Constrain LLM outputs with regex and grammars for valid JSON, XML, and code.
npx skills add https://github.com/rnben/hermes-skills --skill guidance-rnben
Please help me install this Agent Skill. Skill: guidance Source: https://github.com/rnben/hermes-skills/tree/main/plugins/mlops-skills/skills/guidance Command: npx skills add https://github.com/rnben/hermes-skills --skill guidance-rnben
Guidance provides robust mechanisms to control and constrain LLM outputs, ensuring structured and valid results across formats like JSON, XML, and code, reducing hallucinations and post-processing.
Install the Guidance package and begin creating constrained generations with regex and grammars.
High-intent search queries and answers about installing and using this skill.
You can constrain LLM output using regex and grammars to enforce syntactic validity, guaranteeing valid JSON and XML generation. This approach applies constrained generation across structured data tasks to reduce hallucinations and eliminate post-processing.
Yes, constrained generation supports local and hosted backends including OpenAI, Anthropic, and transformers-based models. You can apply grammar-based generation and JSON/XML validation across both local and hosted model environments in multi-step tasks.
Token healing is a constrained generation mechanism that fixes structured output syntax errors during LLM generation. It works alongside regex and grammar enforcement to maintain syntactic validity and prevent malformed JSON, XML, or code generation.
You can create reusable guidance functions using context-manager-like workflows and Pythonic patterns for multi-step structured data tasks. These functions apply regex and grammar constraints across JSON and XML validation steps in both local and hosted model environments.
LLMs produce invalid JSON when generation is unconstrained, but you can enforce syntax during generation using regex and grammars. This constrained generation approach guarantees valid JSON, XML, and code output by applying syntax enforcement directly in the model backend.
Regex constrained generation requires precise pattern formulation and may not cover all complex grammar rules for structured output. Grammar-based generation and token healing provide broader syntax enforcement for JSON, XML, and code validation across OpenAI, Anthropic, and local transformers backends.
ricableGenerate LLM outputs constrained by regex and grammar across multiple frameworks and workflows.
kaminocorpConstrain LLM outputs with regex and grammar-based generation.
DaddyElonMusk69Constrain LLM output to match regex patterns or grammars.
eddieluengEnforce regex and grammar constraints for valid JSON, XML, and code outputs.
