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Training with RasaX


For a detailed user guide for using RasaX, see

Access Rasa X GUI and Train a Bot

To access Rasa X's user interface and train a bot, follow the steps below.

  • To Access the Rasa X GUI, enter http://RasaX-FQDN:5002 in a browser on the machine where Rasa X is deployed. You will see a login screen, where you can enter the default password PASSW0RD

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  • The following Dashboard will appear after the login in displaying various options to help you train a bot.

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  • In the Config Tab, You can add the configuration of your NLU Pipeline, Language and Action Policies as shown below,

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  • In NLU Training Tab You can add examples, assign intents and can change the intents of various training examples.

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    You can also watch the example sentences which are already labeled, by switching to the Training Data Tab

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  • In the Stories tab, you can View, Edit, Delete and Compare stories.

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  • You can edit the domain of your bot in the Domain tab,

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  • You can add templates in the responses tab. In order to add a response, you first need to add it in Domain tab with a prefix utter_ (e.g utter_greet).

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  • Lastly, you can find the Train button under Training. Click on this after you are done with all the above steps.

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  • After the training is complete, you can go to the Models tab. Here you will see the newly trained model. You can mark this as Active.

    model.PNG


  • Conversations between the customer and the agent (if the suggestion is selected) are shown in the Rasa-X conversation tab. You can label the data here and create a story as well.

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  1. Talk to bot feature of Rasa-X is not compatible with Experflow's Custom Rasa 1.x only the strict learning feature is available.

  2. Templates for structured messages are not yet supported in Rasa X and need to be updated manually in the domain.yaml.