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google-native.dialogflow/v2.ConversationModel
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Google Cloud Native is in preview. Google Cloud Classic is fully supported.
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.
Google Native. Dialogflow. V2. Inputs. Google Cloud Dialogflow V2Input Dataset> - Datasets used to create model.
- Display
Name string - The display name of the model. At most 64 bytes long.
- Article
Suggestion Pulumi.Model Metadata Google Native. Dialogflow. V2. Inputs. Google Cloud Dialogflow V2Article Suggestion Model Metadata - Metadata for article suggestion models.
- Language
Code 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
- Smart
Reply Pulumi.Model Metadata Google Native. Dialogflow. V2. Inputs. Google Cloud Dialogflow V2Smart Reply Model Metadata - Metadata for smart reply models.
- Datasets
[]Google
Cloud Dialogflow V2Input Dataset Args - Datasets used to create model.
- Display
Name string - The display name of the model. At most 64 bytes long.
- Article
Suggestion GoogleModel Metadata Cloud Dialogflow V2Article Suggestion Model Metadata Args - Metadata for article suggestion models.
- Language
Code 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
- Smart
Reply GoogleModel Metadata Cloud Dialogflow V2Smart Reply Model Metadata Args - Metadata for smart reply models.
- datasets
List<Google
Cloud Dialogflow V2Input Dataset> - Datasets used to create model.
- display
Name String - The display name of the model. At most 64 bytes long.
- article
Suggestion GoogleModel Metadata Cloud Dialogflow V2Article Suggestion Model Metadata - Metadata for article suggestion models.
- language
Code 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
- smart
Reply GoogleModel Metadata Cloud Dialogflow V2Smart Reply Model Metadata - Metadata for smart reply models.
- datasets
Google
Cloud Dialogflow V2Input Dataset[] - Datasets used to create model.
- display
Name string - The display name of the model. At most 64 bytes long.
- article
Suggestion GoogleModel Metadata Cloud Dialogflow V2Article Suggestion Model Metadata - Metadata for article suggestion models.
- language
Code 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
- smart
Reply GoogleModel Metadata Cloud Dialogflow V2Smart Reply Model Metadata - Metadata for smart reply models.
- datasets
Sequence[Google
Cloud Dialogflow V2Input Dataset Args] - Datasets used to create model.
- display_
name str - The display name of the model. At most 64 bytes long.
- article_
suggestion_ Googlemodel_ metadata Cloud Dialogflow V2Article Suggestion Model Metadata Args - 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_ Googlemodel_ metadata Cloud Dialogflow V2Smart Reply Model Metadata Args - Metadata for smart reply models.
- datasets List<Property Map>
- Datasets used to create model.
- display
Name String - The display name of the model. At most 64 bytes long.
- article
Suggestion Property MapModel Metadata - Metadata for article suggestion models.
- language
Code 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
- smart
Reply Property MapModel Metadata - Metadata for smart reply models.
Outputs
All input properties are implicitly available as output properties. Additionally, the ConversationModel resource produces the following output properties:
- Create
Time 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 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 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 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.
- create
Time 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
- Training
Model Pulumi.Type Google Native. Dialogflow. V2. Google Cloud Dialogflow V2Article Suggestion Model Metadata Training Model Type - Optional. Type of the article suggestion model. If not provided, model_type is used.
- Training
Model GoogleType Cloud Dialogflow V2Article Suggestion Model Metadata Training Model Type - Optional. Type of the article suggestion model. If not provided, model_type is used.
- training
Model GoogleType Cloud Dialogflow V2Article Suggestion Model Metadata Training Model Type - Optional. Type of the article suggestion model. If not provided, model_type is used.
- training
Model GoogleType Cloud Dialogflow V2Article Suggestion Model Metadata Training Model Type - Optional. Type of the article suggestion model. If not provided, model_type is used.
- training_
model_ Googletype Cloud Dialogflow V2Article Suggestion Model Metadata Training Model Type - Optional. Type of the article suggestion model. If not provided, model_type is used.
- training
Model "MODEL_TYPE_UNSPECIFIED" | "SMART_REPLY_DUAL_ENCODER_MODEL" | "SMART_REPLY_BERT_MODEL"Type - Optional. Type of the article suggestion model. If not provided, model_type is used.
GoogleCloudDialogflowV2ArticleSuggestionModelMetadataResponse, GoogleCloudDialogflowV2ArticleSuggestionModelMetadataResponseArgs
- Training
Model stringType - Optional. Type of the article suggestion model. If not provided, model_type is used.
- Training
Model stringType - Optional. Type of the article suggestion model. If not provided, model_type is used.
- training
Model StringType - Optional. Type of the article suggestion model. If not provided, model_type is used.
- training
Model stringType - Optional. Type of the article suggestion model. If not provided, model_type is used.
- training_
model_ strtype - Optional. Type of the article suggestion model. If not provided, model_type is used.
- training
Model StringType - Optional. Type of the article suggestion model. If not provided, model_type is used.
GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelType, GoogleCloudDialogflowV2ArticleSuggestionModelMetadataTrainingModelTypeArgs
- 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.
- Google
Cloud Dialogflow V2Article Suggestion Model Metadata Training Model Type Model Type Unspecified - MODEL_TYPE_UNSPECIFIEDModelType unspecified.
- Google
Cloud Dialogflow V2Article Suggestion Model Metadata Training Model Type Smart Reply Dual Encoder Model - SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
- Google
Cloud Dialogflow V2Article Suggestion Model Metadata Training Model Type 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.
- 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.
- "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
- Training
Model Pulumi.Type Google Native. Dialogflow. V2. Google Cloud Dialogflow V2Smart Reply Model Metadata Training Model Type - Optional. Type of the smart reply model. If not provided, model_type is used.
- Training
Model GoogleType Cloud Dialogflow V2Smart Reply Model Metadata Training Model Type - Optional. Type of the smart reply model. If not provided, model_type is used.
- training
Model GoogleType Cloud Dialogflow V2Smart Reply Model Metadata Training Model Type - Optional. Type of the smart reply model. If not provided, model_type is used.
- training
Model GoogleType Cloud Dialogflow V2Smart Reply Model Metadata Training Model Type - Optional. Type of the smart reply model. If not provided, model_type is used.
- training_
model_ Googletype Cloud Dialogflow V2Smart Reply Model Metadata Training Model Type - Optional. Type of the smart reply model. If not provided, model_type is used.
- training
Model "MODEL_TYPE_UNSPECIFIED" | "SMART_REPLY_DUAL_ENCODER_MODEL" | "SMART_REPLY_BERT_MODEL"Type - Optional. Type of the smart reply model. If not provided, model_type is used.
GoogleCloudDialogflowV2SmartReplyModelMetadataResponse, GoogleCloudDialogflowV2SmartReplyModelMetadataResponseArgs
- Training
Model stringType - Optional. Type of the smart reply model. If not provided, model_type is used.
- Training
Model stringType - Optional. Type of the smart reply model. If not provided, model_type is used.
- training
Model StringType - Optional. Type of the smart reply model. If not provided, model_type is used.
- training
Model stringType - Optional. Type of the smart reply model. If not provided, model_type is used.
- training_
model_ strtype - Optional. Type of the smart reply model. If not provided, model_type is used.
- training
Model StringType - Optional. Type of the smart reply model. If not provided, model_type is used.
GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelType, GoogleCloudDialogflowV2SmartReplyModelMetadataTrainingModelTypeArgs
- 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.
- Google
Cloud Dialogflow V2Smart Reply Model Metadata Training Model Type Model Type Unspecified - MODEL_TYPE_UNSPECIFIEDModelType unspecified.
- Google
Cloud Dialogflow V2Smart Reply Model Metadata Training Model Type Smart Reply Dual Encoder Model - SMART_REPLY_DUAL_ENCODER_MODELModelType smart reply dual encoder model.
- Google
Cloud Dialogflow V2Smart Reply Model Metadata Training Model Type 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.
- 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.
- "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 Cloud Native is in preview. Google Cloud Classic is fully supported.