freshcrate
Skin:/
Home > AI Agents > AgentOS

AgentOS

Manage your tokens, eliminate wasted usage! Not a LangChain/OpenClaw wrapper. A fully self-developed agent team orchestration system with proprietary architecture & memory system, delivering 5x+ effic

Why this rank:Strong adoptionRecent releaseHealthy release cadence

Description

Manage your tokens, eliminate wasted usage! Not a LangChain/OpenClaw wrapper. A fully self-developed agent team orchestration system with proprietary architecture & memory system, delivering 5x+ efficiency and 5x less token consumption than OpenClaw for engineering-grade tasks.

README

Agent OS

The seminal fourth "Operating System Philosophy" in human computing history.

English | 简体中文

AtomGit star GitHubVersion License Build

C/C++ Python Go Rust TypeScript

🌟 Introduction

AgentOS is an intelligent agent operating system that provides comprehensive OS-level support for orchestrating agent teams.

💡 Innovation Highlights

Foundational Theory 👉 Multibody Cybernetic Intelligent System

  • Pure Kernel: Only atomic mechanisms (IPC/Mem/Task/Time), ensuring purity and efficiency.
  • Cognitive Loop: Perception → Planning → Action, with dual-system synergy (System 1 + System 2).
  • Memory Stratification: L1 Raw → L2 Features → L3 Structures → L4 Patterns, enabling intelligence emergence.
  • Inherent Security: Four-layer protection: Sandbox Isolation, Permission Arbitration, Input Sanitization, Audit Trail.
  • Token Efficiency: Saves approximately 500% tokens compared to traditional frameworks.
  • Comprehensive SDKs: Native support for Go / Python / Rust / TypeScript.

🎯 Core Philosophy

Team Orchestration

  • Precisely coordinates multi‑agent collaboration
  • Enables efficient task orchestration and resource scheduling

Autonomous Evolution

  • Self‑evolving capability
  • Dynamically adjusts strategies
  • Continuously optimizes execution effectiveness

✨ Groundbreaking Architecture · Inherent Security · Intelligence Emergence ✨

🏗️ System Architecture

Architecture Design
Complete architecture from kernel to application:

Application Layer (openlab)
    ⇅
Service Layer (daemon)
    ⇅
Kernel Layer (atoms)
    ⇅
Security Layer (cupolas)
    ⇅
Support Layer (commons)
    ⇅
SDK Layer (toolkit)

Design Principles
Built upon ARCHITECTURAL_PRINCIPLES:

  • System Perspective: Feedback loops · Layered decomposition · Holistic design · Emergence management → Response <10ms
  • Kernel Perspective: Minimalist kernel · Contractual interfaces · Service isolation · Pluggable strategies → Kernel ~25K LOC
  • Cognitive Perspective: Dual‑system synergy · Incremental evolution · Memory stratification · Forgetting mechanism → Token savings 500%
  • Engineering Perspective: Security built‑in · Observability · Resource determinism · Cross‑platform consistency → Test coverage >90%
  • Design Aesthetics: Simplicity first · Extreme attention to detail · Human‑centric · Perfectionism → API <50 per module

🚀 Quick Start

📦 Requirements

  • OS: Ubuntu 22.04+ / macOS 13+ / Windows 11 (WSL2)
  • Compiler: GCC 11+ / Clang 14+ (C11/C++17)
  • Build Tools: CMake 3.20+, Ninja
  • Python: 3.10+ (Required for OpenLab)

🔨 Installation & Build

# 1. Clone repository
git clone https://atomgit.com/spharx/agentos.git && cd agentos

# 2. Install dependencies (Ubuntu)
sudo apt install -y build-essential cmake gcc g++ libssl-dev libsqlite3-dev ninja-build

# 3. Build kernel
mkdir build && cd build
cmake .. -G Ninja -DCMAKE_BUILD_TYPE=Release -DBUILD_TESTS=ON
cmake --build . --parallel $(nproc)

# 4. Run tests
ctest --output-on-failure

🐳 Docker Quick Start

# Build image
docker build -f scripts/deploy/docker/Dockerfile.kernel -t agentos:latest .

# Run container
docker run -d --name agentos -p 8080:8080 -v ./config:/app/config agentos:latest

💻 Usage

Language Usage
C/C++ Develop via syscalls.h system call interface
Python Install via pip install agentos then import directly
Go Use import "github.com/spharx/agentos/toolkit/go"
Rust Use use agentos_toolkit::prelude::*;
TypeScript Install via npm install @spharx/agentos-toolkit then import directly

📚 Documentation

Document Core Content
📘 Architectural Principles Multibody Cybernetic Intelligent System, 24 core principles
🚀 Quick Start 5‑minute getting‑started guide
⚙️ Build Guide Detailed build steps and options
🧪 Testing Guide Unit/Integration/Contract testing
🐳 Deployment Guide Docker/Kubernetes deployment

❔ FAQ

Q1: How does AgentOS differ from traditional AI Agent frameworks?

AgentOS is an operating‑system‑level product, not merely a framework:

Dimension AgentOS Traditional Frameworks
Positioning Multi‑agent collaboration OS Single agent
Architecture Microkernel + strict layering Loosely coupled modules
Security Four‑layer inherent security Application‑level protection
Memory Four‑layer stratification system Vector database
Token Efficiency Saves ~500% No optimization
Q2: What scenarios is it suitable for?

✅ Perfect for

  • 🎯 Complex multi‑step task orchestration
  • 🧠 Long‑term memory and knowledge accumulation
  • 🔒 High‑security enterprise applications
  • 💾 Resource‑constrained embedded scenarios (atomslite)
  • 🌐 Multi‑language development teams

❌ Not suitable for

  • 🚫 Simple single‑call tasks (overkill)
Q3: How is security guaranteed?

Security built‑in design, four‑layer protection

Protection Layer Implementation
Virtual Workspace Process/Container/WASM sandbox isolation
Permission Arbitration RBAC + YAML rule engine
Input Sanitization Regex filtering + Type checking
Audit Trail Full‑chain tamper‑proof logging

See cupolas security documentation

Q4: What prerequisites are needed?
Role Prerequisites Time to Get Started
Application Developer Python/Go basics 1‑2 days
System Developer C/C++, OS fundamentals 1‑2 weeks
Architect Microkernel, distributed systems 1 month

Recommended Path: Quick Start → Architectural Principles → CoreLoopThree

☀️ This is not humanity's sunset, but the dawn of a new world ☀️

🤝 Contributing

"Intelligence emergence, and nothing less, is the ultimate sublimation of AI."

This is the future we are stepping into.

🚩 The Power of Belief

Believe
The spirit of open source can unleash the collective wisdom of the community, propelling humanity to new heights.

Witness
Every day of our work is part of history, destined to be engraved on the monument of human civilization, witnessing the true emergence of intelligence.

This is not humanity's sunset, but the dawn of a new world.

💫 Ways to Contribute

Whether you are an experienced developer or just starting out:

  • 🐛 Find Issues → Report bugs, help us improve quality
  • 💡 Share Ideas → Suggest new features, make the project stronger
  • 📝 Share Knowledge → Improve documentation, help more people understand AgentOS
  • 🔧 Write Code → Submit PRs, jointly build a better intelligent agent OS

📝 Contribution Process

See Contributing Guide

Fork Project → Create Branch → Develop & Test → Submit PR → Code Review → Merge to Main

Main Platforms: AtomGit (Recommended) · Gitee · GitHub

🔥 "A faint light cannot illuminate the entire path, yet it guides our direction forward." 🔥

📜 License

This project is licensed under the Apache License 2.0. See LICENSE file for details.


"From data intelligence emerges."

AtomGit · Gitee · GitHub · Official Website

© 2026 SPHARX Ltd. All Rights Reserved.


⭐️ Github Star History

Star History Chart

Release History

VersionChangesUrgencyDate
v0.1.19AgentRT v0.1.19 ## 2. 平台支持 - Linux(主力平台):x86-64 / x86-32 / arm-64 / arm-32 - macOS:arm-64(Apple Silicon)/ x86-64(Intel) - Windows:x86-64 / x86-32 ## 3. 安装 ```bash curl -fsSL https://atomgit.com/openairymax/agentrt/releases/download/v0.1.19/install.sh | bash ``` Windows(PowerShell): ```powershell irm https://atomgit.com/openairymax/agentrt/releases/download/v0.1.19/install.ps1 | iex ``` ## 4. 本版变更 * airy_cli: derive chat tools json from schema ssot macros * commons: advance for the windowsHigh10/19/2026
v0.1.18AgentRT v0.1.18 ## 2. 平台支持 - Linux(主力平台):x86-64 / x86-32 / arm-64 / arm-32 - macOS:arm-64(Apple Silicon)/ x86-64(Intel) - Windows:x86-64 / x86-32 ## 3. 安装 ```bash curl -fsSL https://atomgit.com/openairymax/agentrt/releases/download/v0.1.18/install.sh | bash ``` Windows(PowerShell): ```powershell irm https://atomgit.com/openairymax/agentrt/releases/download/v0.1.18/install.ps1 | iex ``` ## 4. 本版变更 * latest: restore supervisor launcher and bump gate pins * launcher: fix AIRY_HOME discovery High9/23/2026
v0.1.17AgentRT v0.1.17 ## 2. 平台支持 - Linux(主力平台):x86-64 / x86-32 / arm-64 / arm-32 - macOS:arm-64(Apple Silicon)/ x86-64(Intel) - Windows:x86-64 / x86-32 ## 3. 安装 ```bash curl -fsSL https://atomgit.com/openairymax/agentrt/releases/download/v0.1.17/install.sh | bash ``` Windows(PowerShell): ```powershell irm https://atomgit.com/openairymax/agentrt/releases/download/v0.1.17/install.ps1 | iex ``` ## 4. 本版变更 * install: drop explanatory comments and refresh fallback version * gates: enforce cli commanHigh9/17/2026
v0.1.16AgentRT v0.1.16 ## 1. 本版亮点 - **联网与工具可用性(长对话 / 含中文与 emoji)**:记忆的写入与召回由"按字节下标截断"改为"按 UTF-8 字符边界回退",CLI 与网关两条路径同步修复,网关侧再对残余非法字节做一次清洗;含中文或 emoji 的长对话不再把记忆库写坏,也不再因请求体出现非法 UTF-8 而被供应商以 HTTP 400 `invalid unicode code point` 拒收——此前这一类拒绝会被上报为"网络失败",把用户引向并不存在的连通性问题。 - **错误诊断**:模型服务拒绝(HTTP 400/422,如请求体非法)不再被归入笼统的读写错误,改为明确提示"请求被模型服务拒绝"并附上供应商返回的原文,用户可直接据此自助定位。 - **存量数据修复**:早期版本按字节截断写坏的记忆记录本轮做一次性清理(保留备份),消除会再次触发上述 400 的隐患。 ## 2. 平台支持 - Linux(主力平台):x86-64 / x86-32 / arm-64 / arm-32 - macOS:arm-64(Apple SilHigh9/14/2026
v0.1.15AgentRT v0.1.15 ## 1. 本版亮点 - **二轮社区反馈修复(工具不可用 / 连接不上网络)**:工具子进程不再继承运行时 `LD_LIBRARY_PATH`——覆盖 `shell_run`、`web_fetch`/`web_search`、git 工具以及经 `sys_tool_execute` 启动的外部工具,消除 `libcurl.so.4: no version information available` 一类因 ABI 错配导致的工具失效;LLM 供应商 HTTP 401/403/429 不再统一归一化为 `AIRY_ERR_IO`,改为返回可区分的鉴权/限流错误码,用户不再被"网络请求失败"误导去排查并不存在的网络故障,仅 `http_code == 0`(连接确实未建立)仍报网络错误;未配置密钥时不再发送空的 `Authorization` 头,并在日志中明确告警;鉴权、模型与参数类确定性失败不再触发外层 4 次 × 内层 5 次的请求风暴,报错更快且不会触发供应商侧风控;启动阶段适配器暂不可用降级为提示日志,不再记为 ERROR;LLM 供应商单High9/13/2026
v0.1.13AgentRT v0.1.13 ## 平台支持 - Linux(主力平台):x86-64 / x86-32 / ARM64 / ARM32 - macOS:x86-64(Intel)/ ARM64(Apple Silicon) - Windows:x86-64 / x86-32 ## 安装 ```bash curl -fsSL https://atomgit.com/openairymax/agentrt/releases/download/v0.1.13/install.sh | bash ``` Windows(PowerShell): ```powershell irm https://atomgit.com/openairymax/agentrt/releases/download/v0.1.13/install.ps1 | iex ``` ## 本版变更 High9/9/2026
v0.0.5- AirymaxOS v0.0.5 Release - 极镜OS v0.0.5 内测版High5/17/2026
main@2026-05-13Latest activity on main branchHigh5/13/2026
v1.0.0.9Latest release: v1.0.0.9High4/9/2026

Dependencies & License Audit

Loading dependencies...

Similar Packages

agent-aiAi agent abstractionmaster@2026-10-25
CopilotKitThe Frontend Stack for Agents & Generative UI. React + Angular. Makers of the AG-UI Protocolv1.80.0
fronaFrona is a personal AI assistant. You create autonomous agents, give them tools, and talk to them through a chat interface. Agents act on their own. They browse the web, run code, develop applicationsv2026.10.0
MMClawUltra-Lightweight, Pure Python Multimodal Agent.main@2026-07-11
eternegoThe Eternego codebasev0.18.0

More in AI Agents

claude-memA Claude Code plugin that automatically captures everything Claude does during your coding sessions, compresses it with AI (using Claude's agent-sdk), and injects relevant context back into future ses
AIGC-Interview-Book【三年面试五年模拟】AIGC算法工程师面试秘籍。涵盖AIGC、LLM大模型、AI Agent、传统深度学习、自动驾驶、机器学习、计算机视觉、自然语言处理、强化学习、大数据挖掘、具身智能、元宇宙、AGI等AI行业面试笔试干货经验与核心知识。
letta-codeThe memory-first coding agent
nano-banana-pro-prompts-recommend-skillAI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.