Outlines Constrained Generation

Force LLMs to produce valid JSON, regex matches, or grammar-constrained outputs with Outlines. Works with open-weight models via Transformers, vLLM, llama.cpp, and remote APIs that support structured outputs.

This skill helps you use Outlines for guaranteed-valid LLM output. It configures Outlines with Pydantic models for JSON schemas, regex patterns for format constraints, and CFGs for complex grammars. Covers integration with Transformers, vLLM, llama.cpp, and OpenAI's structured outputs API, plus performance patterns for batched generation and avoiding the recompilation tax on hot paths.

When to use

Use when you need 100% schema-valid outputs from local LLMs, are building extraction pipelines where parse failures are unacceptable, or want regex-constrained outputs (phone numbers, IDs, codes) without retry loops.

Examples

Pydantic JSON extraction

Force a local model to output schema-valid JSON

Use Outlines with a local Llama model to extract product attributes into a Pydantic schema, with batched generation for 1000 product descriptions

Grammar-constrained DSL

Generate outputs that match a custom grammar

Write an Outlines generator that produces only valid SQL SELECT statements against a fixed schema, using a context-free grammar