This is documentation for Rasa X/Enterprise Documentation v1.3.x, which is no longer actively maintained.
For up-to-date documentation, see the latest version (1.4.x).

Version: 1.3.x

Set Up a CI/CD pipeline

When improving your assistant, you’ll make different kinds of fixes to your bot. To automate the testing and integration of these improvements into your deployed assistant, you should set up a CI/CD (Continuous Integration/Continuous Deployment) pipeline on your connected git repository.

For example, you could add a step in your pipeline that pushes a newly trained model to Rasa Enterprise everytime a change is merged into your main branch. For more information on setting up a CI/CD pipeline, check out the Rasa Open Source user guide on CI/CD.

Here are a few examples of CI/CD pipelines in Github Actions to get you started:

  • The rasa-demo CI/CD pipeline includes the following steps; some are conditional:

    • Lints and type-tests the action code

    • Validates the data

    • Runs NLU cross-validation

    • Trains a model

    • Tests the model on test conversations

    • Builds and tags an action image

    • Pushes the action image to a private Google Cloud Container Registry

  • This example includes some of the steps above, but with fewer conditions:

  • This example includes the steps above, but also includes steps to create an AWS EKS cluster and deploy the bot there: