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

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

lume pull macos-sequoia-cua:latest

pip install "cua-computer[all]" "cua-agent[all]"

from computer import Computer
from agent import ComputerAgent, LLM

async def main():
    # Start a local macOS VM with a 1024x768 display
    async with Computer(os_type="macos", display="1024x768") as computer:

        # Example: Direct control of a macOS VM with Computer
        await computer.interface.left_click(100, 200)
        await computer.interface.type_text("Hello, world!")
        screenshot_bytes = await computer.interface.screenshot()
        
        # Example: Create and run an agent locally using mlx-community/UI-TARS-1.5-7B-6bit
        agent = ComputerAgent(
          computer=computer,
          loop="UITARS",
          model=LLM(provider="MLXVLM", name="mlx-community/UI-TARS-1.5-7B-6bit")
        )
        await agent.run("Find the trycua/cua repository on GitHub and follow the quick start guide")

main()

# Install Lume CLI and background service
curl -fsSL https://raw.githubusercontent.com/trycua/cua/main/libs/lume/scripts/install.sh | bash

# List all VMs
lume ls

# Pull a VM image
lume pull macos-sequoia-cua:latest

# Create a new VM
lume create my-vm --os macos --cpu 4 --memory 8GB --disk-size 50GB

# Run a VM (creates and starts if it doesn't exist)
lume run macos-sequoia-cua:latest

# Stop a VM
lume stop macos-sequoia-cua_latest

# Delete a VM
lume delete macos-sequoia-cua_latest

# Install Lume CLI and background service
curl -fsSL https://raw.githubusercontent.com/trycua/cua/main/libs/lume/scripts/install.sh | bash

# Run macOS in a Docker container
docker run -it --rm \
    --name lumier-vm \
    -p 8006:8006 \
    -v $(pwd)/storage:/storage \
    -v $(pwd)/shared:/shared \
    -e VM_NAME=lumier-vm \
    -e VERSION=ghcr.io/trycua/macos-sequoia-cua:latest \
    -e CPU_CORES=4 \
    -e RAM_SIZE=8192 \
    -e HOST_STORAGE_PATH=$(pwd)/storage \
    -e HOST_SHARED_PATH=$(pwd)/shared \
    trycua/lumier:latest

# Mouse Actions
await computer.interface.left_click(x, y)       # Left click at coordinates
await computer.interface.right_click(x, y)      # Right click at coordinates
await computer.interface.double_click(x, y)     # Double click at coordinates
await computer.interface.move_cursor(x, y)      # Move cursor to coordinates
await computer.interface.drag_to(x, y, duration)  # Drag to coordinates
await computer.interface.get_cursor_position()  # Get current cursor position

# Keyboard Actions
await computer.interface.type_text("Hello")     # Type text
await computer.interface.press_key("enter")     # Press a single key
await computer.interface.hotkey("command", "c") # Press key combination

# Screen Actions
await computer.interface.screenshot()           # Take a screenshot
await computer.interface.get_screen_size()      # Get screen dimensions

# Clipboard Actions
await computer.interface.set_clipboard(text)    # Set clipboard content
await computer.interface.copy_to_clipboard()    # Get clipboard content

# File System Operations
await computer.interface.file_exists(path)      # Check if file exists
await computer.interface.directory_exists(path) # Check if directory exists
await computer.interface.run_command(cmd)       # Run shell command

# Accessibility
await computer.interface.get_accessibility_tree() # Get accessibility tree

# Import necessary components
from agent import ComputerAgent, LLM, AgentLoop, LLMProvider

# UI-TARS-1.5 agent for local execution with MLX
ComputerAgent(loop=AgentLoop.UITARS, model=LLM(provider=LLMProvider.MLXVLM, name="mlx-community/UI-TARS-1.5-7B-6bit"))   
# OpenAI Computer-Use agent using OPENAI_API_KEY  
ComputerAgent(loop=AgentLoop.OPENAI, model=LLM(provider=LLMProvider.OPENAI, name="computer-use-preview"))
# Anthropic Claude agent using ANTHROPIC_API_KEY
ComputerAgent(loop=AgentLoop.ANTHROPIC, model=LLM(provider=LLMProvider.ANTHROPIC))

# OmniParser loop for UI control using Set-of-Marks (SOM) prompting and any vision LLM
ComputerAgent(loop=AgentLoop.OMNI, model=LLM(provider=LLMProvider.OLLAMA, name="gemma3:12b-it-q4_K_M"))      
# OpenRouter example using OAICOMPAT provider
ComputerAgent(
    loop=AgentLoop.OMNI,
    model=LLM(
        provider=LLMProvider.OAICOMPAT, 
        name="openai/gpt-4o-mini",
        provider_base_url="https://openrouter.ai/api/v1"
    ),
    api_key="your-openrouter-api-key"
)