Generate structured JSON, Pydantic, and regex outputs from local models.
npx skills add https://github.com/x-TheFox/Corvus --skill outlines-x-thefox
Please help me install this Agent Skill. Skill: outlines Source: https://github.com/x-TheFox/Corvus/tree/main/skills/mlops/inference/outlines Command: npx skills add https://github.com/x-TheFox/Corvus --skill outlines-x-thefox
Outlines provides a disciplined approach to generating structured outputs (JSON, Pydantic, and regular-expression constrained text) from LLM prompts, ensuring outputs conform to schemas and are easier to validate.
Load a local model with outlines and generate a typed JSON output from a prompt describing the data you need.
High-intent search queries and answers about installing and using this skill.
Enforcing FSM grammar constraints during token sampling guarantees structured JSON generation that strictly conforms to Pydantic schemas using local models. Outlines integrates Pydantic for automatic schema translation, delivering type-safe results with zero runtime overhead.
Grammar-based generation enforces constrained token sampling via finite state machine (FSM) or context-free grammar (CFG) rules. This mechanism guarantees valid LLM outputs by ensuring generated text always conforms to specified JSON, Pydantic, or regex schemas.
Regex constraints are supported for text classification tasks across multiple local model backends including vLLM and llama.cpp. Outlines applies regex constraints during generation to ensure outputs match specific patterns required by classification workflows.
Structured generation with local models operates with zero overhead by applying FSM constraints directly during token sampling. Outlines enforces schema conformity during the generation process itself, eliminating the need for post-hoc validation or retry loops.
Extracting multiple entities into typed JSON is best handled by combining Pydantic schemas with FSM grammar constraints during local model generation. Outlines supports multi-entity extraction workflows by guaranteeing outputs conform to strict schemas for data extraction and form processing.
MesferAliConstrain LLM outputs to JSON, XML, or regex using Pydantic models.
ruiyangruiyiExtracts structured JSON from LLM outputs using Pydantic schema validation with automatic retries and optional streaming, supporting OpenAI and Anthropic via Instructor.
afel6Constrain token sampling with grammars to generate valid JSON, XML, and code.
ovachieverGenerate schema-valid JSON outputs using FSM-constrained token sampling.
