feat(all): auto-regenerate discovery clients

aiplatform/v1beta1/aiplatform-api.json

@@ -16178,7 +16178,7 @@
       }
     }
   },
-  "revision": "20231107",
+  "revision": "20231111",
   "rootUrl": "https://aiplatform.googleapis.com/",
   "schemas": {
     "GoogleApiHttpBody": {
@@ -20587,7 +20587,7 @@
       "type": "object"
     },
     "GoogleCloudAiplatformV1beta1FeatureOnlineStoreOptimized": {
-      "description": "Optimized storage type to replace lightning",
+      "description": "Optimized storage type",
       "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreOptimized",
       "properties": {},
       "type": "object"
@@ -20806,6 +20806,17 @@
       },
       "type": "object"
     },
+    "GoogleCloudAiplatformV1beta1FeatureViewDataKey": {
+      "description": "Lookup key for a feature view.",
+      "id": "GoogleCloudAiplatformV1beta1FeatureViewDataKey",
+      "properties": {
+        "key": {
+          "description": "String key to use for lookup.",
+          "type": "string"
+        }
+      },
+      "type": "object"
+    },
     "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySource": {
       "description": "A Feature Registry source for features that need to be synced to Online Store.",
       "id": "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySource",
@@ -21149,8 +21160,27 @@
       "description": "Request message for FeatureOnlineStoreService.FetchFeatureValues. All the features under the requested feature view will be returned.",
       "id": "GoogleCloudAiplatformV1beta1FetchFeatureValuesRequest",
       "properties": {
+        "dataFormat": {
+          "description": "Optional. Response data format. If not set, FeatureViewDataFormat.KEY_VALUE will be used.",
+          "enum": [
+            "FEATURE_VIEW_DATA_FORMAT_UNSPECIFIED",
+            "KEY_VALUE",
+            "PROTO_STRUCT"
+          ],
+          "enumDescriptions": [
+            "Not set. Will be treated as the KeyValue format.",
+            "Return response data in key-value format.",
+            "Return response data in proto Struct format."
+          ],
+          "type": "string"
+        },
+        "dataKey": {
+          "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDataKey",
+          "description": "Optional. The request key to fetch feature values for."
+        },
         "format": {
-          "description": "Specify response data format. If not set, KeyValue format will be used.",
+          "deprecated": true,
+          "description": "Specify response data format. If not set, KeyValue format will be used. Deprecated. Use FetchFeatureValuesRequest.data_format.",
           "enum": [
             "FORMAT_UNSPECIFIED",
             "KEY_VALUE",
@@ -21164,6 +21194,7 @@
           "type": "string"
         },
         "id": {
+          "deprecated": true,
           "description": "Simple ID. The whole string will be used as is to identify Entity to fetch feature values for.",
           "type": "string"
         }
@@ -23756,13 +23787,22 @@
           },
           "type": "array"
         },
+        "deploymentTimeout": {
+          "description": "Immutable. Deployment timeout. TODO (b/306244185): Revise documentation before exposing.",
+          "format": "google-duration",
+          "type": "string"
+        },
         "env": {
           "description": "Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: ```json [ { \"name\": \"VAR_1\", \"value\": \"foo\" }, { \"name\": \"VAR_2\", \"value\": \"$(VAR_1) bar\" } ] ``` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).",
           "items": {
             "$ref": "GoogleCloudAiplatformV1beta1EnvVar"
           },
           "type": "array"
         },
+        "healthProbe": {
+          "$ref": "GoogleCloudAiplatformV1beta1Probe",
+          "description": "Immutable. Specification for Kubernetes readiness probe. TODO (b/306244185): Revise documentation before exposing."
+        },
         "healthRoute": {
           "description": "Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#health). For example, if you set this field to `/bar`, then Vertex AI intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/ DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)",
           "type": "string"
@@ -23781,6 +23821,15 @@
         "predictRoute": {
           "description": "Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using projects.locations.endpoints.predict to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)",
           "type": "string"
+        },
+        "sharedMemorySizeMb": {
+          "description": "Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes. TODO (b/306244185): Revise documentation before exposing.",
+          "format": "int64",
+          "type": "string"
+        },
+        "startupProbe": {
+          "$ref": "GoogleCloudAiplatformV1beta1Probe",
+          "description": "Immutable. Specification for Kubernetes startup probe. TODO (b/306244185): Revise documentation before exposing."
         }
       },
       "type": "object"
@@ -26321,6 +26370,41 @@
       },
       "type": "object"
     },
+    "GoogleCloudAiplatformV1beta1Probe": {
+      "description": "Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.",
+      "id": "GoogleCloudAiplatformV1beta1Probe",
+      "properties": {
+        "exec": {
+          "$ref": "GoogleCloudAiplatformV1beta1ProbeExecAction",
+          "description": "Exec specifies the action to take."
+        },
+        "periodSeconds": {
+          "description": "How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. Must be less than timeout_seconds. Maps to Kubernetes probe argument 'periodSeconds'.",
+          "format": "int32",
+          "type": "integer"
+        },
+        "timeoutSeconds": {
+          "description": "Number of seconds after which the probe times out. Defaults to 1 second. Minimum value is 1. Must be greater or equal to period_seconds. Maps to Kubernetes probe argument 'timeoutSeconds'.",
+          "format": "int32",
+          "type": "integer"
+        }
+      },
+      "type": "object"
+    },
+    "GoogleCloudAiplatformV1beta1ProbeExecAction": {
+      "description": "ExecAction specifies a command to execute.",
+      "id": "GoogleCloudAiplatformV1beta1ProbeExecAction",
+      "properties": {
+        "command": {
+          "description": "Command is the command line to execute inside the container, the working directory for the command is root ('/') in the container's filesystem. The command is simply exec'd, it is not run inside a shell, so traditional shell instructions ('|', etc) won't work. To use a shell, you need to explicitly call out to that shell. Exit status of 0 is treated as live/healthy and non-zero is unhealthy.",
+          "items": {
+            "type": "string"
+          },
+          "type": "array"
+        }
+      },
+      "type": "object"
+    },
     "GoogleCloudAiplatformV1beta1PublisherModel": {
       "description": "A Model Garden Publisher Model.",
       "id": "GoogleCloudAiplatformV1beta1PublisherModel",
@@ -27012,6 +27096,17 @@
       },
       "type": "object"
     },
+    "GoogleCloudAiplatformV1beta1RebootPersistentResourceOperationMetadata": {
+      "description": "Details of operations that perform reboot PersistentResource.",
+      "id": "GoogleCloudAiplatformV1beta1RebootPersistentResourceOperationMetadata",
+      "properties": {
+        "genericMetadata": {
+          "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata",
+          "description": "Operation metadata for PersistentResource."
+        }
+      },
+      "type": "object"
+    },
     "GoogleCloudAiplatformV1beta1RemoveContextChildrenRequest": {
       "description": "Request message for MetadataService.DeleteContextChildrenRequest.",
       "id": "GoogleCloudAiplatformV1beta1RemoveContextChildrenRequest",
@@ -33229,7 +33324,7 @@
           "type": "string"
         },
         "serviceAccount": {
-          "description": "Optional. The user-provided custom service account to use to do the model upload. If empty, [Vertex AI Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) will be used. Users uploading the Model must have the `iam.serviceAccounts.actAs` permission on this service account. Also, this account must belong to the project specified in the `parent` field and have all necessary read permissions.",
+          "description": "Optional. The user-provided custom service account to use to do the model upload. If empty, [Vertex AI Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) will be used to access resources needed to upload the model. This account must belong to the target project where the model is uploaded to, i.e., the project specified in the `parent` field of this request and have necessary read permissions (to Google Cloud Storage, Artifact Registry, etc.).",
           "type": "string"
         }
       },