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Testing a deployed model

How to test a deployed model

As soon as you deploy one of your models, you can manually test it.

To test a deployed model, proceed as follows:

  1. Navigate to NLU → Deployments section.

  2. Select a deployed model and click on it. The following page opens:

deployment.png
  1. Click on the Test NLU Deployment button.

You can only test running models. If a deployed model is stopped, the Test NLU Deployment button will be greyed out.

test_button.png
  1. The following window opens.

request_body.png
  1. In the Request tab, make necessary changes in the data by directly editing the values:

    1. Hover over the value you want to edit and click the Edit icon.

      edit_icon.png

    2. Make changes and click the Tick icon.

      tick-icon.png

  2. Click the Test button to start testing.

  3. The response is returned as JSON and displayed in the Response tab. You can copy the response body by clicking the Copy icon.

response.png

Below you can find the description of both request and response properties.

JSON request description

Property

Description

flow_id

The NLU workflow ID that indicates the engine running an annotation.

input

User input.

 

entries

Utterances input by the user.

dialog_context

Dialog context information used to evaluate user input and decide on the next system actions. Part of this context can be referenced in the creation of context sensitive rules.

 

max_nbest

Reserved.

 

nbest

Reserved.

 

ambiguous_utterance

User’s previous utterance(s) in cases the status of the previous step’s intent was ambiguous.

 

system_actions

System actions.

name

The name of the system action.

type

The type of the system action. The following values are applicable: Ask, Suggestion, Disambiguation, Confirmation, Announcement, BackEndCall

subtype

Defines an explicit intent request. The following subtypes are possible:

  • GetIntent: System requests, confirms, disambiguates an intent.

  • GetEntity: System requests, confirms, disambiguates an entity.

tag

Describes the system action. Typically used to group similar actions together.

level

The error level used to identify the prompt that was used. Applicable values are: normal, error, unrecovered.

prompt

The prompt used for the system action.

JSON response description

Property

Description

utterance

Phrase under query.

intents

List of intents and their parameters.

 

name

intent the queried phrase is associated with.

 

source

The source the intent is originated from.
Valid values:

  • ml is Machine Learning, used to expand your model’s understanding using your custom data.

  • rb is rule-based NLU, the out-of-the-box understanding based on the model’s domain.

confidence

The Machine Learning confidence for the intent.

score

A numerical value determining the validity of a constraint for an intent.

 

constraint

Details about the constraint that matches this intent. Null for ml intents.

segment_index

An indicator used in understanding utterances:

  • if there are no connecting words in the utterance, it returns Null.

  • if there are connecting words in the utterance, depending on the part of the utterance, it returns 1 or 2.

nbest_intents

List of nbest intents and their parameters.

 

name

intent the queried phrase is associated with.

 

source

The source the intent is originated from.
Valid values:

  • ml is Machine Learning, used to expand your model’s understanding using your custom data.

  • rb is rule-based NLU, the out-of-the-box understanding based on the model’s domain.

 

confidence

The Machine Learning confidence for the intent.

score

A numerical value determining the validity of a constraint for an intent.

constraint

Details about the constraint that matches this intent. Null for ml intents.

matched_selection_entities

Entities returned based on given utterance.

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