We are pleased to announce the launch of very demanded feature:
Make ML Skills and Datasets public via URL + API Key
What does this enable?
- Deploying ML Skills and continuously improving them on AI Center running in the Automation Cloud without needing to migrate from your existing on-premises Orchestrator.
- Deploying ML Skills and continuously improving them outside of Robots (e.g. add them to your UiPath Apps or even use them within a 3rd party application).
How does this work
The first step is to expose your entities (Datasets and ML Skills) as an endpoint to be able to call them from your on-premises (or not connected) infrastructure.
- Make Dataset public
To make your dataset your dataset public simple select the option while creating or updating your dataset:
Then in dataset details you will see the endpoint and corresponding API Key, you have the possibility to change the API Key but note that old one will stop working and old processes may break.
- Make ML Skills public
To make your ML Skills public, first deploy your ML Skill as usual and then change deployment to make it public:
Again this will expose and endpoint and corresponding API Key to consume this endpoint.
Note: Document Understanding Skills won’t expose an API Key as you can simply use your Document Understanding API Key for all of them. This means that API Key needs to be the one associated with the account where your Skills are deployed.
- Call them from Studio
Download and install new ML Services Activities package (v1.1.6-preview) from preview feed. Both ML Skill and upload file activity have a new field call Connection Mode. Select endpoint and complete the details for accessing your entity (endpoint and API Key) as String.
For ML Skill, you also need to manually set the type of data that you want to send (Remember that JSON is JSON as a string here).
You are all set, you can now start building your intelligent automation process and complete the feedback loops from your on-premises existing infrastructure to AI Center on UiPath Cloud.