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Merge pull request #10 from OSLA-project/6-introduction
6 introduction
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# Welcome to MkDocs
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<figure markdown="span">
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![LARA logo](assets/LARA_logo.svg)
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</figure>
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Things to explain:
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# What is the LARAsuite?
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The LARAsuite is a freely and openly available collection of applications, libraries, databases and tools to plan, manage,
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create, monitor and evaluate (automated) processes in the laboratory. It has been developed by Mark Dörr and Stefan Maak
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from the [LARA group](https://lara.uni-greifswald.de/team/) at the University of Greifswald.
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- What is the LARA suite
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- adaptation template
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- what are processes
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- what are workers
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- Things to reuse, things to implement
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The vision is to cover all steps of laboratory work in a uniform framework with standardized communication protocols and data formats (like SiLA2, AnIML).
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## Pythonlab
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PythonLab is a Python framework for defining, parsing, and managing laboratory automation workflows. It allows you to write laboratory processes in Python syntax and converts them into executable workflow graphs.
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## The LARA workflow
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LARA tries to cover all aspects of a common laboratory workflow, starting from the planning of the experiments until the final presentation of the results.
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## The LARASuite architecture
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The LARAsuite is modular and consists of different components that can be used independently or together to create a complete laboratory automation solution.
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## Workers
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Worker_adaptation also needs to be custom.
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Worker calls steps through the wrappers, and returns the Observable object to orchestrator.
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<figure markdown="span">
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![LARASuite architecture](assets/architecture.png){ width="100%" }
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<figcaption>Architecture of LARASuite</figcaption>
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</figure>
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The most important components are the following:
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## Wrappers
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Wrappers implement calls to actual sila servers. In worker the devices are still just conceptual.
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### PythonLab
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The PythonLab package is a framework to define laboratory processes in python syntax. It converts the process
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definitions into workflow graphs that can be used by the orchestrator and scheduler.
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## Sila servers
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Sila servers have 2 types of commands, one type is observable, other isn’t. If sila command isn’t observable, you have to fake the observable in the wrapper
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### Orchestrator
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The orchestrator is the component that executes the workflow graphs created by PythonLab. It manages the execution of the processes,
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allocates resources, and communicates with the devices through the wrappers.
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## Config file
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Describes the capacity of the devices in your lab. This information is read by both the orchestrator and scheduler.
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### Scheduler
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The scheduler is responsible for optimizing the execution of the workflows. It takes into account the availability of resources,
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the dependencies between tasks, and the overall goals of the laboratory automation.
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### Platform status database
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The platform status database keeps track of the status of all devices, labware, and substances in the laboratory.
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It provides real-time information to the orchestrator and scheduler. It also provides a UI to set the initial status of the lab.
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## Disclaimer
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This documentation has been written with the help of AI.

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- attr_list
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theme:
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name: material
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logo: assets/LARA_logo.svg
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features:
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