Hub¶

The 3LC Hub is a browser-based, no-code entry point to the 3LC platform. It enables users to move seamlessly from data to model to insights without writing code or changing existing infrastructure, unifying dataset management, model training, performance analysis, and retraining into a single continuous, data-centric workflow.

Installation¶

The 3LC Hub makes use of several other 3LC components, and it has its own rich getting started page that may be used to guide you through installation and startup of those components.

Some of those components - including the 3LC Python Package, the Object Service, and the Dashboard - have installation instructions that may also be found in the main getting started page in these docs. But the recommended approach is to use the Hub directly.

Which deployment option should I use, Default or Enterprise On-Prem?

There are two deployment options for 3LC. Regardless of which you choose, your ML data never leaves your infrastructure. To learn more, refer to Deployment Options.

For most cases, we recommend the Default deployment. It uses services hosted by 3LC Inc. to manage user accounts and workspaces and to serve the Dashboard.

The Enterprise On-Prem deployment can be used for running 3LC in isolated environments with restricted access to the public internet. The Dashboard server is hosted in your own infrastructure. Please contact the Sales Team if you are interested in Enterprise On-Prem or in discussing other types of customization.

Which package installer should I use?

Use the Python package installer you prefer! We use uv ourselves and warmly recommend it, but if you are a happy user of pip there is no particular reason to change.

In both cases, we recommend installing the 3LC Python Package in a virtual environment using a supported Python version and platform.

With the Default deployment, we recommend that you continue directly to launching the 3LC Hub below.

Exchange the credential placeholders (USERNAME and PASSWORD) in the snippet below before executing the command, which installs the 3LC Hub Frontend Service.

uv pip install --index-url https://<USERNAME>:<PASSWORD>@pypi.3lc.ai/repositories/prereleases --extra-index-url https://pypi.org/simple 3lc-hub-frontend
pip install --index-url https://<USERNAME>:<PASSWORD>@pypi.3lc.ai/repositories/prereleases --extra-index-url https://pypi.org/simple 3lc-hub-frontend

Launch the Hub¶

Launch the Hub in a browser at https://hub-beta.3lc.ai. Assuming you have not yet started the other 3LC components it requires, you will automatically be redirected to the Hub’s built-in getting started page to make sure everything gets set up correctly. Once everything is running as expected, the Hub will automatically connect to the other components and redirect you to its home page.

To use the 3LC Hub, first start the 3LC Hub Frontend Service, which serves the Hub to the web browser. The Hub Frontend Service requires an authentication secret that will also be required when starting other components the Hub interacts with. This secret is used to secure communication between services in the Enterprise On-Prem deployment. It should be a strong, random string known only to those services. See Secure Communication for more details.

The authentication secret can be specified using the environment variable TLC_OBJECT_SERVICE_AUTH_SECRET.

export TLC_OBJECT_SERVICE_AUTH_SECRET=<AUTH_SECRET>
set TLC_OBJECT_SERVICE_AUTH_SECRET=<AUTH_SECRET>

To start the Hub Frontend Service, use the command:

3lc-hub-frontend

Once it is running, the Hub Frontend Service command will print out the URL where the 3LC Hub can be accessed. Open a browser and navigate to that URL to launch the Hub.

Assuming you have not yet started the other 3LC components the Hub requires, you will automatically be redirected to the Hub’s built-in getting started page to make sure everything gets set up correctly. Once everything is running as expected, the Hub will automatically connect to the other components and redirect you to its home page.

The Hub Frontend Service may be terminated by pressing Ctrl-C in the terminal.