Merge pull request #1481 from mrbullwinkle/mrb_11_11_2024_studio_updates

[Azure OpenAI] Studio updates

Author: prmerger-automator[bot]

articles/ai-services/openai/concepts/system-message.md

@@ -165,5 +165,5 @@ Finally, remember that system messages, or metaprompts, are not "one size fits a
 
 - [Azure OpenAI Service](/azure/ai-services/openai/concepts/prompt-engineering)
 - [System message design with Azure OpenAI](/azure/ai-services/openai/concepts/advanced-prompt-engineering?pivots=programming-language-chat-completions) 
-- [Announcing Safety System Messages in Azure AI Studio and Azure OpenAI Studio](https://techcommunity.microsoft.com/t5/ai-azure-ai-services-blog/announcing-safety-system-messages-in-azure-ai-studio-and-azure/ba-p/4146991) - Microsoft Community Hub 
+- [Announcing Safety System Messages in Azure AI Studio](https://techcommunity.microsoft.com/t5/ai-azure-ai-services-blog/announcing-safety-system-messages-in-azure-ai-studio-and-azure/ba-p/4146991) - Microsoft Community Hub 
 - [Safety system message templates ](./safety-system-message-templates.md)

articles/ai-services/openai/how-to/monitor-openai.md

@@ -71,8 +71,6 @@ After you configure the diagnostic settings, you can work with metrics and log d
 
 After you deploy an Azure OpenAI model, you can send some completions calls by using the **playground** environment in [Azure AI Studio](https://oai.azure.com/).
 
-:::image type="content" source="../media/monitoring/azure-openai-studio-playground.png" alt-text="Screenshot that shows how to generate completions for an Azure OpenAI resource in the Azure OpenAI Studio playground." lightbox="../media/monitoring/azure-openai-studio-playground.png" border="false":::
-
 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.
 
 > [!IMPORTANT]

articles/ai-services/openai/how-to/provisioned-throughput-onboarding.md

@@ -33,7 +33,7 @@ Determining the right amount of provisioned throughput, or PTUs, you require for
 
 ### Estimate provisioned throughput and cost
 
-To get a quick estimate for your workload, open the capacity planner in the [Azure OpenAI Studio](https://oai.azure.com). The capacity planner is under **Shared resources** > **Quota** > **Azure OpenAI Provisioned**.
+To get a quick estimate for your workload, open the capacity planner in the [Azure AI Studio](https://ai.azure.com). The capacity calculator is under **Shared resources** > **Model Quota** > **Azure OpenAI Provisioned**.
 
 The **Provisioned** option and the capacity planner are only available in certain regions within the Quota pane, if you don't see this option setting the quota region to *Sweden Central* will make this option available. Enter the following parameters based on your workload.
 
@@ -49,14 +49,14 @@ After you fill in the required details, select **Calculate** button in the outpu
 
 The values in the output column are the estimated value of PTU units required for the provided workload inputs. The first output value represents the estimated PTU units required for the workload, rounded to the nearest PTU scale increment. The second output value represents the raw estimated PTU units required for the workload. The token totals are calculated using the following equation: `Total = Peak calls per minute * (Tokens in prompt call + Tokens in model response)`.
 
-:::image type="content" source="../media/how-to/provisioned-onboarding/capacity-calculator.png" alt-text="Screenshot of the Azure OpenAI Studio landing page." lightbox="../media/how-to/provisioned-onboarding/capacity-calculator.png":::
+:::image type="content" source="../media/how-to/provisioned-onboarding/capacity-calculator.png" alt-text="Screenshot of the capacity calculator" lightbox="../media/how-to/provisioned-onboarding/capacity-calculator.png":::
 
 > [!NOTE]
 > The capacity calculator provides an estimate based on simple input criteria. The most accurate way to determine your capacity is to benchmark a deployment with a representational workload for your use case.
 
 ## Understanding the Provisioned Throughput Purchase Model 
 
-Azure OpenAI Provisioned and Global Provisiones are purchased on-demand at an hourly basis based on the number of deployed PTUs, with substantial term discount available via the purchase of Azure Reservations.   
+Azure OpenAI Provisioned and Global Provisioned are purchased on-demand at an hourly basis based on the number of deployed PTUs, with substantial term discount available via the purchase of Azure Reservations.   
 
 The hourly model is useful for short-term deployment needs, such as validating new models or acquiring capacity for a hackathon.  However, the discounts provided by the Azure Reservation for Azure OpenAI Provisioned and Global Provisioned are considerable and most customers with consistent long-term usage will find a reserved model to be a better value proposition. 
 
@@ -86,7 +86,7 @@ Customers that require long-term usage of provisioned and global provisioned dep
 
 Discounts on top of the hourly usage price can be obtained by purchasing an Azure Reservation for Azure OpenAI Provisioned and Global Provisioned. An Azure Reservation is a term-discounting mechanism shared by many Azure products. For example, Compute and Cosmos DB. For Azure OpenAI Provisioned and Global Provisioned, the reservation provides a discount for committing to payment for fixed number of PTUs for a one-month or one-year period.  
 
-* Azure Reservations are purchased via the Azure portal, not Azure OpenAI Studio Link to Azure reservation portal. 
+* Azure Reservations are purchased via the Azure portal, not the Azure AI Studio Link to Azure reservation portal.
 
 * Reservations are purchased regionally and can be flexibly scoped to cover usage from a group of deployments. Reservation scopes include: 
 
@@ -115,7 +115,7 @@ The PTU amounts in reservation purchases are independent of PTUs allocated in qu
 
 The best practice is to always purchase a reservation after deployments have been created.  This prevents purchasing a reservation and then finding out that the required capacity is not available for the desired region or model. 
 
-To assist customers with purchasing the correct reservation amounts. The total number of PTUs in a subscription and region that can be covered by a reservation are listed on the Quotas page of Azure OpenAI Studio. See the message "PTUs Available for reservation." 
+To assist customers with purchasing the correct reservation amounts. The total number of PTUs in a subscription and region that can be covered by a reservation are listed on the Quotas page of Azure AI Studio. See the message "PTUs Available for reservation." 
 
 :::image type="content" source="../media/provisioned/available-quota.png" alt-text="A screenshot showing available PTU quota." lightbox="../media/provisioned/available-quota.png":::