Sglang
Skill ActiveFast structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding, agentic workflows with tool calls, or when you need 5× faster inference than vLLM with prefix sharing. Powers 300,000+ GPUs at xAI, AMD, NVIDIA, and LinkedIn.
To provide a significantly faster and more efficient way to serve LLMs, especially for applications involving repeated prefixes, structured outputs, and agentic tool calls, surpassing the performance of traditional systems like vLLM for these use cases.
Features
- Fast LLM inference serving
- Automatic prefix caching (RadixAttention)
- Structured generation (JSON, regex, grammar)
- Agentic workflows with function calling
- OpenAI-compatible API
- Supports multiple model types and hardware
Use Cases
- Building AI agents that make repeated tool calls
- Generating JSON or regex outputs from LLMs
- Serving LLMs with long system prompts or few-shot examples
- Accelerating multi-turn conversations with LLMs
Non-Goals
- Simple text generation without structure or repeated prefixes
- Replacing vLLM when prefix caching is not needed
- Replacing TensorRT-LLM for single-request low-latency NVIDIA-only deployments
Trust
- warning:Issues AttentionThe repository shows 17 open issues and 4 closed issues in the last 90 days, with a low closure rate, suggesting maintainer responsiveness could be improved.
Installation
npx skills add davila7/claude-code-templatesRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
Trust Signals
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SGLang
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