3 repository-uri
Awesome GitHub RepositoriesGenerative Schema Enforcement Frameworks
Systems that apply programmatic constraints during token sampling to ensure machine-readable output.
Distinct from Programmatic Data Model Generation: Focuses on sampling-time constraints for generative models, distinct from static data model generation.
Explore 3 awesome GitHub repositories matching data & databases · Generative Schema Enforcement Frameworks. Refine with filters or upvote what's useful.
Awesome Generative Schema Enforcement Frameworks GitHub Repositories
Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
- outlines-dev/outlines
outlines-dev/outlines
13,965Vezi pe GitHubOutlines is a guided text generation framework and structured output engine for large language models. It enforces precise structural constraints on model output during the sampling process to ensure the generation of valid data. The framework ensures that model outputs strictly adhere to predefined data models, including JSON schemas, regular expressions, and formal grammars. This enables the conversion of natural language inputs into structured arguments for function calling and the generation of valid JSON for downstream processing. The system manages model orchestration through prompt te
Provides a framework that applies programmatic constraints during token sampling to ensure strictly valid, machine-readable output.
Python - normal-computing/outlines
normal-computing/outlines
13,965Vezi pe GitHubOutlines is a guided generation framework designed to enforce structural constraints on large language model output in real time. It serves as a structured output generator that ensures model responses adhere to predefined JSON schemas, regular expressions, or fixed sets of choices to produce predictable and parsable results. The project provides an interface for tool calling by extracting structured function parameters from natural language prompts for programmatic execution. It also includes a prompt templating engine that decouples prompt logic from application code through reusable templa
Provides a framework for applying programmatic constraints during token sampling to ensure predictable and parsable output.
Python - dottxt-ai/outlines
dottxt-ai/outlines
13,446Vezi pe GitHubOutlines is a library designed to ensure machine-readable output from generative models by applying programmatic constraints during the token sampling process. It functions as a toolkit for forcing large language models to generate text that strictly adheres to JSON schemas, regular expressions, and formal grammars, enabling the integration of model responses into existing software systems. The library distinguishes itself by integrating formal language rules directly into the sampling loop. It achieves this by converting regular expressions into deterministic finite automata and utilizing lo
Ensures machine-readable output from generative models by applying programmatic constraints during the token sampling process.
Pythoncfggenerative-aijson
