AIOS: AI Agent Operating System

AIOS is the AI Agent Operating System, which embeds large language model (LLM) into the operating system and facilitates the development and deployment of LLM-based AI Agents. AIOS is designed to address problems (e.g., scheduling, context switch, memory management, storage management, tool management, Agent SDK management, etc.) during the development and deployment of LLM-based agents, towards a better AIOS-Agent ecosystem for agent developers and agent users. AIOS includes the AIOS Kernel (this AIOS repository) and the AIOS SDK (the Cerebrum repository). AIOS supports both Web UI and Terminal UI.

🏠 Architecture of AIOS

Overview

The AIOS system is comprised of two key components: the AIOS kernel and the AIOS-Agent SDK. The AIOS kernel acts as an abstraction layer over the operating system kernel, managing various resources that agents require, such as LLM, memory, storage and tool. The AIOS-Agent SDK is designed for agent users and developers, enabling them to build and run agent applications by interacting with the AIOS kernel. AIOS kernel is the current repository and AIOS-Agent SDK can be found at here

Modules and Connections

Below shows how agents utilize AIOS-Agent SDK to interact with AIOS kernel and how AIOS kernel receives agent queries and leverage the chain of syscalls that are scheduled and dispatched to run in different modules.

📰 News

• [2024-11-30] 🔥 AIOS v0.2.0.beta is released! Including the AIOS Kernel (this AIOS repository) and the AIOS SDK (The Cerebrum repository).
• [2024-09-01] 🔥 AIOS supports multiple agent creation frameworks (e.g., ReAct, Reflexion, OpenAGI, AutoGen, Open Interpreter, MetaGPT). Agents created by these frameworks can onboard AIOS. Onboarding guidelines can be found at the Doc.
• [2024-07-10] 📖 AIOS documentation is up, which can be found at Website.
• [2024-06-20] 🔥 Function calling for open-sourced LLMs (native huggingface, vLLM, ollama) is supported.
• [2024-05-20] 🚀 More agents with ChatGPT-based tool calling are added (i.e., MathAgent, RecAgent, TravelAgent, AcademicAgent and CreationAgent), their profiles and workflows can be found in OpenAGI.
• [2024-05-13] 🛠️ Local models (diffusion models) as tools from HuggingFace are integrated.
• [2024-05-01] 🛠️ The agent creation in AIOS is refactored, which can be found in our OpenAGI package.
• [2024-04-05] 🛠️ AIOS currently supports external tool callings (google search, wolframalpha, rapid API, etc).
• [2024-04-02] 🤝 AIOS Discord Community is up. Welcome to join the community for discussions, brainstorming, development, or just random chats! For how to contribute to AIOS, please see CONTRIBUTE.
• [2024-03-25] ✈️ Our paper AIOS: LLM Agent Operating System is released!
• [2023-12-06] 📋 After several months of working, our perspective paper LLM as OS, Agents as Apps: Envisioning AIOS, Agents and the AIOS-Agent Ecosystem is officially released.

✈️ Getting Started

Please see our ongoing documentation for more information.

• Installation
• Quickstart
• WebUI Quickstart

Installation

Requirements

Python

• Supported versions: Python 3.10 - 3.11

Environment Variables Configuration

AIOS supports several API integrations that require configuration. You can use the following commands:

• aios env list: Show current environment variables, or show available API keys if no variables are set
• aios env set: Show current environment variables, or show available API keys if no variables are set

When no environment variables are set, the following API keys will be shown:

• OPENAI_API_KEY: OpenAI API key for accessing OpenAI services
• GEMINI_API_KEY: Google Gemini API key for accessing Google's Gemini services
• GROQ_API_KEY: Groq API key for accessing Groq services
• HF_AUTH_TOKEN: HuggingFace authentication token for accessing models
• HF_HOME: Optional path to store HuggingFace models

To obtain these API keys:

1. OpenAI API: Visit https://platform.openai.com/api-keys
2. Google Gemini API: Visit https://makersuite.google.com/app/apikey
3. Groq API: Visit https://console.groq.com/keys
4. HuggingFace Token: Visit https://huggingface.co/settings/tokens

Installation from source

Git clone AIOS kernel

git clone https://github.com/agiresearch/AIOS.git
cd AIOS && git checkout v0.2.0.beta

Create venv environment (recommended)

python3.x -m venv venv # Only support for Python 3.10 and 3.11
source venv/bin/activate

or create conda environment

conda create -n venv python=3.x  # Only support for Python 3.10 and 3.11
conda activate venv

If you have GPU environments, you can install the dependencies using

pip install -r requirements-cuda.txt

or else you can install the dependencies using

pip install -r requirements.txt

Note: The machine where the AIOS kernel (AIOS) is installed must also have the AIOS SDK (Cerebrum) installed. Installing AIOS kernel will install the AIOS SDK automatically by default. If you are using the Local Kernel mode, i.e., you are running AIOS and agents on the same machine, then simply install both AIOS and Cerebrum on that machine. If you are using Remote Kernel mode, i.e., running AIOS on Machine 1 and running agents on Machine 2 and the agents remotely interact with the kernel, then you need to install both AIOS kernel and AIOS SDK on Machine 1, and install the AIOS SDK alone on Machine 2. Please follow the guidelines at Cerebrum regarding how to install the SDK.

Quickstart

For the config of LLM endpoints, multiple API keys may be required to set up. Here we provide the .env.example to for easier configuration of these API keys, you can just copy .env.example as .env and set up the required keys based on your needs.

Configurations

Use with OpenAI API

You need to get your OpenAI API key from https://platform.openai.com/api-keys. Then set up your OpenAI API key as an environment variable

export OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>

Use with Gemini API

You need to get your Gemini API key from https://ai.google.dev/gemini-api

export GEMINI_API_KEY=<YOUR_GEMINI_API_KEY>

If you want to use open-sourced models provided by huggingface, here we provide three options:

• Use with ollama
• Use with native huggingface models
• Use with vLLM

Use with ollama

You need to download ollama from from https://ollama.com/.

Then you need to start the ollama server either from ollama app

or using the following command in the terminal

ollama serve

To use models provided by ollama, you need to pull the available models from https://ollama.com/library

ollama pull llama3:8b # use llama3:8b for example

ollama can support both CPU-only and GPU environment, details of how to use ollama can be found at here

Use with native huggingface llm models

Some of the huggingface models require authentification, if you want to use all of the models you need to set up your authentification token in https://huggingface.co/settings/tokens and set up it as an environment variable using the following command

By default, huggingface will download the models in the ~/.cache directory. If you want to designate the download directory, you can set up it using the following command

export HF_HOME=<YOUR_HF_HOME>

Use with vLLM

If you want to speed up the inference of huggingface models, you can use vLLM as the backend.

Note

It is important to note that vLLM currently only supports linux and GPU-enabled environment. So if you do not have the environment, you need to choose other options.

Considering that vLLM itself does not support passing designated GPU ids, you need to either setup the environment variable,

export CUDA_VISIBLE_DEVICES="0" # replace with your designated gpu ids

or you can pass the CUDA_VISIBLE_DEVICES as the prefix

Launch AIOS

After you setup your keys or environment parameters, then you can follow the instructions below to start.

First, you need to start the AIOS kernel by running the following commands

bash runtime/launch_kernel.sh

Then you can start the client provided by the AIOS-Agent SDK either in the terminal or in the WebUI. The instructions can be found at here

Supported Agent Frameworks

• OpenAGI
• AutoGen
• Open-Interpreter
• MetaGPT

Supported LLM Cores

Provider 🏢	Model Name 🤖	Open Source 🔓	Model String ⌨️	Backend ⚙️	Required API Key
Anthropic	Claude 3.5 Sonnet	❌	claude-3-5-sonnet-20241022	anthropic	ANTHROPIC_API_KEY
Anthropic	Claude 3.5 Haiku	❌	claude-3-5-haiku-20241022	anthropic	ANTHROPIC_API_KEY
Anthropic	Claude 3 Opus	❌	claude-3-opus-20240229	anthropic	ANTHROPIC_API_KEY
Anthropic	Claude 3 Sonnet	❌	claude-3-sonnet-20240229	anthropic	ANTHROPIC_API_KEY
Anthropic	Claude 3 Haiku	❌	claude-3-haiku-20240307	anthropic	ANTHROPIC_API_KEY
OpenAI	GPT-4	❌	gpt-4	openai	OPENAI_API_KEY
OpenAI	GPT-4 Turbo	❌	gpt-4-turbo	openai	OPENAI_API_KEY
OpenAI	GPT-4o	❌	gpt-4o	openai	OPENAI_API_KEY
OpenAI	GPT-4o mini	❌	gpt-4o-mini	openai	OPENAI_API_KEY
OpenAI	GPT-3.5 Turbo	❌	gpt-3.5-turbo	openai	OPENAI_API_KEY
Google	Gemini 1.5 Flash	❌	gemini-1.5-flash	google	GEMINI_API_KEY
Google	Gemini 1.5 Flash-8B	❌	gemini-1.5-flash-8b	google	GEMINI_API_KEY
Google	Gemini 1.5 Pro	❌	gemini-1.5-pro	google	GEMINI_API_KEY
Google	Gemini 1.0 Pro	❌	gemini-1.0-pro	google	GEMINI_API_KEY
Groq	Llama 3.2 90B Vision	✅	llama-3.2-90b-vision-preview	groq	GROQ_API_KEY
Groq	Llama 3.2 11B Vision	✅	llama-3.2-11b-vision-preview	groq	GROQ_API_KEY
Groq	Llama 3.1 70B	✅	llama-3.1-70b-versatile	groq	GROQ_API_KEY
Groq	Llama Guard 3 8B	✅	llama-guard-3-8b	groq	GROQ_API_KEY
Groq	Llama 3 70B	✅	llama3-70b-8192	groq	GROQ_API_KEY
Groq	Llama 3 8B	✅	llama3-8b-8192	groq	GROQ_API_KEY
Groq	Mixtral 8x7B	✅	mixtral-8x7b-32768	groq	GROQ_API_KEY
Groq	Gemma 7B	✅	gemma-7b-it	groq	GROQ_API_KEY
Groq	Gemma 2B	✅	gemma2-9b-it	groq	GROQ_API_KEY
Groq	Llama3 Groq 70B	✅	llama3-groq-70b-8192-tool-use-preview	groq	GROQ_API_KEY
Groq	Llama3 Groq 8B	✅	llama3-groq-8b-8192-tool-use-preview	groq	GROQ_API_KEY
ollama	All Models	✅	model-name	ollama	-
vLLM	All Models	✅	model-name	vllm	-
HuggingFace	All Models	✅	model-name	huggingface	HF_HOME

🖋️ References

@article{mei2024aios,
  title={AIOS: LLM Agent Operating System},
  author={Mei, Kai and Li, Zelong and Xu, Shuyuan and Ye, Ruosong and Ge, Yingqiang and Zhang, Yongfeng}
  journal={arXiv:2403.16971},
  year={2024}
}
@article{ge2023llm,
  title={LLM as OS, Agents as Apps: Envisioning AIOS, Agents and the AIOS-Agent Ecosystem},
  author={Ge, Yingqiang and Ren, Yujie and Hua, Wenyue and Xu, Shuyuan and Tan, Juntao and Zhang, Yongfeng},
  journal={arXiv:2312.03815},
  year={2023}
}

🚀 Contributions

For how to contribute, see CONTRIBUTE. If you would like to contribute to the codebase, issues or pull requests are always welcome!

🌍 AIOS Contributors

🤝 Discord Channel

If you would like to join the community, ask questions, chat with fellows, learn about or propose new features, and participate in future developments, join our Discord Community!