TL;DR: c/ua (pronounced "koo-ah", short for Computer-Use Agent) is a framework that enables AI agents to control full operating systems within high-performance, lightweight virtual containers. It delivers up to 97% native speed on Apple Silicon and works with any vision language models.

c/ua offers two primary capabilities in a single integrated framework:

1. High-Performance Virtualization - Create and run macOS/Linux virtual machines on Apple Silicon with near-native performance (up to 97% of native speed) using the Lume CLI with Apple's Virtualization.Framework.

2. Computer-Use Interface & Agent - A framework that allows AI systems to observe and control these virtual environments - interacting with applications, browsing the web, writing code, and performing complex workflows.

• Security & Isolation: Run AI agents in fully isolated virtual environments instead of giving them access to your main system
• Performance: Near-native performance on Apple Silicon
• Flexibility: Run macOS or Linux environments with the same framework
• Reproducibility: Create consistent, deterministic environments for AI agent workflows
• LLM Integration: Built-in support for connecting to various LLM providers

• Mac with Apple Silicon (M1/M2/M3/M4 series)
• macOS 15 (Sequoia) or newer
• Python 3.10+ (required for the Computer, Agent, and MCP libraries). We recommend using Conda (or Anaconda) to create an ad hoc Python environment.
• Disk space for VM images (30GB+ recommended)

If you only need the virtualization capabilities:

sudo /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/trycua/cua/main/libs/lume/scripts/install.sh)"

For Lume usage instructions, refer to the Lume documentation.

If you want to use AI agents with virtualized environments:

1. Install the Lume CLI:

   sudo /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/trycua/cua/main/libs/lume/scripts/install.sh)"

2. Pull the latest macOS CUA image:

   lume pull macos-sequoia-cua:latest

3. Start Lume daemon service:

4. Install the Python libraries:

   pip install cua-computer cua-agent[all]

5. Use the libraries in your Python code:

   from computer import Computer
   from agent import ComputerAgent, LLM, AgentLoop, LLMProvider
   
   async with Computer(verbosity=logging.DEBUG) as macos_computer:
     agent = ComputerAgent(
         computer=macos_computer,
         loop=AgentLoop.OPENAI, # or AgentLoop.ANTHROPIC, or AgentLoop.OMNI
         model=LLM(provider=LLMProvider.OPENAI) # or LLM(provider=LLMProvider.ANTHROPIC)
     )
   
     tasks = [
         "Look for a repository named trycua/cua on GitHub.",
     ]
   
     for task in tasks:
       async for result in agent.run(task):
         print(result)

   Explore the Agent Notebook for a ready-to-run example.

6. Optionally, you can use the Agent with a Gradio UI:

   from utils import load_dotenv_files
   load_dotenv_files()
    
   from agent.ui.gradio.app import create_gradio_ui
   
   app = create_gradio_ui()
   app.launch(share=False)

If you want to contribute to the project or need the latest nightly features:

# Clone the repository
git clone https://github.com/trycua/cua.git
cd cua

# Open the project in VSCode
code ./vscode/py.code-workspace

# Build the project
./scripts/build.sh

See our Developer-Guide for more information.