Label Studio on Spaces
Last updated
Last updated
is an for labeling, annotating, and exploring many different data types. Additionally, Label Studio includes a powerful that can be used for new model training, active learning, supervised learning, and many other training techniques.
This guide will teach you how to deploy Label Studio for data labeling and annotation within the Hugging Face Hub. You can use the default configuration of Label Studio as a self-contained application hosted completely on the Hub using Docker for demonstration and evaluation purposes, or you can attach your own database and cloud storage to host a fully-featured production-ready application hosted on Spaces.
You can deploy Label Studio on Spaces with just a few clicks:
Spaces requires you to define:
An Owner: either your personal account or an organization you’re a part of.
A Space name: the name of the Space within the account you’re creating the Space.
The Visibility: private if you want the Space to be visible only to you or your organization, or public if you want it to be visible to other users or applications using the Label Studio API (suggested).
By default, Label Studio is installed in Spaces with a configuration that uses local storage for the application database to store configuration, account credentials, and project information. Labeling tasks and data items are also held in local storage.
Storage in Hugging Face Spaces is ephemeral, and the data you store in the default configuration can be lost in a reboot or reset of the Space. Because of this, we strongly encourage you to use the default configuration only for testing and demonstration purposes.
After launching Label Studio, you will be presented with the standard login screen. You can start by creating a new account using your email address and logging in with your new credentials. Periodically after logging in, Label Studio will warn you that the storage is ephemeral and data could be lost if your Space is restarted. You will also be preset with a prompt from Heidi, the helpful Label Studio mascot, to create a new project to start labeling your data. To get started, check out the Label Studio with a guide on how to build an annotation interface for sentiment analysis.
To make your Space production-ready, you will need to make three configuration changes:
Disable the unrestricted creation of new accounts.
Enable persistence by attaching an external database.
Attach cloud storage for labeling tasks.
LABEL_STUDIO_DISABLE_SIGNUP_WITHOUT_LINK: Setting this value to true will disable unrestricted account creation.
LABEL_STUDIO_USERNAME: This is the username of the account that you will use as the first user in your Label Studio Space. It should be a valid email address.
LABEL_STUDIO_PASSWORD: The password that will be associated with the first user account.
Restart the Space to apply these settings. The ability to create new accounts from the login screen will be disabled. To create new accounts, you will need to invite new users in the Organization settings in the Label Studio application.
Set the following secret variables to match your own hosted instance of Postgres. We strongly recommend setting these as secrets to prevent leaking information about your database service to the public in your spaces definition.
DJANGO_DB: Set this to default.
POSTGRE_NAME: Set this to the name of the Postgres database.
POSTGRE_USER: Set this to the Postgres username.
POSTGRE_PASSWORD: Set this to the password for your Postgres user.
POSTGRE_HOST: Set this to the host that your Postgres database is running on.
POSTGRE_PORT: Set this to the port that your Pogtgres database is running on.
STORAGE_PERSISTENCE: Set this to 1 to remove the warning about ephemeral storage.
Restart the Space to apply these settings. Information about users, projects, and annotations will be stored in the database, and will be reloaded by Label Studio if the space is restarted or reset.
Amazon S3
STORAGE_TYPE: Set this to s3.
STORAGE_AWS_ACCESS_KEY_ID: <YOUR_ACCESS_KEY_ID>
STORAGE_AWS_SECRET_ACCESS_KEY: <YOUR_SECRET_ACCESS_KEY>
STORAGE_AWS_BUCKET_NAME: <YOUR_BUCKET_NAME>
STORAGE_AWS_REGION_NAME: <YOUR_BUCKET_REGION>
STORAGE_AWS_FOLDER: Set this to an empty string.
Google Cloud Storage
STORAGE_TYPE: Set this to gcs.
STORAGE_GCS_BUCKET_NAME: <YOUR_BUCKET_NAME>
STORAGE_GCS_PROJECT_ID: <YOUR_PROJECT_ID>
STORAGE_GCS_FOLDER: Set this to an empty string.
GOOGLE_APPLICATION_CREDENTIALS: Set this to /opt/heartex/secrets/key.json.
Azure Blob Storage
STORAGE_TYPE: Set this to azure.
STORAGE_AZURE_ACCOUNT_NAME: <YOUR_STORAGE_ACCOUNT>
STORAGE_AZURE_ACCOUNT_KEY: <YOUR_STORAGE_KEY>
STORAGE_AZURE_CONTAINER_NAME: <YOUR_CONTAINER_NAME>
STORAGE_AZURE_FOLDER: Set this to an empty string.
The default configuration on Label Studio allows for the unrestricted creation of new accounts for anyone who has the URL for your application. You can by adding the following configuration secrets to your Space Settings.
By default, this Space stores all project configuration and data annotations in local storage with SQLite. If the Space is reset, all configuration and annotation data in the Space will be lost. You can enable configuration persistence by , guaranteeing that all project and annotation settings are preserved.
By default, the only data storage enabled for this Space is local. In the case of a Space reset, all data will be lost. To enable permanent storage, you must enable a . Choose the appropriate cloud connector and configure the secrets for it.
To get started with Label Studio, check out the Label Studio , which walks you through an example sentiment analysis annotation project. You can find a full set of resources about Label Studio and the Label Studio community on at the . This includes , an for trying out different annotation interfaces, and links to join the .
