flags:
  priority:
    arg_name: priority
    api_field: googleCloudDialogflowV2Intent.priority
    help_text: |
      Priority of the intent.

      Higher numbers represent higher priorities. Zero or negative numbers mean that the intent is
      disabled. Default priority is 500000.

  is_fallback:
    arg_name: is-fallback
    help_text: If true, set this intent as a fallback intent.
    api_field: googleCloudDialogflowV2Intent.isFallback
    type: bool
    action: store_true
  training_phrases:
    arg_name: training-phrases
    api_field: googleCloudDialogflowV2Intent.trainingPhrases
    type: googlecloudsdk.command_lib.dialogflow.intents.hooks:TrainingPhrasesType
    help_text: |
      List of examples or templates.

      Can be provided as comma separated unannotated examples or as a list training phrase objects.
      To provide training phrase objects, specify the flag with `--flags-file`.

      For example, use `--flags-file=flags.yaml`, where `flags.yaml` contains:

      ```
      --training-phrases:
        - type: TEMPLATE
          parts:
          - text: I love the color
          - text: red
            entityType: <entity_type_id>
            alias: color
      ```

      For more information on training phrases, see:
      https://cloud.google.com/dialogflow-enterprise/docs/reference/rest/Shared.Types/Intent#TrainingPhrase

      For more information on `--flags-file`, see `gcloud topics flags-file`.
  responses:
    arg_name: responses
    api_field: googleCloudDialogflowV2Intent.messages
    type: googlecloudsdk.command_lib.dialogflow.intents.hooks:ResponseToMessage
    help_text: |
      Comma separated list of simple text responses to send to the user.
  ml_enabled:
    arg_name: ml-enabled
    api_field: googleCloudDialogflowV2Intent.mlDisabled
    type: bool
    default: true
    action: store_true
    help_text: |
      If true, enable machine learning for the intent.
