deploy method
- GoogleCloudDialogflowV2DeployConversationModelRequest request,
- String name, {
- String? $fields,
Deploys a model.
If a model is already deployed, deploying it has no effect. A model can
only serve prediction requests after it gets deployed. For article
suggestion, custom model will not be used unless it is deployed. This
method is a [long-running
operation](https://cloud.google.com/dialogflow/es/docs/how/long-running-operations).
The returned Operation
type has the following method-specific fields: -
metadata
: DeployConversationModelOperationMetadata - response
: An
Empty message
request
- The metadata request object.
Request parameters:
name
- Required. The conversation model to deploy. Format:
projects//conversationModels/
Value must have pattern
^projects/\[^/\]+/locations/\[^/\]+/conversationModels/\[^/\]+$
.
$fields
- Selector specifying which fields to include in a partial
response.
Completes with a GoogleLongrunningOperation.
Completes with a commons.ApiRequestError if the API endpoint returned an error.
If the used http.Client
completes with an error when making a REST call,
this method will complete with the same error.
Implementation
async.Future<GoogleLongrunningOperation> deploy(
GoogleCloudDialogflowV2DeployConversationModelRequest request,
core.String name, {
core.String? $fields,
}) async {
final body_ = convert.json.encode(request);
final queryParams_ = <core.String, core.List<core.String>>{
if ($fields != null) 'fields': [$fields],
};
final url_ = 'v2/' + core.Uri.encodeFull('$name') + ':deploy';
final response_ = await _requester.request(
url_,
'POST',
body: body_,
queryParams: queryParams_,
);
return GoogleLongrunningOperation.fromJson(
response_ as core.Map<core.String, core.dynamic>);
}