Package com.hashicorp.cdktf.providers.google.dialogflow_cx_flow

Class DialogflowCxFlowNluSettings.Builder

java.lang.Object

com.hashicorp.cdktf.providers.google.dialogflow_cx_flow.DialogflowCxFlowNluSettings.Builder

All Implemented Interfaces:

software.amazon.jsii.Builder<DialogflowCxFlowNluSettings>

Enclosing interface:

DialogflowCxFlowNluSettings

@Stability(Stable)
public static final class DialogflowCxFlowNluSettings.Builder
extends Object
implements software.amazon.jsii.Builder<DialogflowCxFlowNluSettings>

A builder for DialogflowCxFlowNluSettings

Constructor Summary

Constructors

Constructor	Description
Builder()

Method Summary

Modifier and Type	Method	Description
DialogflowCxFlowNluSettings	build()	Builds the configured instance.
DialogflowCxFlowNluSettings.Builder	classificationThreshold(Number classificationThreshold)	Sets the value of DialogflowCxFlowNluSettings.getClassificationThreshold()
DialogflowCxFlowNluSettings.Builder	modelTrainingMode(String modelTrainingMode)	Sets the value of DialogflowCxFlowNluSettings.getModelTrainingMode()
DialogflowCxFlowNluSettings.Builder	modelType(String modelType)	Sets the value of DialogflowCxFlowNluSettings.getModelType()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Builder

public Builder()

Method Detail

classificationThreshold

@Stability(Stable)
public DialogflowCxFlowNluSettings.Builder classificationThreshold(Number classificationThreshold)

Sets the value of DialogflowCxFlowNluSettings.getClassificationThreshold()

Parameters:

classificationThreshold - To filter out false positive results and still get variety in matched natural language inputs for your agent, you can tune the machine learning classification threshold. If the returned score value is less than the threshold value, then a no-match event will be triggered. The score values range from 0.0 (completely uncertain) to 1.0 (completely certain). If set to 0.0, the default of 0.3 is used. Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/dialogflow_cx_flow#classification_threshold DialogflowCxFlow#classification_threshold}

Returns:

this

modelTrainingMode

@Stability(Stable)
public DialogflowCxFlowNluSettings.Builder modelTrainingMode(String modelTrainingMode)

Sets the value of DialogflowCxFlowNluSettings.getModelTrainingMode()

Parameters:

modelTrainingMode - Indicates NLU model training mode. * MODEL_TRAINING_MODE_AUTOMATIC: NLU model training is automatically triggered when a flow gets modified. User can also manually trigger model training in this mode. * MODEL_TRAINING_MODE_MANUAL: User needs to manually trigger NLU model training. Best for large flows whose models take long time to train. Possible values: ["MODEL_TRAINING_MODE_AUTOMATIC", "MODEL_TRAINING_MODE_MANUAL"] Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/dialogflow_cx_flow#model_training_mode DialogflowCxFlow#model_training_mode}

Returns:

this

modelType

@Stability(Stable)
public DialogflowCxFlowNluSettings.Builder modelType(String modelType)

Sets the value of DialogflowCxFlowNluSettings.getModelType()

Parameters:

modelType - Indicates the type of NLU model. * MODEL_TYPE_STANDARD: Use standard NLU model. * MODEL_TYPE_ADVANCED: Use advanced NLU model. Possible values: ["MODEL_TYPE_STANDARD", "MODEL_TYPE_ADVANCED"] Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/dialogflow_cx_flow#model_type DialogflowCxFlow#model_type}

Returns:

this

build

@Stability(Stable)
public DialogflowCxFlowNluSettings build()

Builds the configured instance.

Specified by:

build in interface software.amazon.jsii.Builder<DialogflowCxFlowNluSettings>

Returns:

a new instance of DialogflowCxFlowNluSettings

Throws:

NullPointerException - if any required attribute was not provided