Merge branch 'main' of https://github.com/MicrosoftDocs/azure-docs-pr into wi270830-upcoming-deprecation

Author: ElazarK

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

@@ -38,7 +38,7 @@ curl --location --request POST '<endpoint>/contentsafety/text:analyze?api-versio
   "text": "I hate you",
   "categories": [
    "Hate","Sexual","SelfHarm","Violence"
-  ]
+  ],
    "blocklistNames": [
       "string"
     ],

articles/ai-services/content-safety/studio-quickstart.md

@@ -23,6 +23,7 @@ In this quickstart, get started with the Azure AI Content Safety service using C
 
 * An active Azure account. If you don't have one, you can [create one for free](https://azure.microsoft.com/free/cognitive-services/).
 * A [Content Safety](https://aka.ms/acs-create) Azure resource.
+* The `Cognitive Services User` role assigned to the Content Safety resource in the desired Azure subscription.
 * Sign in to [Content Safety Studio](https://contentsafety.cognitive.azure.com) with your Azure subscription and Content Safety resource. 
 
 

articles/ai-services/openai/concepts/content-filter.md

@@ -6,7 +6,7 @@ author: mrbullwinkle
 ms.author: mbullwin
 ms.service: azure-ai-openai
 ms.topic: conceptual 
-ms.date: 11/06/2023
+ms.date: 06/25/2023
 ms.custom: template-concept, devx-track-python
 manager: nitinme
 ---
@@ -70,10 +70,14 @@ The default content filtering configuration for the GPT model series is set to f
 
 <sup>1</sup> For Azure OpenAI models, only customers who have been approved for modified content filtering have full content filtering control and can turn content filters off. Apply for modified content filters via this form: [Azure OpenAI Limited Access Review: Modified Content Filters](https://ncv.microsoft.com/uEfCgnITdR) For Azure Government customers, please apply for modified content filters via this form: [Azure Government - Request Modified Content Filtering for Azure OpenAI Service](https://aka.ms/AOAIGovModifyContentFilter).
 
-This preview feature is available for the following Azure OpenAI models:
-* GPT model series (text) 
-* GPT-4 Turbo Vision 2024-04-09 (multi-modal text/image)
-* DALL-E 2 and 3 (image)
+Configurable content filters for inputs (prompts) and outputs (completions) are available for the following Azure OpenAI models:
+
+* GPT model series
+* GPT-4 Turbo Vision GA<sup>*</sup> (turbo-2024-04-09)
+* GPT-4o 
+* DALL-E 2 and 3
+
+<sup>*</sup>Only available for GPT-4 Turbo Vision GA, does not apply to GPT-4 Turbo Vision preview 
 
 Content filtering configurations are created within a Resource in Azure AI Studio, and can be associated with Deployments. [Learn more about configurability here](../how-to/content-filters.md).  
 
@@ -847,7 +851,7 @@ To enable Asynchronous Filter in Azure OpenAI Studio, follow the [Content filter
 |Status |GA |Public Preview |
 | Eligibility |All customers |Customers approved for modified content filtering |
 | How to enable | Enabled by default, no action needed |Customers approved for modified content filtering can configure it directly in Azure OpenAI Studio (as part of a content filtering configuration, applied at the deployment level) |
-|Modality and availability |Text; all GPT models |Text; all GPT models except gpt-4-vision |
+|Modality and availability |Text; all GPT models |Text; all GPT models |
 |Streaming experience |Content is buffered and returned in chunks |Zero latency (no buffering, filters run asynchronously) |
 |Content filtering signal |Immediate filtering signal |Delayed filtering signal (in up to ~1,000-character increments) |
 |Content filtering configurations |Supports default and any customer-defined filter setting (including optional models) |Supports default and any customer-defined filter setting (including optional models) |

articles/ai-services/openai/concepts/gpt-with-vision.md

@@ -81,7 +81,7 @@ For a typical use case, take an image with both visible objects and text and a 1
 | Item        | Detail        |  Cost   |
 |-----------------|-----------------|--------------|
 | Text prompt input | 100 text tokens | $0.001 |
-| Example image input (see [Image tokens](/ai-services/openai/overview#image-tokens-gpt-4-turbo-with-vision)) | 170 + 85 image tokens | $0.00255 |
+| Example image input (see [Image tokens](/azure/ai-services/openai/overview#image-tokens-gpt-4-turbo-with-vision)) | 170 + 85 image tokens | $0.00255 |
 | Enhanced add-on features for OCR | $1.50 / 1000 transactions | $0.0015 |
 | Enhanced add-on features for Object Grounding | $1.50 / 1000 transactions | $0.0015 | 
 | Output Tokens      | 100 tokens (assumed)    | $0.003       |

articles/ai-services/openai/how-to/managed-identity.md

@@ -1,17 +1,17 @@
 ---
-title: How to configure Azure OpenAI Service with managed identities
+title: How to configure Azure OpenAI Service with Microsoft Entra ID authentication
 titleSuffix: Azure OpenAI
 description: Provides guidance on how to set managed identity with Microsoft Entra ID
 ms.service: azure-ai-openai
 ms.topic: how-to 
-ms.date: 04/03/2024
+ms.date: 06/25/2024
 author: mrbullwinkle
 ms.author: mbullwin
 recommendations: false
 ms.custom: devx-track-azurecli
 ---
 
-# How to configure Azure OpenAI Service with managed identities
+# How to configure Azure OpenAI Service with Microsoft Entra ID authentication
 
 More complex security scenarios require Azure role-based access control (Azure RBAC). This document covers how to authenticate to your OpenAI resource using Microsoft Entra ID.
 

articles/ai-services/openai/includes/chatgpt-java.md

@@ -110,7 +110,7 @@ dependencies {
         public static void main(String[] args) {
             String azureOpenaiKey = System.getenv("AZURE_OPENAI_API_KEY");;
             String endpoint = System.getenv("AZURE_OPENAI_ENDPOINT");;
-            String deploymentOrModelId = "gpt-35-turbo";
+            String deploymentOrModelId = "gpt-35-turbo"; //Change to match your deployment name
     
           OpenAIClient client = new OpenAIClientBuilder()
                 .endpoint(endpoint)

articles/ai-services/openai/includes/chatgpt-spring.md

@@ -17,7 +17,7 @@ ms.date: 11/27/2023
   Currently, access to this service is granted only by application. You can apply for access to Azure OpenAI Service by completing the form at [https://aka.ms/oai/access](https://aka.ms/oai/access?azure-portal=true).
 - The current version of the [Java Development Kit (JDK)](https://www.microsoft.com/openjdk)
 - The [Spring Boot CLI tool](https://docs.spring.io/spring-boot/docs/current/reference/html/getting-started.html#getting-started.installing.cli)
-- An Azure OpenAI Service resource with the `gpt-35-turbo` model deployed. For more information about model deployment, see the [resource deployment guide](../how-to/create-resource.md).
+- An Azure OpenAI Service resource with the `gpt-35-turbo` model deployed. For more information about model deployment, see the [resource deployment guide](../how-to/create-resource.md). This example assumes that your deployment name matches the model name `gpt-35-turbo`
 
 > [!div class="nextstepaction"]
 > [I ran into an issue with the prerequisites.](https://microsoft.qualtrics.com/jfe/form/SV_0Cl5zkG3CnDjq6O?PLanguage=SPRING&Pillar=AOAI&Product=Chatgpt&Page=quickstart&Section=Prerequisites)

articles/ai-services/openai/whats-new.md

@@ -98,7 +98,7 @@ For more information, see the [deployment types guide](https://aka.ms/aoai/docs/
 
 ### DALL-E and GPT-4 Turbo Vision GA configurable content filters
 
-Create custom content filters for your DALL-E 2 and 3 and GPT-4 Turbo with Vision GA (gpt-4-turbo-2024-04-09) deployments. [Content filtering](/azure/ai-services/openai/concepts/content-filter?tabs=warning%2Cpython-new#configurability-preview)
+Create custom content filters for your DALL-E 2 and 3, GPT-4 Turbo with Vision GA (gpt-4-turbo-2024-04-09) and GPT-4o deployments. [Content filtering](/azure/ai-services/openai/concepts/content-filter?tabs=warning%2Cpython-new#configurability-preview)
 
 ### Asynchronous Filter available for all Azure OpenAI customers
 

articles/ai-studio/concepts/rbac-ai-studio.md

@@ -27,7 +27,7 @@ In this article, you learn how to manage access (authorization) to an Azure AI S
 
 In the Azure AI Studio, there are two levels of access: the hub and the project. The hub is home to the infrastructure (including virtual network setup, customer-managed keys, managed identities, and policies) and where you configure your Azure AI services. Hub access can allow you to modify the infrastructure, create new hubs, and create projects. Projects are a subset of the hub that act as workspaces that allow you to build and deploy AI systems. Within a project you can develop flows, deploy models, and manage project assets. Project access lets you develop AI end-to-end while taking advantage of the infrastructure setup on the hub.
 
-:::image type="content" source="../media/concepts/azureai-hub-project-relationship.png" alt-text="Diagram of the relationship between AI Studio resources." lightbox="../media/concepts/azureai-hub-project-relationship.png":::
+:::image type="content" source="../media/concepts/resource-provider-connected-resources.svg" alt-text="Diagram of the relationship between AI Studio resources.":::
 
 One of the key benefits of the hub and project relationship is that developers can create their own projects that inherit the hub security settings. You might also have developers who are contributors to a project, and can't create new projects.
 

articles/aks/app-routing-nginx-configuration.md

@@ -551,3 +551,4 @@ Learn about monitoring the ingress-nginx controller metrics included with the ap
 [azure-dns-overview]: ../dns/dns-overview.md
 [az-keyvault-certificate-show]: /cli/azure/keyvault/certificate#az-keyvault-certificate-show
 [prometheus-in-grafana]: app-routing-nginx-prometheus.md
+[az-role-assignment-create]: /cli/azure/role/assignment#az-role-assignment-create