OmniParser/computer_use_demo/readme.md

OmniParser+X Computer Use Demo

Control a Windows 11 VM with OmniParser+X (X = [GPT family (4o/o1/o3-mini), Claude, deepseek R1/V3, Qwen-2.5VL]).

Overview

There are three components:

1. windowshost: A Windows 11 VM running in a Docker container
2. omniparserserver: FastAPI server running OmniParser
3. gradio: UI where you can provide commands and watch OmniParser+X reasoning and executing on the Windows 11 VM

Notes:

1. The Windows 11 VM docker is dependent on KVM so can only run quickly on Windows and Linux. This can run on a CPU machine (doesn't need GPU).
2. Though OmniParser can run on a CPU, we have separated this out if you want to run it fast on a GPU machine
3. The Gradio UI can also run on a CPU machine.

Setup

1. windowshost:

   a. Install Docker Desktop

   b. Visit Microsoft Evaluation Center, accept the Terms of Service, and download a Windows 11 Enterprise Evaluation (90-day trial, English, United States) ISO file [~6GB]. Rename the file to custom.iso and copy it to the directory OmniParser/computer_use_demo/windowshost/vm/win11iso

   c. Navigate to vm management script directory withcd OmniParser/computer_use_demo/windowshost/scripts

   d. Build the docker container [400MB] and install the ISO to a storage folder [20GB] with ./manage_vm.sh create

   e. After creating the first time it will store a save of the VM state in vm/win11storage. You can then manage the VM with ./manage_vm.sh start and ./manage_vm.sh stop. To delete the VM, use ./manage_vm.sh delete and delete the OmniParser/computer_use_demo/windowshost/vm/win11storage directory.

2. omniparserserver:

   a. If you already have a conda environment for OmniParser, you can use that. Else follow the following steps to create one

   b. Ensure conda is installed with conda --version or install from the Anaconda website

   c. Navigate to the root of the repo with cd OmniParser

   d. Create a conda python environment with conda create -n "omni" python==3.12

   e. Set the python environment to be used with conda activate omni

   f. Install the dependencies with pip install -r requirements.txt

   g. Continue from here if you already had the conda environment.

   h. Ensure you have the weights downloaded in weights folder. If not download them with: for folder in icon_caption_florence icon_detect icon_detect_v1_5; do huggingface-cli download microsoft/OmniParser --local-dir weights/ --repo-type model --include "$folder/*"; done

   h. Navigate to the server directory with cd OmniParser/computer_use_demo/omniparserserver

   i. Start the server with python -m omniparserserver

3. gradio:

   a. Navigate to the gradio directory with cd OmniParser/computer_use_demo/gradio

   b. Ensure you have activated the conda python environment with conda activate omni

   c. Start the server with python app.py --windows_host_url localhost:8006 --omniparser_server_url localhost:8000

   d. Open the URL in the terminal output, set your API Key from OpenAI and start playing with the AI agent!