guidance

You can enforce valid JSON generation by applying regex constraints and grammars to control the LLM output syntax. This approach guarantees the model generates structured data that strictly adheres to your required JSON format.

The best way to constrain LLM output to specific formats like dates and emails is by enforcing structured formats through grammars. This restricts the language model to generate only valid syntax matching your defined patterns.

Yes, you need both the transformers and guidance libraries to control LLM output with grammars. These dependencies provide the required environment for executing structured formats and multi-step workflows with Pythonic control flow.

Yes, you can build multi-step workflows for code generation using regex constraints and Pythonic control flow. This allows you to guarantee valid code generation while orchestrating complex, structured generation sequences across multiple steps.

LLMs generate invalid XML due to unconstrained token prediction; you can prevent this by enforcing structured formats with grammars. This ensures valid XML generation by strictly controlling the output syntax during the generation process.