From 3a0e1b2d026872b31f969caa21e071b124f77830 Mon Sep 17 00:00:00 2001 From: Elliot Chen Date: Sat, 6 Jun 2026 21:22:20 +0800 Subject: [PATCH 1/2] docs(readme): refine repository watch section Replace the Stay Tuned section with a clearer Watch EverOS call to action in both English and Chinese READMEs. Remove the star GIF and keep star history as lighter social proof. --- README.md | 12 ++++++++---- README.zh-CN.md | 12 +++++++----- 2 files changed, 15 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index c50d3c84..08004c02 100644 --- a/README.md +++ b/README.md @@ -30,7 +30,7 @@ - [Project Structure](#project-structure) - [Documentation](#documentation) - [Use Cases](#use-cases) -- [Stay Tuned](#stay-tuned) +- [Watch EverOS](#watch-everos) - [EverMind Ecosystems](#evermind-ecosystems) - [Contributing](#contributing) @@ -656,11 +656,15 @@ Explore stored entities and relationships in a graph interface. Frontend demo; b -## Stay Tuned +## Watch EverOS -Star the repo or join the community links above to follow new architecture methods, benchmark releases, memory-enabled use cases, Wiki-style memory, and Dreaming updates. +EverOS 1.0.0 is the first release of a larger memory-system roadmap. +Watch this repository for upcoming work on Wiki-style memory, Dreaming, +deeper offline evolution, benchmark releases, and more real-world agent +integrations. -![star us gif](https://github.com/user-attachments/assets/0c512570-945a-483a-9f47-8e067bd34484) +If EverOS is useful to your agent stack, starring the repo helps more +builders discover it. ### Star History diff --git a/README.zh-CN.md b/README.zh-CN.md index 77a04efd..c972491d 100644 --- a/README.zh-CN.md +++ b/README.zh-CN.md @@ -30,7 +30,7 @@ - [项目结构](#项目结构) - [文档](#文档) - [使用场景](#使用场景) -- [持续关注](#持续关注) +- [关注 EverOS](#关注-everos) - [EverMind 生态](#evermind-生态) - [参与贡献](#参与贡献) @@ -642,12 +642,14 @@ Claude Code 的持久记忆插件。自动保存并回忆过去 coding sessions -## 持续关注 +## 关注 EverOS -Star 这个仓库，或加入上面的社区链接，以持续关注新的架构方法、benchmark releases、 -memory-enabled use cases、Wiki 式记忆和 Dreaming 更新。 +EverOS 1.0.0 是更大规模记忆系统路线图的第一个发布版本。Watch 这个仓库， +即可持续关注 Wiki 式记忆、Dreaming、更深入的离线进化、benchmark releases， +以及更多真实 Agent 集成。 -![star us gif](https://github.com/user-attachments/assets/0c512570-945a-483a-9f47-8e067bd34484) +如果 EverOS 对你的 Agent stack 有帮助，Star 这个仓库也会帮助更多 builders +发现它。 ### Star 趋势 From 7dd82b8eabf033a6e89062b51e9c0a0a347d9e48 Mon Sep 17 00:00:00 2001 From: Elliot Chen Date: Sat, 6 Jun 2026 21:31:11 +0800 Subject: [PATCH 2/2] docs(readme): improve highlights table spacing Add spacing below each feature title in the EverOS highlights table. Mirror the same table spacing in the Chinese README. --- README.md | 6 ++++++ README.zh-CN.md | 6 ++++++ 2 files changed, 12 insertions(+) diff --git a/README.md b/README.md index 08004c02..596e576e 100644 --- a/README.md +++ b/README.md @@ -55,16 +55,19 @@ Markdown As Source Of Truth
+
All memory is persisted as .md files: readable, editable, grep-able, Git-versioned, and openable directly in Obsidian. Local Three-Part Stack
+
Markdown + SQLite + LanceDB keep vectors, BM25, and scalar filters local. No MongoDB, Elasticsearch, or Redis required. Dual-Track Memory
+
Agent memory (cases / skills) and user memory (episodes / profile) are extracted independently. @@ -72,16 +75,19 @@ Agent memory (cases / skills) and user memory Multimodal Ingestion
+
Text, images, audio, documents, PDFs, HTML, and email are unified into searchable memory. Self-Evolution
+
Common skills are extracted from real usage; repeated patterns become reusable workflows, no retraining required. Orthogonal Retrieval
+
Search independently by user_id, agent_id, app_id, project_id, and session_id. diff --git a/README.zh-CN.md b/README.zh-CN.md index c972491d..1a382d59 100644 --- a/README.zh-CN.md +++ b/README.zh-CN.md @@ -55,28 +55,34 @@ Markdown As Source Of Truth
+
所有记忆持久化为 .md 文件：可读、可改、可 grep、可 Git 版本化，也可直接用 Obsidian 打开。 Local Three-Part Stack
+
Markdown + SQLite + LanceDB 在本地完成向量、BM25 和标量过滤检索，无需 MongoDB、Elasticsearch 或 Redis。 Dual-Track Memory
+
Agent 记忆（cases / skills）与用户记忆（episodes / profile）独立提取，互不污染。 Multimodal Ingestion
+
文本、图像、音频、文档、PDF、HTML 和邮件统一抽取为可检索的记忆形态。 Self-Evolution
+
从真实使用经验中自动抽取共性 skills，重复模式沉淀为可复用流程，无需重训。 Orthogonal Retrieval
+
按 user_id、agent_id、app_id、project_id 和 session_id 五维独立检索。