AIOS, a Large Language Model (LLM) Agent operating system, embeds large language model into Operating Systems (OS) as the brain of the OS, enabling an operating system "with soul" -- an important step towards AGI. AIOS is designed to optimize resource allocation, facilitate context switch across agents, enable concurrent execution of agents, provide tool service for agents, maintain access control for agents, and provide a rich set of toolkits for LLM Agent developers.

• [2024-03-25] ✈️ Our paper AIOS: LLM Agent Operating System is released and AIOS repository is officially launched!
• [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.

git clone https://github.com/agiresearch/AIOS.git

Make sure you have Python >= 3.9
Install the required packages using pip

pip install -r requirements.txt

Set up Hugging Face token and cache directory

export HUGGING_FACE_HUB_TOKEN=<YOUR READ TOKEN>
export HF_HOME=<YOUR CACHE DIRECTORY>

Replace the max_gpu_memory and eval_device with your own and run

# Use Gemma-2b-it
python main.py --llm_name gemma-2b-it --max_gpu_memory '{"0": "24GB"}' --eval_device "cuda:0" --max_new_tokens 256

# Use Mixtral-8x7b-it
python main.py --llm_name mixtral-8x7b-it --max_gpu_memory '{"0": "48GB", "1": "48GB", "2": "48GB"}' --eval_device "cuda:0" --max_new_tokens 256

Run with Gemini-pro, setup Gemini API Key

export GEMINI_API_KEY=<YOUR GEMINI API KEY>

# Use Gemini-pro
python main.py --llm_name gemini-pro

AIOS is dedicated to facilitating LLM agents' development and deployment in a systematic way, we are always looking for passionate collaborators to join us to foster a more cohesive, effective and efficient AIOS-Agent ecosystem. Suggestions and pull requests are always welcome!

@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}
}