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9c5ecda7cc
Refactored the Bioyond workstation classes to improve parameter handling and workflow management. Updated experiment.py to use BioyondReactionStation with deck and material mappings, and enhanced workflow step parameter mapping and execution logic. Adjusted JSON experiment configs, improved workflow sequence handling, and added UUID assignment to PLR materials. Removed unused station_config and material cache logic, and added detailed docstrings and debug output for workflow methods.
Uni-Lab-OS
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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.
🏆 Competition
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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
Uni-Lab-OS recommends using mamba for environment management. Choose the appropriate environment file for your operating system:
# Create new environment
mamba create -n unilab uni-lab::unilabos -c robostack-staging -c conda-forge
Install Dev Uni-Lab-OS
# Clone the repository
git clone https://github.com/dptech-corp/Uni-Lab-OS.git
cd Uni-Lab-OS
# Install Uni-Lab-OS
pip install .
- Start Uni-Lab System:
Please refer to Documentation - Boot Examples
Message Format
Uni-Lab-OS uses pre-built unilabos_msgs for system communication. You can find the built versions on the GitHub Releases page.
License
This project is licensed under GPL-3.0 - see the LICENSE file for details.
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Contact Us
- GitHub Issues: https://github.com/dptech-corp/Uni-Lab-OS/issues