What it is
A Python package that gives typed, calibrated decisions from any open-weights LLM in one forward pass, running locally on your own GPU. For developers who want Jev-style decision-making without the official SDK.
How it uses Jev
Jev reads a state once and answers each typed question (Choice, Score, Noul) from the next-token distribution at its own position, restricted to the options you give. The result is a choice with a calibrated probability, used directly in code.
Primitives:choicescorenoul
Technique worth stealing
Packing writes the shared state once instead of once per question, cutting tokens and boosting throughput.
Try it
pip install open-alternative-jev, then use Decider.from_pretrained with backend='hf'.
Evidence
Each line is one question put to Jev about the README. ≥ 0.60 reads as yes, ≤ 0.40 as no; in between Jev is not making a call.
- Jev-centricyes0.84
- Shows a System One patternno0.26
- Handles uncertaintyno0.06
- Measuredno0.10
- Runnableyes0.95
- Worth recommendingno0.16
- Model replicayes0.95
- Problem scopescore on a 0–2 scale1.15
- About Jevyes0.95
Signals by Jev jev-1.13.0, card written by DeepSeek V4.1 Flash from the README on 21 Sept 2026.