lmql-constraints

What problem does it solve?

This Skill provides a formal, programmable approach to building constrained, reliable prompts for LLMs, reducing drift, ambiguity, and unpredictable outputs in production prompts.

Core Features & Use Cases

• Constrained generation: Define output formats and constraints (length, regex, membership) to guarantee structure.
• Type-safety & composability: Build queries that preserve types and allow safe composition of multiple constrained steps.
• Real-world use case: Create chat assistants and data extraction pipelines that always produce structured results (e.g., JSON) and predictable behavior.

Quick Start

Install lmql via pip and run a minimal constrained query example. Define a query using the lmql syntax to produce a JSON-like dictionary with fields such as name and age, constrained to valid types, then execute it to verify deterministic output.