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Awesome GitHub RepositoriesGrammar-Constrained Token Samplers

Tools that restrict token generation based on formal language rules.

Distinct from Tokenizers: Focuses on grammar-based sampling tools, distinct from general tokenizers.

Explore 3 awesome GitHub repositories matching artificial intelligence & ml · Grammar-Constrained Token Samplers. Refine with filters or upvote what's useful.

Awesome Grammar-Constrained Token Samplers GitHub Repositories

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  • guidance-ai/guidanceguidance-ai 的头像

    guidance-ai/guidance

    21,502在 GitHub 上查看↗

    Guidance is a generative AI orchestration framework designed to manage complex interactions with language models by embedding programmatic control directly into the prompt generation process. It functions as a prompt programming environment that allows developers to interleave raw text with executable logic, enabling the construction of sophisticated, multi-step agentic workflows. The framework distinguishes itself through grammar-constrained token sampling and stateful stream interception, which restrict the model's output distribution based on formal language rules. By enforcing these const

    Restricts language model token generation based on formal language rules to ensure strict adherence to output schemas.

    Jupyter Notebook
    在 GitHub 上查看↗21,502
  • outlines-dev/outlinesoutlines-dev 的头像

    outlines-dev/outlines

    13,965在 GitHub 上查看↗

    Outlines 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

    Modifies the token probability distribution to ensure generated text adheres to specific regular expressions or grammars.

    Python
    在 GitHub 上查看↗13,965
  • dottxt-ai/outlinesdottxt-ai 的头像

    dottxt-ai/outlines

    13,446在 GitHub 上查看↗

    Outlines 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

    Restricts the model's next-token probability distribution by zeroing out tokens that violate defined grammar or schema constraints.

    Pythoncfggenerative-aijson
    在 GitHub 上查看↗13,446
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