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CommunityTools & Integrations273 starsVerified 2026-09-22

jev-align

An experimental Sutro CLI that evaluates CSV, Parquet, and JSONL data with Jev, asks you to label ambiguous and random audit rows, and uses GEPA to propose improved function definitions.

Open github.comsutro-sh/jev-align
Category
Tools & Integrations
Published by
Community
Author
sutro-sh
Added
2026-09-22
Tagscommunitypythoncliclassificationevaluation

Highlights

  • Each round measures uncertainty, selects ambiguous rows plus a random audit sample, runs GEPA, and shows a definition diff to accept, reject, or rewind.
  • Supports binary, multiclass, multilabel, and score tasks with 5, 10, 15, or 20 training annotations per round and a default GEPA budget of 300 metric calls.
  • Runs Jev through TypeSafe AI, Vercel AI Gateway, or Cloudflare Workers AI; the Vercel and Cloudflare routes do not need a TYPESAFE_API_KEY.
  • Published functions go to ai-functions.dev with their definition, labels, and rationales; the registry is public, so publish only data you can share.

Quickstart

bash
uv tool install jev-align
export TYPESAFE_API_KEY=YOUR_API_KEY
export OPENAI_API_KEY=YOUR_OPENAI_KEY
jeva

Watch out

Apache-2.0. Needs Python 3.11+ and a TYPESAFE_API_KEY or Vercel/Cloudflare credentials, plus an OpenAI, Anthropic, or Gemini key for GEPA; Sutro is not affiliated with TypeSafe AI.

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From the community

Posts from builders shipping with Jev right now.

Follow @typesafeai

Security decisions that fit Jev

Kostas
Kostas
@Kostastsale
·

This made me rethink where AI actually fits into security engineering. For purely engineering work, forget about ChatGPT or Claude. TypeSafe AI just released Jev, and I think it’s going to change how we build AI into security workflows. Instead of asking an LLM to “investigate Show more

TypeSafe AI
TypeSafe AI
@typesafeai

we are officially out of stealth! join the frontier and get access to Jev on our website (link on profile)

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Read 14 replies

A million judged questions

Inferring Jev's internals from 1,000 calls

iwashi / Yoshimasa Iwase
iwashi / Yoshimasa Iwase
@iwashi86
·

Jevの内部アーキテクチャを推測している技術記事(Jev’s Architecture Unmasked)からメモ。 ・本記事はJevのAPIを約1万回の呼び出して、内部構造を推測したもの ・従来の言語モデルを用いた分類やルーティングでは、トークンを1文字ずつ逐次生成するために膨大な無駄な計算コストが発生していた。 Show more

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Read 2 replies

The open System One roundup

小墨同学
小墨同学
@xiaomovps
·

Jev 发布没几天，开源社区已经开始疯狂复刻了🔥 最值得推荐的五个模型： 1、Laya 421M：原生决策模型，支持 Mac 2、Decider-2B：最像 Jev，基于 Qwen3.5 3、NanoJev 0.6B：专门的 Decision Head 4、Reflex：Qwen3.5 + Direct Logits 5、System-One 4B：专门做概率校准 Show more

小墨同学
小墨同学
@xiaomovps

Jev 刚发布没几天，开源社区就出现了同款🔥 Decider-2B模型，是基于 Qwen3.5-2B 做了特殊调整 它和 Jev 模型是一样的 只做选择 评分和判断 不是文本类的 LLM 模型 但两者还是有几个明显区别： 1、模型 Jev：闭源 System One Model Decider：Qwen3.5-2B，约 1.9B 参数，Apache 2.0 开源 2、价格

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The launch post

Trading bot, one decision per block