Merge branch 'multimodal' of https://github.com/haileytap/azure-ai-docs-pr into multimodal

Author: haileytap

articles/ai-foundry/ai-services/content-safety-overview.md

@@ -14,7 +14,7 @@ author: PatrickFarley
 
 # Content Safety in the Azure AI Foundry portal
 
-Azure AI Content Safety is an AI service that detects harmful user-generated and AI-generated content in applications and services. Azure AI Content Safety includes APIs that allow you to detect and prevent the output of harmful content. The interactive Content Safety **try it out** page in [Azure AI Foundry portal](https://ai.azure.com) allows you to view, explore, and try out sample code for detecting harmful content across different modalities. 
+Azure AI Content Safety is an AI service that detects harmful user-generated and AI-generated content in applications and services. Azure AI Content Safety includes APIs that allow you to detect and prevent the output of harmful content. The interactive Content Safety **try it out** page in [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs) allows you to view, explore, and try out sample code for detecting harmful content across different modalities. 
 
 ## Features
 
@@ -46,4 +46,4 @@ Refer to the [Content Safety overview](/azure/ai-services/content-safety/overvie
 
 ## Next step
 
-Get started using Azure AI Content Safety in [Azure AI Foundry portal](https://ai.azure.com) by following the [How-to guide](/azure/ai-services/content-safety/how-to/foundry).
+Get started using Azure AI Content Safety in [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs) by following the [How-to guide](/azure/ai-services/content-safety/how-to/foundry).

articles/ai-foundry/concepts/ai-resources.md

@@ -2,18 +2,20 @@
 title: Hubs and hub-based project overview
 titleSuffix: Azure AI Foundry
 description: This article introduces concepts about Azure AI Foundry hubs for your Azure AI Foundry projects.
+author: Blackmist
+ms.author: larryfr
 manager: scottpolly
+ms.reviewer: deeikele
+ms.date: 04/28/2025
 ms.service: azure-ai-foundry
+ms.topic: conceptual
 ms.custom:
   - ignite-2023
   - build-2024
   - ai-learning-hub
   - ignite-2024
-ms.topic: conceptual
-ms.date: 04/28/2025
-ms.reviewer: deeikele
-ms.author: larryfr
-author: Blackmist
+  - build-aifnd
+  - build-2025
 ---
 
 # Hub resources overview
@@ -23,7 +25,7 @@ author: Blackmist
 
 Azure AI Hub is a resource type that is used in combination with Azure AI Foundry resource type, and is only required for selected use cases. Hub resources provides access to open-source model hosting and finetuning capabilities, as well as Azure Machine Learning capabilities, next to capabilities supported by its associated AI Foundry resource.
 
-When you create an AI Hub, an Azure AI Foundry resource is automatically provisioned. Hub resources can be used in [Azure AI Foundry](https://ai.azure.com) and [Azure Machine Learning studio](https://ml.azure.com).
+When you create an AI Hub, an Azure AI Foundry resource is automatically provisioned. Hub resources can be used in [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs) and [Azure Machine Learning studio](https://ml.azure.com).
 
 Hubs have their own project types that support a differentiated feature set from Foundry projects. See [project types](../what-is-azure-ai-foundry.md#which-type-of-project-do-i-need) for an overview of supported features.
 
@@ -35,7 +37,7 @@ Hubs group one or more projects together with common settings including data acc
 
 ## Create a hub-based project
 
-To start developing, [create a project](../how-to/create-projects.md). Hub-projects can be accessed in [AI Foundry Portal](https://ai.azure.com) to build with generative AI tools, and [ML Studio](https://ml.azure.com) to build with tools designed for custom machine learning model training.
+To start developing, [create a project](../how-to/create-projects.md). Hub-projects can be accessed in [AI Foundry Portal](https://ai.azure.com/?cid=learnDocs) to build with generative AI tools, and [ML Studio](https://ml.azure.com) to build with tools designed for custom machine learning model training.
 
 ## Project concepts
 

articles/ai-foundry/concepts/content-filtering.md

@@ -17,7 +17,7 @@ author: PatrickFarley
 
 # Content filtering in Azure AI Foundry portal
 
-[Azure AI Foundry](https://ai.azure.com) includes a content filtering system that works alongside core models and image generation models.
+[Azure AI Foundry](https://ai.azure.com/?cid=learnDocs) includes a content filtering system that works alongside core models and image generation models.
 
 > [!IMPORTANT]
 > The content filtering system isn't applied to prompts and completions processed by the Whisper model in Azure OpenAI in Azure AI Foundry Models. Learn more about the [Whisper model in Azure OpenAI](../../ai-services/openai/concepts/models.md).

articles/ai-foundry/concepts/encryption-keys-portal.md

@@ -4,19 +4,21 @@ titleSuffix: Azure AI Foundry
 description: Learn about using customer-managed keys for encryption to improve data security with Azure AI Foundry.
 author: Blackmist
 ms.author: larryfr
+ms.reviewer: deeikele
+ms.date: 05/01/2025
 ms.service: azure-ai-services
+ms.topic: concept-article
 ms.custom:
   - ignite-2023
-ms.topic: concept-article
-ms.date: 05/01/2025
-ms.reviewer: deeikele
+  - build-aifnd
+  - build-2025
 zone_pivot_groups: project-type
 # Customer intent: As an admin, I want to understand how I can use my own encryption keys with Azure AI Foundry.
 ---
 
 # Customer-managed keys for encryption with Azure AI Foundry
 
-Customer-managed keys (CMKs) in [Azure AI Foundry portal](https://ai.azure.com/) provide enhanced control over the encryption of your data. By using CMKs, you can manage your own encryption keys to add an extra layer of protection and meet compliance requirements more effectively.
+Customer-managed keys (CMKs) in [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs) provide enhanced control over the encryption of your data. By using CMKs, you can manage your own encryption keys to add an extra layer of protection and meet compliance requirements more effectively.
 
 ## About encryption in Azure AI Foundry
 
@@ -66,7 +68,7 @@ Two architecture options are available when using customer-managed keys:
   |-----|-----|-----|
   |Azure Cosmos DB|Stores metadata for your Azure AI projects and tools|Index names, tags; Flow creation timestamps; deployment tags; evaluation metrics|
   |Azure AI Search|Stores indices that are used to help query your Azure AI Foundry content.|An index based off your model deployment names|
-  |Azure Storage Account|Stores instructions for how customization tasks are orchestrated|JSON representation of flows you create in [Azure AI Foundry portal](https://ai.azure.com/)|
+  |Azure Storage Account|Stores instructions for how customization tasks are orchestrated|JSON representation of flows you create in [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs)|
 
 
 ::: zone-end

articles/ai-foundry/concepts/evaluation-evaluators/agent-evaluators.md

@@ -2,13 +2,16 @@
 title: Agent evaluators for generative AI
 titleSuffix: Azure AI Foundry
 description: Learn how to evaluate Azure AI agents using intent resolution, tool call accuracy, and task adherence evaluators.
+author: lgayhardt
+ms.author: lagayhar
 manager: scottpolly
+ms.reviewer: changliu2
+ms.date: 05/19/2025
 ms.service: azure-ai-foundry
 ms.topic: reference
-ms.date: 05/19/2025
-ms.reviewer: changliu2
-ms.author: lagayhar
-author: lgayhardt
+ms.custom:
+  - build-aifnd
+  - build-2025
 ---
 
 # Agent evaluators (preview)

articles/ai-foundry/concepts/evaluation-evaluators/azure-openai-graders.md

@@ -2,13 +2,16 @@
 title: Azure OpenAI Graders for generative AI
 titleSuffix: Azure AI Foundry
 description: Learn about Azure OpenAI Graders for evaluating AI model outputs, including label grading, string checking, text similarity, and custom grading.
+author: lgayhardt
+ms.author: lagayhar
 manager: scottpolly
+ms.reviewer: mithigpe
+ms.date: 05/19/2025
 ms.service: azure-ai-foundry
 ms.topic: reference
-ms.date: 05/19/2025
-ms.reviewer: mithigpe
-ms.author: lagayhar
-author: lgayhardt
+ms.custom:
+  - build-aifnd
+  - build-2025
 ---
 
 # Azure OpenAI Graders (preview)

articles/ai-foundry/concepts/evaluation-evaluators/custom-evaluators.md

@@ -2,13 +2,16 @@
 title: Custom evaluators
 titleSuffix: Azure AI Foundry
 description: Learn how to create custom evaluators for your AI applications using code-based or prompt-based approaches.
+author: lgayhardt
+ms.author: lagayhar
 manager: scottpolly
+ms.reviewer: mithigpe
+ms.date: 05/19/2025
 ms.service: azure-ai-foundry
 ms.topic: reference
-ms.date: 05/19/2025
-ms.reviewer: mithigpe
-ms.author: lagayhar
-author: lgayhardt
+ms.custom:
+  - build-aifnd
+  - build-2025
 ---
 
 # Custom evaluators
@@ -152,4 +155,4 @@ friendliness_score = friendliness_eval(response="I will not apologize for my beh
 ## Related content
 
 - [How to run batch evaluation on a dataset](../../how-to/develop/evaluate-sdk.md#local-evaluation-on-test-datasets-using-evaluate)  
-- [How to run batch evaluation on a target](../../how-to/develop/evaluate-sdk.md#local-evaluation-on-a-target)
+- [How to run batch evaluation on a target](../../how-to/develop/evaluate-sdk.md#local-evaluation-on-a-target)

articles/ai-foundry/concepts/evaluation-evaluators/general-purpose-evaluators.md

@@ -2,13 +2,16 @@
 title: General purpose evaluators for generative AI
 titleSuffix: Azure AI Foundry
 description: Learn about general-purpose evaluators for generative AI, including coherence, fluency, and question-answering composite evaluation.
+author: lgayhardt
+ms.author: lagayhar
 manager: scottpolly
+ms.reviewer: changliu2
+ms.date: 05/19/2025
 ms.service: azure-ai-foundry
 ms.topic: reference
-ms.date: 05/19/2025
-ms.reviewer: changliu2
-ms.author: lagayhar
-author: lgayhardt
+ms.custom:
+  - build-aifnd
+  - build-2025
 ---
 
 # General purpose evaluators
@@ -161,4 +164,4 @@ While F1 score outputs a numerical score on 0-1 float scale, the other evaluator
 ## Related content
 
 - [How to run batch evaluation on a dataset](../../how-to/develop/evaluate-sdk.md#local-evaluation-on-test-datasets-using-evaluate)  
-- [How to run batch evaluation on a target](../../how-to/develop/evaluate-sdk.md#local-evaluation-on-a-target)
+- [How to run batch evaluation on a target](../../how-to/develop/evaluate-sdk.md#local-evaluation-on-a-target)

articles/ai-foundry/concepts/evaluation-evaluators/rag-evaluators.md

@@ -2,13 +2,16 @@
 title: Retrieval-augmented Generation (RAG) evaluators for generative AI
 titleSuffix: Azure AI Foundry
 description: Learn about Retrieval-augmented Generation (RAG) evaluators for assessing relevance, groundedness, and response completeness in generative AI systems.
+author: lgayhardt
+ms.author: lagayhar
 manager: scottpolly
+ms.reviewer: changliu2
+ms.date: 05/19/2025
 ms.service: azure-ai-foundry
 ms.topic: reference
-ms.date: 05/19/2025
-ms.reviewer: changliu2
-ms.author: lagayhar
-author: lgayhardt
+ms.custom:
+  - build-aifnd
+  - build-2025
 ---
 
 # Retrieval-augmented Generation (RAG) evaluators

articles/ai-foundry/concepts/evaluation-evaluators/risk-safety-evaluators.md

@@ -2,13 +2,16 @@
 title: Risk and safety evaluators for generative AI
 titleSuffix: Azure AI Foundry
 description: Learn about risk and safety evaluators for generative AI, including tools for assessing content safety, jailbreak vulnerabilities, and code security risks.
+author: lgayhardt
+ms.author: lagayhar
 manager: scottpolly
+ms.reviewer: mithigpe
+ms.date: 05/19/2025
 ms.service: azure-ai-foundry
 ms.topic: reference
-ms.date: 05/19/2025
-ms.reviewer: mithigpe
-ms.author: lagayhar
-author: lgayhardt
+ms.custom:
+  - build-aifnd
+  - build-2025
 ---
 
 # Risk and safety evaluators (preview)