The Language Understanding (LUIS) container loads your trained or published Language Understanding model. It provides access to the query predictions from the container's API endpoints. You plan to use them in your environment to comply with your organization's security and compliance requirements. As a prerequisite, you have a docker engine installed and configured on your host computer. It is also connected to Azure for billing purposes. You also have an Azure AI Services resource and trained or published The Language Understanding (LUIS) app packaged as a mounted input to the container. Review the steps below and sequence them to get the container image and use it on your host computer: Step 1: Query the container's prediction endpoint Step 2: Export the trained or published application package using the Language Understanding (LUIS) portal. Step 3: Move the package file into the required input directory on the host computer Step 4: Run the container with the required input mount and billing settings Step 5: Get the docker image using docker pull Step 6: Import the endpoint logs for active learning Step 7: Log user queries to enable active learning