Merge pull request #5327 from MicrosoftDocs/main

06/02/2025 AM Publishing

Author: v-alje

articles/ai-foundry/how-to/configure-managed-network.md

@@ -809,7 +809,7 @@ If you plan to use __HuggingFace models__ with the hub, add outbound _FQDN_ rule
 * *.docker.io
 * *.docker.com
 * production.cloudflare.docker.com
-* cnd.auth0.com
+* cdn.auth0.com
 * cdn-lfs.huggingface.co
 
 ### Scenario: Models Sold Directly by Azure 

articles/ai-foundry/whats-new-azure-ai-foundry.md

@@ -1,39 +1,22 @@
 ---
-title: "Azure AI Foundry docs: What's new for April 2025"
-description: "What's new in the Azure AI Foundry docs for April 2025."
+title: "Azure AI Foundry docs: What's new for May 2025"
+description: "What's new in the Azure AI Foundry docs for May 2025."
 ms.author: smcdowell
 author: skpmcdowell
 ms.topic: whats-new
-ms.subject: ai-studio
-ms.custom: April-2025
-ms.date: 05/03/2025
+ms.subject: ai-foundry
+ms.custom: May-2025
+ms.date: 06/02/2025
 ---
 
-# Azure AI Foundry docs: What's new for April 2025
+# Azure AI Foundry docs: What's new for May 2025
 
-Welcome to what's new in the Azure AI Foundry docs for April 2025. This article lists some of the major changes to docs during this period.
+Welcome to what's new in the Azure AI Foundry docs for May 2025. This article lists some of the major changes to docs during this period.
 
+## Updated articles
 
-## Azure AI Foundry
+- [Evaluate your Generative AI application on the cloud with Azure AI Projects SDK (preview)](../ai-foundry/how-to/develop/cloud-evaluation.md)
 
-### New articles
-
-- [AI Red Teaming Agent (preview)](../ai-foundry/concepts/ai-red-teaming-agent.md)
-- [Evaluate your AI agents locally with Azure AI Evaluation SDK (preview)](../ai-foundry/how-to/develop/agent-evaluate-sdk.md)
-- [How to use structured outputs for chat models](../ai-foundry/model-inference/how-to/use-structured-outputs.md)
-- [Run automated safety scans with AI Red Teaming Agent (preview)](../ai-foundry/how-to/develop/run-scans-ai-red-teaming-agent.md)
-- [Work with Azure AI Agent Service in Visual Studio Code (Preview)](../ai-foundry/how-to/develop/vs-code-agents.md)
-- [Work with the Azure AI Foundry for Visual Studio Code extension (Preview)](../ai-foundry/how-to/develop/get-started-projects-vs-code.md)
-
-
-### Updated articles
-
-- [Evaluate your AI agents locally with Azure AI Evaluation SDK (preview)](../ai-foundry/how-to/develop/agent-evaluate-sdk.md)  
-- [Evaluate your Generative AI application locally with the Azure AI Evaluation SDK](../ai-foundry/how-to/develop/evaluate-sdk.md) 
-- [Evaluation and monitoring metrics for generative AI](../ai-foundry/concepts/evaluation-metrics-built-in.md)  
-- [Fine-tune models using standard deployments in Azure AI Foundry](../ai-foundry/how-to/fine-tune-serverless.md) 
-- [How to configure a private link for Azure AI Foundry hubs](../ai-foundry/how-to/configure-private-link.md) 
-- [How to use MedImageParse healthcare AI models for segmentation of medical images](../ai-foundry/how-to/healthcare-ai/deploy-medimageparse.md)
 
 
 

articles/ai-services/agents/how-to/tools/logic-apps.md

@@ -143,4 +143,4 @@ print("Deleted agent")
 
 ## Next steps
 
-[See the full sample for Logic Apps integration.](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-projects/samples/agents/sample_agents_logic_apps.py)
+[See the full sample for Logic Apps integration.](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-agents/samples/agents_tools/sample_agents_logic_apps.py)

articles/ai-services/document-intelligence/train/custom-lifecycle.md

@@ -6,7 +6,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-document-intelligence
 ms.topic: conceptual
-ms.date: 11/19/2024
+ms.date: 06/02/2025
 ms.author: lajanuar
 monikerRange: '>=doc-intel-3.1.0'
 ---
@@ -22,7 +22,9 @@ With the v3.1 (GA) and later APIs, custom models introduce a expirationDateTime
 
 ## Models trained with GA API version
 
-With the v3.1 API, custom models introduce a new model expiration property. The model expiration is set to two years from the date the model is built for all requests that use a GA API to build a model. To continue to use the model past the expiration date, you need to  train the model with a current GA API version. The API version can be the one that the model was originally trained with or a later API version. The following figure illustrates the options when you need to retrain an expiring or expired model.
+With the v3.1 API, custom models introduce a new model expiration property. The model is configured to expire two years after its creation for all requests utilizing a GA API to build it. The API version can be the one that the model was originally trained with or a later API version. The following figure illustrates the options when you need to retrain an expiring or expired model.
+
+> Note: The model expiration date for v3.1/4.0 models is only set if the training is done post release of v3.1/v4.0. If the models were created earlier with no expiration date associated with them and were not retrained after v3.1/v4.0, the expiration date will be null. The models with expiration date property will still be available until the API retires. Notification of retirement of any particular GA API version will be communicated at least 3 years before expiration.
 
 :::image type="content" source="../media/model-lifecycle.png" alt-text="Screenshot showing how to choose an API version and retrain a model.":::
 

articles/ai-services/language-service/personally-identifiable-information/concepts/entity-categories.md

@@ -24,7 +24,7 @@ The PII feature includes the ability to detect personal (`PII`) and health (`PHI
 
 The following entity categories are returned when you're sending API requests PII feature.
 
-# [Generally Available API](#tab/ga-api)
+# [Preview API](#tab/preview-api)
 
 ## Category: Person
 
@@ -627,7 +627,7 @@ These entity categories include identifiable Azure information like authenticati
     :::column-end:::
 :::row-end:::
 
-# [Preview API](#tab/preview-api)
+# [Generally Available API](#tab/ga-api)
 
 ## Type: Person