Google
Cloud Platform
Amazon Web Services
Microsoft AzureConnect to SuperAnnotate
SuperAnnotate’s Python SDK integrates with Databricks to provide an all-in-one AI data infrastructure platform that helps to annotate, debug, manage, and version top-quality training data with Databricks’ exhaustive data management, distributed computing, and machine learning capabilities.
The SuperAnnotate connector simplifies this process by transforming annotation data into Apache Spark dataframes, enabling ML teams to shift their focus from data wrangling to training their machine learning models. This collaboration includes the ability to set up active learning workflows, where low-confidence predictions are automatically routed to the SuperAnnotate platform.
Requirements
Before you integrate with SuperAnnotate, you must have the following:
A Databricks SQL warehouse in your Databricks workspace.
A Databricks personal access token.
Note
As a security best practice, when you authenticate with automated tools, systems, scripts, and apps, Databricks recommends that you use personal access tokens belonging to service principals instead of workspace users. To create tokens for service principals, see Manage tokens for a service principal.
Connect to SuperAnnotate using Partner Connect
Note
Partner Connect only supports SQL warehouses for SuperAnnotate.
To connect your Databricks workspace to SuperAnnotate using Partner Connect, do the following:
In the sidebar, click
Partner Connect.Click the partner tile.
Check the provided information, and click Next.
You will be redirected to SuperAnnotate, where you can sign up, or log in if you already have an account.
After these steps, an Organization will be created for you, along with your first team, named My Team. Your organization will also automatically have a Databricks integration with the values given in Step 3, and it will be added to the team by default.
Next steps
Once you’ve set up your organization and team through Partner Connect, you’ll need to create an LLMs and GenAI project. Set up your form according to the data you’ll be importing, and add items with your Databricks integration.