Jev Driving Lab / typesafe-playground

Demo03 built with Fable, showing the 3D road, four camera feeds, sensor readings, speed-sign memory and Jev decision panel — Image from github.com

kavehmz/typesafe-playground on GitHub

Stars: 13
Forks: 4
Language: JavaScript
Last push: 22 Sep 2026

Read from GitHub on 24 Sep 2026. Counts change daily.

How it uses Jev

  response = await fetchImpl('https://api.typesafe.ai/v1/systemone', {
    method: 'POST', redirect: 'error',
    headers: { Authorization: `Bearer ${apiKey}`, 'Content-Type': 'application/json' },
    body: JSON.stringify(request), signal: AbortSignal.timeout(20000)
  });
} catch (error) {
  if (error.name === 'TimeoutError' || error.name === 'AbortError') throw new PublicError(504, 'TypeSafe did not respond within 20 seconds. Try again.');
  throw new PublicError(502, 'Could not reach TypeSafe. Check the container’s internet connection.');

View in demo01/server.mjs

Open on GitHub

PrimitivesChoice Score Noul

Use casesSupport inbox triage Real-time control

Jev Ultrafast (Browser Use)

Browser Use's fast browser agent where Jev picks the operation and the DOM element in a single request; a small LLM is only invoked to write text when typing is required. Demoed on a Google Flights search.

browser-useOpen

19k starsFlight search 7.1 s

ProjectTyped tool dispatch+2

Introducing Clef: our open-source decision models, and new RL fine-tuning platform

Cloudflare's launch post for Clef and Clef-flash, two decision models on Workers AI that accept the Jev request format and open weights under Apache 2.0. It covers the architecture, Cloudflare's own benchmark tables against Jev, Kev and Laya, and a new reinforcement learning service.

Michelle Chen (@michellechen)140k viewsOpen

ArticleSupport inbox triage

Laya-MLX

An independent MLX port of Laya for Apple Silicon, 13.4ms median for a short English decision and 7.4ms on the multilingual checkpoint, with a Snake demo that plays at up to 75 moves per second under 1GB of memory.

mizorewwwOpen

6.1k starsShort decision 13.4 ms P50Snake demo 75.4 moves/s

ToolReal-time control

SetFit: efficient few-shot text classification

Fine-tunes Sentence Transformer embeddings plus a lightweight head for high-accuracy classification from a handful of labeled examples, with no prompting. The standard cheap alternative to an LLM classification call when the label set is fixed. Star count is GitHub's rounded display figure.

huggingface2.8k starsOpen

AlternativeSupport inbox triage+2

GLiNER2.5-Decide

Open-weights 340M-parameter decision model from Fastino Labs. It jointly decodes typed classification questions and, per Fastino's own internal benchmark, leads 9 of 17 datasets against JevK5, SemIf and Laya.

Fastino Labs (@fastinoAI)Open

2.2k starsCPU latency 167 msGPU latency 38-47 ms

ToolIntent and model routing+1

ModernBERT

Modernized BERT encoder used as the backbone for fast fine-tuned classifiers and rerankers. The non-generative baseline Jev's cost and latency claims are usually measured against. Star count is GitHub's rounded display figure.

AnswerDotAI1.7k starsOpen

AlternativeSupport inbox triage+3

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