Changelog

New features

Prompts is now generally available

Prompts is now available in Label Studio Enterprise SaaS.

Prompts is a tool that leverages LLMs to automatically generate predictions for your labeling tasks, allowing you to pre-annotate data and quickly bootstrap projects. It can also be used to evaluate your LLM prompts against ground truth data.

For more information, see the Prompts documentation and Accelerate Labeling and Model Evaluation with Prompts—Now Generally Available.

Pause an annotator

There is a new action to pause annotators. This is available from the Members dashboard and via the API.

For more information, see Pause an annotator.

Personal access tokens

There is a new type of token available for API access. The new tokens use JWT standards and, unlike the current tokens in use, allow you to set an expiration date.

You can enable or disable these tokens from the Organization page. Once enabled, they will be available for users to generate from their Account & Settings page. Legacy tokens can still be used unless disabled from the organization level.

For more information, see Access tokens.

Deep link annotations and regions

You can now link directly to specific annotations or regions within an annotation. These actions are available from the labeling interface in the overflow menus for the annotation and the region.

Feature updates

Set ground truths by user

There is a new action from the Data Manager that allows you to mark the annotations submitted by a specific user as ground truth annotations.

Known issues

Users in the Manager, Annotator, and Reviewer role cannot currently retrieve their API access tokens from the Label Studio UI.

This does not affect the functionality of any existing scripts or automations currently using their access tokens.

Bug fixes

• Fixed an issue that was causing intermittent loading errors in the Data Manager.
• Fixed an issue where filters were not being respected when performing bulk annotation actions.
• Fixed an issue where bulk annotation was sometimes failing with a 500 error.
• Fixed an issue where bulk annotation was not respecting the Allow empty annotations setting.
• Fixed an issue that caused incorrect video frame to be rendered when pausing.
• Fixed an issue where users were getting their role reset if they were provisioned via SCIM without an assigned group.
• Fixed an issue where an error was sometimes thrown when loading the workspaces list.
• Fixed an issue that would cause an API error when switching workspaces and fetching the incorrect page of projects.

New features

Introducing the Prompts tool

The Prompts tool leverages ChatGPT to help you evaluate and refine your LLM prompts. You can also use Prompts to generate predictions for automating your labeling process, and to quickly bootstrap labeling projects.

For more information, see Automate Data Labeling with HumanSignal and our Prompts documentation.

Refreshed Label Studio interface

The Label Studio UI has been upgraded with updated colors and fonts, giving it a sleek new look while maintaining the same intuitive navigation you're familiar with. All Label Studio tools, features, and settings are still in the same place, ensuring a smooth transition.

Feature updates

Improved performance on the Projects list page due to improvement on the API level.

Breaking changes

Fixed an issue with Google Cloud Storage when the connection has the Use pre-signed URLs option disabled. In these situations, Google was sending pre-signed URLs with the format https://storage.googleapis.com rather than sending BLOBs.

With this fix, Google Cloud Storage will begin returning BLOBs/base64 encoded data when Use pre-signed URLs is off. This means that Label Studio will start reading data from Google Cloud Storage buckets, which can result in large amounts of data being sent to your Label Studio instance - potentially affecting performance.

Bug fixes

• Fixed an issue where Redis storage connections were causing errors due to a missing field in the storage form (Storage Title).
• Fixed an issue where annotators were not being prompted to leave a comment when skipping a task, even though the project settings required them to do so.
• Fixed an issue where connected ML backends were unable to return more than one prediction per task.