chore: Update discovery artifacts (#2729)

## Deleted keys were detected in the following stable discovery artifacts:
apihub v1 https://togithub.com/googleapis/google-api-python-client/commit/d5853837b735d4094892f84433d95bd11b451fa8
datalineage v1 https://togithub.com/googleapis/google-api-python-client/commit/8abec73202e20ecc92dc34be35d0ee60d0a4592a
dataplex v1 https://togithub.com/googleapis/google-api-python-client/commit/3834f263bb60bccd631e98b4faeac6ab1e61e762
discoveryengine v1 https://togithub.com/googleapis/google-api-python-client/commit/e51e83aa00e8cae6ad874e422b675fe0ca15c451
fcm v1 https://togithub.com/googleapis/google-api-python-client/commit/242ee76b2de143a24959021e6a3a75685a878aec
workloadmanager v1 https://togithub.com/googleapis/google-api-python-client/commit/565e85ee7c6ff98c849d1834712c35449f77cbf1

## Deleted keys were detected in the following pre-stable discovery artifacts:
compute alpha https://togithub.com/googleapis/google-api-python-client/commit/166ea8146c4387cb03395ccba85c64970dab52de
discoveryengine v1alpha https://togithub.com/googleapis/google-api-python-client/commit/e51e83aa00e8cae6ad874e422b675fe0ca15c451
discoveryengine v1beta https://togithub.com/googleapis/google-api-python-client/commit/e51e83aa00e8cae6ad874e422b675fe0ca15c451

## Discovery Artifact Change Summary:
feat(admin): update the api https://togithub.com/googleapis/google-api-python-client/commit/5577adf2b4a615e185fc5f46b3255588165ca97b
feat(aiplatform): update the api https://togithub.com/googleapis/google-api-python-client/commit/f4eee62a0eb42e6b82648abd8aa10dfb1aa37d16
feat(analyticshub): update the api https://togithub.com/googleapis/google-api-python-client/commit/0ae6b5ef1979366181fa6c2518767769c45be897
feat(androidpublisher): update the api https://togithub.com/googleapis/google-api-python-client/commit/3bcae30e9a5b4ab190b71118301ba987f57b39c7
feat(apihub): update the api https://togithub.com/googleapis/google-api-python-client/commit/d5853837b735d4094892f84433d95bd11b451fa8
feat(backupdr): update the api https://togithub.com/googleapis/google-api-python-client/commit/df7e53eccd94a3772b9cfc091971d7b8d01b94e9
feat(bigquery): update the api https://togithub.com/googleapis/google-api-python-client/commit/a2ecc21536965effba0c9190c43f01f29eb8588f
feat(bigqueryreservation): update the api https://togithub.com/googleapis/google-api-python-client/commit/3132d9257677c88bda0e5122b78f7bc6671c73cf
feat(ces): update the api https://togithub.com/googleapis/google-api-python-client/commit/2dc2ec0afd7236cb60e543ad96bebdbb69cd36e9
feat(classroom): update the api https://togithub.com/googleapis/google-api-python-client/commit/cffc11aaf58752e163fc930a4279b820ffe93daf
feat(cloudbuild): update the api https://togithub.com/googleapis/google-api-python-client/commit/a4d5055d1829938f95c5b6455771b3b39fd86f98
feat(cloudidentity): update the api https://togithub.com/googleapis/google-api-python-client/commit/5eefc0e054eb1923754ef247815a90bf5855fe69
feat(compute): update the api https://togithub.com/googleapis/google-api-python-client/commit/166ea8146c4387cb03395ccba85c64970dab52de
feat(contactcenterinsights): update the api https://togithub.com/googleapis/google-api-python-client/commit/ee644fcb3f92cb82a843ae5d3e9a5949dbeece16
feat(css): update the api https://togithub.com/googleapis/google-api-python-client/commit/e7ad7419e23ac8bee818329be25ad8e0cef4e387
feat(datalineage): update the api https://togithub.com/googleapis/google-api-python-client/commit/8abec73202e20ecc92dc34be35d0ee60d0a4592a
feat(dataplex): update the api https://togithub.com/googleapis/google-api-python-client/commit/3834f263bb60bccd631e98b4faeac6ab1e61e762
feat(discoveryengine): update the api https://togithub.com/googleapis/google-api-python-client/commit/e51e83aa00e8cae6ad874e422b675fe0ca15c451
feat(displayvideo): update the api https://togithub.com/googleapis/google-api-python-client/commit/6346814a18e61174f5e72a0619f9ef66cdd5d9d7
feat(drive): update the api https://togithub.com/googleapis/google-api-python-client/commit/b538e2ec1463b95f01fb3fad110b521085b92ea4
feat(fcm): update the api https://togithub.com/googleapis/google-api-python-client/commit/242ee76b2de143a24959021e6a3a75685a878aec
feat(iam): update the api https://togithub.com/googleapis/google-api-python-client/commit/44b794c39ef2e2f9b16fbcdb6bb78dc20477db42
feat(migrationcenter): update the api https://togithub.com/googleapis/google-api-python-client/commit/54b06e5eceeb875513d96efd0d650f13ab938040
feat(networkconnectivity): update the api https://togithub.com/googleapis/google-api-python-client/commit/8371670da6d9d37f44120ba7c7f8e8b7a7146036
feat(redis): update the api https://togithub.com/googleapis/google-api-python-client/commit/3317e693e0c56dd9c155ba8ceef5275c00abf8e9
feat(run): update the api https://togithub.com/googleapis/google-api-python-client/commit/afe9f8a85609e6b7bb2b4e4a5930aa59fad8511f
feat(searchads360): update the api https://togithub.com/googleapis/google-api-python-client/commit/0fb2f3b7531fb0a8694737ad7603841aefd2ab72
fix(sts): update the api https://togithub.com/googleapis/google-api-python-client/commit/fb1d3d2bcfbb453a5acd52963479cdb1c540e5ee
feat(workloadmanager): update the api https://togithub.com/googleapis/google-api-python-client/commit/565e85ee7c6ff98c849d1834712c35449f77cbf1

Author: yoshi-code-bot

docs/dyn/accesscontextmanager_v1.accessPolicies.servicePerimeters.html

@@ -320,7 +320,25 @@ <h3>Method Details</h3>
               &quot;title&quot;: &quot;A String&quot;, # Title of the label
             },
           ],
-          &quot;id&quot;: &quot;A String&quot;, # Identifier of the resource.
+          &quot;id&quot;: &quot;A String&quot;, # Identifier of the resource, such as a doc_id for a Drive document, a conference_id for a Meet conference, or a &quot;gaia_id/rfc2822_message_id&quot; for an email.
+          &quot;ownerDetails&quot;: { # Details of the owner of the resource. # Owner details of the resource.
+            &quot;ownerIdentity&quot;: [ # Identity details of the owner(s) of the resource.
+              { # Identity details of the owner of the resource.
+                &quot;customerIdentity&quot;: { # Identity of the Google Workspace customer who owns the resource. # Identity of the Google Workspace customer who owns the resource.
+                  &quot;id&quot;: &quot;A String&quot;, # Customer id.
+                },
+                &quot;groupIdentity&quot;: { # Identity of the group who owns the resource. # Identity of the group who owns the resource.
+                  &quot;groupEmail&quot;: &quot;A String&quot;, # Group email.
+                  &quot;id&quot;: &quot;A String&quot;, # Group gaia id.
+                },
+                &quot;userIdentity&quot;: { # Identity of the user who owns the resource. # Identity of the user who owns the resource.
+                  &quot;id&quot;: &quot;A String&quot;, # User gaia id.
+                  &quot;userEmail&quot;: &quot;A String&quot;, # User email.
+                },
+              },
+            ],
+            &quot;ownerType&quot;: &quot;A String&quot;, # Type of the owner of the resource.
+          },
           &quot;relation&quot;: &quot;A String&quot;, # Defines relationship of the resource to the events
           &quot;title&quot;: &quot;A String&quot;, # Title of the resource. For instance, in case of a drive document, this would be the title of the document. In case of an email, this would be the subject.
           &quot;type&quot;: &quot;A String&quot;, # Type of the resource - document, email, chat message

docs/dyn/admin_reports_v1.activities.html

@@ -281,6 +281,11 @@ <h3>Method Details</h3>
       },
       &quot;sampleCount&quot;: 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
     },
+    &quot;datasetCustomMetrics&quot;: [ # Optional. Specifications for custom dataset-level aggregations.
+      { # Defines a custom dataset-level aggregation.
+        &quot;displayName&quot;: &quot;A String&quot;, # Optional. A display name for this custom summary metric. Used to prefix keys in the output summaryMetrics map. If not provided, a default name like &quot;dataset_custom_metric_1&quot;, &quot;dataset_custom_metric_2&quot;, etc., will be generated based on the order in the repeated field.
+      },
+    ],
     &quot;metrics&quot;: [ # Required. The metrics to be calculated in the evaluation run.
       { # The metric used for evaluation runs.
         &quot;computationBasedMetricSpec&quot;: { # Specification for a computation based metric. # Spec for a computation based metric.
@@ -1389,7 +1394,7 @@ <h3>Method Details</h3>
         &quot;topK&quot;: 3.14, # Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.
         &quot;topP&quot;: 3.14, # Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It&#x27;s recommended to adjust either temperature or `top_p`, but not both.
       },
-      &quot;model&quot;: &quot;A String&quot;, # Optional. The fully qualified name of the publisher model or endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
+      &quot;model&quot;: &quot;A String&quot;, # Optional. The fully qualified name of the publisher model or endpoint to use. Anthropic and Llama third-party models are also supported through Model Garden. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Third-party model format: `projects/{project}/locations/{location}/publishers/anthropic/models/{model}` `projects/{project}/locations/{location}/publishers/llama/models/{model}` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
     },
   },
   &quot;labels&quot;: { # Optional. Labels for the evaluation run.
@@ -1555,6 +1560,11 @@ <h3>Method Details</h3>
       },
       &quot;sampleCount&quot;: 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
     },
+    &quot;datasetCustomMetrics&quot;: [ # Optional. Specifications for custom dataset-level aggregations.
+      { # Defines a custom dataset-level aggregation.
+        &quot;displayName&quot;: &quot;A String&quot;, # Optional. A display name for this custom summary metric. Used to prefix keys in the output summaryMetrics map. If not provided, a default name like &quot;dataset_custom_metric_1&quot;, &quot;dataset_custom_metric_2&quot;, etc., will be generated based on the order in the repeated field.
+      },
+    ],
     &quot;metrics&quot;: [ # Required. The metrics to be calculated in the evaluation run.
       { # The metric used for evaluation runs.
         &quot;computationBasedMetricSpec&quot;: { # Specification for a computation based metric. # Spec for a computation based metric.
@@ -2663,7 +2673,7 @@ <h3>Method Details</h3>
         &quot;topK&quot;: 3.14, # Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.
         &quot;topP&quot;: 3.14, # Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It&#x27;s recommended to adjust either temperature or `top_p`, but not both.
       },
-      &quot;model&quot;: &quot;A String&quot;, # Optional. The fully qualified name of the publisher model or endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
+      &quot;model&quot;: &quot;A String&quot;, # Optional. The fully qualified name of the publisher model or endpoint to use. Anthropic and Llama third-party models are also supported through Model Garden. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Third-party model format: `projects/{project}/locations/{location}/publishers/anthropic/models/{model}` `projects/{project}/locations/{location}/publishers/llama/models/{model}` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
     },
   },
   &quot;labels&quot;: { # Optional. Labels for the evaluation run.
@@ -2871,6 +2881,11 @@ <h3>Method Details</h3>
       },
       &quot;sampleCount&quot;: 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
     },
+    &quot;datasetCustomMetrics&quot;: [ # Optional. Specifications for custom dataset-level aggregations.
+      { # Defines a custom dataset-level aggregation.
+        &quot;displayName&quot;: &quot;A String&quot;, # Optional. A display name for this custom summary metric. Used to prefix keys in the output summaryMetrics map. If not provided, a default name like &quot;dataset_custom_metric_1&quot;, &quot;dataset_custom_metric_2&quot;, etc., will be generated based on the order in the repeated field.
+      },
+    ],
     &quot;metrics&quot;: [ # Required. The metrics to be calculated in the evaluation run.
       { # The metric used for evaluation runs.
         &quot;computationBasedMetricSpec&quot;: { # Specification for a computation based metric. # Spec for a computation based metric.
@@ -3979,7 +3994,7 @@ <h3>Method Details</h3>
         &quot;topK&quot;: 3.14, # Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.
         &quot;topP&quot;: 3.14, # Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It&#x27;s recommended to adjust either temperature or `top_p`, but not both.
       },
-      &quot;model&quot;: &quot;A String&quot;, # Optional. The fully qualified name of the publisher model or endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
+      &quot;model&quot;: &quot;A String&quot;, # Optional. The fully qualified name of the publisher model or endpoint to use. Anthropic and Llama third-party models are also supported through Model Garden. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Third-party model format: `projects/{project}/locations/{location}/publishers/anthropic/models/{model}` `projects/{project}/locations/{location}/publishers/llama/models/{model}` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
     },
   },
   &quot;labels&quot;: { # Optional. Labels for the evaluation run.
@@ -4158,6 +4173,11 @@ <h3>Method Details</h3>
           },
           &quot;sampleCount&quot;: 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
         },
+        &quot;datasetCustomMetrics&quot;: [ # Optional. Specifications for custom dataset-level aggregations.
+          { # Defines a custom dataset-level aggregation.
+            &quot;displayName&quot;: &quot;A String&quot;, # Optional. A display name for this custom summary metric. Used to prefix keys in the output summaryMetrics map. If not provided, a default name like &quot;dataset_custom_metric_1&quot;, &quot;dataset_custom_metric_2&quot;, etc., will be generated based on the order in the repeated field.
+          },
+        ],
         &quot;metrics&quot;: [ # Required. The metrics to be calculated in the evaluation run.
           { # The metric used for evaluation runs.
             &quot;computationBasedMetricSpec&quot;: { # Specification for a computation based metric. # Spec for a computation based metric.
@@ -5266,7 +5286,7 @@ <h3>Method Details</h3>
             &quot;topK&quot;: 3.14, # Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.
             &quot;topP&quot;: 3.14, # Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It&#x27;s recommended to adjust either temperature or `top_p`, but not both.
           },
-          &quot;model&quot;: &quot;A String&quot;, # Optional. The fully qualified name of the publisher model or endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
+          &quot;model&quot;: &quot;A String&quot;, # Optional. The fully qualified name of the publisher model or endpoint to use. Anthropic and Llama third-party models are also supported through Model Garden. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Third-party model format: `projects/{project}/locations/{location}/publishers/anthropic/models/{model}` `projects/{project}/locations/{location}/publishers/llama/models/{model}` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
         },
       },
       &quot;labels&quot;: { # Optional. Labels for the evaluation run.