GitHub collection gathers hundreds of Jev decision tools
A GitHub collection brings together projects built on Jev, covering agent control, search and bulk analysis, and safety checks; in a demo it analyzed 724 ads in 40 seconds for $0.09.
SOMEONE COLLECTED HUNDREDS OF JEV TOOLS THAT MAKE AI DECISIONS DIRT CHEAP A GitHub collection brings together projects built around a new kind of model that picks from predefined options instead of generating text According to the developers, it can be up to 194× faster and 445× cheaper than conventional LLMs In the video demo, it analyzed 724 ads by hook, format, and CTA in just 40 seconds Total cost: $0.09 The collection covers tools, libraries, and projects for: → Agent control - choosing the cheapest suitable model, deciding which button to press, and picking the next action → Search and bulk analysis, my favorite - flagging urgent emails, separating useful information from noise, and classifying large streams of data → Checks and safeguards - cleaning up agent context, reviewing another model’s answer before it goes out, and detecting prompt injections Reported response times range from 70 to 500 ms, with input priced at 4.2 cents per million tokens The team says output will stay free forever
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