memsearch
Project / 项目 · In the catalogue / 在目录中查看
What Jev decides here · Jev 在这里做什么决定
noul: text signal only: the cited file contains their request or answer shape 仅文本信号:引用的文件里出现了它们的请求或回答格式
a person read the call site 有人读过调用点 · · Cited file / 引用的文件: src/memsearch/jev_reranker.py
Summary · 摘要
Shared semantic memory for AI coding agents such as Claude Code and Codex, kept as Markdown with a Milvus index. Optional Jev reranking sends the query and every candidate in one request, a noul per passage on whether it states what the query asks, and sorts results by those probabilities.written by a model
供 Claude Code、Codex 等 AI 编程智能体共用的语义记忆,以 Markdown 文件保存,用 Milvus 建索引。可选的 Jev 重排把查询和全部候选放进一次请求,对每段候选提一个 noul,问它是否陈述了查询要找的信息,再按这些概率排序。模型撰写机翻
Launches · 发布记录
Not launched yet. 还没有发布过。 Launch it / 发布它 ↗ · How a product launches / 怎样发布一个产品
Makers · Maker
Made this? Confirm or correct its entry / 这是你做的?确认或更正条目 ↗
The same form takes the product's one line and a demo link, in its maker's own words. 同一个表单也可以补上产品的一句话和演示链接,用 Maker 自己的话。
Badge for its README · README 徽章
[](https://kydlikebtc.github.io/awesome-jev/products/memsearch.html)
One line for the product's README, linked to this page. The picture says that it is listed; while it is on the launch board, that it is launching; after a week in the top three, its place. It is rebuilt with the site, so the line never needs changing. 放进产品 README 的一行,链接到本页。图片显示已收录;在发布榜上时显示正在发布;进过某周前三后显示名次。它随网站一起重建,这一行不用再改。
Also under this pattern · 同一模式的其他产品
AutoGPT TypeSafe blocks
Seven production blocks — choice, score, yes/no, ask-many, route, pick-best, filter — with a UTF-8 byte budget, verbatim wire capture and eleven test files.
OpenViking: retrieval reranking
One Noul per candidate document in a single batched request, with the yes-probability used directly as the relevance score.
oh-my-pi
⌥ Coding agent with the IDE wired in
FastMCP jev_search transform
Two-stage MCP tool search: a wide Choice coarse-ranks the whole catalogue, then a shortlist gets full descriptions plus one Noul each to decide whether it does the job at all.
jcode: memory recall without embeddings
Replaces the whole retrieval stack for memory recall — no embeddings, no BM25, no reranker — with one batched Noul per candidate memory.