EverMind-AI / EverOS

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 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 memory to the agent and workflow platforms below—and comes
built into Raven. Choose an integration to open its setup guide.
 DeepSeek Harness 
 Hermes 
 OpenClaw 
 Raven 
 Dify 
## Quick Start
> One OpenRouter API key is enough to start EverOS, write durable memories,
> and retrieve them with keyword search.
### Prerequisites
- Python 3.12+
- One OpenRouter API key
### 1. Install
 [code] 
### 2. Try the standalone demo — no key required
No API key or server setup required—run one command to quickly experience how
EverOS stores and recalls memory:
 [code] 
Enter something EverOS should remember, then ask a related question to watch
the memory move through ingest -> extract -> index -> recall.
### 3. Initialize and add your OpenRouter key
 [code] 
This creates `~/.everos/everos.toml` and `~/.everos/ome.toml`. Open
`~/.everos/everos.toml`; the generated model and OpenRouter URL are already
correct, so replace only the empty `api_key`:
 [code] 
This is the smallest Tier 1 setup: memory add, flush, Markdown persistence,
cascade indexing, and keyword search.
Use `everos init --root ` if you want a different memory roo