Jev AI

Jev Wrapped

reads up to 1,500 posts from the last year of a public Telegram channel and asks Jev a `Choice` over ten kinds of post plus three `Noul` questions (paid ad, clickbait, emotional pressure) about each, counting an ad from 0.7, or from 0.4 when the kind is also ad, and clickbait and pressure from 0.5, then draws the monthly mix on a shareable card that links the highest-scoring posts for a manual check.

OWNER
gaborishka
INDUSTRY
Media analysis
CATEGORY
Classification & Routing
KIND
REPO
HOST
github.com
VIEW ON GITHUB

WHAT IT DECIDES

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.

THE SHAPE OF A SCORE CALL

A generic skeleton for this question type, not this project's actual code.

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)
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