Gut
Project / 项目 · In the catalogue / 在目录中查看
What Jev decides here · Jev 在这里做什么决定
Classification (分类), Intent routing (意图路由)
choice: read in the code by a model, not yet by a person 由模型在代码里读到，尚无人复核
a model read the call site; no person yet 模型读过调用点，尚无人复核 · · Cited file / 引用的文件: lib/gut/req_llm/jev.ex
Summary · 摘要
Elixir DSL for LLM decisions: Gut.feel(subject, question, choices) returns one of your Elixir values, such as the team that should handle a ticket. Its Jev adapter asks the question as one Choice through ReqLLM; other adapters use any ReqLLM model, Ollama or your own code.written by a model
用于 LLM 决策的 Elixir DSL：Gut.feel(subject, question, choices) 返回你给定的某个 Elixir 值，例如应处理某张工单的团队。其 Jev 适配器通过 ReqLLM 以一个 Choice 问题提问；其他适配器可用任意 ReqLLM 模型、Ollama 或你自己的代码。模型撰写机翻
Notes · 备注
Published on Hex. This row cites the Jev adapter, Gut.ReqLLM.Jev, which needs the optional req_llm dependency and a model such as typesafe:jev-latest. Row drafted from the discovery queue (issue #14) by an AI assistant that read the README and the cited file on 2026-11-02; a maintainer has not yet read the call site.
已发布到 Hex。本条目引用 Jev 适配器 Gut.ReqLLM.Jev，它需要可选依赖 req_llm 以及 typesafe:jev-latest 这类模型。本条目由 AI 助手根据发现队列（issue #14）起草，于 2026-11-02 阅读了 README 和所引文件；维护者尚未亲自阅读调用点。
Launches · 发布记录
Not launched yet. 还没有发布过。 Launch it / 发布它 ↗ · How a product launches / 怎样发布一个产品
Makers · Maker
Made this? Confirm or correct its entry / 这是你做的？确认或更正条目 ↗
The same form takes the product's one line and a demo link, in its maker's own words. 同一个表单也可以补上产品的一句话和演示链接，用 Maker 自己的话。
Badge for its README · README 徽章
[](https://kydlikebtc.github.io/awesome-jev/products/gut.html)One line for the product's README, linked to this page. The picture says that it is listed; while it is on the launch board, that it is launching; after a week in the top three, its place. It is rebuilt with the site, so the line never needs changing. 放进产品 README 的一行，链接到本页。图片显示已收录；在发布榜上时显示正在发布；进过某周前三后显示名次。它随网站一起重建，这一行不用再改。
Also under this pattern · 同一模式的其他产品
json-render
Vercel Labs' generative UI framework. In its Jev experiment the model does not write JSON token by token — it only picks components, props and layout.
Inbox Zero: seven email decisions
Seven distinct email decisions, each with its own separately chosen threshold, falling back to the normal LLM on any error.
pg-jev
A real PostgreSQL extension exposing the primitives as SQL functions, so a semantic decision can appear in a WHERE clause over any row type.
jev-mcp
A ready-made judgement toolbox for agents: fact verification, content screening, semantic ranking, classification and extraction as separate tools.
docjev
Classifies and splits PDF, DOCX and PPTX files: LiteParse extracts page text locally, then Jev picks a document's category with a choice over your rules, or for a packet answers per page a category choice and a noul on whether a new document starts there. Its report covers 40 real PDFs.