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docs(trtllm): Update the trtllm installation instructions#11066

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tanmayv-trtllm-install-doc
Jul 2, 2026
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docs(trtllm): Update the trtllm installation instructions#11066
rmccorm4 merged 3 commits into
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tanmayv-trtllm-install-doc

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@tanmayv25

@tanmayv25 tanmayv25 commented Jun 29, 2026

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Overview:

Updates the installation instructions for TRTLLM. The tensorrt-llm pip installation is fragile and might not work OOTB. We are also not exercising the ai-dynamo[trtllm] in our CI which makes instructions in our documentation in regards to trtllm inaccurate.

Related Issues

🚫 This PR is NOT linked to an issue:

  • Confirmed — no related issue

Summary by CodeRabbit

  • Documentation
    • Clarified local installation guidance to show that PyPI installs are supported for vLLM and SGLang only.
    • Updated TensorRT-LLM setup instructions to direct users to the container-based installation path.
    • Refined troubleshooting guidance for Python version compatibility with TensorRT-LLM.
    • Aligned release artifact instructions with the recommended container workflow for TensorRT-LLM.

@tanmayv25 tanmayv25 requested a review from a team as a code owner June 29, 2026 22:43
@github-actions github-actions Bot added the documentation Improvements or additions to documentation label Jun 29, 2026
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Review Change Stack

Walkthrough

Documentation updates across three files remove TensorRT-LLM from the PyPI installation path (Option B), restricting it to vLLM and SGLang only. TensorRT-LLM users are redirected to the NGC tensorrtllm-runtime container. Troubleshooting and release-artifacts reference docs are updated accordingly.

Changes

TensorRT-LLM container-only redirect

Layer / File(s) Summary
Option B restriction and troubleshooting (EN + ZH)
docs/getting-started/local-installation.md, docs/getting-started/local-installation.zh-CN.md
Option B is now marked vLLM/SGLang-only; TensorRT-LLM pip install steps are removed; Python 3.11 troubleshooting updated to offer tensorrtllm-runtime container as alternative.
Release artifacts NGC redirect
docs/reference/release-artifacts.md
Python Wheels section and Quick Install Commands replace ai-dynamo[trtllm] pip instructions with a docker pull for the tensorrtllm-runtime:1.2.1 NGC image.

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~3 minutes

🚥 Pre-merge checks | ✅ 5
✅ Passed checks (5 passed)
Check name Status Explanation
Description check ✅ Passed The description has an overview and the required no-issue confirmation, but it omits the Details and reviewer-start sections.
Docstring Coverage ✅ Passed No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.
Linked Issues check ✅ Passed Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check ✅ Passed Check skipped because no linked issues were found for this pull request.
Title check ✅ Passed The title accurately summarizes the main documentation change: revising TRTLLM installation instructions.

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Actionable comments posted: 2

🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

Inline comments:
In `@docs/getting-started/local-installation.md`:
- Around line 203-204: The TensorRT-LLM fallback note in the local installation
guide still suggests Python 3.10 or 3.12 as a valid option, but the updated flow
should be container-only. Update the affected paragraph in the
local-installation guidance to remove any local Python/PyPI fallback language
and keep only the `tensorrtllm-runtime` container path (Option A), making sure
the surrounding Option B wording is consistent with the `TensorRT-LLM` install
flow.

In `@docs/getting-started/local-installation.zh-CN.md`:
- Around line 203-204: The local-installation guidance still suggests Python
3.10 or 3.12 as a TensorRT-LLM fallback, but the updated flow should be
container-only. Update the note in the TensorRT-LLM section of the
getting-started local installation doc so it no longer mentions any local Python
version workaround, and make the wording around the TensorRT-LLM install path
consistent with the option that uses the tensorrtllm-runtime container.
🪄 Autofix (Beta)

Fix all unresolved CodeRabbit comments on this PR:

  • Push a commit to this branch (recommended)
  • Create a new PR with the fixes

ℹ️ Review info
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Configuration used: Path: .coderabbit.yaml

Review profile: CHILL

Plan: Enterprise

Run ID: b3c442de-4702-45bb-b7ec-33f6b5478968

📥 Commits

Reviewing files that changed from the base of the PR and between 0adf974 and 244286d.

📒 Files selected for processing (3)
  • docs/getting-started/local-installation.md
  • docs/getting-started/local-installation.zh-CN.md
  • docs/reference/release-artifacts.md

Comment thread docs/getting-started/local-installation.md Outdated
Comment thread docs/getting-started/local-installation.zh-CN.md Outdated
Remove the local Python 3.10/3.12 fallback suggestion from the
TensorRT-LLM troubleshooting note, keeping only the tensorrtllm-runtime
container path (Option A) for consistency with the Option B install flow.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
@rmccorm4 rmccorm4 changed the title doc: Update the trtllm installation instructions docs(trtllm): Update the trtllm installation instructions Jul 2, 2026
@github-actions github-actions Bot added the docs label Jul 2, 2026
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Signed-off-by: Ryan McCormick <mccormick.codes@gmail.com>
@rmccorm4 rmccorm4 enabled auto-merge (squash) July 2, 2026 07:15
@rmccorm4 rmccorm4 merged commit dd3b71e into main Jul 2, 2026
79 of 80 checks passed
@rmccorm4 rmccorm4 deleted the tanmayv-trtllm-install-doc branch July 2, 2026 07:17
dagil-nvidia added a commit that referenced this pull request Jul 2, 2026
Regenerate the mirror from latest main so the TRT-LLM installation
changes from #11066 carry into the translated page, and update the
dynamo-docs skill's translation convention to the fern/translations
mirror layout.

Signed-off-by: Dan Gil <dagil@nvidia.com>
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3 participants