vllm-omni/docs/contributing/README.md

Contributing to vLLM-Omni

Thank you for your interest in contributing to vLLM-Omni! This document provides guidelines and instructions for contributing.

!!! note vLLM-Omni hosts developer-facing meetings for Chinese- and English-language audiences. See Community Meetings for current schedules, access details, agendas, and past notes.

Getting Started

vLLM-Omni uses uv as the environment manager, to create and manage Python environments. Please follow the documentation to install uv. After installing uv, you can create a new Python environment using the following commands:

uv venv --python 3.12 --seed
source .venv/bin/activate

Development Environment for vLLM and vLLM-Omni

vLLM-Omni is quickly evolving, please see the installation guide for details. It's recommended to build from source to provide the latest development environment.

!!! tip vLLM-Omni is compatible with Python versions 3.10 to 3.12. However, we recommend developing with Python 3.12 to minimize the chance of your local environment clashing with our CI environment.

Adding a new model to vLLM-Omni

Please check model implementation for how to add diffusion and omni-modality models to vLLM-Omni.

Linting

vLLM-Omni uses pre-commit to lint and format the codebase. See pre-commit documentation if pre-commit is new to you. Setting up pre-commit is as easy as:

uv pip install pre-commit
pre-commit install

vLLM-Omni's pre-commit hooks will now run automatically every time you commit.

!!! tip You can manually run the pre-commit hooks using:

```bash
pre-commit run     # runs on staged files
pre-commit run --show-diff-on-failure --color=always --all-files  # runs on all files (short for --all-files)
```

!!! warning GitHub Actions pre-commit skips several local gates so a whole-tree --all-files run stays green while historical debt is cleaned up. The current SKIP list in .github/workflows/pre-commit.yml is check-mark, markdownlint-cli2, shellcheck, check-spdx-header, and mypy-3.10. Those hooks still run on your commit for changed files. A passing GitHub pre-commit check does not mean they passed locally. Hooks not on that list (forbidden imports, torch.cuda, TTS adapter ratchet, Buildkite schema, Ruff, typos, …) run in both places.

The hooks below are new relative to the previous Omni config (Ruff, typos, actionlint, YAML/whitespace, DCO sign-off, and the pickle-only checker were already there). check-pickle-imports is gone: pickle is now one rule inside check-forbidden-imports.

Hook id	Enforces	GitHub Actions
markdownlint-cli2	Markdown in docs/, recipes/, README.md, CONTRIBUTING.md (not .claude/ / .cursor/ / CLAUDE.md)	skipped
mypy-3.10	Type-check changed vllm_omni/ files (model trees excluded). tests/ uses --follow-imports skip	skipped
mypy-3.11 / 3.12 / 3.13	Same checker, extra Python versions	not installed; pre-commit run --hook-stage manual mypy-3.12
check-mark	Every tests/**/test_*.py has a CI level mark and a hardware platform mark or helper; no direct pytest.mark.H100 / SKU	skipped
check-tts-adapter-migration	self._tts_model_type branches in serving_speech.py must not increase	runs
shellcheck	*.sh quoting / undefined vars	skipped
check-spdx-header	Omni SPDX header on .py / .pyi / .sh / .rs / .proto	skipped
check-forbidden-imports	pickle, stdlib re/base64, Triton, TileLang, Hugging Face Hub download/API	runs
check-torch-cuda-call	Direct torch.cuda.* helpers outside platform adapters	runs
check-buildkite	.buildkite/*.yml against the Buildkite schema	runs

Related config (not a new hook id): Ruff TID251 also bans librosa and several torch.cuda.* names; typos is pinned and ignores git-describe hashes (+g + hex) and NumPy writeable. Keep the suggestion hook last in .pre-commit-config.yaml so autofix output does not bury the SKIP tip.

SPDX headers

Source files must start with:

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project

Rust and proto files use // instead of #. Empty files are exempt. A stale Copyright contributors to the vLLM project line is rewritten in place to the Omni copyright; the hook then exits non-zero so you restage the rewrite.

Forbidden imports

Under vllm_omni/, do not use:

• stdlib re → import regex as re
• stdlib base64 → import pybase64 (or import pybase64 as base64)
• pickle / cloudpickle (also banned in most tests)
• from huggingface_hub import snapshot_download / hf_hub_download / HfApi / similar → vllm.transformers_utils.repo_utils
• direct triton / tilelang → vllm.triton_utils / vllm.tilelang_utils

examples/, tests/, benchmarks/, apps/, docs/, tools/, scripts/, .buildkite/, and .github/ may keep stdlib re and base64 (_NON_LIBRARY_DIRS). Pickle is stricter: tests are not exempt unless the file is on the pickle allowlist.

torch.cuda call sites

Prefer current_omni_platform / OmniPlatform. Platform adapters under vllm_omni/platforms/ are allowed; other files must not add new torch.cuda.* helpers (device_count, synchronize, empty_cache, device(), manual_seed, and similar). import torch is fine.

shellcheck

The hook does not download a binary. Install shellcheck with a signed package manager, then re-run:

• Debian/Ubuntu/WSL: sudo apt-get install shellcheck
• Fedora: sudo dnf install ShellCheck
• macOS: brew install shellcheck
• Git Bash (MINGW): scoop install shellcheck so shellcheck.exe is on PATH. WSL is Linux: use apt-get, not a Windows .exe.

If no native binary is found, the wrapper prints those commands (and the upstream install page) and exits 1. AMD and other vendor scripts are not excluded.

mypy

mypy-3.10 runs on commit for changed files. [tool.mypy] uses Python 3.12, ignore_missing_imports = true, and follow_imports = "silent". Wrapper tools/pre_commit/mypy.py skips vllm_omni/model_executor/models/ and vllm_omni/diffusion/models/, and type-checks tests/ with --follow-imports skip. Extra versions:

pre-commit run --hook-stage manual mypy-3.12

Test CI marks

check-mark requires each collected test module under tests/ to have at least one CI level mark (core_model, advanced_model, full_model, local_model, or slow) and a hardware platform mark (cpu, cuda, …) or helper (hardware_test( / hardware_marks(). SKU marks (H100, L4, …) must come from those helpers so cards_{n} is attached; direct pytest.mark.H100 is rejected. GitHub Actions skips this hook; local commit does not. See the test writing guide.

TTS adapter ratchet

check-tts-adapter-migration counts self._tts_model_type comparisons in vllm_omni/entrypoints/openai/serving_speech.py. The count must stay at or below MAX_MODEL_TYPE_BRANCHES in tools/pre_commit/check_tts_adapter.py. New per-model behavior belongs in vllm_omni/entrypoints/openai/tts_adapters/. Removing branches must lower the budget in the same change; raising it is a reviewable policy edit.

Markdownlint and Buildkite

markdownlint-cli2 auto-fixes docs/, recipes/, and the root README / CONTRIBUTING (rules in .markdownlint.yaml). Skill files under .claude/ and .cursor/ are excluded.

check-buildkite validates .buildkite/*.yml against the official schema after the same expansion upload_pipeline.py uses. Omni-only keys such as mirror_hardwares are stripped or rendered first. A few files are skipped in SKIP_FILES inside tools/pre_commit/check_buildkite.py.

Extending allowlists and budgets

Prefer fixing the call site. Growing an allowlist or raising a budget is a policy change and needs review — do not edit these just to make the hook pass.

Gate	File	What to edit
pickle, re, base64, Hugging Face Hub, Triton/TileLang	tools/pre_commit/check_forbidden_imports.py	CHECK_IMPORTS[<rule>].allowed_files. Use allowed_dirs only when a whole tree should stay exempt.
torch.cuda	tools/pre_commit/check_torch_cuda.py	ALLOWED_FILES, or ALLOWED_PREFIXES for a platform adapter tree.
TTS _tts_model_type branches	tools/pre_commit/check_tts_adapter.py	MAX_MODEL_TYPE_BRANCHES (down only, unless the PR justifies a raise).
Buildkite skip list	tools/pre_commit/check_buildkite.py	SKIP_FILES for pipelines that cannot be expanded.

To skip one hook for a single commit (discouraged): SKIP=<hook-id> git commit. To bypass every hook: git commit --no-verify (also discouraged).

Documentation

MkDocs is a fast, simple and downright gorgeous static site generator that's geared towards building project documentation. Documentation source files are written in Markdown, and configured with a single YAML configuration file, mkdocs.yml.

Get started with:

uv pip install -e ".[docs]"

MkDocs comes with a built-in dev-server that lets you preview your documentation as you work on it. From the root of the repository, run:

mkdocs serve                           # with API ref (~10 minutes)
API_AUTONAV_EXCLUDE=vllm_omni mkdocs serve  # API ref off (~15 seconds)

Once you see Serving on http://127.0.0.1:8000/ in the logs, the live preview is ready! Open http://127.0.0.1:8000/ in your browser to see it.

For additional features and advanced configurations, refer to the:

• MkDocs documentation
• Material for MkDocs documentation (the MkDocs theme we use)

Testing

vLLM-Omni uses pytest to test the codebase. Please refer to the test instructions for detailed testing information.

!!! warning Currently, not all unit tests pass when run on CPU platforms. If you don't have access to a GPU platform to run unit tests locally, rely on the continuous integration system to run the tests for now.

Using repository skills with coding agents

vLLM-Omni maintains repository-scale skills for common coding, testing, performance, and review workflows. These skills capture repository-specific structure, validation requirements, and evidence standards that a general coding agent may not know.

If your coding agent discovers repository skills automatically, ask it to use the relevant skill by name. Otherwise, point it to the linked SKILL.md and ask it to read the file before changing code. Skills can be combined: use a domain skill for the implementation, vllm-omni-test for test and CI decisions, and precheck-pr before opening the pull request.

Task	Repository skill
Add or extend a diffusion model	add-diffusion-model
Add or extend a text-to-speech model	add-tts-model
Add, select, or debug quantization	quantization
Diagnose or optimize diffusion performance	diffusion-perf-opt
Upgrade an NPU model runner	vllm-omni-npu-model-runner-upgrade
Add a regression test, choose L1-L4 coverage, or wire Buildkite	vllm-omni-test
Self-check a branch before opening a pull request	precheck-pr
Perform a maintainer or reviewer review of an existing pull request or local branch	review-pr

Use the following workflow when collaborating with a coding agent:

1. Ground the task. Provide the issue, RFC, or design document that defines the expected behavior. Ask the agent to state its assumptions and identify the affected module or feature contracts before editing code.
2. Select the narrowest applicable skills. Start with the domain skill that owns the change. Add vllm-omni-test whenever production behavior or tests change. For a bug fix, ask for the smallest reproducer and a regression test tied to the original symptom.
3. Require executable evidence. Ask the agent to run the narrowest relevant checks and report the exact commands and results. It must identify tests it could not run because of unavailable hardware, model weights, credentials, or dependencies; an unrun check is not a pass.
4. Inspect the resulting diff. Confirm that the implementation stays within the issue or RFC, does not overwrite unrelated work, and includes the required tests, documentation, and benchmark or accuracy evidence.
5. Run the pre-submit workflow. Use precheck-pr, then run the applicable local tests and pre-commit hooks before opening the pull request.

For example:

Use add-diffusion-model and vllm-omni-test to implement the linked issue.
Read the relevant design documents first, keep the change within the issue,
and report every test command, result, and hardware validation gap.

Use vllm-omni-test to turn this bug reproducer into the smallest deterministic
regression test. Prefer L1 CPU coverage; if the failure requires real weights
or serving, explain the required L2/L3 environment and provide the exact command.

Repository skills guide the agent, but they do not replace contributor judgment, the accepted issue or RFC, required test evidence, or maintainer review. Review all generated changes before submitting them.

AI Usage Policy

AI tools are welcome in vLLM-Omni contributions. Contributors, including maintainers, remain responsible for everything they submit. These requirements apply to pull requests, issues, discussions, and review comments:

• Disclose AI assistance. Name the tools used and describe their role in the submission, including assistance with code, tests, documentation, or writing.
• Understand your changes. Review every generated change and be able to explain its behavior, design choices, and interaction with vLLM-Omni without relying on AI to answer for you.
• Validate before submitting. Run relevant checks and report actual results. For model, kernel, or performance changes, include the hardware, model, configuration, and commands needed to reproduce accuracy or benchmark evidence. Clearly identify checks you could not run; generated claims are not test results.
• Keep communication useful. Verify technical claims, search for existing reports, and edit AI-assisted text for accuracy and brevity. Submit only content you have personally reviewed, and take responsibility for responding to review feedback.
• Label generated media. Model-generated images, video, and audio are valid examples or test artifacts for this multimodal project. Identify them as generated output and provide the model, inputs, and reproduction settings. Do not present them as ground-truth references or independent evidence of correctness.

For example, a PR description could include:

AI assistance: Used Codex to draft the regression test and PR description.
I reviewed the changes and verified the test reproduces the reported failure.
Validation: <commands, results, hardware, and any checks not run>.

Maintainer review time is limited. Contributions that are unverified, misleading, or beyond the author's understanding may be closed. Repeated violations may lead to contribution restrictions. New contributors are welcome to ask for help and submit small, well-understood changes.

This policy is adapted from Ghostty's AI Usage Policy for vLLM-Omni's contribution and multimodal validation workflows. The coding-agent workflow provides practical guidance for applying it.

Issues

If you encounter a bug or have a feature request, please search existing issues first to see if it has already been reported. If not, please file a new issue, providing as much relevant information as possible.

!!! important Do not report suspected security vulnerabilities through a public issue, pull request, discussion, or Slack channel. Follow the security disclosure instructions to arrange a private report.

Pull Requests & Code Reviews

Thank you for your contribution to vLLM-Omni! Before submitting the pull request, please ensure the PR meets the following criteria. This helps vLLM-Omni maintain the code quality and improve the efficiency of the review process.

Pull Request Limit

To avoid agent spam, vLLM-Omni uses GitHub's pull request limit for contributors without write access. The current cap is 5 open PRs. If this blocks well-intentioned critical work, contact a committer to request bypass list access.

DCO and Signed-off-by

When contributing changes to this project, you must agree to the DCO. Commits must include a Signed-off-by: header which certifies agreement with the terms of the DCO.

Using -s with git commit will automatically add this header.

!!! tip You can enable automatic sign-off via your IDE:

- **PyCharm**: Click on the `Show Commit Options` icon to the right of the `Commit and Push...` button in the `Commit` window. It will bring up a `git` window where you can modify the `Author` and enable `Sign-off commit`.
- **VSCode**: Open the Settings editor and enable the `Git: Always Sign Off` (`git.alwaysSignOff`) field.

PR Title and Classification

Only specific types of PRs will be reviewed. The PR title is prefixed appropriately to indicate the type of change. Please use one of the following:

• [Bugfix] for bug fixes.
• [CI/Build] for build or continuous integration improvements.
• [Doc] for documentation fixes and improvements.
• [Model] for adding a new model or improving an existing model. Model name should appear in the title.
• [Frontend] For changes on the vLLM-Omni frontend (e.g., OpenAI API server, Omni/AsyncOmni, etc.)
• [Kernel] for changes affecting CUDA kernels or other compute kernels.
• [Core] for changes in the core vLLM-Omni logic (e.g., OmniProcessor, OmniARScheduler, etc.)
• [Hardware][Vendor] for hardware-specific changes. Vendor name should appear in the prefix, such as [Ascend] for Ascend NPUs.
• [Misc] for PRs that do not fit the above categories. Please use this sparingly.

!!! note If the PR spans more than one category, please include all relevant prefixes.

Pre-Check Before Submitting

Before submitting a PR, run the precheck-pr skill with the code agent for a self-review against project conventions:

The skill offers two modes:

• Quick (~3 min): catches showstoppers — PR title format, missing benchmark claims, rebase status
• Full (~10 min): thorough maintainer-grade review — dead code scan, copy-paste detection, import hygiene

The precheck covers five PR types: Bug Fix, Performance, New Model, Diffusion Model, and General. Each type has a tailored checklist that validates evidence quality (repro steps, A/B benchmarks, registry entries, etc.). See the precheck-pr skill for the full checklist.

Local Test

Please run the L1 and L2 test cases locally first and attach the results before contacting us to add the "ready" label. Please refer to the test instructions for running the test cases.

Automatic skip-ci (docs and pytest skip marks)

On pull requests and main pushes, the bootstrap step in .buildkite/cuda/pipeline.yml runs .buildkite/common/scripts/upload_pipeline.py against the git diff. When every changed file qualifies, L2 (ready) and L3 (merge-test) pipelines are not uploaded, so the default GPU CI jobs are skipped.

Change per file	Examples
Documentation	docs/**, any *.md, mkdocs.yml
Pytest skip marks only (under tests/)	Add/remove/edit @pytest.mark.skip, @pytest.mark.skipif, or pytest.skip(...); reformat pytestmark only to add a skip/skipif alongside existing pytest.mark.* entries
New skipped test module	New tests/**/*.py whose pytestmark includes unconditional pytest.mark.skip

These PR shapes all trigger skip-ci:

• Documentation only
• Qualifying skip-mark edits in tests/**/*.py only
• A mix of documentation and qualifying skip-mark test edits

Skip-ci does not apply when the diff also touches product code (for example vllm_omni/), or when test files change assertions, imports, fixtures, or other non-skip logic. If the diff cannot be resolved (non-PR branches outside main), CI runs as usual.

!!! note Skipping L2/L3 does not disable the Docker image build step. Nightly (L4) upload can still run when the PR has a nightly-test label or on scheduled main builds with NIGHTLY=1. Weekly (L5) upload can still run with weekly-test, WEEKLY=1, or NON_CRITICAL=1. Bootstrap child steps live in bootstrap-upload-steps.yml; the hook entry step runs upload_pipeline.py --upload <platform>/bootstrap-upload-steps.yml, which injects if by step key from skip-ci before upload. See CI Settings — Diff-aware CI and Test System Overview.

Code Quality

The PR needs to meet the following code quality standards:

• We adhere to Google Python style guide and Google C++ style guide.
• Pass all linter checks.
• The code needs to be well-documented to ensure future contributors can easily understand the code.
• Include sufficient tests to ensure the project stays correct and robust. This includes both unit tests and integration tests.
• Please add documentation to docs/ if the PR modifies the user-facing behaviors of vLLM-Omni. It helps vLLM-Omni users understand and utilize the new features or changes.

Notes for Large Changes

Please keep the changes as concise as possible. For major architectural changes (>500 LOC excluding kernel/data/config/test), we would expect a GitHub issue (RFC) discussing the technical design and justification. Otherwise, we will tag it with rfc-required and might not go through the PR.

What to Expect for the Reviews

The goal of the vLLM-Omni team is to be a transparent reviewing machine. We would like to make the review process transparent and efficient and make sure no contributor feels confused or frustrated. However, the vLLM-Omni team is small, so we need to prioritize some PRs over others. Here is what you can expect from the review process:

• After the PR is submitted, the PR will be assigned to a reviewer. Every reviewer will pick up the PRs based on their expertise and availability.
• After the PR is assigned, the reviewer will provide status updates every 2-3 days. If the PR is not reviewed within 7 days, please feel free to ping the reviewer or the vLLM-Omni team.
• After the review, the reviewer will put an action-required label on the PR if there are changes required. The contributor should address the comments and ping the reviewer to re-review the PR.
• Please respond to all comments within a reasonable time frame. If a comment isn't clear or you disagree with a suggestion, feel free to ask for clarification or discuss the suggestion.

Additional Resources

• Design Documents - Architecture and design documentation

Thank You

Finally, thank you for taking the time to read these guidelines and for your interest in contributing to vLLM-Omni. All of your contributions help make vLLM-Omni a great tool and community for everyone!