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https://github.com/deepmodeling/Uni-Lab-OS
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问题： - 日志中 submit_auto_export_excel 收到 resource=[]（工作流本身不传成品电池资源， 电池由人工搬运），原代码 n = len(resource) = 0 → 整个循环跳过 → "共 0 颗电池，成功下发 0 颗"。 - neware_driver.start_test 原来不接收 filetype kwarg，导致 TypeError 阻塞下发。 修复： 1. submit_auto_export_excel 改为由 mount_resource 驱动循环长度： - 新签名以 mount_resource 为主，resource/pole_weight/coin_cell_code 均可选 - 新增 coin_cell_code 入参，coin_id 优先级 coin_cell_code > resource.name > fallback - n==0 时提前返回并给出明确错误信息 2. manual_confirm 的返回值与 YAML handles/output 新增 coin_cell_code （从已解包的 assembly_data 直接取） 3. submit_auto_export_excel YAML goal/schema/goal_default/handles.input 新增 coin_cell_code；required 中移除 resource（不再强制） 4. neware_driver.build_start_command / start_test 增加 filetype:int=1 参数， 动态嵌入 XML backup 配置，消除 TypeError Made-with: Cursor
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