From 6cb1b2dfc1c252e0227e47b242ff6f3255a55398 Mon Sep 17 00:00:00 2001 From: Dave Berenbaum Date: Sat, 21 Oct 2023 09:05:20 -0400 Subject: [PATCH] guide: explain artifacts and model registry (#4949) --- .../docs/command-reference/artifacts/get.md | 2 ++ .../discovering-and-accessing-data.md | 21 +++++++++++++++++++ 2 files changed, 23 insertions(+) diff --git a/content/docs/command-reference/artifacts/get.md b/content/docs/command-reference/artifacts/get.md index 7398ac36a1..00426fb138 100644 --- a/content/docs/command-reference/artifacts/get.md +++ b/content/docs/command-reference/artifacts/get.md @@ -3,6 +3,8 @@ Download an artifact tracked in the model registry into the current working directory (with optional Studio support). +> See also our `dvc.api.artifacts_show()` Python API function. + ## Synopsis ```usage diff --git a/content/docs/user-guide/data-management/discovering-and-accessing-data.md b/content/docs/user-guide/data-management/discovering-and-accessing-data.md index 8083eaec7d..615b968b66 100644 --- a/content/docs/user-guide/data-management/discovering-and-accessing-data.md +++ b/content/docs/user-guide/data-management/discovering-and-accessing-data.md @@ -127,3 +127,24 @@ with dvc.api.open( ) as f: # f is a file-like object which can be processed normally ``` + +## Artifacts + +You can add aliases and metadata for files and directories under the +artifacts section of +[`dvc.yaml`](/doc/user-guide/project-structure/dvcyaml-files#artifacts). This +can help you organize your artifacts, and you can use `dvc artifacts get` and +`dvc.api.artifacts_show()` to retrieve them by their alias rather than their +path. + +## Model Registry + +Artifacts become more useful as part of the model registry, where +semantic versions can be registered and lifecycle stages (think +`dev`/`test`/`prod`) can be assigned using Git tags managed by [GTO](/doc/gto). +These tags give you a full history of your model lifecycle in Git and enable you +to trigger CICD workflows based on changes in the model registry. With +[DVC Studio](https://studio.iterative.ai), you can see models and their metadata +across all projects, and you can download artifacts by name, version, and +lifecycle stage, without needing to configure access to the underlying Git +repository or remote storage.