Constrain LLM outputs with regex and grammars for valid JSON structures.
npx skills add https://github.com/CUexter/hermes-agent --skill guidance-cuexter
Please help me install this Agent Skill. Skill: guidance Source: https://github.com/CUexter/hermes-agent/tree/main/skills/mlops/inference/guidance Command: npx skills add https://github.com/CUexter/hermes-agent --skill guidance-cuexter
Guidance enables precise control over LLM outputs using regex and grammars, ensuring valid JSON/XML/code and enforcing consistent, structured formats across prompts and pipelines.
Invoke a constrained-generation workflow by defining a regex constraint and generating a JSON object with Guidance.
High-intent search queries and answers about installing and using this skill.
Constrained generation uses regex and grammars to guarantee valid structured outputs like JSON from LLMs. This enforces consistent formats across prompts and pipelines, preventing invalid syntax and formatting errors in production.
Token healing fixes token boundary issues in constrained generation, ensuring regex and grammar constraints apply cleanly. It supports local-model deployments by maintaining deterministic results and guaranteeing valid structured formats across pipelines.
Yes, this approach works with transformers for grammar-based data extraction. You can build multi-step workflows and local-model pipelines using Pythonic tooling to enforce regex and grammar constraints for reliable structured outputs.
The best way to build a constrained generation pipeline for XML extraction is using Pythonic guidance functions with grammar-based generation. This guarantees valid structured formats and enables reusable patterns for document extraction workflows.
LLMs output invalid JSON despite prompt schemas because unconstrained generation lacks enforcement. Applying grammar-based constraints and token healing forces the model to generate only valid structured formats, eliminating syntax errors.
Use constrained generation instead of standard prompt engineering when you need guaranteed valid JSON, XML, or code formats. Grammar-based constraints and regex enforcement ensure deterministic results for production-grade pipelines and data validation.
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