Awesome

💡 Introduction

Welcome to Agent S, an open-source framework designed to enable autonomous interaction with computers through Agent-Computer Interface. Our mission is to build intelligent GUI agents that can learn from past experiences and perform complex tasks autonomously on your computer.

Whether you're interested in AI, automation, or contributing to cutting-edge agent-based systems, we're excited to have you here!

🎯 Current Results

🛠️ Installation

Clone the repository

git clone https://github.com/simular-ai/Agent-S.git

Install the gui-agents package

pip install gui-agents

Set your LLM API Keys and other environment variables. You can do this by adding the following lines to your .bashrc (Linux), or .zshrc (MacOS) file.

export OPENAI_API_KEY=<YOUR_API_KEY>

We also support Azure OpenAI, Anthropic, and vLLM inference. For more information refer to models.md.

⚠️ Warning: The agent will directly run python code to control your computer. Please use with care.

🚀 Usage

Run Locally on your Own Computer

Run agent_s on your computer using:

agent_s --model gpt-4o

This will show a user query prompt where you can enter your query and interact with Agent S. You can use any model from the list of supported models in models.md.

OSWorld

To deploy Agent S in OSWorld, follow the OSWorld Deployment instructions.

WindowsAgentArena

To deploy Agent S in WindowsAgentArena, follow the WindowsAgentArena Deployment instructions.

Setup Retrieval from Web using Perplexica

AgentS works best with web-knowledge retrieval. To enable this feature, you need to setup Perplexica:

1. Ensure Docker is installed and running on your system.

2. Initialize the Perplexica submodule:

   cd Agent-S
   git submodule update --init
   

3. After initializing, navigate to the directory containing the project files.

   cd Perplexica
   

4. Rename the sample.config.toml file to config.toml. For Docker setups, you need only fill in the following fields:

   • OPENAI: Your OpenAI API key. You only need to fill this if you wish to use OpenAI's models.

   • OLLAMA: Your Ollama API URL. You should enter it as http://host.docker.internal:PORT_NUMBER. If you installed Ollama on port 11434, use http://host.docker.internal:11434. For other ports, adjust accordingly. You need to fill this if you wish to use Ollama's models instead of OpenAI's.

   • GROQ: Your Groq API key. You only need to fill this if you wish to use Groq's hosted models.

   • ANTHROPIC: Your Anthropic API key. You only need to fill this if you wish to use Anthropic models.

     Note: You can change these after starting Perplexica from the settings dialog.

   • SIMILARITY_MEASURE: The similarity measure to use (This is filled by default; you can leave it as is if you are unsure about it.)

5. Ensure you are in the directory containing the docker-compose.yaml file and execute:

   docker compose up -d
   

6. Our implementation of Agent S incorporates the Perplexica API to integrate a search engine capability, which allows for a more convenient and responsive user experience. If you want to tailor the API to your settings and specific requirements, you may modify the URL and the message of request parameters in agent_s/query_perplexica.py. For a comprehensive guide on configuring the Perplexica API, please refer to Perplexica Search API Documentation

For a more detailed setup and usage guide, please refer to the Perplexica Repository

Setup Paddle-OCR Server

Run the ocr_server.py file code to use OCR-based bounding boxes.

cd agent_s
python ocr_server.py

Switch to a new terminal where you will run Agent S. Set the OCR_SERVER_ADDRESS environment variable as shown below. For a better experience, add the following line directly to your .bashrc (Linux), or .zshrc (MacOS) file.

export OCR_SERVER_ADDRESS=http://localhost:8000/ocr/

You can change the server address by editing the address in agent_s/utils/ocr_server.py file

🙌 Contributors

We’re grateful to all the amazing people who have contributed to this project. Thank you! 🙏
Contributors List

💬 Citation

@misc{agashe2024agentsopenagentic,
      title={Agent S: An Open Agentic Framework that Uses Computers Like a Human}, 
      author={Saaket Agashe and Jiuzhou Han and Shuyu Gan and Jiachen Yang and Ang Li and Xin Eric Wang},
      year={2024},
      eprint={2410.08164},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2410.08164}, 
}