README.md

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Table of Contents

• What is EverOS
• Architecture at a glance
• Quick start
• Storage layout
• Features
• Project structure
• Documentation
• Use Cases
• Stay Tuned
• Contributing

What is EverOS

EverOS is an open-source Python framework that turns conversations, agent trajectories, and files into structured, retrievable, evolving long-term memory for AI agents and user chats. Designed for lightweight local deployments (small teams, individual developers), with three core principles:

1. Markdown as Source of Truth — All memory persists as plain .md files. Open, edit, grep, version with Git, view in Obsidian. No black-box database lock-in.
2. Lightweight three-piece storage — Markdown files (truth) + SQLite (state/queue) + LanceDB (vector + BM25 + scalar). No MongoDB / Elasticsearch / Milvus / Redis / Kafka required.
3. EverAlgo as pure algorithm library — Memory extraction algorithms are decoupled into a separate library; this project orchestrates and persists.

Architecture at a glance

┌───────────────────────────────────────────────┐
│  entrypoints/  (CLI + HTTP API)                │  presentation
├───────────────────────────────────────────────┤
│  service/      (use cases: memorize/retrieve)  │  application
├───────────────────────────────────────────────┤
│  memory/       (extract + search + cascade)    │  domain
├───────────────────────────────────────────────┤
│  infra/        (markdown / sqlite / lancedb)   │  infrastructure
└───────────────────────────────────────────────┘
        ↑                    ↑
   component/            core/
   (LLM/Embedding)       (observability/lifespan)

DDD 5 layers, single-direction dependency. See docs/architecture.md.

Quick start

Install as a package

uv pip install everos               # or: pip install everos

# Generate a starter .env (OpenRouter + DeepInfra defaults; bundled inside the wheel)
everos init                          # writes ./.env (use --xdg for ~/.config/everos/.env)
# Edit .env and fill the API key fields (see comments inside).

everos --help
everos server start

everos server start searches for .env in this order: --env-file <path> → ./.env (cwd) → ${XDG_CONFIG_HOME:-~/.config}/everos/.env → ~/.everos/.env. The endpoint stack is OpenAI-protocol compatible (OpenAI / OpenRouter / vLLM / Ollama / DeepInfra …) — override *__BASE_URL in the generated .env to point at any of them.

Multi-modal (optional)

To ingest non-text content (image / pdf / audio / office documents) through /api/v1/memory/add content items, install the optional extra:

uv pip install 'everos[multimodal]'   # or: pip install 'everos[multimodal]'

This pulls in everalgo-parser (with the [svg] bundle for SVG support via cairosvg) and wires up the multimodal LLM client (EVEROS_MULTIMODAL__* fields in .env, defaults to google/gemini-3-flash-preview via OpenRouter).

Office document support requires LibreOffice as a system dependency. The parser shells out to soffice (LibreOffice's headless renderer) to convert .doc / .docx / .ppt / .pptx / .xls / .xlsx to PDF before feeding the result into the multimodal LLM. Without LibreOffice, office uploads return HTTP 415 with a clear error message; PDF / image / audio / HTML / email parsing is unaffected.

Install on the host before serving office documents:

brew install --cask libreoffice              # macOS
sudo apt-get install -y libreoffice          # Debian / Ubuntu

For a step-by-step walkthrough (add a conversation → flush → search → read the markdown), see QUICKSTART.md.

Develop locally

git clone <repo>
cd everos
uv sync                              # creates ./.venv and installs deps
source .venv/bin/activate            # — or skip activation and prefix every command with `uv run`
everos init                         # fill in EVEROS_LLM__API_KEY in the generated .env

everos --help
make test

Storage layout

~/.everos/
├── default_app/                  # app_id  ("default" → "default_app" on disk)
│   └── default_project/          # project_id ("default" → "default_project")
│       ├── users/<user_id>/
│       │   ├── user.md           # profile
│       │   ├── episodes/         # daily-log episodes (visible)
│       │   ├── .atomic_facts/    # nested facts (dotfile-hidden)
│       │   └── .foresights/      # predictive memory (dotfile-hidden)
│       └── agents/<agent_id>/
│           ├── agent.md
│           ├── .cases/           # one task case per entry
│           └── skills/           # named procedural memories
├── .index/                       # derived indexes (rebuildable from md)
│   ├── sqlite/system.db          # state + queue + audit
│   └── lancedb/*.lance/          # vector + BM25 + scalar
└── .tmp/                         # transient working files

Open any <app>/<project>/users/<user_id>/ folder in Obsidian — your agent's brain is just files. The dotfile directories (.atomic_facts/, .foresights/, .cases/) stay hidden by default so the visible folder is the user-facing memory surface, while extracted derivatives sit quietly alongside.

Features

• Hybrid retrieval: BM25 + vector (HNSW/IVF-PQ) + scalar filter, single-query in LanceDB
• Cascade index sync: edit a .md → file watcher → entry-level diff → LanceDB sync, sub-second
• Multi-source extraction: conversations / agent trajectories / file knowledge
• Dual-track memory: user-track (Episodes / Profiles) + agent-track (Cases / Skills)
• Async-first: full asyncio, single event loop
• Multi-modal: text + small image / audio inline; large media via S3/OSS reference

Project structure

everos/                        # repo root
├── src/everos/                # main package (src layout)
│   ├── entrypoints/           # cli + api
│   ├── service/               # use case orchestration
│   ├── memory/                # domain: extract + search + cascade + prompt_slots
│   ├── infra/                 # storage: markdown + lancedb + sqlite
│   ├── component/             # cross-cutting: llm / embedding / config / utils
│   ├── core/                  # runtime: observability / lifespan / context
│   └── config/                # configuration data + Settings schema
├── tests/                     # unit / integration / golden / fixtures
├── docs/                      # design docs
└── .claude/                   # team-shared rules + skills (auto-loaded by Claude Code)

Documentation

• docs/overview.md — Project overview & vision
• docs/architecture.md — DDD layered architecture & dependency rules
• docs/engineering.md — Engineering & dev-efficiency infrastructure (CI / tooling / Claude Code)
• CHANGELOG.md — Release notes
• CONTRIBUTING.md — How to contribute
• .claude/rules/ — Detailed coding conventions (auto-loaded by Claude Code)

Use Cases

Use cases show what persistent memory makes possible in real products and workflows. Some examples are packaged in this repository; others point to external demos or integrations you can study and adapt.

Reunite - Find with EverOS Parents describe what they remember. Children describe what they recall. Reunite uses semantic memory to surface the connections. Learn more	Hive Orchestrator Browser-native hive-mind for CLI coding agents — Claude Code, Codex, Gemini, and OpenCode collaborate as real PTY processes via a team protocol. Code
AI Coding Assistants with EverOS Universal long-term memory layer for AI coding assistants, powered by EverOS. Code	AI Data Techician An agentic AI system that learns from scientist interaction to inspect, analyze, and classify high-dimensional time series data — with persistent memory that improves across sessions. Code
Rokid AI Assistant with EverOS Connect to EverOS within Rokid Glasses enabling long-term memory for all of your smart activities. Coming soon	Creative Assistant with Memory Creative assistant with long-term memory, never forget your crativites anymore. Coming soon
Earth Online Memory Game Earth Online is a memory-aware productivity game that turns everyday planning into a living quest log. Code	Multi-Agent Orchestration Platform Golutra presents a multi-agent workforce for engineering teams, extending the IDE model from a single assistant to coordinated agents. Code
Your Personal Tasting Universe Record, visualize, and explore your tasting journey through an immersive 3D star map. Code	EverOS Open Her Build AI that feels. Open-source persona engine — personality emerges from neural drives, not prompts. Inspired by Her. Code
Browser Agent for Personal Memory Ruminer brings persistent memory to a browser agent so it can carry personal context across web tasks. Plugin	EverMem Sync with EverOS One command to connect any AI coding CLI to EverMemOS long-term memory. Code
MCO - Orchestrate AI Coding Agents MCO equips your primary agent with an agent team that can work together to solve complex tasks. Code	Study Buddy with Self-Evolving Memory Study proactively with an agent that has self-evolving memory. Code
Alzheimer’s Memory Assistant Empowering individuals with advanced memory support and daily assistance. Code	Memory-Driven Multi-Agent NPC Experience An iOS sci-fi mystery game where players explore and uncover the truth. Code
Mobi Companion An iOS app where users create, nurture, and live with a personalized AI companion called Mobi. Code	AI Wearable with Memory A context-native AI wearable that listens to everyday life and converts conversations into memory. Code
OpenClaw Agent Memory A 24/7 agent workflow with continuous learning memory across sessions. Plugin	Live2D Character with Memory Add long-term memory to a real-time Live2D character, powered by TEN Framework. Code
Computer-Use with Memory Run screenshot-based analysis with computer-use and store the results in memory. Live Demo	Game of Thrones Memories A demonstration of AI memory infrastructure through an interactive Q&A experience with A Game of Thrones. Code
Claude Code Plugin Persistent memory for Claude Code. Automatically saves and recalls context from past coding sessions. Code	Memory Graph Visualization Explore stored entities and relationships in a graph interface. Frontend demo; backend integration is in progress. Live Demo

Stay Tuned

Star the repo or join the community links above to follow new architecture methods, benchmark releases, and memory-enabled use cases.

Contributing

Contributions are welcome across the whole repository: architecture methods, benchmark coverage, use-case examples, documentation, and bug fixes. Browse Issues to find a good entry point, then open a PR when you are ready.

Tip

Welcome all kinds of contributions 🎉

Help make EverOS better. Code, documentation, benchmark reports, use-case write-ups, and integration examples are all valuable. Share your projects on social media to inspire others.

Connect with one of the EverOS maintainers @elliotchen200 on 𝕏 or @cyfyifanchen on GitHub for project updates, discussions, and collaboration opportunities.

Code Contributors

License

Apache License 2.0 — see NOTICE for third-party attributions.

Citation

If you use EverOS in research, see CITATION.md.