Merge branch 'main' of https://github.com/MicrosoftDocs/azure-ai-docs-pr into deploy-online-endpoints

Author: paulth1

.acrolinx-config.edn

@@ -1,2 +1,2 @@
 {:allowed-branchname-matches ["main" "release-.*"]
- :allowed-filename-matches ["(?i)articles/(?:(?!active-directory/saas-apps/toc.yml|role-based-access-control/resource-provider-operations.md|.*policy/samples/|.*resource-graph/samples/))" "(?i)includes/(?:(?!policy/reference/|policy/standards/|resource-graph/samples/))"]}
+ :allowed-filename-matches ["articles"]}

.gitignore

@@ -9,4 +9,8 @@ _site/
 _themes*/
 _repo.*/
 
-.openpublishing.buildcore.ps1
+.openpublishing.buildcore.ps1
+
+# CoPilot instructions and prompts
+.github/copilot-instructions.md
+.github/prompts/*.md

articles/ai-foundry/concepts/model-benchmarks.md

@@ -9,8 +9,8 @@ ms.custom:
 ms.topic: concept-article
 ms.date: 04/04/2025
 ms.reviewer: changliu2
-ms.author: mopeakande
-author: msakande
+ms.author: lagayhar  
+author: lgayhardt
 ---
 
 # Model leaderboards in Azure AI Foundry portal (preview)

articles/ai-foundry/concepts/models-featured.md

@@ -27,9 +27,9 @@ To perform inferencing with the models, some models such as [Nixtla's TimeGEN-1]
 
 The Jamba family models are AI21's production-grade Mamba-based large language model (LLM) which uses AI21's hybrid Mamba-Transformer architecture. It's an instruction-tuned version of AI21's hybrid structured state space model (SSM) transformer Jamba model. The Jamba family models are built for reliable commercial use with respect to quality and performance.
 
-| Model  | Type | Capabilities | 
-| ------ | ---- | --- | 
-| [AI21-Jamba-1.5-Mini](https://ai.azure.com/explore/models/AI21-Jamba-1.5-Mini/version/1/registry/azureml-ai21) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (262,144 tokens) <br /> - **Output:**  text (4,096 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** Text, JSON, structured outputs | | 
+| Model  | Type | Capabilities |
+| ------ | ---- | --- |
+| [AI21-Jamba-1.5-Mini](https://ai.azure.com/explore/models/AI21-Jamba-1.5-Mini/version/1/registry/azureml-ai21) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (262,144 tokens) <br /> - **Output:**  text (4,096 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** Text, JSON, structured outputs |
 | [AI21-Jamba-1.5-Large](https://ai.azure.com/explore/models/AI21-Jamba-1.5-Large/version/1/registry/azureml-ai21) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (262,144 tokens) <br /> - **Output:**  text (4,096 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** Text, JSON, structured outputs |
 
 
@@ -68,10 +68,12 @@ The following table lists the Cohere models that you can inference via the  Azur
 
 | Model  | Type | Capabilities | 
 | ------ | ---- | --- | 
+| [Cohere-command-A](https://aka.ms/aistudio/landing/cohere-command-a) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (256,000 tokens) <br /> - **Output:** text (8,000 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** Text |
 | [Cohere-command-r-plus-08-2024](https://ai.azure.com/explore/models/Cohere-command-r-plus-08-2024/version/1/registry/azureml-cohere) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (131,072 tokens) <br /> - **Output:** text (4,096 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** Text, JSON |
 | [Cohere-command-r-08-2024](https://ai.azure.com/explore/models/Cohere-command-r-08-2024/version/1/registry/azureml-cohere) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (131,072 tokens) <br /> - **Output:** text (4,096 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** Text, JSON |
 | [Cohere-command-r-plus](https://ai.azure.com/explore/models/Cohere-command-r-plus/version/1/registry/azureml-cohere) <br> (deprecated) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (131,072 tokens) <br /> - **Output:** text (4,096 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** Text, JSON |
 | [Cohere-command-r](https://ai.azure.com/explore/models/Cohere-command-r/version/1/registry/azureml-cohere) <br> (deprecated)| [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (131,072 tokens) <br /> - **Output:** text (4,096 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** Text, JSON |
+| [Cohere-embed-4](https://aka.ms/aistudio/landing/cohere-embed-4) | [embeddings](../model-inference/how-to/use-embeddings.md?context=/azure/ai-foundry/context/context) <br /> [image-embeddings](../model-inference/how-to/use-image-embeddings.md?context=/azure/ai-foundry/context/context) | - **Input:** image, text <br /> - **Output:** image, text (128,000 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** image, text  |
 | [Cohere-embed-v3-english](https://ai.azure.com/explore/models/Cohere-embed-v3-english/version/1/registry/azureml-cohere) | [embeddings](../model-inference/how-to/use-embeddings.md?context=/azure/ai-foundry/context/context) <br /> [image-embeddings](../model-inference/how-to/use-image-embeddings.md?context=/azure/ai-foundry/context/context) | - **Input:** text (512 tokens) <br /> - **Output:** Vector (1,024 dim.) |
 | [Cohere-embed-v3-multilingual](https://ai.azure.com/explore/models/Cohere-embed-v3-multilingual/version/1/registry/azureml-cohere) | [embeddings](../model-inference/how-to/use-embeddings.md?context=/azure/ai-foundry/context/context) <br /> [image-embeddings](../model-inference/how-to/use-image-embeddings.md?context=/azure/ai-foundry/context/context) | - **Input:** text (512 tokens) <br /> - **Output:** Vector (1,024 dim.) |
 
@@ -207,10 +209,12 @@ For more examples of how to use Meta Llama models, see the following examples:
 
 ## Microsoft
 
-Phi is a family of lightweight, state-of-the-art open models. These models were trained with Phi-3 datasets. The datasets include both synthetic data and the filtered, publicly available websites data, with a focus on high quality and reasoning-dense properties. The models underwent a rigorous enhancement process, incorporating both supervised fine-tuning, proximal policy optimization, and direct preference optimization to ensure precise instruction adherence and robust safety measures.
+Microsoft models include various model groups such as MAI models, Phi models, healthcare AI models, and more. To see all the available Microsoft models, view [the Microsoft model collection in Azure AI Foundry portal](https://ai.azure.com/explore/models?&selectedCollection=phi).
+
 
 | Model  | Type | Capabilities |
 | ------ | ---- | ------------ |
+| [MAI-DS-R1](https://ai.azure.com/explore/models/MAI-DS-R1/version/1/registry/azureml) | [chat-completion with reasoning content](../model-inference/how-to/use-chat-reasoning.md?context=/azure/ai-foundry/context/context) | - **Input:** text (163,840 tokens) <br /> - **Output:** text (163,840 tokens) <br />  - **Tool calling:** No <br /> - **Response formats:** Text. |
 | [Phi-4-multimodal-instruct](https://ai.azure.com/explore/models/Phi-4-multimodal-instruct/version/1/registry/azureml) | [chat-completion (with image and audio content)](../model-inference/how-to/use-chat-multi-modal.md?context=/azure/ai-foundry/context/context) | - **Input:** text, images, and audio (131,072 tokens) <br /> - **Output:** text (4,096 tokens) <br /> - **Tool calling:** No <br /> - **Response formats:** Text |
 | [Phi-4-mini-instruct](https://ai.azure.com/explore/models/Phi-4-mini-instruct/version/1/registry/azureml) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (131,072 tokens) <br /> - **Output:** text (4,096 tokens) <br />  - **Tool calling:** No <br /> - **Response formats:** Text |
 | [Phi-4](https://ai.azure.com/explore/models/Phi-4/version/2/registry/azureml) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (16,384 tokens) <br /> - **Output:** text (16,384 tokens) <br /> - **Tool calling:** No <br /> - **Response formats:** Text |
@@ -224,12 +228,9 @@ Phi is a family of lightweight, state-of-the-art open models. These models were
 | [Phi-3-medium-128k-instruct](https://ai.azure.com/explore/models/Phi-3-medium-128k-instruct/version/6/registry/azureml) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (131,072 tokens) <br /> - **Output:** text (4,096 tokens) <br />  - **Tool calling:** No <br /> - **Response formats:** Text |
 | [Phi-3-medium-4k-instruct](https://ai.azure.com/explore/models/Phi-3-medium-4k-instruct/version/5/registry/azureml) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (4,096 tokens) <br /> - **Output:** text (4,096 tokens) <br />  - **Tool calling:** No <br /> - **Response formats:** Text |
 
+#### Inference examples: Microsoft models
 
-See [this model collection in Azure AI Foundry portal](https://ai.azure.com/explore/models?&selectedCollection=phi).
-
-#### Inference examples: Microsoft Phi
-
-For more examples of how to use Phi-3 family models, see the following examples:    
+For more examples of how to use Microsoft models, see the following examples:    
 
 | Description                               | Language          | Sample                                                          |    
 |-------------------------------------------|-------------------|-----------------------------------------------------------------|    
@@ -240,6 +241,9 @@ For more examples of how to use Phi-3 family models, see the following examples:
 | Llama-Index                               | Python            | [Link](https://aka.ms/azureai/llamaindex)             |  
 
 
+See [the Microsoft model collection in Azure AI Foundry portal](https://ai.azure.com/explore/models?&selectedCollection=phi).
+
+
 ## Mistral AI
 
 Mistral AI offers two categories of models, namely: 

articles/ai-foundry/how-to/benchmark-model-in-catalog.md

@@ -10,8 +10,8 @@ ms.topic: how-to
 ms.date: 04/07/2025
 ms.reviewer: changliu2
 reviewer: changliu2
-ms.author: mopeakande
-author: msakande
+ms.author: lagayhar  
+author: lgayhardt
 ---
 
 # Compare and select models using the model leaderboard in Azure AI Foundry portal (preview)

articles/ai-foundry/how-to/configure-private-link.md

@@ -10,6 +10,7 @@ ms.date: 01/15/2025
 ms.reviewer: meerakurup
 ms.author: larryfr
 author: Blackmist
+zone_pivot_groups: azure-portal-and-cli
 # Customer intent: As an admin, I want to configure a private link for hub so that I can secure my hubs.
 ---
 
@@ -25,7 +26,6 @@ You get several hub default resources in your resource group. You need to config
 - Establish private endpoint connection to hub default resources. You need to have both a blob and file private endpoint for the default storage account.
 - If your storage account is private, [assign roles](#private-storage-configuration) to allow access.
 
-
 ## Prerequisites
 
 * You must have an existing Azure Virtual Network to create the private endpoint in. 
@@ -37,9 +37,9 @@ You get several hub default resources in your resource group. You need to config
 
 ## Create a hub that uses a private endpoint
 
-If you are creating a new hub, use the following tabs to select how you are creating the hub (Azure portal or Azure CLI.) Each of these methods __requires an existing virtual network__:
+If you are creating a new hub, use the following methods to create the hub (Azure portal or Azure CLI). Each of these methods __requires an existing virtual network__:
 
-# [Azure portal](#tab/azure-portal)
+:::zone pivot="azure-portal"
 
 > [!NOTE]
 > The information in this document is only about configuring a private link. For a walkthrough of creating a secure hub in the portal, see [Create a secure hub in the Azure portal](create-secure-ai-hub.md).
@@ -55,7 +55,9 @@ If you are creating a new hub, use the following tabs to select how you are crea
 
 1. Input required fields. When selecting the __Region__, select the same region as your virtual network.
 
-# [Azure CLI](#tab/cli)
+:::zone-end
+
+:::zone pivot="cli"
 
 > [!NOTE]
 > The information in this section doesn't cover basic hub configuration. For more information, see [Create a hub using the Azure CLI](./develop/create-hub-project-sdk.md?tabs=azurecli).
@@ -95,34 +97,17 @@ az network private-endpoint dns-zone-group create \
     --name myzonegroup \
     --private-dns-zone privatelink.api.azureml.ms \
     --zone-name privatelink.api.azureml.ms
-
-# Add privatelink.notebooks.azure.net
-az network private-dns zone create \
-    -g <resource-group-name> \
-    --name privatelink.notebooks.azure.net
-
-az network private-dns link vnet create \
-    -g <resource-group-name> \
-    --zone-name privatelink.notebooks.azure.net \
-    --name <link-name> \
-    --virtual-network <vnet-name> \
-    --registration-enabled false
-
-az network private-endpoint dns-zone-group add \
-    -g <resource-group-name> \
-    --endpoint-name <private-endpoint-name> \
-    --name myzonegroup \
-    --private-dns-zone privatelink.notebooks.azure.net \
-    --zone-name privatelink.notebooks.azure.net
 ```
 
+:::zone-end
+
 ---
 
 ## Add a private endpoint to a hub
 
 Use one of the following methods to add a private endpoint to an existing hub:
 
-# [Azure portal](#tab/azure-portal)
+:::zone pivot="azure-portal"
 
 1. From the [Azure portal](https://portal.azure.com), select your hub.
 1. From the left side of the page, select __Settings__, __Networking__, and then select the __Private endpoint connections__ tab. Select __+ Private endpoint__.
@@ -131,13 +116,15 @@ Use one of the following methods to add a private endpoint to an existing hub:
 
 1. When going through the forms to create a private endpoint, be sure to:
 
-    - From __Basics__, select the same the __Region__ as your virtual network.
+    - From __Basics__, select the same __Region__ as your virtual network.
     - From __Resource__, select `amlworkspace` as the __target sub-resource__.
     - From the __Virtual Network__ form, select the virtual network and subnet that you want to connect to.
 
 1. After populating the forms with any additional network configurations you require, use the __Review + create__ tab to review your settings and select __Create__ to create the private endpoint.
 
-# [Azure CLI](#tab/cli)
+:::zone-end
+
+:::zone pivot="cli"
 
 Use the [Azure networking CLI commands](/cli/azure/network/private-endpoint#az-network-private-endpoint-create) to create a private link endpoint for the hub.
 
@@ -159,11 +146,11 @@ To create the private DNS zone entries for the workspace, use the following comm
 # Add privatelink.api.azureml.ms
 az network private-dns zone create \
     -g <resource-group-name> \
-    --name 'privatelink.api.azureml.ms'
+    --name privatelink.api.azureml.ms
 
 az network private-dns link vnet create \
     -g <resource-group-name> \
-    --zone-name 'privatelink.api.azureml.ms' \
+    --zone-name privatelink.api.azureml.ms \
     --name <link-name> \
     --virtual-network <vnet-name> \
     --registration-enabled false
@@ -172,17 +159,17 @@ az network private-endpoint dns-zone-group create \
     -g <resource-group-name> \
     --endpoint-name <private-endpoint-name> \
     --name myzonegroup \
-    --private-dns-zone 'privatelink.api.azureml.ms' \
-    --zone-name 'privatelink.api.azureml.ms'
+    --private-dns-zone privatelink.api.azureml.ms \
+    --zone-name privatelink.api.azureml.ms
 
 # Add privatelink.notebooks.azure.net
 az network private-dns zone create \
     -g <resource-group-name> \
-    --name 'privatelink.notebooks.azure.net'
+    --name privatelink.notebooks.azure.net
 
 az network private-dns link vnet create \
     -g <resource-group-name> \
-    --zone-name 'privatelink.notebooks.azure.net' \
+    --zone-name privatelink.notebooks.azure.net \
     --name <link-name> \
     --virtual-network <vnet-name> \
     --registration-enabled false
@@ -191,10 +178,12 @@ az network private-endpoint dns-zone-group add \
     -g <resource-group-name> \
     --endpoint-name <private-endpoint-name> \
     --name myzonegroup \
-    --private-dns-zone 'privatelink.notebooks.azure.net' \
-    --zone-name 'privatelink.notebooks.azure.net'
+    --private-dns-zone privatelink.notebooks.azure.net \
+    --zone-name privatelink.notebooks.azure.net
 ```
 
+:::zone-end
+
 ---
 
 ## Remove a private endpoint
@@ -206,24 +195,28 @@ You can remove one or all private endpoints for a hub. Removing a private endpoi
 
 To remove a private endpoint, use the following information:
 
-# [Azure portal](#tab/azure-portal)
+:::zone pivot="azure-portal"
 
 1. From the [Azure portal](https://portal.azure.com), select your hub.
 1. From the left side of the page, select __Settings__, __Networking__, and then select the __Private endpoint connections__ tab.
 1. Select the endpoint to remove and then select __Remove__.
 
     :::image type="content" source="../media/how-to/network/remove-private-endpoint.png" alt-text="Screenshot of a selected private endpoint with the remove option highlighted.":::
 
-# [Azure CLI](#tab/cli)
+:::zone-end
+
+:::zone pivot="cli"
 
 When using the Azure CLI, use the following command to remove the private endpoint:
 
 ```azurecli
 az network private-endpoint delete \
     --name <private-endpoint-name> \
-    --resource-group <resource-group-name> \
+    --resource-group <resource-group-name>
 ```
 
+:::zone-end
+
 ---
 
 ## Enable public access
@@ -235,13 +228,15 @@ In some situations, you might want to allow someone to connect to your secured h
 
 To enable public access, use the following steps:
 
-# [Azure portal](#tab/azure-portal)
+:::zone pivot="azure-portal"
 
 1. From the [Azure portal](https://portal.azure.com), select your hub.
 1. From the left side of the page, select __Networking__ and then select the __Public access__ tab.
 1. Select __Enabled from all networks__, and then select __Save__.
 
-# [Azure CLI](#tab/cli)
+:::zone-end
+
+:::zone pivot="cli"
 
 Use the following Azure CLI command to enable public access:
 
@@ -255,8 +250,9 @@ If you receive an error that the `ml` command isn't found, use the following com
 az extension add --name ml
 ```
 
----
+:::zone-end
 
+---
 
 ## Private storage configuration