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Enable UTF-8 for later conda run commands so anaconda-client version output does not fail under the Windows code page. fix conda plugin timing in windows workflows Set CONDA_NO_PLUGINS only after mamba installs anaconda-client so setup-miniconda can initialize normally while later conda commands avoid the anaconda-auth plugin crash. fix conda plugin crash in windows workflows Disable conda plugins in build jobs so anaconda-auth from anaconda-client does not break conda info or conda run on Windows. fix windows mamba bat quoting in workflows Pass the mamba.bat command to cmd without nested escaped quotes so Git Bash does not produce an invalid program name. fix windows mamba install in conda workflows Use the Windows mamba.bat entrypoint from Git Bash so the setup-miniconda wrapper does not break after recent runner updates.
Uni-Lab-OS
English | 中文
Uni-Lab-OS is a platform for laboratory automation, designed to connect and control various experimental equipment, enabling automation and standardization of experimental workflows.
Key Features
- Multi-device integration management
- Automated experimental workflows
- Cloud connectivity capabilities
- Flexible configuration system
- Support for multiple experimental protocols
Documentation
Detailed documentation can be found at:
Quick Start
1. Setup Conda Environment
Uni-Lab-OS recommends using mamba for environment management. Choose the package that fits your needs:
| Package | Use Case | Contents |
|---|---|---|
unilabos |
Recommended for most users | Complete package, ready to use |
unilabos-env |
Developers (editable install) | Environment only, install unilabos via pip |
unilabos-full |
Simulation/Visualization | unilabos + ROS2 Desktop + Gazebo + MoveIt |
# Create new environment
mamba create -n unilab python=3.11.14
mamba activate unilab
# Option A: Standard installation (recommended for most users)
mamba install uni-lab::unilabos -c robostack-staging -c conda-forge
# Option B: For developers (editable mode development)
mamba install uni-lab::unilabos-env -c robostack-staging -c conda-forge
# Then install unilabos and dependencies:
git clone https://github.com/deepmodeling/Uni-Lab-OS.git && cd Uni-Lab-OS
pip install -e .
uv pip install -r unilabos/utils/requirements.txt
# Option C: Full installation (simulation/visualization)
mamba install uni-lab::unilabos-full -c robostack-staging -c conda-forge
When to use which?
- unilabos: Standard installation for production deployment and general usage (recommended)
- unilabos-env: For developers who need
pip install -e .editable mode, modify source code - unilabos-full: For simulation (Gazebo), visualization (rviz2), and Jupyter notebooks
2. Clone Repository (Optional, for developers)
# Clone the repository (only needed for development or examples)
git clone https://github.com/deepmodeling/Uni-Lab-OS.git
cd Uni-Lab-OS
- Start Uni-Lab System
Please refer to Documentation - Boot Examples
- Best Practice
Message Format
Uni-Lab-OS uses pre-built unilabos_msgs for system communication. You can find the built versions on the GitHub Releases page.
Citation
If you use Uni-Lab-OS in academic research, please cite:
@article{gao2025unilabos,
title = {UniLabOS: An AI-Native Operating System for Autonomous Laboratories},
doi = {10.48550/arXiv.2512.21766},
publisher = {arXiv},
author = {Gao, Jing and Chang, Junhan and Que, Haohui and Xiong, Yanfei and
Zhang, Shixiang and Qi, Xianwei and Liu, Zhen and Wang, Jun-Jie and
Ding, Qianjun and Li, Xinyu and Pan, Ziwei and Xie, Qiming and
Yan, Zhuang and Yan, Junchi and Zhang, Linfeng},
year = {2025}
}
License
This project uses a dual licensing structure:
- Main Framework: GPL-3.0 - see LICENSE
- Device Drivers (
unilabos/devices/): DP Technology Proprietary License
See NOTICE for complete licensing details.
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Contact Us
- GitHub Issues: https://github.com/deepmodeling/Uni-Lab-OS/issues