> ## Documentation Index
> Fetch the complete documentation index at: https://anaconda.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Working with channels and packages

Data Science & AI Workbench uses *packages* to bundle software files and information about the software—such as its name, specific version and description—into a single file that can be easily installed and managed.

Packages are distributed via *channels*. Channels can point to a cloud-based repository or a private location on a remote or local repository that you or someone else in your organization created. For more information, see [channels and packages](./channels).

<Note>
  Workbench supports the use of both `.conda` and `.pip` packages in its repository. To manage channels and packages for your Workbench Repository using a command line interface (CLI), follow the steps for the [administration server setup](../../environment-prep/byok8s-prep#administration-server) on your current machine to install the CLI.
</Note>

[Building a conda package](./build) requires familiarity with the conda package manager and command line interface (CLI), so not all Workbench users will create packages and channels.

Many Workbench users can interact with packages primarily within the context of *projects* and *deployments*. In this case, they will likely do the following:

* Access and download any packages and installers they need from the list of available channels.
* Work with the contents of the package as they create models and dashboards.
* [Add any packages the project depends on](../projects/project-config#adding-conda-packages) to the project configurations before [deploying the project](../deployments/main).

Other users might primarily build packages, [upload them to channels](./channels#uploading-a-package-to-a-channel), and [share them with others](./channels#sharing-channels) to access and download.