gum-ai 0.1.0

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GUM (General User Models)

Documentation

We have some early auto-generated docs here: docs/gum.md

This is very much an alpha release---things will get a lot cleaner and less buggy very soon. In the mean time, feel free to follow the instructions below.

Installation

[!WARNING] This repository uses GPT 4.1 as a placeholder. However, we STRONGLY encourage users to deploy their own local models to serve GUMs. Our paper uses Qwen 2.5 VL and Llama 3.3. We use the OpenAI ChatCompletions API, but awesome open source inference projects like vLLM support the endpoint.

Install from source for now (package coming soon!) As of now, we've only tested MacOS:

git clone https://github.com/GeneralUserModels/gum
cd gum
pip install -e .

Usage

1. Basic setup:

# Make sure to set OPENAI API ENV variables

import asyncio
from gum import gum
from gum.observers import Screen

async def main():
    async with gum("Omar Shaikh", Screen()):
        await asyncio.Future() # run forever (Ctrl-C to stop)

if __name__ == "__main__":
    asyncio.run(main())

2. Using the CLI:

gum start --user-name "your_name"

3. Setting up an MCP:

Check out this repository for using GUMs with MCP.

Project Structure

• gum/: Main package directory
  • gum.py: Core functionality and gum classes
  • models.py: Database models and schemas
  • db_utils.py: Database utilities
  • observers/: Observer implementations
  • cli.py: Command-line interface
  • prompts/: Prompt templates

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License

Citation and Paper!

If you're interested in reading more, please check out our paper!

Creating General User Models from Computer Use

@article{shaikh2025gums,
    title={Creating General User Models from Computer Use},
    author={Shaikh, Omar and Sapkota, Shardul and Rizvi, Shan and Horvitz, Eric and Park, Joon Sung and Yang, Diyi and Bernstein, Michael S.},
    journal={arXiv preprint},
    year={2025}
}