guidance

You can enforce valid structured JSON output from LLMs by applying regex patterns and grammars to constrain generation, ensuring the syntax matches your exact format requirements.

Building multi-step workflows for structured data generation uses Pythonic control flow to guide LLMs, transforming free-form input text into constrained, valid structured outputs like a resume JSON.

Yes, you can use custom regex and grammars to control LLM syntax generation, enforcing specific format constraints and structured output rules directly during the language model generation phase.

Yes, constrained generation using grammars and regex works with llama_cpp and transformers, requiring these dependencies to enforce structured formats and custom logic during LLM inference.

You need grammars for automated code generation and data transformation to guarantee syntax validity, preventing malformed structures and ensuring the LLM output adheres to strict structural constraints.