python-toon and toonify
These are competitors offering alternative serialization formats for the same purpose—both claim to reduce LLM token costs by 30-60% through compact data representation, so users would typically choose one approach rather than use them together.
About python-toon
xaviviro/python-toon
🐍 TOON for Python (Token-Oriented Object Notation) Encoder/Decoder - Reduce LLM token costs by 30-60% with structured data.
This tool helps anyone working with Large Language Models (LLMs) significantly reduce their token usage and associated costs when sending structured data. It takes standard data formats like JSON and converts them into a compact "Token-Oriented Object Notation" (TOON), which is specifically optimized for LLM processing. This means you feed in your data, get back a much smaller representation, and then send that to your LLM.
About toonify
ScrapeGraphAI/toonify
Toonify: Compact data format reducing LLM token usage by 30-60%
When working with Large Language Models (LLMs), this tool helps you send structured information more efficiently. It takes your data (like customer lists, product details, or survey results) and converts it into a super-compact, human-readable format. The LLM then processes this condensed data, saving you money on token usage and allowing more information in a single request. This is for anyone who uses LLMs to process or generate structured data, like data analysts, content creators, or business intelligence professionals.
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