# Contributing to SGLang Diffusion This guide outlines the requirements for contributing to the SGLang Diffusion module (`sglang.multimodal_gen`). ## On AI-Assisted ("Vibe Coding") PRs Vibe-coded PRs are welcome — we judge code quality, not how it was produced. The bar is the same for all PRs: - **No over-commenting.** If the name says it all, skip the docstring. - **No over-catching.** Don't guard against errors that virtually never happen in practice. - **Test before submitting.** AI-generated code can be subtly wrong — verify correctness end-to-end. ## Commit Message Convention We follow a structured commit message format to maintain a clean history. **Format:** ```text [diffusion] : ``` **Examples:** - `[diffusion] cli: add --perf-dump-path argument` - `[diffusion] scheduler: fix deadlock in batch processing` - `[diffusion] model: support Stable Diffusion 3.5` **Rules:** - **Prefix**: Always start with `[diffusion]`. - **Scope** (Optional): `cli`, `scheduler`, `model`, `pipeline`, `docs`, etc. - **Subject**: Imperative mood, short and clear (e.g., "add feature" not "added feature"). ## Performance Reporting For PRs that impact **latency**, **throughput**, or **memory usage**, you **should** provide a performance comparison report. ### How to Generate a Report 1. **Baseline**: run the benchmark (for a single generation task) ```bash $ sglang generate --model-path --prompt "A benchmark prompt" --perf-dump-path baseline.json ``` 2. **New**: run the same benchmark, without modifying any server_args or sampling_params ```bash $ sglang generate --model-path --prompt "A benchmark prompt" --perf-dump-path new.json ``` 3. **Compare**: run the compare script, which will print a Markdown table to the console ```bash $ python python/sglang/multimodal_gen/benchmarks/compare_perf.py baseline.json new.json [new2.json ...] ### Performance Comparison Report ... ``` 4. **Paste**: paste the table into the PR description ## CI-Based Change Protection Consider adding tests to the `pr-test` or `nightly-test` suites to safeguard your changes, especially for PRs that: - support a new model - add a testcase for this new model to `testcase_configs.py` - support or fix important features - significantly improve performance Please run the according testcase, then update/add the baseline to `perf_baselines.json` by following the instruction in console if applicable. See [test](https://github.com/sgl-project/sglang/tree/main/python/sglang/multimodal_gen/test) for examples