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: