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Add lychee link checking and fix broken links - #760

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jayavenkatesh19 merged 5 commits into
rapidsai:mainfrom
jayavenkatesh19:lychee-link-check
Sep 18, 2026
Merged

jayavenkatesh19 merged 5 commits into
rapidsai:mainfrom
jayavenkatesh19:lychee-link-check

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@jayavenkatesh19

@jayavenkatesh19 jayavenkatesh19 commented Sep 17, 2026 •

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Closes #744, with the design in the comment on the issue

The weekly check (lychee.yml) builds the site and runs lychee over the rendered HTML every Monday at 08:00 UTC. On failure, it waits for 5 minutes and rechecks only the failed links. If failures appear, it comments on an existing open issue (we need to create a new lychee label as that is what it filters on), or opens a new issue and fails the job.

PR check (in build-and-deploy.yaml) runs lychee on rendered pages whose sources changed in the PR. Informational only without failing the PR checks. This check is only informative because any transitive failures (website being down temporarily), should not fail the PR checks. This is caught by the weekly workflow instead which has a 5 min wait time before retries.

I also fixed 17 broken links which showed up when I ran lychee locally. Removed two dead links to non existing pages, and added anchors to raw HTML links.

Signed-off-by: Jaya Venkatesh <jjayabaskar@nvidia.com>
@jayavenkatesh19 jayavenkatesh19 self-assigned this Sep 17, 2026
@jayavenkatesh19
jayavenkatesh19 requested a review from a team as a code owner September 17, 2026 22:32
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@ncclementi ncclementi left a comment •

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Left a few comments with some questions and suggestions.

Now I noticed that the on PR action run see summary https://github.com/rapidsai/deployment/actions/runs/35282550055 it's unclear based on the report if it's checking everything or just what was modified. Any ideas?

Comment thread .github/workflows/build-and-deploy.yml Outdated
uses: lycheeverse/lychee-action@e7477775783ea5526144ba13e8db5eec57747ce8 # v2.9.0
with:
args: --no-progress --root-dir "$(pwd)/build/dirhtml" --files-from "${RUNNER_TEMP}/changed-pages"
fail: false

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If this doesn't fail on PR, should we publish a comment with the failed links in the PR?

env:
GH_TOKEN: ${{ github.token }}
run: |
number="$(gh issue list --repo "${GITHUB_REPOSITORY}" --label lychee --state open --limit 1 --json number --jq '.[0].number // empty')"

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Created the label.

Comment thread source/cloud/aws/sagemaker.md Outdated
## SageMaker AI Estimators

RAPIDS can also be used in [SageMaker Estimators](https://sagemaker.readthedocs.io/en/stable/api/training/estimators.html).
RAPIDS can also be used in [SageMaker Estimators](https://sagemaker.readthedocs.io/en/v2.245.0/api/training/estimators.html).

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It seems like the estimators page is from the specific version, but it might be outdated. Should we point to this https://sagemaker.readthedocs.io/en/stable/training/#model-training

"\n",
"## RAPIDS\n",
"The RAPIDS framework provides a suite of libraries to execute end-to-end data science pipelines entirely on GPUs. One of the libraries in this framework is cuML, which implements common machine learning models with a scikit-learn-compatible API and a GPU-accelerated backend. You can learn more about RAPIDS [here](https://rapids.ai/about.html).\n",
"The RAPIDS framework provides a suite of libraries to execute end-to-end data science pipelines entirely on GPUs. One of the libraries in this framework is cuML, which implements common machine learning models with a scikit-learn-compatible API and a GPU-accelerated backend. You can learn more about RAPIDS [here](https://rapids.ai/).\n",

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It seems we didn't catch this link but let's point to here instead. We'll change the language of rapids on a alter PR

Suggested change
"The RAPIDS framework provides a suite of libraries to execute end-to-end data science pipelines entirely on GPUs. One of the libraries in this framework is cuML, which implements common machine learning models with a scikit-learn-compatible API and a GPU-accelerated backend. You can learn more about RAPIDS [here](https://rapids.ai/).\n",
"The RAPIDS framework provides a suite of libraries to execute end-to-end data science pipelines entirely on GPUs. One of the libraries in this framework is cuML, which implements common machine learning models with a scikit-learn-compatible API and a GPU-accelerated backend. You can learn more about RAPIDS [here](https://docs.nvidia.com/datascience/).\n",

Signed-off-by: Jaya Venkatesh <jjayabaskar@nvidia.com>
Signed-off-by: Jaya Venkatesh <jjayabaskar@nvidia.com>
Signed-off-by: Jaya Venkatesh <jjayabaskar@nvidia.com>
@jayavenkatesh19
jayavenkatesh19 merged commit 13a71ec into rapidsai:main Sep 18, 2026
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Implement Lychee GHA

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