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GitHub-Issue-Classification-Using-Jev

GitHub Action triage that asks eight Jev questions in one call, gates labels in plain Python, and layers regex redaction, a Jev guard battery, and a write guard.

Stars
0
Language
Python
License
MIT
Published by
Community
Author
KalyanM45
Last verified
Oct 2026

This repository contains a GitHub issue classifier built on Jev, TypeSafe AI's System One model. It labels every new issue with typed values and calibrated confidence in milliseconds, labelling what it is sure about and escalating what it is not. Three guardrail layers guard every write, and a frozen eval suite gates each deploy.

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0
Last pushed
Updated Sep 2026

Repo stats from the GitHub API, cached Oct 2026.

About this project

Automatic GitHub issue triage built on Jev, TypeSafe AI's System One model. Jev is not an LLM and writes no text: it returns typed values with calibrated probabilities, in 70–500 ms, at $0.042 per million input tokens with output free. An issue opens and, before you have finished reading the title:

Quoted from the project's README. Read the full README.

Highlights

  • Eight questions in one system_one call: type, area, severity score, plus five noul probabilities.
  • Policy gates on numbers in code, withholding low-confidence labels and never auto-labeling duplicates.
  • Layer 1 redacts nine secret patterns locally before anything leaves the machine; layer 3 caps writes.
  • Frozen triage and red-team sets score accuracy, calibration, selective coverage, latency, and cost.

Watch out

Writing is off by default and security labels need a human; absolute floors are placeholders until a real baseline run. Copy reviewed against the repository README on 2026-10-04, not from running it.

Questions about this entry

Short answers drawn from the linked project or page.

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