Xuwznln 2a5ddd611d Upgrade to py 3.11.14; ROS2 Humble 0.7; unilabos 0.10.16
Workbench example, adjust log level, and ci check (#220)

* TestLatency Return Value Example & gitignore update

* Adjust log level & Add workbench virtual example & Add not action decorator & Add check_mode &

* Add CI Check

Fix/workstation yb revision (#217)

* Revert log change & update registry

* Revert opcua client & move electrolyte node

Workstation yb merge dev ready 260113 (#216)

* feat(bioyond): 添加计算实验设计功能,支持化合物配比和滴定比例参数

* feat(bioyond): 添加测量小瓶功能,支持基本参数配置

* feat(bioyond): 添加测量小瓶配置,支持新设备参数

* feat(bioyond): 更新仓库布局和尺寸,支持竖向排列的测量小瓶和试剂存放堆栈

* feat(bioyond): 优化任务创建流程,确保无论成功与否都清理任务队列以避免重复累积

* feat(bioyond): 添加设置反应器温度功能,支持温度范围和异常处理

* feat(bioyond): 调整反应器位置配置,统一坐标格式

* feat(bioyond): 添加调度器启动功能,支持任务队列执行并处理异常

* feat(bioyond): 优化调度器启动功能,添加异常处理并更新相关配置

* feat(opcua): 增强节点ID解析兼容性和数据类型处理

改进节点ID解析逻辑以支持多种格式,包括字符串和数字标识符
添加数据类型转换处理,确保写入值时类型匹配
优化错误提示信息,便于调试节点连接问题

* feat(registry): 新增后处理站的设备配置文件

添加后处理站的YAML配置文件,包含动作映射、状态类型和设备描述

* 添加调度器启动功能,合并物料参数配置,优化物料参数处理逻辑

* 添加从 Bioyond 系统自动同步工作流序列的功能,并更新相关配置

* fix:兼容 BioyondReactionStation 中 workflow_sequence 被重写为 property

* fix:同步工作流序列

* feat: remove commented workflow synchronization from `reaction_station.py`.

* 添加时间约束功能及相关配置

* fix:自动更新物料缓存功能,添加物料时更新缓存并在删除时移除缓存项

* fix:在添加物料时处理字符串和字典返回值,确保正确更新缓存

* fix:更新奔曜错误处理报送为物料变更报送,调整日志记录和响应消息

* feat:添加实验报告简化功能,去除冗余信息并保留关键信息

* feat: 添加任务状态事件发布功能,监控并报告任务运行、超时、完成和错误状态

* fix: 修复添加物料时数据格式错误

* Refactor bioyond_dispensing_station and reaction_station_bioyond YAML configurations

- Removed redundant action value mappings from bioyond_dispensing_station.
- Updated goal properties in bioyond_dispensing_station to use enums for target_stack and other parameters.
- Changed data types for end_point and start_point in reaction_station_bioyond to use string enums (Start, End).
- Simplified descriptions and updated measurement units from μL to mL where applicable.
- Removed unused commands from reaction_station_bioyond to streamline the configuration.

* fix:Change the material unit from μL to mL

* fix:refresh_material_cache

* feat: 动态获取工作流步骤ID,优化工作流配置

* feat: 添加清空服务端所有非核心工作流功能

* fix:修复Bottle类的序列化和反序列化方法

* feat:增强材料缓存更新逻辑,支持处理返回数据中的详细信息

* Add debug log

* feat(workstation): update bioyond config migration and coin cell material search logic

- Migrate bioyond_cell config to JSON structure and remove global variable dependencies
- Implement material search confirmation dialog auto-handling
- Add documentation: 20260113_物料搜寻确认弹窗自动处理功能.md and 20260113_配置迁移修改总结.md

* Refactor module paths for Bioyond devices in YAML configuration files

- Updated the module path for BioyondDispensingStation in bioyond_dispensing_station.yaml to reflect the new directory structure.
- Updated the module path for BioyondReactionStation and BioyondReactor in reaction_station_bioyond.yaml to align with the revised organization of the codebase.

* fix: WareHouse 的不可哈希类型错误,优化父节点去重逻辑

* refactor: Move config from module to instance initialization

* fix: 修正 reaction_station 目录名拼写错误

* feat: Integrate material search logic and cleanup deprecated files

- Update coin_cell_assembly.py with material search dialog handling
- Update YB_warehouses.py with latest warehouse configurations
- Remove outdated documentation and test data files

* Refactor: Use instance attributes for action names and workflow step IDs

* refactor: Split tipbox storage into left and right warehouses

* refactor: Merge tipbox storage left and right into single warehouse

---------

Co-authored-by: ZiWei <131428629+ZiWei09@users.noreply.github.com>
Co-authored-by: Andy6M <xieqiming1132@qq.com>

fix: WareHouse 的不可哈希类型错误,优化父节点去重逻辑

fix parent_uuid fetch when bind_parent_id == node_name

物料更新也是用父节点进行报送

Add None conversion for tube rack etc.

Add set_liquid example.

Add create_resource and test_resource example.

Add restart.
Temp allow action message.

Add no_update_feedback option.

Create session_id by edge.

bump version to 0.10.15

temp cancel update req
2026-01-27 15:21:55 +08:00
2026-01-07 20:54:20 +08:00
2025-04-17 15:19:47 +08:00
2025-11-15 03:15:44 +08:00
2025-04-17 14:19:48 +08:00
2026-01-07 20:46:23 +08:00

Uni-Lab Logo

Uni-Lab-OS

English | 中文

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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
  1. Start Uni-Lab System

Please refer to Documentation - Boot Examples

  1. Best Practice

See Best Practice Guide

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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