. + + Attributes: + parent (str): + Required. The parent location resource where this + DeploymentResourcePool will be created. Format: + ``projects/{project}/locations/{location}`` + deployment_resource_pool (google.cloud.aiplatform_v1beta1.types.DeploymentResourcePool): + Required. The DeploymentResourcePool to + create. + deployment_resource_pool_id (str): + Required. The ID to use for the DeploymentResourcePool, + which will become the final component of the + DeploymentResourcePool's resource name. + + The maximum length is 63 characters, and valid characters + are ``/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/``. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + deployment_resource_pool: gca_deployment_resource_pool.DeploymentResourcePool = ( + proto.Field( + proto.MESSAGE, + number=2, + message=gca_deployment_resource_pool.DeploymentResourcePool, + ) + ) + deployment_resource_pool_id: str = proto.Field( + proto.STRING, + number=3, + ) + + +class CreateDeploymentResourcePoolOperationMetadata(proto.Message): + r"""Runtime operation information for + CreateDeploymentResourcePool method. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + The operation generic information. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class GetDeploymentResourcePoolRequest(proto.Message): + r"""Request message for GetDeploymentResourcePool method. + + Attributes: + name (str): + Required. The name of the DeploymentResourcePool to + retrieve. Format: + ``projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`` + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class ListDeploymentResourcePoolsRequest(proto.Message): + r"""Request message for ListDeploymentResourcePools method. + + Attributes: + parent (str): + Required. The parent Location which owns this collection of + DeploymentResourcePools. Format: + ``projects/{project}/locations/{location}`` + page_size (int): + The maximum number of DeploymentResourcePools + to return. The service may return fewer than + this value. + page_token (str): + A page token, received from a previous + ``ListDeploymentResourcePools`` call. Provide this to + retrieve the subsequent page. + + When paginating, all other parameters provided to + ``ListDeploymentResourcePools`` must match the call that + provided the page token. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + page_size: int = proto.Field( + proto.INT32, + number=2, + ) + page_token: str = proto.Field( + proto.STRING, + number=3, + ) + + +class ListDeploymentResourcePoolsResponse(proto.Message): + r"""Response message for ListDeploymentResourcePools method. + + Attributes: + deployment_resource_pools (MutableSequence[google.cloud.aiplatform_v1beta1.types.DeploymentResourcePool]): + The DeploymentResourcePools from the + specified location. + next_page_token (str): + A token, which can be sent as ``page_token`` to retrieve the + next page. If this field is omitted, there are no subsequent + pages. + """ + + @property + def raw_page(self): + return self + + deployment_resource_pools: MutableSequence[ + gca_deployment_resource_pool.DeploymentResourcePool + ] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=gca_deployment_resource_pool.DeploymentResourcePool, + ) + next_page_token: str = proto.Field( + proto.STRING, + number=2, + ) + + +class UpdateDeploymentResourcePoolRequest(proto.Message): + r"""Request message for UpdateDeploymentResourcePool method. + + Attributes: + deployment_resource_pool (google.cloud.aiplatform_v1beta1.types.DeploymentResourcePool): + Required. The DeploymentResourcePool to update. + + The DeploymentResourcePool's ``name`` field is used to + identify the DeploymentResourcePool to update. Format: + ``projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`` + update_mask (google.protobuf.field_mask_pb2.FieldMask): + Required. The list of fields to update. + """ + + deployment_resource_pool: gca_deployment_resource_pool.DeploymentResourcePool = ( + proto.Field( + proto.MESSAGE, + number=1, + message=gca_deployment_resource_pool.DeploymentResourcePool, + ) + ) + update_mask: field_mask_pb2.FieldMask = proto.Field( + proto.MESSAGE, + number=2, + message=field_mask_pb2.FieldMask, + ) + + +class UpdateDeploymentResourcePoolOperationMetadata(proto.Message): + r"""Runtime operation information for + UpdateDeploymentResourcePool method. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + The operation generic information. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class DeleteDeploymentResourcePoolRequest(proto.Message): + r"""Request message for DeleteDeploymentResourcePool method. + + Attributes: + name (str): + Required. The name of the DeploymentResourcePool to delete. + Format: + ``projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`` + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class QueryDeployedModelsRequest(proto.Message): + r"""Request message for QueryDeployedModels method. + + Attributes: + deployment_resource_pool (str): + Required. The name of the target DeploymentResourcePool to + query. Format: + ``projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`` + page_size (int): + The maximum number of DeployedModels to + return. The service may return fewer than this + value. + page_token (str): + A page token, received from a previous + ``QueryDeployedModels`` call. Provide this to retrieve the + subsequent page. + + When paginating, all other parameters provided to + ``QueryDeployedModels`` must match the call that provided + the page token. + """ + + deployment_resource_pool: str = proto.Field( + proto.STRING, + number=1, + ) + page_size: int = proto.Field( + proto.INT32, + number=2, + ) + page_token: str = proto.Field( + proto.STRING, + number=3, + ) + + +class QueryDeployedModelsResponse(proto.Message): + r"""Response message for QueryDeployedModels method. + + Attributes: + deployed_models (MutableSequence[google.cloud.aiplatform_v1beta1.types.DeployedModel]): + DEPRECATED Use deployed_model_refs instead. + next_page_token (str): + A token, which can be sent as ``page_token`` to retrieve the + next page. If this field is omitted, there are no subsequent + pages. + deployed_model_refs (MutableSequence[google.cloud.aiplatform_v1beta1.types.DeployedModelRef]): + References to the DeployedModels that share + the specified deploymentResourcePool. + total_deployed_model_count (int): + The total number of DeployedModels on this + DeploymentResourcePool. + total_endpoint_count (int): + The total number of Endpoints that have + DeployedModels on this DeploymentResourcePool. + """ + + @property + def raw_page(self): + return self + + deployed_models: MutableSequence[endpoint.DeployedModel] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=endpoint.DeployedModel, + ) + next_page_token: str = proto.Field( + proto.STRING, + number=2, + ) + deployed_model_refs: MutableSequence[deployed_model_ref.DeployedModelRef] = ( + proto.RepeatedField( + proto.MESSAGE, + number=3, + message=deployed_model_ref.DeployedModelRef, + ) + ) + total_deployed_model_count: int = proto.Field( + proto.INT32, + number=4, + ) + total_endpoint_count: int = proto.Field( + proto.INT32, + number=5, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/env_var.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/env_var.py new file mode 100644 index 0000000000000000000000000000000000000000..d42ad216bdb3df89a3eae6091757e6d4b8e243fb --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/env_var.py @@ -0,0 +1,112 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "EnvVar", + "SecretRef", + "SecretEnvVar", + }, +) + + +class EnvVar(proto.Message): + r"""Represents an environment variable present in a Container or + Python Module. + + Attributes: + name (str): + Required. Name of the environment variable. + Must be a valid C identifier. + value (str): + Required. Variables that reference a $(VAR_NAME) are + expanded using the previous defined environment variables in + the container and any service environment variables. If a + variable cannot be resolved, the reference in the input + string will be unchanged. The $(VAR_NAME) syntax can be + escaped with a double $$, ie: $$(VAR_NAME). Escaped + references will never be expanded, regardless of whether the + variable exists or not. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + value: str = proto.Field( + proto.STRING, + number=2, + ) + + +class SecretRef(proto.Message): + r"""Reference to a secret stored in the Cloud Secret Manager that + will provide the value for this environment variable. + + Attributes: + secret (str): + Required. The name of the secret in Cloud Secret Manager. + Format: {secret_name}. + version (str): + The Cloud Secret Manager secret version. + Can be 'latest' for the latest version, an + integer for a specific version, or a version + alias. + """ + + secret: str = proto.Field( + proto.STRING, + number=1, + ) + version: str = proto.Field( + proto.STRING, + number=2, + ) + + +class SecretEnvVar(proto.Message): + r"""Represents an environment variable where the value is a + secret in Cloud Secret Manager. + + Attributes: + name (str): + Required. Name of the secret environment + variable. + secret_ref (google.cloud.aiplatform_v1beta1.types.SecretRef): + Required. Reference to a secret stored in the + Cloud Secret Manager that will provide the value + for this environment variable. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + secret_ref: "SecretRef" = proto.Field( + proto.MESSAGE, + number=2, + message="SecretRef", + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/execution.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/execution.py new file mode 100644 index 0000000000000000000000000000000000000000..4184b21bbca9ee135829610e07583c41b629e027 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/execution.py @@ -0,0 +1,174 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +import google.protobuf.struct_pb2 as struct_pb2 # type: ignore +import google.protobuf.timestamp_pb2 as timestamp_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "Execution", + }, +) + + +class Execution(proto.Message): + r"""Instance of a general execution. + + Attributes: + name (str): + Output only. The resource name of the + Execution. + display_name (str): + User provided display name of the Execution. + May be up to 128 Unicode characters. + state (google.cloud.aiplatform_v1beta1.types.Execution.State): + The state of this Execution. This is a + property of the Execution, and does not imply or + capture any ongoing process. This property is + managed by clients (such as Vertex AI Pipelines) + and the system does not prescribe or check the + validity of state transitions. + etag (str): + An eTag used to perform consistent + read-modify-write updates. If not set, a blind + "overwrite" update happens. + labels (MutableMapping[str, str]): + The labels with user-defined metadata to + organize your Executions. + Label keys and values can be no longer than 64 + characters (Unicode codepoints), can only + contain lowercase letters, numeric characters, + underscores and dashes. International characters + are allowed. No more than 64 user labels can be + associated with one Execution (System labels are + excluded). + create_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when this Execution + was created. + update_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when this Execution + was last updated. + schema_title (str): + The title of the schema describing the + metadata. + Schema title and version is expected to be + registered in earlier Create Schema calls. And + both are used together as unique identifiers to + identify schemas within the local metadata + store. + schema_version (str): + The version of the schema in ``schema_title`` to use. + + Schema title and version is expected to be registered in + earlier Create Schema calls. And both are used together as + unique identifiers to identify schemas within the local + metadata store. + metadata (google.protobuf.struct_pb2.Struct): + Properties of the Execution. + Top level metadata keys' heading and trailing + spaces will be trimmed. The size of this field + should not exceed 200KB. + description (str): + Description of the Execution + """ + + class State(proto.Enum): + r"""Describes the state of the Execution. + + Values: + STATE_UNSPECIFIED (0): + Unspecified Execution state + NEW (1): + The Execution is new + RUNNING (2): + The Execution is running + COMPLETE (3): + The Execution has finished running + FAILED (4): + The Execution has failed + CACHED (5): + The Execution completed through Cache hit. + CANCELLED (6): + The Execution was cancelled. + """ + + STATE_UNSPECIFIED = 0 + NEW = 1 + RUNNING = 2 + COMPLETE = 3 + FAILED = 4 + CACHED = 5 + CANCELLED = 6 + + name: str = proto.Field( + proto.STRING, + number=1, + ) + display_name: str = proto.Field( + proto.STRING, + number=2, + ) + state: State = proto.Field( + proto.ENUM, + number=6, + enum=State, + ) + etag: str = proto.Field( + proto.STRING, + number=9, + ) + labels: MutableMapping[str, str] = proto.MapField( + proto.STRING, + proto.STRING, + number=10, + ) + create_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=11, + message=timestamp_pb2.Timestamp, + ) + update_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=12, + message=timestamp_pb2.Timestamp, + ) + schema_title: str = proto.Field( + proto.STRING, + number=13, + ) + schema_version: str = proto.Field( + proto.STRING, + number=14, + ) + metadata: struct_pb2.Struct = proto.Field( + proto.MESSAGE, + number=15, + message=struct_pb2.Struct, + ) + description: str = proto.Field( + proto.STRING, + number=16, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/explanation.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/explanation.py new file mode 100644 index 0000000000000000000000000000000000000000..b95b6c0edb405e4390839d48d7165cd9071fc20b --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/explanation.py @@ -0,0 +1,1068 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import explanation_metadata +from google.cloud.aiplatform_v1beta1.types import io +import google.protobuf.struct_pb2 as struct_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "Explanation", + "ModelExplanation", + "Attribution", + "Neighbor", + "ExplanationSpec", + "ExplanationParameters", + "SampledShapleyAttribution", + "IntegratedGradientsAttribution", + "XraiAttribution", + "SmoothGradConfig", + "FeatureNoiseSigma", + "BlurBaselineConfig", + "Examples", + "Presets", + "ExplanationSpecOverride", + "ExplanationMetadataOverride", + "ExamplesOverride", + "ExamplesRestrictionsNamespace", + }, +) + + +class Explanation(proto.Message): + r"""Explanation of a prediction (provided in + [PredictResponse.predictions][google.cloud.aiplatform.v1beta1.PredictResponse.predictions]) + produced by the Model on a given + [instance][google.cloud.aiplatform.v1beta1.ExplainRequest.instances]. + + Attributes: + attributions (MutableSequence[google.cloud.aiplatform_v1beta1.types.Attribution]): + Output only. Feature attributions grouped by predicted + outputs. + + For Models that predict only one output, such as regression + Models that predict only one score, there is only one + attibution that explains the predicted output. For Models + that predict multiple outputs, such as multiclass Models + that predict multiple classes, each element explains one + specific item. + [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] + can be used to identify which output this attribution is + explaining. + + By default, we provide Shapley values for the predicted + class. However, you can configure the explanation request to + generate Shapley values for any other classes too. For + example, if a model predicts a probability of ``0.4`` for + approving a loan application, the model's decision is to + reject the application since + ``p(reject) = 0.6 > p(approve) = 0.4``, and the default + Shapley values would be computed for rejection decision and + not approval, even though the latter might be the positive + class. + + If users set + [ExplanationParameters.top_k][google.cloud.aiplatform.v1beta1.ExplanationParameters.top_k], + the attributions are sorted by + [instance_output_value][Attributions.instance_output_value] + in descending order. If + [ExplanationParameters.output_indices][google.cloud.aiplatform.v1beta1.ExplanationParameters.output_indices] + is specified, the attributions are stored by + [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] + in the same order as they appear in the output_indices. + neighbors (MutableSequence[google.cloud.aiplatform_v1beta1.types.Neighbor]): + Output only. List of the nearest neighbors + for example-based explanations. + For models deployed with the examples + explanations feature enabled, the attributions + field is empty and instead the neighbors field + is populated. + """ + + attributions: MutableSequence["Attribution"] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message="Attribution", + ) + neighbors: MutableSequence["Neighbor"] = proto.RepeatedField( + proto.MESSAGE, + number=2, + message="Neighbor", + ) + + +class ModelExplanation(proto.Message): + r"""Aggregated explanation metrics for a Model over a set of + instances. + + Attributes: + mean_attributions (MutableSequence[google.cloud.aiplatform_v1beta1.types.Attribution]): + Output only. Aggregated attributions explaining the Model's + prediction outputs over the set of instances. The + attributions are grouped by outputs. + + For Models that predict only one output, such as regression + Models that predict only one score, there is only one + attibution that explains the predicted output. For Models + that predict multiple outputs, such as multiclass Models + that predict multiple classes, each element explains one + specific item. + [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] + can be used to identify which output this attribution is + explaining. + + The + [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], + [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] + and + [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] + fields are averaged over the test data. + + NOTE: Currently AutoML tabular classification Models produce + only one attribution, which averages attributions over all + the classes it predicts. + [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] + is not populated. + """ + + mean_attributions: MutableSequence["Attribution"] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message="Attribution", + ) + + +class Attribution(proto.Message): + r"""Attribution that explains a particular prediction output. + + Attributes: + baseline_output_value (float): + Output only. Model predicted output if the input instance is + constructed from the baselines of all the features defined + in + [ExplanationMetadata.inputs][google.cloud.aiplatform.v1beta1.ExplanationMetadata.inputs]. + The field name of the output is determined by the key in + [ExplanationMetadata.outputs][google.cloud.aiplatform.v1beta1.ExplanationMetadata.outputs]. + + If the Model's predicted output has multiple dimensions + (rank > 1), this is the value in the output located by + [output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index]. + + If there are multiple baselines, their output values are + averaged. + instance_output_value (float): + Output only. Model predicted output on the corresponding + [explanation instance][ExplainRequest.instances]. The field + name of the output is determined by the key in + [ExplanationMetadata.outputs][google.cloud.aiplatform.v1beta1.ExplanationMetadata.outputs]. + + If the Model predicted output has multiple dimensions, this + is the value in the output located by + [output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index]. + feature_attributions (google.protobuf.struct_pb2.Value): + Output only. Attributions of each explained feature. + Features are extracted from the [prediction + instances][google.cloud.aiplatform.v1beta1.ExplainRequest.instances] + according to [explanation metadata for + inputs][google.cloud.aiplatform.v1beta1.ExplanationMetadata.inputs]. + + The value is a struct, whose keys are the name of the + feature. The values are how much the feature in the + [instance][google.cloud.aiplatform.v1beta1.ExplainRequest.instances] + contributed to the predicted result. + + The format of the value is determined by the feature's input + format: + + - If the feature is a scalar value, the attribution value is + a [floating number][google.protobuf.Value.number_value]. + + - If the feature is an array of scalar values, the + attribution value is an + [array][google.protobuf.Value.list_value]. + + - If the feature is a struct, the attribution value is a + [struct][google.protobuf.Value.struct_value]. The keys in + the attribution value struct are the same as the keys in + the feature struct. The formats of the values in the + attribution struct are determined by the formats of the + values in the feature struct. + + The + [ExplanationMetadata.feature_attributions_schema_uri][google.cloud.aiplatform.v1beta1.ExplanationMetadata.feature_attributions_schema_uri] + field, pointed to by the + [ExplanationSpec][google.cloud.aiplatform.v1beta1.ExplanationSpec] + field of the + [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models] + object, points to the schema file that describes the + features and their attribution values (if it is populated). + output_index (MutableSequence[int]): + Output only. The index that locates the explained prediction + output. + + If the prediction output is a scalar value, output_index is + not populated. If the prediction output has multiple + dimensions, the length of the output_index list is the same + as the number of dimensions of the output. The i-th element + in output_index is the element index of the i-th dimension + of the output vector. Indices start from 0. + output_display_name (str): + Output only. The display name of the output identified by + [output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index]. + For example, the predicted class name by a + multi-classification Model. + + This field is only populated iff the Model predicts display + names as a separate field along with the explained output. + The predicted display name must has the same shape of the + explained output, and can be located using output_index. + approximation_error (float): + Output only. Error of + [feature_attributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] + caused by approximation used in the explanation method. + Lower value means more precise attributions. + + - For Sampled Shapley + [attribution][google.cloud.aiplatform.v1beta1.ExplanationParameters.sampled_shapley_attribution], + increasing + [path_count][google.cloud.aiplatform.v1beta1.SampledShapleyAttribution.path_count] + might reduce the error. + - For Integrated Gradients + [attribution][google.cloud.aiplatform.v1beta1.ExplanationParameters.integrated_gradients_attribution], + increasing + [step_count][google.cloud.aiplatform.v1beta1.IntegratedGradientsAttribution.step_count] + might reduce the error. + - For [XRAI + attribution][google.cloud.aiplatform.v1beta1.ExplanationParameters.xrai_attribution], + increasing + [step_count][google.cloud.aiplatform.v1beta1.XraiAttribution.step_count] + might reduce the error. + + See `this + introduction `__ + for more information. + output_name (str): + Output only. Name of the explain output. Specified as the + key in + [ExplanationMetadata.outputs][google.cloud.aiplatform.v1beta1.ExplanationMetadata.outputs]. + """ + + baseline_output_value: float = proto.Field( + proto.DOUBLE, + number=1, + ) + instance_output_value: float = proto.Field( + proto.DOUBLE, + number=2, + ) + feature_attributions: struct_pb2.Value = proto.Field( + proto.MESSAGE, + number=3, + message=struct_pb2.Value, + ) + output_index: MutableSequence[int] = proto.RepeatedField( + proto.INT32, + number=4, + ) + output_display_name: str = proto.Field( + proto.STRING, + number=5, + ) + approximation_error: float = proto.Field( + proto.DOUBLE, + number=6, + ) + output_name: str = proto.Field( + proto.STRING, + number=7, + ) + + +class Neighbor(proto.Message): + r"""Neighbors for example-based explanations. + + Attributes: + neighbor_id (str): + Output only. The neighbor id. + neighbor_distance (float): + Output only. The neighbor distance. + """ + + neighbor_id: str = proto.Field( + proto.STRING, + number=1, + ) + neighbor_distance: float = proto.Field( + proto.DOUBLE, + number=2, + ) + + +class ExplanationSpec(proto.Message): + r"""Specification of Model explanation. + + Attributes: + parameters (google.cloud.aiplatform_v1beta1.types.ExplanationParameters): + Required. Parameters that configure + explaining of the Model's predictions. + metadata (google.cloud.aiplatform_v1beta1.types.ExplanationMetadata): + Optional. Metadata describing the Model's + input and output for explanation. + """ + + parameters: "ExplanationParameters" = proto.Field( + proto.MESSAGE, + number=1, + message="ExplanationParameters", + ) + metadata: explanation_metadata.ExplanationMetadata = proto.Field( + proto.MESSAGE, + number=2, + message=explanation_metadata.ExplanationMetadata, + ) + + +class ExplanationParameters(proto.Message): + r"""Parameters to configure explaining for Model's predictions. + + This message has `oneof`_ fields (mutually exclusive fields). + For each oneof, at most one member field can be set at the same time. + Setting any member of the oneof automatically clears all other + members. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + sampled_shapley_attribution (google.cloud.aiplatform_v1beta1.types.SampledShapleyAttribution): + An attribution method that approximates + Shapley values for features that contribute to + the label being predicted. A sampling strategy + is used to approximate the value rather than + considering all subsets of features. Refer to + this paper for model details: + https://arxiv.org/abs/1306.4265. + + This field is a member of `oneof`_ ``method``. + integrated_gradients_attribution (google.cloud.aiplatform_v1beta1.types.IntegratedGradientsAttribution): + An attribution method that computes + Aumann-Shapley values taking advantage of the + model's fully differentiable structure. Refer to + this paper for more details: + https://arxiv.org/abs/1703.01365 + + This field is a member of `oneof`_ ``method``. + xrai_attribution (google.cloud.aiplatform_v1beta1.types.XraiAttribution): + An attribution method that redistributes + Integrated Gradients attribution to segmented + regions, taking advantage of the model's fully + differentiable structure. Refer to this paper + for more details: + https://arxiv.org/abs/1906.02825 + + XRAI currently performs better on natural + images, like a picture of a house or an animal. + If the images are taken in artificial + environments, like a lab or manufacturing line, + or from diagnostic equipment, like x-rays or + quality-control cameras, use Integrated + Gradients instead. + + This field is a member of `oneof`_ ``method``. + examples (google.cloud.aiplatform_v1beta1.types.Examples): + Example-based explanations that returns the + nearest neighbors from the provided dataset. + + This field is a member of `oneof`_ ``method``. + top_k (int): + If populated, returns attributions for top K + indices of outputs (defaults to 1). Only applies + to Models that predicts more than one outputs + (e,g, multi-class Models). When set to -1, + returns explanations for all outputs. + output_indices (google.protobuf.struct_pb2.ListValue): + If populated, only returns attributions that have + [output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] + contained in output_indices. It must be an ndarray of + integers, with the same shape of the output it's explaining. + + If not populated, returns attributions for + [top_k][google.cloud.aiplatform.v1beta1.ExplanationParameters.top_k] + indices of outputs. If neither top_k nor output_indices is + populated, returns the argmax index of the outputs. + + Only applicable to Models that predict multiple outputs + (e,g, multi-class Models that predict multiple classes). + """ + + sampled_shapley_attribution: "SampledShapleyAttribution" = proto.Field( + proto.MESSAGE, + number=1, + oneof="method", + message="SampledShapleyAttribution", + ) + integrated_gradients_attribution: "IntegratedGradientsAttribution" = proto.Field( + proto.MESSAGE, + number=2, + oneof="method", + message="IntegratedGradientsAttribution", + ) + xrai_attribution: "XraiAttribution" = proto.Field( + proto.MESSAGE, + number=3, + oneof="method", + message="XraiAttribution", + ) + examples: "Examples" = proto.Field( + proto.MESSAGE, + number=7, + oneof="method", + message="Examples", + ) + top_k: int = proto.Field( + proto.INT32, + number=4, + ) + output_indices: struct_pb2.ListValue = proto.Field( + proto.MESSAGE, + number=5, + message=struct_pb2.ListValue, + ) + + +class SampledShapleyAttribution(proto.Message): + r"""An attribution method that approximates Shapley values for + features that contribute to the label being predicted. A + sampling strategy is used to approximate the value rather than + considering all subsets of features. + + Attributes: + path_count (int): + Required. The number of feature permutations to consider + when approximating the Shapley values. + + Valid range of its value is [1, 50], inclusively. + """ + + path_count: int = proto.Field( + proto.INT32, + number=1, + ) + + +class IntegratedGradientsAttribution(proto.Message): + r"""An attribution method that computes the Aumann-Shapley value + taking advantage of the model's fully differentiable structure. + Refer to this paper for more details: + https://arxiv.org/abs/1703.01365 + + Attributes: + step_count (int): + Required. The number of steps for approximating the path + integral. A good value to start is 50 and gradually increase + until the sum to diff property is within the desired error + range. + + Valid range of its value is [1, 100], inclusively. + smooth_grad_config (google.cloud.aiplatform_v1beta1.types.SmoothGradConfig): + Config for SmoothGrad approximation of + gradients. + When enabled, the gradients are approximated by + averaging the gradients from noisy samples in + the vicinity of the inputs. Adding noise can + help improve the computed gradients. Refer to + this paper for more details: + https://arxiv.org/pdf/1706.03825.pdf + blur_baseline_config (google.cloud.aiplatform_v1beta1.types.BlurBaselineConfig): + Config for IG with blur baseline. + + When enabled, a linear path from the maximally + blurred image to the input image is created. + Using a blurred baseline instead of zero (black + image) is motivated by the BlurIG approach + explained here: + + https://arxiv.org/abs/2004.03383 + """ + + step_count: int = proto.Field( + proto.INT32, + number=1, + ) + smooth_grad_config: "SmoothGradConfig" = proto.Field( + proto.MESSAGE, + number=2, + message="SmoothGradConfig", + ) + blur_baseline_config: "BlurBaselineConfig" = proto.Field( + proto.MESSAGE, + number=3, + message="BlurBaselineConfig", + ) + + +class XraiAttribution(proto.Message): + r"""An explanation method that redistributes Integrated Gradients + attributions to segmented regions, taking advantage of the + model's fully differentiable structure. Refer to this paper for + more details: + + https://arxiv.org/abs/1906.02825 + + Supported only by image Models. + + Attributes: + step_count (int): + Required. The number of steps for approximating the path + integral. A good value to start is 50 and gradually increase + until the sum to diff property is met within the desired + error range. + + Valid range of its value is [1, 100], inclusively. + smooth_grad_config (google.cloud.aiplatform_v1beta1.types.SmoothGradConfig): + Config for SmoothGrad approximation of + gradients. + When enabled, the gradients are approximated by + averaging the gradients from noisy samples in + the vicinity of the inputs. Adding noise can + help improve the computed gradients. Refer to + this paper for more details: + https://arxiv.org/pdf/1706.03825.pdf + blur_baseline_config (google.cloud.aiplatform_v1beta1.types.BlurBaselineConfig): + Config for XRAI with blur baseline. + + When enabled, a linear path from the maximally + blurred image to the input image is created. + Using a blurred baseline instead of zero (black + image) is motivated by the BlurIG approach + explained here: + + https://arxiv.org/abs/2004.03383 + """ + + step_count: int = proto.Field( + proto.INT32, + number=1, + ) + smooth_grad_config: "SmoothGradConfig" = proto.Field( + proto.MESSAGE, + number=2, + message="SmoothGradConfig", + ) + blur_baseline_config: "BlurBaselineConfig" = proto.Field( + proto.MESSAGE, + number=3, + message="BlurBaselineConfig", + ) + + +class SmoothGradConfig(proto.Message): + r"""Config for SmoothGrad approximation of gradients. + + When enabled, the gradients are approximated by averaging the + gradients from noisy samples in the vicinity of the inputs. + Adding noise can help improve the computed gradients. Refer to + this paper for more details: + + https://arxiv.org/pdf/1706.03825.pdf + + This message has `oneof`_ fields (mutually exclusive fields). + For each oneof, at most one member field can be set at the same time. + Setting any member of the oneof automatically clears all other + members. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + noise_sigma (float): + This is a single float value and will be used to add noise + to all the features. Use this field when all features are + normalized to have the same distribution: scale to range [0, + 1], [-1, 1] or z-scoring, where features are normalized to + have 0-mean and 1-variance. Learn more about + `normalization `__. + + For best results the recommended value is about 10% - 20% of + the standard deviation of the input feature. Refer to + section 3.2 of the SmoothGrad paper: + https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1. + + If the distribution is different per feature, set + [feature_noise_sigma][google.cloud.aiplatform.v1beta1.SmoothGradConfig.feature_noise_sigma] + instead for each feature. + + This field is a member of `oneof`_ ``GradientNoiseSigma``. + feature_noise_sigma (google.cloud.aiplatform_v1beta1.types.FeatureNoiseSigma): + This is similar to + [noise_sigma][google.cloud.aiplatform.v1beta1.SmoothGradConfig.noise_sigma], + but provides additional flexibility. A separate noise sigma + can be provided for each feature, which is useful if their + distributions are different. No noise is added to features + that are not set. If this field is unset, + [noise_sigma][google.cloud.aiplatform.v1beta1.SmoothGradConfig.noise_sigma] + will be used for all features. + + This field is a member of `oneof`_ ``GradientNoiseSigma``. + noisy_sample_count (int): + The number of gradient samples to use for approximation. The + higher this number, the more accurate the gradient is, but + the runtime complexity increases by this factor as well. + Valid range of its value is [1, 50]. Defaults to 3. + """ + + noise_sigma: float = proto.Field( + proto.FLOAT, + number=1, + oneof="GradientNoiseSigma", + ) + feature_noise_sigma: "FeatureNoiseSigma" = proto.Field( + proto.MESSAGE, + number=2, + oneof="GradientNoiseSigma", + message="FeatureNoiseSigma", + ) + noisy_sample_count: int = proto.Field( + proto.INT32, + number=3, + ) + + +class FeatureNoiseSigma(proto.Message): + r"""Noise sigma by features. Noise sigma represents the standard + deviation of the gaussian kernel that will be used to add noise + to interpolated inputs prior to computing gradients. + + Attributes: + noise_sigma (MutableSequence[google.cloud.aiplatform_v1beta1.types.FeatureNoiseSigma.NoiseSigmaForFeature]): + Noise sigma per feature. No noise is added to + features that are not set. + """ + + class NoiseSigmaForFeature(proto.Message): + r"""Noise sigma for a single feature. + + Attributes: + name (str): + The name of the input feature for which noise sigma is + provided. The features are defined in [explanation metadata + inputs][google.cloud.aiplatform.v1beta1.ExplanationMetadata.inputs]. + sigma (float): + This represents the standard deviation of the Gaussian + kernel that will be used to add noise to the feature prior + to computing gradients. Similar to + [noise_sigma][google.cloud.aiplatform.v1beta1.SmoothGradConfig.noise_sigma] + but represents the noise added to the current feature. + Defaults to 0.1. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + sigma: float = proto.Field( + proto.FLOAT, + number=2, + ) + + noise_sigma: MutableSequence[NoiseSigmaForFeature] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=NoiseSigmaForFeature, + ) + + +class BlurBaselineConfig(proto.Message): + r"""Config for blur baseline. + + When enabled, a linear path from the maximally blurred image to + the input image is created. Using a blurred baseline instead of + zero (black image) is motivated by the BlurIG approach explained + here: + + https://arxiv.org/abs/2004.03383 + + Attributes: + max_blur_sigma (float): + The standard deviation of the blur kernel for + the blurred baseline. The same blurring + parameter is used for both the height and the + width dimension. If not set, the method defaults + to the zero (i.e. black for images) baseline. + """ + + max_blur_sigma: float = proto.Field( + proto.FLOAT, + number=1, + ) + + +class Examples(proto.Message): + r"""Example-based explainability that returns the nearest + neighbors from the provided dataset. + + This message has `oneof`_ fields (mutually exclusive fields). + For each oneof, at most one member field can be set at the same time. + Setting any member of the oneof automatically clears all other + members. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + example_gcs_source (google.cloud.aiplatform_v1beta1.types.Examples.ExampleGcsSource): + The Cloud Storage input instances. + + This field is a member of `oneof`_ ``source``. + nearest_neighbor_search_config (google.protobuf.struct_pb2.Value): + The full configuration for the generated index, the + semantics are the same as + [metadata][google.cloud.aiplatform.v1beta1.Index.metadata] + and should match + `NearestNeighborSearchConfig `__. + + This field is a member of `oneof`_ ``config``. + presets (google.cloud.aiplatform_v1beta1.types.Presets): + Simplified preset configuration, which + automatically sets configuration values based on + the desired query speed-precision trade-off and + modality. + + This field is a member of `oneof`_ ``config``. + gcs_source (google.cloud.aiplatform_v1beta1.types.GcsSource): + The Cloud Storage locations that contain the + instances to be indexed for approximate nearest + neighbor search. + neighbor_count (int): + The number of neighbors to return when + querying for examples. + """ + + class ExampleGcsSource(proto.Message): + r"""The Cloud Storage input instances. + + Attributes: + data_format (google.cloud.aiplatform_v1beta1.types.Examples.ExampleGcsSource.DataFormat): + The format in which instances are given, if + not specified, assume it's JSONL format. + Currently only JSONL format is supported. + gcs_source (google.cloud.aiplatform_v1beta1.types.GcsSource): + The Cloud Storage location for the input + instances. + """ + + class DataFormat(proto.Enum): + r"""The format of the input example instances. + + Values: + DATA_FORMAT_UNSPECIFIED (0): + Format unspecified, used when unset. + JSONL (1): + Examples are stored in JSONL files. + """ + + DATA_FORMAT_UNSPECIFIED = 0 + JSONL = 1 + + data_format: "Examples.ExampleGcsSource.DataFormat" = proto.Field( + proto.ENUM, + number=1, + enum="Examples.ExampleGcsSource.DataFormat", + ) + gcs_source: io.GcsSource = proto.Field( + proto.MESSAGE, + number=2, + message=io.GcsSource, + ) + + example_gcs_source: ExampleGcsSource = proto.Field( + proto.MESSAGE, + number=5, + oneof="source", + message=ExampleGcsSource, + ) + nearest_neighbor_search_config: struct_pb2.Value = proto.Field( + proto.MESSAGE, + number=2, + oneof="config", + message=struct_pb2.Value, + ) + presets: "Presets" = proto.Field( + proto.MESSAGE, + number=4, + oneof="config", + message="Presets", + ) + gcs_source: io.GcsSource = proto.Field( + proto.MESSAGE, + number=1, + message=io.GcsSource, + ) + neighbor_count: int = proto.Field( + proto.INT32, + number=3, + ) + + +class Presets(proto.Message): + r"""Preset configuration for example-based explanations + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + query (google.cloud.aiplatform_v1beta1.types.Presets.Query): + Preset option controlling parameters for speed-precision + trade-off when querying for examples. If omitted, defaults + to ``PRECISE``. + + This field is a member of `oneof`_ ``_query``. + modality (google.cloud.aiplatform_v1beta1.types.Presets.Modality): + The modality of the uploaded model, which + automatically configures the distance + measurement and feature normalization for the + underlying example index and queries. If your + model does not precisely fit one of these types, + it is okay to choose the closest type. + """ + + class Query(proto.Enum): + r"""Preset option controlling parameters for query + speed-precision trade-off + + Values: + PRECISE (0): + More precise neighbors as a trade-off against + slower response. + FAST (1): + Faster response as a trade-off against less + precise neighbors. + """ + + PRECISE = 0 + FAST = 1 + + class Modality(proto.Enum): + r"""Preset option controlling parameters for different modalities + + Values: + MODALITY_UNSPECIFIED (0): + Should not be set. Added as a recommended + best practice for enums + IMAGE (1): + IMAGE modality + TEXT (2): + TEXT modality + TABULAR (3): + TABULAR modality + """ + + MODALITY_UNSPECIFIED = 0 + IMAGE = 1 + TEXT = 2 + TABULAR = 3 + + query: Query = proto.Field( + proto.ENUM, + number=1, + optional=True, + enum=Query, + ) + modality: Modality = proto.Field( + proto.ENUM, + number=2, + enum=Modality, + ) + + +class ExplanationSpecOverride(proto.Message): + r"""The + [ExplanationSpec][google.cloud.aiplatform.v1beta1.ExplanationSpec] + entries that can be overridden at [online + explanation][google.cloud.aiplatform.v1beta1.PredictionService.Explain] + time. + + Attributes: + parameters (google.cloud.aiplatform_v1beta1.types.ExplanationParameters): + The parameters to be overridden. Note that + the attribution method cannot be changed. If not + specified, no parameter is overridden. + metadata (google.cloud.aiplatform_v1beta1.types.ExplanationMetadataOverride): + The metadata to be overridden. If not + specified, no metadata is overridden. + examples_override (google.cloud.aiplatform_v1beta1.types.ExamplesOverride): + The example-based explanations parameter + overrides. + """ + + parameters: "ExplanationParameters" = proto.Field( + proto.MESSAGE, + number=1, + message="ExplanationParameters", + ) + metadata: "ExplanationMetadataOverride" = proto.Field( + proto.MESSAGE, + number=2, + message="ExplanationMetadataOverride", + ) + examples_override: "ExamplesOverride" = proto.Field( + proto.MESSAGE, + number=3, + message="ExamplesOverride", + ) + + +class ExplanationMetadataOverride(proto.Message): + r"""The + [ExplanationMetadata][google.cloud.aiplatform.v1beta1.ExplanationMetadata] + entries that can be overridden at [online + explanation][google.cloud.aiplatform.v1beta1.PredictionService.Explain] + time. + + Attributes: + inputs (MutableMapping[str, google.cloud.aiplatform_v1beta1.types.ExplanationMetadataOverride.InputMetadataOverride]): + Required. Overrides the [input + metadata][google.cloud.aiplatform.v1beta1.ExplanationMetadata.inputs] + of the features. The key is the name of the feature to be + overridden. The keys specified here must exist in the input + metadata to be overridden. If a feature is not specified + here, the corresponding feature's input metadata is not + overridden. + """ + + class InputMetadataOverride(proto.Message): + r"""The [input + metadata][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata] + entries to be overridden. + + Attributes: + input_baselines (MutableSequence[google.protobuf.struct_pb2.Value]): + Baseline inputs for this feature. + + This overrides the ``input_baseline`` field of the + [ExplanationMetadata.InputMetadata][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata] + object of the corresponding feature's input metadata. If + it's not specified, the original baselines are not + overridden. + """ + + input_baselines: MutableSequence[struct_pb2.Value] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=struct_pb2.Value, + ) + + inputs: MutableMapping[str, InputMetadataOverride] = proto.MapField( + proto.STRING, + proto.MESSAGE, + number=1, + message=InputMetadataOverride, + ) + + +class ExamplesOverride(proto.Message): + r"""Overrides for example-based explanations. + + Attributes: + neighbor_count (int): + The number of neighbors to return. + crowding_count (int): + The number of neighbors to return that have + the same crowding tag. + restrictions (MutableSequence[google.cloud.aiplatform_v1beta1.types.ExamplesRestrictionsNamespace]): + Restrict the resulting nearest neighbors to + respect these constraints. + return_embeddings (bool): + If true, return the embeddings instead of + neighbors. + data_format (google.cloud.aiplatform_v1beta1.types.ExamplesOverride.DataFormat): + The format of the data being provided with + each call. + """ + + class DataFormat(proto.Enum): + r"""Data format enum. + + Values: + DATA_FORMAT_UNSPECIFIED (0): + Unspecified format. Must not be used. + INSTANCES (1): + Provided data is a set of model inputs. + EMBEDDINGS (2): + Provided data is a set of embeddings. + """ + + DATA_FORMAT_UNSPECIFIED = 0 + INSTANCES = 1 + EMBEDDINGS = 2 + + neighbor_count: int = proto.Field( + proto.INT32, + number=1, + ) + crowding_count: int = proto.Field( + proto.INT32, + number=2, + ) + restrictions: MutableSequence["ExamplesRestrictionsNamespace"] = ( + proto.RepeatedField( + proto.MESSAGE, + number=3, + message="ExamplesRestrictionsNamespace", + ) + ) + return_embeddings: bool = proto.Field( + proto.BOOL, + number=4, + ) + data_format: DataFormat = proto.Field( + proto.ENUM, + number=5, + enum=DataFormat, + ) + + +class ExamplesRestrictionsNamespace(proto.Message): + r"""Restrictions namespace for example-based explanations + overrides. + + Attributes: + namespace_name (str): + The namespace name. + allow (MutableSequence[str]): + The list of allowed tags. + deny (MutableSequence[str]): + The list of deny tags. + """ + + namespace_name: str = proto.Field( + proto.STRING, + number=1, + ) + allow: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=2, + ) + deny: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=3, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/extension_registry_service.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/extension_registry_service.py new file mode 100644 index 0000000000000000000000000000000000000000..6559430fbf85e6439799a0cb8b0954e580587689 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/extension_registry_service.py @@ -0,0 +1,228 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import extension as gca_extension +from google.cloud.aiplatform_v1beta1.types import operation +import google.protobuf.field_mask_pb2 as field_mask_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "ImportExtensionRequest", + "ImportExtensionOperationMetadata", + "GetExtensionRequest", + "UpdateExtensionRequest", + "ListExtensionsRequest", + "ListExtensionsResponse", + "DeleteExtensionRequest", + }, +) + + +class ImportExtensionRequest(proto.Message): + r"""Request message for + [ExtensionRegistryService.ImportExtension][google.cloud.aiplatform.v1beta1.ExtensionRegistryService.ImportExtension]. + + Attributes: + parent (str): + Required. The resource name of the Location to import the + Extension in. Format: + ``projects/{project}/locations/{location}`` + extension (google.cloud.aiplatform_v1beta1.types.Extension): + Required. The Extension to import. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + extension: gca_extension.Extension = proto.Field( + proto.MESSAGE, + number=2, + message=gca_extension.Extension, + ) + + +class ImportExtensionOperationMetadata(proto.Message): + r"""Details of + [ExtensionRegistryService.ImportExtension][google.cloud.aiplatform.v1beta1.ExtensionRegistryService.ImportExtension] + operation. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + The common part of the operation metadata. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class GetExtensionRequest(proto.Message): + r"""Request message for + [ExtensionRegistryService.GetExtension][google.cloud.aiplatform.v1beta1.ExtensionRegistryService.GetExtension]. + + Attributes: + name (str): + Required. The name of the Extension resource. Format: + ``projects/{project}/locations/{location}/extensions/{extension}`` + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class UpdateExtensionRequest(proto.Message): + r"""Request message for + [ExtensionRegistryService.UpdateExtension][google.cloud.aiplatform.v1beta1.ExtensionRegistryService.UpdateExtension]. + + Attributes: + extension (google.cloud.aiplatform_v1beta1.types.Extension): + Required. The Extension which replaces the + resource on the server. + update_mask (google.protobuf.field_mask_pb2.FieldMask): + Required. Mask specifying which fields to update. Supported + fields: + + :: + + * `display_name` + * `description` + * `runtime_config` + * `tool_use_examples` + * `manifest.description` + """ + + extension: gca_extension.Extension = proto.Field( + proto.MESSAGE, + number=1, + message=gca_extension.Extension, + ) + update_mask: field_mask_pb2.FieldMask = proto.Field( + proto.MESSAGE, + number=2, + message=field_mask_pb2.FieldMask, + ) + + +class ListExtensionsRequest(proto.Message): + r"""Request message for + [ExtensionRegistryService.ListExtensions][google.cloud.aiplatform.v1beta1.ExtensionRegistryService.ListExtensions]. + + Attributes: + parent (str): + Required. The resource name of the Location to list the + Extensions from. Format: + ``projects/{project}/locations/{location}`` + filter (str): + Optional. The standard list filter. Supported fields: \* + ``display_name`` \* ``create_time`` \* ``update_time`` + + More detail in `AIP-160 `__. + page_size (int): + Optional. The standard list page size. + page_token (str): + Optional. The standard list page token. + order_by (str): + Optional. A comma-separated list of fields to order by, + sorted in ascending order. Use "desc" after a field name for + descending. Supported fields: + + - ``display_name`` + - ``create_time`` + - ``update_time`` + + Example: ``display_name, create_time desc``. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + filter: str = proto.Field( + proto.STRING, + number=2, + ) + page_size: int = proto.Field( + proto.INT32, + number=3, + ) + page_token: str = proto.Field( + proto.STRING, + number=4, + ) + order_by: str = proto.Field( + proto.STRING, + number=6, + ) + + +class ListExtensionsResponse(proto.Message): + r"""Response message for + [ExtensionRegistryService.ListExtensions][google.cloud.aiplatform.v1beta1.ExtensionRegistryService.ListExtensions] + + Attributes: + extensions (MutableSequence[google.cloud.aiplatform_v1beta1.types.Extension]): + List of Extension in the requested page. + next_page_token (str): + A token to retrieve the next page of results. Pass to + [ListExtensionsRequest.page_token][google.cloud.aiplatform.v1beta1.ListExtensionsRequest.page_token] + to obtain that page. + """ + + @property + def raw_page(self): + return self + + extensions: MutableSequence[gca_extension.Extension] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=gca_extension.Extension, + ) + next_page_token: str = proto.Field( + proto.STRING, + number=2, + ) + + +class DeleteExtensionRequest(proto.Message): + r"""Request message for + [ExtensionRegistryService.DeleteExtension][google.cloud.aiplatform.v1beta1.ExtensionRegistryService.DeleteExtension]. + + Attributes: + name (str): + Required. The name of the Extension resource to be deleted. + Format: + ``projects/{project}/locations/{location}/extensions/{extension}`` + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/feature_monitor.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/feature_monitor.py new file mode 100644 index 0000000000000000000000000000000000000000..1e753ec0ab9e703e21903eb38006ce86710634dd --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/feature_monitor.py @@ -0,0 +1,288 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +import google.protobuf.struct_pb2 as struct_pb2 # type: ignore +import google.protobuf.timestamp_pb2 as timestamp_pb2 # type: ignore +import google.type.interval_pb2 as interval_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "FeatureMonitor", + "ScheduleConfig", + "FeatureSelectionConfig", + "FeatureStatsAndAnomaly", + "FeatureStatsAndAnomalySpec", + }, +) + + +class FeatureMonitor(proto.Message): + r"""Vertex AI Feature Monitor. + + Attributes: + name (str): + Identifier. Name of the FeatureMonitor. Format: + ``projects/{project}/locations/{location}/featureGroups/{featureGroup}/featureMonitors/{featureMonitor}`` + create_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when this + FeatureMonitor was created. + update_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when this + FeatureMonitor was last updated. + etag (str): + Optional. Used to perform consistent + read-modify-write updates. If not set, a blind + "overwrite" update happens. + labels (MutableMapping[str, str]): + Optional. The labels with user-defined + metadata to organize your FeatureMonitor. + + Label keys and values can be no longer than 64 + characters (Unicode codepoints), can only + contain lowercase letters, numeric characters, + underscores and dashes. International characters + are allowed. + + See https://goo.gl/xmQnxf for more information + on and examples of labels. No more than 64 user + labels can be associated with one + FeatureMonitor(System labels are excluded)." + System reserved label keys are prefixed with + "aiplatform.googleapis.com/" and are immutable. + description (str): + Optional. Description of the FeatureMonitor. + schedule_config (google.cloud.aiplatform_v1beta1.types.ScheduleConfig): + Required. Schedule config for the + FeatureMonitor. + feature_selection_config (google.cloud.aiplatform_v1beta1.types.FeatureSelectionConfig): + Required. Feature selection config for the + FeatureMonitor. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + create_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=2, + message=timestamp_pb2.Timestamp, + ) + update_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=3, + message=timestamp_pb2.Timestamp, + ) + etag: str = proto.Field( + proto.STRING, + number=4, + ) + labels: MutableMapping[str, str] = proto.MapField( + proto.STRING, + proto.STRING, + number=5, + ) + description: str = proto.Field( + proto.STRING, + number=6, + ) + schedule_config: "ScheduleConfig" = proto.Field( + proto.MESSAGE, + number=7, + message="ScheduleConfig", + ) + feature_selection_config: "FeatureSelectionConfig" = proto.Field( + proto.MESSAGE, + number=8, + message="FeatureSelectionConfig", + ) + + +class ScheduleConfig(proto.Message): + r"""Schedule configuration for the FeatureMonitor. + + Attributes: + cron (str): + Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch + scheduled runs. To explicitly set a timezone to the cron + tab, apply a prefix in the cron tab: + "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The + ${IANA_TIME_ZONE} may only be a valid string from IANA time + zone database. For example, "CRON_TZ=America/New_York 1 \* + \* \* \*", or "TZ=America/New_York 1 \* \* \* \*". + """ + + cron: str = proto.Field( + proto.STRING, + number=1, + ) + + +class FeatureSelectionConfig(proto.Message): + r"""Feature selection configuration for the FeatureMonitor. + + Attributes: + feature_configs (MutableSequence[google.cloud.aiplatform_v1beta1.types.FeatureSelectionConfig.FeatureConfig]): + Optional. A list of features to be monitored + and each feature's drift threshold. + """ + + class FeatureConfig(proto.Message): + r"""Feature configuration. + + Attributes: + feature_id (str): + Required. The ID of the feature resource. + Final component of the Feature's resource name. + drift_threshold (float): + Optional. Drift threshold. If calculated + difference with baseline data larger than + threshold, it will be considered as the feature + has drift. If not present, the threshold will be + default to 0.3. + """ + + feature_id: str = proto.Field( + proto.STRING, + number=1, + ) + drift_threshold: float = proto.Field( + proto.DOUBLE, + number=2, + ) + + feature_configs: MutableSequence[FeatureConfig] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=FeatureConfig, + ) + + +class FeatureStatsAndAnomaly(proto.Message): + r"""Stats and Anomaly generated by FeatureMonitorJobs. Anomaly + only includes Drift. + + Attributes: + feature_id (str): + Feature Id. + feature_stats (google.protobuf.struct_pb2.Value): + Feature stats. e.g. histogram buckets. + In the format of + tensorflow.metadata.v0.DatasetFeatureStatistics. + distribution_deviation (float): + Deviation from the current stats to baseline + stats. + 1. For categorical feature, the distribution + distance is calculated by L-inifinity + norm. + 2. For numerical feature, the distribution + distance is calculated by + Jensen–Shannon divergence. + drift_detection_threshold (float): + This is the threshold used when detecting drifts, which is + set in + FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold + drift_detected (bool): + If set to true, indicates current stats is + detected as and comparing with baseline stats. + stats_time (google.protobuf.timestamp_pb2.Timestamp): + The timestamp we take snapshot for feature + values to generate stats. + feature_monitor_job_id (int): + The ID of the FeatureMonitorJob that + generated this FeatureStatsAndAnomaly. + feature_monitor_id (str): + The ID of the FeatureMonitor that this + FeatureStatsAndAnomaly generated according to. + """ + + feature_id: str = proto.Field( + proto.STRING, + number=1, + ) + feature_stats: struct_pb2.Value = proto.Field( + proto.MESSAGE, + number=2, + message=struct_pb2.Value, + ) + distribution_deviation: float = proto.Field( + proto.DOUBLE, + number=3, + ) + drift_detection_threshold: float = proto.Field( + proto.DOUBLE, + number=4, + ) + drift_detected: bool = proto.Field( + proto.BOOL, + number=5, + ) + stats_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=6, + message=timestamp_pb2.Timestamp, + ) + feature_monitor_job_id: int = proto.Field( + proto.INT64, + number=7, + ) + feature_monitor_id: str = proto.Field( + proto.STRING, + number=8, + ) + + +class FeatureStatsAndAnomalySpec(proto.Message): + r"""Defines how to select FeatureStatsAndAnomaly to be populated + in response. If set, retrieves FeatureStatsAndAnomaly generated + by FeatureMonitors based on this spec. + + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + latest_stats_count (int): + Optional. If set, returns the most recent count of stats. + Valid value is [0, 100]. If stats_time_range is set, return + most recent count of stats within the stats_time_range. + + This field is a member of `oneof`_ ``_latest_stats_count``. + stats_time_range (google.type.interval_pb2.Interval): + Optional. If set, return all stats generated between + [start_time, end_time). If latest_stats_count is set, return + the most recent count of stats within the stats_time_range. + """ + + latest_stats_count: int = proto.Field( + proto.INT32, + number=1, + optional=True, + ) + stats_time_range: interval_pb2.Interval = proto.Field( + proto.MESSAGE, + number=2, + message=interval_pb2.Interval, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/feature_monitor_job.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/feature_monitor_job.py new file mode 100644 index 0000000000000000000000000000000000000000..5c8959fd8102e8af2c00aec15edcd5f12b37b024 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/feature_monitor_job.py @@ -0,0 +1,176 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import feature_monitor +import google.protobuf.timestamp_pb2 as timestamp_pb2 # type: ignore +import google.rpc.status_pb2 as status_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "FeatureMonitorJob", + }, +) + + +class FeatureMonitorJob(proto.Message): + r"""Vertex AI Feature Monitor Job. + + Attributes: + name (str): + Identifier. Name of the FeatureMonitorJob. Format: + ``projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}/featureMonitorJobs/{feature_monitor_job}``. + create_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when this + FeatureMonitorJob was created. Creation of a + FeatureMonitorJob means that the job is pending + / waiting for sufficient resources but may not + have started running yet. + final_status (google.rpc.status_pb2.Status): + Output only. Final status of the + FeatureMonitorJob. + job_summary (google.cloud.aiplatform_v1beta1.types.FeatureMonitorJob.JobSummary): + Output only. Summary from the + FeatureMonitorJob. + labels (MutableMapping[str, str]): + Optional. The labels with user-defined + metadata to organize your FeatureMonitorJob. + + Label keys and values can be no longer than 64 + characters (Unicode codepoints), can only + contain lowercase letters, numeric characters, + underscores and dashes. International characters + are allowed. + + See https://goo.gl/xmQnxf for more information + on and examples of labels. No more than 64 user + labels can be associated with one + FeatureMonitor(System labels are excluded)." + System reserved label keys are prefixed with + "aiplatform.googleapis.com/" and are immutable. + description (str): + Optional. Description of the FeatureMonitor. + drift_base_feature_monitor_job_id (int): + Output only. FeatureMonitorJob ID comparing + to which the drift is calculated. + drift_base_snapshot_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Data snapshot time comparing to + which the drift is calculated. + feature_selection_config (google.cloud.aiplatform_v1beta1.types.FeatureSelectionConfig): + Output only. Feature selection config used + when creating FeatureMonitorJob. + trigger_type (google.cloud.aiplatform_v1beta1.types.FeatureMonitorJob.FeatureMonitorJobTrigger): + Output only. Trigger type of the Feature + Monitor Job. + """ + + class FeatureMonitorJobTrigger(proto.Enum): + r"""Choices of the trigger type. + + Values: + FEATURE_MONITOR_JOB_TRIGGER_UNSPECIFIED (0): + Trigger type unspecified. + FEATURE_MONITOR_JOB_TRIGGER_PERIODIC (1): + Triggered by periodic schedule. + FEATURE_MONITOR_JOB_TRIGGER_ON_DEMAND (2): + Triggered on demand by + CreateFeatureMonitorJob request. + """ + + FEATURE_MONITOR_JOB_TRIGGER_UNSPECIFIED = 0 + FEATURE_MONITOR_JOB_TRIGGER_PERIODIC = 1 + FEATURE_MONITOR_JOB_TRIGGER_ON_DEMAND = 2 + + class JobSummary(proto.Message): + r"""Summary from the FeatureMonitorJob. + + Attributes: + total_slot_ms (int): + Output only. BigQuery slot milliseconds + consumed. + feature_stats_and_anomalies (MutableSequence[google.cloud.aiplatform_v1beta1.types.FeatureStatsAndAnomaly]): + Output only. Features and their stats and + anomalies + """ + + total_slot_ms: int = proto.Field( + proto.INT64, + number=1, + ) + feature_stats_and_anomalies: MutableSequence[ + feature_monitor.FeatureStatsAndAnomaly + ] = proto.RepeatedField( + proto.MESSAGE, + number=2, + message=feature_monitor.FeatureStatsAndAnomaly, + ) + + name: str = proto.Field( + proto.STRING, + number=1, + ) + create_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=2, + message=timestamp_pb2.Timestamp, + ) + final_status: status_pb2.Status = proto.Field( + proto.MESSAGE, + number=3, + message=status_pb2.Status, + ) + job_summary: JobSummary = proto.Field( + proto.MESSAGE, + number=4, + message=JobSummary, + ) + labels: MutableMapping[str, str] = proto.MapField( + proto.STRING, + proto.STRING, + number=5, + ) + description: str = proto.Field( + proto.STRING, + number=6, + ) + drift_base_feature_monitor_job_id: int = proto.Field( + proto.INT64, + number=7, + ) + drift_base_snapshot_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=8, + message=timestamp_pb2.Timestamp, + ) + feature_selection_config: feature_monitor.FeatureSelectionConfig = proto.Field( + proto.MESSAGE, + number=9, + message=feature_monitor.FeatureSelectionConfig, + ) + trigger_type: FeatureMonitorJobTrigger = proto.Field( + proto.ENUM, + number=10, + enum=FeatureMonitorJobTrigger, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/feature_registry_service.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/feature_registry_service.py new file mode 100644 index 0000000000000000000000000000000000000000..5abbc62ac32a7125e278307c75fe450c90ebaa71 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/feature_registry_service.py @@ -0,0 +1,725 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import feature_group as gca_feature_group +from google.cloud.aiplatform_v1beta1.types import feature_monitor as gca_feature_monitor +from google.cloud.aiplatform_v1beta1.types import ( + feature_monitor_job as gca_feature_monitor_job, +) +from google.cloud.aiplatform_v1beta1.types import operation +import google.protobuf.field_mask_pb2 as field_mask_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "CreateFeatureGroupRequest", + "GetFeatureGroupRequest", + "ListFeatureGroupsRequest", + "ListFeatureGroupsResponse", + "UpdateFeatureGroupRequest", + "DeleteFeatureGroupRequest", + "CreateFeatureMonitorRequest", + "GetFeatureMonitorRequest", + "ListFeatureMonitorsRequest", + "UpdateFeatureMonitorRequest", + "DeleteFeatureMonitorRequest", + "ListFeatureMonitorsResponse", + "CreateFeatureGroupOperationMetadata", + "UpdateFeatureGroupOperationMetadata", + "CreateRegistryFeatureOperationMetadata", + "UpdateFeatureOperationMetadata", + "CreateFeatureMonitorOperationMetadata", + "UpdateFeatureMonitorOperationMetadata", + "CreateFeatureMonitorJobRequest", + "GetFeatureMonitorJobRequest", + "ListFeatureMonitorJobsRequest", + "ListFeatureMonitorJobsResponse", + }, +) + + +class CreateFeatureGroupRequest(proto.Message): + r"""Request message for + [FeatureRegistryService.CreateFeatureGroup][google.cloud.aiplatform.v1beta1.FeatureRegistryService.CreateFeatureGroup]. + + Attributes: + parent (str): + Required. The resource name of the Location to create + FeatureGroups. Format: + ``projects/{project}/locations/{location}`` + feature_group (google.cloud.aiplatform_v1beta1.types.FeatureGroup): + Required. The FeatureGroup to create. + feature_group_id (str): + Required. The ID to use for this FeatureGroup, which will + become the final component of the FeatureGroup's resource + name. + + This value may be up to 128 characters, and valid characters + are ``[a-z0-9_]``. The first character cannot be a number. + + The value must be unique within the project and location. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + feature_group: gca_feature_group.FeatureGroup = proto.Field( + proto.MESSAGE, + number=2, + message=gca_feature_group.FeatureGroup, + ) + feature_group_id: str = proto.Field( + proto.STRING, + number=3, + ) + + +class GetFeatureGroupRequest(proto.Message): + r"""Request message for + [FeatureRegistryService.GetFeatureGroup][google.cloud.aiplatform.v1beta1.FeatureRegistryService.GetFeatureGroup]. + + Attributes: + name (str): + Required. The name of the FeatureGroup + resource. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class ListFeatureGroupsRequest(proto.Message): + r"""Request message for + [FeatureRegistryService.ListFeatureGroups][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureGroups]. + + Attributes: + parent (str): + Required. The resource name of the Location to list + FeatureGroups. Format: + ``projects/{project}/locations/{location}`` + filter (str): + Lists the FeatureGroups that match the filter expression. + The following fields are supported: + + - ``create_time``: Supports ``=``, ``!=``, ``<``, ``>``, + ``<=``, and ``>=`` comparisons. Values must be in RFC 3339 + format. + - ``update_time``: Supports ``=``, ``!=``, ``<``, ``>``, + ``<=``, and ``>=`` comparisons. Values must be in RFC 3339 + format. + - ``labels``: Supports key-value equality and key presence. + + Examples: + + - ``create_time > "2020-01-01" OR update_time > "2020-01-01"`` + FeatureGroups created or updated after 2020-01-01. + - ``labels.env = "prod"`` FeatureGroups with label "env" set + to "prod". + page_size (int): + The maximum number of FeatureGroups to + return. The service may return fewer than this + value. If unspecified, at most 100 FeatureGroups + will be returned. The maximum value is 100; any + value greater than 100 will be coerced to 100. + page_token (str): + A page token, received from a previous + [FeatureGroupAdminService.ListFeatureGroups][] call. Provide + this to retrieve the subsequent page. + + When paginating, all other parameters provided to + [FeatureGroupAdminService.ListFeatureGroups][] must match + the call that provided the page token. + order_by (str): + A comma-separated list of fields to order by, sorted in + ascending order. Use "desc" after a field name for + descending. Supported Fields: + + - ``create_time`` + - ``update_time`` + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + filter: str = proto.Field( + proto.STRING, + number=2, + ) + page_size: int = proto.Field( + proto.INT32, + number=3, + ) + page_token: str = proto.Field( + proto.STRING, + number=4, + ) + order_by: str = proto.Field( + proto.STRING, + number=5, + ) + + +class ListFeatureGroupsResponse(proto.Message): + r"""Response message for + [FeatureRegistryService.ListFeatureGroups][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureGroups]. + + Attributes: + feature_groups (MutableSequence[google.cloud.aiplatform_v1beta1.types.FeatureGroup]): + The FeatureGroups matching the request. + next_page_token (str): + A token, which can be sent as + [ListFeatureGroupsRequest.page_token][google.cloud.aiplatform.v1beta1.ListFeatureGroupsRequest.page_token] + to retrieve the next page. If this field is omitted, there + are no subsequent pages. + """ + + @property + def raw_page(self): + return self + + feature_groups: MutableSequence[gca_feature_group.FeatureGroup] = ( + proto.RepeatedField( + proto.MESSAGE, + number=1, + message=gca_feature_group.FeatureGroup, + ) + ) + next_page_token: str = proto.Field( + proto.STRING, + number=2, + ) + + +class UpdateFeatureGroupRequest(proto.Message): + r"""Request message for + [FeatureRegistryService.UpdateFeatureGroup][google.cloud.aiplatform.v1beta1.FeatureRegistryService.UpdateFeatureGroup]. + + Attributes: + feature_group (google.cloud.aiplatform_v1beta1.types.FeatureGroup): + Required. The FeatureGroup's ``name`` field is used to + identify the FeatureGroup to be updated. Format: + ``projects/{project}/locations/{location}/featureGroups/{feature_group}`` + update_mask (google.protobuf.field_mask_pb2.FieldMask): + Field mask is used to specify the fields to be overwritten + in the FeatureGroup resource by the update. The fields + specified in the update_mask are relative to the resource, + not the full request. A field will be overwritten if it is + in the mask. If the user does not provide a mask then only + the non-empty fields present in the request will be + overwritten. Set the update_mask to ``*`` to override all + fields. + + Updatable fields: + + - ``labels`` + - ``description`` + - ``big_query`` + - ``big_query.entity_id_columns`` + """ + + feature_group: gca_feature_group.FeatureGroup = proto.Field( + proto.MESSAGE, + number=1, + message=gca_feature_group.FeatureGroup, + ) + update_mask: field_mask_pb2.FieldMask = proto.Field( + proto.MESSAGE, + number=2, + message=field_mask_pb2.FieldMask, + ) + + +class DeleteFeatureGroupRequest(proto.Message): + r"""Request message for + [FeatureRegistryService.DeleteFeatureGroup][google.cloud.aiplatform.v1beta1.FeatureRegistryService.DeleteFeatureGroup]. + + Attributes: + name (str): + Required. The name of the FeatureGroup to be deleted. + Format: + ``projects/{project}/locations/{location}/featureGroups/{feature_group}`` + force (bool): + If set to true, any Features under this + FeatureGroup will also be deleted. (Otherwise, + the request will only work if the FeatureGroup + has no Features.) + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + force: bool = proto.Field( + proto.BOOL, + number=2, + ) + + +class CreateFeatureMonitorRequest(proto.Message): + r"""Request message for + [FeatureRegistryService.CreateFeatureMonitorRequest][]. + + Attributes: + parent (str): + Required. The resource name of FeatureGroup to create + FeatureMonitor. Format: + ``projects/{project}/locations/{location}/featureGroups/{featuregroup}`` + feature_monitor (google.cloud.aiplatform_v1beta1.types.FeatureMonitor): + Required. The Monitor to create. + feature_monitor_id (str): + Required. The ID to use for this FeatureMonitor, which will + become the final component of the FeatureGroup's resource + name. + + This value may be up to 60 characters, and valid characters + are ``[a-z0-9_]``. The first character cannot be a number. + + The value must be unique within the FeatureGroup. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + feature_monitor: gca_feature_monitor.FeatureMonitor = proto.Field( + proto.MESSAGE, + number=2, + message=gca_feature_monitor.FeatureMonitor, + ) + feature_monitor_id: str = proto.Field( + proto.STRING, + number=3, + ) + + +class GetFeatureMonitorRequest(proto.Message): + r"""Request message for + [FeatureRegistryService.GetFeatureMonitor][google.cloud.aiplatform.v1beta1.FeatureRegistryService.GetFeatureMonitor]. + + Attributes: + name (str): + Required. The name of the FeatureMonitor + resource. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class ListFeatureMonitorsRequest(proto.Message): + r"""Request message for + [FeatureRegistryService.ListFeatureMonitors][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitors]. + + Attributes: + parent (str): + Required. The resource name of the FeatureGroup to list + FeatureMonitors. Format: + ``projects/{project}/locations/{location}/featureGroups/{featureGroup}`` + filter (str): + Optional. Lists the FeatureMonitors that match the filter + expression. The following fields are supported: + + - ``create_time``: Supports ``=``, ``!=``, ``<``, ``>``, + ``<=``, and ``>=`` comparisons. Values must be in RFC 3339 + format. + - ``update_time``: Supports ``=``, ``!=``, ``<``, ``>``, + ``<=``, and ``>=`` comparisons. Values must be in RFC 3339 + format. + - ``labels``: Supports key-value equality and key presence. + + Examples: + + - ``create_time > "2020-01-01" OR update_time > "2020-01-01"`` + FeatureMonitors created or updated after 2020-01-01. + - ``labels.env = "prod"`` FeatureGroups with label "env" set + to "prod". + page_size (int): + Optional. The maximum number of FeatureGroups + to return. The service may return fewer than + this value. If unspecified, at most 100 + FeatureMonitors will be returned. The maximum + value is 100; any value greater than 100 will be + coerced to 100. + page_token (str): + Optional. A page token, received from a previous + [FeatureRegistryService.ListFeatureMonitors][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitors] + call. Provide this to retrieve the subsequent page. + + When paginating, all other parameters provided to + [FeatureRegistryService.ListFeatureMonitors][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitors] + must match the call that provided the page token. + order_by (str): + Optional. A comma-separated list of fields to order by, + sorted in ascending order. Use "desc" after a field name for + descending. Supported Fields: + + - ``create_time`` + - ``update_time`` + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + filter: str = proto.Field( + proto.STRING, + number=2, + ) + page_size: int = proto.Field( + proto.INT32, + number=3, + ) + page_token: str = proto.Field( + proto.STRING, + number=4, + ) + order_by: str = proto.Field( + proto.STRING, + number=5, + ) + + +class UpdateFeatureMonitorRequest(proto.Message): + r"""Request message for + [FeatureRegistryService.UpdateFeatureMonitor][google.cloud.aiplatform.v1beta1.FeatureRegistryService.UpdateFeatureMonitor]. + + Attributes: + feature_monitor (google.cloud.aiplatform_v1beta1.types.FeatureMonitor): + Required. The FeatureMonitor's ``name`` field is used to + identify the FeatureMonitor to be updated. Format: + ``projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}`` + update_mask (google.protobuf.field_mask_pb2.FieldMask): + Optional. Field mask is used to specify the fields to be + overwritten in the FeatureMonitor resource by the update. + The fields specified in the update_mask are relative to the + resource, not the full request. A field will be overwritten + if it is in the mask. If the user does not provide a mask + then only the non-empty fields present in the request will + be overwritten. Set the update_mask to ``*`` to override all + fields. + + Updatable fields: + + - ``labels`` + """ + + feature_monitor: gca_feature_monitor.FeatureMonitor = proto.Field( + proto.MESSAGE, + number=1, + message=gca_feature_monitor.FeatureMonitor, + ) + update_mask: field_mask_pb2.FieldMask = proto.Field( + proto.MESSAGE, + number=2, + message=field_mask_pb2.FieldMask, + ) + + +class DeleteFeatureMonitorRequest(proto.Message): + r"""Request message for + [FeatureRegistryService.DeleteFeatureMonitor][google.cloud.aiplatform.v1beta1.FeatureRegistryService.DeleteFeatureMonitor]. + + Attributes: + name (str): + Required. The name of the FeatureMonitor to be deleted. + Format: + ``projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}`` + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class ListFeatureMonitorsResponse(proto.Message): + r"""Response message for + [FeatureRegistryService.ListFeatureMonitors][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitors]. + + Attributes: + feature_monitors (MutableSequence[google.cloud.aiplatform_v1beta1.types.FeatureMonitor]): + The FeatureMonitors matching the request. + next_page_token (str): + A token, which can be sent as + [ListFeatureMonitorsRequest.page_token][google.cloud.aiplatform.v1beta1.ListFeatureMonitorsRequest.page_token] + to retrieve the next page. If this field is omitted, there + are no subsequent pages. + """ + + @property + def raw_page(self): + return self + + feature_monitors: MutableSequence[gca_feature_monitor.FeatureMonitor] = ( + proto.RepeatedField( + proto.MESSAGE, + number=1, + message=gca_feature_monitor.FeatureMonitor, + ) + ) + next_page_token: str = proto.Field( + proto.STRING, + number=2, + ) + + +class CreateFeatureGroupOperationMetadata(proto.Message): + r"""Details of operations that perform create FeatureGroup. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + Operation metadata for FeatureGroup. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class UpdateFeatureGroupOperationMetadata(proto.Message): + r"""Details of operations that perform update FeatureGroup. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + Operation metadata for FeatureGroup. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class CreateRegistryFeatureOperationMetadata(proto.Message): + r"""Details of operations that perform create FeatureGroup. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + Operation metadata for Feature. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class UpdateFeatureOperationMetadata(proto.Message): + r"""Details of operations that perform update Feature. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + Operation metadata for Feature Update. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class CreateFeatureMonitorOperationMetadata(proto.Message): + r"""Details of operations that perform create FeatureMonitor. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + Operation metadata for Feature. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class UpdateFeatureMonitorOperationMetadata(proto.Message): + r"""Details of operations that perform update FeatureMonitor. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + Operation metadata for FeatureMonitor. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class CreateFeatureMonitorJobRequest(proto.Message): + r"""Request message for + [FeatureRegistryService.CreateFeatureMonitorJobRequest][]. + + Attributes: + parent (str): + Required. The resource name of FeatureMonitor to create + FeatureMonitorJob. Format: + ``projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}`` + feature_monitor_job (google.cloud.aiplatform_v1beta1.types.FeatureMonitorJob): + Required. The Monitor to create. + feature_monitor_job_id (int): + Optional. Output only. System-generated ID + for feature monitor job. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + feature_monitor_job: gca_feature_monitor_job.FeatureMonitorJob = proto.Field( + proto.MESSAGE, + number=2, + message=gca_feature_monitor_job.FeatureMonitorJob, + ) + feature_monitor_job_id: int = proto.Field( + proto.INT64, + number=3, + ) + + +class GetFeatureMonitorJobRequest(proto.Message): + r"""Request message for + [FeatureRegistryService.GetFeatureMonitorJob][google.cloud.aiplatform.v1beta1.FeatureRegistryService.GetFeatureMonitorJob]. + + Attributes: + name (str): + Required. The name of the FeatureMonitorJob resource. + Format: + ``projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}/featureMonitorJobs/{feature_monitor_job}`` + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class ListFeatureMonitorJobsRequest(proto.Message): + r"""Request message for + [FeatureRegistryService.ListFeatureMonitorJobs][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitorJobs]. + + Attributes: + parent (str): + Required. The resource name of the FeatureMonitor to list + FeatureMonitorJobs. Format: + ``projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}`` + filter (str): + Optional. Lists the FeatureMonitorJobs that match the filter + expression. The following fields are supported: + + - ``create_time``: Supports ``=``, ``!=``, ``<``, ``>``, + ``<=``, and ``>=`` comparisons. Values must be + + Examples: + + - ``create_time > "2020-01-01"`` FeatureMonitorJobs created + after 2020-01-01. + page_size (int): + Optional. The maximum number of + FeatureMonitorJobs to return. The service may + return fewer than this value. If unspecified, at + most 100 FeatureMonitorJobs will be returned. + The maximum value is 100; any value greater than + 100 will be coerced to 100. + page_token (str): + Optional. A page token, received from a previous + [FeatureRegistryService.ListFeatureMonitorJobs][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitorJobs] + call. Provide this to retrieve the subsequent page. + + When paginating, all other parameters provided to + [FeatureRegistryService.ListFeatureMonitorJobs][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitorJobs] + must match the call that provided the page token. + order_by (str): + Optional. A comma-separated list of fields to order by, + sorted in ascending order. Use "desc" after a field name for + descending. Supported Fields: + + - ``create_time`` + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + filter: str = proto.Field( + proto.STRING, + number=2, + ) + page_size: int = proto.Field( + proto.INT32, + number=3, + ) + page_token: str = proto.Field( + proto.STRING, + number=4, + ) + order_by: str = proto.Field( + proto.STRING, + number=5, + ) + + +class ListFeatureMonitorJobsResponse(proto.Message): + r"""Response message for + [FeatureRegistryService.ListFeatureMonitorJobs][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitorJobs]. + + Attributes: + feature_monitor_jobs (MutableSequence[google.cloud.aiplatform_v1beta1.types.FeatureMonitorJob]): + The FeatureMonitorJobs matching the request. + next_page_token (str): + A token, which can be sent as + [ListFeatureMonitorJobsRequest.page_token][google.cloud.aiplatform.v1beta1.ListFeatureMonitorJobsRequest.page_token] + to retrieve the next page. If this field is omitted, there + are no subsequent pages. + """ + + @property + def raw_page(self): + return self + + feature_monitor_jobs: MutableSequence[gca_feature_monitor_job.FeatureMonitorJob] = ( + proto.RepeatedField( + proto.MESSAGE, + number=1, + message=gca_feature_monitor_job.FeatureMonitorJob, + ) + ) + next_page_token: str = proto.Field( + proto.STRING, + number=2, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/featurestore.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/featurestore.py new file mode 100644 index 0000000000000000000000000000000000000000..771721c0b15c2872b5fcc6039a9f5f214a0d11eb --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/featurestore.py @@ -0,0 +1,248 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import encryption_spec as gca_encryption_spec +import google.protobuf.timestamp_pb2 as timestamp_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "Featurestore", + }, +) + + +class Featurestore(proto.Message): + r"""Vertex AI Feature Store provides a centralized repository for + organizing, storing, and serving ML features. The Featurestore + is a top-level container for your features and their values. + + Attributes: + name (str): + Output only. Name of the Featurestore. Format: + ``projects/{project}/locations/{location}/featurestores/{featurestore}`` + create_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when this Featurestore + was created. + update_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when this Featurestore + was last updated. + etag (str): + Optional. Used to perform consistent + read-modify-write updates. If not set, a blind + "overwrite" update happens. + labels (MutableMapping[str, str]): + Optional. The labels with user-defined + metadata to organize your Featurestore. + + Label keys and values can be no longer than 64 + characters (Unicode codepoints), can only + contain lowercase letters, numeric characters, + underscores and dashes. International characters + are allowed. + + See https://goo.gl/xmQnxf for more information + on and examples of labels. No more than 64 user + labels can be associated with one + Featurestore(System labels are excluded)." + System reserved label keys are prefixed with + "aiplatform.googleapis.com/" and are immutable. + online_serving_config (google.cloud.aiplatform_v1beta1.types.Featurestore.OnlineServingConfig): + Optional. Config for online storage resources. The field + should not co-exist with the field of + ``OnlineStoreReplicationConfig``. If both of it and + OnlineStoreReplicationConfig are unset, the feature store + will not have an online store and cannot be used for online + serving. + state (google.cloud.aiplatform_v1beta1.types.Featurestore.State): + Output only. State of the featurestore. + online_storage_ttl_days (int): + Optional. TTL in days for feature values that will be stored + in online serving storage. The Feature Store online storage + periodically removes obsolete feature values older than + ``online_storage_ttl_days`` since the feature generation + time. Note that ``online_storage_ttl_days`` should be less + than or equal to ``offline_storage_ttl_days`` for each + EntityType under a featurestore. If not set, default to 4000 + days + encryption_spec (google.cloud.aiplatform_v1beta1.types.EncryptionSpec): + Optional. Customer-managed encryption key + spec for data storage. If set, both of the + online and offline data storage will be secured + by this key. + satisfies_pzs (bool): + Output only. Reserved for future use. + satisfies_pzi (bool): + Output only. Reserved for future use. + """ + + class State(proto.Enum): + r"""Possible states a featurestore can have. + + Values: + STATE_UNSPECIFIED (0): + Default value. This value is unused. + STABLE (1): + State when the featurestore configuration is + not being updated and the fields reflect the + current configuration of the featurestore. The + featurestore is usable in this state. + UPDATING (2): + The state of the featurestore configuration when it is being + updated. During an update, the fields reflect either the + original configuration or the updated configuration of the + featurestore. For example, + ``online_serving_config.fixed_node_count`` can take minutes + to update. While the update is in progress, the featurestore + is in the UPDATING state, and the value of + ``fixed_node_count`` can be the original value or the + updated value, depending on the progress of the operation. + Until the update completes, the actual number of nodes can + still be the original value of ``fixed_node_count``. The + featurestore is still usable in this state. + """ + + STATE_UNSPECIFIED = 0 + STABLE = 1 + UPDATING = 2 + + class OnlineServingConfig(proto.Message): + r"""OnlineServingConfig specifies the details for provisioning + online serving resources. + + Attributes: + fixed_node_count (int): + The number of nodes for the online store. The + number of nodes doesn't scale automatically, but + you can manually update the number of nodes. If + set to 0, the featurestore will not have an + online store and cannot be used for online + serving. + scaling (google.cloud.aiplatform_v1beta1.types.Featurestore.OnlineServingConfig.Scaling): + Online serving scaling configuration. Only one of + ``fixed_node_count`` and ``scaling`` can be set. Setting one + will reset the other. + """ + + class Scaling(proto.Message): + r"""Online serving scaling configuration. If min_node_count and + max_node_count are set to the same value, the cluster will be + configured with the fixed number of node (no auto-scaling). + + Attributes: + min_node_count (int): + Required. The minimum number of nodes to + scale down to. Must be greater than or equal to + 1. + max_node_count (int): + The maximum number of nodes to scale up to. Must be greater + than min_node_count, and less than or equal to 10 times of + 'min_node_count'. + cpu_utilization_target (int): + Optional. The cpu utilization that the + Autoscaler should be trying to achieve. This + number is on a scale from 0 (no utilization) to + 100 (total utilization), and is limited between + 10 and 80. When a cluster's CPU utilization + exceeds the target that you have set, Bigtable + immediately adds nodes to the cluster. When CPU + utilization is substantially lower than the + target, Bigtable removes nodes. If not set or + set to 0, default to 50. + """ + + min_node_count: int = proto.Field( + proto.INT32, + number=1, + ) + max_node_count: int = proto.Field( + proto.INT32, + number=2, + ) + cpu_utilization_target: int = proto.Field( + proto.INT32, + number=3, + ) + + fixed_node_count: int = proto.Field( + proto.INT32, + number=2, + ) + scaling: "Featurestore.OnlineServingConfig.Scaling" = proto.Field( + proto.MESSAGE, + number=4, + message="Featurestore.OnlineServingConfig.Scaling", + ) + + name: str = proto.Field( + proto.STRING, + number=1, + ) + create_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=3, + message=timestamp_pb2.Timestamp, + ) + update_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=4, + message=timestamp_pb2.Timestamp, + ) + etag: str = proto.Field( + proto.STRING, + number=5, + ) + labels: MutableMapping[str, str] = proto.MapField( + proto.STRING, + proto.STRING, + number=6, + ) + online_serving_config: OnlineServingConfig = proto.Field( + proto.MESSAGE, + number=7, + message=OnlineServingConfig, + ) + state: State = proto.Field( + proto.ENUM, + number=8, + enum=State, + ) + online_storage_ttl_days: int = proto.Field( + proto.INT32, + number=13, + ) + encryption_spec: gca_encryption_spec.EncryptionSpec = proto.Field( + proto.MESSAGE, + number=10, + message=gca_encryption_spec.EncryptionSpec, + ) + satisfies_pzs: bool = proto.Field( + proto.BOOL, + number=14, + ) + satisfies_pzi: bool = proto.Field( + proto.BOOL, + number=15, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/featurestore_monitoring.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/featurestore_monitoring.py new file mode 100644 index 0000000000000000000000000000000000000000..2c4c6801fa2813ab1d9d74c078a0daff2a5c0d6e --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/featurestore_monitoring.py @@ -0,0 +1,256 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +import google.protobuf.duration_pb2 as duration_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "FeaturestoreMonitoringConfig", + }, +) + + +class FeaturestoreMonitoringConfig(proto.Message): + r"""Configuration of how features in Featurestore are monitored. + + Attributes: + snapshot_analysis (google.cloud.aiplatform_v1beta1.types.FeaturestoreMonitoringConfig.SnapshotAnalysis): + The config for Snapshot Analysis Based + Feature Monitoring. + import_features_analysis (google.cloud.aiplatform_v1beta1.types.FeaturestoreMonitoringConfig.ImportFeaturesAnalysis): + The config for ImportFeatures Analysis Based + Feature Monitoring. + numerical_threshold_config (google.cloud.aiplatform_v1beta1.types.FeaturestoreMonitoringConfig.ThresholdConfig): + Threshold for numerical features of anomaly detection. This + is shared by all objectives of Featurestore Monitoring for + numerical features (i.e. Features with type + ([Feature.ValueType][google.cloud.aiplatform.v1beta1.Feature.ValueType]) + DOUBLE or INT64). + categorical_threshold_config (google.cloud.aiplatform_v1beta1.types.FeaturestoreMonitoringConfig.ThresholdConfig): + Threshold for categorical features of anomaly detection. + This is shared by all types of Featurestore Monitoring for + categorical features (i.e. Features with type + ([Feature.ValueType][google.cloud.aiplatform.v1beta1.Feature.ValueType]) + BOOL or STRING). + """ + + class SnapshotAnalysis(proto.Message): + r"""Configuration of the Featurestore's Snapshot Analysis Based + Monitoring. This type of analysis generates statistics for each + Feature based on a snapshot of the latest feature value of each + entities every monitoring_interval. + + Attributes: + disabled (bool): + The monitoring schedule for snapshot analysis. For + EntityType-level config: unset / disabled = true indicates + disabled by default for Features under it; otherwise by + default enable snapshot analysis monitoring with + monitoring_interval for Features under it. Feature-level + config: disabled = true indicates disabled regardless of the + EntityType-level config; unset monitoring_interval indicates + going with EntityType-level config; otherwise run snapshot + analysis monitoring with monitoring_interval regardless of + the EntityType-level config. Explicitly Disable the snapshot + analysis based monitoring. + monitoring_interval (google.protobuf.duration_pb2.Duration): + Configuration of the snapshot analysis based monitoring + pipeline running interval. The value is rolled up to full + day. If both + [monitoring_interval_days][google.cloud.aiplatform.v1beta1.FeaturestoreMonitoringConfig.SnapshotAnalysis.monitoring_interval_days] + and the deprecated ``monitoring_interval`` field are set + when creating/updating EntityTypes/Features, + [monitoring_interval_days][google.cloud.aiplatform.v1beta1.FeaturestoreMonitoringConfig.SnapshotAnalysis.monitoring_interval_days] + will be used. + monitoring_interval_days (int): + Configuration of the snapshot analysis based + monitoring pipeline running interval. The value + indicates number of days. + staleness_days (int): + Customized export features time window for + snapshot analysis. Unit is one day. Default + value is 3 weeks. Minimum value is 1 day. + Maximum value is 4000 days. + """ + + disabled: bool = proto.Field( + proto.BOOL, + number=1, + ) + monitoring_interval: duration_pb2.Duration = proto.Field( + proto.MESSAGE, + number=2, + message=duration_pb2.Duration, + ) + monitoring_interval_days: int = proto.Field( + proto.INT32, + number=3, + ) + staleness_days: int = proto.Field( + proto.INT32, + number=4, + ) + + class ImportFeaturesAnalysis(proto.Message): + r"""Configuration of the Featurestore's ImportFeature Analysis Based + Monitoring. This type of analysis generates statistics for values of + each Feature imported by every + [ImportFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreService.ImportFeatureValues] + operation. + + Attributes: + state (google.cloud.aiplatform_v1beta1.types.FeaturestoreMonitoringConfig.ImportFeaturesAnalysis.State): + Whether to enable / disable / inherite + default hebavior for import features analysis. + anomaly_detection_baseline (google.cloud.aiplatform_v1beta1.types.FeaturestoreMonitoringConfig.ImportFeaturesAnalysis.Baseline): + The baseline used to do anomaly detection for + the statistics generated by import features + analysis. + """ + + class State(proto.Enum): + r"""The state defines whether to enable ImportFeature analysis. + + Values: + STATE_UNSPECIFIED (0): + Should not be used. + DEFAULT (1): + The default behavior of whether to enable the + monitoring. EntityType-level config: disabled. + Feature-level config: inherited from the + configuration of EntityType this Feature belongs + to. + ENABLED (2): + Explicitly enables import features analysis. + EntityType-level config: by default enables + import features analysis for all Features under + it. Feature-level config: enables import + features analysis regardless of the + EntityType-level config. + DISABLED (3): + Explicitly disables import features analysis. + EntityType-level config: by default disables + import features analysis for all Features under + it. Feature-level config: disables import + features analysis regardless of the + EntityType-level config. + """ + + STATE_UNSPECIFIED = 0 + DEFAULT = 1 + ENABLED = 2 + DISABLED = 3 + + class Baseline(proto.Enum): + r"""Defines the baseline to do anomaly detection for feature values + imported by each + [ImportFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreService.ImportFeatureValues] + operation. + + Values: + BASELINE_UNSPECIFIED (0): + Should not be used. + LATEST_STATS (1): + Choose the later one statistics generated by + either most recent snapshot analysis or previous + import features analysis. If non of them exists, + skip anomaly detection and only generate a + statistics. + MOST_RECENT_SNAPSHOT_STATS (2): + Use the statistics generated by the most + recent snapshot analysis if exists. + PREVIOUS_IMPORT_FEATURES_STATS (3): + Use the statistics generated by the previous + import features analysis if exists. + """ + + BASELINE_UNSPECIFIED = 0 + LATEST_STATS = 1 + MOST_RECENT_SNAPSHOT_STATS = 2 + PREVIOUS_IMPORT_FEATURES_STATS = 3 + + state: "FeaturestoreMonitoringConfig.ImportFeaturesAnalysis.State" = ( + proto.Field( + proto.ENUM, + number=1, + enum="FeaturestoreMonitoringConfig.ImportFeaturesAnalysis.State", + ) + ) + anomaly_detection_baseline: ( + "FeaturestoreMonitoringConfig.ImportFeaturesAnalysis.Baseline" + ) = proto.Field( + proto.ENUM, + number=2, + enum="FeaturestoreMonitoringConfig.ImportFeaturesAnalysis.Baseline", + ) + + class ThresholdConfig(proto.Message): + r"""The config for Featurestore Monitoring threshold. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + value (float): + Specify a threshold value that can trigger + the alert. + 1. For categorical feature, the distribution + distance is calculated by L-inifinity norm. + 2. For numerical feature, the distribution + distance is calculated by Jensen–Shannon + divergence. Each feature must have a + non-zero threshold if they need to be + monitored. Otherwise no alert will be + triggered for that feature. + + This field is a member of `oneof`_ ``threshold``. + """ + + value: float = proto.Field( + proto.DOUBLE, + number=1, + oneof="threshold", + ) + + snapshot_analysis: SnapshotAnalysis = proto.Field( + proto.MESSAGE, + number=1, + message=SnapshotAnalysis, + ) + import_features_analysis: ImportFeaturesAnalysis = proto.Field( + proto.MESSAGE, + number=2, + message=ImportFeaturesAnalysis, + ) + numerical_threshold_config: ThresholdConfig = proto.Field( + proto.MESSAGE, + number=3, + message=ThresholdConfig, + ) + categorical_threshold_config: ThresholdConfig = proto.Field( + proto.MESSAGE, + number=4, + message=ThresholdConfig, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/gen_ai_cache_service.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/gen_ai_cache_service.py new file mode 100644 index 0000000000000000000000000000000000000000..b9bf309391dd2b3993fe306075fc0a0f59202c3f --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/gen_ai_cache_service.py @@ -0,0 +1,185 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import cached_content as gca_cached_content +import google.protobuf.field_mask_pb2 as field_mask_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "CreateCachedContentRequest", + "GetCachedContentRequest", + "UpdateCachedContentRequest", + "DeleteCachedContentRequest", + "ListCachedContentsRequest", + "ListCachedContentsResponse", + }, +) + + +class CreateCachedContentRequest(proto.Message): + r"""Request message for + [GenAiCacheService.CreateCachedContent][google.cloud.aiplatform.v1beta1.GenAiCacheService.CreateCachedContent]. + + Attributes: + parent (str): + Required. The parent resource where the + cached content will be created + cached_content (google.cloud.aiplatform_v1beta1.types.CachedContent): + Required. The cached content to create + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + cached_content: gca_cached_content.CachedContent = proto.Field( + proto.MESSAGE, + number=2, + message=gca_cached_content.CachedContent, + ) + + +class GetCachedContentRequest(proto.Message): + r"""Request message for + [GenAiCacheService.GetCachedContent][google.cloud.aiplatform.v1beta1.GenAiCacheService.GetCachedContent]. + + Attributes: + name (str): + Required. The resource name referring to the + cached content + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class UpdateCachedContentRequest(proto.Message): + r"""Request message for + [GenAiCacheService.UpdateCachedContent][google.cloud.aiplatform.v1beta1.GenAiCacheService.UpdateCachedContent]. + Only expire_time or ttl can be updated. + + Attributes: + cached_content (google.cloud.aiplatform_v1beta1.types.CachedContent): + Required. The cached content to update + update_mask (google.protobuf.field_mask_pb2.FieldMask): + Required. The list of fields to update. + """ + + cached_content: gca_cached_content.CachedContent = proto.Field( + proto.MESSAGE, + number=1, + message=gca_cached_content.CachedContent, + ) + update_mask: field_mask_pb2.FieldMask = proto.Field( + proto.MESSAGE, + number=2, + message=field_mask_pb2.FieldMask, + ) + + +class DeleteCachedContentRequest(proto.Message): + r"""Request message for + [GenAiCacheService.DeleteCachedContent][google.cloud.aiplatform.v1beta1.GenAiCacheService.DeleteCachedContent]. + + Attributes: + name (str): + Required. The resource name referring to the + cached content + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class ListCachedContentsRequest(proto.Message): + r"""Request to list CachedContents. + + Attributes: + parent (str): + Required. The parent, which owns this + collection of cached contents. + page_size (int): + Optional. The maximum number of cached + contents to return. The service may return fewer + than this value. If unspecified, some default + (under maximum) number of items will be + returned. The maximum value is 1000; values + above 1000 will be coerced to 1000. + page_token (str): + Optional. A page token, received from a previous + ``ListCachedContents`` call. Provide this to retrieve the + subsequent page. + + When paginating, all other parameters provided to + ``ListCachedContents`` must match the call that provided the + page token. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + page_size: int = proto.Field( + proto.INT32, + number=2, + ) + page_token: str = proto.Field( + proto.STRING, + number=3, + ) + + +class ListCachedContentsResponse(proto.Message): + r"""Response with a list of CachedContents. + + Attributes: + cached_contents (MutableSequence[google.cloud.aiplatform_v1beta1.types.CachedContent]): + List of cached contents. + next_page_token (str): + A token, which can be sent as ``page_token`` to retrieve the + next page. If this field is omitted, there are no subsequent + pages. + """ + + @property + def raw_page(self): + return self + + cached_contents: MutableSequence[gca_cached_content.CachedContent] = ( + proto.RepeatedField( + proto.MESSAGE, + number=1, + message=gca_cached_content.CachedContent, + ) + ) + next_page_token: str = proto.Field( + proto.STRING, + number=2, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/io.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/io.py new file mode 100644 index 0000000000000000000000000000000000000000..0274af9930810610c338e61d2f95d19751c45a4c --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/io.py @@ -0,0 +1,554 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import api_auth +import google.protobuf.timestamp_pb2 as timestamp_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "AvroSource", + "CsvSource", + "GcsSource", + "GcsDestination", + "BigQuerySource", + "BigQueryDestination", + "VertexMultimodalDatasetSource", + "VertexMultimodalDatasetDestination", + "CsvDestination", + "TFRecordDestination", + "ContainerRegistryDestination", + "GoogleDriveSource", + "DirectUploadSource", + "SlackSource", + "JiraSource", + "SharePointSources", + }, +) + + +class AvroSource(proto.Message): + r"""The storage details for Avro input content. + + Attributes: + gcs_source (google.cloud.aiplatform_v1beta1.types.GcsSource): + Required. Google Cloud Storage location. + """ + + gcs_source: "GcsSource" = proto.Field( + proto.MESSAGE, + number=1, + message="GcsSource", + ) + + +class CsvSource(proto.Message): + r"""The storage details for CSV input content. + + Attributes: + gcs_source (google.cloud.aiplatform_v1beta1.types.GcsSource): + Required. Google Cloud Storage location. + """ + + gcs_source: "GcsSource" = proto.Field( + proto.MESSAGE, + number=1, + message="GcsSource", + ) + + +class GcsSource(proto.Message): + r"""The Google Cloud Storage location for the input content. + + Attributes: + uris (MutableSequence[str]): + Required. Google Cloud Storage URI(-s) to the + input file(s). May contain wildcards. For more + information on wildcards, see + https://cloud.google.com/storage/docs/wildcards. + """ + + uris: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=1, + ) + + +class GcsDestination(proto.Message): + r"""The Google Cloud Storage location where the output is to be + written to. + + Attributes: + output_uri_prefix (str): + Required. Google Cloud Storage URI to output + directory. If the uri doesn't end with + '/', a '/' will be automatically appended. The + directory is created if it doesn't exist. + """ + + output_uri_prefix: str = proto.Field( + proto.STRING, + number=1, + ) + + +class BigQuerySource(proto.Message): + r"""The BigQuery location for the input content. + + Attributes: + input_uri (str): + Required. BigQuery URI to a table, up to 2000 characters + long. Accepted forms: + + - BigQuery path. For example: + ``bq://projectId.bqDatasetId.bqTableId``. + """ + + input_uri: str = proto.Field( + proto.STRING, + number=1, + ) + + +class BigQueryDestination(proto.Message): + r"""The BigQuery location for the output content. + + Attributes: + output_uri (str): + Required. BigQuery URI to a project or table, up to 2000 + characters long. + + When only the project is specified, the Dataset and Table is + created. When the full table reference is specified, the + Dataset must exist and table must not exist. + + Accepted forms: + + - BigQuery path. For example: ``bq://projectId`` or + ``bq://projectId.bqDatasetId`` or + ``bq://projectId.bqDatasetId.bqTableId``. + """ + + output_uri: str = proto.Field( + proto.STRING, + number=1, + ) + + +class VertexMultimodalDatasetSource(proto.Message): + r"""The Vertex Multimodal Dataset for the input content. + + Attributes: + dataset_name (str): + Required. The resource name of the Vertex Dataset. Format: + ``projects/{project}/locations/{location}/datasets/{dataset}`` + """ + + dataset_name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class VertexMultimodalDatasetDestination(proto.Message): + r"""The details for a Vertex Multimodal Dataset output. + + Attributes: + bigquery_destination (google.cloud.aiplatform_v1beta1.types.BigQueryDestination): + Optional. The destination of the underlying + BigQuery table that will be created for the + output Multimodal Dataset. If not specified, the + BigQuery table will be created in a default + BigQuery dataset. + display_name (str): + Optional. Display name of the output dataset. + """ + + bigquery_destination: "BigQueryDestination" = proto.Field( + proto.MESSAGE, + number=1, + message="BigQueryDestination", + ) + display_name: str = proto.Field( + proto.STRING, + number=2, + ) + + +class CsvDestination(proto.Message): + r"""The storage details for CSV output content. + + Attributes: + gcs_destination (google.cloud.aiplatform_v1beta1.types.GcsDestination): + Required. Google Cloud Storage location. + """ + + gcs_destination: "GcsDestination" = proto.Field( + proto.MESSAGE, + number=1, + message="GcsDestination", + ) + + +class TFRecordDestination(proto.Message): + r"""The storage details for TFRecord output content. + + Attributes: + gcs_destination (google.cloud.aiplatform_v1beta1.types.GcsDestination): + Required. Google Cloud Storage location. + """ + + gcs_destination: "GcsDestination" = proto.Field( + proto.MESSAGE, + number=1, + message="GcsDestination", + ) + + +class ContainerRegistryDestination(proto.Message): + r"""The Container Registry location for the container image. + + Attributes: + output_uri (str): + Required. Container Registry URI of a container image. Only + Google Container Registry and Artifact Registry are + supported now. Accepted forms: + + - Google Container Registry path. For example: + ``gcr.io/projectId/imageName:tag``. + + - Artifact Registry path. For example: + ``us-central1-docker.pkg.dev/projectId/repoName/imageName:tag``. + + If a tag is not specified, "latest" will be used as the + default tag. + """ + + output_uri: str = proto.Field( + proto.STRING, + number=1, + ) + + +class GoogleDriveSource(proto.Message): + r"""The Google Drive location for the input content. + + Attributes: + resource_ids (MutableSequence[google.cloud.aiplatform_v1beta1.types.GoogleDriveSource.ResourceId]): + Required. Google Drive resource IDs. + """ + + class ResourceId(proto.Message): + r"""The type and ID of the Google Drive resource. + + Attributes: + resource_type (google.cloud.aiplatform_v1beta1.types.GoogleDriveSource.ResourceId.ResourceType): + Required. The type of the Google Drive + resource. + resource_id (str): + Required. The ID of the Google Drive + resource. + """ + + class ResourceType(proto.Enum): + r"""The type of the Google Drive resource. + + Values: + RESOURCE_TYPE_UNSPECIFIED (0): + Unspecified resource type. + RESOURCE_TYPE_FILE (1): + File resource type. + RESOURCE_TYPE_FOLDER (2): + Folder resource type. + """ + + RESOURCE_TYPE_UNSPECIFIED = 0 + RESOURCE_TYPE_FILE = 1 + RESOURCE_TYPE_FOLDER = 2 + + resource_type: "GoogleDriveSource.ResourceId.ResourceType" = proto.Field( + proto.ENUM, + number=1, + enum="GoogleDriveSource.ResourceId.ResourceType", + ) + resource_id: str = proto.Field( + proto.STRING, + number=2, + ) + + resource_ids: MutableSequence[ResourceId] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=ResourceId, + ) + + +class DirectUploadSource(proto.Message): + r"""The input content is encapsulated and uploaded in the + request. + + """ + + +class SlackSource(proto.Message): + r"""The Slack source for the ImportRagFilesRequest. + + Attributes: + channels (MutableSequence[google.cloud.aiplatform_v1beta1.types.SlackSource.SlackChannels]): + Required. The Slack channels. + """ + + class SlackChannels(proto.Message): + r"""SlackChannels contains the Slack channels and corresponding + access token. + + Attributes: + channels (MutableSequence[google.cloud.aiplatform_v1beta1.types.SlackSource.SlackChannels.SlackChannel]): + Required. The Slack channel IDs. + api_key_config (google.cloud.aiplatform_v1beta1.types.ApiAuth.ApiKeyConfig): + Required. The SecretManager secret version + resource name (e.g. + projects/{project}/secrets/{secret}/versions/{version}) + storing the Slack channel access token that has + access to the slack channel IDs. See: + https://api.slack.com/tutorials/tracks/getting-a-token. + """ + + class SlackChannel(proto.Message): + r"""SlackChannel contains the Slack channel ID and the time range + to import. + + Attributes: + channel_id (str): + Required. The Slack channel ID. + start_time (google.protobuf.timestamp_pb2.Timestamp): + Optional. The starting timestamp for messages + to import. + end_time (google.protobuf.timestamp_pb2.Timestamp): + Optional. The ending timestamp for messages + to import. + """ + + channel_id: str = proto.Field( + proto.STRING, + number=1, + ) + start_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=2, + message=timestamp_pb2.Timestamp, + ) + end_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=3, + message=timestamp_pb2.Timestamp, + ) + + channels: MutableSequence["SlackSource.SlackChannels.SlackChannel"] = ( + proto.RepeatedField( + proto.MESSAGE, + number=1, + message="SlackSource.SlackChannels.SlackChannel", + ) + ) + api_key_config: api_auth.ApiAuth.ApiKeyConfig = proto.Field( + proto.MESSAGE, + number=3, + message=api_auth.ApiAuth.ApiKeyConfig, + ) + + channels: MutableSequence[SlackChannels] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=SlackChannels, + ) + + +class JiraSource(proto.Message): + r"""The Jira source for the ImportRagFilesRequest. + + Attributes: + jira_queries (MutableSequence[google.cloud.aiplatform_v1beta1.types.JiraSource.JiraQueries]): + Required. The Jira queries. + """ + + class JiraQueries(proto.Message): + r"""JiraQueries contains the Jira queries and corresponding + authentication. + + Attributes: + projects (MutableSequence[str]): + A list of Jira projects to import in their + entirety. + custom_queries (MutableSequence[str]): + A list of custom Jira queries to import. For + information about JQL (Jira Query Language), see + https://support.atlassian.com/jira-service-management-cloud/docs/use-advanced-search-with-jira-query-language-jql/ + email (str): + Required. The Jira email address. + server_uri (str): + Required. The Jira server URI. + api_key_config (google.cloud.aiplatform_v1beta1.types.ApiAuth.ApiKeyConfig): + Required. The SecretManager secret version resource name + (e.g. + projects/{project}/secrets/{secret}/versions/{version}) + storing the Jira API key. See `Manage API tokens for your + Atlassian + account `__. + """ + + projects: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=3, + ) + custom_queries: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=4, + ) + email: str = proto.Field( + proto.STRING, + number=5, + ) + server_uri: str = proto.Field( + proto.STRING, + number=6, + ) + api_key_config: api_auth.ApiAuth.ApiKeyConfig = proto.Field( + proto.MESSAGE, + number=7, + message=api_auth.ApiAuth.ApiKeyConfig, + ) + + jira_queries: MutableSequence[JiraQueries] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=JiraQueries, + ) + + +class SharePointSources(proto.Message): + r"""The SharePointSources to pass to ImportRagFiles. + + Attributes: + share_point_sources (MutableSequence[google.cloud.aiplatform_v1beta1.types.SharePointSources.SharePointSource]): + The SharePoint sources. + """ + + class SharePointSource(proto.Message): + r"""An individual SharePointSource. + + This message has `oneof`_ fields (mutually exclusive fields). + For each oneof, at most one member field can be set at the same time. + Setting any member of the oneof automatically clears all other + members. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + sharepoint_folder_path (str): + The path of the SharePoint folder to download + from. + + This field is a member of `oneof`_ ``folder_source``. + sharepoint_folder_id (str): + The ID of the SharePoint folder to download + from. + + This field is a member of `oneof`_ ``folder_source``. + drive_name (str): + The name of the drive to download from. + + This field is a member of `oneof`_ ``drive_source``. + drive_id (str): + The ID of the drive to download from. + + This field is a member of `oneof`_ ``drive_source``. + client_id (str): + The Application ID for the app registered in + Microsoft Azure Portal. The application must + also be configured with MS Graph permissions + "Files.ReadAll", "Sites.ReadAll" and + BrowserSiteLists.Read.All. + client_secret (google.cloud.aiplatform_v1beta1.types.ApiAuth.ApiKeyConfig): + The application secret for the app registered + in Azure. + tenant_id (str): + Unique identifier of the Azure Active + Directory Instance. + sharepoint_site_name (str): + The name of the SharePoint site to download + from. This can be the site name or the site id. + file_id (str): + Output only. The SharePoint file id. Output + only. + """ + + sharepoint_folder_path: str = proto.Field( + proto.STRING, + number=5, + oneof="folder_source", + ) + sharepoint_folder_id: str = proto.Field( + proto.STRING, + number=6, + oneof="folder_source", + ) + drive_name: str = proto.Field( + proto.STRING, + number=7, + oneof="drive_source", + ) + drive_id: str = proto.Field( + proto.STRING, + number=8, + oneof="drive_source", + ) + client_id: str = proto.Field( + proto.STRING, + number=1, + ) + client_secret: api_auth.ApiAuth.ApiKeyConfig = proto.Field( + proto.MESSAGE, + number=2, + message=api_auth.ApiAuth.ApiKeyConfig, + ) + tenant_id: str = proto.Field( + proto.STRING, + number=3, + ) + sharepoint_site_name: str = proto.Field( + proto.STRING, + number=4, + ) + file_id: str = proto.Field( + proto.STRING, + number=9, + ) + + share_point_sources: MutableSequence[SharePointSource] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=SharePointSource, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/match_service.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/match_service.py new file mode 100644 index 0000000000000000000000000000000000000000..841054cda61fd4a6e435a79380c8650af2e12672 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/match_service.py @@ -0,0 +1,285 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import index + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "FindNeighborsRequest", + "FindNeighborsResponse", + "ReadIndexDatapointsRequest", + "ReadIndexDatapointsResponse", + }, +) + + +class FindNeighborsRequest(proto.Message): + r"""The request message for + [MatchService.FindNeighbors][google.cloud.aiplatform.v1beta1.MatchService.FindNeighbors]. + + Attributes: + index_endpoint (str): + Required. The name of the index endpoint. Format: + ``projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`` + deployed_index_id (str): + The ID of the DeployedIndex that will serve the request. + This request is sent to a specific IndexEndpoint, as per the + IndexEndpoint.network. That IndexEndpoint also has + IndexEndpoint.deployed_indexes, and each such index has a + DeployedIndex.id field. The value of the field below must + equal one of the DeployedIndex.id fields of the + IndexEndpoint that is being called for this request. + queries (MutableSequence[google.cloud.aiplatform_v1beta1.types.FindNeighborsRequest.Query]): + The list of queries. + return_full_datapoint (bool): + If set to true, the full datapoints + (including all vector values and restricts) of + the nearest neighbors are returned. Note that + returning full datapoint will significantly + increase the latency and cost of the query. + """ + + class Query(proto.Message): + r"""A query to find a number of the nearest neighbors (most + similar vectors) of a vector. + + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + rrf (google.cloud.aiplatform_v1beta1.types.FindNeighborsRequest.Query.RRF): + Optional. Represents RRF algorithm that + combines search results. + + This field is a member of `oneof`_ ``ranking``. + datapoint (google.cloud.aiplatform_v1beta1.types.IndexDatapoint): + Required. The datapoint/vector whose nearest + neighbors should be searched for. + neighbor_count (int): + The number of nearest neighbors to be + retrieved from database for each query. If not + set, will use the default from the service + configuration + (https://cloud.google.com/vertex-ai/docs/matching-engine/configuring-indexes#nearest-neighbor-search-config). + per_crowding_attribute_neighbor_count (int): + Crowding is a constraint on a neighbor list produced by + nearest neighbor search requiring that no more than some + value k' of the k neighbors returned have the same value of + crowding_attribute. It's used for improving result + diversity. This field is the maximum number of matches with + the same crowding tag. + approximate_neighbor_count (int): + The number of neighbors to find via + approximate search before exact reordering is + performed. If not set, the default value from + scam config is used; if set, this value must be + > 0. + fraction_leaf_nodes_to_search_override (float): + The fraction of the number of leaves to search, set at query + time allows user to tune search performance. This value + increase result in both search accuracy and latency + increase. The value should be between 0.0 and 1.0. If not + set or set to 0.0, query uses the default value specified in + NearestNeighborSearchConfig.TreeAHConfig.fraction_leaf_nodes_to_search. + """ + + class RRF(proto.Message): + r"""Parameters for RRF algorithm that combines search results. + + Attributes: + alpha (float): + Required. Users can provide an alpha value to + give more weight to dense vs sparse results. For + example, if the alpha is 0, we only return + sparse and if the alpha is 1, we only return + dense. + """ + + alpha: float = proto.Field( + proto.FLOAT, + number=1, + ) + + rrf: "FindNeighborsRequest.Query.RRF" = proto.Field( + proto.MESSAGE, + number=6, + oneof="ranking", + message="FindNeighborsRequest.Query.RRF", + ) + datapoint: index.IndexDatapoint = proto.Field( + proto.MESSAGE, + number=1, + message=index.IndexDatapoint, + ) + neighbor_count: int = proto.Field( + proto.INT32, + number=2, + ) + per_crowding_attribute_neighbor_count: int = proto.Field( + proto.INT32, + number=3, + ) + approximate_neighbor_count: int = proto.Field( + proto.INT32, + number=4, + ) + fraction_leaf_nodes_to_search_override: float = proto.Field( + proto.DOUBLE, + number=5, + ) + + index_endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + deployed_index_id: str = proto.Field( + proto.STRING, + number=2, + ) + queries: MutableSequence[Query] = proto.RepeatedField( + proto.MESSAGE, + number=3, + message=Query, + ) + return_full_datapoint: bool = proto.Field( + proto.BOOL, + number=4, + ) + + +class FindNeighborsResponse(proto.Message): + r"""The response message for + [MatchService.FindNeighbors][google.cloud.aiplatform.v1beta1.MatchService.FindNeighbors]. + + Attributes: + nearest_neighbors (MutableSequence[google.cloud.aiplatform_v1beta1.types.FindNeighborsResponse.NearestNeighbors]): + The nearest neighbors of the query + datapoints. + """ + + class Neighbor(proto.Message): + r"""A neighbor of the query vector. + + Attributes: + datapoint (google.cloud.aiplatform_v1beta1.types.IndexDatapoint): + The datapoint of the neighbor. Note that full datapoints are + returned only when "return_full_datapoint" is set to true. + Otherwise, only the "datapoint_id" and "crowding_tag" fields + are populated. + distance (float): + The distance between the neighbor and the + dense embedding query. + sparse_distance (float): + The distance between the neighbor and the query + sparse_embedding. + """ + + datapoint: index.IndexDatapoint = proto.Field( + proto.MESSAGE, + number=1, + message=index.IndexDatapoint, + ) + distance: float = proto.Field( + proto.DOUBLE, + number=2, + ) + sparse_distance: float = proto.Field( + proto.DOUBLE, + number=3, + ) + + class NearestNeighbors(proto.Message): + r"""Nearest neighbors for one query. + + Attributes: + id (str): + The ID of the query datapoint. + neighbors (MutableSequence[google.cloud.aiplatform_v1beta1.types.FindNeighborsResponse.Neighbor]): + All its neighbors. + """ + + id: str = proto.Field( + proto.STRING, + number=1, + ) + neighbors: MutableSequence["FindNeighborsResponse.Neighbor"] = ( + proto.RepeatedField( + proto.MESSAGE, + number=2, + message="FindNeighborsResponse.Neighbor", + ) + ) + + nearest_neighbors: MutableSequence[NearestNeighbors] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=NearestNeighbors, + ) + + +class ReadIndexDatapointsRequest(proto.Message): + r"""The request message for + [MatchService.ReadIndexDatapoints][google.cloud.aiplatform.v1beta1.MatchService.ReadIndexDatapoints]. + + Attributes: + index_endpoint (str): + Required. The name of the index endpoint. Format: + ``projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`` + deployed_index_id (str): + The ID of the DeployedIndex that will serve + the request. + ids (MutableSequence[str]): + IDs of the datapoints to be searched for. + """ + + index_endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + deployed_index_id: str = proto.Field( + proto.STRING, + number=2, + ) + ids: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=3, + ) + + +class ReadIndexDatapointsResponse(proto.Message): + r"""The response message for + [MatchService.ReadIndexDatapoints][google.cloud.aiplatform.v1beta1.MatchService.ReadIndexDatapoints]. + + Attributes: + datapoints (MutableSequence[google.cloud.aiplatform_v1beta1.types.IndexDatapoint]): + The result list of datapoints. + """ + + datapoints: MutableSequence[index.IndexDatapoint] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=index.IndexDatapoint, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/metadata_store.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/metadata_store.py new file mode 100644 index 0000000000000000000000000000000000000000..fcf0f5e5779bb04180b51abbc423943fbe4d09e2 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/metadata_store.py @@ -0,0 +1,125 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import encryption_spec as gca_encryption_spec +import google.protobuf.timestamp_pb2 as timestamp_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "MetadataStore", + }, +) + + +class MetadataStore(proto.Message): + r"""Instance of a metadata store. Contains a set of metadata that + can be queried. + + Attributes: + name (str): + Output only. The resource name of the + MetadataStore instance. + create_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when this + MetadataStore was created. + update_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when this + MetadataStore was last updated. + encryption_spec (google.cloud.aiplatform_v1beta1.types.EncryptionSpec): + Customer-managed encryption key spec for a + Metadata Store. If set, this Metadata Store and + all sub-resources of this Metadata Store are + secured using this key. + description (str): + Description of the MetadataStore. + state (google.cloud.aiplatform_v1beta1.types.MetadataStore.MetadataStoreState): + Output only. State information of the + MetadataStore. + dataplex_config (google.cloud.aiplatform_v1beta1.types.MetadataStore.DataplexConfig): + Optional. Dataplex integration settings. + """ + + class MetadataStoreState(proto.Message): + r"""Represents state information for a MetadataStore. + + Attributes: + disk_utilization_bytes (int): + The disk utilization of the MetadataStore in + bytes. + """ + + disk_utilization_bytes: int = proto.Field( + proto.INT64, + number=1, + ) + + class DataplexConfig(proto.Message): + r"""Represents Dataplex integration settings. + + Attributes: + enabled_pipelines_lineage (bool): + Optional. Whether or not Data Lineage + synchronization is enabled for Vertex Pipelines. + """ + + enabled_pipelines_lineage: bool = proto.Field( + proto.BOOL, + number=1, + ) + + name: str = proto.Field( + proto.STRING, + number=1, + ) + create_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=3, + message=timestamp_pb2.Timestamp, + ) + update_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=4, + message=timestamp_pb2.Timestamp, + ) + encryption_spec: gca_encryption_spec.EncryptionSpec = proto.Field( + proto.MESSAGE, + number=5, + message=gca_encryption_spec.EncryptionSpec, + ) + description: str = proto.Field( + proto.STRING, + number=6, + ) + state: MetadataStoreState = proto.Field( + proto.MESSAGE, + number=7, + message=MetadataStoreState, + ) + dataplex_config: DataplexConfig = proto.Field( + proto.MESSAGE, + number=8, + message=DataplexConfig, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/model_garden_service.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/model_garden_service.py new file mode 100644 index 0000000000000000000000000000000000000000..3389bdff1b32f6d735798d6ef8e5eaf719a9d6b2 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/model_garden_service.py @@ -0,0 +1,882 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import io +from google.cloud.aiplatform_v1beta1.types import machine_resources +from google.cloud.aiplatform_v1beta1.types import model as gca_model +from google.cloud.aiplatform_v1beta1.types import operation +from google.cloud.aiplatform_v1beta1.types import publisher_model as gca_publisher_model +from google.cloud.aiplatform_v1beta1.types import service_networking + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "PublisherModelView", + "GetPublisherModelRequest", + "ListPublisherModelsRequest", + "ListPublisherModelsResponse", + "DeployRequest", + "DeployPublisherModelRequest", + "DeployResponse", + "DeployPublisherModelResponse", + "DeployOperationMetadata", + "DeployPublisherModelOperationMetadata", + "ExportPublisherModelResponse", + "ExportPublisherModelOperationMetadata", + "ExportPublisherModelRequest", + "CheckPublisherModelEulaAcceptanceRequest", + "AcceptPublisherModelEulaRequest", + "PublisherModelEulaAcceptance", + }, +) + + +class PublisherModelView(proto.Enum): + r"""View enumeration of PublisherModel. + + Values: + PUBLISHER_MODEL_VIEW_UNSPECIFIED (0): + The default / unset value. The API will + default to the BASIC view. + PUBLISHER_MODEL_VIEW_BASIC (1): + Include basic metadata about the publisher + model, but not the full contents. + PUBLISHER_MODEL_VIEW_FULL (2): + Include everything. + PUBLISHER_MODEL_VERSION_VIEW_BASIC (3): + Include: VersionId, ModelVersionExternalName, + and SupportedActions. + """ + + PUBLISHER_MODEL_VIEW_UNSPECIFIED = 0 + PUBLISHER_MODEL_VIEW_BASIC = 1 + PUBLISHER_MODEL_VIEW_FULL = 2 + PUBLISHER_MODEL_VERSION_VIEW_BASIC = 3 + + +class GetPublisherModelRequest(proto.Message): + r"""Request message for + [ModelGardenService.GetPublisherModel][google.cloud.aiplatform.v1beta1.ModelGardenService.GetPublisherModel] + + Attributes: + name (str): + Required. The name of the PublisherModel resource. Format: + ``publishers/{publisher}/models/{publisher_model}`` + language_code (str): + Optional. The IETF BCP-47 language code + representing the language in which the publisher + model's text information should be written in. + view (google.cloud.aiplatform_v1beta1.types.PublisherModelView): + Optional. PublisherModel view specifying + which fields to read. + is_hugging_face_model (bool): + Optional. Boolean indicates whether the + requested model is a Hugging Face model. + hugging_face_token (str): + Optional. Token used to access Hugging Face + gated models. + include_equivalent_model_garden_model_deployment_configs (bool): + Optional. Whether to cnclude the deployment + configs from the equivalent Model Garden model + if the requested model is a Hugging Face model. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + language_code: str = proto.Field( + proto.STRING, + number=2, + ) + view: "PublisherModelView" = proto.Field( + proto.ENUM, + number=3, + enum="PublisherModelView", + ) + is_hugging_face_model: bool = proto.Field( + proto.BOOL, + number=5, + ) + hugging_face_token: str = proto.Field( + proto.STRING, + number=6, + ) + include_equivalent_model_garden_model_deployment_configs: bool = proto.Field( + proto.BOOL, + number=7, + ) + + +class ListPublisherModelsRequest(proto.Message): + r"""Request message for + [ModelGardenService.ListPublisherModels][google.cloud.aiplatform.v1beta1.ModelGardenService.ListPublisherModels]. + + Attributes: + parent (str): + Required. The name of the Publisher from which to list the + PublisherModels. Format: ``publishers/{publisher}`` + filter (str): + Optional. The standard list filter. + page_size (int): + Optional. The standard list page size. + page_token (str): + Optional. The standard list page token. Typically obtained + via + [ListPublisherModelsResponse.next_page_token][google.cloud.aiplatform.v1beta1.ListPublisherModelsResponse.next_page_token] + of the previous + [ModelGardenService.ListPublisherModels][google.cloud.aiplatform.v1beta1.ModelGardenService.ListPublisherModels] + call. + view (google.cloud.aiplatform_v1beta1.types.PublisherModelView): + Optional. PublisherModel view specifying + which fields to read. + order_by (str): + Optional. A comma-separated list of fields to + order by, sorted in ascending order. Use "desc" + after a field name for descending. + language_code (str): + Optional. The IETF BCP-47 language code + representing the language in which the publisher + models' text information should be written in. + If not set, by default English (en). + list_all_versions (bool): + Optional. List all publisher model versions + if the flag is set to true. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + filter: str = proto.Field( + proto.STRING, + number=2, + ) + page_size: int = proto.Field( + proto.INT32, + number=3, + ) + page_token: str = proto.Field( + proto.STRING, + number=4, + ) + view: "PublisherModelView" = proto.Field( + proto.ENUM, + number=5, + enum="PublisherModelView", + ) + order_by: str = proto.Field( + proto.STRING, + number=6, + ) + language_code: str = proto.Field( + proto.STRING, + number=7, + ) + list_all_versions: bool = proto.Field( + proto.BOOL, + number=8, + ) + + +class ListPublisherModelsResponse(proto.Message): + r"""Response message for + [ModelGardenService.ListPublisherModels][google.cloud.aiplatform.v1beta1.ModelGardenService.ListPublisherModels]. + + Attributes: + publisher_models (MutableSequence[google.cloud.aiplatform_v1beta1.types.PublisherModel]): + List of PublisherModels in the requested + page. + next_page_token (str): + A token to retrieve next page of results. Pass to + [ListPublisherModels.page_token][] to obtain that page. + """ + + @property + def raw_page(self): + return self + + publisher_models: MutableSequence[gca_publisher_model.PublisherModel] = ( + proto.RepeatedField( + proto.MESSAGE, + number=1, + message=gca_publisher_model.PublisherModel, + ) + ) + next_page_token: str = proto.Field( + proto.STRING, + number=2, + ) + + +class DeployRequest(proto.Message): + r"""Request message for + [ModelGardenService.Deploy][google.cloud.aiplatform.v1beta1.ModelGardenService.Deploy]. + + This message has `oneof`_ fields (mutually exclusive fields). + For each oneof, at most one member field can be set at the same time. + Setting any member of the oneof automatically clears all other + members. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + publisher_model_name (str): + The Model Garden model to deploy. Format: + ``publishers/{publisher}/models/{publisher_model}@{version_id}``, + or + ``publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}@001``. + + This field is a member of `oneof`_ ``artifacts``. + hugging_face_model_id (str): + The Hugging Face model to deploy. Format: Hugging Face model + ID like ``google/gemma-2-2b-it``. + + This field is a member of `oneof`_ ``artifacts``. + custom_model (google.cloud.aiplatform_v1beta1.types.DeployRequest.CustomModel): + The custom model to deploy from a Google + Cloud Storage URI. + + This field is a member of `oneof`_ ``artifacts``. + destination (str): + Required. The resource name of the Location to deploy the + model in. Format: + ``projects/{project}/locations/{location}`` + model_config (google.cloud.aiplatform_v1beta1.types.DeployRequest.ModelConfig): + Optional. The model config to use for the + deployment. If not specified, the default model + config will be used. + endpoint_config (google.cloud.aiplatform_v1beta1.types.DeployRequest.EndpointConfig): + Optional. The endpoint config to use for the + deployment. If not specified, the default + endpoint config will be used. + deploy_config (google.cloud.aiplatform_v1beta1.types.DeployRequest.DeployConfig): + Optional. The deploy config to use for the + deployment. If not specified, the default deploy + config will be used. + """ + + class CustomModel(proto.Message): + r"""The custom model to deploy from model weights in a Google + Cloud Storage URI or Model Registry model. + + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + gcs_uri (str): + Immutable. The Google Cloud Storage URI of + the custom model, storing weights and config + files (which can be used to infer the base + model). + + This field is a member of `oneof`_ ``model_source``. + """ + + gcs_uri: str = proto.Field( + proto.STRING, + number=2, + oneof="model_source", + ) + + class ModelConfig(proto.Message): + r"""The model config to use for the deployment. + + Attributes: + accept_eula (bool): + Optional. Whether the user accepts the End + User License Agreement (EULA) for the model. + hugging_face_access_token (str): + Optional. The Hugging Face read access token + used to access the model artifacts of gated + models. + hugging_face_cache_enabled (bool): + Optional. If true, the model will deploy with + a cached version instead of directly downloading + the model artifacts from Hugging Face. This is + suitable for VPC-SC users with limited internet + access. + model_display_name (str): + Optional. The user-specified display name of + the uploaded model. If not set, a default name + will be used. + container_spec (google.cloud.aiplatform_v1beta1.types.ModelContainerSpec): + Optional. The specification of the container + that is to be used when deploying. If not set, + the default container spec will be used. + model_user_id (str): + Optional. The ID to use for the uploaded Model, which will + become the final component of the model resource name. When + not provided, Vertex AI will generate a value for this ID. + When Model Registry model is provided, this field will be + ignored. + + This value may be up to 63 characters, and valid characters + are ``[a-z0-9_-]``. The first character cannot be a number + or hyphen. + """ + + accept_eula: bool = proto.Field( + proto.BOOL, + number=1, + ) + hugging_face_access_token: str = proto.Field( + proto.STRING, + number=2, + ) + hugging_face_cache_enabled: bool = proto.Field( + proto.BOOL, + number=3, + ) + model_display_name: str = proto.Field( + proto.STRING, + number=4, + ) + container_spec: gca_model.ModelContainerSpec = proto.Field( + proto.MESSAGE, + number=5, + message=gca_model.ModelContainerSpec, + ) + model_user_id: str = proto.Field( + proto.STRING, + number=6, + ) + + class EndpointConfig(proto.Message): + r"""The endpoint config to use for the deployment. + + Attributes: + endpoint_display_name (str): + Optional. The user-specified display name of + the endpoint. If not set, a default name will be + used. + dedicated_endpoint_enabled (bool): + Optional. Deprecated. Use dedicated_endpoint_disabled + instead. If true, the endpoint will be exposed through a + dedicated DNS [Endpoint.dedicated_endpoint_dns]. Your + request to the dedicated DNS will be isolated from other + users' traffic and will have better performance and + reliability. Note: Once you enabled dedicated endpoint, you + won't be able to send request to the shared DNS + {region}-aiplatform.googleapis.com. The limitations will be + removed soon. + dedicated_endpoint_disabled (bool): + Optional. By default, if dedicated endpoint is enabled and + private service connect config is not set, the endpoint will + be exposed through a dedicated DNS + [Endpoint.dedicated_endpoint_dns]. If private service + connect config is set, the endpoint will be exposed through + private service connect. Your request to the dedicated DNS + will be isolated from other users' traffic and will have + better performance and reliability. Note: Once you enabled + dedicated endpoint, you won't be able to send request to the + shared DNS {region}-aiplatform.googleapis.com. The + limitations will be removed soon. + + If this field is set to true, the dedicated endpoint will be + disabled and the deployed model will be exposed through the + shared DNS {region}-aiplatform.googleapis.com. + private_service_connect_config (google.cloud.aiplatform_v1beta1.types.PrivateServiceConnectConfig): + Optional. Configuration for private service + connect. If set, the endpoint will be exposed + through private service connect. + endpoint_user_id (str): + Optional. Immutable. The ID to use for endpoint, which will + become the final component of the endpoint resource name. If + not provided, Vertex AI will generate a value for this ID. + + If the first character is a letter, this value may be up to + 63 characters, and valid characters are ``[a-z0-9-]``. The + last character must be a letter or number. + + If the first character is a number, this value may be up to + 9 characters, and valid characters are ``[0-9]`` with no + leading zeros. + + When using HTTP/JSON, this field is populated based on a + query string argument, such as ``?endpoint_id=12345``. This + is the fallback for fields that are not included in either + the URI or the body. + """ + + endpoint_display_name: str = proto.Field( + proto.STRING, + number=1, + ) + dedicated_endpoint_enabled: bool = proto.Field( + proto.BOOL, + number=2, + ) + dedicated_endpoint_disabled: bool = proto.Field( + proto.BOOL, + number=4, + ) + private_service_connect_config: ( + service_networking.PrivateServiceConnectConfig + ) = proto.Field( + proto.MESSAGE, + number=5, + message=service_networking.PrivateServiceConnectConfig, + ) + endpoint_user_id: str = proto.Field( + proto.STRING, + number=3, + ) + + class DeployConfig(proto.Message): + r"""The deploy config to use for the deployment. + + Attributes: + dedicated_resources (google.cloud.aiplatform_v1beta1.types.DedicatedResources): + Optional. The dedicated resources to use for + the endpoint. If not set, the default resources + will be used. + fast_tryout_enabled (bool): + Optional. If true, enable the QMT fast tryout + feature for this model if possible. + system_labels (MutableMapping[str, str]): + Optional. System labels for Model Garden + deployments. These labels are managed by Google + and for tracking purposes only. + """ + + dedicated_resources: machine_resources.DedicatedResources = proto.Field( + proto.MESSAGE, + number=1, + message=machine_resources.DedicatedResources, + ) + fast_tryout_enabled: bool = proto.Field( + proto.BOOL, + number=2, + ) + system_labels: MutableMapping[str, str] = proto.MapField( + proto.STRING, + proto.STRING, + number=3, + ) + + publisher_model_name: str = proto.Field( + proto.STRING, + number=1, + oneof="artifacts", + ) + hugging_face_model_id: str = proto.Field( + proto.STRING, + number=2, + oneof="artifacts", + ) + custom_model: CustomModel = proto.Field( + proto.MESSAGE, + number=3, + oneof="artifacts", + message=CustomModel, + ) + destination: str = proto.Field( + proto.STRING, + number=4, + ) + model_config: ModelConfig = proto.Field( + proto.MESSAGE, + number=5, + message=ModelConfig, + ) + endpoint_config: EndpointConfig = proto.Field( + proto.MESSAGE, + number=6, + message=EndpointConfig, + ) + deploy_config: DeployConfig = proto.Field( + proto.MESSAGE, + number=7, + message=DeployConfig, + ) + + +class DeployPublisherModelRequest(proto.Message): + r"""Request message for + [ModelGardenService.DeployPublisherModel][google.cloud.aiplatform.v1beta1.ModelGardenService.DeployPublisherModel]. + + Attributes: + model (str): + Required. The model to deploy. Format: + + 1. ``publishers/{publisher}/models/{publisher_model}@{version_id}``, + or + ``publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}@001``. + 2. Hugging Face model ID like ``google/gemma-2-2b-it``. + 3. Custom model Google Cloud Storage URI like + ``gs://bucket``. + 4. Custom model zip file like ``https://example.com/a.zip``. + destination (str): + Required. The resource name of the Location to deploy the + model in. Format: + ``projects/{project}/locations/{location}`` + endpoint_display_name (str): + Optional. The user-specified display name of + the endpoint. If not set, a default name will be + used. + dedicated_resources (google.cloud.aiplatform_v1beta1.types.DedicatedResources): + Optional. The dedicated resources to use for + the endpoint. If not set, the default resources + will be used. + model_display_name (str): + Optional. The user-specified display name of + the uploaded model. If not set, a default name + will be used. + hugging_face_access_token (str): + Optional. The Hugging Face read access token + used to access the model artifacts of gated + models. + accept_eula (bool): + Optional. Whether the user accepts the End + User License Agreement (EULA) for the model. + """ + + model: str = proto.Field( + proto.STRING, + number=1, + ) + destination: str = proto.Field( + proto.STRING, + number=2, + ) + endpoint_display_name: str = proto.Field( + proto.STRING, + number=3, + ) + dedicated_resources: machine_resources.DedicatedResources = proto.Field( + proto.MESSAGE, + number=4, + message=machine_resources.DedicatedResources, + ) + model_display_name: str = proto.Field( + proto.STRING, + number=5, + ) + hugging_face_access_token: str = proto.Field( + proto.STRING, + number=6, + ) + accept_eula: bool = proto.Field( + proto.BOOL, + number=7, + ) + + +class DeployResponse(proto.Message): + r"""Response message for + [ModelGardenService.Deploy][google.cloud.aiplatform.v1beta1.ModelGardenService.Deploy]. + + Attributes: + publisher_model (str): + Output only. The name of the PublisherModel resource. + Format: + ``publishers/{publisher}/models/{publisher_model}@{version_id}``, + or + ``publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}@001`` + endpoint (str): + Output only. The name of the Endpoint created. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + model (str): + Output only. The name of the Model created. Format: + ``projects/{project}/locations/{location}/models/{model}`` + """ + + publisher_model: str = proto.Field( + proto.STRING, + number=1, + ) + endpoint: str = proto.Field( + proto.STRING, + number=2, + ) + model: str = proto.Field( + proto.STRING, + number=3, + ) + + +class DeployPublisherModelResponse(proto.Message): + r"""Response message for + [ModelGardenService.DeployPublisherModel][google.cloud.aiplatform.v1beta1.ModelGardenService.DeployPublisherModel]. + + Attributes: + publisher_model (str): + Output only. The name of the PublisherModel resource. + Format: + ``publishers/{publisher}/models/{publisher_model}@{version_id}``, + or + ``publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}@001`` + endpoint (str): + Output only. The name of the Endpoint created. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + model (str): + Output only. The name of the Model created. Format: + ``projects/{project}/locations/{location}/models/{model}`` + """ + + publisher_model: str = proto.Field( + proto.STRING, + number=1, + ) + endpoint: str = proto.Field( + proto.STRING, + number=2, + ) + model: str = proto.Field( + proto.STRING, + number=3, + ) + + +class DeployOperationMetadata(proto.Message): + r"""Runtime operation information for + [ModelGardenService.Deploy][google.cloud.aiplatform.v1beta1.ModelGardenService.Deploy]. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + The operation generic information. + publisher_model (str): + Output only. The name of the model resource. + destination (str): + Output only. The resource name of the Location to deploy the + model in. Format: + ``projects/{project}/locations/{location}`` + project_number (int): + Output only. The project number where the + deploy model request is sent. + model_id (str): + Output only. The model id to be used at query + time. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + publisher_model: str = proto.Field( + proto.STRING, + number=2, + ) + destination: str = proto.Field( + proto.STRING, + number=3, + ) + project_number: int = proto.Field( + proto.INT64, + number=4, + ) + model_id: str = proto.Field( + proto.STRING, + number=5, + ) + + +class DeployPublisherModelOperationMetadata(proto.Message): + r"""Runtime operation information for + [ModelGardenService.DeployPublisherModel][google.cloud.aiplatform.v1beta1.ModelGardenService.DeployPublisherModel]. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + The operation generic information. + publisher_model (str): + Output only. The name of the PublisherModel resource. + Format: + ``publishers/{publisher}/models/{publisher_model}@{version_id}``, + or + ``publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}@001`` + destination (str): + Output only. The resource name of the Location to deploy the + model in. Format: + ``projects/{project}/locations/{location}`` + project_number (int): + Output only. The project number where the + deploy model request is sent. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + publisher_model: str = proto.Field( + proto.STRING, + number=2, + ) + destination: str = proto.Field( + proto.STRING, + number=3, + ) + project_number: int = proto.Field( + proto.INT64, + number=4, + ) + + +class ExportPublisherModelResponse(proto.Message): + r"""Response message for + [ModelGardenService.ExportPublisherModel][google.cloud.aiplatform.v1beta1.ModelGardenService.ExportPublisherModel]. + + Attributes: + publisher_model (str): + The name of the PublisherModel resource. Format: + ``publishers/{publisher}/models/{publisher_model}@{version_id}`` + destination_uri (str): + The destination uri of the model weights. + """ + + publisher_model: str = proto.Field( + proto.STRING, + number=1, + ) + destination_uri: str = proto.Field( + proto.STRING, + number=2, + ) + + +class ExportPublisherModelOperationMetadata(proto.Message): + r"""Runtime operation information for + [ModelGardenService.ExportPublisherModel][google.cloud.aiplatform.v1beta1.ModelGardenService.ExportPublisherModel]. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + The operation generic information. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class ExportPublisherModelRequest(proto.Message): + r"""Request message for + [ModelGardenService.ExportPublisherModel][google.cloud.aiplatform.v1beta1.ModelGardenService.ExportPublisherModel]. + + Attributes: + name (str): + Required. The name of the PublisherModel resource. Format: + ``publishers/{publisher}/models/{publisher_model}@{version_id}``, + or + ``publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}@001`` + destination (google.cloud.aiplatform_v1beta1.types.GcsDestination): + Required. The target where we are exporting + the model weights to + parent (str): + Required. The Location to export the model weights from + Format: ``projects/{project}/locations/{location}`` + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + destination: io.GcsDestination = proto.Field( + proto.MESSAGE, + number=2, + message=io.GcsDestination, + ) + parent: str = proto.Field( + proto.STRING, + number=3, + ) + + +class CheckPublisherModelEulaAcceptanceRequest(proto.Message): + r"""Request message for [ModelGardenService.CheckPublisherModelEula][]. + + Attributes: + parent (str): + Required. The project requesting access for named model. The + format is ``projects/{project}``. + publisher_model (str): + Required. The name of the PublisherModel resource. Format: + ``publishers/{publisher}/models/{publisher_model}``, or + ``publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}`` + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + publisher_model: str = proto.Field( + proto.STRING, + number=2, + ) + + +class AcceptPublisherModelEulaRequest(proto.Message): + r"""Request message for + [ModelGardenService.AcceptPublisherModelEula][google.cloud.aiplatform.v1beta1.ModelGardenService.AcceptPublisherModelEula]. + + Attributes: + parent (str): + Required. The project requesting access for named model. The + format is ``projects/{project}``. + publisher_model (str): + Required. The name of the PublisherModel resource. Format: + ``publishers/{publisher}/models/{publisher_model}``, or + ``publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}`` + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + publisher_model: str = proto.Field( + proto.STRING, + number=2, + ) + + +class PublisherModelEulaAcceptance(proto.Message): + r"""Response message for + [ModelGardenService.UpdatePublisherModelEula][]. + + Attributes: + project_number (int): + The project number requesting access for + named model. + publisher_model (str): + The publisher model resource name. + publisher_model_eula_acked (bool): + The EULA content acceptance status. + """ + + project_number: int = proto.Field( + proto.INT64, + number=1, + ) + publisher_model: str = proto.Field( + proto.STRING, + number=2, + ) + publisher_model_eula_acked: bool = proto.Field( + proto.BOOL, + number=3, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/model_monitor.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/model_monitor.py new file mode 100644 index 0000000000000000000000000000000000000000..855ccfbb64623d7d20c6f9c3ec5624e3e8109ee8 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/model_monitor.py @@ -0,0 +1,320 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import encryption_spec as gca_encryption_spec +from google.cloud.aiplatform_v1beta1.types import explanation +from google.cloud.aiplatform_v1beta1.types import model_monitoring_spec +import google.protobuf.timestamp_pb2 as timestamp_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "ModelMonitor", + "ModelMonitoringSchema", + }, +) + + +class ModelMonitor(proto.Message): + r"""Vertex AI Model Monitoring Service serves as a central hub + for the analysis and visualization of data quality and + performance related to models. ModelMonitor stands as a top + level resource for overseeing your model monitoring tasks. + + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + tabular_objective (google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveSpec.TabularObjective): + Optional default tabular model monitoring + objective. + + This field is a member of `oneof`_ ``default_objective``. + name (str): + Immutable. Resource name of the ModelMonitor. Format: + ``projects/{project}/locations/{location}/modelMonitors/{model_monitor}``. + display_name (str): + The display name of the ModelMonitor. + The name can be up to 128 characters long and + can consist of any UTF-8. + model_monitoring_target (google.cloud.aiplatform_v1beta1.types.ModelMonitor.ModelMonitoringTarget): + The entity that is subject to analysis. + Currently only models in Vertex AI Model + Registry are supported. If you want to analyze + the model which is outside the Vertex AI, you + could register a model in Vertex AI Model + Registry using just a display name. + training_dataset (google.cloud.aiplatform_v1beta1.types.ModelMonitoringInput): + Optional training dataset used to train the + model. It can serve as a reference dataset to + identify changes in production. + notification_spec (google.cloud.aiplatform_v1beta1.types.ModelMonitoringNotificationSpec): + Optional default notification spec, it can be + overridden in the ModelMonitoringJob + notification spec. + output_spec (google.cloud.aiplatform_v1beta1.types.ModelMonitoringOutputSpec): + Optional default monitoring metrics/logs + export spec, it can be overridden in the + ModelMonitoringJob output spec. If not + specified, a default Google Cloud Storage bucket + will be created under your project. + explanation_spec (google.cloud.aiplatform_v1beta1.types.ExplanationSpec): + Optional model explanation spec. It is used + for feature attribution monitoring. + model_monitoring_schema (google.cloud.aiplatform_v1beta1.types.ModelMonitoringSchema): + Monitoring Schema is to specify the model's + features, prediction outputs and ground truth + properties. It is used to extract pertinent data + from the dataset and to process features based + on their properties. Make sure that the schema + aligns with your dataset, if it does not, we + will be unable to extract data from the dataset. + It is required for most models, but optional for + Vertex AI AutoML Tables unless the schem + information is not available. + encryption_spec (google.cloud.aiplatform_v1beta1.types.EncryptionSpec): + Customer-managed encryption key spec for a + ModelMonitor. If set, this ModelMonitor and all + sub-resources of this ModelMonitor will be + secured by this key. + create_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when this ModelMonitor + was created. + update_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when this ModelMonitor + was updated most recently. + satisfies_pzs (bool): + Output only. Reserved for future use. + satisfies_pzi (bool): + Output only. Reserved for future use. + """ + + class ModelMonitoringTarget(proto.Message): + r"""The monitoring target refers to the entity that is subject to + analysis. e.g. Vertex AI Model version. + + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + vertex_model (google.cloud.aiplatform_v1beta1.types.ModelMonitor.ModelMonitoringTarget.VertexModelSource): + Model in Vertex AI Model Registry. + + This field is a member of `oneof`_ ``source``. + """ + + class VertexModelSource(proto.Message): + r"""Model in Vertex AI Model Registry. + + Attributes: + model (str): + Model resource name. Format: + + projects/{project}/locations/{location}/models/{model}. + model_version_id (str): + Model version id. + """ + + model: str = proto.Field( + proto.STRING, + number=1, + ) + model_version_id: str = proto.Field( + proto.STRING, + number=2, + ) + + vertex_model: "ModelMonitor.ModelMonitoringTarget.VertexModelSource" = ( + proto.Field( + proto.MESSAGE, + number=1, + oneof="source", + message="ModelMonitor.ModelMonitoringTarget.VertexModelSource", + ) + ) + + tabular_objective: ( + model_monitoring_spec.ModelMonitoringObjectiveSpec.TabularObjective + ) = proto.Field( + proto.MESSAGE, + number=11, + oneof="default_objective", + message=model_monitoring_spec.ModelMonitoringObjectiveSpec.TabularObjective, + ) + name: str = proto.Field( + proto.STRING, + number=1, + ) + display_name: str = proto.Field( + proto.STRING, + number=2, + ) + model_monitoring_target: ModelMonitoringTarget = proto.Field( + proto.MESSAGE, + number=3, + message=ModelMonitoringTarget, + ) + training_dataset: model_monitoring_spec.ModelMonitoringInput = proto.Field( + proto.MESSAGE, + number=10, + message=model_monitoring_spec.ModelMonitoringInput, + ) + notification_spec: model_monitoring_spec.ModelMonitoringNotificationSpec = ( + proto.Field( + proto.MESSAGE, + number=12, + message=model_monitoring_spec.ModelMonitoringNotificationSpec, + ) + ) + output_spec: model_monitoring_spec.ModelMonitoringOutputSpec = proto.Field( + proto.MESSAGE, + number=13, + message=model_monitoring_spec.ModelMonitoringOutputSpec, + ) + explanation_spec: explanation.ExplanationSpec = proto.Field( + proto.MESSAGE, + number=16, + message=explanation.ExplanationSpec, + ) + model_monitoring_schema: "ModelMonitoringSchema" = proto.Field( + proto.MESSAGE, + number=9, + message="ModelMonitoringSchema", + ) + encryption_spec: gca_encryption_spec.EncryptionSpec = proto.Field( + proto.MESSAGE, + number=5, + message=gca_encryption_spec.EncryptionSpec, + ) + create_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=6, + message=timestamp_pb2.Timestamp, + ) + update_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=7, + message=timestamp_pb2.Timestamp, + ) + satisfies_pzs: bool = proto.Field( + proto.BOOL, + number=17, + ) + satisfies_pzi: bool = proto.Field( + proto.BOOL, + number=18, + ) + + +class ModelMonitoringSchema(proto.Message): + r"""The Model Monitoring Schema definition. + + Attributes: + feature_fields (MutableSequence[google.cloud.aiplatform_v1beta1.types.ModelMonitoringSchema.FieldSchema]): + Feature names of the model. Vertex AI will try to match the + features from your dataset as follows: + + - For 'csv' files, the header names are required, and we + will extract the corresponding feature values when the + header names align with the feature names. + - For 'jsonl' files, we will extract the corresponding + feature values if the key names match the feature names. + Note: Nested features are not supported, so please ensure + your features are flattened. Ensure the feature values are + scalar or an array of scalars. + - For 'bigquery' dataset, we will extract the corresponding + feature values if the column names match the feature + names. Note: The column type can be a scalar or an array + of scalars. STRUCT or JSON types are not supported. You + may use SQL queries to select or aggregate the relevant + features from your original table. However, ensure that + the 'schema' of the query results meets our requirements. + - For the Vertex AI Endpoint Request Response Logging table + or Vertex AI Batch Prediction Job results. If the + [instance_type][google.cloud.aiplatform.v1beta1.ModelMonitoringSchema.instance_type] + is an array, ensure that the sequence in + [feature_fields][google.cloud.aiplatform.v1beta1.ModelMonitoringSchema.feature_fields] + matches the order of features in the prediction instance. + We will match the feature with the array in the order + specified in [feature_fields]. + prediction_fields (MutableSequence[google.cloud.aiplatform_v1beta1.types.ModelMonitoringSchema.FieldSchema]): + Prediction output names of the model. The requirements are + the same as the + [feature_fields][google.cloud.aiplatform.v1beta1.ModelMonitoringSchema.feature_fields]. + For AutoML Tables, the prediction output name presented in + schema will be: ``predicted_{target_column}``, the + ``target_column`` is the one you specified when you train + the model. For Prediction output drift analysis: + + - AutoML Classification, the distribution of the argmax + label will be analyzed. + - AutoML Regression, the distribution of the value will be + analyzed. + ground_truth_fields (MutableSequence[google.cloud.aiplatform_v1beta1.types.ModelMonitoringSchema.FieldSchema]): + Target /ground truth names of the model. + """ + + class FieldSchema(proto.Message): + r"""Schema field definition. + + Attributes: + name (str): + Field name. + data_type (str): + Supported data types are: ``float`` ``integer`` ``boolean`` + ``string`` ``categorical`` + repeated (bool): + Describes if the schema field is an array of + given data type. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + data_type: str = proto.Field( + proto.STRING, + number=2, + ) + repeated: bool = proto.Field( + proto.BOOL, + number=3, + ) + + feature_fields: MutableSequence[FieldSchema] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=FieldSchema, + ) + prediction_fields: MutableSequence[FieldSchema] = proto.RepeatedField( + proto.MESSAGE, + number=2, + message=FieldSchema, + ) + ground_truth_fields: MutableSequence[FieldSchema] = proto.RepeatedField( + proto.MESSAGE, + number=3, + message=FieldSchema, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/model_monitoring_alert.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/model_monitoring_alert.py new file mode 100644 index 0000000000000000000000000000000000000000..69fa127a670b53ac3bdc90d0577939bb1f735190 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/model_monitoring_alert.py @@ -0,0 +1,170 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +import google.protobuf.struct_pb2 as struct_pb2 # type: ignore +import google.protobuf.timestamp_pb2 as timestamp_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "ModelMonitoringAlertCondition", + "ModelMonitoringAnomaly", + "ModelMonitoringAlert", + }, +) + + +class ModelMonitoringAlertCondition(proto.Message): + r"""Monitoring alert triggered condition. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + threshold (float): + A condition that compares a stats value + against a threshold. Alert will be triggered if + value above the threshold. + + This field is a member of `oneof`_ ``condition``. + """ + + threshold: float = proto.Field( + proto.DOUBLE, + number=1, + oneof="condition", + ) + + +class ModelMonitoringAnomaly(proto.Message): + r"""Represents a single model monitoring anomaly. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + tabular_anomaly (google.cloud.aiplatform_v1beta1.types.ModelMonitoringAnomaly.TabularAnomaly): + Tabular anomaly. + + This field is a member of `oneof`_ ``anomaly``. + model_monitoring_job (str): + Model monitoring job resource name. + algorithm (str): + Algorithm used to calculated the metrics, eg: + jensen_shannon_divergence, l_infinity. + """ + + class TabularAnomaly(proto.Message): + r"""Tabular anomaly details. + + Attributes: + anomaly_uri (str): + Additional anomaly information. e.g. Google + Cloud Storage uri. + summary (str): + Overview of this anomaly. + anomaly (google.protobuf.struct_pb2.Value): + Anomaly body. + trigger_time (google.protobuf.timestamp_pb2.Timestamp): + The time the anomaly was triggered. + condition (google.cloud.aiplatform_v1beta1.types.ModelMonitoringAlertCondition): + The alert condition associated with this + anomaly. + """ + + anomaly_uri: str = proto.Field( + proto.STRING, + number=1, + ) + summary: str = proto.Field( + proto.STRING, + number=2, + ) + anomaly: struct_pb2.Value = proto.Field( + proto.MESSAGE, + number=3, + message=struct_pb2.Value, + ) + trigger_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=4, + message=timestamp_pb2.Timestamp, + ) + condition: "ModelMonitoringAlertCondition" = proto.Field( + proto.MESSAGE, + number=5, + message="ModelMonitoringAlertCondition", + ) + + tabular_anomaly: TabularAnomaly = proto.Field( + proto.MESSAGE, + number=1, + oneof="anomaly", + message=TabularAnomaly, + ) + model_monitoring_job: str = proto.Field( + proto.STRING, + number=2, + ) + algorithm: str = proto.Field( + proto.STRING, + number=3, + ) + + +class ModelMonitoringAlert(proto.Message): + r"""Represents a single monitoring alert. This is currently used + in the SearchModelMonitoringAlerts api, thus the alert wrapped + in this message belongs to the resource asked in the request. + + Attributes: + stats_name (str): + The stats name. + objective_type (str): + One of the supported monitoring objectives: + ``raw-feature-drift`` ``prediction-output-drift`` + ``feature-attribution`` + alert_time (google.protobuf.timestamp_pb2.Timestamp): + Alert creation time. + anomaly (google.cloud.aiplatform_v1beta1.types.ModelMonitoringAnomaly): + Anomaly details. + """ + + stats_name: str = proto.Field( + proto.STRING, + number=1, + ) + objective_type: str = proto.Field( + proto.STRING, + number=2, + ) + alert_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=3, + message=timestamp_pb2.Timestamp, + ) + anomaly: "ModelMonitoringAnomaly" = proto.Field( + proto.MESSAGE, + number=4, + message="ModelMonitoringAnomaly", + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/notebook_idle_shutdown_config.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/notebook_idle_shutdown_config.py new file mode 100644 index 0000000000000000000000000000000000000000..325fb37bfc7873fb2930250e5df747b1f392f5ad --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/notebook_idle_shutdown_config.py @@ -0,0 +1,62 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +import google.protobuf.duration_pb2 as duration_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "NotebookIdleShutdownConfig", + }, +) + + +class NotebookIdleShutdownConfig(proto.Message): + r"""The idle shutdown configuration of NotebookRuntimeTemplate, which + contains the idle_timeout as required field. + + Attributes: + idle_timeout (google.protobuf.duration_pb2.Duration): + Required. Duration is accurate to the second. In Notebook, + Idle Timeout is accurate to minute so the range of + idle_timeout (second) is: 10 \* 60 ~ 1440 + + - + + 60. + idle_shutdown_disabled (bool): + Whether Idle Shutdown is disabled in this + NotebookRuntimeTemplate. + """ + + idle_timeout: duration_pb2.Duration = proto.Field( + proto.MESSAGE, + number=1, + message=duration_pb2.Duration, + ) + idle_shutdown_disabled: bool = proto.Field( + proto.BOOL, + number=2, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/notebook_software_config.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/notebook_software_config.py new file mode 100644 index 0000000000000000000000000000000000000000..2e340b640dac32b7a84d4482986cfce2e76a57af --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/notebook_software_config.py @@ -0,0 +1,150 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import env_var + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "PostStartupScriptConfig", + "ColabImage", + "NotebookSoftwareConfig", + }, +) + + +class PostStartupScriptConfig(proto.Message): + r"""Post-startup script config. + + Attributes: + post_startup_script (str): + Optional. Post-startup script to run after + runtime is started. + post_startup_script_url (str): + Optional. Post-startup script url to + download. Example: https://bucket/script.sh + post_startup_script_behavior (google.cloud.aiplatform_v1beta1.types.PostStartupScriptConfig.PostStartupScriptBehavior): + Optional. Post-startup script behavior that + defines download and execution behavior. + """ + + class PostStartupScriptBehavior(proto.Enum): + r"""Represents a notebook runtime post-startup script behavior. + + Values: + POST_STARTUP_SCRIPT_BEHAVIOR_UNSPECIFIED (0): + Unspecified post-startup script behavior. + RUN_ONCE (1): + Run the post-startup script only once, during + runtime creation. + RUN_EVERY_START (2): + Run the post-startup script after every + start. + DOWNLOAD_AND_RUN_EVERY_START (3): + After every start, download the post-startup + script from its source and run it. + """ + + POST_STARTUP_SCRIPT_BEHAVIOR_UNSPECIFIED = 0 + RUN_ONCE = 1 + RUN_EVERY_START = 2 + DOWNLOAD_AND_RUN_EVERY_START = 3 + + post_startup_script: str = proto.Field( + proto.STRING, + number=1, + ) + post_startup_script_url: str = proto.Field( + proto.STRING, + number=2, + ) + post_startup_script_behavior: PostStartupScriptBehavior = proto.Field( + proto.ENUM, + number=3, + enum=PostStartupScriptBehavior, + ) + + +class ColabImage(proto.Message): + r"""Colab image of the runtime. + + Attributes: + release_name (str): + Optional. The release name of the + NotebookRuntime Colab image, e.g. "py310". If + not specified, detault to the latest release. + description (str): + Output only. A human-readable description of + the specified colab image release, populated by + the system. Example: "Python 3.10", "Latest - + current Python 3.11". + """ + + release_name: str = proto.Field( + proto.STRING, + number=1, + ) + description: str = proto.Field( + proto.STRING, + number=2, + ) + + +class NotebookSoftwareConfig(proto.Message): + r"""Notebook Software Config. This is passed to the backend when + user makes software configurations in UI. + + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + colab_image (google.cloud.aiplatform_v1beta1.types.ColabImage): + Optional. Google-managed NotebookRuntime + colab image. + + This field is a member of `oneof`_ ``runtime_image``. + env (MutableSequence[google.cloud.aiplatform_v1beta1.types.EnvVar]): + Optional. Environment variables to be passed + to the container. Maximum limit is 100. + post_startup_script_config (google.cloud.aiplatform_v1beta1.types.PostStartupScriptConfig): + Optional. Post-startup script config. + """ + + colab_image: "ColabImage" = proto.Field( + proto.MESSAGE, + number=5, + oneof="runtime_image", + message="ColabImage", + ) + env: MutableSequence[env_var.EnvVar] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=env_var.EnvVar, + ) + post_startup_script_config: "PostStartupScriptConfig" = proto.Field( + proto.MESSAGE, + number=2, + message="PostStartupScriptConfig", + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/online_evaluator.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/online_evaluator.py new file mode 100644 index 0000000000000000000000000000000000000000..5a699141963a4ff5b327fa2189aecd0c0516f935 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/online_evaluator.py @@ -0,0 +1,414 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import evaluation_service +import google.protobuf.timestamp_pb2 as timestamp_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "OnlineEvaluator", + }, +) + + +class OnlineEvaluator(proto.Message): + r"""An OnlineEvaluator contains the configuration for an Online + Evaluation. + + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + cloud_observability (google.cloud.aiplatform_v1beta1.types.OnlineEvaluator.CloudObservability): + Data source for the OnlineEvaluator, based on + GCP Observability stack (Cloud Trace & Cloud + Logging). + + This field is a member of `oneof`_ ``data_source``. + name (str): + Identifier. The resource name of the + OnlineEvaluator. Format: + projects/{project}/locations/{location}/onlineEvaluators/{id}. + agent_resource (str): + Required. Immutable. The name of the agent that the + OnlineEvaluator evaluates periodically. This value is used + to filter the traces with a matching cloud.resource_id and + link the evaluation results with relevant dashboards/UIs. + + This field is immutable. Once set, it cannot be changed. + metric_sources (MutableSequence[google.cloud.aiplatform_v1beta1.types.MetricSource]): + Required. A list of metric sources to be used for evaluating + samples. At least one MetricSource must be provided. Right + now, only predefined metrics and registered metrics are + supported. + + Every registered metric must have ``display_name`` (or + ``title``) and ``score_range`` defined. Otherwise, the + evaluations will fail. + + The maximum number of ``metric_sources`` is 25. + config (google.cloud.aiplatform_v1beta1.types.OnlineEvaluator.Config): + Required. Configuration for the + OnlineEvaluator. + state (google.cloud.aiplatform_v1beta1.types.OnlineEvaluator.State): + Output only. The state of the + OnlineEvaluator. + state_details (MutableSequence[google.cloud.aiplatform_v1beta1.types.OnlineEvaluator.StateDetails]): + Output only. Contains additional information + about the state of the OnlineEvaluator. This is + used to provide more details in the event of a + failure. + create_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when the + OnlineEvaluator was created. + update_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when the + OnlineEvaluator was last updated. + display_name (str): + Optional. Human-readable name for the ``OnlineEvaluator``. + + The name doesn't have to be unique. + + The name can consist of any UTF-8 characters. The maximum + length is ``63`` characters. If the display name exceeds max + characters, an ``INVALID_ARGUMENT`` error is returned. + """ + + class State(proto.Enum): + r"""The state of the OnlineEvaluator. + + Values: + STATE_UNSPECIFIED (0): + Default value. + ACTIVE (1): + Indicates that the OnlineEvaluator is active. + SUSPENDED (2): + Indicates that the OnlineEvaluator is + suspended. In this state, the OnlineEvaluator + will not evaluate any samples. + FAILED (3): + Indicates that the OnlineEvaluator is in a failed state. + + This can happen if, for example, the ``log_view`` or + ``trace_view`` set on the ``CloudObservability`` does not + exist. + WARNING (4): + Indicates that the OnlineEvaluator is in a warning state. + This can happen if, for example, some of the metrics in the + ``metric_sources`` are invalid. Evaluation will still run + with the remaining valid metrics. + """ + + STATE_UNSPECIFIED = 0 + ACTIVE = 1 + SUSPENDED = 2 + FAILED = 3 + WARNING = 4 + + class CloudObservability(proto.Message): + r"""Data source for the OnlineEvaluator, based on GCP + Observability stack (Cloud Trace & Cloud Logging). + + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + trace_scope (google.cloud.aiplatform_v1beta1.types.OnlineEvaluator.CloudObservability.TraceScope): + Scope online evaluation to single traces. + + This field is a member of `oneof`_ ``eval_scope``. + open_telemetry (google.cloud.aiplatform_v1beta1.types.OnlineEvaluator.CloudObservability.OpenTelemetry): + Data source follows OpenTelemetry convention. + + This field is a member of `oneof`_ ``convention``. + log_view (str): + Optional. Optional log view that will be used to query logs. + If empty, the ``_Default`` view will be used. + trace_view (str): + Optional. Optional trace view that will be used to query + traces. If empty, the ``_Default`` view will be used. + + NOTE: This field is not supported yet and will be ignored if + set. + """ + + class NumericPredicate(proto.Message): + r"""Defines a predicate for filtering based on a numeric value. + + Attributes: + comparison_operator (google.cloud.aiplatform_v1beta1.types.OnlineEvaluator.CloudObservability.NumericPredicate.ComparisonOperator): + Required. The comparison operator to apply. + value (float): + Required. The value to compare against. + """ + + class ComparisonOperator(proto.Enum): + r"""Comparison operators for numeric predicates. + + Values: + COMPARISON_OPERATOR_UNSPECIFIED (0): + Unspecified comparison operator. This value + should not be used. + LESS (1): + Less than. + LESS_OR_EQUAL (2): + Less than or equal to. + EQUAL (3): + Equal to. + NOT_EQUAL (4): + Not equal to. + GREATER_OR_EQUAL (5): + Greater than or equal to. + GREATER (6): + Greater than. + """ + + COMPARISON_OPERATOR_UNSPECIFIED = 0 + LESS = 1 + LESS_OR_EQUAL = 2 + EQUAL = 3 + NOT_EQUAL = 4 + GREATER_OR_EQUAL = 5 + GREATER = 6 + + comparison_operator: ( + "OnlineEvaluator.CloudObservability.NumericPredicate.ComparisonOperator" + ) = proto.Field( + proto.ENUM, + number=1, + enum="OnlineEvaluator.CloudObservability.NumericPredicate.ComparisonOperator", + ) + value: float = proto.Field( + proto.FLOAT, + number=2, + ) + + class TraceScope(proto.Message): + r"""If chosen, the online evaluator will evaluate single traces matching + specified ``filter``. + + Attributes: + filter (MutableSequence[google.cloud.aiplatform_v1beta1.types.OnlineEvaluator.CloudObservability.TraceScope.Predicate]): + Optional. A list of predicates to filter + traces. Multiple predicates are combined using + AND. + + The maximum number of predicates is 10. + """ + + class Predicate(proto.Message): + r"""Defines a single filter predicate. + + This message has `oneof`_ fields (mutually exclusive fields). + For each oneof, at most one member field can be set at the same time. + Setting any member of the oneof automatically clears all other + members. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + duration (google.cloud.aiplatform_v1beta1.types.OnlineEvaluator.CloudObservability.NumericPredicate): + Filter on the duration of a trace. + + This field is a member of `oneof`_ ``predicate``. + total_token_usage (google.cloud.aiplatform_v1beta1.types.OnlineEvaluator.CloudObservability.NumericPredicate): + Filter on the total token usage within a + trace. + + This field is a member of `oneof`_ ``predicate``. + """ + + duration: "OnlineEvaluator.CloudObservability.NumericPredicate" = ( + proto.Field( + proto.MESSAGE, + number=1, + oneof="predicate", + message="OnlineEvaluator.CloudObservability.NumericPredicate", + ) + ) + total_token_usage: ( + "OnlineEvaluator.CloudObservability.NumericPredicate" + ) = proto.Field( + proto.MESSAGE, + number=2, + oneof="predicate", + message="OnlineEvaluator.CloudObservability.NumericPredicate", + ) + + filter: MutableSequence[ + "OnlineEvaluator.CloudObservability.TraceScope.Predicate" + ] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message="OnlineEvaluator.CloudObservability.TraceScope.Predicate", + ) + + class OpenTelemetry(proto.Message): + r"""Configuration for data source following OpenTelemetry. + + Attributes: + semconv_version (str): + Required. Defines which version OTel Semantic + Convention the data follows. Can be "1.39.0" or + newer. + """ + + semconv_version: str = proto.Field( + proto.STRING, + number=1, + ) + + trace_scope: "OnlineEvaluator.CloudObservability.TraceScope" = proto.Field( + proto.MESSAGE, + number=3, + oneof="eval_scope", + message="OnlineEvaluator.CloudObservability.TraceScope", + ) + open_telemetry: "OnlineEvaluator.CloudObservability.OpenTelemetry" = ( + proto.Field( + proto.MESSAGE, + number=4, + oneof="convention", + message="OnlineEvaluator.CloudObservability.OpenTelemetry", + ) + ) + log_view: str = proto.Field( + proto.STRING, + number=1, + ) + trace_view: str = proto.Field( + proto.STRING, + number=2, + ) + + class Config(proto.Message): + r"""Configuration for sampling behavior of the OnlineEvaluator. + The OnlineEvaluator runs at a fixed interval of 10 minutes. + + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + random_sampling (google.cloud.aiplatform_v1beta1.types.OnlineEvaluator.Config.RandomSampling): + Random sampling method. + + This field is a member of `oneof`_ ``sampling_method``. + max_evaluated_samples_per_run (int): + Optional. The maximum number of evaluations + to perform per run. If set to 0, the number is + unbounded. + """ + + class RandomSampling(proto.Message): + r"""Configuration for random sampling. + + Attributes: + percentage (int): + Required. The percentage of traces to sample for evaluation. + Must be an integer between ``1`` and ``100``. + """ + + percentage: int = proto.Field( + proto.INT32, + number=1, + ) + + random_sampling: "OnlineEvaluator.Config.RandomSampling" = proto.Field( + proto.MESSAGE, + number=2, + oneof="sampling_method", + message="OnlineEvaluator.Config.RandomSampling", + ) + max_evaluated_samples_per_run: int = proto.Field( + proto.INT64, + number=1, + ) + + class StateDetails(proto.Message): + r"""Contains additional information about the state of the + OnlineEvaluator. + + Attributes: + message (str): + Output only. Human-readable message + describing the state of the OnlineEvaluator. + """ + + message: str = proto.Field( + proto.STRING, + number=1, + ) + + cloud_observability: CloudObservability = proto.Field( + proto.MESSAGE, + number=4, + oneof="data_source", + message=CloudObservability, + ) + name: str = proto.Field( + proto.STRING, + number=1, + ) + agent_resource: str = proto.Field( + proto.STRING, + number=2, + ) + metric_sources: MutableSequence[evaluation_service.MetricSource] = ( + proto.RepeatedField( + proto.MESSAGE, + number=3, + message=evaluation_service.MetricSource, + ) + ) + config: Config = proto.Field( + proto.MESSAGE, + number=5, + message=Config, + ) + state: State = proto.Field( + proto.ENUM, + number=6, + enum=State, + ) + state_details: MutableSequence[StateDetails] = proto.RepeatedField( + proto.MESSAGE, + number=10, + message=StateDetails, + ) + create_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=7, + message=timestamp_pb2.Timestamp, + ) + update_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=8, + message=timestamp_pb2.Timestamp, + ) + display_name: str = proto.Field( + proto.STRING, + number=9, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/online_evaluator_service.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/online_evaluator_service.py new file mode 100644 index 0000000000000000000000000000000000000000..4966caf9b71dbc4ff370fcba91442ca8667dab64 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/online_evaluator_service.py @@ -0,0 +1,324 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import ( + online_evaluator as gca_online_evaluator, +) +from google.cloud.aiplatform_v1beta1.types import operation +import google.protobuf.field_mask_pb2 as field_mask_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "CreateOnlineEvaluatorRequest", + "CreateOnlineEvaluatorOperationMetadata", + "GetOnlineEvaluatorRequest", + "UpdateOnlineEvaluatorRequest", + "UpdateOnlineEvaluatorOperationMetadata", + "DeleteOnlineEvaluatorRequest", + "DeleteOnlineEvaluatorOperationMetadata", + "ListOnlineEvaluatorsRequest", + "ListOnlineEvaluatorsResponse", + "ActivateOnlineEvaluatorRequest", + "ActivateOnlineEvaluatorOperationMetadata", + "SuspendOnlineEvaluatorRequest", + "SuspendOnlineEvaluatorOperationMetadata", + }, +) + + +class CreateOnlineEvaluatorRequest(proto.Message): + r"""Request message for CreateOnlineEvaluator. + + Attributes: + parent (str): + Required. The parent resource where the + OnlineEvaluator will be created. Format: + projects/{project}/locations/{location}. + online_evaluator (google.cloud.aiplatform_v1beta1.types.OnlineEvaluator): + Required. The OnlineEvaluator to create. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + online_evaluator: gca_online_evaluator.OnlineEvaluator = proto.Field( + proto.MESSAGE, + number=2, + message=gca_online_evaluator.OnlineEvaluator, + ) + + +class CreateOnlineEvaluatorOperationMetadata(proto.Message): + r"""Metadata for the CreateOnlineEvaluator operation. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + Common part of operation metadata. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class GetOnlineEvaluatorRequest(proto.Message): + r"""Request message for GetOnlineEvaluator. + + Attributes: + name (str): + Required. The name of the OnlineEvaluator to + retrieve. Format: + projects/{project}/locations/{location}/onlineEvaluators/{id}. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class UpdateOnlineEvaluatorRequest(proto.Message): + r"""Request message for UpdateOnlineEvaluator. + + Attributes: + online_evaluator (google.cloud.aiplatform_v1beta1.types.OnlineEvaluator): + Required. The OnlineEvaluator to update. + Format: + projects/{project}/locations/{location}/onlineEvaluators/{id}. + update_mask (google.protobuf.field_mask_pb2.FieldMask): + Optional. Field mask is used to control which + fields get updated. If the mask is not present, + all fields will be updated. + """ + + online_evaluator: gca_online_evaluator.OnlineEvaluator = proto.Field( + proto.MESSAGE, + number=1, + message=gca_online_evaluator.OnlineEvaluator, + ) + update_mask: field_mask_pb2.FieldMask = proto.Field( + proto.MESSAGE, + number=2, + message=field_mask_pb2.FieldMask, + ) + + +class UpdateOnlineEvaluatorOperationMetadata(proto.Message): + r"""Metadata for the UpdateOnlineEvaluator operation. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + Generic operation metadata. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class DeleteOnlineEvaluatorRequest(proto.Message): + r"""Request message for DeleteOnlineEvaluator. + + Attributes: + name (str): + Required. The name of the OnlineEvaluator to + delete. Format: + projects/{project}/locations/{location}/onlineEvaluators/{id}. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class DeleteOnlineEvaluatorOperationMetadata(proto.Message): + r"""Metadata for the DeleteOnlineEvaluator operation. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + Generic operation metadata. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class ListOnlineEvaluatorsRequest(proto.Message): + r"""Request message for ListOnlineEvaluators. + + Attributes: + parent (str): + Required. The parent resource of the + OnlineEvaluators to list. Format: + projects/{project}/locations/{location}. + page_size (int): + Optional. The maximum number of + OnlineEvaluators to return. The service may + return fewer than this value. If unspecified, at + most 50 OnlineEvaluators will be returned. The + maximum value is 100; values above 100 will be + coerced to 100. Based on aip.dev/158. + page_token (str): + Optional. A token identifying a page of + results the server should return. Based on + aip.dev/158. + filter (str): + Optional. Standard list filter. Supported fields: \* + ``create_time`` \* ``update_time`` \* ``agent_resource`` + Example: ``create_time>"2026-01-01T00:00:00-04:00"`` where + the timestamp is in RFC 3339 format) Based on aip.dev/160. + order_by (str): + Optional. A comma-separated list of fields to order by. The + default sorting order is ascending. Use "desc" after a field + name for descending. Supported fields: + + - ``create_time`` + - ``update_time`` + + Example: ``create_time desc``. Based on aip.dev/132. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + page_size: int = proto.Field( + proto.INT32, + number=2, + ) + page_token: str = proto.Field( + proto.STRING, + number=3, + ) + filter: str = proto.Field( + proto.STRING, + number=4, + ) + order_by: str = proto.Field( + proto.STRING, + number=5, + ) + + +class ListOnlineEvaluatorsResponse(proto.Message): + r"""Response message for ListOnlineEvaluators. + + Attributes: + online_evaluators (MutableSequence[google.cloud.aiplatform_v1beta1.types.OnlineEvaluator]): + A list of OnlineEvaluators matching the + request. + next_page_token (str): + A token to retrieve the next page. Absence of + this field indicates there are no subsequent + pages. + """ + + @property + def raw_page(self): + return self + + online_evaluators: MutableSequence[gca_online_evaluator.OnlineEvaluator] = ( + proto.RepeatedField( + proto.MESSAGE, + number=1, + message=gca_online_evaluator.OnlineEvaluator, + ) + ) + next_page_token: str = proto.Field( + proto.STRING, + number=2, + ) + + +class ActivateOnlineEvaluatorRequest(proto.Message): + r"""Request message for ActivateOnlineEvaluator. + + Attributes: + name (str): + Required. The name of the OnlineEvaluator to + activate. Format: + projects/{project}/locations/{location}/onlineEvaluators/{id}. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class ActivateOnlineEvaluatorOperationMetadata(proto.Message): + r"""Metadata for the ActivateOnlineEvaluator operation. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + Common part of operation metadata. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class SuspendOnlineEvaluatorRequest(proto.Message): + r"""Request message for SuspendOnlineEvaluator. + + Attributes: + name (str): + Required. The name of the OnlineEvaluator to + suspend. Format: + projects/{project}/locations/{location}/onlineEvaluators/{id}. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class SuspendOnlineEvaluatorOperationMetadata(proto.Message): + r"""Metadata for the SuspendOnlineEvaluator operation. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + Common part of operation metadata. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/operation.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/operation.py new file mode 100644 index 0000000000000000000000000000000000000000..a174ee5645ad68da5dac81cdb3fd24d3739dbc4c --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/operation.py @@ -0,0 +1,87 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +import google.protobuf.timestamp_pb2 as timestamp_pb2 # type: ignore +import google.rpc.status_pb2 as status_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "GenericOperationMetadata", + "DeleteOperationMetadata", + }, +) + + +class GenericOperationMetadata(proto.Message): + r"""Generic Metadata shared by all operations. + + Attributes: + partial_failures (MutableSequence[google.rpc.status_pb2.Status]): + Output only. Partial failures encountered. + E.g. single files that couldn't be read. + This field should never exceed 20 entries. + Status details field will contain standard + Google Cloud error details. + create_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Time when the operation was + created. + update_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Time when the operation was + updated for the last time. If the operation has + finished (successfully or not), this is the + finish time. + """ + + partial_failures: MutableSequence[status_pb2.Status] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=status_pb2.Status, + ) + create_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=2, + message=timestamp_pb2.Timestamp, + ) + update_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=3, + message=timestamp_pb2.Timestamp, + ) + + +class DeleteOperationMetadata(proto.Message): + r"""Details of operations that perform deletes of any entities. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + The common part of the operation metadata. + """ + + generic_metadata: "GenericOperationMetadata" = proto.Field( + proto.MESSAGE, + number=1, + message="GenericOperationMetadata", + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/pipeline_state.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/pipeline_state.py new file mode 100644 index 0000000000000000000000000000000000000000..5ef7a3bb6075690070fcb2d40add1f42d8f55b73 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/pipeline_state.py @@ -0,0 +1,70 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "PipelineState", + }, +) + + +class PipelineState(proto.Enum): + r"""Describes the state of a pipeline. + + Values: + PIPELINE_STATE_UNSPECIFIED (0): + The pipeline state is unspecified. + PIPELINE_STATE_QUEUED (1): + The pipeline has been created or resumed, and + processing has not yet begun. + PIPELINE_STATE_PENDING (2): + The service is preparing to run the pipeline. + PIPELINE_STATE_RUNNING (3): + The pipeline is in progress. + PIPELINE_STATE_SUCCEEDED (4): + The pipeline completed successfully. + PIPELINE_STATE_FAILED (5): + The pipeline failed. + PIPELINE_STATE_CANCELLING (6): + The pipeline is being cancelled. From this state, the + pipeline may only go to either PIPELINE_STATE_SUCCEEDED, + PIPELINE_STATE_FAILED or PIPELINE_STATE_CANCELLED. + PIPELINE_STATE_CANCELLED (7): + The pipeline has been cancelled. + PIPELINE_STATE_PAUSED (8): + The pipeline has been stopped, and can be + resumed. + """ + + PIPELINE_STATE_UNSPECIFIED = 0 + PIPELINE_STATE_QUEUED = 1 + PIPELINE_STATE_PENDING = 2 + PIPELINE_STATE_RUNNING = 3 + PIPELINE_STATE_SUCCEEDED = 4 + PIPELINE_STATE_FAILED = 5 + PIPELINE_STATE_CANCELLING = 6 + PIPELINE_STATE_CANCELLED = 7 + PIPELINE_STATE_PAUSED = 8 + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/prediction_service.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/prediction_service.py new file mode 100644 index 0000000000000000000000000000000000000000..e992bb711309ad058e1fa10eb9083f1e1a689ad3 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/prediction_service.py @@ -0,0 +1,1495 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import content as gca_content +from google.cloud.aiplatform_v1beta1.types import explanation +from google.cloud.aiplatform_v1beta1.types import tool +from google.cloud.aiplatform_v1beta1.types import types +from google.cloud.aiplatform_v1beta1.types import usage_metadata as gca_usage_metadata +import google.api.httpbody_pb2 as httpbody_pb2 # type: ignore +import google.protobuf.struct_pb2 as struct_pb2 # type: ignore +import google.protobuf.timestamp_pb2 as timestamp_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "PredictRequest", + "PredictResponse", + "RawPredictRequest", + "StreamRawPredictRequest", + "DirectPredictRequest", + "DirectPredictResponse", + "DirectRawPredictRequest", + "DirectRawPredictResponse", + "StreamDirectPredictRequest", + "StreamDirectPredictResponse", + "StreamDirectRawPredictRequest", + "StreamDirectRawPredictResponse", + "StreamingPredictRequest", + "StreamingPredictResponse", + "StreamingRawPredictRequest", + "StreamingRawPredictResponse", + "ExplainRequest", + "ExplainResponse", + "CountTokensRequest", + "CountTokensResponse", + "GenerateContentRequest", + "GenerateContentResponse", + "ChatCompletionsRequest", + "PredictLongRunningResponse", + "PredictLongRunningMetadata", + "GenerateVideoResponse", + "EmbedContentRequest", + "EmbedContentResponse", + }, +) + + +class PredictRequest(proto.Message): + r"""Request message for + [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]. + + Attributes: + endpoint (str): + Required. The name of the Endpoint requested to serve the + prediction. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + instances (MutableSequence[google.protobuf.struct_pb2.Value]): + Required. The instances that are the input to the prediction + call. A DeployedModel may have an upper limit on the number + of instances it supports per request, and when it is + exceeded the prediction call errors in case of AutoML + Models, or, in case of customer created Models, the + behaviour is as documented by that Model. The schema of any + single instance may be specified via Endpoint's + DeployedModels' + [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model] + [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] + [instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]. + parameters (google.protobuf.struct_pb2.Value): + The parameters that govern the prediction. The schema of the + parameters may be specified via Endpoint's DeployedModels' + [Model's + ][google.cloud.aiplatform.v1beta1.DeployedModel.model] + [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] + [parameters_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri]. + labels (MutableMapping[str, str]): + Optional. The user labels for Imagen billing + usage only. Only Imagen supports labels. For + other use cases, it will be ignored. + """ + + endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + instances: MutableSequence[struct_pb2.Value] = proto.RepeatedField( + proto.MESSAGE, + number=2, + message=struct_pb2.Value, + ) + parameters: struct_pb2.Value = proto.Field( + proto.MESSAGE, + number=3, + message=struct_pb2.Value, + ) + labels: MutableMapping[str, str] = proto.MapField( + proto.STRING, + proto.STRING, + number=4, + ) + + +class PredictResponse(proto.Message): + r"""Response message for + [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]. + + Attributes: + predictions (MutableSequence[google.protobuf.struct_pb2.Value]): + The predictions that are the output of the predictions call. + The schema of any single prediction may be specified via + Endpoint's DeployedModels' [Model's + ][google.cloud.aiplatform.v1beta1.DeployedModel.model] + [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] + [prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri]. + deployed_model_id (str): + ID of the Endpoint's DeployedModel that + served this prediction. + model (str): + Output only. The resource name of the Model + which is deployed as the DeployedModel that this + prediction hits. + model_version_id (str): + Output only. The version ID of the Model + which is deployed as the DeployedModel that this + prediction hits. + model_display_name (str): + Output only. The [display + name][google.cloud.aiplatform.v1beta1.Model.display_name] of + the Model which is deployed as the DeployedModel that this + prediction hits. + metadata (google.protobuf.struct_pb2.Value): + Output only. Request-level metadata returned + by the model. The metadata type will be + dependent upon the model implementation. + """ + + predictions: MutableSequence[struct_pb2.Value] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=struct_pb2.Value, + ) + deployed_model_id: str = proto.Field( + proto.STRING, + number=2, + ) + model: str = proto.Field( + proto.STRING, + number=3, + ) + model_version_id: str = proto.Field( + proto.STRING, + number=5, + ) + model_display_name: str = proto.Field( + proto.STRING, + number=4, + ) + metadata: struct_pb2.Value = proto.Field( + proto.MESSAGE, + number=6, + message=struct_pb2.Value, + ) + + +class RawPredictRequest(proto.Message): + r"""Request message for + [PredictionService.RawPredict][google.cloud.aiplatform.v1beta1.PredictionService.RawPredict]. + + Attributes: + endpoint (str): + Required. The name of the Endpoint requested to serve the + prediction. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + http_body (google.api.httpbody_pb2.HttpBody): + The prediction input. Supports HTTP headers and arbitrary + data payload. + + A + [DeployedModel][google.cloud.aiplatform.v1beta1.DeployedModel] + may have an upper limit on the number of instances it + supports per request. When this limit it is exceeded for an + AutoML model, the + [RawPredict][google.cloud.aiplatform.v1beta1.PredictionService.RawPredict] + method returns an error. When this limit is exceeded for a + custom-trained model, the behavior varies depending on the + model. + + You can specify the schema for each instance in the + [predict_schemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] + field when you create a + [Model][google.cloud.aiplatform.v1beta1.Model]. This schema + applies when you deploy the ``Model`` as a ``DeployedModel`` + to an [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] + and use the ``RawPredict`` method. + """ + + endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + http_body: httpbody_pb2.HttpBody = proto.Field( + proto.MESSAGE, + number=2, + message=httpbody_pb2.HttpBody, + ) + + +class StreamRawPredictRequest(proto.Message): + r"""Request message for + [PredictionService.StreamRawPredict][google.cloud.aiplatform.v1beta1.PredictionService.StreamRawPredict]. + + Attributes: + endpoint (str): + Required. The name of the Endpoint requested to serve the + prediction. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + http_body (google.api.httpbody_pb2.HttpBody): + The prediction input. Supports HTTP headers + and arbitrary data payload. + """ + + endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + http_body: httpbody_pb2.HttpBody = proto.Field( + proto.MESSAGE, + number=2, + message=httpbody_pb2.HttpBody, + ) + + +class DirectPredictRequest(proto.Message): + r"""Request message for + [PredictionService.DirectPredict][google.cloud.aiplatform.v1beta1.PredictionService.DirectPredict]. + + Attributes: + endpoint (str): + Required. The name of the Endpoint requested to serve the + prediction. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + inputs (MutableSequence[google.cloud.aiplatform_v1beta1.types.Tensor]): + The prediction input. + parameters (google.cloud.aiplatform_v1beta1.types.Tensor): + The parameters that govern the prediction. + """ + + endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + inputs: MutableSequence[types.Tensor] = proto.RepeatedField( + proto.MESSAGE, + number=2, + message=types.Tensor, + ) + parameters: types.Tensor = proto.Field( + proto.MESSAGE, + number=3, + message=types.Tensor, + ) + + +class DirectPredictResponse(proto.Message): + r"""Response message for + [PredictionService.DirectPredict][google.cloud.aiplatform.v1beta1.PredictionService.DirectPredict]. + + Attributes: + outputs (MutableSequence[google.cloud.aiplatform_v1beta1.types.Tensor]): + The prediction output. + parameters (google.cloud.aiplatform_v1beta1.types.Tensor): + The parameters that govern the prediction. + """ + + outputs: MutableSequence[types.Tensor] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=types.Tensor, + ) + parameters: types.Tensor = proto.Field( + proto.MESSAGE, + number=2, + message=types.Tensor, + ) + + +class DirectRawPredictRequest(proto.Message): + r"""Request message for + [PredictionService.DirectRawPredict][google.cloud.aiplatform.v1beta1.PredictionService.DirectRawPredict]. + + Attributes: + endpoint (str): + Required. The name of the Endpoint requested to serve the + prediction. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + method_name (str): + Fully qualified name of the API method being invoked to + perform predictions. + + Format: ``/namespace.Service/Method/`` Example: + ``/tensorflow.serving.PredictionService/Predict`` + input (bytes): + The prediction input. + """ + + endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + method_name: str = proto.Field( + proto.STRING, + number=2, + ) + input: bytes = proto.Field( + proto.BYTES, + number=3, + ) + + +class DirectRawPredictResponse(proto.Message): + r"""Response message for + [PredictionService.DirectRawPredict][google.cloud.aiplatform.v1beta1.PredictionService.DirectRawPredict]. + + Attributes: + output (bytes): + The prediction output. + """ + + output: bytes = proto.Field( + proto.BYTES, + number=1, + ) + + +class StreamDirectPredictRequest(proto.Message): + r"""Request message for + [PredictionService.StreamDirectPredict][google.cloud.aiplatform.v1beta1.PredictionService.StreamDirectPredict]. + + The first message must contain + [endpoint][google.cloud.aiplatform.v1beta1.StreamDirectPredictRequest.endpoint] + field and optionally [input][]. The subsequent messages must contain + [input][]. + + Attributes: + endpoint (str): + Required. The name of the Endpoint requested to serve the + prediction. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + inputs (MutableSequence[google.cloud.aiplatform_v1beta1.types.Tensor]): + Optional. The prediction input. + parameters (google.cloud.aiplatform_v1beta1.types.Tensor): + Optional. The parameters that govern the + prediction. + """ + + endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + inputs: MutableSequence[types.Tensor] = proto.RepeatedField( + proto.MESSAGE, + number=2, + message=types.Tensor, + ) + parameters: types.Tensor = proto.Field( + proto.MESSAGE, + number=3, + message=types.Tensor, + ) + + +class StreamDirectPredictResponse(proto.Message): + r"""Response message for + [PredictionService.StreamDirectPredict][google.cloud.aiplatform.v1beta1.PredictionService.StreamDirectPredict]. + + Attributes: + outputs (MutableSequence[google.cloud.aiplatform_v1beta1.types.Tensor]): + The prediction output. + parameters (google.cloud.aiplatform_v1beta1.types.Tensor): + The parameters that govern the prediction. + """ + + outputs: MutableSequence[types.Tensor] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=types.Tensor, + ) + parameters: types.Tensor = proto.Field( + proto.MESSAGE, + number=2, + message=types.Tensor, + ) + + +class StreamDirectRawPredictRequest(proto.Message): + r"""Request message for + [PredictionService.StreamDirectRawPredict][google.cloud.aiplatform.v1beta1.PredictionService.StreamDirectRawPredict]. + + The first message must contain + [endpoint][google.cloud.aiplatform.v1beta1.StreamDirectRawPredictRequest.endpoint] + and + [method_name][google.cloud.aiplatform.v1beta1.StreamDirectRawPredictRequest.method_name] + fields and optionally + [input][google.cloud.aiplatform.v1beta1.StreamDirectRawPredictRequest.input]. + The subsequent messages must contain + [input][google.cloud.aiplatform.v1beta1.StreamDirectRawPredictRequest.input]. + [method_name][google.cloud.aiplatform.v1beta1.StreamDirectRawPredictRequest.method_name] + in the subsequent messages have no effect. + + Attributes: + endpoint (str): + Required. The name of the Endpoint requested to serve the + prediction. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + method_name (str): + Optional. Fully qualified name of the API method being + invoked to perform predictions. + + Format: ``/namespace.Service/Method/`` Example: + ``/tensorflow.serving.PredictionService/Predict`` + input (bytes): + Optional. The prediction input. + """ + + endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + method_name: str = proto.Field( + proto.STRING, + number=2, + ) + input: bytes = proto.Field( + proto.BYTES, + number=3, + ) + + +class StreamDirectRawPredictResponse(proto.Message): + r"""Response message for + [PredictionService.StreamDirectRawPredict][google.cloud.aiplatform.v1beta1.PredictionService.StreamDirectRawPredict]. + + Attributes: + output (bytes): + The prediction output. + """ + + output: bytes = proto.Field( + proto.BYTES, + number=1, + ) + + +class StreamingPredictRequest(proto.Message): + r"""Request message for + [PredictionService.StreamingPredict][google.cloud.aiplatform.v1beta1.PredictionService.StreamingPredict]. + + The first message must contain + [endpoint][google.cloud.aiplatform.v1beta1.StreamingPredictRequest.endpoint] + field and optionally [input][]. The subsequent messages must contain + [input][]. + + Attributes: + endpoint (str): + Required. The name of the Endpoint requested to serve the + prediction. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + inputs (MutableSequence[google.cloud.aiplatform_v1beta1.types.Tensor]): + The prediction input. + parameters (google.cloud.aiplatform_v1beta1.types.Tensor): + The parameters that govern the prediction. + """ + + endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + inputs: MutableSequence[types.Tensor] = proto.RepeatedField( + proto.MESSAGE, + number=2, + message=types.Tensor, + ) + parameters: types.Tensor = proto.Field( + proto.MESSAGE, + number=3, + message=types.Tensor, + ) + + +class StreamingPredictResponse(proto.Message): + r"""Response message for + [PredictionService.StreamingPredict][google.cloud.aiplatform.v1beta1.PredictionService.StreamingPredict]. + + Attributes: + outputs (MutableSequence[google.cloud.aiplatform_v1beta1.types.Tensor]): + The prediction output. + parameters (google.cloud.aiplatform_v1beta1.types.Tensor): + The parameters that govern the prediction. + """ + + outputs: MutableSequence[types.Tensor] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=types.Tensor, + ) + parameters: types.Tensor = proto.Field( + proto.MESSAGE, + number=2, + message=types.Tensor, + ) + + +class StreamingRawPredictRequest(proto.Message): + r"""Request message for + [PredictionService.StreamingRawPredict][google.cloud.aiplatform.v1beta1.PredictionService.StreamingRawPredict]. + + The first message must contain + [endpoint][google.cloud.aiplatform.v1beta1.StreamingRawPredictRequest.endpoint] + and + [method_name][google.cloud.aiplatform.v1beta1.StreamingRawPredictRequest.method_name] + fields and optionally + [input][google.cloud.aiplatform.v1beta1.StreamingRawPredictRequest.input]. + The subsequent messages must contain + [input][google.cloud.aiplatform.v1beta1.StreamingRawPredictRequest.input]. + [method_name][google.cloud.aiplatform.v1beta1.StreamingRawPredictRequest.method_name] + in the subsequent messages have no effect. + + Attributes: + endpoint (str): + Required. The name of the Endpoint requested to serve the + prediction. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + method_name (str): + Fully qualified name of the API method being invoked to + perform predictions. + + Format: ``/namespace.Service/Method/`` Example: + ``/tensorflow.serving.PredictionService/Predict`` + input (bytes): + The prediction input. + """ + + endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + method_name: str = proto.Field( + proto.STRING, + number=2, + ) + input: bytes = proto.Field( + proto.BYTES, + number=3, + ) + + +class StreamingRawPredictResponse(proto.Message): + r"""Response message for + [PredictionService.StreamingRawPredict][google.cloud.aiplatform.v1beta1.PredictionService.StreamingRawPredict]. + + Attributes: + output (bytes): + The prediction output. + """ + + output: bytes = proto.Field( + proto.BYTES, + number=1, + ) + + +class ExplainRequest(proto.Message): + r"""Request message for + [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]. + + Attributes: + endpoint (str): + Required. The name of the Endpoint requested to serve the + explanation. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + instances (MutableSequence[google.protobuf.struct_pb2.Value]): + Required. The instances that are the input to the + explanation call. A DeployedModel may have an upper limit on + the number of instances it supports per request, and when it + is exceeded the explanation call errors in case of AutoML + Models, or, in case of customer created Models, the + behaviour is as documented by that Model. The schema of any + single instance may be specified via Endpoint's + DeployedModels' + [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model] + [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] + [instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]. + parameters (google.protobuf.struct_pb2.Value): + The parameters that govern the prediction. The schema of the + parameters may be specified via Endpoint's DeployedModels' + [Model's + ][google.cloud.aiplatform.v1beta1.DeployedModel.model] + [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] + [parameters_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri]. + explanation_spec_override (google.cloud.aiplatform_v1beta1.types.ExplanationSpecOverride): + If specified, overrides the + [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] + of the DeployedModel. Can be used for explaining prediction + results with different configurations, such as: + + - Explaining top-5 predictions results as opposed to top-1; + - Increasing path count or step count of the attribution + methods to reduce approximate errors; + - Using different baselines for explaining the prediction + results. + concurrent_explanation_spec_override (MutableMapping[str, google.cloud.aiplatform_v1beta1.types.ExplanationSpecOverride]): + Optional. This field is the same as the one above, but + supports multiple explanations to occur in parallel. The key + can be any string. Each override will be run against the + model, then its explanations will be grouped together. + + Note - these explanations are run **In Addition** to the + default Explanation in the deployed model. + deployed_model_id (str): + If specified, this ExplainRequest will be served by the + chosen DeployedModel, overriding + [Endpoint.traffic_split][google.cloud.aiplatform.v1beta1.Endpoint.traffic_split]. + """ + + endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + instances: MutableSequence[struct_pb2.Value] = proto.RepeatedField( + proto.MESSAGE, + number=2, + message=struct_pb2.Value, + ) + parameters: struct_pb2.Value = proto.Field( + proto.MESSAGE, + number=4, + message=struct_pb2.Value, + ) + explanation_spec_override: explanation.ExplanationSpecOverride = proto.Field( + proto.MESSAGE, + number=5, + message=explanation.ExplanationSpecOverride, + ) + concurrent_explanation_spec_override: MutableMapping[ + str, explanation.ExplanationSpecOverride + ] = proto.MapField( + proto.STRING, + proto.MESSAGE, + number=6, + message=explanation.ExplanationSpecOverride, + ) + deployed_model_id: str = proto.Field( + proto.STRING, + number=3, + ) + + +class ExplainResponse(proto.Message): + r"""Response message for + [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]. + + Attributes: + explanations (MutableSequence[google.cloud.aiplatform_v1beta1.types.Explanation]): + The explanations of the Model's + [PredictResponse.predictions][google.cloud.aiplatform.v1beta1.PredictResponse.predictions]. + + It has the same number of elements as + [instances][google.cloud.aiplatform.v1beta1.ExplainRequest.instances] + to be explained. + concurrent_explanations (MutableMapping[str, google.cloud.aiplatform_v1beta1.types.ExplainResponse.ConcurrentExplanation]): + This field stores the results of the + explanations run in parallel with The default + explanation strategy/method. + deployed_model_id (str): + ID of the Endpoint's DeployedModel that + served this explanation. + predictions (MutableSequence[google.protobuf.struct_pb2.Value]): + The predictions that are the output of the predictions call. + Same as + [PredictResponse.predictions][google.cloud.aiplatform.v1beta1.PredictResponse.predictions]. + """ + + class ConcurrentExplanation(proto.Message): + r"""This message is a wrapper grouping Concurrent Explanations. + + Attributes: + explanations (MutableSequence[google.cloud.aiplatform_v1beta1.types.Explanation]): + The explanations of the Model's + [PredictResponse.predictions][google.cloud.aiplatform.v1beta1.PredictResponse.predictions]. + + It has the same number of elements as + [instances][google.cloud.aiplatform.v1beta1.ExplainRequest.instances] + to be explained. + """ + + explanations: MutableSequence[explanation.Explanation] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=explanation.Explanation, + ) + + explanations: MutableSequence[explanation.Explanation] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=explanation.Explanation, + ) + concurrent_explanations: MutableMapping[str, ConcurrentExplanation] = ( + proto.MapField( + proto.STRING, + proto.MESSAGE, + number=4, + message=ConcurrentExplanation, + ) + ) + deployed_model_id: str = proto.Field( + proto.STRING, + number=2, + ) + predictions: MutableSequence[struct_pb2.Value] = proto.RepeatedField( + proto.MESSAGE, + number=3, + message=struct_pb2.Value, + ) + + +class CountTokensRequest(proto.Message): + r"""Request message for + [PredictionService.CountTokens][google.cloud.aiplatform.v1beta1.PredictionService.CountTokens]. + + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + endpoint (str): + Required. The name of the Endpoint requested to perform + token counting. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + model (str): + Optional. The name of the publisher model requested to serve + the prediction. Format: + ``projects/{project}/locations/{location}/publishers/*/models/*`` + instances (MutableSequence[google.protobuf.struct_pb2.Value]): + Optional. The instances that are the input to + token counting call. Schema is identical to the + prediction schema of the underlying model. + contents (MutableSequence[google.cloud.aiplatform_v1beta1.types.Content]): + Optional. Input content. + system_instruction (google.cloud.aiplatform_v1beta1.types.Content): + Optional. The user provided system + instructions for the model. Note: only text + should be used in parts and content in each part + will be in a separate paragraph. + + This field is a member of `oneof`_ ``_system_instruction``. + tools (MutableSequence[google.cloud.aiplatform_v1beta1.types.Tool]): + Optional. A list of ``Tools`` the model may use to generate + the next response. + + A ``Tool`` is a piece of code that enables the system to + interact with external systems to perform an action, or set + of actions, outside of knowledge and scope of the model. + generation_config (google.cloud.aiplatform_v1beta1.types.GenerationConfig): + Optional. Generation config that the model + will use to generate the response. + + This field is a member of `oneof`_ ``_generation_config``. + """ + + endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + model: str = proto.Field( + proto.STRING, + number=3, + ) + instances: MutableSequence[struct_pb2.Value] = proto.RepeatedField( + proto.MESSAGE, + number=2, + message=struct_pb2.Value, + ) + contents: MutableSequence[gca_content.Content] = proto.RepeatedField( + proto.MESSAGE, + number=4, + message=gca_content.Content, + ) + system_instruction: gca_content.Content = proto.Field( + proto.MESSAGE, + number=5, + optional=True, + message=gca_content.Content, + ) + tools: MutableSequence[tool.Tool] = proto.RepeatedField( + proto.MESSAGE, + number=6, + message=tool.Tool, + ) + generation_config: gca_content.GenerationConfig = proto.Field( + proto.MESSAGE, + number=7, + optional=True, + message=gca_content.GenerationConfig, + ) + + +class CountTokensResponse(proto.Message): + r"""Response message for + [PredictionService.CountTokens][google.cloud.aiplatform.v1beta1.PredictionService.CountTokens]. + + Attributes: + total_tokens (int): + The total number of tokens counted across all + instances from the request. + total_billable_characters (int): + The total number of billable characters + counted across all instances from the request. + prompt_tokens_details (MutableSequence[google.cloud.aiplatform_v1beta1.types.ModalityTokenCount]): + Output only. List of modalities that were + processed in the request input. + """ + + total_tokens: int = proto.Field( + proto.INT32, + number=1, + ) + total_billable_characters: int = proto.Field( + proto.INT32, + number=2, + ) + prompt_tokens_details: MutableSequence[gca_content.ModalityTokenCount] = ( + proto.RepeatedField( + proto.MESSAGE, + number=3, + message=gca_content.ModalityTokenCount, + ) + ) + + +class GenerateContentRequest(proto.Message): + r"""Request message for [PredictionService.GenerateContent]. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + model (str): + Required. The fully qualified name of the publisher model or + tuned model endpoint to use. + + Publisher model format: + ``projects/{project}/locations/{location}/publishers/*/models/*`` + + Tuned model endpoint format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + contents (MutableSequence[google.cloud.aiplatform_v1beta1.types.Content]): + Required. The content of the current + conversation with the model. + For single-turn queries, this is a single + instance. For multi-turn queries, this is a + repeated field that contains conversation + history + latest request. + system_instruction (google.cloud.aiplatform_v1beta1.types.Content): + Optional. The user provided system + instructions for the model. Note: only text + should be used in parts and content in each part + will be in a separate paragraph. + + This field is a member of `oneof`_ ``_system_instruction``. + cached_content (str): + Optional. The name of the cached content used as context to + serve the prediction. Note: only used in explicit caching, + where users can have control over caching (e.g. what content + to cache) and enjoy guaranteed cost savings. Format: + ``projects/{project}/locations/{location}/cachedContents/{cachedContent}`` + tools (MutableSequence[google.cloud.aiplatform_v1beta1.types.Tool]): + Optional. A list of ``Tools`` the model may use to generate + the next response. + + A ``Tool`` is a piece of code that enables the system to + interact with external systems to perform an action, or set + of actions, outside of knowledge and scope of the model. + tool_config (google.cloud.aiplatform_v1beta1.types.ToolConfig): + Optional. Tool config. This config is shared + for all tools provided in the request. + labels (MutableMapping[str, str]): + Optional. The labels with user-defined + metadata for the request. It is used for billing + and reporting only. + + Label keys and values can be no longer than 63 + characters (Unicode codepoints) and can only + contain lowercase letters, numeric characters, + underscores, and dashes. International + characters are allowed. Label values are + optional. Label keys must start with a letter. + safety_settings (MutableSequence[google.cloud.aiplatform_v1beta1.types.SafetySetting]): + Optional. Per request settings for blocking + unsafe content. Enforced on + GenerateContentResponse.candidates. + model_armor_config (google.cloud.aiplatform_v1beta1.types.ModelArmorConfig): + Optional. Settings for prompt and response sanitization + using the Model Armor service. If supplied, safety_settings + must not be supplied. + generation_config (google.cloud.aiplatform_v1beta1.types.GenerationConfig): + Optional. Generation config. + """ + + model: str = proto.Field( + proto.STRING, + number=5, + ) + contents: MutableSequence[gca_content.Content] = proto.RepeatedField( + proto.MESSAGE, + number=2, + message=gca_content.Content, + ) + system_instruction: gca_content.Content = proto.Field( + proto.MESSAGE, + number=8, + optional=True, + message=gca_content.Content, + ) + cached_content: str = proto.Field( + proto.STRING, + number=9, + ) + tools: MutableSequence[tool.Tool] = proto.RepeatedField( + proto.MESSAGE, + number=6, + message=tool.Tool, + ) + tool_config: tool.ToolConfig = proto.Field( + proto.MESSAGE, + number=7, + message=tool.ToolConfig, + ) + labels: MutableMapping[str, str] = proto.MapField( + proto.STRING, + proto.STRING, + number=10, + ) + safety_settings: MutableSequence[gca_content.SafetySetting] = proto.RepeatedField( + proto.MESSAGE, + number=3, + message=gca_content.SafetySetting, + ) + model_armor_config: gca_content.ModelArmorConfig = proto.Field( + proto.MESSAGE, + number=11, + message=gca_content.ModelArmorConfig, + ) + generation_config: gca_content.GenerationConfig = proto.Field( + proto.MESSAGE, + number=4, + message=gca_content.GenerationConfig, + ) + + +class GenerateContentResponse(proto.Message): + r"""Response message for [PredictionService.GenerateContent]. + + Attributes: + candidates (MutableSequence[google.cloud.aiplatform_v1beta1.types.Candidate]): + Output only. Generated candidates. + model_version (str): + Output only. The model version used to + generate the response. + create_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when the request is + made to the server. + response_id (str): + Output only. response_id is used to identify each response. + It is the encoding of the event_id. + prompt_feedback (google.cloud.aiplatform_v1beta1.types.GenerateContentResponse.PromptFeedback): + Output only. Content filter results for a + prompt sent in the request. Note: Sent only in + the first stream chunk. Only happens when no + candidates were generated due to content + violations. + usage_metadata (google.cloud.aiplatform_v1beta1.types.GenerateContentResponse.UsageMetadata): + Usage metadata about the response(s). + """ + + class PromptFeedback(proto.Message): + r"""Content filter results for a prompt sent in the request. + + Attributes: + block_reason (google.cloud.aiplatform_v1beta1.types.GenerateContentResponse.PromptFeedback.BlockedReason): + Output only. Blocked reason. + safety_ratings (MutableSequence[google.cloud.aiplatform_v1beta1.types.SafetyRating]): + Output only. Safety ratings. + block_reason_message (str): + Output only. A readable block reason message. + """ + + class BlockedReason(proto.Enum): + r"""Blocked reason enumeration. + + Values: + BLOCKED_REASON_UNSPECIFIED (0): + Unspecified blocked reason. + SAFETY (1): + Candidates blocked due to safety. + OTHER (2): + Candidates blocked due to other reason. + BLOCKLIST (3): + Candidates blocked due to the terms which are + included from the terminology blocklist. + PROHIBITED_CONTENT (4): + Candidates blocked due to prohibited content. + MODEL_ARMOR (5): + The user prompt was blocked by Model Armor. + """ + + BLOCKED_REASON_UNSPECIFIED = 0 + SAFETY = 1 + OTHER = 2 + BLOCKLIST = 3 + PROHIBITED_CONTENT = 4 + MODEL_ARMOR = 5 + + block_reason: "GenerateContentResponse.PromptFeedback.BlockedReason" = ( + proto.Field( + proto.ENUM, + number=1, + enum="GenerateContentResponse.PromptFeedback.BlockedReason", + ) + ) + safety_ratings: MutableSequence[gca_content.SafetyRating] = proto.RepeatedField( + proto.MESSAGE, + number=2, + message=gca_content.SafetyRating, + ) + block_reason_message: str = proto.Field( + proto.STRING, + number=3, + ) + + class UsageMetadata(proto.Message): + r"""Usage metadata about response(s). + + Attributes: + prompt_token_count (int): + Number of tokens in the request. When ``cached_content`` is + set, this is still the total effective prompt size meaning + this includes the number of tokens in the cached content. + candidates_token_count (int): + Number of tokens in the response(s). + thoughts_token_count (int): + Output only. Number of tokens present in + thoughts output. + total_token_count (int): + Total token count for prompt and response + candidates. + cached_content_token_count (int): + Output only. Number of tokens in the cached + part in the input (the cached content). + prompt_tokens_details (MutableSequence[google.cloud.aiplatform_v1beta1.types.ModalityTokenCount]): + Output only. List of modalities that were + processed in the request input. + cache_tokens_details (MutableSequence[google.cloud.aiplatform_v1beta1.types.ModalityTokenCount]): + Output only. List of modalities of the cached + content in the request input. + candidates_tokens_details (MutableSequence[google.cloud.aiplatform_v1beta1.types.ModalityTokenCount]): + Output only. List of modalities that were + returned in the response. + """ + + prompt_token_count: int = proto.Field( + proto.INT32, + number=1, + ) + candidates_token_count: int = proto.Field( + proto.INT32, + number=2, + ) + thoughts_token_count: int = proto.Field( + proto.INT32, + number=14, + ) + total_token_count: int = proto.Field( + proto.INT32, + number=3, + ) + cached_content_token_count: int = proto.Field( + proto.INT32, + number=5, + ) + prompt_tokens_details: MutableSequence[gca_content.ModalityTokenCount] = ( + proto.RepeatedField( + proto.MESSAGE, + number=9, + message=gca_content.ModalityTokenCount, + ) + ) + cache_tokens_details: MutableSequence[gca_content.ModalityTokenCount] = ( + proto.RepeatedField( + proto.MESSAGE, + number=10, + message=gca_content.ModalityTokenCount, + ) + ) + candidates_tokens_details: MutableSequence[gca_content.ModalityTokenCount] = ( + proto.RepeatedField( + proto.MESSAGE, + number=11, + message=gca_content.ModalityTokenCount, + ) + ) + + candidates: MutableSequence[gca_content.Candidate] = proto.RepeatedField( + proto.MESSAGE, + number=2, + message=gca_content.Candidate, + ) + model_version: str = proto.Field( + proto.STRING, + number=11, + ) + create_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=12, + message=timestamp_pb2.Timestamp, + ) + response_id: str = proto.Field( + proto.STRING, + number=13, + ) + prompt_feedback: PromptFeedback = proto.Field( + proto.MESSAGE, + number=3, + message=PromptFeedback, + ) + usage_metadata: UsageMetadata = proto.Field( + proto.MESSAGE, + number=4, + message=UsageMetadata, + ) + + +class ChatCompletionsRequest(proto.Message): + r"""Request message for [PredictionService.ChatCompletions] + + Attributes: + endpoint (str): + Required. The name of the endpoint requested to serve the + prediction. Format: + ``projects/{project}/locations/{location}/endpoints/{endpoint}`` + http_body (google.api.httpbody_pb2.HttpBody): + Optional. The prediction input. Supports HTTP + headers and arbitrary data payload. + """ + + endpoint: str = proto.Field( + proto.STRING, + number=1, + ) + http_body: httpbody_pb2.HttpBody = proto.Field( + proto.MESSAGE, + number=2, + message=httpbody_pb2.HttpBody, + ) + + +class PredictLongRunningResponse(proto.Message): + r"""Response message for [PredictionService.PredictLongRunning] + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + generate_video_response (google.cloud.aiplatform_v1beta1.types.GenerateVideoResponse): + The response of the video generation + prediction. + + This field is a member of `oneof`_ ``response``. + """ + + generate_video_response: "GenerateVideoResponse" = proto.Field( + proto.MESSAGE, + number=1, + oneof="response", + message="GenerateVideoResponse", + ) + + +class PredictLongRunningMetadata(proto.Message): + r"""Metadata for PredictLongRunning long running operations.""" + + +class GenerateVideoResponse(proto.Message): + r"""Generate video response. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + generated_samples (MutableSequence[str]): + The cloud storage uris of the generated + videos. + rai_media_filtered_count (int): + Returns if any videos were filtered due to + RAI policies. + + This field is a member of `oneof`_ ``_rai_media_filtered_count``. + rai_media_filtered_reasons (MutableSequence[str]): + Returns rai failure reasons if any. + """ + + generated_samples: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=1, + ) + rai_media_filtered_count: int = proto.Field( + proto.INT32, + number=2, + optional=True, + ) + rai_media_filtered_reasons: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=3, + ) + + +class EmbedContentRequest(proto.Message): + r"""Request message for + [PredictionService.EmbedContent][google.cloud.aiplatform.v1beta1.PredictionService.EmbedContent]. + + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + model (str): + Required. The name of the publisher model requested to serve + the prediction. Format: + ``projects/{project}/locations/{location}/publishers/*/models/*`` + + This field is a member of `oneof`_ ``_model``. + content (google.cloud.aiplatform_v1beta1.types.Content): + Required. Input content to be embedded. + + This field is a member of `oneof`_ ``_content``. + title (str): + Optional. Deprecated: Please use + EmbedContentConfig.title instead. The title for + the text. + + This field is a member of `oneof`_ ``_title``. + task_type (google.cloud.aiplatform_v1beta1.types.EmbedContentRequest.EmbeddingTaskType): + Optional. Deprecated: Please use + EmbedContentConfig.task_type instead. The task type of the + embedding. + + This field is a member of `oneof`_ ``_task_type``. + output_dimensionality (int): + Optional. Deprecated: Please use + EmbedContentConfig.output_dimensionality instead. Reduced + dimension for the output embedding. If set, excessive values + in the output embedding are truncated from the end. + + This field is a member of `oneof`_ ``_output_dimensionality``. + auto_truncate (bool): + Optional. Deprecated: Please use + EmbedContentConfig.auto_truncate instead. Whether to + silently truncate the input content if it's longer than the + maximum sequence length. + + This field is a member of `oneof`_ ``_auto_truncate``. + embed_content_config (google.cloud.aiplatform_v1beta1.types.EmbedContentRequest.EmbedContentConfig): + Optional. Configuration for the EmbedContent + request. + + This field is a member of `oneof`_ ``_embed_content_config``. + """ + + class EmbeddingTaskType(proto.Enum): + r"""Represents a downstream task the embeddings will be used for. + + Values: + UNSPECIFIED (0): + Unset value, which will default to one of the + other enum values. + RETRIEVAL_QUERY (2): + Specifies the given text is a query in a + search/retrieval setting. + RETRIEVAL_DOCUMENT (3): + Specifies the given text is a document from + the corpus being searched. + SEMANTIC_SIMILARITY (4): + Specifies the given text will be used for + STS. + CLASSIFICATION (5): + Specifies that the given text will be + classified. + CLUSTERING (6): + Specifies that the embeddings will be used + for clustering. + QUESTION_ANSWERING (7): + Specifies that the embeddings will be used + for question answering. + FACT_VERIFICATION (8): + Specifies that the embeddings will be used + for fact verification. + CODE_RETRIEVAL_QUERY (9): + Specifies that the embeddings will be used + for code retrieval. + """ + + UNSPECIFIED = 0 + RETRIEVAL_QUERY = 2 + RETRIEVAL_DOCUMENT = 3 + SEMANTIC_SIMILARITY = 4 + CLASSIFICATION = 5 + CLUSTERING = 6 + QUESTION_ANSWERING = 7 + FACT_VERIFICATION = 8 + CODE_RETRIEVAL_QUERY = 9 + + class EmbedContentConfig(proto.Message): + r"""Configurations for the EmbedContent API. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + title (str): + Optional. The title for the text. + + Only applicable to text-only embedding models. + + This field is a member of `oneof`_ ``_title``. + task_type (google.cloud.aiplatform_v1beta1.types.EmbedContentRequest.EmbeddingTaskType): + Optional. The task type of the embedding. + + Only applicable to text-only embedding models. + + This field is a member of `oneof`_ ``_task_type``. + auto_truncate (bool): + Optional. Whether to silently truncate the + input content if it's longer than the maximum + sequence length. + + Only applicable to text-only embedding models. + + This field is a member of `oneof`_ ``_auto_truncate``. + output_dimensionality (int): + Optional. Reduced dimension for the output + embedding. If set, excessive values in the + output embedding are truncated from the end. + + This field is a member of `oneof`_ ``_output_dimensionality``. + document_ocr (bool): + Optional. Whether to enable OCR for document + content. + + This field is a member of `oneof`_ ``_document_ocr``. + audio_track_extraction (bool): + Optional. Whether to extract audio from video + content. + + This field is a member of `oneof`_ ``_audio_track_extraction``. + """ + + title: str = proto.Field( + proto.STRING, + number=1, + optional=True, + ) + task_type: "EmbedContentRequest.EmbeddingTaskType" = proto.Field( + proto.ENUM, + number=2, + optional=True, + enum="EmbedContentRequest.EmbeddingTaskType", + ) + auto_truncate: bool = proto.Field( + proto.BOOL, + number=3, + optional=True, + ) + output_dimensionality: int = proto.Field( + proto.INT32, + number=4, + optional=True, + ) + document_ocr: bool = proto.Field( + proto.BOOL, + number=5, + optional=True, + ) + audio_track_extraction: bool = proto.Field( + proto.BOOL, + number=6, + optional=True, + ) + + model: str = proto.Field( + proto.STRING, + number=1, + optional=True, + ) + content: gca_content.Content = proto.Field( + proto.MESSAGE, + number=2, + optional=True, + message=gca_content.Content, + ) + title: str = proto.Field( + proto.STRING, + number=4, + optional=True, + ) + task_type: EmbeddingTaskType = proto.Field( + proto.ENUM, + number=5, + optional=True, + enum=EmbeddingTaskType, + ) + output_dimensionality: int = proto.Field( + proto.INT32, + number=6, + optional=True, + ) + auto_truncate: bool = proto.Field( + proto.BOOL, + number=7, + optional=True, + ) + embed_content_config: EmbedContentConfig = proto.Field( + proto.MESSAGE, + number=8, + optional=True, + message=EmbedContentConfig, + ) + + +class EmbedContentResponse(proto.Message): + r"""Response message for + [PredictionService.EmbedContent][google.cloud.aiplatform.v1beta1.PredictionService.EmbedContent]. + + Attributes: + embedding (google.cloud.aiplatform_v1beta1.types.EmbedContentResponse.Embedding): + The embedding generated from the input + content. + usage_metadata (google.cloud.aiplatform_v1beta1.types.UsageMetadata): + Usage metadata about the response(s). + truncated (bool): + Whether the input content was truncated + before generating the embedding. + """ + + class Embedding(proto.Message): + r"""A list of floats representing an embedding. + + Attributes: + values (MutableSequence[float]): + Embedding vector values. + """ + + values: MutableSequence[float] = proto.RepeatedField( + proto.FLOAT, + number=1, + ) + + embedding: Embedding = proto.Field( + proto.MESSAGE, + number=1, + message=Embedding, + ) + usage_metadata: gca_usage_metadata.UsageMetadata = proto.Field( + proto.MESSAGE, + number=2, + message=gca_usage_metadata.UsageMetadata, + ) + truncated: bool = proto.Field( + proto.BOOL, + number=4, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/reasoning_engine_service.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/reasoning_engine_service.py new file mode 100644 index 0000000000000000000000000000000000000000..737660721cca5074de3bf060390dc1eab8c29ee3 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/reasoning_engine_service.py @@ -0,0 +1,236 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import operation +from google.cloud.aiplatform_v1beta1.types import ( + reasoning_engine as gca_reasoning_engine, +) +import google.protobuf.field_mask_pb2 as field_mask_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "CreateReasoningEngineRequest", + "CreateReasoningEngineOperationMetadata", + "GetReasoningEngineRequest", + "UpdateReasoningEngineRequest", + "UpdateReasoningEngineOperationMetadata", + "ListReasoningEnginesRequest", + "ListReasoningEnginesResponse", + "DeleteReasoningEngineRequest", + }, +) + + +class CreateReasoningEngineRequest(proto.Message): + r"""Request message for + [ReasoningEngineService.CreateReasoningEngine][google.cloud.aiplatform.v1beta1.ReasoningEngineService.CreateReasoningEngine]. + + Attributes: + parent (str): + Required. The resource name of the Location to create the + ReasoningEngine in. Format: + ``projects/{project}/locations/{location}`` + reasoning_engine (google.cloud.aiplatform_v1beta1.types.ReasoningEngine): + Required. The ReasoningEngine to create. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + reasoning_engine: gca_reasoning_engine.ReasoningEngine = proto.Field( + proto.MESSAGE, + number=2, + message=gca_reasoning_engine.ReasoningEngine, + ) + + +class CreateReasoningEngineOperationMetadata(proto.Message): + r"""Details of + [ReasoningEngineService.CreateReasoningEngine][google.cloud.aiplatform.v1beta1.ReasoningEngineService.CreateReasoningEngine] + operation. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + The common part of the operation metadata. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class GetReasoningEngineRequest(proto.Message): + r"""Request message for + [ReasoningEngineService.GetReasoningEngine][google.cloud.aiplatform.v1beta1.ReasoningEngineService.GetReasoningEngine]. + + Attributes: + name (str): + Required. The name of the ReasoningEngine resource. Format: + ``projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`` + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class UpdateReasoningEngineRequest(proto.Message): + r"""Request message for + [ReasoningEngineService.UpdateReasoningEngine][google.cloud.aiplatform.v1beta1.ReasoningEngineService.UpdateReasoningEngine]. + + Attributes: + reasoning_engine (google.cloud.aiplatform_v1beta1.types.ReasoningEngine): + Required. The ReasoningEngine which replaces + the resource on the server. + update_mask (google.protobuf.field_mask_pb2.FieldMask): + Optional. Mask specifying which fields to + update. + """ + + reasoning_engine: gca_reasoning_engine.ReasoningEngine = proto.Field( + proto.MESSAGE, + number=1, + message=gca_reasoning_engine.ReasoningEngine, + ) + update_mask: field_mask_pb2.FieldMask = proto.Field( + proto.MESSAGE, + number=2, + message=field_mask_pb2.FieldMask, + ) + + +class UpdateReasoningEngineOperationMetadata(proto.Message): + r"""Details of + [ReasoningEngineService.UpdateReasoningEngine][google.cloud.aiplatform.v1beta1.ReasoningEngineService.UpdateReasoningEngine] + operation. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + The common part of the operation metadata. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class ListReasoningEnginesRequest(proto.Message): + r"""Request message for + [ReasoningEngineService.ListReasoningEngines][google.cloud.aiplatform.v1beta1.ReasoningEngineService.ListReasoningEngines]. + + Attributes: + parent (str): + Required. The resource name of the Location to list the + ReasoningEngines from. Format: + ``projects/{project}/locations/{location}`` + filter (str): + Optional. The standard list filter. More detail in + `AIP-160 `__. + page_size (int): + Optional. The standard list page size. + page_token (str): + Optional. The standard list page token. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + filter: str = proto.Field( + proto.STRING, + number=2, + ) + page_size: int = proto.Field( + proto.INT32, + number=3, + ) + page_token: str = proto.Field( + proto.STRING, + number=4, + ) + + +class ListReasoningEnginesResponse(proto.Message): + r"""Response message for + [ReasoningEngineService.ListReasoningEngines][google.cloud.aiplatform.v1beta1.ReasoningEngineService.ListReasoningEngines] + + Attributes: + reasoning_engines (MutableSequence[google.cloud.aiplatform_v1beta1.types.ReasoningEngine]): + List of ReasoningEngines in the requested + page. + next_page_token (str): + A token to retrieve the next page of results. Pass to + [ListReasoningEnginesRequest.page_token][google.cloud.aiplatform.v1beta1.ListReasoningEnginesRequest.page_token] + to obtain that page. + """ + + @property + def raw_page(self): + return self + + reasoning_engines: MutableSequence[gca_reasoning_engine.ReasoningEngine] = ( + proto.RepeatedField( + proto.MESSAGE, + number=1, + message=gca_reasoning_engine.ReasoningEngine, + ) + ) + next_page_token: str = proto.Field( + proto.STRING, + number=2, + ) + + +class DeleteReasoningEngineRequest(proto.Message): + r"""Request message for + [ReasoningEngineService.DeleteReasoningEngine][google.cloud.aiplatform.v1beta1.ReasoningEngineService.DeleteReasoningEngine]. + + Attributes: + name (str): + Required. The name of the ReasoningEngine resource to be + deleted. Format: + ``projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`` + force (bool): + Optional. If set to true, child resources of this reasoning + engine will also be deleted. Otherwise, the request will + fail with FAILED_PRECONDITION error when the reasoning + engine has undeleted child resources. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + force: bool = proto.Field( + proto.BOOL, + number=2, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/session_service.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/session_service.py new file mode 100644 index 0000000000000000000000000000000000000000..be67687627ebde93aa09c3f4bd22adc5fbd730ad --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/session_service.py @@ -0,0 +1,365 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import operation +from google.cloud.aiplatform_v1beta1.types import session as gca_session +import google.protobuf.field_mask_pb2 as field_mask_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "CreateSessionRequest", + "CreateSessionOperationMetadata", + "GetSessionRequest", + "ListSessionsRequest", + "ListSessionsResponse", + "UpdateSessionRequest", + "DeleteSessionRequest", + "ListEventsRequest", + "ListEventsResponse", + "AppendEventRequest", + "AppendEventResponse", + }, +) + + +class CreateSessionRequest(proto.Message): + r"""Request message for + [SessionService.CreateSession][google.cloud.aiplatform.v1beta1.SessionService.CreateSession]. + + Attributes: + parent (str): + Required. The resource name of the location to create the + session in. Format: + ``projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`` + session (google.cloud.aiplatform_v1beta1.types.Session): + Required. The session to create. + session_id (str): + Optional. The user defined ID to use for session, which will + become the final component of the session resource name. If + not provided, Vertex AI will generate a value for this ID. + + This value may be up to 63 characters, and valid characters + are ``[a-z0-9-]``. The first character must be a letter, and + the last character must be a letter or number. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + session: gca_session.Session = proto.Field( + proto.MESSAGE, + number=2, + message=gca_session.Session, + ) + session_id: str = proto.Field( + proto.STRING, + number=3, + ) + + +class CreateSessionOperationMetadata(proto.Message): + r"""Metadata associated with the + [SessionService.CreateSession][google.cloud.aiplatform.v1beta1.SessionService.CreateSession] + operation. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + The common part of the operation metadata. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class GetSessionRequest(proto.Message): + r"""Request message for + [SessionService.GetSession][google.cloud.aiplatform.v1beta1.SessionService.GetSession]. + + Attributes: + name (str): + Required. The resource name of the session. Format: + ``projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`` + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class ListSessionsRequest(proto.Message): + r"""Request message for + [SessionService.ListSessions][google.cloud.aiplatform.v1beta1.SessionService.ListSessions]. + + Attributes: + parent (str): + Required. The resource name of the location to list sessions + from. Format: + ``projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`` + page_size (int): + Optional. The maximum number of sessions to + return. The service may return fewer than this + value. If unspecified, at most 100 sessions will + be returned. + page_token (str): + Optional. The + [next_page_token][google.cloud.aiplatform.v1beta1.ListSessionsResponse.next_page_token] + value returned from a previous list + [SessionService.ListSessions][google.cloud.aiplatform.v1beta1.SessionService.ListSessions] + call. + filter (str): + Optional. The standard list filter. Supported fields: \* + ``display_name`` \* ``user_id`` \* ``labels`` + + Example: ``display_name="abc"``, ``user_id="123"``, + ``labels.key="value"``. + order_by (str): + Optional. A comma-separated list of fields to order by, + sorted in ascending order. Use "desc" after a field name for + descending. Supported fields: + + - ``create_time`` + - ``update_time`` + + Example: ``create_time desc``. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + page_size: int = proto.Field( + proto.INT32, + number=2, + ) + page_token: str = proto.Field( + proto.STRING, + number=3, + ) + filter: str = proto.Field( + proto.STRING, + number=4, + ) + order_by: str = proto.Field( + proto.STRING, + number=5, + ) + + +class ListSessionsResponse(proto.Message): + r"""Response message for + [SessionService.ListSessions][google.cloud.aiplatform.v1beta1.SessionService.ListSessions]. + + Attributes: + sessions (MutableSequence[google.cloud.aiplatform_v1beta1.types.Session]): + A list of sessions matching the request. + next_page_token (str): + A token, which can be sent as + [ListSessionsRequest.page_token][google.cloud.aiplatform.v1beta1.ListSessionsRequest.page_token] + to retrieve the next page. Absence of this field indicates + there are no subsequent pages. + """ + + @property + def raw_page(self): + return self + + sessions: MutableSequence[gca_session.Session] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=gca_session.Session, + ) + next_page_token: str = proto.Field( + proto.STRING, + number=2, + ) + + +class UpdateSessionRequest(proto.Message): + r"""Request message for + [SessionService.UpdateSession][google.cloud.aiplatform.v1beta1.SessionService.UpdateSession]. + + Attributes: + session (google.cloud.aiplatform_v1beta1.types.Session): + Required. The session to update. Format: + ``projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`` + update_mask (google.protobuf.field_mask_pb2.FieldMask): + Optional. Field mask is used to control which + fields get updated. If the mask is not present, + all fields will be updated. + """ + + session: gca_session.Session = proto.Field( + proto.MESSAGE, + number=1, + message=gca_session.Session, + ) + update_mask: field_mask_pb2.FieldMask = proto.Field( + proto.MESSAGE, + number=2, + message=field_mask_pb2.FieldMask, + ) + + +class DeleteSessionRequest(proto.Message): + r"""Request message for + [SessionService.DeleteSession][google.cloud.aiplatform.v1beta1.SessionService.DeleteSession]. + + Attributes: + name (str): + Required. The resource name of the session. Format: + ``projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`` + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class ListEventsRequest(proto.Message): + r"""Request message for + [SessionService.ListEvents][google.cloud.aiplatform.v1beta1.SessionService.ListEvents]. + + Attributes: + parent (str): + Required. The resource name of the session to list events + from. Format: + ``projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`` + page_size (int): + Optional. The maximum number of events to + return. The service may return fewer than this + value. If unspecified, at most 100 events will + be returned. These events are ordered by + timestamp in ascending order. + page_token (str): + Optional. The + [next_page_token][google.cloud.aiplatform.v1beta1.ListEventsResponse.next_page_token] + value returned from a previous list + [SessionService.ListEvents][google.cloud.aiplatform.v1beta1.SessionService.ListEvents] + call. + filter (str): + Optional. The standard list filter. Supported fields: \* + ``timestamp`` range (i.e. + ``timestamp>="2025-01-31T11:30:00-04:00"`` where the + timestamp is in RFC 3339 format) + + More detail in `AIP-160 `__. + order_by (str): + Optional. A comma-separated list of fields to order by, + sorted in ascending order. Use "desc" after a field name for + descending. Supported fields: + + - ``timestamp`` + + Example: ``timestamp desc``. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + page_size: int = proto.Field( + proto.INT32, + number=2, + ) + page_token: str = proto.Field( + proto.STRING, + number=3, + ) + filter: str = proto.Field( + proto.STRING, + number=4, + ) + order_by: str = proto.Field( + proto.STRING, + number=5, + ) + + +class ListEventsResponse(proto.Message): + r"""Response message for + [SessionService.ListEvents][google.cloud.aiplatform.v1beta1.SessionService.ListEvents]. + + Attributes: + session_events (MutableSequence[google.cloud.aiplatform_v1beta1.types.SessionEvent]): + A list of events matching the request. + Ordered by timestamp in ascending order. + next_page_token (str): + A token, which can be sent as + [ListEventsRequest.page_token][google.cloud.aiplatform.v1beta1.ListEventsRequest.page_token] + to retrieve the next page. Absence of this field indicates + there are no subsequent pages. + """ + + @property + def raw_page(self): + return self + + session_events: MutableSequence[gca_session.SessionEvent] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message=gca_session.SessionEvent, + ) + next_page_token: str = proto.Field( + proto.STRING, + number=2, + ) + + +class AppendEventRequest(proto.Message): + r"""Request message for + [SessionService.AppendEvent][google.cloud.aiplatform.v1beta1.SessionService.AppendEvent]. + + Attributes: + name (str): + Required. The resource name of the session to append event + to. Format: + ``projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`` + event (google.cloud.aiplatform_v1beta1.types.SessionEvent): + Required. The event to append to the session. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + event: gca_session.SessionEvent = proto.Field( + proto.MESSAGE, + number=2, + message=gca_session.SessionEvent, + ) + + +class AppendEventResponse(proto.Message): + r"""Response message for + [SessionService.AppendEvent][google.cloud.aiplatform.v1beta1.SessionService.AppendEvent]. + + """ + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/specialist_pool_service.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/specialist_pool_service.py new file mode 100644 index 0000000000000000000000000000000000000000..d9ae174344d652d45a529260a835e5788f3264d4 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/specialist_pool_service.py @@ -0,0 +1,243 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import operation +from google.cloud.aiplatform_v1beta1.types import specialist_pool as gca_specialist_pool +import google.protobuf.field_mask_pb2 as field_mask_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "CreateSpecialistPoolRequest", + "CreateSpecialistPoolOperationMetadata", + "GetSpecialistPoolRequest", + "ListSpecialistPoolsRequest", + "ListSpecialistPoolsResponse", + "DeleteSpecialistPoolRequest", + "UpdateSpecialistPoolRequest", + "UpdateSpecialistPoolOperationMetadata", + }, +) + + +class CreateSpecialistPoolRequest(proto.Message): + r"""Request message for + [SpecialistPoolService.CreateSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.CreateSpecialistPool]. + + Attributes: + parent (str): + Required. The parent Project name for the new + SpecialistPool. The form is + ``projects/{project}/locations/{location}``. + specialist_pool (google.cloud.aiplatform_v1beta1.types.SpecialistPool): + Required. The SpecialistPool to create. + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + specialist_pool: gca_specialist_pool.SpecialistPool = proto.Field( + proto.MESSAGE, + number=2, + message=gca_specialist_pool.SpecialistPool, + ) + + +class CreateSpecialistPoolOperationMetadata(proto.Message): + r"""Runtime operation information for + [SpecialistPoolService.CreateSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.CreateSpecialistPool]. + + Attributes: + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + The operation generic information. + """ + + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=1, + message=operation.GenericOperationMetadata, + ) + + +class GetSpecialistPoolRequest(proto.Message): + r"""Request message for + [SpecialistPoolService.GetSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.GetSpecialistPool]. + + Attributes: + name (str): + Required. The name of the SpecialistPool resource. The form + is + ``projects/{project}/locations/{location}/specialistPools/{specialist_pool}``. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + + +class ListSpecialistPoolsRequest(proto.Message): + r"""Request message for + [SpecialistPoolService.ListSpecialistPools][google.cloud.aiplatform.v1beta1.SpecialistPoolService.ListSpecialistPools]. + + Attributes: + parent (str): + Required. The name of the SpecialistPool's parent resource. + Format: ``projects/{project}/locations/{location}`` + page_size (int): + The standard list page size. + page_token (str): + The standard list page token. Typically obtained by + [ListSpecialistPoolsResponse.next_page_token][google.cloud.aiplatform.v1beta1.ListSpecialistPoolsResponse.next_page_token] + of the previous + [SpecialistPoolService.ListSpecialistPools][google.cloud.aiplatform.v1beta1.SpecialistPoolService.ListSpecialistPools] + call. Return first page if empty. + read_mask (google.protobuf.field_mask_pb2.FieldMask): + Mask specifying which fields to read. + FieldMask represents a set of + """ + + parent: str = proto.Field( + proto.STRING, + number=1, + ) + page_size: int = proto.Field( + proto.INT32, + number=2, + ) + page_token: str = proto.Field( + proto.STRING, + number=3, + ) + read_mask: field_mask_pb2.FieldMask = proto.Field( + proto.MESSAGE, + number=4, + message=field_mask_pb2.FieldMask, + ) + + +class ListSpecialistPoolsResponse(proto.Message): + r"""Response message for + [SpecialistPoolService.ListSpecialistPools][google.cloud.aiplatform.v1beta1.SpecialistPoolService.ListSpecialistPools]. + + Attributes: + specialist_pools (MutableSequence[google.cloud.aiplatform_v1beta1.types.SpecialistPool]): + A list of SpecialistPools that matches the + specified filter in the request. + next_page_token (str): + The standard List next-page token. + """ + + @property + def raw_page(self): + return self + + specialist_pools: MutableSequence[gca_specialist_pool.SpecialistPool] = ( + proto.RepeatedField( + proto.MESSAGE, + number=1, + message=gca_specialist_pool.SpecialistPool, + ) + ) + next_page_token: str = proto.Field( + proto.STRING, + number=2, + ) + + +class DeleteSpecialistPoolRequest(proto.Message): + r"""Request message for + [SpecialistPoolService.DeleteSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.DeleteSpecialistPool]. + + Attributes: + name (str): + Required. The resource name of the SpecialistPool to delete. + Format: + ``projects/{project}/locations/{location}/specialistPools/{specialist_pool}`` + force (bool): + If set to true, any specialist managers in + this SpecialistPool will also be deleted. + (Otherwise, the request will only work if the + SpecialistPool has no specialist managers.) + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + force: bool = proto.Field( + proto.BOOL, + number=2, + ) + + +class UpdateSpecialistPoolRequest(proto.Message): + r"""Request message for + [SpecialistPoolService.UpdateSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.UpdateSpecialistPool]. + + Attributes: + specialist_pool (google.cloud.aiplatform_v1beta1.types.SpecialistPool): + Required. The SpecialistPool which replaces + the resource on the server. + update_mask (google.protobuf.field_mask_pb2.FieldMask): + Required. The update mask applies to the + resource. + """ + + specialist_pool: gca_specialist_pool.SpecialistPool = proto.Field( + proto.MESSAGE, + number=1, + message=gca_specialist_pool.SpecialistPool, + ) + update_mask: field_mask_pb2.FieldMask = proto.Field( + proto.MESSAGE, + number=2, + message=field_mask_pb2.FieldMask, + ) + + +class UpdateSpecialistPoolOperationMetadata(proto.Message): + r"""Runtime operation metadata for + [SpecialistPoolService.UpdateSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.UpdateSpecialistPool]. + + Attributes: + specialist_pool (str): + Output only. The name of the SpecialistPool to which the + specialists are being added. Format: + ``projects/{project_id}/locations/{location_id}/specialistPools/{specialist_pool}`` + generic_metadata (google.cloud.aiplatform_v1beta1.types.GenericOperationMetadata): + The operation generic information. + """ + + specialist_pool: str = proto.Field( + proto.STRING, + number=1, + ) + generic_metadata: operation.GenericOperationMetadata = proto.Field( + proto.MESSAGE, + number=2, + message=operation.GenericOperationMetadata, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/tensorboard.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/tensorboard.py new file mode 100644 index 0000000000000000000000000000000000000000..60cbc3be23cf996d95bd82e1888fbd518b31d755 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/tensorboard.py @@ -0,0 +1,159 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import encryption_spec as gca_encryption_spec +import google.protobuf.timestamp_pb2 as timestamp_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "Tensorboard", + }, +) + + +class Tensorboard(proto.Message): + r"""Tensorboard is a physical database that stores users' + training metrics. A default Tensorboard is provided in each + region of a Google Cloud project. If needed users can also + create extra Tensorboards in their projects. + + Attributes: + name (str): + Output only. Name of the Tensorboard. Format: + ``projects/{project}/locations/{location}/tensorboards/{tensorboard}`` + display_name (str): + Required. User provided name of this + Tensorboard. + description (str): + Description of this Tensorboard. + encryption_spec (google.cloud.aiplatform_v1beta1.types.EncryptionSpec): + Customer-managed encryption key spec for a + Tensorboard. If set, this Tensorboard and all + sub-resources of this Tensorboard will be + secured by this key. + blob_storage_path_prefix (str): + Output only. Consumer project Cloud Storage + path prefix used to store blob data, which can + either be a bucket or directory. Does not end + with a '/'. + run_count (int): + Output only. The number of Runs stored in + this Tensorboard. + create_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when this Tensorboard + was created. + update_time (google.protobuf.timestamp_pb2.Timestamp): + Output only. Timestamp when this Tensorboard + was last updated. + labels (MutableMapping[str, str]): + The labels with user-defined metadata to + organize your Tensorboards. + Label keys and values can be no longer than 64 + characters (Unicode codepoints), can only + contain lowercase letters, numeric characters, + underscores and dashes. International characters + are allowed. No more than 64 user labels can be + associated with one Tensorboard (System labels + are excluded). + + See https://goo.gl/xmQnxf for more information + and examples of labels. System reserved label + keys are prefixed with + "aiplatform.googleapis.com/" and are immutable. + etag (str): + Used to perform a consistent + read-modify-write updates. If not set, a blind + "overwrite" update happens. + is_default (bool): + Used to indicate if the TensorBoard instance + is the default one. Each project & region can + have at most one default TensorBoard instance. + Creation of a default TensorBoard instance and + updating an existing TensorBoard instance to be + default will mark all other TensorBoard + instances (if any) as non default. + satisfies_pzs (bool): + Output only. Reserved for future use. + satisfies_pzi (bool): + Output only. Reserved for future use. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + display_name: str = proto.Field( + proto.STRING, + number=2, + ) + description: str = proto.Field( + proto.STRING, + number=3, + ) + encryption_spec: gca_encryption_spec.EncryptionSpec = proto.Field( + proto.MESSAGE, + number=11, + message=gca_encryption_spec.EncryptionSpec, + ) + blob_storage_path_prefix: str = proto.Field( + proto.STRING, + number=10, + ) + run_count: int = proto.Field( + proto.INT32, + number=5, + ) + create_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=6, + message=timestamp_pb2.Timestamp, + ) + update_time: timestamp_pb2.Timestamp = proto.Field( + proto.MESSAGE, + number=7, + message=timestamp_pb2.Timestamp, + ) + labels: MutableMapping[str, str] = proto.MapField( + proto.STRING, + proto.STRING, + number=8, + ) + etag: str = proto.Field( + proto.STRING, + number=9, + ) + is_default: bool = proto.Field( + proto.BOOL, + number=12, + ) + satisfies_pzs: bool = proto.Field( + proto.BOOL, + number=13, + ) + satisfies_pzi: bool = proto.Field( + proto.BOOL, + number=14, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/tool.py b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/tool.py new file mode 100644 index 0000000000000000000000000000000000000000..3f06b9348473a58bf9d4c2f5acb1fa853b634c50 --- /dev/null +++ b/data/conda_envs/evalclaw/lib/python3.11/site-packages/google/cloud/aiplatform_v1beta1/types/tool.py @@ -0,0 +1,1465 @@ +# -*- coding: utf-8 -*- +# 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. +# +from __future__ import annotations + +from typing import MutableMapping, MutableSequence + +import proto # type: ignore + +from google.cloud.aiplatform_v1beta1.types import openapi +import google.protobuf.struct_pb2 as struct_pb2 # type: ignore +import google.type.latlng_pb2 as latlng_pb2 # type: ignore + + +__protobuf__ = proto.module( + package="google.cloud.aiplatform.v1beta1", + manifest={ + "Tool", + "UrlContext", + "ToolUseExample", + "FunctionDeclaration", + "FunctionCall", + "PartialArg", + "FunctionResponsePart", + "FunctionResponseBlob", + "FunctionResponseFileData", + "FunctionResponse", + "ExecutableCode", + "CodeExecutionResult", + "Retrieval", + "VertexRagStore", + "VertexAISearch", + "GoogleSearchRetrieval", + "GoogleMaps", + "EnterpriseWebSearch", + "DynamicRetrievalConfig", + "ToolConfig", + "FunctionCallingConfig", + "RetrievalConfig", + "RagRetrievalConfig", + }, +) + + +class Tool(proto.Message): + r"""Tool details that the model may use to generate response. + + A ``Tool`` is a piece of code that enables the system to interact + with external systems to perform an action, or set of actions, + outside of knowledge and scope of the model. A Tool object should + contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval + or GoogleSearchRetrieval). + + Attributes: + function_declarations (MutableSequence[google.cloud.aiplatform_v1beta1.types.FunctionDeclaration]): + Optional. Function tool type. One or more function + declarations to be passed to the model along with the + current user query. Model may decide to call a subset of + these functions by populating + [FunctionCall][google.cloud.aiplatform.v1beta1.Part.function_call] + in the response. User should provide a + [FunctionResponse][google.cloud.aiplatform.v1beta1.Part.function_response] + for each function call in the next turn. Based on the + function responses, Model will generate the final response + back to the user. Maximum 128 function declarations can be + provided. + retrieval (google.cloud.aiplatform_v1beta1.types.Retrieval): + Optional. Retrieval tool type. + System will always execute the provided + retrieval tool(s) to get external knowledge to + answer the prompt. Retrieval results are + presented to the model for generation. + google_search (google.cloud.aiplatform_v1beta1.types.Tool.GoogleSearch): + Optional. GoogleSearch tool type. + Tool to support Google Search in Model. Powered + by Google. + google_search_retrieval (google.cloud.aiplatform_v1beta1.types.GoogleSearchRetrieval): + Optional. GoogleSearchRetrieval tool type. + Specialized retrieval tool that is powered by + Google search. + google_maps (google.cloud.aiplatform_v1beta1.types.GoogleMaps): + Optional. GoogleMaps tool type. + Tool to support Google Maps in Model. + enterprise_web_search (google.cloud.aiplatform_v1beta1.types.EnterpriseWebSearch): + Optional. Tool to support searching public + web data, powered by Vertex AI Search and Sec4 + compliance. + code_execution (google.cloud.aiplatform_v1beta1.types.Tool.CodeExecution): + Optional. CodeExecution tool type. + Enables the model to execute code as part of + generation. + url_context (google.cloud.aiplatform_v1beta1.types.UrlContext): + Optional. Tool to support URL context + retrieval. + computer_use (google.cloud.aiplatform_v1beta1.types.Tool.ComputerUse): + Optional. Tool to support the model + interacting directly with the computer. If + enabled, it automatically populates computer-use + specific Function Declarations. + """ + + class PhishBlockThreshold(proto.Enum): + r"""These are available confidence level user can set to block + malicious urls with chosen confidence and above. For + understanding different confidence of webrisk, please refer to + https://cloud.google.com/web-risk/docs/reference/rpc/google.cloud.webrisk.v1eap1#confidencelevel + + Values: + PHISH_BLOCK_THRESHOLD_UNSPECIFIED (0): + Defaults to unspecified. + BLOCK_LOW_AND_ABOVE (30): + Blocks Low and above confidence URL that is + risky. + BLOCK_MEDIUM_AND_ABOVE (40): + Blocks Medium and above confidence URL that + is risky. + BLOCK_HIGH_AND_ABOVE (50): + Blocks High and above confidence URL that is + risky. + BLOCK_HIGHER_AND_ABOVE (55): + Blocks Higher and above confidence URL that + is risky. + BLOCK_VERY_HIGH_AND_ABOVE (60): + Blocks Very high and above confidence URL + that is risky. + BLOCK_ONLY_EXTREMELY_HIGH (100): + Blocks Extremely high confidence URL that is + risky. + """ + + PHISH_BLOCK_THRESHOLD_UNSPECIFIED = 0 + BLOCK_LOW_AND_ABOVE = 30 + BLOCK_MEDIUM_AND_ABOVE = 40 + BLOCK_HIGH_AND_ABOVE = 50 + BLOCK_HIGHER_AND_ABOVE = 55 + BLOCK_VERY_HIGH_AND_ABOVE = 60 + BLOCK_ONLY_EXTREMELY_HIGH = 100 + + class GoogleSearch(proto.Message): + r"""GoogleSearch tool type. + Tool to support Google Search in Model. Powered by Google. + + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + exclude_domains (MutableSequence[str]): + Optional. List of domains to be excluded from the search + results. The default limit is 2000 domains. Example: + ["amazon.com", "facebook.com"]. + blocking_confidence (google.cloud.aiplatform_v1beta1.types.Tool.PhishBlockThreshold): + Optional. Sites with confidence level chosen + & above this value will be blocked from the + search results. + + This field is a member of `oneof`_ ``_blocking_confidence``. + """ + + exclude_domains: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=3, + ) + blocking_confidence: "Tool.PhishBlockThreshold" = proto.Field( + proto.ENUM, + number=4, + optional=True, + enum="Tool.PhishBlockThreshold", + ) + + class CodeExecution(proto.Message): + r"""Tool that executes code generated by the model, and automatically + returns the result to the model. + + See also [ExecutableCode]and [CodeExecutionResult] which are input + and output to this tool. + + """ + + class ComputerUse(proto.Message): + r"""Tool to support computer use. + + Attributes: + environment (google.cloud.aiplatform_v1beta1.types.Tool.ComputerUse.Environment): + Required. The environment being operated. + excluded_predefined_functions (MutableSequence[str]): + Optional. By default, `predefined + functions `__ + are included in the final model call. Some of them can be + explicitly excluded from being automatically included. This + can serve two purposes: + + 1. Using a more restricted / different action space. + 2. Improving the definitions / instructions of predefined + functions. + """ + + class Environment(proto.Enum): + r"""Represents the environment being operated, such as a web + browser. + + Values: + ENVIRONMENT_UNSPECIFIED (0): + Defaults to browser. + ENVIRONMENT_BROWSER (1): + Operates in a web browser. + """ + + ENVIRONMENT_UNSPECIFIED = 0 + ENVIRONMENT_BROWSER = 1 + + environment: "Tool.ComputerUse.Environment" = proto.Field( + proto.ENUM, + number=1, + enum="Tool.ComputerUse.Environment", + ) + excluded_predefined_functions: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=2, + ) + + function_declarations: MutableSequence["FunctionDeclaration"] = proto.RepeatedField( + proto.MESSAGE, + number=1, + message="FunctionDeclaration", + ) + retrieval: "Retrieval" = proto.Field( + proto.MESSAGE, + number=2, + message="Retrieval", + ) + google_search: GoogleSearch = proto.Field( + proto.MESSAGE, + number=7, + message=GoogleSearch, + ) + google_search_retrieval: "GoogleSearchRetrieval" = proto.Field( + proto.MESSAGE, + number=3, + message="GoogleSearchRetrieval", + ) + google_maps: "GoogleMaps" = proto.Field( + proto.MESSAGE, + number=5, + message="GoogleMaps", + ) + enterprise_web_search: "EnterpriseWebSearch" = proto.Field( + proto.MESSAGE, + number=6, + message="EnterpriseWebSearch", + ) + code_execution: CodeExecution = proto.Field( + proto.MESSAGE, + number=4, + message=CodeExecution, + ) + url_context: "UrlContext" = proto.Field( + proto.MESSAGE, + number=10, + message="UrlContext", + ) + computer_use: ComputerUse = proto.Field( + proto.MESSAGE, + number=11, + message=ComputerUse, + ) + + +class UrlContext(proto.Message): + r"""Tool to support URL context.""" + + +class ToolUseExample(proto.Message): + r"""A single example of the tool usage. + + This message has `oneof`_ fields (mutually exclusive fields). + For each oneof, at most one member field can be set at the same time. + Setting any member of the oneof automatically clears all other + members. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + extension_operation (google.cloud.aiplatform_v1beta1.types.ToolUseExample.ExtensionOperation): + Extension operation to call. + + This field is a member of `oneof`_ ``Target``. + function_name (str): + Function name to call. + + This field is a member of `oneof`_ ``Target``. + display_name (str): + Required. The display name for example. + query (str): + Required. Query that should be routed to this + tool. + request_params (google.protobuf.struct_pb2.Struct): + Request parameters used for executing this + tool. + response_params (google.protobuf.struct_pb2.Struct): + Response parameters generated by this tool. + response_summary (str): + Summary of the tool response to the user + query. + """ + + class ExtensionOperation(proto.Message): + r"""Identifies one operation of the extension. + + Attributes: + extension (str): + Resource name of the extension. + operation_id (str): + Required. Operation ID of the extension. + """ + + extension: str = proto.Field( + proto.STRING, + number=1, + ) + operation_id: str = proto.Field( + proto.STRING, + number=2, + ) + + extension_operation: ExtensionOperation = proto.Field( + proto.MESSAGE, + number=10, + oneof="Target", + message=ExtensionOperation, + ) + function_name: str = proto.Field( + proto.STRING, + number=11, + oneof="Target", + ) + display_name: str = proto.Field( + proto.STRING, + number=1, + ) + query: str = proto.Field( + proto.STRING, + number=2, + ) + request_params: struct_pb2.Struct = proto.Field( + proto.MESSAGE, + number=3, + message=struct_pb2.Struct, + ) + response_params: struct_pb2.Struct = proto.Field( + proto.MESSAGE, + number=4, + message=struct_pb2.Struct, + ) + response_summary: str = proto.Field( + proto.STRING, + number=5, + ) + + +class FunctionDeclaration(proto.Message): + r"""Structured representation of a function declaration as defined by + the `OpenAPI 3.0 + specification `__. Included in + this declaration are the function name, description, parameters and + response type. This FunctionDeclaration is a representation of a + block of code that can be used as a ``Tool`` by the model and + executed by the client. + + Attributes: + name (str): + Required. The name of the function to call. + Must start with a letter or an underscore. + Must be a-z, A-Z, 0-9, or contain underscores, + dots and dashes, with a maximum length of 64. + description (str): + Optional. Description and purpose of the + function. Model uses it to decide how and + whether to call the function. + parameters (google.cloud.aiplatform_v1beta1.types.Schema): + Optional. Describes the parameters to this + function in JSON Schema Object format. Reflects + the Open API 3.03 Parameter Object. string Key: + the name of the parameter. Parameter names are + case sensitive. Schema Value: the Schema + defining the type used for the parameter. For + function with no parameters, this can be left + unset. Parameter names must start with a letter + or an underscore and must only contain chars + a-z, A-Z, 0-9, or underscores with a maximum + length of 64. Example with 1 required and 1 + optional parameter: type: OBJECT properties: + + param1: + + type: STRING + param2: + + type: INTEGER + required: + + - param1 + parameters_json_schema (google.protobuf.struct_pb2.Value): + Optional. Describes the parameters to the function in JSON + Schema format. The schema must describe an object where the + properties are the parameters to the function. For example: + + :: + + { + "type": "object", + "properties": { + "name": { "type": "string" }, + "age": { "type": "integer" } + }, + "additionalProperties": false, + "required": ["name", "age"], + "propertyOrdering": ["name", "age"] + } + + This field is mutually exclusive with ``parameters``. + response (google.cloud.aiplatform_v1beta1.types.Schema): + Optional. Describes the output from this + function in JSON Schema format. Reflects the + Open API 3.03 Response Object. The Schema + defines the type used for the response value of + the function. + response_json_schema (google.protobuf.struct_pb2.Value): + Optional. Describes the output from this function in JSON + Schema format. The value specified by the schema is the + response value of the function. + + This field is mutually exclusive with ``response``. + """ + + name: str = proto.Field( + proto.STRING, + number=1, + ) + description: str = proto.Field( + proto.STRING, + number=2, + ) + parameters: openapi.Schema = proto.Field( + proto.MESSAGE, + number=3, + message=openapi.Schema, + ) + parameters_json_schema: struct_pb2.Value = proto.Field( + proto.MESSAGE, + number=5, + message=struct_pb2.Value, + ) + response: openapi.Schema = proto.Field( + proto.MESSAGE, + number=4, + message=openapi.Schema, + ) + response_json_schema: struct_pb2.Value = proto.Field( + proto.MESSAGE, + number=6, + message=struct_pb2.Value, + ) + + +class FunctionCall(proto.Message): + r"""A predicted [FunctionCall] returned from the model that contains a + string representing the [FunctionDeclaration.name] and a structured + JSON object containing the parameters and their values. + + Attributes: + id (str): + Optional. The unique id of the function call. If populated, + the client to execute the ``function_call`` and return the + response with the matching ``id``. + name (str): + Optional. The name of the function to call. Matches + [FunctionDeclaration.name]. + args (google.protobuf.struct_pb2.Struct): + Optional. The function parameters and values in JSON object + format. See [FunctionDeclaration.parameters] for parameter + details. + partial_args (MutableSequence[google.cloud.aiplatform_v1beta1.types.PartialArg]): + Optional. The partial argument value of the + function call. If provided, represents the + arguments/fields that are streamed + incrementally. + will_continue (bool): + Optional. Whether this is the last part of + the FunctionCall. If true, another partial + message for the current FunctionCall is expected + to follow. + """ + + id: str = proto.Field( + proto.STRING, + number=3, + ) + name: str = proto.Field( + proto.STRING, + number=1, + ) + args: struct_pb2.Struct = proto.Field( + proto.MESSAGE, + number=2, + message=struct_pb2.Struct, + ) + partial_args: MutableSequence["PartialArg"] = proto.RepeatedField( + proto.MESSAGE, + number=4, + message="PartialArg", + ) + will_continue: bool = proto.Field( + proto.BOOL, + number=5, + ) + + +class PartialArg(proto.Message): + r"""Partial argument value of the function call. + + This message has `oneof`_ fields (mutually exclusive fields). + For each oneof, at most one member field can be set at the same time. + Setting any member of the oneof automatically clears all other + members. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + null_value (google.protobuf.struct_pb2.NullValue): + Optional. Represents a null value. + + This field is a member of `oneof`_ ``delta``. + number_value (float): + Optional. Represents a double value. + + This field is a member of `oneof`_ ``delta``. + string_value (str): + Optional. Represents a string value. + + This field is a member of `oneof`_ ``delta``. + bool_value (bool): + Optional. Represents a boolean value. + + This field is a member of `oneof`_ ``delta``. + json_path (str): + Required. A JSON Path (RFC 9535) to the argument being + streamed. https://datatracker.ietf.org/doc/html/rfc9535. + e.g. "$.foo.bar[0].data". + will_continue (bool): + Optional. Whether this is not the last part of the same + json_path. If true, another PartialArg message for the + current json_path is expected to follow. + """ + + null_value: struct_pb2.NullValue = proto.Field( + proto.ENUM, + number=2, + oneof="delta", + enum=struct_pb2.NullValue, + ) + number_value: float = proto.Field( + proto.DOUBLE, + number=3, + oneof="delta", + ) + string_value: str = proto.Field( + proto.STRING, + number=4, + oneof="delta", + ) + bool_value: bool = proto.Field( + proto.BOOL, + number=5, + oneof="delta", + ) + json_path: str = proto.Field( + proto.STRING, + number=1, + ) + will_continue: bool = proto.Field( + proto.BOOL, + number=6, + ) + + +class FunctionResponsePart(proto.Message): + r"""A datatype containing media that is part of a ``FunctionResponse`` + message. + + A ``FunctionResponsePart`` consists of data which has an associated + datatype. A ``FunctionResponsePart`` can only contain one of the + accepted types in ``FunctionResponsePart.data``. + + A ``FunctionResponsePart`` must have a fixed IANA MIME type + identifying the type and subtype of the media if the ``inline_data`` + field is filled with raw bytes. + + This message has `oneof`_ fields (mutually exclusive fields). + For each oneof, at most one member field can be set at the same time. + Setting any member of the oneof automatically clears all other + members. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + inline_data (google.cloud.aiplatform_v1beta1.types.FunctionResponseBlob): + Inline media bytes. + + This field is a member of `oneof`_ ``data``. + file_data (google.cloud.aiplatform_v1beta1.types.FunctionResponseFileData): + URI based data. + + This field is a member of `oneof`_ ``data``. + """ + + inline_data: "FunctionResponseBlob" = proto.Field( + proto.MESSAGE, + number=1, + oneof="data", + message="FunctionResponseBlob", + ) + file_data: "FunctionResponseFileData" = proto.Field( + proto.MESSAGE, + number=2, + oneof="data", + message="FunctionResponseFileData", + ) + + +class FunctionResponseBlob(proto.Message): + r"""Raw media bytes for function response. + + Text should not be sent as raw bytes, use the 'text' field. + + Attributes: + mime_type (str): + Required. The IANA standard MIME type of the + source data. + data (bytes): + Required. Raw bytes. + display_name (str): + Optional. Display name of the blob. + + Used to provide a label or filename to distinguish blobs. + + This field is only returned in PromptMessage for prompt + management. It is currently used in the Gemini + GenerateContent calls only when server side tools + (code_execution, google_search, and url_context) are + enabled. + """ + + mime_type: str = proto.Field( + proto.STRING, + number=1, + ) + data: bytes = proto.Field( + proto.BYTES, + number=2, + ) + display_name: str = proto.Field( + proto.STRING, + number=4, + ) + + +class FunctionResponseFileData(proto.Message): + r"""URI based data for function response. + + Attributes: + mime_type (str): + Required. The IANA standard MIME type of the + source data. + file_uri (str): + Required. URI. + display_name (str): + Optional. Display name of the file data. + + Used to provide a label or filename to distinguish file + datas. + + This field is only returned in PromptMessage for prompt + management. It is currently used in the Gemini + GenerateContent calls only when server side tools + (code_execution, google_search, and url_context) are + enabled. + """ + + mime_type: str = proto.Field( + proto.STRING, + number=1, + ) + file_uri: str = proto.Field( + proto.STRING, + number=2, + ) + display_name: str = proto.Field( + proto.STRING, + number=3, + ) + + +class FunctionResponse(proto.Message): + r"""The result output from a [FunctionCall] that contains a string + representing the [FunctionDeclaration.name] and a structured JSON + object containing any output from the function is used as context to + the model. This should contain the result of a [FunctionCall] made + based on model prediction. + + Attributes: + id (str): + Optional. The id of the function call this response is for. + Populated by the client to match the corresponding function + call ``id``. + name (str): + Required. The name of the function to call. Matches + [FunctionDeclaration.name] and [FunctionCall.name]. + response (google.protobuf.struct_pb2.Struct): + Required. The function response in JSON + object format. Use "output" key to specify + function output and "error" key to specify error + details (if any). If "output" and "error" keys + are not specified, then whole "response" is + treated as function output. + parts (MutableSequence[google.cloud.aiplatform_v1beta1.types.FunctionResponsePart]): + Optional. Ordered ``Parts`` that constitute a function + response. Parts may have different IANA MIME types. + """ + + id: str = proto.Field( + proto.STRING, + number=3, + ) + name: str = proto.Field( + proto.STRING, + number=1, + ) + response: struct_pb2.Struct = proto.Field( + proto.MESSAGE, + number=2, + message=struct_pb2.Struct, + ) + parts: MutableSequence["FunctionResponsePart"] = proto.RepeatedField( + proto.MESSAGE, + number=4, + message="FunctionResponsePart", + ) + + +class ExecutableCode(proto.Message): + r"""Code generated by the model that is meant to be executed, and the + result returned to the model. + + Generated when using the [FunctionDeclaration] tool and + [FunctionCallingConfig] mode is set to [Mode.CODE]. + + Attributes: + language (google.cloud.aiplatform_v1beta1.types.ExecutableCode.Language): + Required. Programming language of the ``code``. + code (str): + Required. The code to be executed. + """ + + class Language(proto.Enum): + r"""Supported programming languages for the generated code. + + Values: + LANGUAGE_UNSPECIFIED (0): + Unspecified language. This value should not + be used. + PYTHON (1): + Python >= 3.10, with numpy and simpy + available. + """ + + LANGUAGE_UNSPECIFIED = 0 + PYTHON = 1 + + language: Language = proto.Field( + proto.ENUM, + number=1, + enum=Language, + ) + code: str = proto.Field( + proto.STRING, + number=2, + ) + + +class CodeExecutionResult(proto.Message): + r"""Result of executing the [ExecutableCode]. + + Always follows a ``part`` containing the [ExecutableCode]. + + Attributes: + outcome (google.cloud.aiplatform_v1beta1.types.CodeExecutionResult.Outcome): + Required. Outcome of the code execution. + output (str): + Optional. Contains stdout when code execution + is successful, stderr or other description + otherwise. + """ + + class Outcome(proto.Enum): + r"""Enumeration of possible outcomes of the code execution. + + Values: + OUTCOME_UNSPECIFIED (0): + Unspecified status. This value should not be + used. + OUTCOME_OK (1): + Code execution completed successfully. + OUTCOME_FAILED (2): + Code execution finished but with a failure. ``stderr`` + should contain the reason. + OUTCOME_DEADLINE_EXCEEDED (3): + Code execution ran for too long, and was + cancelled. There may or may not be a partial + output present. + """ + + OUTCOME_UNSPECIFIED = 0 + OUTCOME_OK = 1 + OUTCOME_FAILED = 2 + OUTCOME_DEADLINE_EXCEEDED = 3 + + outcome: Outcome = proto.Field( + proto.ENUM, + number=1, + enum=Outcome, + ) + output: str = proto.Field( + proto.STRING, + number=2, + ) + + +class Retrieval(proto.Message): + r"""Defines a retrieval tool that model can call to access + external knowledge. + + This message has `oneof`_ fields (mutually exclusive fields). + For each oneof, at most one member field can be set at the same time. + Setting any member of the oneof automatically clears all other + members. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + vertex_ai_search (google.cloud.aiplatform_v1beta1.types.VertexAISearch): + Set to use data source powered by Vertex AI + Search. + + This field is a member of `oneof`_ ``source``. + vertex_rag_store (google.cloud.aiplatform_v1beta1.types.VertexRagStore): + Set to use data source powered by Vertex RAG + store. User data is uploaded via the + VertexRagDataService. + + This field is a member of `oneof`_ ``source``. + disable_attribution (bool): + Optional. Deprecated. This option is no + longer supported. + """ + + vertex_ai_search: "VertexAISearch" = proto.Field( + proto.MESSAGE, + number=2, + oneof="source", + message="VertexAISearch", + ) + vertex_rag_store: "VertexRagStore" = proto.Field( + proto.MESSAGE, + number=4, + oneof="source", + message="VertexRagStore", + ) + disable_attribution: bool = proto.Field( + proto.BOOL, + number=3, + ) + + +class VertexRagStore(proto.Message): + r"""Retrieve from Vertex RAG Store for grounding. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + rag_corpora (MutableSequence[str]): + Optional. Deprecated. Please use rag_resources instead. + rag_resources (MutableSequence[google.cloud.aiplatform_v1beta1.types.VertexRagStore.RagResource]): + Optional. The representation of the rag + source. It can be used to specify corpus only or + ragfiles. Currently only support one corpus or + multiple files from one corpus. In the future we + may open up multiple corpora support. + similarity_top_k (int): + Optional. Number of top k results to return + from the selected corpora. + + This field is a member of `oneof`_ ``_similarity_top_k``. + vector_distance_threshold (float): + Optional. Only return results with vector + distance smaller than the threshold. + + This field is a member of `oneof`_ ``_vector_distance_threshold``. + rag_retrieval_config (google.cloud.aiplatform_v1beta1.types.RagRetrievalConfig): + Optional. The retrieval config for the Rag + query. + store_context (bool): + Optional. Currently only supported for Gemini Multimodal + Live API. + + In Gemini Multimodal Live API, if ``store_context`` bool is + true, Gemini will leverage it to automatically memorize the + interactions between the client and Gemini, and retrieve + context when needed to augment the response generation for + users' ongoing and future interactions. + """ + + class RagResource(proto.Message): + r"""The definition of the Rag resource. + + Attributes: + rag_corpus (str): + Optional. RagCorpora resource name. Format: + ``projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`` + rag_file_ids (MutableSequence[str]): + Optional. rag_file_id. The files should be in the same + rag_corpus set in rag_corpus field. + """ + + rag_corpus: str = proto.Field( + proto.STRING, + number=1, + ) + rag_file_ids: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=2, + ) + + rag_corpora: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=1, + ) + rag_resources: MutableSequence[RagResource] = proto.RepeatedField( + proto.MESSAGE, + number=4, + message=RagResource, + ) + similarity_top_k: int = proto.Field( + proto.INT32, + number=2, + optional=True, + ) + vector_distance_threshold: float = proto.Field( + proto.DOUBLE, + number=3, + optional=True, + ) + rag_retrieval_config: "RagRetrievalConfig" = proto.Field( + proto.MESSAGE, + number=6, + message="RagRetrievalConfig", + ) + store_context: bool = proto.Field( + proto.BOOL, + number=7, + ) + + +class VertexAISearch(proto.Message): + r"""Retrieve from Vertex AI Search datastore or engine for + grounding. datastore and engine are mutually exclusive. See + https://cloud.google.com/products/agent-builder + + Attributes: + datastore (str): + Optional. Fully-qualified Vertex AI Search data store + resource ID. Format: + ``projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`` + engine (str): + Optional. Fully-qualified Vertex AI Search engine resource + ID. Format: + ``projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`` + max_results (int): + Optional. Number of search results to return + per query. The default value is 10. + The maximumm allowed value is 10. + filter (str): + Optional. Filter strings to be passed to the + search API. + data_store_specs (MutableSequence[google.cloud.aiplatform_v1beta1.types.VertexAISearch.DataStoreSpec]): + Specifications that define the specific + DataStores to be searched, along with + configurations for those data stores. This is + only considered for Engines with multiple data + stores. + It should only be set if engine is used. + """ + + class DataStoreSpec(proto.Message): + r"""Define data stores within engine to filter on in a search + call and configurations for those data stores. For more + information, see + https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec + + Attributes: + data_store (str): + Full resource name of DataStore, such as Format: + ``projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`` + filter (str): + Optional. Filter specification to filter documents in the + data store specified by data_store field. For more + information on filtering, see + `Filtering `__ + """ + + data_store: str = proto.Field( + proto.STRING, + number=1, + ) + filter: str = proto.Field( + proto.STRING, + number=2, + ) + + datastore: str = proto.Field( + proto.STRING, + number=1, + ) + engine: str = proto.Field( + proto.STRING, + number=2, + ) + max_results: int = proto.Field( + proto.INT32, + number=3, + ) + filter: str = proto.Field( + proto.STRING, + number=4, + ) + data_store_specs: MutableSequence[DataStoreSpec] = proto.RepeatedField( + proto.MESSAGE, + number=5, + message=DataStoreSpec, + ) + + +class GoogleSearchRetrieval(proto.Message): + r"""Tool to retrieve public web data for grounding, powered by + Google. + + Attributes: + dynamic_retrieval_config (google.cloud.aiplatform_v1beta1.types.DynamicRetrievalConfig): + Specifies the dynamic retrieval configuration + for the given source. + """ + + dynamic_retrieval_config: "DynamicRetrievalConfig" = proto.Field( + proto.MESSAGE, + number=2, + message="DynamicRetrievalConfig", + ) + + +class GoogleMaps(proto.Message): + r"""Tool to retrieve public maps data for grounding, powered by + Google. + + Attributes: + enable_widget (bool): + If true, include the widget context token in + the response. + """ + + enable_widget: bool = proto.Field( + proto.BOOL, + number=1, + ) + + +class EnterpriseWebSearch(proto.Message): + r"""Tool to search public web data, powered by Vertex AI Search + and Sec4 compliance. + + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + exclude_domains (MutableSequence[str]): + Optional. List of domains to be excluded from + the search results. The default limit is 2000 + domains. + blocking_confidence (google.cloud.aiplatform_v1beta1.types.Tool.PhishBlockThreshold): + Optional. Sites with confidence level chosen + & above this value will be blocked from the + search results. + + This field is a member of `oneof`_ ``_blocking_confidence``. + """ + + exclude_domains: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=1, + ) + blocking_confidence: "Tool.PhishBlockThreshold" = proto.Field( + proto.ENUM, + number=4, + optional=True, + enum="Tool.PhishBlockThreshold", + ) + + +class DynamicRetrievalConfig(proto.Message): + r"""Describes the options to customize dynamic retrieval. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + mode (google.cloud.aiplatform_v1beta1.types.DynamicRetrievalConfig.Mode): + The mode of the predictor to be used in + dynamic retrieval. + dynamic_threshold (float): + Optional. The threshold to be used in dynamic + retrieval. If not set, a system default value is + used. + + This field is a member of `oneof`_ ``_dynamic_threshold``. + """ + + class Mode(proto.Enum): + r"""The mode of the predictor to be used in dynamic retrieval. + + Values: + MODE_UNSPECIFIED (0): + Always trigger retrieval. + MODE_DYNAMIC (1): + Run retrieval only when system decides it is + necessary. + """ + + MODE_UNSPECIFIED = 0 + MODE_DYNAMIC = 1 + + mode: Mode = proto.Field( + proto.ENUM, + number=1, + enum=Mode, + ) + dynamic_threshold: float = proto.Field( + proto.FLOAT, + number=2, + optional=True, + ) + + +class ToolConfig(proto.Message): + r"""Tool config. This config is shared for all tools provided in + the request. + + Attributes: + function_calling_config (google.cloud.aiplatform_v1beta1.types.FunctionCallingConfig): + Optional. Function calling config. + retrieval_config (google.cloud.aiplatform_v1beta1.types.RetrievalConfig): + Optional. Retrieval config. + """ + + function_calling_config: "FunctionCallingConfig" = proto.Field( + proto.MESSAGE, + number=1, + message="FunctionCallingConfig", + ) + retrieval_config: "RetrievalConfig" = proto.Field( + proto.MESSAGE, + number=2, + message="RetrievalConfig", + ) + + +class FunctionCallingConfig(proto.Message): + r"""Function calling config. + + Attributes: + mode (google.cloud.aiplatform_v1beta1.types.FunctionCallingConfig.Mode): + Optional. Function calling mode. + allowed_function_names (MutableSequence[str]): + Optional. Function names to call. Only set when the Mode is + ANY. Function names should match [FunctionDeclaration.name]. + With mode set to ANY, model will predict a function call + from the set of function names provided. + stream_function_call_arguments (bool): + Optional. When set to true, arguments of a single function + call will be streamed out in multiple + parts/contents/responses. Partial parameter results will be + returned in the [FunctionCall.partial_args] field. + """ + + class Mode(proto.Enum): + r"""Function calling mode. + + Values: + MODE_UNSPECIFIED (0): + Unspecified function calling mode. This value + should not be used. + AUTO (1): + Default model behavior, model decides to + predict either function calls or natural + language response. + ANY (2): + Model is constrained to always predicting function calls + only. If + [allowed_function_names][FunctionCallingConfig.allowed_function_names] + are set, the predicted function calls will be limited to any + one of ``allowed_function_names``, else the predicted + function calls will be any one of the provided + [FunctionDeclaration]. + NONE (3): + Model will not predict any function calls. + Model behavior is same as when not passing any + function declarations. + VALIDATED (5): + Model is constrained to predict either function calls or + natural language response. If + [allowed_function_names][FunctionCallingConfig.allowed_function_names] + are set, the predicted function calls will be limited to any + one of ``allowed_function_names``, else the predicted + function calls will be any one of the provided + [FunctionDeclaration]. + """ + + MODE_UNSPECIFIED = 0 + AUTO = 1 + ANY = 2 + NONE = 3 + VALIDATED = 5 + + mode: Mode = proto.Field( + proto.ENUM, + number=1, + enum=Mode, + ) + allowed_function_names: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=2, + ) + stream_function_call_arguments: bool = proto.Field( + proto.BOOL, + number=4, + ) + + +class RetrievalConfig(proto.Message): + r"""Retrieval config. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + lat_lng (google.type.latlng_pb2.LatLng): + The location of the user. + + This field is a member of `oneof`_ ``_lat_lng``. + language_code (str): + The language code of the user. + + This field is a member of `oneof`_ ``_language_code``. + """ + + lat_lng: latlng_pb2.LatLng = proto.Field( + proto.MESSAGE, + number=1, + optional=True, + message=latlng_pb2.LatLng, + ) + language_code: str = proto.Field( + proto.STRING, + number=2, + optional=True, + ) + + +class RagRetrievalConfig(proto.Message): + r"""Specifies the context retrieval config. + + Attributes: + top_k (int): + Optional. The number of contexts to retrieve. + hybrid_search (google.cloud.aiplatform_v1beta1.types.RagRetrievalConfig.HybridSearch): + Optional. Config for Hybrid Search. + filter (google.cloud.aiplatform_v1beta1.types.RagRetrievalConfig.Filter): + Optional. Config for filters. + ranking (google.cloud.aiplatform_v1beta1.types.RagRetrievalConfig.Ranking): + Optional. Config for ranking and reranking. + """ + + class HybridSearch(proto.Message): + r"""Config for Hybrid Search. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + alpha (float): + Optional. Alpha value controls the weight between dense and + sparse vector search results. The range is [0, 1], while 0 + means sparse vector search only and 1 means dense vector + search only. The default value is 0.5 which balances sparse + and dense vector search equally. + + This field is a member of `oneof`_ ``_alpha``. + """ + + alpha: float = proto.Field( + proto.FLOAT, + number=1, + optional=True, + ) + + class Filter(proto.Message): + r"""Config for filters. + + This message has `oneof`_ fields (mutually exclusive fields). + For each oneof, at most one member field can be set at the same time. + Setting any member of the oneof automatically clears all other + members. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + vector_distance_threshold (float): + Optional. Only returns contexts with vector + distance smaller than the threshold. + + This field is a member of `oneof`_ ``vector_db_threshold``. + vector_similarity_threshold (float): + Optional. Only returns contexts with vector + similarity larger than the threshold. + + This field is a member of `oneof`_ ``vector_db_threshold``. + metadata_filter (str): + Optional. String for metadata filtering. + """ + + vector_distance_threshold: float = proto.Field( + proto.DOUBLE, + number=3, + oneof="vector_db_threshold", + ) + vector_similarity_threshold: float = proto.Field( + proto.DOUBLE, + number=4, + oneof="vector_db_threshold", + ) + metadata_filter: str = proto.Field( + proto.STRING, + number=2, + ) + + class Ranking(proto.Message): + r"""Config for ranking and reranking. + + This message has `oneof`_ fields (mutually exclusive fields). + For each oneof, at most one member field can be set at the same time. + Setting any member of the oneof automatically clears all other + members. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + rank_service (google.cloud.aiplatform_v1beta1.types.RagRetrievalConfig.Ranking.RankService): + Optional. Config for Rank Service. + + This field is a member of `oneof`_ ``ranking_config``. + llm_ranker (google.cloud.aiplatform_v1beta1.types.RagRetrievalConfig.Ranking.LlmRanker): + Optional. Config for LlmRanker. + + This field is a member of `oneof`_ ``ranking_config``. + """ + + class RankService(proto.Message): + r"""Config for Rank Service. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + model_name (str): + Optional. The model name of the rank service. Format: + ``semantic-ranker-512@latest`` + + This field is a member of `oneof`_ ``_model_name``. + """ + + model_name: str = proto.Field( + proto.STRING, + number=1, + optional=True, + ) + + class LlmRanker(proto.Message): + r"""Config for LlmRanker. + + .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields + + Attributes: + model_name (str): + Optional. The model name used for ranking. Format: + ``gemini-1.5-pro`` + + This field is a member of `oneof`_ ``_model_name``. + """ + + model_name: str = proto.Field( + proto.STRING, + number=1, + optional=True, + ) + + rank_service: "RagRetrievalConfig.Ranking.RankService" = proto.Field( + proto.MESSAGE, + number=1, + oneof="ranking_config", + message="RagRetrievalConfig.Ranking.RankService", + ) + llm_ranker: "RagRetrievalConfig.Ranking.LlmRanker" = proto.Field( + proto.MESSAGE, + number=3, + oneof="ranking_config", + message="RagRetrievalConfig.Ranking.LlmRanker", + ) + + top_k: int = proto.Field( + proto.INT32, + number=1, + ) + hybrid_search: HybridSearch = proto.Field( + proto.MESSAGE, + number=2, + message=HybridSearch, + ) + filter: Filter = proto.Field( + proto.MESSAGE, + number=3, + message=Filter, + ) + ranking: Ranking = proto.Field( + proto.MESSAGE, + number=4, + message=Ranking, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest))