Managing ML Skills
Creating ML Skills
Stopping ML Skills
To stop an ML Skill, use the following procedure:
Redeploying Stopped ML Skills
To redeploy an ML Package, use the following procedure:
Managing Package Versions
The ML Skill Details page enables you to manage the package version used within the deployed skill. You can update the skill to use a specific package version, or you can perform a rollback to the previously used version.
Updating Package Version
Rolling Back to Previous Version
- In the ML Skill Details page, click Rollback. The Update Skill window is displayed.
- In the Update Skill window, click OK to update the skill to use the previous used package version.
Modifying Current Deployment
In addition to updating a skill to a different version, a deployed skill can be kept at the same version, but modified to use a GPU or not. To do that, select Modify current deployment in the ML Skill Details page > Update skill window, as below:
Enabling GPU disables the CPU choices, from the Resources Per Replica field, and the AI Units are updated, based on your selection in the Replica Count field.
Make ML Skill Public/Private
You have the possibility to make an ML Skill public. Doing so, the ML Skill will be accessible via an endpoint from outside of UiPath environment. This means that you can call it without the need to go through a robot connected to the specific tenant.
To do that, select Modify current deployment in the ML Skill Details page > Update skill window, as below.
Note this will redeploy the ML Skill, once the ML Skill is available you will see the corresponding url in the ML Skill Details and a button will help you copying the URL. Depending of base ML Package an API Key will also be exposed to be used with this Skill in ML Skill activity.
- Port 433 must be open.
- Access to the target ML Skill URL.
- Access to the AI Units API key for the organization the ML Skill is deployed on.
Deleting ML Skills
ML Skills Report
You can download a report of ML Skill by clicking on the Download ML Skills Report button.
We recommend attaching this report when submitting an issue for faster troubleshooting.
This report gathers all the necessary information required to debug an issue, including account ID, tenant ID, AI Units, and the respective package and ML Skill information.
Check the screenshot below for an ML Skills report example.