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Chris-Chai-Minjae
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outlines

Generates JSON, XML, or code from prompts using FSM-based constraints and Pydantic models.

Updated Apr 23, 2026
Search Tags:#pydantic#json#fsm#backends#outlines#local-models#structured-generation
One-click install
npx skills add https://github.com/Chris-Chai-Minjae/hermes-agent-r1-bridge --skill outlines-chris-chai-minjae
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: outlines
Source: https://github.com/Chris-Chai-Minjae/hermes-agent-r1-bridge/tree/main/skills/mlops/inference/outlines
Command: npx skills add https://github.com/Chris-Chai-Minjae/hermes-agent-r1-bridge --skill outlines-chris-chai-minjae

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables reliable generation of structured outputs (JSON/XML/code) with strict typing via Pydantic, ensuring outputs adhere to schemas while using a unified, fast generation approach.

Core Features & Use Cases

  • Grammar-based generation with Finite State Machines to guarantee validity.
  • Native Pydantic integration for type-safe outputs and easy schema translation.
  • Local-model backends support (Transformers, llama.cpp, vLLM) for fast, offline inference; cross-backend interoperability.

Quick Start

Use outlines to generate structured, type-safe outputs from prompts against local models.

Frequently Asked Questions about outlines

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate valid JSON from a local model using Pydantic schemas?▼

To generate valid JSON from local models, apply FSM-based constraints and Pydantic schemas to enforce type-safe structured outputs. This guarantees grammar-based generation across Transformers, llama.cpp, and vLLM backends.

What is FSM-based structured generation for language models?▼

FSM-based structured generation uses Finite State Machines to constrain AI outputs to specific grammars and schemas. This enforces valid JSON, XML, or code generation by mapping allowed tokens to defined state transitions.

Can I use outlines with vLLM and llama.cpp backends?▼

Yes, structured generation supports vLLM and llama.cpp backends for local-model inference. It provides cross-backend interoperability through a unified API, ensuring fast and offline type-safe outputs across supported environments.

How do I enforce type-safe schemas for AI generated outputs?▼

Enforce type-safe schemas by integrating Pydantic models directly with the generation API. This natively translates Python type definitions into grammar constraints, guaranteeing outputs strictly adhere to specified schemas.

Does structured generation work offline with Transformers?▼

Yes, structured generation works offline with Transformers backends for local-model inference. It applies grammar-based constraints directly during generation, ensuring fast and safe typed outputs without requiring external API calls.

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