EverOS

项目详情摘要

Website · Documentation · Blog · 中文 Table of Contents Why EverOS Ecosystem Integrations Quick Start Use Cases Documentation EverMind Ecosystem Contributing Why EverOS EverOS is a Python library and local-first memory runtime for agents and makers. It gives one portable memory layer across coding assistants, apps, devices, and workflows from day one. It stores conversations, files, and agent trajectories as readable Markdown, then syncs local SQLite and LanceDB indexes for fast retrieval and self-evolving reuse. Title EverOS Other Agent Memory Libraries Markdown source of truth ✅ Canonical .md files that are readable, editable, diffable, and Git-versioned ❌ Usually API, vector, graph, dashboard, or database state Direct file editing ✅ Edit .md files; cascade watcher syncs ❌ Usually SDK, API, dashboard, or backend update paths Local three-part stack ✅ Markdown + SQLite + LanceDB; no MongoDB, Elasticsearch, or Redis required ❌ Often depends on managed services, vector DBs, graph DBs, or server stacks User + agent tracks ✅ User episodes/profile and agent cases/skills are separate first-class surfaces ❌ Usually centered on chat history, profiles, entities, facts, or retrieval records Orthogonal retrieval ✅ Search by user_id , agent_id , app_id , project_id , and session_id ❌ Usually app, namespace, tenant, thread, or graph scoped Knowledge Wiki ✅ Editable, source-backed Markdown knowledge pages with taxonomy, CRUD APIs, and topic search ❌ Usually separate from memory, trapped in a dashboard, or not tied back to source files Reflection ✅ Offline memory evolution that merges episode clusters and refines profiles and skills between sessions ❌ Usually retrieval-only memory with little background consolidation or long-horizon improvement Ecosystem Integrations EverOS adds durable