Cua Multi-System Collaborative Automation Program
achieved through Cua's hybrid virtualization capabilities:
- Infrastructure setup::
1. Start both macOS and LinuxVM:lume run ubuntu-latest -n linux-vm
lume run macos-sequoia-vanilla -n mac-vm
2. Bycua-computer-serverBuilding bridges of communication - Distribution of mandates::
-Define workflows using Python scripts:from cua_agent import CrossVMTask
task = CrossVMTask()
.add_step('mac-vm','打开Safari')
.add_step('linux-vm','运行爬虫脚本') - data synchronization::
1. Configure the shared folder:lume share-folder ~/data /mnt/share
2. Use in-memory temporary storage to accelerate exchange - Exception handling::
-Built-in heartbeat detection mechanism
-Automatic rollback of task timeouts
Typical use cases: GUI operations on the macOS side and background calculations on the Linux side.
This answer comes from the articleCua: Enabling AI agents to securely execute applications in macOS/Linux sandboxesThe
May not be reproduced without permission:AI productivity tools " How to achieve collaborative execution of AI automation tasks across platforms?
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