Jev for semantic search and reranking

Saksham Malhotra

@SakshamMalhot27

Launching JevRelevanceRetriever just $0.73 across 6,460 calls Open src Jev LangChain BaseRetriever for rel scoring Install and use it, no chain changes ;) pip install jev-relevance Repo-https://github.com/saksham-malhotra-27/jev-relevance Open for issues and PRs, feel free to contribute

Gabriel Pauli

@gabrielpavli

Working on a simple tool that uses JEV to help organise my bookmarks. The UI is awful and it’s nothing crazy, but it’s been nice to learn about JEV and how it works.

Viv

@Vtrivedy10

Jev for RAG in almost all cases you trust the semantic matching capability of Jev more than dot product similarity very useful as the direct similarity metric in small data cases and a great reranker with big data

NO1ennn

@N01ennn

this is pure f*cking treasure A Stanford AI research group finally drew the perfect RAG system: retrieval, Jev and agents in one loop, and it fixes the 3 things that break every RAG app: > the LLM reads 20 passages when only 3 matter > it answers questions your docs can't answer > it trusts whatever text it retrieves here's how it runs: > a lead agent sends the query > hybrid search pulls the top 20 candidates, dense + keyword > ONE Jev request scores all 20 + 2 gates: answerable? injection? > only passages above 0.6 reach the writer agent > a second Jev call checks every claim against its source > grounded answer, with citations and when the docs don't have it: > answerable fails, the writer never runs > a researcher agent rewrites the query and retries once > still nothing? "not in the docs". zero tokens spent on a guess retrieval casts the net. Jev decides what's real. agents do the work save this before you build your next RAG

Avi Chawla

@_avichawla

Another insane Jev use case! Traditional database filters need precise, predefined conditions. But many questions are semantic: - Is this article mainly about software engineering? - Which topic best describes it? - How technically deep does it appear? These usually require moving rows into application code, invoking a model, parsing its output, and writing the result back. pg-jev is an open-source Postgres extension that exposes Jev through SQL functions. - jev() works inside WHERE - jev_prob() returns a probability - jev_choice() selects a label - jev_score() ranks rows across ordered levels. It needs no vector column or embedding index. Under the hood, pg-jev batches rows, sends them to Jev, and returns typed answers that SQL can filter, sort, group, and combine with exact predicates. The recording below runs it against real Hacker News stories stored in Postgres. It first shows the rows, then asks Jev to find software-engineering stories, classify them by topic, and rank them by technical depth. The final query reports requests, tokens, cost, and cache hits from the database session. GitHub repo: https://github.com/realZachi/pg-jev (don't forget to star it ⭐) Postgres keeps the data and controls the query, while Jev handles the part SQL cannot express as a deterministic condition. If you want to understand what Jev is doing under the hood, I also wrote a hands-on guide to building a Jev-style model with open models, entirely locally. Read it below.

Paone

@paonx_eth

i sent a crawler through github's new ai repos from the last 30 days. this is what it looks like 1 crawler turns into 128 2,000 repos, every readme, every word it steps on each one goes to jev with one question: is this worth your time? 99.3% got thrown out. wrappers, copies, empty readmes, lists of lists 9 survived: 01 colibri · runs a 744b model on 16gb of ram and a big ssd. slow, but it's yours 02 voicebox · clone a voice from a few seconds of audio. 23 languages, nothing leaves your machine 03 BrowserSkill · tencent. claude code or codex works in your logged-in browser while you keep working 04 security-audit-skill · the skill cloudflare's bug-hunting harness grew from 05 open-code-review · alibaba's internal ai code reviewer. ~1/9 the tokens of claude code on the same model 06 agent-skills · 25 senior-engineer workflows: /spec /plan /build /test /review /ship 07 OpenResearch · turns claude code or codex into a research agent: papers, hypotheses, experiments 08 WeKnora · tencent. drop in your docs, get rag answers, an agent and a wiki that maintains itself 09 ECC · 68 agents and 293 skills for claude code, codex and cursor. 272k stars 4 of the 9 come from alibaba, cloudflare and tencent. big tech is open-sourcing the ai tools it runs on itself links in the reply. save this

Eduardo

@eduardo_builds

I built Smart Find: Ctrl+F, but for questions. Ask any web page a question and it jumps you to the passages that answer it. Powered by Jev, each search takes under a second and costs less than a cent. Open source Chrome extension github.com/eduardoalba00/…