Constrain LLM outputs with regex and grammars for valid JSON, XML, and code.
npx skills add https://github.com/LynxLabVN/office-agent --skill guidance-lynxlabvn
Please help me install this Agent Skill. Skill: guidance Source: https://github.com/LynxLabVN/office-agent/tree/main/agent-core/optional-skills/mlops/guidance Command: npx skills add https://github.com/LynxLabVN/office-agent --skill guidance-lynxlabvn
This Skill allows you to control and enforce the syntax, grammar, and format of LLM outputs, ensuring structured and accurate generation of JSON, XML, code, and more.
Generate a structured JSON object with a person's name, age, and email by using the following command: generate_person "John Doe" 30 "[email protected]".
High-intent search queries and answers about installing and using this skill.
You can enforce structured JSON output from an LLM by applying regex constraints and context-free grammars. This ensures generated text strictly follows valid formats, preventing syntax errors during data generation.
Yes, you can use regex patterns to control LLM text generation and enforce specific formats. This constrains the output to match your defined regular expressions, ensuring accurate text formatting for structured data.
The best way to generate valid XML is by using grammar-based generation to enforce complex structures. This applies context-free grammars to the LLM, guaranteeing syntactically correct XML outputs for APIs.
Context-free grammars work for constraining code generation by defining strict structural rules that the LLM must follow. This enforces complex structures and ensures the generated code snippets are syntactically valid.
Broken token boundaries in structured data often occur due to tokenization misalignment during generation. Token healing automatically corrects these boundaries, ensuring natural text flow and valid structured output.
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