[None][docs] update stale link for AutoDeploy #7135
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📝 WalkthroughWalkthroughUpdated the AutoDeploy link in README.md’s Useful Links section from a local repository path to an external NVIDIA documentation URL; anchor text and description remain unchanged. No other content or exported/public declarations were modified. Changes
Sequence Diagram(s)(omitted — changes are documentation-only and do not affect runtime control flow) Estimated code review effort🎯 1 (Trivial) | ⏱️ ~2 minutes Possibly related PRs
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Actionable comments posted: 0
🧹 Nitpick comments (2)
README.md (2)
256-256: Fix markdownlint MD004: use asterisks for list bullets.The linter expects
*list markers; this line uses-. Update the bullet to keep CI clean and stay consistent with the repo’s markdown style.Apply within this PR (minimal change):
- - [AutoDeploy](https://nvidia.github.io/TensorRT-LLM/torch/auto_deploy/auto-deploy.html): A prototype backend for TensorRT-LLM to simplify and accelerate the deployment of PyTorch models. + * [AutoDeploy](https://nvidia.github.io/TensorRT-LLM/torch/auto_deploy/auto-deploy.html): A prototype backend for TensorRT-LLM to simplify and accelerate the deployment of PyTorch models.Optional follow-up for consistency: convert the entire “Useful Links” block (Lines 254–257) to
*bullets as well.
256-256: Optional: add automated link checking to CI to prevent future rot.Consider a lightweight GitHub Action using lychee to catch broken/stale links in Markdown on every PR.
Example workflow snippet (save as .github/workflows/link-check.yml):
name: Link Check on: pull_request: paths: - '**/*.md' jobs: lychee: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: lycheeverse/lychee-action@v1 with: args: --no-progress --max-concurrency 4 --accept 200,204 --exclude-mail ./README.md env: GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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📒 Files selected for processing (1)
README.md(1 hunks)
🧰 Additional context used
🪛 markdownlint-cli2 (0.17.2)
README.md
256-256: Unordered list style
Expected: asterisk; Actual: dash
(MD004, ul-style)
🔇 Additional comments (2)
README.md (2)
256-256: LGTM: Switched AutoDeploy link to canonical docs.Good call moving from a repo-local path to the published documentation URL to reduce future staleness.
256-256: AutoDeploy link verification passed
- The URL
https://nvidia.github.io/TensorRT-LLM/torch/auto_deploy/auto-deploy.htmlreturns HTTP 200 with no redirects.- No further updates are required for this link.
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Actionable comments posted: 0
🧹 Nitpick comments (1)
README.md (1)
254-258: Fix markdownlint MD004 (unordered list style) in Useful Linksmarkdownlint flags the list marker style here (expects asterisks, found dashes). Aligning with the repo’s lint rule will keep CI/lint quiet and make the section consistent with other lists above.
Apply this diff to switch the markers:
- - [Quantized models on Hugging Face](https://huggingface.co/collections/nvidia/model-optimizer-66aa84f7966b3150262481a4): A growing collection of quantized (e.g., FP8, FP4) and optimized LLMs, including [DeepSeek FP4](https://huggingface.co/nvidia/DeepSeek-R1-FP4), ready for fast inference with TensorRT-LLM. - - [NVIDIA Dynamo](https://github.com/ai-dynamo/dynamo): A datacenter scale distributed inference serving framework that works seamlessly with TensorRT-LLM. - - [AutoDeploy](https://nvidia.github.io/TensorRT-LLM/torch/auto_deploy/auto-deploy.html): A prototype backend for TensorRT-LLM to simplify and accelerate the deployment of PyTorch models. - - [WeChat Discussion Group](https://github.com/NVIDIA/TensorRT-LLM/issues/5359): A real-time channel for TensorRT-LLM Q&A and news. + * [Quantized models on Hugging Face](https://huggingface.co/collections/nvidia/model-optimizer-66aa84f7966b3150262481a4): A growing collection of quantized (e.g., FP8, FP4) and optimized LLMs, including [DeepSeek FP4](https://huggingface.co/nvidia/DeepSeek-R1-FP4), ready for fast inference with TensorRT-LLM. + * [NVIDIA Dynamo](https://github.com/ai-dynamo/dynamo): A datacenter scale distributed inference serving framework that works seamlessly with TensorRT-LLM. + * [AutoDeploy](https://nvidia.github.io/TensorRT-LLM/torch/auto_deploy/auto-deploy.html): A prototype backend for TensorRT-LLM to simplify and accelerate the deployment of PyTorch models. + * [WeChat Discussion Group](https://github.com/NVIDIA/TensorRT-LLM/issues/5359): A real-time channel for TensorRT-LLM Q&A and news.
📜 Review details
Configuration used: .coderabbit.yaml
Review profile: CHILL
Plan: Pro
💡 Knowledge Base configuration:
- MCP integration is disabled by default for public repositories
- Jira integration is disabled by default for public repositories
- Linear integration is disabled by default for public repositories
You can enable these sources in your CodeRabbit configuration.
📒 Files selected for processing (1)
README.md(1 hunks)
🧰 Additional context used
🪛 markdownlint-cli2 (0.17.2)
README.md
256-256: Unordered list style
Expected: asterisk; Actual: dash
(MD004, ul-style)
🔇 Additional comments (2)
README.md (2)
256-256: LGTM: AutoDeploy link now points to published docsThe update from a repo-local path to the docs site improves discoverability and avoids 404s when browsing on GitHub.
256-256: URL Verification CompletedThe URL
https://nvidia.github.io/TensorRT-LLM/torch/auto_deploy/auto-deploy.htmlreturns HTTP 200 and does not redirect, confirming it’s canonical and stable.
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/bot skip --comment "README change only" |
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PR_Github #16090 [ skip ] triggered by Bot |
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PR_Github #16090 [ skip ] completed with state |
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