rebrand from Azure OpenAI Studio

eric-urban · eric-urban · commit bc6d6d805f46 · 2025-01-07T20:11:01.000-08:00
diff --git a/articles/ai-services/agents/quotas-limits.md b/articles/ai-services/agents/quotas-limits.md
@@ -21,7 +21,7 @@ The following sections provide you with a guide to the default quotas and limits
 
 | Limit Name | Limit Value |
 |--|--|
-| Max files per agent/thread | 10,000 when using the API or Azure AI Foundry portal. 20 when using Azure OpenAI Studio.|
+| Max files per agent/thread | 10,000 when using the API or Azure AI Foundry portal. In Azure OpenAI Studio the limit was 20.|
 | Max file size for agents & fine-tuning | 512 MB |
 | Max size for all uploaded files for agents |100 GB |  
 | agents token limit | 2,000,000 token limit |
diff --git a/articles/ai-services/openai/dall-e-quickstart.md b/articles/ai-services/openai/dall-e-quickstart.md
@@ -1,7 +1,7 @@
 ---
 title: 'Quickstart: Generate images with Azure OpenAI Service'
 titleSuffix: Azure OpenAI
-description: Learn how to get started generating images with Azure OpenAI Service by using the Python SDK, the REST APIs, or Azure OpenAI Studio.
+description: Learn how to get started generating images with Azure OpenAI Service by using the Python SDK, the REST APIs, or Azure AI Foundry portal.
 #services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
@@ -20,7 +20,7 @@ zone_pivot_groups: openai-quickstart-dall-e
 
 ::: zone pivot="programming-language-studio"
 
-[!INCLUDE [Studio quickstart](includes/dall-e-studio.md)]
+[!INCLUDE [Portal quickstart](includes/dall-e-studio.md)]
 
 ::: zone-end
 
diff --git a/articles/ai-services/openai/how-to/monitor-openai.md b/articles/ai-services/openai/how-to/monitor-openai.md
@@ -69,7 +69,7 @@ After you configure the diagnostic settings, you can work with metrics and log d
 
 [!INCLUDE [horz-monitor-kusto-queries](~/reusable-content/ce-skilling/azure/includes/azure-monitor/horizontals/horz-monitor-kusto-queries.md)]
 
-After you deploy an Azure OpenAI model, you can send some completions calls by using the **playground** environment in [Azure AI Foundry](https://oai.azure.com/).
+After you deploy an Azure OpenAI model, you can send some completions calls by using the **playground** environment in [Azure AI Foundry](https://ai.azure.com/).
 
 Any text that you enter in the **Completions playground** or the **Chat completions playground** generates metrics and log data for your Azure OpenAI resource. In the Log Analytics workspace for your resource, you can query the monitoring data by using the [Kusto](/azure/data-explorer/kusto/query/) query language.
 
diff --git a/articles/ai-services/openai/how-to/risks-safety-monitor.md b/articles/ai-services/openai/how-to/risks-safety-monitor.md
@@ -14,13 +14,13 @@ manager: nitinme
 
 When you use an Azure OpenAI model deployment with a content filter, you might want to check the results of the filtering activity. You can use that information to further adjust your [filter configuration](/azure/ai-services/openai/how-to/content-filters) to serve your specific business needs and Responsible AI principles.  
 
-[Azure AI Foundry](https://oai.azure.com/) provides a Risks & Safety monitoring dashboard for each of your deployments that uses a content filter configuration.
+[Azure AI Foundry](https://ai.azure.com/) provides a Risks & Safety monitoring dashboard for each of your deployments that uses a content filter configuration.
 
 ## Access Risks & Safety monitoring
 
 To access Risks & Safety monitoring, you need an Azure OpenAI resource in one of the supported Azure regions: East US, Switzerland North, France Central, Sweden Central, Canada East. You also need a model deployment that uses a content filter configuration.
 
-Go to [Azure AI Foundry](https://oai.azure.com/) and sign in with the credentials associated with your Azure OpenAI resource. Select a project. Then select the **Models + endpoints** tab on the left and then select your model deployment from the list. On the deployment's page, select the **Metrics** tab at the top. Then select **Open in Azure Monitor** to view the full report in the Azure portal.
+Go to [Azure AI Foundry](https://ai.azure.com/) and sign in with the credentials associated with your Azure OpenAI resource. Select a project. Then select the **Models + endpoints** tab on the left and then select your model deployment from the list. On the deployment's page, select the **Metrics** tab at the top. Then select **Open in Azure Monitor** to view the full report in the Azure portal.
 
 ## Configure metrics   
 
diff --git a/articles/ai-services/openai/includes/chatgpt-studio.md b/articles/ai-services/openai/includes/chatgpt-studio.md
@@ -24,7 +24,7 @@ From the Azure OpenAI Studio landing page, select **Chat playground**.
 
 ## Playground
 
-Start exploring OpenAI capabilities with a no-code approach through the Azure OpenAI Studio Chat playground. From this page, you can quickly iterate and experiment with the capabilities.
+Start exploring Azure OpenAI Service capabilities with a no-code approach through the Azure OpenAI Studio Chat playground. From this page, you can quickly iterate and experiment with the capabilities.
 
 :::image type="content" source="../media/quickstarts/chatgpt-playground-load-new.png" alt-text="Screenshot of the Chat playground page." lightbox="../media/quickstarts/chatgpt-playground-load-new.png":::
 
diff --git a/articles/ai-services/openai/includes/dall-e-studio.md b/articles/ai-services/openai/includes/dall-e-studio.md
@@ -21,7 +21,7 @@ Use this guide to get started generating images with Azure OpenAI in your browse
 
 ## Go to Azure AI Foundry
 
-Browse to [Azure AI Foundry](https://oai.azure.com/) and sign in with the credentials associated with your Azure OpenAI resource. During or after the sign-in workflow, select the appropriate directory, Azure subscription, and Azure OpenAI resource.
+Browse to [Azure AI Foundry](https://ai.azure.com/) and sign in with the credentials associated with your Azure OpenAI resource. During or after the sign-in workflow, select the appropriate directory, Azure subscription, and Azure OpenAI resource.
 
 From the Azure AI Foundry landing page, create or select a new project. Navigate to the **Models + endpoints** page on the left nav. Select **Deploy model** and then choose one of the DALL-E models from the list. Complete the deployment process. 
 
diff --git a/articles/ai-services/openai/includes/on-your-data-authentication.md b/articles/ai-services/openai/includes/on-your-data-authentication.md
@@ -11,8 +11,7 @@ ms.date: 03/27/2024
 
 You need to select how you want to authenticate the connection from Azure OpenAI, Azure AI Search, and Azure blob storage. You can choose a *System assigned managed identity* or an *API key*. By selecting *API key* as the authentication type, the system will automatically populate the API key for you to connect with your Azure AI Search, Azure OpenAI, and Azure Blob Storage resources. By selecting *System assigned managed identity*, the authentication will be based on the [role assignment](../how-to/on-your-data-configuration.md#role-assignments) you have. *System assigned managed identity* is selected by default for security. 
 
-
-:::image type="content" source="../media/use-your-data/data-connection-authentication.png" alt-text="A screenshot showing the managed identity option in Azure OpenAI Studio." lightbox="../media/use-your-data/data-connection-authentication.png":::
+:::image type="content" source="../media/use-your-data/data-connection-authentication.png" alt-text="A screenshot showing the managed identity option in Azure AI Foundry portal." lightbox="../media/use-your-data/data-connection-authentication.png":::
 
 Once you select the **next** button, it will automatically validate your setup to use the selected authentication method. If you encounter an error, see the [role assignments article](../how-to/on-your-data-configuration.md#role-assignments) to update your setup.
 
