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CommunityCookbooks & Demos8 starsVerified 2026-09-22

PROMPT FPS

Two WebAssembly builds of the Chocolate Doom 3.1.1 engine play the same Freedoom map from the same initial state, with a Jev Choice decision picking each tactical macro and a local controller turning it into inputs.

Open github.comlukaske/jev-doom-agent
Category
Cookbooks & Demos
Published by
Community
Author
lukaske
Added
2026-09-22
Tagscommunitytypescriptgamesbrowserdemo

Highlights

  • Jev receives structured game state - health, armor, ammo, damage, coordinates, kills, line-of-sight monsters, and pickups - not raw pixels.
  • The local motor controller executes each macro as movement, turning, firing, weapon, or use inputs; Jev never controls engine internals.
  • A failed or low-confidence call is marked FALLBACK and never silently becomes simulated Jev; offline mode displays OFFLINE SIMULATED POLICY - NOT JEV.
  • A vendored GPL Chocolate Doom fork built with Emscripten 4.0.14 drives the engine, and the API key is kept only in process memory, never logged or persisted.
  • The project ships only Freedoom 0.13.0 content, and the controller performs short keyboard-level macros rather than omniscient pathfinding.

Quickstart

bash
npm install
npm run dev
# open http://127.0.0.1:5173/compare and click Connect Jev

Watch out

No license file, so reuse terms are unclear, while the vendored Chocolate Doom fork is GPL-2.0-or-later and Freedoom content is BSD-licensed; needs Node and a TypeSafe API key for live decisions.

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From the community

Posts from builders shipping with Jev right now.

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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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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