69 lines
3.3 KiB
Markdown
69 lines
3.3 KiB
Markdown
<p align="center">
|
|
<img src="../imgs/header_bar.png" alt="OmniParser+X Computer Use Demo screenshot">
|
|
</p>
|
|
|
|
# OmniTool
|
|
|
|
Control a Windows 11 VM with OmniParser+X (OpenAI (4o/o1/o3-mini), DeepSeek (R1), Qwen (2.5VL)) or Anthropic Computer Use.
|
|
|
|
## Overview
|
|
|
|
There are three components:
|
|
|
|
1. **omnibox**: A Windows 11 VM running in a Docker container
|
|
2. **omniparserserver**: FastAPI server running OmniParser V2
|
|
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. We suggest running **omnibox** and **gradio** on the same CPU machine and **omniparserserver** on a GPU server.
|
|
|
|
## Setup
|
|
|
|
1. **omnibox**:
|
|
|
|
a. Install Docker Desktop
|
|
|
|
b. Visit [Microsoft Evaluation Center](https://info.microsoft.com/ww-landing-windows-11-enterprise.html), 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/omnitool/omnibox/vm/win11iso`
|
|
|
|
c. Navigate to vm management script directory with`cd OmniParser/omnitool/omnibox/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/omnitool/omnibox/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](https://www.anaconda.com/download/success)
|
|
|
|
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/omnitool/omniparserserver`
|
|
|
|
i. Start the server with `python -m omniparserserver`
|
|
|
|
3. **gradio**:
|
|
|
|
a. Navigate to the gradio directory with `cd OmniParser/omnitool/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!
|