Skip to content
aiqbench takeAI Products

aiqbench analysis

This article details the implementation of Jev, a decision model by TypeSafe, for automating marketplace listing moderation using TypeScript. It focuses on structuring unstructured input into typed judgments with probability outputs to guide code-based actions like publish or reject. The piece serves as a technical guide for integrating specific AI decision logic into application workflows rather than discussing broader research or policy.
Source coveringOpenRouter
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

How to Use Jev: Moderation with the Jev API in TypeScript

OpenRouter21 min read

A method for putting Jev to work on a new problem, worked end to end on marketplace listing moderation: what stays in code, what Jev sees, how to phrase the questions, and how to turn its probabilities into publish, hold, or reject.

Jev is a decision model from TypeSafe. It takes unstructured input and gives you typed judgments with probabilities in return, and your code decides what to do next. This guide shows how to use Jev on a problem of your own, worked end to end on one example, moderating listings on a marketplace in TypeScript. Okay, so you understand what Jev is for and feel like you’re on the right track. Now, the question is: what does a Jev request look like under the hood? Let’s start from the beginning. Every Jev request consists of a state and a set of questions. The state is the input that Jev should evaluate. It could be a string, JSON object, or array of strings. If you’re attempting to evaluate a sequence of items, such as messages in a conversation, the array is going to be the way to go. The questions are a list of judgments that Jev should perform on the state. A question consists of two elements, namely, instructions and criteria. The instructions describe the judgment that should be performed. The criteria describe the possible answers. When evaluating the state, Jev will determine how well each of the criteria fits…

Excerpt shown under the publisher's RSS terms · 200 words · full text and figures are on the publisher's site

Related coverage