# OS-Copilot
**Repository Path**: my_forks/OS-Copilot
## Basic Information
- **Project Name**: OS-Copilot
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: LividWo-update-issue-template
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-07-30
- **Last Updated**: 2024-07-30
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# OS-Copilot: Towards Generalist Computer Agents with Self-Improvement
[](https://os-copilot.github.io/)
[](https://arxiv.org/pdf/2402.07456.pdf)
[](https://os-copilot.readthedocs.io/en/latest/)

[](https://discord.com/invite/rXS2XbgfaD)
[](https://twitter.com/oscopilot)
## 🔥 News
- *2024.3*: 🎉 OS-Copilot is accepted at the [LLM Agents Workshop](https://llmagents.github.io/)@ICLR 2024.
## What is OS-Copilot
OS-Copilot is an open-source library to build generalist agents capable of automatically interfacing with comprehensive elements in an operating system (OS), including the web, code terminals, files, multimedia, and various third-party applications.
## ⚡️ Quickstart
1. **Clone the GitHub Repository:**
```
git clone https://github.com/OS-Copilot/OS-Copilot.git
```
2. **Set Up Python Environment and Install Dependencies:**
```
conda create -n oscopilot_env python=3.10 -y
conda activate oscopilot_env
cd OS-Copilot
pip install -e .
```
4. **Set OpenAI API Key:** Configure your OpenAI API key in [.env](.env).
```
cp .env_template .env
```
5. **Now you are ready to have fun:**
```
python quick_start.py
```
\* **FRIDAY currently only supports single-round conversation**.
## 🛠️ Tutorial
| **Level** | **Tutorial** | **Description** |
|------------------|-------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------|
| **Beginner** | [Installation](https://os-copilot.readthedocs.io/en/latest/installation.html)| Explore three methods to install FRIDAY. |
| **Beginner** | [Getting Started](https://os-copilot.readthedocs.io/en/latest/quick_start.html)| The simplest demonstration of FRIDAY with a quick_start.py script. |
| **Intermediate** | [Adding Your Tools](https://os-copilot.readthedocs.io/en/latest/tutorials/add_tool.html)| Adding and removing tools to the FRIDAY. |
| **Intermediate** | [Deploying API Services](https://os-copilot.readthedocs.io/en/latest/tutorials/deploy_api_service.html)| Demonstrate the deployment of API services for FRIDAY. |
| **Intermediate** | [Example: Automating Excel Tasks](https://os-copilot.readthedocs.io/en/latest/tutorials/example_excel.html)| Automating Excel control using FRIDAY. |
| **Intermediate** | [Enhancing FRIDAY with Self-Learning for Excel Task Automation](https://os-copilot.readthedocs.io/en/latest/tutorials/self_learning.html) | Improved Excel control with self-directed learning. |
| **Advanced** | [Designing New API Tools](https://os-copilot.readthedocs.io/en/latest/tutorials/design_new_api_tool.html)| Guides on deploying custom API tools for FRIDAY to extend its functionalities. |
## 🏫 Community
Join our community to connect with other enthusiasts, researchers and developers:
- **[Discord](https://discord.com/invite/rXS2XbgfaD)**: Join our Discord server for real-time discussions and support.
- **[Twitter](https://twitter.com/oscopilot)**: Follow our Twitter to get latest new or tag us to share your demos!
## 👨💻 Contributing
**Visit [the roadmap](./docs/roadmap.md) to preview what the community is working on and become a contributor!**
## 🛡 Disclaimer
OS-Copilot is provided "as is" without warranty of any kind. Users assume full responsibility for any risks associated with its use, including **potential data loss** or **changes to system settings**. The developers of OS-Copilot are not liable for any damages or losses resulting from its use. Users must ensure their actions comply with applicable laws and regulations.
## 🔎 Citation
```
@misc{wu2024oscopilot,
title={OS-Copilot: Towards Generalist Computer Agents with Self-Improvement},
author={Zhiyong Wu and Chengcheng Han and Zichen Ding and Zhenmin Weng and Zhoumianze Liu and Shunyu Yao and Tao Yu and Lingpeng Kong},
year={2024},
eprint={2402.07456},
archivePrefix={arXiv},
primaryClass={cs.AI}
}
```
## 📬 Contact
If you have any inquiries, suggestions, or wish to contact us for any reason, we warmly invite you to email us at wuzhiyong@pjlab.org.cn.