[TRTLLM-9157][doc] Guided decoding doc improvement #9359
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Signed-off-by: Enwei Zhu <[email protected]>
Signed-off-by: Enwei Zhu <[email protected]>
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📝 WalkthroughWalkthroughDocumentation for Guided Decoding is reorganized by creating a dedicated file with expanded content, removing the original section from sampling.md, and registering the new file in the documentation index for navigation. Changes
Estimated code review effort🎯 2 (Simple) | ⏱️ ~10 minutes
Pre-merge checks and finishing touches❌ Failed checks (1 inconclusive)
✅ Passed checks (2 passed)
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📒 Files selected for processing (3)
docs/source/features/guided-decoding.md(1 hunks)docs/source/features/sampling.md(0 hunks)docs/source/index.rst(1 hunks)
💤 Files with no reviewable changes (1)
- docs/source/features/sampling.md
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🧠 Learnings (2)
📓 Common learnings
Learnt from: venkywonka
Repo: NVIDIA/TensorRT-LLM PR: 6029
File: .github/pull_request_template.md:45-53
Timestamp: 2025-08-27T17:50:13.264Z
Learning: For PR templates in TensorRT-LLM, avoid suggesting changes that would increase developer overhead, such as converting plain bullets to mandatory checkboxes. The team prefers guidance-style bullets that don't require explicit interaction to reduce friction in the PR creation process.
📚 Learning: 2025-08-21T00:16:56.457Z
Learnt from: farshadghodsian
Repo: NVIDIA/TensorRT-LLM PR: 7101
File: docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md:36-36
Timestamp: 2025-08-21T00:16:56.457Z
Learning: TensorRT-LLM container release tags in documentation should only reference published NGC container images. The README badge version may be ahead of the actual published container versions.
Applied to files:
docs/source/features/guided-decoding.md
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- GitHub Check: Pre-commit Check
🔇 Additional comments (6)
docs/source/index.rst (1)
73-73: Documentation entry properly registered.The new guided-decoding.md file is correctly added to the Features toctree with proper placement and formatting.
docs/source/features/guided-decoding.md (5)
1-8: Documentation structure and introduction are clear.The opening section effectively explains guided decoding and clearly identifies the two supported backends with direct links to their specific versions.
10-311: Online API examples are comprehensive and well-formatted.All four backend types (JSON Schema, regex, EBNF, structural tag) are demonstrated with clear, runnable examples. The code follows proper Python conventions, and the brace escaping in the f-strings is correct. Expected outputs are realistic.
313-583: Offline API examples mirror online examples appropriately.The Offline API section maintains parallel structure and coverage as the Online API section. Code examples correctly use the LLM API and
GuidedDecodingParamswith proper imports and syntax. The structural tag implementation matches the online version semantically.
34-77: Model identifier format is correct—no changes needed.The model identifier "nvidia/Llama-3.1-8B-Instruct-FP8" is the correct Hugging Face–style NGC model ID per TensorRT-LLM and Model Optimizer documentation. The code example uses the current and official format for published containers.
6-7: Update LLGuidance version from v1.1.1 to v1.0.0 to match TensorRT-LLM 1.1 recommendations.XGrammar v0.1.21 is correct per the TensorRT-LLM release notes, but LLGuidance should be pinned to v1.0.0 rather than v1.1.1. Update line 7 to reference the correct version.
⛔ Skipped due to learnings
Learnt from: farshadghodsian Repo: NVIDIA/TensorRT-LLM PR: 7101 File: docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md:36-36 Timestamp: 2025-08-21T00:16:56.457Z Learning: TensorRT-LLM container release tags in documentation should only reference published NGC container images. The README badge version may be ahead of the actual published container versions.
Signed-off-by: Enwei Zhu <[email protected]>
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[TRTLLM-9157][doc] Guided decoding doc improvement
Description
This PR improves the documentation for guided decoding, comprehensively demonstrating all features.
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PR Checklist
Please review the following before submitting your PR:
PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.
PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.
Test cases are provided for new code paths (see test instructions)
Any new dependencies have been scanned for license and vulnerabilities
CODEOWNERS updated if ownership changes
Documentation updated as needed
Update tava architecture diagram if there is a significant design change in PR.
The reviewers assigned automatically/manually are appropriate for the PR.
Please check this after reviewing the above items as appropriate for this PR.
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