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Jev Search

Plain-language web search where a decision model like Jev picks query, sources and time range, then ranks Search1API results.

AppproductionMIT
View on GitHub ↗Live demo ↗

Overview

Jev Search lets you search the web in plain language. A decision model, TypeSafe's Jev, Cloudflare's Clef or OpenAI's GPT-6 Luna Decisions, answers typed questions about the request, and the app uses those judgments to choose a query, sources and a time range, which you can override. It then searches Google, DuckDuckGo, Yandex and vertical engines such as Hacker News, Reddit, GitHub, arXiv, YouTube, Wikipedia, IMDb and WeChat through Search1API concurrently.

The decision model scores each result for relevance; results are merged by URL, ordered by relevance, engine agreement and original rank, streamed as each lane finishes, and lower-scoring matches are grouped separately. There are no generated answers, only links and snippets with visible relevance scores. Failed sources show a warning rather than a zero count. When several models are configured, users can pick one or use Auto. The app does not record queries or clicks in its own analytics. It is installable as a web app, built by Search1API, independent of TypeSafe, and MIT-licensed with 534 stars in the input data.

What the decision model decides

TypeQuestionAnswers
ChoiceWhich sources should this request search?—
ChoiceWhat time range fits this request?—
Yes / noIs this result relevant to the request?yes · no

How it works

  1. Interpret the request with typed questions
  2. Choose query, sources and time range
  3. Search engines concurrently via Search1API
  4. Score results for relevance and merge by URL
  5. Stream ranked lanes to the user

Strengths

  • No generated answers; links with visible scores
  • Multiple decision-model providers
  • Robust to individual engine failures

Caveats

  • Depends on Search1API and a decision-model provider
  • Model choices and coverage can vary

Getting started

Try it at https://jev.s1.dev

At a glance

Type
App
Status
production
Language
TypeScript
Runtime
Web app (PWA)
Has code
yes
License
MIT
Stars
534

Use cases and integrations

How curated lists describe it

  • Web search: uses Jev Noul judgments on result titles and snippets to rank Search1API results by relevance, with application code merging duplicate URLs and grouping lower-scoring matches separately.

    yibie/awesome-jev

  • Unofficial web search app using Jev's Choice and Noul judgments to select sources, time ranges, and query candidates, then rank results retrieved through Search1API

    AnotiaWang/awesome-decision-models

  • Searches the web with Jev choosing sources and time ranges, then ranking returned links.

    logicrw/awesome-jev-projects

  • Search the web with TypeSafe's Jev: source selection, query understanding and relevance ranking. Built with Search1API.

    wh000wh000/awesome-jev-live

  • Uses Jev to select search sources and rank Search1API results, returning source links and snippets.

    cobanov/awesome-jev

  • Search the web with TypeSafe's Jev: source selection, query understanding and relevance ranking. Built with Search1API.

    hellogumbo/awesome-jev

  • Search the web in plain language: Jev answers typed questions about your request, and the app uses those judgments to pick the query, the sources and the time range before ranking what comes back. Installable from the browser as an app.

    MrJev/awesome-jev

Frequently asked questions

What does the decision model decide?

Which query, sources and time range to use, and how relevant each result is.

Does it write answers?

No. It returns links and snippets with relevance scores.

Which models are supported?

Jev, Cloudflare Clef and OpenAI GPT-6 Luna Decisions.

Related projects

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    Live SEO audit from one homepage URL: crawl, 52 rules, Core Web Vitals and Jev page judgments, reported as PDF, XLSX and Markdown.

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    Chrome extension that re-ranks Google results with Jev questions per result and folds away sales pages and SEO filler.

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  • LinkScout

    Browser extension that has Jev score search results for relevance, depth, SEO filler and page type, then re-ranks them with a 0-100 badge.

    Browser extensionprototypeJavaScript
  • Jev Deep Research

    Research agent where GPT plans and Jev finds evidence in parallel across document regions with Choice and Noul.

    Browser extensionresearchTypeScript
  • jevsearch

    shadcn/ui site-search block that shows keyword hits instantly, then has Jev re-rank the top 20 by what the visitor meant.

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  • mappity

    Map where you ask anything in plain words and Jev gives every nearby place a probability, lighting up those likely to match.

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