add docs badge

README.md

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 [![PyPI version](https://badge.fury.io/py/semantic-link-labs.svg)](https://badge.fury.io/py/semantic-link-labs)
 
+[![Read The Docs](https://readthedocs.org/projects/<project-slug>/badge/?version=0.4.1&style=flat)](https://readthedocs.org/projects/semantic-link-labs/)
+
 This is a python library intended to be used in [Microsoft Fabric notebooks](https://learn.microsoft.com/fabric/data-engineering/how-to-use-notebook). This library was originally intended to contain functions used for [migrating semantic models to Direct Lake mode](https://github.com/microsoft/semantic-link-labs?tab=readme-ov-file#direct-lake-migration-1). However, it quickly became apparent that functions within such a library could support many other useful activities in the realm of semantic models, reports, lakehouses and really anything Fabric-related. As such, this library contains a variety of functions ranging from running [Vertipaq Analyzer](https://github.com/microsoft/semantic-link-labs?tab=readme-ov-file#vertipaq_analyzer) or the [Best Practice Analyzer](https://github.com/microsoft/semantic-link-labs?tab=readme-ov-file#run_model_bpa) against a semantic model to seeing if any [lakehouse tables hit Direct Lake guardrails](https://github.com/microsoft/semantic-link-labs?tab=readme-ov-file#get_lakehouse_tables) or accessing the [Tabular Object Model](https://github.com/microsoft/semantic-link-labs/#tabular-object-model-tom) and more!
 
 Instructions for migrating import/DirectQuery semantic models to Direct Lake mode can be found [here](https://github.com/microsoft/semantic-link-labs?tab=readme-ov-file#direct-lake-migration-1).

docs/source/conf.py

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 project = 'semantic-link-labs'
 copyright = '2024, Microsoft and community'
 author = 'Microsoft and community'
-release = '0.4.0'
+release = '0.4.1'
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration