vLLM · Structured output and tool calling

Uses the Outlines library to constrain model output to a JSON schema, Pydantic model, regex or fixed set of choices when running local models.

Orchestra-Research/AI-Research-SKILLs

Deploy LLM models on OCI using AI Quick Actions (AQUA) - single model, multi-model, stacked (LoRA), with GPU shape selection, vLLM configuration, streaming, and tool calling.

oracle/accelerated-data-science

Covers serving LLMs with SGLang, whose RadixAttention reuses cached prefixes, and constraining output to JSON, regex or grammar for agent and tool-calling workloads.

Orchestra-Research/AI-Research-SKILLs

Deploy and serve LLMs with vLLM behind an OpenAI-compatible endpoint, with tool calling enabled for agent workloads.

Prism-Shadow/penguin-harness

LLM and multimodal serving systems. An agent skill from uw-syfi/vibesys.

uw-syfi/vibesys

Use this vLLM sub-skill for structured outputs, JSON/regex/grammar constraints, tool calling, reasoning parsers, chat-template/tool-parser routing, streaming tool-call deltas, and parser/backend…

VectorSpaceLab/AREX-Skill