Add Getting Started admonitions (#648)

docs/guides/frameworks/tensorflow/integration_keras_tuner.md

@@ -3,6 +3,11 @@ title: Keras Tuner
 displayed_sidebar: mainSidebar
 ---
 
+:::tip
+If you are not already using ClearML, see [Getting Started](../getting_started/ds/ds_first_steps.md) for setup 
+instructions.
+:::
+
 Integrate ClearML into code that uses [Keras Tuner](https://www.tensorflow.org/tutorials/keras/keras_tuner). By 
 specifying `ClearMLTunerLogger` (see [kerastuner.py](https://github.com/allegroai/clearml/blob/master/clearml/external/kerastuner.py)) 
 as the Keras Tuner logger, ClearML automatically logs scalars and hyperparameter optimization.  

docs/integrations/click.md

@@ -2,6 +2,11 @@
 title: Click
 ---
 
+:::tip
+If you are not already using ClearML, see [Getting Started](../getting_started/ds/ds_first_steps.md) for setup 
+instructions.
+:::
+
 [`click`](https://click.palletsprojects.com) is a python package for creating command-line interfaces. ClearML integrates 
 seamlessly with `click` and automatically logs its command-line parameters. 
 

docs/integrations/hydra.md

@@ -2,6 +2,11 @@
 title: Hydra
 ---
 
+:::tip
+If you are not already using ClearML, see [Getting Started](../getting_started/ds/ds_first_steps.md) for setup 
+instructions.
+:::
+
 
 [Hydra](https://github.com/facebookresearch/hydra) is a Python framework for managing experiment parameters. ClearML integrates seamlessly
 with Hydra and automatically logs the `OmegaConf` which holds all the configuration files, as well as 

docs/integrations/ignite.md

@@ -2,6 +2,11 @@
 title: PyTorch Ignite
 ---
 
+:::tip
+If you are not already using ClearML, see [Getting Started](../getting_started/ds/ds_first_steps.md) for setup 
+instructions.
+:::
+
 [PyTorch Ignite](https://pytorch.org/ignite/index.html) is a library for training and evaluating neural networks in 
 PyTorch. You can integrate ClearML into your code using Ignite’s built-in loggers: [TensorboardLogger](#tensorboardlogger) 
 and [ClearMLLogger](#clearmllogger). 

docs/integrations/openmmv.md

@@ -2,6 +2,11 @@
 title: OpenMMLab
 ---
 
+:::tip
+If you are not already using ClearML, see [Getting Started](../getting_started/ds/ds_first_steps.md) for setup 
+instructions.
+:::
+
 [OpenMMLab](https://github.com/open-mmlab) is a computer vision framework. You can integrate ClearML into your 
 code using the `mmcv` package's [`ClearMLLoggerHook`](https://mmcv.readthedocs.io/en/master/_modules/mmcv/runner/hooks/logger/clearml.html)
 class. This class is used to create a ClearML Task and to automatically log metrics. 

docs/integrations/seaborn.md

@@ -2,6 +2,11 @@
 title: Seaborn
 ---
 
+:::tip
+If you are not already using ClearML, see [Getting Started](../getting_started/ds/ds_first_steps.md) for setup 
+instructions.
+:::
+
 [seaborn](https://seaborn.pydata.org/) is a Python library for data visualization. 
 ClearML automatically captures plots created using `seaborn`. All you have to do is add two
 lines of code to your script: