jev-align (Sutro)

evaluates CSV, Parquet, and JSONL rows with Jev `Choice`, `Score`, or `Boolean` decisions, sends ambiguous and audit samples to a human, and uses accepted human labels to optimize the saved definition with GEPA.

작성자

sutro-sh

분야

Dataset engineering

분류

데이터 라벨링과 정리

유형

REPO

호스트

github.com

GITHUB에서 보기

무엇을 판단하는가

CHOICE

Picks one option from a fixed set

SCORE

Rates against ordered levels

NOUL

Answers a yes / no question

Inferred from this project's own one-line summary in the community list — it reads as a SCORE + NOUL decision. Read the source to confirm.

SCORE 호출은 이렇게 생겼다

이 질문 유형의 일반적인 뼈대이지 이 프로젝트의 실제 코드가 아니다.

from typesafe import TypeSafe

ts = TypeSafe()
result = ts.evaluate(
    state=candidate,
    questions={
        "relevance": {
            "type": "score",
            "levels": ["low", "medium", "high"],
            "instructions": "How relevant is this to the query?",
        }
    },
)
if result["relevance"] >= 0.7:
    keep(candidate)

데이터 라벨링과 정리 프로젝트 더 보기

jev-curatesifts synthetic JSONL and Parquet rows using Jev Noul checks and calibrated confidence scores, streaming passed records and rejections straight to disk.typeful-triagemultiplayer triage dashboard where Jev answers a fixed set of typed questions per issue — kind, severity, urgency, duplicate, and next step — and every human correction is kept and shown back to the model on later runs.jlinklinks records under a plain-English match rule using Jev Noul pair judgments, with local candidate blocking and match resolution.jgrepfilters text, structured records, functions, and diff hunks against plain-English descriptions using Jev Noul judgments.