notjev：利用logprobs将本地LLM转为Jev风格决策引擎

Hi there !

I built notjev, a small Node library that turns any OpenAI-compatible model into a fast System 1 decision engine.

Instead of generating text, it asks the model for a single token (`A`, `B`, `C`…) with `logprobs: true`, keeps only the letter probabilities, renormalises them, and returns:

• a verdict
• a probability
• a margin
• a tunable abstention threshold

You get Choice / Score / Noul style answers, just like Jev, but from the model you already run (vLLM, llama.cpp, Ollama, OpenAI…).

Why it’s interesting

• Zero runtime dependencies
• Works with any model that supports logprobs
• Same weights as your chat model → true System 1 / System 2 split
• Speaks the Jev `/v1/systemone` wire contract
• Very fast: 23 ms p50 on Qwen3-8B with llama-server

Quick example

```js

const { createClient } = require('notjev');

const jev = createClient();

const r = await jev.decide({

state: 'A: "Sarah Knafo"\nB: "Sarah Knafot"',

question: 'same entity?',

options: ['SAME', 'OTHER'],

theta: 0.5,

});

console.log(r.choice, r.p1, r.band, r.undecided);

// → null 0.50 med true

When the margin is too thin, you just escalate to the same model in normal chat mode.
### Repo
https://github.com/9pings/notjev
Would love feedback, especially from people already playing with local models or Jev alternatives.
submitted by /u/n8tz
[link] [comments]