Merge branch 'main' into GSK-2617

Author: kevinmessiaen

README.md

@@ -1,6 +1,6 @@
 <p align="center">
-  <img alt="giskardlogo" src="readme/giskard_logo.png#gh-light-mode-only">
-  <img alt="giskardlogo" src="readme/giskard_logo_green.png#gh-dark-mode-only">
+  <img alt="giskardlogo" src="https://raw.githubusercontent.com/giskard-ai/giskard/main/readme/giskard_logo.png#gh-light-mode-only">
+  <img alt="giskardlogo" src="https://raw.githubusercontent.com/giskard-ai/giskard/main/readme/giskard_logo_green.png#gh-dark-mode-only">
 </p>
 <h1 align="center" weight='300' >The testing framework dedicated to ML models, from tabular to LLMs</h1>
 <h3 align="center" weight='300' >Scan AI models to detect risks of biases, performance issues and errors. In 4 lines of code. </h3>
@@ -36,28 +36,28 @@ We officially support Python 3.9, 3.10 and 3.11.
 ______________________________________________________________________
 
 <p align="center">
-  <img src="readme/architechture_giskard.png" alt="Giskard Architechture" width="800">
+  <img src="https://raw.githubusercontent.com/giskard-ai/giskard/main/readme/architechture_giskard.png" alt="Giskard Architechture" width="800">
 </p>
 
 Giskard is a Python library that automatically **detects vulnerabilities** in AI models, from tabular models to LLM, including performance biases, data leakage, spurious correlation, hallucination, toxicity, security issues and many more.
 
 It's a powerful tool that helps data scientists **save time and effort** drilling down on model issues, and produce more **reliable and trustworthy models**.
 
 <p align="center">
-  <img src="readme/scan_example.gif" alt="Scan Example" width="800">
+  <img src="https://raw.githubusercontent.com/giskard-ai/giskard/main/readme/scan_example.gif" alt="Scan Example" width="800">
 </p>
 
 Instantaneously generate test suites for your models ⤵️
 
 <p align="center">
-  <img src="readme/suite_example.png" alt="Test Suite Example" width="800">
+  <img src="https://raw.githubusercontent.com/giskard-ai/giskard/main/readme/suite_example.png" alt="Test Suite Example" width="800">
 </p>
 
 
 Giskard works with any model, in any environment and integrates seamlessly with your favorite tools ⤵️ <br/>
 
 <p align="center">
-  <img width='600' src="readme/tools.png">
+  <img width='600' src="https://raw.githubusercontent.com/giskard-ai/giskard/main/readme/tools.png">
 </p>
 <br/>
 
@@ -143,7 +143,7 @@ The Giskard hub is Giskard's premium offering. It provides a number of additiona
 If you are interested in learning more about Giskard's premium offering, please [contact us](https://www.giskard.ai/contact).
 
 <p align="center">
-  <img src="readme/catalog_example.png" alt="Scan Example" width="700px">
+  <img src="https://raw.githubusercontent.com/giskard-ai/giskard/main/readme/catalog_example.png" alt="Scan Example" width="700px">
 </p>
 
 ## 1. Start the Giskard hub

docs/giskard_hub/write_and_debug_tests/index.md

@@ -34,7 +34,7 @@ To add tests from the catalog, click on "add test" in your test suite tab. This
 catalog showing all Giskard tests. You then have the possibility to run your test before adding it to your suite. 
 
 > ⚠️ Warning
-> * If you add a test **without** specifying the input of your test, you'll be asked to define the input at **suite execution time**. This input will become a *suite input*. Models are a great suite input to [compare different model](../compare_models/index.md) with the same test suite.
+> * If you add a test **without** specifying the input of your test, you'll be asked to define the input at **suite execution time**. This input will become a *suite input*. Models are a great suite input to [compare different models](../compare_models/index.md) with the same test suite.
 > * If you add a test by **specifying the input** of your test, you won't be asked to define it at suite 
 > execution time. This input becomes a *fixed value* of your suite. Data slices or thresholds are 
 > great fixed values because they are inherent to your suite.

docs/integrations/pytest/index.md

@@ -9,9 +9,9 @@
 ```
 
 
-It is possible to execute Giskard test via pytest with very minimal code. Using pytest to execute tests can facilitate the integration with CI/CD scripts and leverage builtin functionalities like test report or advanced markings (xfail, skip).
+It is possible to execute Giskard tests via pytest with very minimal code. Using pytest to execute tests can facilitate the integration with CI/CD scripts and leverage builtin functionalities like test report or advanced markings (xfail, skip).
 
-Once define in a script, the execution of the tests can be triggred using the pytest command:
+Once defined in a script, the execution of the tests can be triggered using the pytest command:
 
 ```console
 $ pytest test_ml_model.py

docs/open_source/scan/scan_llm/index.md

@@ -250,7 +250,7 @@ Jump to the [test customization](https://docs.giskard.ai/en/latest/open_source/c
 
 ### 2. Upload your test suite to the Giskard Hub to:
 * Compare the quality of different models and prompts to decide which one to promote
-* Create more tests relevant to your use case, combining input prompts that make your model fail and custome evaluation criteria
+* Create more tests relevant to your use case, combining input prompts that make your model fail and custom evaluation criteria
 * Share results, and collaborate with your team to integrate business feedback
 
 To upload your test suite, you must have created a project on Giskard Hub and instantiated a Giskard Python client. If you haven't done this yet, follow the first steps of [upload your object](https://docs.giskard.ai/en/latest/giskard_hub/upload/index.html#upload-your-object) guide.