Merge pull request #5083 from aahill/removal

Stacyrch140 · web-flow · commit 29bfbd517313 · 2025-05-20T16:47:02.000-04:00
adding note, other updates
diff --git a/articles/ai-services/agents/how-to/tools/azure-functions-samples.md b/articles/ai-services/agents/how-to/tools/azure-functions-samples.md
@@ -6,7 +6,7 @@ services: azure-ai-agent-service
 manager: nitinme
 ms.service: azure-ai-agent-service
 ms.topic: how-to
-ms.date: 01/30/2025
+ms.date: 05/20/2025
 author: aahill
 ms.author: aahi
 ms.custom: azure-ai-agents
@@ -15,7 +15,7 @@ zone_pivot_groups: selection-azure-functions-samples
 
 # How to use Azure Functions with Azure AI Agents 
 
-Azure AI Agents supports function calling, which allows you to describe the structure of functions to an Assistant and then return the functions that need to be called along with their arguments. These examples show how to use Azure Functions to process the function calls through queue messages in Azure Storage. You can see a complete working sample on [GitHub](https://github.com/Azure-Samples/azure-functions-ai-services-agent-python)
+Azure AI Agents supports function calling, which allows you to describe the structure of functions to an Assistant and then return the functions that need to be called along with their arguments. These examples show how to use Azure Functions to process the function calls through queue messages in Azure Storage.
 
 
 ## Prerequisites
@@ -25,6 +25,8 @@ Azure AI Agents supports function calling, which allows you to describe the stru
 
 ::: zone pivot="python"
 
+> [!TIP]
+> You can find a complete working sample on [GitHub](https://github.com/Azure-Samples/azure-functions-ai-services-agent-python)
 
 ## Define a function for your agent to call
 
@@ -312,6 +314,9 @@ For any issues with the TypeScript code, create an issue on the [sample code rep
 -->
 ::: zone pivot="csharp"
 
+> [!TIP]
+> You can find a complete working sample on [GitHub](https://github.com/Azure-Samples/azure-functions-ai-services-agent-dotnet)
+
 ## Prerequisites for .NET Azure Function Sample
 To make a function call, we need to create and deploy the Azure function. In the code snippet, we have an example of function on C# which can be used by the earlier code.
 
diff --git a/articles/ai-services/openai/concepts/assistants.md b/articles/ai-services/openai/concepts/assistants.md
@@ -13,8 +13,7 @@ recommendations: false
 
 # Azure OpenAI Assistants API (Preview)
 
-> [!NOTE]
-> The [Azure AI Foundry Agent Service](../../agents/overview.md) is now Generally Available, which provides more tools and better enterprise features. We recommend using the new service for the latest feature updates and improvements.
+[!INCLUDE [agent-service](../includes/agent-service.md)]
 
 Assistants, a feature of Azure OpenAI in Azure AI Foundry Models, is available in public preview starting in the `2024-02-15-preview` API version. Assistants API makes it easier for developers to create applications with sophisticated copilot-like experiences that can sift through data, suggest solutions, and automate tasks.
 
diff --git a/articles/ai-services/openai/how-to/assistant-functions.md b/articles/ai-services/openai/how-to/assistant-functions.md
@@ -6,7 +6,7 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 03/31/2025
+ms.date: 05/20/2025
 author: aahill
 ms.author: aahi
 recommendations: false
@@ -15,6 +15,8 @@ recommendations: false
 
 # Azure OpenAI Assistants function calling
 
+[!INCLUDE [agent-service](../includes/agent-service.md)]
+
 The Assistants API supports function calling, which allows you to describe the structure of functions to an Assistant and then return the functions that need to be called along with their arguments.
 
 ## Function calling support
diff --git a/articles/ai-services/openai/how-to/assistants-logic-apps.md b/articles/ai-services/openai/how-to/assistants-logic-apps.md
@@ -6,14 +6,16 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 04/29/2025
+ms.date: 05/20/2025
 author: aahill
 ms.author: aahi
 recommendations: false
 ---
 
 # Call Azure Logic apps as functions using Azure OpenAI Assistants 
 
+[!INCLUDE [agent-service](../includes/agent-service.md)]
+
 [Azure Logic Apps](https://azure.microsoft.com/products/logic-apps) is an integration platform in Azure that allows you to build applications and automation workflows with low code tools enabling developer productivity and faster time to market. By using the visual designer and selecting from hundreds of prebuilt connectors, you can quickly build a workflow that integrates and manages your apps, data, services, and systems.
 
 Azure Logic Apps is fully managed by Microsoft Azure, which frees you from worrying about hosting, scaling, managing, monitoring, and maintaining solutions built with these services. When you use these capabilities to create [serverless](/azure/logic-apps/logic-apps-overview) apps and solutions, you can just focus on the business logic and functionality. These services automatically scale to meet your needs, make automation workflows faster, and help you build robust cloud apps using little to no code.
diff --git a/articles/ai-services/openai/how-to/azure-developer-cli.md b/articles/ai-services/openai/how-to/azure-developer-cli.md
@@ -7,13 +7,13 @@ ms.service: azure-ai-openai
 ms.topic: quickstart
 author: aahill
 ms.author: aahi
-ms.date: 02/25/2025
+ms.date: 05/20/2025
 recommendations: false
 ---
 
 # Use the Azure Developer CLI to deploy resources for Azure OpenAI On Your Data 
 
-Use this article to learn how to automate resource deployment for Azure OpenAI in Azure AI Foundry Models On Your Data. The Azure Developer CLI (`azd`) is an open-source command-line tool that streamlines provisioning and deploying resources to Azure by using a template system. The template contains infrastructure files to provision the necessary Azure OpenAI resources and configurations. The source code for the template can be found on [GitHub](https://github.com/Azure-Samples/openai-chat-your-own-data/tree/main).
+Use this article to learn how to automate resource deployment for Azure OpenAI On Your Data. The Azure Developer CLI (`azd`) is an open-source command-line tool that streamlines provisioning and deploying resources to Azure by using a template system. The template contains infrastructure files to provision the necessary Azure OpenAI resources and configurations. The source code for the template can be found on [GitHub](https://github.com/Azure-Samples/openai-chat-your-own-data/tree/main).
 
 ## Prerequisites
 
diff --git a/articles/ai-services/openai/how-to/code-interpreter.md b/articles/ai-services/openai/how-to/code-interpreter.md
@@ -6,7 +6,7 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 02/03/2025
+ms.date: 05/20/2025
 author: aahill
 ms.author: aahi
 recommendations: false
@@ -15,6 +15,8 @@ recommendations: false
 
 # Azure OpenAI Assistants Code Interpreter (Preview)
 
+[!INCLUDE [agent-service](../includes/agent-service.md)]
+
 Code Interpreter allows the Assistants API to write and run Python code in a sandboxed execution environment. With Code Interpreter enabled, your Assistant can run code iteratively to solve more challenging code, math, and data analysis problems. When your Assistant writes code that fails to run, it can iterate on this code by modifying and running different code until the code execution succeeds.
 
 > [!IMPORTANT]
diff --git a/articles/ai-services/openai/how-to/file-search.md b/articles/ai-services/openai/how-to/file-search.md
@@ -6,14 +6,16 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 03/31/2025
+ms.date: 05/20/2025
 author: aahill
 ms.author: aahi
 recommendations: false
 ---
 
 # Azure OpenAI Assistants file search tool (Preview)
 
+[!INCLUDE [agent-service](../includes/agent-service.md)]
+
 File Search augments the Assistant with knowledge from outside its model, such as proprietary product information or documents provided by your users. OpenAI automatically parses and chunks your documents, creates and stores the embeddings, and use both vector and keyword search to retrieve relevant content to answer user queries.
 
 > [!IMPORTANT]
diff --git a/articles/ai-services/openai/how-to/spillover-traffic-management.md b/articles/ai-services/openai/how-to/spillover-traffic-management.md
@@ -5,7 +5,7 @@ author: aahill # GitHub alias
 ms.author: aahi
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 03/05/2025
+ms.date: 05/20/2025
 ---
 
 # Manage traffic with spillover for provisioned deployments (Preview)
@@ -18,15 +18,15 @@ Spillover manages traffic fluctuations on provisioned deployments by routing ove
 
 - The provisioned and standard deployments must be in the same Azure OpenAI resource to be eligible for spillover.
 
-- The data processing level of your standard deployment must match your provisioned deployment (e.g. global provisioned deployment must be used with a global standard spillover deployment).
+- The data processing level of your standard deployment must match your provisioned deployment (for example, a global provisioned deployment must be used with a global standard spillover deployment).
 
 ## When to enable spillover on provisioned deployments
 To maximize the utilization of your provisioned deployment, it is recommended to enable spillover for all global and data zone provisioned deployments. With spillover, bursts or fluctuations in traffic can be automatically managed by the service. This capability reduces the risk of experiencing disruptions when a provisioned deployment is fully utilized. Alternatively, spillover is configurable per-request to provide flexibility across different scenarios and workloads.  
 
 ## When does spillover come into effect?
 When spillover is enabled for a deployment or configured for a given inference request, spillover is initiated when a non-200 response code is received for a given inference request. When a request results in a non-200 response code, the Azure OpenAI automatically sends the request from your provisioned deployment to your standard deployment to be processed. Even if a subset of requests is routed to the standard deployment, the service prioritizes sending requests to the provisioned deployment before sending any overage requests to the standard deployment.
 
-## How does spillover impact cost?
+## How does spillover affect cost?
 Since spillover uses a combination of provisioned and standard deployments to manage traffic fluctuations, billing for spillover involves two components:
 
 - For any requests processed by your provisioned deployment, only the hourly provisioned deployment cost applies. No additional costs are incurred for these requests.
diff --git a/articles/ai-services/openai/how-to/use-web-app.md b/articles/ai-services/openai/how-to/use-web-app.md
@@ -7,7 +7,7 @@ ms.service: azure-ai-openai
 ms.topic: how-to
 author: aahill
 ms.author: aahi
-ms.date: 02/19/2025
+ms.date: 05/20/2025
 recommendations: false
 ---
 
diff --git a/articles/ai-services/openai/includes/agent-service.md b/articles/ai-services/openai/includes/agent-service.md
@@ -0,0 +1,12 @@
+---
+manager: nitinme
+ms.service: azure-ai-services
+ms.custom:
+ms.topic: include
+ms.date: 05/20/2025
+ms.author: aahi
+author: aahill
+---
+
+> [!NOTE]
+> The [Azure AI Foundry Agent Service](../../agents/overview.md) is now Generally Available, which provides more tools and better enterprise features. We recommend using the new service for the latest feature updates and improvements.
