PR fixes

Author: PatrickFarley

articles/ai-services/content-safety/includes/quickstarts/rest-quickstart-custom-categories.md

@@ -12,7 +12,7 @@ ms.author: pafarley
 ## Prerequisites
 
 * An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services/)
-* Once you have your Azure subscription, <a href="https://aka.ms/acs-create"  title="Create a Content Safety resource"  target="_blank">create a Content Safety resource</a> in the Azure portal to get your key and endpoint. Enter a unique name for your resource, select your subscription, and select a resource group, [supported region](./overview.md#region-availability), and supported pricing tier. Then select **Create**.
+* Once you have your Azure subscription, <a href="https://aka.ms/acs-create"  title="Create a Content Safety resource"  target="_blank">create a Content Safety resource</a> in the Azure portal to get your key and endpoint. Enter a unique name for your resource, select your subscription, and select a resource group, [supported region](../overview.md#region-availability), and supported pricing tier. Then select **Create**.
    * The resource takes a few minutes to deploy. After it finishes, Select **go to resource**. In the left pane, under **Resource Management**, select **Subscription Key and Endpoint**. Copy the endpoint and either of the key values to a temporary location for later use.
 * Also [create an Azure blob storage container](https://ms.portal.azure.com/#create/Microsoft.StorageAccount-ARM) where you'll keep your training annotation file.
 * One of the following installed:
@@ -25,7 +25,7 @@ ms.author: pafarley
 To train a custom category, you need example text data that represents the category you want to detect. In this guide, you can use sample data. The provided annotation file contains text prompts about survival advice in camping/wilderness situations. The trained model will learn to detect this type of content in new text data.
 
 > [!TIP]
-> For tips on creating your own data set, see the [How-to guide](./how-to/custom-categories.md#prepare-your-training-data).
+> For tips on creating your own data set, see the [How-to guide](../how-to/custom-categories.md#prepare-your-training-data).
 
 1. Download the [sample text data file](https://github.com/Azure-Samples/cognitive-services-sample-data-files/blob/master/ContentSafety/survival-advice.jsonl) from the GitHub repository.
 1. Upload the _.jsonl_ file to your Azure Storage account blob container. Then copy the blob URL to a temporary location for later use.
@@ -36,7 +36,7 @@ For example, your blob URL cannot be split into two layers, such as example/exam
 >
 ### Grant storage access 
 
-[!INCLUDE [storage-account-access](./includes/storage-account-access.md)]
+[!INCLUDE [storage-account-access](../storage-account-access.md)]
 
 ## Create and train a custom category
 

articles/ai-services/content-safety/includes/quickstarts/rest-quickstart-groundedness.md

@@ -14,13 +14,13 @@ ms.author: pafarley
 ## Prerequisites
 
 * An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services/) 
-* Once you have your Azure subscription, <a href="https://aka.ms/acs-create"  title="Create a Content Safety resource"  target="_blank">create a Content Safety resource </a> in the Azure portal to get your key and endpoint. Enter a unique name for your resource, select your subscription, and select a resource group, [supported region](./overview.md#region-availability), and supported pricing tier. Then select **Create**.
+* Once you have your Azure subscription, <a href="https://aka.ms/acs-create"  title="Create a Content Safety resource"  target="_blank">create a Content Safety resource </a> in the Azure portal to get your key and endpoint. Enter a unique name for your resource, select your subscription, and select a resource group, [supported region](../overview.md#region-availability), and supported pricing tier. Then select **Create**.
 * The resource takes a few minutes to deploy. After it does, go to the new resource. In the left pane, under **Resource Management**, select **API Keys and Endpoints**. Copy one of the subscription key values and endpoint to a temporary location for later use.
 * (Optional) If you want to use the _reasoning_ feature, create an Azure OpenAI Service resource with a GPT model deployed.
 * [cURL](https://curl.haxx.se/) or [Python](https://www.python.org/downloads/) installed.
 
 ## Authentication
-For enhanced security, you need to use Managed Identity (MI) to manage access to your resources, for more details, please refer to [Security](./overview.md#security).
+For enhanced security, you need to use Managed Identity (MI) to manage access to your resources, for more details, please refer to [Security](../overview.md#security).
 
 ## Check groundedness without reasoning
 
@@ -130,7 +130,7 @@ The parameters in the request body are defined in this table:
 | **qna**       | (Optional) Holds QnA data when the task type is `QnA`.  | String  |
 | - `query`       | (Optional) This represents the question in a QnA task. Character limit: 7,500. | String  |
 | **text**   | (Required) The LLM output text to be checked. Character limit: 7,500. |  String  |
-| **groundingSources**  | (Required) Uses an array of grounding sources to validate AI-generated text. See [Input requirements](./overview.md#input-requirements) for limits. | String array    |
+| **groundingSources**  | (Required) Uses an array of grounding sources to validate AI-generated text. See [Input requirements](../overview.md#input-requirements) for limits. | String array    |
 | **reasoning**  | (Optional) Specifies whether to use the reasoning feature. The default value is `false`. If `true`, you need to bring your own Azure OpenAI GPT4o (0513, 0806 version) to provide an explanation. Be careful: using reasoning increases the processing time.| Boolean   |
 
 ### Interpret the API response
@@ -287,7 +287,7 @@ The parameters in the request body are defined in this table:
 | **qna**       | (Optional) Holds QnA data when the task type is `QnA`.  | String  |
 | - `query`       | (Optional) This represents the question in a QnA task. Character limit: 7,500. | String  |
 | **text**   | (Required) The LLM output text to be checked. Character limit: 7,500. |  String  |
-| **groundingSources**  | (Required) Uses an array of grounding sources to validate AI-generated text. See [Input requirements](./overview.md#input-requirements) for limits, | String array    |
+| **groundingSources**  | (Required) Uses an array of grounding sources to validate AI-generated text. See [Input requirements](../overview.md#input-requirements) for limits, | String array    |
 | **reasoning**  | (Optional) Set to `true`, the service uses Azure OpenAI resources to provide an explanation. Be careful: using reasoning increases the processing time and incurs extra fees.| Boolean   |
 | **llmResource**  | (Required) If you want to use your own Azure OpenAI GPT4o (0513, 0806 version) resource to enable reasoning, add this field and include the subfields for the resources used. | String   |
 | - `resourceType `| Specifies the type of resource being used. Currently it only allows `AzureOpenAI`. We only support Azure OpenAI GPT4o (0513, 0806 version)  resources and do not support other GPT types. | Enum|
@@ -441,7 +441,7 @@ The parameters in the request body are defined in this table:
 | **qna**       | (Optional) Holds QnA data when the task type is `QnA`.  | String  |
 | - `query`       | (Optional) This represents the question in a QnA task. Character limit: 7,500. | String  |
 | **text**   | (Required) The LLM output text to be checked. Character limit: 7,500. |  String  |
-| **groundingSources**  | (Required) Uses an array of grounding sources to validate AI-generated text. See [Input requirements](./overview.md#input-requirements) for limits. | String Array    |
+| **groundingSources**  | (Required) Uses an array of grounding sources to validate AI-generated text. See [Input requirements](../overview.md#input-requirements) for limits. | String Array    |
 | **correction**  | (Optional) Set to `true`, the service uses Azure OpenAI resources to provide the corrected text, ensuring consistency with the grounding sources. Be careful: using correction increases the processing time and incurs extra fees.| Boolean   |
 | **llmResource**  | (Required) If you want to use your own Azure OpenAI GPT4o (0513, 0806 version) resource to enable reasoning, add this field and include the subfields for the resources used. | String   |
 | - `resourceType `| Specifies the type of resource being used. Currently it only allows `AzureOpenAI`. We only support Azure OpenAI GPT4o (0513, 0806 version) resources and do not support other GPT types. | Enum|

articles/ai-services/content-safety/includes/quickstarts/rest-quickstart-protected-material-code.md

@@ -25,7 +25,7 @@ The following section walks through a sample request with cURL. Paste the comman
 1. Replace `<your_subscription_key>` with one of the keys that come with your resource.
 1. Optionally, replace the `"code"` field in the body with your own Code you'd like to analyze.
     > [!TIP]
-    > See [Input requirements](./overview.md#input-requirements) for maximum Code length limitations. Protected material detection is meant to be run on LLM completions, not user prompts.
+    > See [Input requirements](../overview.md#input-requirements) for maximum Code length limitations. Protected material detection is meant to be run on LLM completions, not user prompts.
 
 ```shell
 curl --location --request POST '<endpoint>/contentsafety/text:detectProtectedMaterialForCode?api-version=2024-09-15-preview' \
@@ -95,11 +95,6 @@ The JSON fields in the output are defined here:
 
 If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
 
-- [Azure portal](../multi-service-resource.md?pivots=azportal#clean-up-resources)
-- [Azure CLI](../multi-service-resource.md?pivots=azcli#clean-up-resources)
+- [Azure portal](../../multi-service-resource.md?pivots=azportal#clean-up-resources)
+- [Azure CLI](../../multi-service-resource.md?pivots=azcli#clean-up-resources)
 
-
-## Related content
-
-* [Protected material detection concepts](./concepts/protected-material.md)
-* Configure filters for each category and test on datasets using [Content Safety Studio](studio-quickstart.md), export the code and deploy.

articles/ai-services/content-safety/includes/quickstarts/rest-quickstart-protected-material-text.md

@@ -25,7 +25,7 @@ The following section walks through a sample request with cURL. Paste the comman
 1. Replace `<your_subscription_key>` with one of the keys that come with your resource.
 1. Optionally, replace the `"text"` field in the body with your own text you'd like to analyze.
     > [!TIP]
-    > See [Input requirements](./overview.md#input-requirements) for maximum text length limitations. Protected material detection is meant to be run on LLM completions, not user prompts.
+    > See [Input requirements](../overview.md#input-requirements) for maximum text length limitations. Protected material detection is meant to be run on LLM completions, not user prompts.
 
 ```shell
 curl --location --request POST '<endpoint>/contentsafety/text:detectProtectedMaterial?api-version=2024-09-01' \
@@ -79,5 +79,5 @@ The JSON fields in the output are defined here:
 
 If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
 
-- [Azure portal](../multi-service-resource.md?pivots=azportal#clean-up-resources)
-- [Azure CLI](../multi-service-resource.md?pivots=azcli#clean-up-resources)
+- [Azure portal](../../multi-service-resource.md?pivots=azportal#clean-up-resources)
+- [Azure CLI](../../multi-service-resource.md?pivots=azcli#clean-up-resources)

zone-pivots/zone-pivot-groups.yml

@@ -79,7 +79,7 @@ groups:
     title: Python
   - id: programming-language-rest
     title: REST
-- id: programming-languages-content-safety-rest-portal
+- id: programming-languages-content-safety-foundry-rest
 # Owner: pafarley
   title: Programming languages
   prompt: Choose a platform