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+
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-# Welcome to MkDocs
+
+
+
-Things to explain:
+# What is the LARAsuite?
+The LARAsuite is a freely and openly available collection of applications, libraries, databases and tools to plan, manage,
+create, monitor and evaluate (automated) processes in the laboratory. It has been developed by Mark Dörr and Stefan Maak
+from the [LARA group](https://lara.uni-greifswald.de/team/) at the University of Greifswald.
-- What is the LARA suite
-- adaptation template
-- what are processes
-- what are workers
-- Things to reuse, things to implement
+The vision is to cover all steps of laboratory work in a uniform framework with standardized communication protocols and data formats (like SiLA2, AnIML).
-## Pythonlab
-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.
+## The LARA workflow
+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.
+## The LARASuite architecture
+The LARAsuite is modular and consists of different components that can be used independently or together to create a complete laboratory automation solution.
-## Workers
-Worker_adaptation also needs to be custom.
-Worker calls steps through the wrappers, and returns the Observable object to orchestrator.
+
+ { width="100%" }
+ Architecture of LARASuite
+
+The most important components are the following:
-## Wrappers
-Wrappers implement calls to actual sila servers. In worker the devices are still just conceptual.
+### PythonLab
+The PythonLab package is a framework to define laboratory processes in python syntax. It converts the process
+definitions into workflow graphs that can be used by the orchestrator and scheduler.
-## Sila servers
-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
+### Orchestrator
+The orchestrator is the component that executes the workflow graphs created by PythonLab. It manages the execution of the processes,
+allocates resources, and communicates with the devices through the wrappers.
-## Config file
-Describes the capacity of the devices in your lab. This information is read by both the orchestrator and scheduler.
+### Scheduler
+The scheduler is responsible for optimizing the execution of the workflows. It takes into account the availability of resources,
+the dependencies between tasks, and the overall goals of the laboratory automation.
+
+### Platform status database
+The platform status database keeps track of the status of all devices, labware, and substances in the laboratory.
+It provides real-time information to the orchestrator and scheduler. It also provides a UI to set the initial status of the lab.
## Disclaimer
This documentation has been written with the help of AI.
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diff --git a/mkdocs.yml b/mkdocs.yml
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+++ b/mkdocs.yml
@@ -13,8 +13,13 @@ markdown_extensions:
class: mermaid
format: !!python/name:pymdownx.superfences.fence_code_format
+ - attr_list
+ - md_in_html
+ - pymdownx.blocks.caption
+
theme:
name: material
+ logo: assets/LARA_logo.svg
features:
- content.code.copy