Docs Home Pulumi IaC Pulumi ESC Pulumi Insights Pulumi Cloud Packages Tutorials
  1. Packages
  2. Google Cloud Native
  3. API Docs
  4. dialogflow
  5. dialogflow/v2
  6. ConversationModel

Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

google-native.dialogflow/v2.ConversationModel

Explore with Pulumi AI

google-native logo

Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

    Creates a model. This method is a long-running operation. The returned Operation type has the following method-specific fields: - metadata: CreateConversationModelOperationMetadata - response: ConversationModel

    Create ConversationModel Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new ConversationModel(name: string, args: ConversationModelArgs, opts?: CustomResourceOptions);
    @overload
def ConversationModel(resource_name: str,
                      args: ConversationModelArgs,
                      opts: Optional[ResourceOptions] = None)

@overload
def ConversationModel(resource_name: str,
                      opts: Optional[ResourceOptions] = None,
                      datasets: Optional[Sequence[GoogleCloudDialogflowV2InputDatasetArgs]] = None,
                      display_name: Optional[str] = None,
                      article_suggestion_model_metadata: Optional[GoogleCloudDialogflowV2ArticleSuggestionModelMetadataArgs] = None,
                      language_code: Optional[str] = None,
                      location: Optional[str] = None,
                      name: Optional[str] = None,
                      project: Optional[str] = None,
                      smart_reply_model_metadata: Optional[GoogleCloudDialogflowV2SmartReplyModelMetadataArgs] = None)
    func NewConversationModel(ctx *Context, name string, args ConversationModelArgs, opts ...ResourceOption) (*ConversationModel, error)
    public ConversationModel(string name, ConversationModelArgs args, CustomResourceOptions? opts = null)
    public ConversationModel(String name, ConversationModelArgs args)
public ConversationModel(String name, ConversationModelArgs args, CustomResourceOptions options)

    type: google-native:dialogflow/v2:ConversationModel
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

    Parameters

    name string
    The unique name of the resource.
    args ConversationModelArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args ConversationModelArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args ConversationModelArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args ConversationModelArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args ConversationModelArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Constructor example

    The following reference example uses placeholder values for all input properties.

    var conversationModelResource = new GoogleNative.Dialogflow.V2.ConversationModel("conversationModelResource", new()
{
    Datasets = new[]
    {
        new GoogleNative.Dialogflow.V2.Inputs.GoogleCloudDialogflowV2InputDatasetArgs
        {
            Dataset = "string",
        },
    },
    DisplayName = "string",
    ArticleSuggestionModelMetadata = new GoogleNative.Dialogflow.V2.Inputs.GoogleCloudDialogflowV2ArticleSuggestionModelMetadataArgs
    {
        TrainingModelType = GoogleNative.Dialogflow.V2.GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelType.ModelTypeUnspecified,
    },
    LanguageCode = "string",
    Location = "string",
    Name = "string",
    Project = "string",
    SmartReplyModelMetadata = new GoogleNative.Dialogflow.V2.Inputs.GoogleCloudDialogflowV2SmartReplyModelMetadataArgs
    {
        TrainingModelType = GoogleNative.Dialogflow.V2.GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelType.ModelTypeUnspecified,
    },
});

    example, err := dialogflow.NewConversationModel(ctx, "conversationModelResource", &dialogflow.ConversationModelArgs{
	Datasets: dialogflow.GoogleCloudDialogflowV2InputDatasetArray{
		&dialogflow.GoogleCloudDialogflowV2InputDatasetArgs{
			Dataset: pulumi.String("string"),
		},
	},
	DisplayName: pulumi.String("string"),
	ArticleSuggestionModelMetadata: &dialogflow.GoogleCloudDialogflowV2ArticleSuggestionModelMetadataArgs{
		TrainingModelType: dialogflow.GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelTypeModelTypeUnspecified,
	},
	LanguageCode: pulumi.String("string"),
	Location:     pulumi.String("string"),
	Name:         pulumi.String("string"),
	Project:      pulumi.String("string"),
	SmartReplyModelMetadata: &dialogflow.GoogleCloudDialogflowV2SmartReplyModelMetadataArgs{
		TrainingModelType: dialogflow.GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelTypeModelTypeUnspecified,
	},
})

    var conversationModelResource = new ConversationModel("conversationModelResource", ConversationModelArgs.builder()
    .datasets(GoogleCloudDialogflowV2InputDatasetArgs.builder()
        .dataset("string")
        .build())
    .displayName("string")
    .articleSuggestionModelMetadata(GoogleCloudDialogflowV2ArticleSuggestionModelMetadataArgs.builder()
        .trainingModelType("MODEL_TYPE_UNSPECIFIED")
        .build())
    .languageCode("string")
    .location("string")
    .name("string")
    .project("string")
    .smartReplyModelMetadata(GoogleCloudDialogflowV2SmartReplyModelMetadataArgs.builder()
        .trainingModelType("MODEL_TYPE_UNSPECIFIED")
        .build())
    .build());

    conversation_model_resource = google_native.dialogflow.v2.ConversationModel("conversationModelResource",
    datasets=[{
        "dataset": "string",
    }],
    display_name="string",
    article_suggestion_model_metadata={
        "training_model_type": google_native.dialogflow.v2.GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelType.MODEL_TYPE_UNSPECIFIED,
    },
    language_code="string",
    location="string",
    name="string",
    project="string",
    smart_reply_model_metadata={
        "training_model_type": google_native.dialogflow.v2.GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelType.MODEL_TYPE_UNSPECIFIED,
    })

    const conversationModelResource = new google_native.dialogflow.v2.ConversationModel("conversationModelResource", {
    datasets: [{
        dataset: "string",
    }],
    displayName: "string",
    articleSuggestionModelMetadata: {
        trainingModelType: google_native.dialogflow.v2.GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelType.ModelTypeUnspecified,
    },
    languageCode: "string",
    location: "string",
    name: "string",
    project: "string",
    smartReplyModelMetadata: {
        trainingModelType: google_native.dialogflow.v2.GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelType.ModelTypeUnspecified,
    },
});

    type: google-native:dialogflow/v2:ConversationModel
properties:
    articleSuggestionModelMetadata:
        trainingModelType: MODEL_TYPE_UNSPECIFIED
    datasets:
        - dataset: string
    displayName: string
    languageCode: string
    location: string
    name: string
    project: string
    smartReplyModelMetadata:
        trainingModelType: MODEL_TYPE_UNSPECIFIED

    ConversationModel Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The ConversationModel resource accepts the following input properties:

    Datasets List<Pulumi.GoogleNative.Dialogflow.V2.Inputs.GoogleCloudDialogflowV2InputDataset>
    Datasets used to create model.
    DisplayName string
    The display name of the model. At most 64 bytes long.
    ArticleSuggestionModelMetadata Pulumi.GoogleNative.Dialogflow.V2.Inputs.GoogleCloudDialogflowV2ArticleSuggestionModelMetadata
    Metadata for article suggestion models.
    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".
    Location string
    Name string
    ConversationModel resource name. Format: projects//conversationModels/
    Project string
    SmartReplyModelMetadata Pulumi.GoogleNative.Dialogflow.V2.Inputs.GoogleCloudDialogflowV2SmartReplyModelMetadata
    Metadata for smart reply models.
    Datasets []GoogleCloudDialogflowV2InputDatasetArgs
    Datasets used to create model.
    DisplayName string
    The display name of the model. At most 64 bytes long.
    ArticleSuggestionModelMetadata GoogleCloudDialogflowV2ArticleSuggestionModelMetadataArgs
    Metadata for article suggestion models.
    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".
    Location string
    Name string
    ConversationModel resource name. Format: projects//conversationModels/
    Project string
    SmartReplyModelMetadata GoogleCloudDialogflowV2SmartReplyModelMetadataArgs
    Metadata for smart reply models.
    datasets List<GoogleCloudDialogflowV2InputDataset>
    Datasets used to create model.
    displayName String
    The display name of the model. At most 64 bytes long.
    articleSuggestionModelMetadata GoogleCloudDialogflowV2ArticleSuggestionModelMetadata
    Metadata for article suggestion models.
    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".
    location String
    name String
    ConversationModel resource name. Format: projects//conversationModels/
    project String
    smartReplyModelMetadata GoogleCloudDialogflowV2SmartReplyModelMetadata
    Metadata for smart reply models.
    datasets GoogleCloudDialogflowV2InputDataset[]
    Datasets used to create model.
    displayName string
    The display name of the model. At most 64 bytes long.
    articleSuggestionModelMetadata GoogleCloudDialogflowV2ArticleSuggestionModelMetadata
    Metadata for article suggestion models.
    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".
    location string
    name string
    ConversationModel resource name. Format: projects//conversationModels/
    project string
    smartReplyModelMetadata GoogleCloudDialogflowV2SmartReplyModelMetadata
    Metadata for smart reply models.
    datasets Sequence[GoogleCloudDialogflowV2InputDatasetArgs]
    Datasets used to create model.
    display_name str
    The display name of the model. At most 64 bytes long.
    article_suggestion_model_metadata GoogleCloudDialogflowV2ArticleSuggestionModelMetadataArgs
    Metadata for article suggestion models.
    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".
    location str
    name str
    ConversationModel resource name. Format: projects//conversationModels/
    project str
    smart_reply_model_metadata GoogleCloudDialogflowV2SmartReplyModelMetadataArgs
    Metadata for smart reply models.
    datasets List<Property Map>
    Datasets used to create model.
    displayName String
    The display name of the model. At most 64 bytes long.
    articleSuggestionModelMetadata Property Map
    Metadata for article suggestion models.
    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".
    location String
    name String
    ConversationModel resource name. Format: projects//conversationModels/
    project String
    smartReplyModelMetadata Property Map
    Metadata for smart reply models.

    Outputs

    All input properties are implicitly available as output properties. Additionally, the ConversationModel resource produces the following output properties:

    CreateTime string
    Creation time of this model.
    Id string
    The provider-assigned unique ID for this managed resource.
    State string
    State of the model. A model can only serve prediction requests after it gets deployed.
    CreateTime string
    Creation time of this model.
    Id string
    The provider-assigned unique ID for this managed resource.
    State string
    State of the model. A model can only serve prediction requests after it gets deployed.
    createTime String
    Creation time of this model.
    id String
    The provider-assigned unique ID for this managed resource.
    state String
    State of the model. A model can only serve prediction requests after it gets deployed.
    createTime string
    Creation time of this model.
    id string
    The provider-assigned unique ID for this managed resource.
    state string
    State of the model. A model can only serve prediction requests after it gets deployed.
    create_time str
    Creation time of this model.
    id str
    The provider-assigned unique ID for this managed resource.
    state str
    State of the model. A model can only serve prediction requests after it gets deployed.
    createTime String
    Creation time of this model.
    id String
    The provider-assigned unique ID for this managed resource.
    state String
    State of the model. A model can only serve prediction requests after it gets deployed.

    Supporting Types

    GoogleCloudDialogflowV2ArticleSuggestionModelMetadata, GoogleCloudDialogflowV2ArticleSuggestionModelMetadataArgs

    TrainingModelType Pulumi.GoogleNative.Dialogflow.V2.GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelType
    Optional. Type of the article suggestion model. If not provided, model_type is used.
    TrainingModelType GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelType
    Optional. Type of the article suggestion model. If not provided, model_type is used.
    trainingModelType GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelType
    Optional. Type of the article suggestion model. If not provided, model_type is used.
    trainingModelType GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelType
    Optional. Type of the article suggestion model. If not provided, model_type is used.
    training_model_type GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelType
    Optional. Type of the article suggestion model. If not provided, model_type is used.
    trainingModelType "MODEL_TYPE_UNSPECIFIED" | "SMART_REPLY_DUAL_ENCODER_MODEL" | "SMART_REPLY_BERT_MODEL"
    Optional. Type of the article suggestion model. If not provided, model_type is used.

    GoogleCloudDialogflowV2ArticleSuggestionModelMetadataResponse, GoogleCloudDialogflowV2ArticleSuggestionModelMetadataResponseArgs

    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.

    GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelType, GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelTypeArgs

    ModelTypeUnspecified
    MODEL_TYPE_UNSPECIFIEDModelType unspecified.
    SmartReplyDualEncoderModel
    SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
    SmartReplyBertModel
    SMART_REPLY_BERT_MODELModelType smart reply bert model.
    GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelTypeModelTypeUnspecified
    MODEL_TYPE_UNSPECIFIEDModelType unspecified.
    GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelTypeSmartReplyDualEncoderModel
    SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
    GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelTypeSmartReplyBertModel
    SMART_REPLY_BERT_MODELModelType smart reply bert model.
    ModelTypeUnspecified
    MODEL_TYPE_UNSPECIFIEDModelType unspecified.
    SmartReplyDualEncoderModel
    SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
    SmartReplyBertModel
    SMART_REPLY_BERT_MODELModelType smart reply bert model.
    ModelTypeUnspecified
    MODEL_TYPE_UNSPECIFIEDModelType unspecified.
    SmartReplyDualEncoderModel
    SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
    SmartReplyBertModel
    SMART_REPLY_BERT_MODELModelType smart reply bert model.
    MODEL_TYPE_UNSPECIFIED
    MODEL_TYPE_UNSPECIFIEDModelType unspecified.
    SMART_REPLY_DUAL_ENCODER_MODEL
    SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
    SMART_REPLY_BERT_MODEL
    SMART_REPLY_BERT_MODELModelType smart reply bert model.
    "MODEL_TYPE_UNSPECIFIED"
    MODEL_TYPE_UNSPECIFIEDModelType unspecified.
    "SMART_REPLY_DUAL_ENCODER_MODEL"
    SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
    "SMART_REPLY_BERT_MODEL"
    SMART_REPLY_BERT_MODELModelType smart reply bert model.

    GoogleCloudDialogflowV2InputDataset, GoogleCloudDialogflowV2InputDatasetArgs

    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/

    GoogleCloudDialogflowV2InputDatasetResponse, GoogleCloudDialogflowV2InputDatasetResponseArgs

    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/

    GoogleCloudDialogflowV2SmartReplyModelMetadata, GoogleCloudDialogflowV2SmartReplyModelMetadataArgs

    TrainingModelType Pulumi.GoogleNative.Dialogflow.V2.GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelType
    Optional. Type of the smart reply model. If not provided, model_type is used.
    TrainingModelType GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelType
    Optional. Type of the smart reply model. If not provided, model_type is used.
    trainingModelType GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelType
    Optional. Type of the smart reply model. If not provided, model_type is used.
    trainingModelType GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelType
    Optional. Type of the smart reply model. If not provided, model_type is used.
    training_model_type GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelType
    Optional. Type of the smart reply model. If not provided, model_type is used.
    trainingModelType "MODEL_TYPE_UNSPECIFIED" | "SMART_REPLY_DUAL_ENCODER_MODEL" | "SMART_REPLY_BERT_MODEL"
    Optional. Type of the smart reply model. If not provided, model_type is used.

    GoogleCloudDialogflowV2SmartReplyModelMetadataResponse, GoogleCloudDialogflowV2SmartReplyModelMetadataResponseArgs

    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.

    GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelType, GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelTypeArgs

    ModelTypeUnspecified
    MODEL_TYPE_UNSPECIFIEDModelType unspecified.
    SmartReplyDualEncoderModel
    SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
    SmartReplyBertModel
    SMART_REPLY_BERT_MODELModelType smart reply bert model.
    GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelTypeModelTypeUnspecified
    MODEL_TYPE_UNSPECIFIEDModelType unspecified.
    GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelTypeSmartReplyDualEncoderModel
    SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
    GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelTypeSmartReplyBertModel
    SMART_REPLY_BERT_MODELModelType smart reply bert model.
    ModelTypeUnspecified
    MODEL_TYPE_UNSPECIFIEDModelType unspecified.
    SmartReplyDualEncoderModel
    SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
    SmartReplyBertModel
    SMART_REPLY_BERT_MODELModelType smart reply bert model.
    ModelTypeUnspecified
    MODEL_TYPE_UNSPECIFIEDModelType unspecified.
    SmartReplyDualEncoderModel
    SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
    SmartReplyBertModel
    SMART_REPLY_BERT_MODELModelType smart reply bert model.
    MODEL_TYPE_UNSPECIFIED
    MODEL_TYPE_UNSPECIFIEDModelType unspecified.
    SMART_REPLY_DUAL_ENCODER_MODEL
    SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
    SMART_REPLY_BERT_MODEL
    SMART_REPLY_BERT_MODELModelType smart reply bert model.
    "MODEL_TYPE_UNSPECIFIED"
    MODEL_TYPE_UNSPECIFIEDModelType unspecified.
    "SMART_REPLY_DUAL_ENCODER_MODEL"
    SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
    "SMART_REPLY_BERT_MODEL"
    SMART_REPLY_BERT_MODELModelType smart reply bert model.

    Package Details

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

    Google Cloud Native is in preview. Google Cloud Classic is fully supported.

    Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
    pulumi/pulumi-google-native