DataJev

an LLM performs Python-based analysis while Jev reads the compressed analytical state and decides whether the agent should continue the current direction, switch to another one, verify a finding, or stop and synthesize the answer.

NOUL 호출은 이렇게 생겼다

이 질문 유형의 일반적인 뼈대이지 이 프로젝트의 실제 코드가 아니다.

from typesafe import TypeSafe

ts = TypeSafe()
result = ts.evaluate(
    state=tool_call,
    questions={
        "is_risky": {
            "type": "noul",
            "instructions": "Could this call delete or overwrite user data?",
        }
    },
)
if result["is_risky"] and result["is_risky_confidence"] > 0.6:
    escalate_to_human(tool_call)