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https://github.com/othersideai/self-operating-computer
A framework to enable multimodal models to operate a computer.
https://github.com/othersideai/self-operating-computer
automation openai pyautogui
Last synced: 5 days ago
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A framework to enable multimodal models to operate a computer.
- Host: GitHub
- URL: https://github.com/othersideai/self-operating-computer
- Owner: OthersideAI
- License: mit
- Created: 2023-11-04T03:13:45.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-25T18:54:07.000Z (26 days ago)
- Last Synced: 2024-12-09T14:14:47.786Z (12 days ago)
- Topics: automation, openai, pyautogui
- Language: Python
- Homepage: https://www.hyperwriteai.com/self-operating-computer
- Size: 12.2 MB
- Stars: 8,948
- Watchers: 128
- Forks: 1,203
- Open Issues: 71
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
- awesome-ChatGPT-repositories - self-operating-computer - A framework to enable multimodal models to operate a computer. (Openai)
README
Self-Operating Computer Framework
A framework to enable multimodal models to operate a computer.
Using the same inputs and outputs as a human operator, the model views the screen and decides on a series of mouse and keyboard actions to reach an objective.
## Key Features
- **Compatibility**: Designed for various multimodal models.
- **Integration**: Currently integrated with **GPT-4o, Gemini Pro Vision, Claude 3 and LLaVa.**
- **Future Plans**: Support for additional models.
## Ongoing Development
At [HyperwriteAI](https://www.hyperwriteai.com/), we are developing Agent-1-Vision a multimodal model with more accurate click location predictions.
## Agent-1-Vision Model API Access
We will soon be offering API access to our Agent-1-Vision model.
If you're interested in gaining access to this API, sign up [here](https://othersideai.typeform.com/to/FszaJ1k8?typeform-source=www.hyperwriteai.com).
## Demo
https://github.com/OthersideAI/self-operating-computer/assets/42594239/9e8abc96-c76a-46fb-9b13-03678b3c67e0
## Run `Self-Operating Computer`
1. **Install the project**
```
pip install self-operating-computer
```
2. **Run the project**
```
operate
```
3. **Enter your OpenAI Key**: If you don't have one, you can obtain an OpenAI key [here](https://platform.openai.com/account/api-keys). If you need you change your key at a later point, run `vim .env` to open the `.env` and replace the old key.
4. **Give Terminal app the required permissions**: As a last step, the Terminal app will ask for permission for "Screen Recording" and "Accessibility" in the "Security & Privacy" page of Mac's "System Preferences".
## Using `operate` Modes
### Multimodal Models `-m`
An additional model is now compatible with the Self Operating Computer Framework. Try Google's `gemini-pro-vision` by following the instructions below.
Start `operate` with the Gemini model
```
operate -m gemini-pro-vision
```
**Enter your Google AI Studio API key when terminal prompts you for it** If you don't have one, you can obtain a key [here](https://makersuite.google.com/app/apikey) after setting up your Google AI Studio account. You may also need [authorize credentials for a desktop application](https://ai.google.dev/palm_docs/oauth_quickstart). It took me a bit of time to get it working, if anyone knows a simpler way, please make a PR.
#### Try Claude `-m claude-3`
Use Claude 3 with Vision to see how it stacks up to GPT-4-Vision at operating a computer. Navigate to the [Claude dashboard](https://console.anthropic.com/dashboard) to get an API key and run the command below to try it.
```
operate -m claude-3
```
#### Try LLaVa Hosted Through Ollama `-m llava`
If you wish to experiment with the Self-Operating Computer Framework using LLaVA on your own machine, you can with Ollama!
*Note: Ollama currently only supports MacOS and Linux*
First, install Ollama on your machine from https://ollama.ai/download.
Once Ollama is installed, pull the LLaVA model:
```
ollama pull llava
```
This will download the model on your machine which takes approximately 5 GB of storage.
When Ollama has finished pulling LLaVA, start the server:
```
ollama serve
```
That's it! Now start `operate` and select the LLaVA model:
```
operate -m llava
```
**Important:** Error rates when using LLaVA are very high. This is simply intended to be a base to build off of as local multimodal models improve over time.
Learn more about Ollama at its [GitHub Repository](https://www.github.com/ollama/ollama)
### Voice Mode `--voice`
The framework supports voice inputs for the objective. Try voice by following the instructions below.
**Clone the repo** to a directory on your computer:
```
git clone https://github.com/OthersideAI/self-operating-computer.git
```
**Cd into directory**:
```
cd self-operating-computer
```
Install the additional `requirements-audio.txt`
```
pip install -r requirements-audio.txt
```
**Install device requirements**
For mac users:
```
brew install portaudio
```
For Linux users:
```
sudo apt install portaudio19-dev python3-pyaudio
```
Run with voice mode
```
operate --voice
```
### Optical Character Recognition Mode `-m gpt-4-with-ocr`
The Self-Operating Computer Framework now integrates Optical Character Recognition (OCR) capabilities with the `gpt-4-with-ocr` mode. This mode gives GPT-4 a hash map of clickable elements by coordinates. GPT-4 can decide to `click` elements by text and then the code references the hash map to get the coordinates for that element GPT-4 wanted to click.
Based on recent tests, OCR performs better than `som` and vanilla GPT-4 so we made it the default for the project. To use the OCR mode you can simply write:
`operate` or `operate -m gpt-4-with-ocr` will also work.
### Set-of-Mark Prompting `-m gpt-4-with-som`
The Self-Operating Computer Framework now supports Set-of-Mark (SoM) Prompting with the `gpt-4-with-som` command. This new visual prompting method enhances the visual grounding capabilities of large multimodal models.
Learn more about SoM Prompting in the detailed arXiv paper: [here](https://arxiv.org/abs/2310.11441).
For this initial version, a simple YOLOv8 model is trained for button detection, and the `best.pt` file is included under `model/weights/`. Users are encouraged to swap in their `best.pt` file to evaluate performance improvements. If your model outperforms the existing one, please contribute by creating a pull request (PR).
Start `operate` with the SoM model
```
operate -m gpt-4-with-som
```
## Contributions are Welcomed!:
If you want to contribute yourself, see [CONTRIBUTING.md](https://github.com/OthersideAI/self-operating-computer/blob/main/CONTRIBUTING.md).
## Feedback
For any input on improving this project, feel free to reach out to [Josh](https://twitter.com/josh_bickett) on Twitter.
## Join Our Discord Community
For real-time discussions and community support, join our Discord server.
- If you're already a member, join the discussion in [#self-operating-computer](https://discord.com/channels/877638638001877052/1181241785834541157).
- If you're new, first [join our Discord Server](https://discord.gg/YqaKtyBEzM) and then navigate to the [#self-operating-computer](https://discord.com/channels/877638638001877052/1181241785834541157).
## Follow HyperWriteAI for More Updates
Stay updated with the latest developments:
- Follow HyperWriteAI on [Twitter](https://twitter.com/HyperWriteAI).
- Follow HyperWriteAI on [LinkedIn](https://www.linkedin.com/company/othersideai/).
## Compatibility
- This project is compatible with Mac OS, Windows, and Linux (with X server installed).
## OpenAI Rate Limiting Note
The ```gpt-4o``` model is required. To unlock access to this model, your account needs to spend at least \$5 in API credits. Pre-paying for these credits will unlock access if you haven't already spent the minimum \$5.
Learn more **[here](https://platform.openai.com/docs/guides/rate-limits?context=tier-one)**