Merge pull request #36 from goeckslab/Release_v3.3.2

change the repo name in shed yml

tools/.shed.yml

@@ -1,8 +1,28 @@
 categories: 
   - Machine Learning
-description: Tools for machine learning with pycaret in a simple, powerful and robust way 
-name: galaxy-pycaret
+description: A powerful and robust low-code library for simplifying machine learning workflows with PyCaret.
+name: galaxy_pycaret
 owner: goeckslab
-long_description: Tools for machine learning with pycaret in a simple, powerful and robust way
+long_description: |
+  PyCaret is a low-code machine learning library that simplifies the process of building, training, and deploying machine learning models.
+  With its comprehensive suite of tools, PyCaret enables users to perform complex tasks such as data preprocessing,
+  model selection, hyperparameter tuning, and evaluation, all within a single, intuitive interface. 
+  It is designed to be powerful and robust, making it suitable for both beginners and advanced users. 
+  Whether you are exploring data for insights, building predictive models, or deploying them into production, 
+  PyCaret provides a streamlined workflow that saves time and reduces code complexity.
 remote_repository_url: https://github.com/goeckslab/Galaxy-Pycaret
-homepage_url: https://github.com/goeckslab/Galaxy-Pycaret
+homepage_url: https://github.com/goeckslab/Galaxy-Pycaret
+
+auto_tool_repositories:
+  name_template: "{{ tool_id }}"
+  description_template: "Wrapper for pycaret tool: {{ tool_name }}"
+suite:
+  name: suite_pycaret
+  description: A powerful and robust low-code library for simplifying machine learning workflows with PyCaret.
+  long_description: |
+    PyCaret is a low-code machine learning library that simplifies the process of building, training, and deploying machine learning models.
+    With its comprehensive suite of tools, PyCaret enables users to perform complex tasks such as data preprocessing,
+    model selection, hyperparameter tuning, and evaluation, all within a single, intuitive interface. 
+    It is designed to be powerful and robust, making it suitable for both beginners and advanced users. 
+    Whether you are exploring data for insights, building predictive models, or deploying them into production, 
+    PyCaret provides a streamlined workflow that saves time and reduces code complexity.