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LLM Pleasant: The structure is built to be easily parsed by AI types when minimizing the token depend, preserving expenditures and context window House.
If you must convert this back again to whole JSON afterwards, You may use the --extend-paths safe flag throughout decoding to reconstruct the deep object structure completely.
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In this workflow, you fetch the info, extract only the Lively users, convert it into a pipe-delimited TOON structure, and acquire a stats report on what number of tokens you merely saved.
Pero por ahora, TOON es la mejor herramienta disponible para optimizar datos estructurados en aplicaciones de IA.
When you feed it a .json file, it assumes you would like to encode it to TOON. In case you offer a .toon file, it switches to decoding mode to give you back JSON.
A diferencia de JSON, que fue creado para intercambio de datos entre aplicaciones web, TOON está optimizado para reducir el consumo de tokens, lo TOON formater que se traduce en ahorros significativos tanto en costes de API como en capacidad de contexto.
Within this guide, We're going to have a look JSON2TOON at how you can leverage the TOON Command Line Interface to combine info optimization straight into your shell workflows.
This Instrument is perfect for builders, researchers, and anyone working with LLMs who really should enhance their API use and deal with costs properly though preserving details privacy. It offers a useful Option towards the issues posed by JSON's verbosity and rigidity in AI contexts.
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The TOON CLI is designed to be wise about what you are attempting to carry out. You seldom need to explicitly explain to it to encode or decode; it appears to be at your file extensions to determine.
The actual power of your TOON CLI will come once you chain it with other tools like curl and jq. You may fetch info from an API, filter it all the way down to the essentials, and convert it to TOON in one line—able to be pasted right into a prompt or sent to an inference endpoint.