WindowsAgentArena

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WindowsAgentArena (WAA) is an AI Agents & Automation tool that provides a scalable OS platform for testing and benchmarking multi-modal AI agents. It offers a reproducible Windows OS environment for AI research and agentic AI workflows.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is WindowsAgentArena?

WindowsAgentArena (WAA) is a scalable Windows AI agent platform designed for testing and benchmarking multi-modal, desktop AI agents. It provides researchers and developers with a reproducible and realistic Windows OS environment, enabling the testing of agentic AI workflows across a diverse range of tasks. WAA supports the deployment of agents at scale using Azure ML cloud infrastructure, allowing for parallel execution of multiple agents and delivering quick benchmark results for hundreds of tasks in minutes. The platform includes features like a new difficulty mode for tasks, the Navi agent with Omniparser, and the open-sourced Omniparser screen understanding model. Users can deploy locally using Docker and WSL 2, or leverage Azure for parallel benchmarking.

Best used for

Ideal for developers and researchers who need to test and benchmark multi-modal AI agents, deploy agents at scale, and conduct AI research in a reproducible Windows OS environment. Especially valuable for quickly obtaining benchmark results for hundreds of tasks using Azure ML cloud infrastructure.

Common actions

test AI agents

benchmark AI agents

develop AI workflows

research AI agents

deepfakecollaborationworkflowslow-code/no-codeopen-sourceautomated workflowgithub copilot"AI Agents"face swapping

Capabilities

Key features

Scalable Windows OS platform
Multi-modal AI agent testing
Azure ML cloud integration
Reproducible OS environment
Customizable task difficulty
Omniparser screen understanding

Target Audience

developerprofessor

Integrations

azure-mldockeropenai

Pricing & Plans

Open Source

Free

FAQs

What are the prerequisites for running WindowsAgentArena locally?

To run WAA locally, you need Docker daemon installed (with WSL 2 on Windows), an OpenAI or Azure OpenAI API Key, and Python 3.9. The repository also requires cloning and installing dependencies via pip.

How can I deploy agents at scale using WindowsAgentArena?

WAA supports scalable deployment using Azure ML cloud infrastructure. This allows for parallel running of multiple agents, significantly reducing the time needed to test agents across all benchmark tasks from days to minutes.

Can I customize the difficulty of tasks in WindowsAgentArena?

Yes, WAA includes a new difficulty mode. You can change the default 'normal' difficulty to 'hard' in the start_client.sh script. In harder tasks, agents must initialize and set up tasks themselves.

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This tool also appears in

Research & Education › Academic Research Coding & Development › Testing & QA

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