Google Cloud Native v0.28.0, Feb 2 23

google-native.dialogflow/v2.getConversationModel

Gets conversation model.

Using getConversationModel

Two invocation forms are available. The direct form accepts plain arguments and either blocks until the result value is available, or returns a Promise-wrapped result. The output form accepts Input-wrapped arguments and returns an Output-wrapped result.

function getConversationModel(args: GetConversationModelArgs, opts?: InvokeOptions): Promise<GetConversationModelResult>
function getConversationModelOutput(args: GetConversationModelOutputArgs, opts?: InvokeOptions): Output<GetConversationModelResult>

def get_conversation_model(conversation_model_id: Optional[str] = None,
                           location: Optional[str] = None,
                           project: Optional[str] = None,
                           opts: Optional[InvokeOptions] = None) -> GetConversationModelResult
def get_conversation_model_output(conversation_model_id: Optional[pulumi.Input[str]] = None,
                           location: Optional[pulumi.Input[str]] = None,
                           project: Optional[pulumi.Input[str]] = None,
                           opts: Optional[InvokeOptions] = None) -> Output[GetConversationModelResult]

func LookupConversationModel(ctx *Context, args *LookupConversationModelArgs, opts ...InvokeOption) (*LookupConversationModelResult, error)
func LookupConversationModelOutput(ctx *Context, args *LookupConversationModelOutputArgs, opts ...InvokeOption) LookupConversationModelResultOutput

> Note: This function is named LookupConversationModel in the Go SDK.

public static class GetConversationModel 
{
    public static Task<GetConversationModelResult> InvokeAsync(GetConversationModelArgs args, InvokeOptions? opts = null)
    public static Output<GetConversationModelResult> Invoke(GetConversationModelInvokeArgs args, InvokeOptions? opts = null)
}

public static CompletableFuture<GetConversationModelResult> getConversationModel(GetConversationModelArgs args, InvokeOptions options)
// Output-based functions aren't available in Java yet

fn::invoke:
  function: google-native:dialogflow/v2:getConversationModel
  arguments:
    # arguments dictionary

The following arguments are supported:

ConversationModelId string
Location string
Project string

ConversationModelId string
Location string
Project string

conversationModelId String
location String
project String

conversationModelId string
location string
project string

conversation_model_id str
location str
project str

conversationModelId String
location String
project String

getConversationModel Result

The following output properties are available:

ArticleSuggestionModelMetadata Pulumi.GoogleNative.Dialogflow.V2.Outputs.GoogleCloudDialogflowV2ArticleSuggestionModelMetadataResponse: Metadata for article suggestion models.
CreateTime string: Creation time of this model.
Datasets List<Pulumi.GoogleNative.Dialogflow.V2.Outputs.GoogleCloudDialogflowV2InputDatasetResponse>: Datasets used to create model.
DisplayName string: The display name of the model. At most 64 bytes long.
LanguageCode string: Language code for the conversation model. If not specified, the language is en-US. Language at ConversationModel should be set for all non en-us languages. This should be a BCP-47 language tag. Example: "en-US".
Name string: ConversationModel resource name. Format: projects//conversationModels/
SmartReplyModelMetadata Pulumi.GoogleNative.Dialogflow.V2.Outputs.GoogleCloudDialogflowV2SmartReplyModelMetadataResponse: Metadata for smart reply models.
State string: State of the model. A model can only serve prediction requests after it gets deployed.

ArticleSuggestionModelMetadata GoogleCloudDialogflowV2ArticleSuggestionModelMetadataResponse: Metadata for article suggestion models.
CreateTime string: Creation time of this model.
Datasets []GoogleCloudDialogflowV2InputDatasetResponse: Datasets used to create model.
DisplayName string: The display name of the model. At most 64 bytes long.
LanguageCode string: Language code for the conversation model. If not specified, the language is en-US. Language at ConversationModel should be set for all non en-us languages. This should be a BCP-47 language tag. Example: "en-US".
Name string: ConversationModel resource name. Format: projects//conversationModels/
SmartReplyModelMetadata GoogleCloudDialogflowV2SmartReplyModelMetadataResponse: Metadata for smart reply models.
State string: State of the model. A model can only serve prediction requests after it gets deployed.

articleSuggestionModelMetadata GoogleCloudDialogflowV2ArticleSuggestionModelMetadataResponse: Metadata for article suggestion models.
createTime String: Creation time of this model.
datasets List<GoogleCloudDialogflowV2InputDatasetResponse>: Datasets used to create model.
displayName String: The display name of the model. At most 64 bytes long.
languageCode String: Language code for the conversation model. If not specified, the language is en-US. Language at ConversationModel should be set for all non en-us languages. This should be a BCP-47 language tag. Example: "en-US".
name String: ConversationModel resource name. Format: projects//conversationModels/
smartReplyModelMetadata GoogleCloudDialogflowV2SmartReplyModelMetadataResponse: Metadata for smart reply models.
state String: State of the model. A model can only serve prediction requests after it gets deployed.

articleSuggestionModelMetadata GoogleCloudDialogflowV2ArticleSuggestionModelMetadataResponse: Metadata for article suggestion models.
createTime string: Creation time of this model.
datasets GoogleCloudDialogflowV2InputDatasetResponse[]: Datasets used to create model.
displayName string: The display name of the model. At most 64 bytes long.
languageCode string: Language code for the conversation model. If not specified, the language is en-US. Language at ConversationModel should be set for all non en-us languages. This should be a BCP-47 language tag. Example: "en-US".
name string: ConversationModel resource name. Format: projects//conversationModels/
smartReplyModelMetadata GoogleCloudDialogflowV2SmartReplyModelMetadataResponse: Metadata for smart reply models.
state string: State of the model. A model can only serve prediction requests after it gets deployed.

article_suggestion_model_metadata GoogleCloudDialogflowV2ArticleSuggestionModelMetadataResponse: Metadata for article suggestion models.
create_time str: Creation time of this model.
datasets Sequence[GoogleCloudDialogflowV2InputDatasetResponse]: Datasets used to create model.
display_name str: The display name of the model. At most 64 bytes long.
language_code str: Language code for the conversation model. If not specified, the language is en-US. Language at ConversationModel should be set for all non en-us languages. This should be a BCP-47 language tag. Example: "en-US".
name str: ConversationModel resource name. Format: projects//conversationModels/
smart_reply_model_metadata GoogleCloudDialogflowV2SmartReplyModelMetadataResponse: Metadata for smart reply models.
state str: State of the model. A model can only serve prediction requests after it gets deployed.

articleSuggestionModelMetadata Property Map: Metadata for article suggestion models.
createTime String: Creation time of this model.
datasets List<Property Map>: Datasets used to create model.
displayName String: The display name of the model. At most 64 bytes long.
languageCode String: Language code for the conversation model. If not specified, the language is en-US. Language at ConversationModel should be set for all non en-us languages. This should be a BCP-47 language tag. Example: "en-US".
name String: ConversationModel resource name. Format: projects//conversationModels/
smartReplyModelMetadata Property Map: Metadata for smart reply models.
state String: State of the model. A model can only serve prediction requests after it gets deployed.

Supporting Types

GoogleCloudDialogflowV2ArticleSuggestionModelMetadataResponse

TrainingModelType string: Optional. Type of the article suggestion model. If not provided, model_type is used.

TrainingModelType string: Optional. Type of the article suggestion model. If not provided, model_type is used.

trainingModelType String: Optional. Type of the article suggestion model. If not provided, model_type is used.

trainingModelType string: Optional. Type of the article suggestion model. If not provided, model_type is used.

training_model_type str: Optional. Type of the article suggestion model. If not provided, model_type is used.

trainingModelType String: Optional. Type of the article suggestion model. If not provided, model_type is used.

GoogleCloudDialogflowV2InputDatasetResponse

Dataset string: ConversationDataset resource name. Format: projects//locations//conversationDatasets/

Dataset string: ConversationDataset resource name. Format: projects//locations//conversationDatasets/

dataset String: ConversationDataset resource name. Format: projects//locations//conversationDatasets/

dataset string: ConversationDataset resource name. Format: projects//locations//conversationDatasets/

dataset str: ConversationDataset resource name. Format: projects//locations//conversationDatasets/

dataset String: ConversationDataset resource name. Format: projects//locations//conversationDatasets/

GoogleCloudDialogflowV2SmartReplyModelMetadataResponse

TrainingModelType string: Optional. Type of the smart reply model. If not provided, model_type is used.

TrainingModelType string: Optional. Type of the smart reply model. If not provided, model_type is used.

trainingModelType String: Optional. Type of the smart reply model. If not provided, model_type is used.

trainingModelType string: Optional. Type of the smart reply model. If not provided, model_type is used.

training_model_type str: Optional. Type of the smart reply model. If not provided, model_type is used.

trainingModelType String: Optional. Type of the smart reply model. If not provided, model_type is used.

Package Details

Repository: Google Cloud Native pulumi/pulumi-google-native
License: Apache-2.0