sgl-project/sglang
GitHubSGLang is a high-performance serving framework for large language models and multimodal models.
- attention
- blackwell
- cuda
- deepseek
- diffusion
- glm
- gpt-oss
- inference
- llama
- llm
- minimax
- moe
- qwen
- qwen-image
- reinforcement-learning
- transformer
- vlm
- wan
- Stars:
- 38.4k
- Language:
- Python
- Default branch:
- main
- Last scored:
At a glance
- Rank
- #350 of 401
- #51 of 56 Python repos
- Checks passed
- 7 of 17
- Full list below
- Best set up for
- Devin
- Score 57.4
- Needs most work for
- Cursor
- Biggest fix: Cursor rules (.cursor/rules) (+11.5 pts)
What it has
What it's missing
What to fix first
Showing fixes for Claude Code
- 1AGENTS.md / CLAUDE.mdAdd an AGENTS.md covering project goals, layout, setup commands, and conventions. Aim for 800+ chars of real guidance (not boilerplate).+13.2 pts
- 2Dependency manifestCommit a proper manifest (package.json, pyproject.toml, Cargo.toml, go.mod, etc.) plus a lockfile.+9.2 pts
- 3Linter / formatter configConfigure a linter/formatter (ESLint+Prettier, Biome, Ruff, rustfmt+clippy, golangci-lint) and commit the config.+7.9 pts
Score for each AI agent
Each agent weighs the checks by its own docs. Under each score are its top three. How each agent is scored →
Does sgl-project/sglang have agent instructions?
An AGENTS.md (or CLAUDE.md) at the root tells AI coding agents how to build, test and work in the repo. A few agents also read a file of their own.
- AGENTS.md / CLAUDE.md
- None at the root (no AGENTS.md, CLAUDE.md, AGENT.md, .claude/CLAUDE.md or .claude/AGENTS.md)
- Agent-specific files
.agents/skills(new tab) (29 skills)No GEMINI.md, .cursor/rules, .openhands/setup.sh or .aider.conf.yml- Repos that have one
- 29 of 56 Python repos · 221 of 401 repos on the leaderboard · See examples →
Get a starter AGENTS.md
From the files the checks found. Fill in the commands, then commit it at the root.
# AGENTS.md
Guidance for AI coding agents working in sgl-project/sglang. SGLang is a high-performance serving framework for large language models and multimodal models. Written mainly in Python.
## Where things are
- Tests live in `test`.
- CI is defined in `.github/workflows`; read it for the exact install, lint and test steps.
- Commit hooks are set up in `.pre-commit-config.yaml`; don't skip them.
- A reproducible environment is defined in `.devcontainer/devcontainer.json`.
- Follow the conventions in `docs/CONTRIBUTING.md`.
## Commands
<!-- Fill in the exact commands CI runs. -->
- Install: TODO
- Test: TODO
- Lint: TODO
All 17 checks · 7 passed
How sgl-project/sglang compares
- vs leaderboard average
- 15.3 pts below
- Average 66.8
- vs Python average
- 19.5 pts below
- Average 71.0
- Stars among Python repos
- #36 of 56
Missing here, and how many repos have it
- Dependency manifest · passed by 92% of leaderboard repos, 89% of Python repos
- Type configuration · passed by 68% of leaderboard repos, 57% of Python repos
- Linter / formatter config · passed by 65% of leaderboard repos, 89% of Python repos
Passes checks most repos miss
- Skills (.agents/skills) · only 17% of repos pass it
- Pre-commit / git hooks · only 29% of repos pass it
One fix for the most agents: Linter / formatter config would raise the score for all 9 agents, by up to 14.1 points.
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Same language and host as this repo, closest in overall score.
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Same topics, any language
Repos tagged with the same GitHub topics, most shared first.
- Python · blackwell, deepseek, gpt oss, inference, llama, LLM, moe, qwen, transformer
- ollama/ollama76.7Go · deepseek, glm, gpt oss, llama, LLM, minimax, qwen
- Python · deepseek, glm, LLM, qwen, transformer, vlm
- Python · deepseek, LLM, llama, moe, qwen
- Python · diffusion, qwen image
- C++ · inference, transformer
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