Merge branch 'main' into release-scommi

Author: v-alje

articles/active-directory-b2c/oauth2-error-technical-profile.md

@@ -9,7 +9,7 @@ manager: CelesteDG
 ms.service: active-directory
 
 ms.topic: reference
-ms.date: 01/11/2024
+ms.date: 05/07/2024
 ms.author: kengaderdus
 ms.subservice: B2C
 
@@ -73,6 +73,43 @@ The following example shows a technical profile for `ReturnOAuth2Error`:
 </ClaimsProviders> -->
 ```
 
+## Define claims transformation to generate custom values of error code and error message
+
+Use these steps to generate custom values of error code and error message:
+
+1. Locate the `ClaimsTransformations` element, then add the following code inside it
+
+    ```xml
+    <!--
+     <ClaimsTransformations> -->
+    <ClaimsTransformation Id="GenerateErrorCode" TransformationMethod="CreateStringClaim">
+            <InputParameters>
+              <InputParameter Id="value" DataType="string" Value="Error_001" />
+            </InputParameters>
+            <OutputClaims>
+              <OutputClaim ClaimTypeReferenceId="errorCode" TransformationClaimType="createdClaim" />
+            </OutputClaims>
+          </ClaimsTransformation>
+          <ClaimsTransformation Id="GenerateErrorMessage" TransformationMethod="CreateStringClaim">
+            <InputParameters>
+              <InputParameter Id="value" DataType="string" Value="Insert error description." />
+            </InputParameters>
+            <OutputClaims>
+              <OutputClaim ClaimTypeReferenceId="errorMessage" TransformationClaimType="createdClaim" />
+            </OutputClaims>
+          </ClaimsTransformation>
+    <!--
+    </ClaimsTransformations> -->
+    ```
+
+1. Add the two claims transformations in the `OutputClaimsTransformations` element of any technical profile before Oauth2 technical that you define:
+
+    ```xml
+        <OutputClaimsTransformations>
+          <OutputClaimsTransformation ReferenceId="generateErrorCode" />
+          <OutputClaimsTransformation ReferenceId="generateErrorMessage" />
+        </OutputClaimsTransformations>
+    ```
 ## Input claims
 
 The **InputClaims** element contains a list of claims required to return OAuth2 error. 
@@ -123,6 +160,20 @@ In the following example:
 </UserJourney>
 ```
 
+Optionally, you can use preconditions to manipulate the Oauth2 error technical profile. For example, if there is no email claim, you can set to call Oauth2 error technical profile:
+
+```xml
+<OrchestrationStep Order="3" Type="SendClaims" CpimIssuerTechnicalProfileReferenceId="ReturnOAuth2Error">
+      <Preconditions>
+        <Precondition Type="ClaimsExist" ExecuteActionsIf="false">
+          <Value>email</Value>
+          <Action>SkipThisOrchestrationStep</Action>
+        </Precondition>
+      </Preconditions>
+    </OrchestrationStep>
+```
+
+
 ## Next steps
 
 Learn about [UserJourneys](userjourneys.md)

articles/ai-services/openai/concepts/model-retirements.md

@@ -66,9 +66,9 @@ These models are currently available for use in Azure OpenAI Service.
 | `gpt-35-turbo` | 0125 | No earlier than Feb 22, 2025 |
 | `gpt-4`<br>`gpt-4-32k` | 0314 | No earlier than July 13, 2024 |
 | `gpt-4`<br>`gpt-4-32k` | 0613 | No earlier than Sep 30, 2024 |
-| `gpt-4` | 1106-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on June 10, 2024, or later **<sup>1</sup>** |
-| `gpt-4` | 0125-preview |To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on June 10, 2024, or later  **<sup>1</sup>**  |
-| `gpt-4` | vision-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on June 10, 2024, or later  **<sup>1</sup>** |
+| `gpt-4` | 1106-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on July 15, 2024, or later **<sup>1</sup>** |
+| `gpt-4` | 0125-preview |To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on July 15, 2024, or later  **<sup>1</sup>**  |
+| `gpt-4` | vision-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on July 15, 2024, or later  **<sup>1</sup>** |
 | `gpt-3.5-turbo-instruct` | 0914 | No earlier than Sep 14, 2025 |
 | `text-embedding-ada-002` | 2 | No earlier than April 3, 2025 |
 | `text-embedding-ada-002` | 1 | No earlier than April 3, 2025 |

articles/ai-services/openai/faq.yml

@@ -265,6 +265,7 @@ sections:
         answer: |
           * Inference cost (input and output) of the base model you're using for each Assistant (for example gpt-4-0125). If you've created multiple Assistants, you will be charged for the base model attached to each Assistant.
           * If you've enabled the Code Interpreter tool. For example if your assistant calls Code Interpreter simultaneously in two different threads, this would create two Code Interpreter sessions, each of which would be charged. Each session is active by default for one hour, which means that you would only pay this fee once if your user keeps giving instructions to Code Interpreter in the same thread for up to one hour.
+          * File search is currently not billed. 
 
           For more information, see the [pricing page](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/).
       - question: |

articles/ai-services/speech-service/captioning-concepts.md

@@ -27,7 +27,7 @@ The following are aspects to consider when using captioning:
 * Let your audience know that captions are generated by an automated service.
 * Center captions horizontally on the screen, in a large and prominent font. 
 * Consider whether to use partial results, when to start displaying captions, and how many words to show at a time. 
-* Learn about captioning protocols such as [SMPTE-TT](https://ieeexplore.ieee.org/document/7291854). 
+* Learn about captioning protocols such as [SMPTE-TT](https://pub.smpte.org/doc/st2052-1/20101203-pub/st2052-1-2010.pdf). 
 * Consider output formats such as SRT (SubRip Text) and WebVTT (Web Video Text Tracks). These can be loaded onto most video players such as VLC, automatically adding the captions on to your video.
 
 > [!TIP]

articles/ai-services/speech-service/includes/speech-studio-vnet.md

@@ -26,9 +26,9 @@ This section describes working with the different kind of Speech Studio projects
 1. In the **Resource Management** group in the left pane, select **Networking** > **Firewalls and virtual networks**. 
 1. Select one option from **All networks**, **Selected Networks and Private Endpoints**, or **Disabled**. 
 
-#### Custom speech
+#### Custom speech, Custom voice and Audio Content Creation
 
-The following table describes custom speech project accessibility per Speech resource **Networking** > **Firewalls and virtual networks** security setting.
+The following table describes custom speech/custom voice/audio content creation project accessibility per Speech resource **Networking** > **Firewalls and virtual networks** security setting.
 
 > [!NOTE]
 > If you allow only private endpoints via the **Networking** > **Private endpoint connections** tab, then you can't use Speech Studio with the Speech resource. You can still use the Speech resource outside of Speech Studio.  
@@ -47,6 +47,4 @@ To use custom speech without relaxing network access restrictions on your produc
 * Create another Speech resource for development that can be used on a public network. Prepare your custom model in Speech Studio on the development resource, and then copy the model to your production resource. See the [Models_CopyTo](/rest/api/speechtotext/models/copy-to) REST request with [Speech to text REST API](../rest-speech-to-text.md).
 * You have the option to not use Speech Studio for custom speech. Use the [Speech to text REST API](../rest-speech-to-text.md) for all custom speech operations. 
 
-#### Custom voice and Audio Content Creation
-
-You can use custom voice and Audio Content Creation Speech Studio projects only when the Speech resource network security setting is **All networks**.
+To use custom voice without relaxing network access restrictions on your production Speech resource, consider Use the [Custom voice REST API](/rest/api/speechapi/operation-groups?&preserve-view=true=rest-speechapi-2023-12-01-preview) for all custom voice operations.

articles/ai-studio/how-to/create-projects.md

@@ -1,7 +1,7 @@
 ---
 title: Create an Azure AI Studio project in Azure AI Studio
 titleSuffix: Azure AI Studio
-description: This article describes how to create an Azure AI Studio project.
+description: This article describes how to create an Azure AI Studio project from an Azure AI Studio hub that was previously created.
 manager: scottpolly
 ms.service: azure-ai-studio
 ms.custom:
@@ -12,20 +12,69 @@ ms.date: 5/21/2024
 ms.reviewer: deeikele
 ms.author: sgilley
 author: sdgilley
+# customer intent: As a developer, I want to create an Azure AI Studio project so I can work with generative AI.
 ---
 
 # Create a project in Azure AI Studio
 
-This article describes how to create a project in Azure AI Studio. A project is used to organize your work and save state while building customized AI apps. 
+This article describes how to create an Azure AI Studio project. A project is used to organize your work and save state while building customized AI apps. 
 
 Projects are hosted by an Azure AI Studio hub that provides enterprise-grade security and a collaborative environment. For more information about the projects and resources model, see [Azure AI Studio hubs](../concepts/ai-resources.md).
 
 ## Create a project
 
+Use the following tabs to select the method you plan to use to create a project:
+
+# [Azure AI Studio](#tab/ai-studio)
+
 [!INCLUDE [Create Azure AI Studio project](../includes/create-projects.md)]
 
+# [Python SDK](#tab/python)
+
+[!INCLUDE [SDK setup](../includes/development-environment-config.md)]
+
+8. Use the following code to create a project from a hub you or your administrator created previously. Replace example string values with your own values:
+
+    ```Python
+    from azure.ai.ml.entities import Project
+
+    my_project_name = "myexampleproject"
+    my_location = "East US"
+    my_display_name = "My Example Project"
+    hub_id = "" # Azure resource manager ID of the hub
+
+    my_project = Project(name=my_hub_name, 
+                    location=my_location,
+                    display_name=my_display_name,
+                    hub_id=created_hub.id)
+
+    created_project = ml_client.workspaces.begin_create(workspace=my_hub).result() 
+    ```
+
+# [Azure CLI](#tab/azurecli)
+
+1. If you don't have the Azure CLI and machine learning extension installed, follow the steps in the [Install and set up the machine learning extension](/azure/machine-learning/how-to-configure-cli) article.
+
+1. To authenticate to your Azure subscription from the Azure CLI, use the following command:
+
+    ```azurecli
+    az login
+    ```
+
+    For more information on authenticating, see [Authentication methods](/cli/azure/authenticate-azure-cli).
+
+1. Once the extension is installed and authenticated to your Azure subscription, use the following command to create a new Azure AI project from an existing Azure AI hub:
+
+    ```azurecli
+    az ml workspace create --kind project --hub-id {my_hub_ARM_ID} --resource-group {my_resource_group} --name {my_project_name}
+    ```
+
+---
+
 ## Project settings
 
+# [Azure AI Studio](#tab/ai-studio)
+
 On the project **Settings** page you can find information about the project, such as the project name, description, and the hub that hosts the project. You can also find the project ID, which is used to identify the project via SDK or API.
 
 :::image type="content" source="../media/how-to/projects/project-settings.png" alt-text="Screenshot of an AI Studio project settings page." lightbox = "../media/how-to/projects/project-settings.png":::
@@ -38,6 +87,25 @@ On the project **Settings** page you can find information about the project, suc
 
 Select **Manage in the Azure portal** to navigate to the project resources in the Azure portal.
 
+# [Python SDK](#tab/python)
+
+To manage or use the new project, include it in the `MLClient`:
+
+```python
+ml_client = MLClient(workspace_name=my_project_name, resource_group_name=my_resource_group, subscription_id=my_subscription_id,credential=DefaultAzureCredential())
+```
+
+# [Azure CLI](#tab/azurecli)
+
+To view settings for the project, use the `az ml workspace show` command. For example:
+
+```azurecli
+az ml workspace show --name {my_project_name} --resource-group {my_resource_group}
+```
+
+
+---
+
 ## Next steps
 
 - [Deploy an enterprise chat web app](../tutorials/deploy-chat-web-app.md)

articles/ai-studio/how-to/develop/create-hub-project-sdk.md

@@ -1,7 +1,7 @@
 ---
-title: How to create a hub and project using the Azure Machine Learning SDK
+title: How to create a hub using the Azure Machine Learning SDK/CLI
 titleSuffix: Azure AI Studio
-description: This article provides instructions on how to create an AI Studio hub and project using the Azure Machine Learning SDK.
+description: This article provides instructions on how to create an AI Studio hub using the Azure Machine Learning SDK and Azure CLI extension.
 manager: nitinme
 ms.service: azure-ai-studio
 ms.custom:
@@ -13,30 +13,48 @@ ms.author: eur
 author: eric-urban
 ---
 
-# Create a hub and project using the Azure Machine Learning SDK
+# Create a hub using the Azure Machine Learning SDK and CLI
 
 [!INCLUDE [Feature preview](~/reusable-content/ce-skilling/azure/includes/ai-studio/includes/feature-preview.md)]
 
-In this article, you learn how to create the following AI Studio resources using the Azure Machine Learning SDK:
+In this article, you learn how to create the following AI Studio resources using the Azure Machine Learning SDK and Azure CLI (with machine learning extension):
 - An Azure AI Studio hub
 - An Azure AI Services connection
-- An Azure AI Studio project
 
 ## Prerequisites
 
 - An Azure subscription. If you don't have an Azure subscription, create a free account before you begin. Try the [free or paid version of Azure AI Studio](https://azure.microsoft.com/free/) today.
 
 ## Set up your environment
 
+Use the following tabs to select whether you're using the Python SDK or Azure CLI:
+
+# [Python SDK](#tab/python)
+
 [!INCLUDE [SDK setup](../../includes/development-environment-config.md)]
 
+# [Azure CLI](#tab/azurecli)
+
+1. If you don't have the Azure CLI and machine learning extension installed, follow the steps in the [Install and set up the machine learning extension](/azure/machine-learning/how-to-configure-cli) article.
+
+1. To authenticate to your Azure subscription from the Azure CLI, use the following command:
+
+    ```azurecli
+    az login
+    ```
+
+    For more information on authenticating, see [Authentication methods](/cli/azure/authenticate-azure-cli).
+
+---
+
 ## Create the AI Studio hub and AI Services connection
 
-Use the following code to create a new hub and AI Services connection. Replace example string values with your own values:
+Use the following examples to create a new hub. Replace example string values with your own values:
+
+# [Python SDK](#tab/python)
 
 ```Python
 from azure.ai.ml.entities import Hub
-from azure.ai.ml.entities import AzureAIServicesConnection
 
 my_hub_name = "myexamplehub"
 my_location = "East US"
@@ -49,49 +67,69 @@ my_hub = Hub(name=my_hub_name,
 
 created_hub = ml_client.workspaces.begin_create(my_hub).result()
 
+```
+
+# [Azure CLI](#tab/azurecli)
+
+```azurecli
+az ml workspace create --kind hub --resource-group {my_resource_group} --name {my_hub_name}
+```
+
+---
+
+## Create an AI Services connection
+
+After creating your own AI Services, you can connect it to your hub:
+
+# [Python SDK](#tab/python)
+
+```python
+from azure.ai.ml.entities import AzureAIServicesConnection
+
 # constrict an AI Services connection
 my_connection_name = "myaiservivce"
 my_endpoint = "demo.endpoint" # this could also be called target
 my_api_keys = None # leave blank for Authentication type = AAD
 my_ai_services_resource_id = "" # ARM id required
 
-my_connection = AIServicesConnection(name=my_connection_name,
+my_connection = AzureAIServicesConnection(name=my_connection_name,
                                     endpoint=my_endpoint, 
                                     api_key= my_api_keys,
                                     ai_services_resource_id=my_ai_services_resource_id)
 
+# Create the connection
 ml_client.connections.create_or_update(my_connection)
 ```
 
-## Create AI Studio project
+# [Azure CLI](#tab/azurecli)
 
-Use the following code to create a project from the hub you created previously. Replace example string values with your own values:
-
-```Python
-from azure.ai.ml.entities import Project
+```azurecli
+az ml connection create --file {connection.yml} --resource-group {my_resource_group} --workspace-name {my_hub_name}
+```
 
-my_project_name = "myexampleproject"
-my_location = "East US"
-my_display_name = "My Example Project"
+You can use either an API key or credential-less YAML configuration file. For more information on the YAML configuration file, see the [AI Services connection YAML schema](/azure/machine-learning/reference-yaml-connection-ai-services):
 
-my_hub = Project(name=my_hub_name, 
-                location=my_location,
-                display_name=my_display_name,
-                hub_id=created_hub.id)
+- API Key example:
 
-created_project = ml_client.workspaces.begin_create(workspace=my_hub).result() 
-```
+    ```yml
+    name: myazai_ei
+    type: azure_ai_services
+    endpoint: https://contoso.cognitiveservices.azure.com/
+    api_key: XXXXXXXXXXXXXXX
+    ```
 
-## Update the MLClient
+- Credential-less
 
-To use the new project, include it in the `MLClient`.
+    ```yml    
+    name: myazai_apk
+    type: azure_ai_services
+    endpoint: https://contoso.cognitiveservices.azure.com/
+    ```
 
-```python
-ml_client = MLClient(workspace_name=my_project_name, resource_group_name=my_resource_group, subscription_id=my_subscription_id,credential=DefaultAzureCredential())
-```
+---
 
 ## Related content
 
 - [Get started building a chat app using the prompt flow SDK](../../quickstarts/get-started-code.md)
-- [Work with projects in VS Code](vscode.md)
+- [Work with projects in Visual Studio Code](vscode.md)
 - [Configure a managed network](../configure-managed-network.md?tabs=python)

articles/ai-studio/toc.yml

@@ -48,11 +48,11 @@ items:
       - name: Create a hub in the Azure portal
         href: how-to/create-secure-ai-hub.md
       - name: Create a hub from template
-        href: how-to/create-azure-ai-hub-template.md      
+        href: how-to/create-azure-ai-hub-template.md
+      - name: Create a hub using the Azure Machine Learning SDK and CLI
+        href: how-to/develop/create-hub-project-sdk.md
     - name: Create a project
       href: how-to/create-projects.md
-    - name: Create a hub and project using the Azure Machine Learning SDK
-      href: how-to/develop/create-hub-project-sdk.md
     - name: Create and manage compute
       href: how-to/create-manage-compute.md
     - name: Connect to external resources