disable content filtering

Author: laujan

articles/ai-services/content-understanding/overview.md

@@ -78,7 +78,7 @@ See [Quickstart](quickstart/use-ai-foundry.md) for more examples.
 
 ### Modified Content Filtering
 
-Azure AI Content Understanding now supports disabling content filtering for approved customers. The subscription IDs with approved modified content filtering impacts the Azure AI Content Understanding output. By default, Content Understanding employs a content filtering system that identifies specific risk categories for potentially harmful content in both submitted prompts and generated outputs. If content is flagged with a high severity level, indicating a significant potential for harm, the output is blocked. For more information on risk categories, *see* [Content filtering: risk categories](../openai/concepts/content-filter.md#risk-categories).
+Azure AI Content Understanding now supports modifying the content filtering system for approved customers. The subscription IDs with approved modified content filtering impacts the Azure AI Content Understanding output. By default, Content Understanding employs a content filtering system that identifies specific risk categories for potentially harmful content in both submitted prompts and generated outputs. By modifying the content filtering setting, the system will annotate rather than block potentially harmful output allowing you to decide how potentially harmful content is handled. For more information on content filter types, *see* [Content filtering: filter types](../openai/concepts/content-filter.md#content-filter-types).
 
 > [!IMPORTANT]
 >

articles/ai-services/content-understanding/quickstart/use-rest-api.md

@@ -83,37 +83,6 @@ First, create a JSON file named `request_body.json` with the following content:
 }
 ```
 
-##### Content filtering
-
-* Azure AI Content Understanding allows approved customers to disable content filtering.
-
-* To request modified content filtering, complete the following form: [Azure OpenAI Limited Access Review: Modified Content Filters](https://ncv.microsoft.com/uEfCgnITdR).
-
-* Once approved, create or update your `request_body.json` file to include the `"disableContentFiltering": true` property. Here is an example:
-
-   ```json
-   {
-     "description": "Sample invoice analyzer",
-     "scenario": "document",
-     "config": {
-
-       "disableContentFiltering": true,
-
-       "enableFace": true,
-       "returnDetails": true,
-       },
-       "fieldSchema": {
-
-      <insert your schema here>
-
-       }
-   }
-
-   ```
-
-For more information, *see* [**Content Filtering**](../../openai/concepts/content-filter.md).
-
-
 # [Image](#tab/image)
 
 To create a custom analyzer, you need to define a field schema that describes the structured data you want to extract. In the following example, we define a schema for identifying detects in images of metal plates.
@@ -138,35 +107,6 @@ First, create a JSON file named `request_body.json` with the following content:
 }
 ```
 
-##### Content filtering
-
-* Azure AI Content Understanding allows approved customers to disable content filtering.
-
-* To request modified content filtering, complete the following form: [Azure OpenAI Limited Access Review: Modified Content Filters](https://ncv.microsoft.com/uEfCgnITdR).
-
-* Once approved, create or update your `request_body.json` file to include the `"disableContentFiltering": true` property. Here is an example:
-
-   ```json
-   {
-     "description": "Sample chart analyzer",
-     "scenario": "image",
-     "config": {
-
-       "disableContentFiltering": true,
-
-       "returnDetails": true,
-       },
-       "fieldSchema": { 
-
-       <insert your schema here>
-
-       }
-   }
-
-   ```
-
-For more information, *see* [**Content Filtering**](../../openai/concepts/content-filter.md).
-
 # [Audio](#tab/audio)
 
 To create a custom analyzer, you need to define a field schema that describes the structured data you want to extract. In the following example, we define a schema for extracting basic information from call transcripts.
@@ -207,27 +147,83 @@ First, create a JSON file named `request_body.json` with the following content:
 }
 ```
 
-##### Content filtering
+# [Video](#tab/video)
+
+To create a custom analyzer, you need to define a field schema that describes the structured data you want to extract. In the following example, we define a schema for extracting basic information from marketing videos.
+
+First, create a JSON file named `request_body.json` with the following content:
+```json
+{
+  "description": "Sample marketing video analyzer",
+  "scenario": "videoShot",
+  "fieldSchema": {
+    "fields": {
+      "Description": {
+        "type": "string",
+        "description": "Detailed summary of the video segment, focusing on product characteristics, lighting, and color palette."
+      },
+      "Sentiment": {
+        "type": "string",
+        "method": "classify",
+        "enum": [ "Positive", "Neutral", "Negative" ]
+      }
+    }
+  }
+}
+```
+
+---
 
-* Azure AI Content Understanding allows approved customers to disable content filtering.
+### Modified content filtering
 
-* To request modified content filtering, complete the following form: [Azure OpenAI Limited Access Review: Modified Content Filters](https://ncv.microsoft.com/uEfCgnITdR).
+* Approved Azure AI Content Understanding customers can modify the default content filtering system. Once modified, the output filters annotate content instead of blocking it providing enhanced control over content filtering in the Content Understanding output.
 
-* Once approved, create or update your `request_body.json` file to include the `"disableContentFiltering": true` property. Here is an example:
+* To request approval for modified content filtering, complete the following form: [Azure OpenAI Limited Access Review: Modified Content Filters](https://ncv.microsoft.com/uEfCgnITdR).
+
+* Once approved, create or update your `request_body.json` file to include the `"disableContentFiltering": true` property.
+
+# [Document](#tab/document)
+
+ Here's a document modality code sample using the`"disableContentFiltering": true` property:
 
    ```json
    {
-     "description": "Sample call transcript analyzer",
-     "scenario": "callCenter",
+     "description": "Sample invoice analyzer",
+     "scenario": "document",
      "config": {
 
        "disableContentFiltering": true,
 
+       "enableFace": true,
        "returnDetails": true,
-       "locales": ["en-US"]
        },
        "fieldSchema": {
 
+      <insert your schema here>
+
+       }
+   }
+
+   ```
+
+For more information, *see* [**Content Filtering**](../../openai/concepts/content-filter.md).
+
+# [Image](#tab/image)
+
+Here's an image modality code sample using the`"disableContentFiltering": true` property:
+
+   ```json
+   {
+     "description": "Sample chart analyzer",
+     "scenario": "image",
+     "config": {
+
+       "disableContentFiltering": true,
+
+       "returnDetails": true,
+       },
+       "fieldSchema": { 
+
        <insert your schema here>
 
        }
@@ -237,37 +233,36 @@ First, create a JSON file named `request_body.json` with the following content:
 
 For more information, *see* [**Content Filtering**](../../openai/concepts/content-filter.md).
 
-# [Video](#tab/video)
+# [Audio](#tab/audio)
 
-To create a custom analyzer, you need to define a field schema that describes the structured data you want to extract. In the following example, we define a schema for extracting basic information from marketing videos.
+Here's an audio modality code sample using the`"disableContentFiltering": true` property:
 
-First, create a JSON file named `request_body.json` with the following content:
-```json
-{
-  "description": "Sample marketing video analyzer",
-  "scenario": "videoShot",
-  "fieldSchema": {
-    "fields": {
-      "Description": {
-        "type": "string",
-        "description": "Detailed summary of the video segment, focusing on product characteristics, lighting, and color palette."
-      },
-      "Sentiment": {
-        "type": "string",
-        "method": "classify",
-        "enum": [ "Positive", "Neutral", "Negative" ]
-      }
-    }
-  }
-}
-```
-##### Content filtering
+   ```json
+   {
+     "description": "Sample call transcript analyzer",
+     "scenario": "callCenter",
+     "config": {
 
-* Azure AI Content Understanding allows approved customers to disable content filtering.
+       "disableContentFiltering": true,
+
+       "returnDetails": true,
+       "locales": ["en-US"]
+       },
+       "fieldSchema": {
 
-* To request modified content filtering, complete the following form: [Azure OpenAI Limited Access Review: Modified Content Filters](https://ncv.microsoft.com/uEfCgnITdR).
+       <insert your schema here>
 
-* Once approved, create or update your `request_body.json` file to include the `"disableContentFiltering": true` property. Here is an example:
+       }
+   }
+
+   ```
+
+For more information, *see* [**Content Filtering**](../../openai/concepts/content-filter.md).
+
+
+# [Video](#tab/video)
+
+ Here's a video modality code sample using the`"disableContentFiltering": true` property:
 
    ```json
    {
@@ -286,11 +281,11 @@ First, create a JSON file named `request_body.json` with the following content:
    }
 
    ```
-
 For more information, *see* [**Content Filtering**](../../openai/concepts/content-filter.md).
 
 ---
 
+
 Before running the following `cURL` commands, make the following changes to the HTTP request:
 
 1. Replace `{endpoint}` and `{key}` with the endpoint and key values from your Azure portal Azure AI Services instance.