chore: Update discovery artifacts

docs/dyn/admin_directory_v1.customer.devices.chromeos.commands.html

@@ -106,7 +106,7 @@ <h3>Method Details</h3>
   &quot;commandExpireTime&quot;: &quot;A String&quot;, # The time at which the command will expire. If the device doesn&#x27;t execute the command within this time the command will become expired.
   &quot;commandId&quot;: &quot;A String&quot;, # Unique ID of a device command.
   &quot;commandResult&quot;: { # The result of executing a command. # The result of the command execution.
-    &quot;commandResultPayload&quot;: &quot;A String&quot;, # The payload for the command result. The following commands respond with a payload: * `DEVICE_START_CRD_SESSION`: Payload is a stringified JSON object in the form: { &quot;url&quot;: url }. The URL provides a link to the Chrome Remote Desktop session.
+    &quot;commandResultPayload&quot;: &quot;A String&quot;, # The payload for the command result. The following commands respond with a payload: * `DEVICE_START_CRD_SESSION`: Payload is a stringified JSON object in the form: { &quot;url&quot;: url }. The URL provides a link to the Chrome Remote Desktop session. * `FETCH_CRD_AVAILABILITY_INFO`: Payload is a stringified JSON object in the form: { &quot;deviceIdleTimeInSeconds&quot;: number, &quot;userSessionType&quot;: string, &quot;remoteSupportAvailability&quot;: string, &quot;remoteAccessAvailability&quot;: string }. The &quot;remoteSupportAvailability&quot; field is set to &quot;AVAILABLE&quot; if `shared` CRD session to the device is available. The &quot;remoteAccessAvailability&quot; field is set to &quot;AVAILABLE&quot; if `private` CRD session to the device is available.
     &quot;errorMessage&quot;: &quot;A String&quot;, # The error message with a short explanation as to why the command failed. Only present if the command failed.
     &quot;executeTime&quot;: &quot;A String&quot;, # The time at which the command was executed or failed to execute.
     &quot;result&quot;: &quot;A String&quot;, # The result of the command.

docs/dyn/aiplatform_v1.endpoints.html

@@ -314,6 +314,7 @@ <h3>Method Details</h3>
     ],
     &quot;temperature&quot;: 3.14, # Optional. Controls the randomness of predictions.
     &quot;thinkingConfig&quot;: { # Config for thinking features. # Optional. Config for thinking features. An error will be returned if this field is set for models that don&#x27;t support thinking.
+      &quot;includeThoughts&quot;: True or False, # Optional. Indicates whether to include thoughts in the response. If true, thoughts are returned only when available.
       &quot;thinkingBudget&quot;: 42, # Optional. Indicates the thinking budget in tokens. This is only applied when enable_thinking is true.
     },
     &quot;topK&quot;: 3.14, # Optional. If specified, top-k sampling will be used.
@@ -468,6 +469,8 @@ <h3>Method Details</h3>
         &quot;vertexAiSearch&quot;: { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
           &quot;datastore&quot;: &quot;A String&quot;, # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
           &quot;engine&quot;: &quot;A String&quot;, # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+          &quot;filter&quot;: &quot;A String&quot;, # Optional. Filter strings to be passed to the search API.
+          &quot;maxResults&quot;: 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
         },
         &quot;vertexRagStore&quot;: { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
           &quot;ragResources&quot;: [ # 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.
@@ -651,6 +654,7 @@ <h3>Method Details</h3>
     ],
     &quot;temperature&quot;: 3.14, # Optional. Controls the randomness of predictions.
     &quot;thinkingConfig&quot;: { # Config for thinking features. # Optional. Config for thinking features. An error will be returned if this field is set for models that don&#x27;t support thinking.
+      &quot;includeThoughts&quot;: True or False, # Optional. Indicates whether to include thoughts in the response. If true, thoughts are returned only when available.
       &quot;thinkingBudget&quot;: 42, # Optional. Indicates the thinking budget in tokens. This is only applied when enable_thinking is true.
     },
     &quot;topK&quot;: 3.14, # Optional. If specified, top-k sampling will be used.
@@ -826,6 +830,8 @@ <h3>Method Details</h3>
         &quot;vertexAiSearch&quot;: { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
           &quot;datastore&quot;: &quot;A String&quot;, # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
           &quot;engine&quot;: &quot;A String&quot;, # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+          &quot;filter&quot;: &quot;A String&quot;, # Optional. Filter strings to be passed to the search API.
+          &quot;maxResults&quot;: 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
         },
         &quot;vertexRagStore&quot;: { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
           &quot;ragResources&quot;: [ # 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.
@@ -1232,6 +1238,7 @@ <h3>Method Details</h3>
     ],
     &quot;temperature&quot;: 3.14, # Optional. Controls the randomness of predictions.
     &quot;thinkingConfig&quot;: { # Config for thinking features. # Optional. Config for thinking features. An error will be returned if this field is set for models that don&#x27;t support thinking.
+      &quot;includeThoughts&quot;: True or False, # Optional. Indicates whether to include thoughts in the response. If true, thoughts are returned only when available.
       &quot;thinkingBudget&quot;: 42, # Optional. Indicates the thinking budget in tokens. This is only applied when enable_thinking is true.
     },
     &quot;topK&quot;: 3.14, # Optional. If specified, top-k sampling will be used.
@@ -1407,6 +1414,8 @@ <h3>Method Details</h3>
         &quot;vertexAiSearch&quot;: { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
           &quot;datastore&quot;: &quot;A String&quot;, # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
           &quot;engine&quot;: &quot;A String&quot;, # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+          &quot;filter&quot;: &quot;A String&quot;, # Optional. Filter strings to be passed to the search API.
+          &quot;maxResults&quot;: 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
         },
         &quot;vertexRagStore&quot;: { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
           &quot;ragResources&quot;: [ # 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.