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Tonl A Llm Friendly Serialization Format Github

Overview Toml Serialization
Overview Toml Serialization

Overview Toml Serialization Tonl is a production ready data platform that combines compact serialization with powerful query, modification, indexing, and streaming capabilities. designed for llm token efficiency while providing a rich api for data access and manipulation. A text first, llm friendly serialization format. up to 50% smaller tokens than json.

Github Nusnlp Llm Tls Repo For Acl2024 Paper From Moments To
Github Nusnlp Llm Tls Repo For Acl2024 Paper From Moments To

Github Nusnlp Llm Tls Repo For Acl2024 Paper From Moments To Tonl is a text first, llm friendly serialization format that combines the compactness of binary formats with human readability. designed to reduce token costs in llm prompts while maintaining clear structure and optional schema hints. Tonl is a llm friendly serialization format that can cut your data size by up to 50–60% compared to json, which also means dramatically lower llm token costs. Overview tonl is a text based serialization format designed for: token efficiency in llm contexts human readability and maintainability schema support with optional type hints recursive structure support for nested data bidirectional compatibility with json. Check out the full getting started guide on github.

Github Underlogic Toml Serialization Unity Package Library For
Github Underlogic Toml Serialization Unity Package Library For

Github Underlogic Toml Serialization Unity Package Library For Overview tonl is a text based serialization format designed for: token efficiency in llm contexts human readability and maintainability schema support with optional type hints recursive structure support for nested data bidirectional compatibility with json. Check out the full getting started guide on github. Token optimized notation language a compact serialization format designed for llm contexts, human readability, and perfect json compatibility. pytonl is a pure python implementation of the tonl format. The missing piece is serialization for llm consumption rather than gui rendering. a committed skeleton would provide persistent structural knowledge across agent sessions, eliminating the current pattern where each session rebuilds understanding from scratch. Links source: github tonl dev tonl json api: repos.ecosyste.ms purl: pkg:github tonl dev tonl repository details étoiles823 forks31 issues ouvertes1 licencemit langagetypescript taille3,42 mo date de créationil y a 5 mois date de mise à jouril y a 30 jours enregistréil y a 30 jours dernière synchronisationil y a 30 jours. Toon offers a leaner alternative to json for llms, slashing token usage by 30 60%. boost efficiency and cut costs with this human readable, compact format.

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