Summary

AgentOS is an intelligent agent operating system designed for orchestrating complex multi-agent collaborations. It targets developers building sophisticated AI applications requiring long-term memory, high accuracy, and robust security, offering significant efficiency gains.

How It Works

Built on a "Multibody Cybernetic Intelligent System" (MCIS) foundation, AgentOS employs a minimalist kernel and a Cognitive Loop (Perception, Planning, Action). Core innovations include Memory Stratification (L1-L4) for efficient knowledge management and Inherent Security across four layers (sandbox, permissions, sanitization, audit). This architecture enables substantial token efficiency (~500% savings) and real-time responses (<10ms), supported by native SDKs in Go, Python, Rust, and TypeScript.

Quick Start & Requirements

Requires Ubuntu 22.04+, macOS 13+, or Windows 11 (WSL2), with GCC 11+/Clang 14+, CMake 3.20+, Ninja, and Python 3.10+. Installation involves cloning, installing system dependencies (e.g., sudo apt install build-essential cmake ninja-build libssl-dev libsqlite3-dev), and compiling the kernel via CMake. Docker images are provided. Usage is supported via native SDKs for C/C++, Python (pip install agentos), Go, Rust, and TypeScript. Detailed guides are available.

Highlighted Details

• Achieves 200K+ context window and 8-10M memory.
• Claims 99.10% accuracy for 1000-hour tasks and 5x efficiency over mainstream frameworks.
• Features a four-layer inherent security model: Virtual Workspace, Permission Arbitration, Input Sanitization, and Audit Trail.
• Compatible with LangChain, Claude, OpenAI, and other agent frameworks.
• Kernel is ~25K LOC with >90% test coverage.

Maintenance & Community

Actively seeks contributions via bug reports, feature suggestions, documentation, and code submissions. Primary platforms: AtomGit, Gitee, GitHub. Contributors listed in AUTHORS.md. No specific community channels (e.g., Discord, Slack) mentioned.

Licensing & Compatibility

Licensed under Apache License 2.0, permitting commercial use and integration into closed-source projects. No specific compatibility restrictions noted.

Limitations & Caveats

Not recommended for simple, single-call tasks ("sledgehammer to crack a nut"). Setup requires compilation from source, potentially time-consuming, and specific build environment configurations.