Merge pull request #5057 from MicrosoftDocs/main

[Out of Band Publish] azure-ai-docs-pr - 05/19 - 4:00 PM PT

Author: Albertyang0

articles/ai-foundry/how-to/develop/cloud-evaluation.md

@@ -16,11 +16,11 @@ ms.custom: include file
 > Users who previously used oai.azure.com to manage their model deployments and run evaluations and have since onboarded to Foundry Developer Platform (FDP) will have a few limitations when using ai.azure.com:
 >
 > - First, users will be unable to view their evaluations that were created using the Azure OpenAI API. Instead, to view these, users have to navigate back to oai.azure.com.
-> - Second, users will be unable to use the Azure OpenAI API to run evaluations within AI Foundry. Instead, these users should continue to use oai.azure.com for this. However, users can use the Azure OpenAI evaluators that are available directly in AI Foundry (ai.azure.com) in the dataset evaluation creation option. The Fine-tuned  model evaluation option isn't supported if the deployment is a migration from Azure OpenAI service to Azure Foundry.
+> - Second, users will be unable to use the Azure OpenAI API to run evaluations within AI Foundry. Instead, these users should continue to use oai.azure.com for this. However, users can use the Azure OpenAI evaluators that are available directly in AI Foundry (ai.azure.com) in the dataset evaluation creation option. The Fine-tuned  model evaluation option isn't supported if the deployment is a migration from Azure OpenAI to Azure Foundry.
 > - For the dataset upload + bring your own storage scenario, a few configurations requirements need to happen:
 >
 >   - Account authentication needs to be Entra ID.
 >   - The storage needs to be added to the account (if it’s added to the project, you'll get service errors).
 >   - User needs to add their project to their storage account through access control in the Azure portal.
 >
-> To learn more about creating evaluations specifically with OpenAI evaluation graders in Azure OpenAI Hub, see [How to use Azure OpenAI Service evaluation](../../ai-services/openai/how-to/evaluations.md)
+> To learn more about creating evaluations specifically with OpenAI evaluation graders in Azure OpenAI Hub, see [How to use Azure OpenAI in Azure AI Foundry Models evaluation](../../ai-services/openai/how-to/evaluations.md)

articles/ai-foundry/includes/fdp-backward-compatibility-azure-openai.md

@@ -17,7 +17,7 @@ ms.custom: azure-ai-agents
 Use this article if you want to use the Azure Agent Service with resources you already have. 
 
 > [!NOTE]
-> * If you use an existing AI Services / Azure OpenAI Service resource, no model will be deployed. You can deploy a model to the resource after the agent setup is complete. 
+> * If you use an existing AI Services / Azure OpenAI in Azure AI Foundry Models resource, no model will be deployed. You can deploy a model to the resource after the agent setup is complete. 
 > * Make sure your Azure OpenAI resource and Azure AI Foundry project are in the same region. 
 
 ## Choose basic or standard agent setup

articles/ai-services/agents/how-to/use-your-own-resources.md

@@ -30,7 +30,7 @@ The following services are Limited Access:
 - [Azure AI Face](/legal/cognitive-services/computer-vision/limited-access-identity?context=/azure/ai-services/computer-vision/context/context): Identify and Verify features, face ID property
 - [Azure AI Vision](/legal/cognitive-services/computer-vision/limited-access?context=/azure/ai-services/computer-vision/context/context): Celebrity Recognition feature
 - [Azure AI Video Indexer](/azure/azure-video-indexer/limited-access-features): Celebrity Recognition and Face Identify features
-- [Azure OpenAI](/legal/cognitive-services/openai/limited-access): Azure OpenAI Service, modified abuse monitoring, and modified content filters
+- [Azure OpenAI](/legal/cognitive-services/openai/limited-access): Azure OpenAI in Azure AI Foundry Models, modified abuse monitoring, and modified content filters
 
 Features of these services that aren't listed are available without registration. 
 
@@ -46,7 +46,7 @@ Submit a registration form for each Limited Access service you would like to use
 - [Azure AI Face](https://aka.ms/facerecognition): Identify and Verify features
 - [Azure AI Vision](https://aka.ms/facerecognition): Celebrity Recognition feature 
 - [Azure AI Video Indexer](https://aka.ms/facerecognition): Celebrity Recognition and Face Identify features 
-- [Azure OpenAI](/legal/cognitive-services/openai/limited-access): Azure OpenAI Service, modified abuse monitoring, and modified content filters 
+- [Azure OpenAI](/legal/cognitive-services/openai/limited-access): Azure OpenAI, modified abuse monitoring, and modified content filters 
 
 ### How long does the registration process take?
 

articles/ai-services/cognitive-services-limited-access.md

@@ -532,7 +532,7 @@ When you create a private endpoint, specify the Azure AI services resource that
 ### Connect to private endpoints
 
 > [!NOTE]
-> Azure OpenAI Service uses a different private DNS zone and public DNS zone forwarder than other Azure AI services. For the correct zone and forwarder names, see [Azure services DNS zone configuration](/azure/private-link/private-endpoint-dns#azure-services-dns-zone-configuration).
+> Azure OpenAI in Azure AI Foundry Models uses a different private DNS zone and public DNS zone forwarder than other Azure AI services. For the correct zone and forwarder names, see [Azure services DNS zone configuration](/azure/private-link/private-endpoint-dns#azure-services-dns-zone-configuration).
 
 Clients on a virtual network that use the private endpoint use the same connection string for the Azure AI services resource as clients connecting to the public endpoint. The exception is the Speech service, which requires a separate endpoint. For more information, see [Use private endpoints with the Speech service](#use-private-endpoints-with-the-speech-service) in this article. DNS resolution automatically routes the connections from the virtual network to the Azure AI services resource over a private link.
 

articles/ai-services/cognitive-services-virtual-networks.md

@@ -42,7 +42,7 @@ You can connect Azure AI services resources to an Azure AI Foundry project after
 
     :::image type="content" source="./media/ai-foundry/connections-add.png" alt-text="Screenshot of the connected resources page with the button to create a new connection." lightbox="./media/ai-foundry/connections-add.png":::
 
-1. On the **Add a connection to external assets** page, select the kind of AI service that you want to connect to the project. For example, you can select Azure AI services (for a connection to multiple services in one resource), Azure OpenAI Service, Azure AI Content Safety, Azure AI Speech, Azure AI Language, and other AI services.
+1. On the **Add a connection to external assets** page, select the kind of AI service that you want to connect to the project. For example, you can select Azure AI services (for a connection to multiple services in one resource), Azure OpenAI in Azure AI Foundry Models, Azure AI Content Safety, Azure AI Speech, Azure AI Language, and other AI services.
 
     :::image type="content" source="./media/ai-foundry/connections-add-assets.png" alt-text="Screenshot of the page to select the kind of AI service that you want to connect to the project." lightbox="./media/ai-foundry/connections-add-assets.png":::
 

articles/ai-services/connect-services-ai-foundry-portal.md

@@ -45,9 +45,9 @@ In addition to adjusting the severity levels for false negatives, you can also u
 
 Read the [Configurability](/en-us/azure/ai-services/openai/concepts/content-filter?tabs=warning%2Cuser-prompt%2Cpython-new#configurability-preview) documentation, as some content filtering configurations may require approval through the process mentioned there.
 
-Follow the steps in the documentation to update configurations to handle false positives or negatives: [How to use content filters (preview) with Azure OpenAI Service](/azure/ai-services/openai/how-to/content-filters). 
+Follow the steps in the documentation to update configurations to handle false positives or negatives: [How to use content filters (preview) with Azure OpenAI in Azure AI Foundry Models](/azure/ai-services/openai/how-to/content-filters). 
 
-In addition to adjusting the severity levels for false negatives, you can also use blocklists. Detailed instruction can be found in [How to use blocklists with Azure OpenAI Service](/azure/ai-services/openai/how-to/use-blocklists).
+In addition to adjusting the severity levels for false negatives, you can also use blocklists. Detailed instruction can be found in [How to use blocklists with Azure OpenAI](/azure/ai-services/openai/how-to/use-blocklists).
 
 #### [Azure AI Foundry](#tab/azure-ai-studio)
 

articles/ai-services/content-safety/how-to/improve-performance.md

@@ -16,7 +16,7 @@ ms.author: pafarley
 * 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**.
 * 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.
+* (Optional) If you want to use the _reasoning_ feature, create an Azure OpenAI in Azure AI Foundry Models resource with a GPT model deployed.
 * [cURL](https://curl.haxx.se/) or [Python](https://www.python.org/downloads/) installed.
 
 ## Authentication
@@ -166,7 +166,7 @@ The Groundedness detection API provides the option to include _reasoning_ in the
 ### Connect your own GPT deployment
 
 > [!TIP]
-> We only support Azure OpenAI GPT-4o (versions 0513, 0806) resources and don't support other models. You have the flexibility to deploy your Azure OpenAI GPT-4o (versions 0513, 0806) resources in any region. However, to minimize potential latency and avoid any geographical boundary data privacy and risk concerns, we recommend situating them in the same region as your Azure AI Content Safety resources. For comprehensive details on data privacy, refer to the [Data, privacy and security guidelines for Azure OpenAI Service](/legal/cognitive-services/openai/data-privacy) and [Data, privacy, and security for Azure AI Content Safety](/legal/cognitive-services/content-safety/data-privacy?context=%2Fazure%2Fai-services%2Fcontent-safety%2Fcontext%2Fcontext).
+> We only support Azure OpenAI GPT-4o (versions 0513, 0806) resources and don't support other models. You have the flexibility to deploy your Azure OpenAI GPT-4o (versions 0513, 0806) resources in any region. However, to minimize potential latency and avoid any geographical boundary data privacy and risk concerns, we recommend situating them in the same region as your Azure AI Content Safety resources. For comprehensive details on data privacy, refer to the [Data, privacy and security guidelines for Azure OpenAI](/legal/cognitive-services/openai/data-privacy) and [Data, privacy, and security for Azure AI Content Safety](/legal/cognitive-services/content-safety/data-privacy?context=%2Fazure%2Fai-services%2Fcontent-safety%2Fcontext%2Fcontext).
 
 In order to use your Azure OpenAI GPT-4o (versions 0513, 0806) resource to enable the reasoning feature, use Managed Identity to allow your Content Safety resource to access the Azure OpenAI resource:
 
@@ -348,7 +348,7 @@ The groundedness detection API includes a correction feature that automatically
 ### Connect your own GPT deployment
 
 > [!TIP]
-> Currently, the correction feature supports only **Azure OpenAI GPT-4o (versions 0513, 0806)** resources. To minimize latency and adhere to data privacy guidelines, it's recommended to deploy your Azure OpenAI GPT-4o (versions 0513, 0806) in the same region as your Azure AI Content Safety resources. For more details on data privacy, refer to the [Data, privacy and security guidelines for Azure OpenAI Service](/legal/cognitive-services/openai/data-privacy?context=/azure/ai-services/openai/context/context)
+> Currently, the correction feature supports only **Azure OpenAI GPT-4o (versions 0513, 0806)** resources. To minimize latency and adhere to data privacy guidelines, it's recommended to deploy your Azure OpenAI GPT-4o (versions 0513, 0806) in the same region as your Azure AI Content Safety resources. For more details on data privacy, refer to the [Data, privacy and security guidelines for Azure OpenAI](/legal/cognitive-services/openai/data-privacy?context=/azure/ai-services/openai/context/context)
  and [Data, privacy, and security for Azure AI Content Safety](/legal/cognitive-services/content-safety/data-privacy?context=/azure/ai-services/content-safety/context/context).
 
 To use your Azure OpenAI GPT-4o (versions 0513, 0806) resource for enabling the correction feature, use Managed Identity to allow your Content Safety resource to access the Azure OpenAI resource. Follow the steps in the [earlier section](#connect-your-own-gpt-deployment) to set up the Managed Identity.

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

@@ -275,7 +275,7 @@ You can also customize prebuilt analyzers for more fine-grained control of the o
 ## Conversational Knowledge Mining Solution Accelerator
 For an end-2-end quickstart for Speech Analytics solutions, refer to the [Conversation knowledge mining solution accelerator](https://aka.ms/Conversational-Knowledge-Mining).
 
-Gain actionable insights from large volumes of conversational data by identifying key themes, patterns, and relationships. By using Azure AI Foundry, Azure AI Content Understanding, Azure OpenAI Service, and Azure AI Search, this solution analyzes unstructured dialogue and maps it to meaningful, structured insights.
+Gain actionable insights from large volumes of conversational data by identifying key themes, patterns, and relationships. By using Azure AI Foundry, Azure AI Content Understanding, Azure OpenAI in Azure AI Foundry Models, and Azure AI Search, this solution analyzes unstructured dialogue and maps it to meaningful, structured insights.
 
 Capabilities such as topic modeling, key phrase extraction, speech-to-text transcription, and interactive chat enable users to explore data naturally and make faster, more informed decisions.
 

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

@@ -52,7 +52,7 @@ sections:
         answer: |
           **Yes.**
 
-           You can also use a document generative AI solution to chat with your documents (RAG), generate captivating content from those documents, and access Azure OpenAI Service models on your data.
+           You can also use a document generative AI solution to chat with your documents (RAG), generate captivating content from those documents, and access Azure OpenAI models on your data.
 
           - With Azure AI Document Intelligence and Azure OpenAI combined, you can build an enterprise application to seamlessly interact with your documents using natural language. You can easily find answers, gain valuable insights, and generate new and engaging content from existing documents.