Merge pull request #275772 from MicrosoftDocs/release-build-azure-ai-studio-follow

Release build azure ai studio follow--scheduled release at 10am of 5/21

Author: huypub

articles/ai-services/content-safety/includes/openai-account-access.md

@@ -0,0 +1,27 @@
+---
+title: "Azure OpenAI account access"
+description: Azure OpenAI account access
+author: PatrickFarley
+manager: nitinme
+ms.service: azure-ai-content-safety
+ms.topic: include
+ms.date: 04/12/2024
+ms.author: pafarley
+---
+
+
+1. Enable Managed Identity for Azure AI Content Safety.
+
+    Navigate to your Azure AI Content Safety instance in the Azure portal. Find the **Identity** section under the **Settings** category. Enable the system-assigned managed identity. This action grants your Azure AI Content Safety instance an identity that can be recognized and used within Azure for accessing other resources. 
+
+    :::image type="content" source="/azure/ai-services/content-safety/media/content-safety-identity.png" alt-text="Screenshot of a Content Safety identity resource in the Azure portal." lightbox="/azure/ai-services/content-safety/media/content-safety-identity.png":::
+
+1. Assign role to Managed Identity.
+
+    Navigate to your Azure OpenAI instance, select **Add role assignment** to start the process of assigning an Azure OpenAI role to the Azure AI Content Safety identity. 
+
+    :::image type="content" source="/azure/ai-services/content-safety/media/add-role-assignment.png" alt-text="Screenshot of adding role assignment in Azure portal.":::
+
+    Choose the **User** or **Contributor** role.
+
+    :::image type="content" source="/azure/ai-services/content-safety/media/assigned-roles-simple.png" alt-text="Screenshot of the Azure portal with the Contributor and User roles displayed in a list." lightbox="/azure/ai-services/content-safety/media/assigned-roles-simple.png":::

articles/ai-services/openai/concepts/content-filter.md

@@ -59,21 +59,26 @@ The content filtering system integrated in the Azure OpenAI Service contains:
 
 ## Configurability (preview)
 
-The default content filtering configuration is set to filter at the medium severity threshold for all four content harm categories for both prompts and completions. That means that content that is detected at severity level medium or high is filtered, while content detected at severity level low isn't filtered by the content filters. The configurability feature is available in preview and allows customers to adjust the settings, separately for prompts and completions, to filter content for each content category at different severity levels as described in the table below:
+The default content filtering configuration for the GPT model series is set to filter at the medium severity threshold for all four content harm categories (hate, violence, sexual, and self-harm) and applies to both prompts (text, multi-modal text/image) and completions (text). This means that content that is detected at severity level medium or high is filtered, while content detected at severity level low isn't filtered by the content filters. For DALL-E, the default severity threshold is set to low for both prompts (text) and completions (images), so content detected at severity levels low, medium, or high is filtered. The configurability feature is available in preview and allows customers to adjust the settings, separately for prompts and completions, to filter content for each content category at different severity levels as described in the table below:
 
 | Severity filtered | Configurable for prompts | Configurable for completions | Descriptions |
 |-------------------|--------------------------|------------------------------|--------------|
-| Low, medium, high | Yes | Yes | Strictest filtering configuration. Content detected at severity levels low, medium, and high is filtered.|
-| Medium, high      | Yes | Yes | Default setting. Content detected at severity level low isn't filtered, content at medium and high is filtered.|
-| High              | Yes| Yes | Content detected at severity levels low and medium isn't filtered. Only content at severity level high is filtered.|
-| No filters | If approved<sup>\*</sup>| If approved<sup>\*</sup>| No content is filtered regardless of severity level detected. Requires approval<sup>\*</sup>.|
+| Low, medium, high | Yes | Yes | Strictest filtering configuration. Content detected at severity levels low, medium and high is filtered.|
+| Medium, high      | Yes | Yes | Content detected at severity level low isn't filtered, content at medium and high is filtered.|
+| High              | If approved<sup>1</sup>| If approved<sup>1</sup> | Content detected at severity levels low and medium isn't filtered. Only content at severity level high is filtered. Requires approval<sup>1</sup>.|
+| No filters | If approved<sup>1</sup>| If approved<sup>1</sup>| No content is filtered regardless of severity level detected. Requires approval<sup>1</sup>.|
 
-<sup>\*</sup> Only customers who have been approved for modified content filtering have full content filtering control and can turn content filters partially or fully off. Content filtering control doesn't apply to content filters for DALL-E (preview) or GPT-4 Turbo with Vision (preview). Apply for modified content filters using this form: [Azure OpenAI Limited Access Review: Modified Content Filtering (microsoft.com)](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUMlBQNkZMR0lFRldORTdVQzQ0TEI5Q1ExOSQlQCN0PWcu). 
+<sup>1</sup> For Azure OpenAI models, only customers who have been approved for modified content filtering have full content filtering control, including configuring content filters at severity level high only or turning off content filters. Apply for modified content filters via this form: [Azure OpenAI Limited Access Review: Modified Content Filters and Abuse Monitoring (microsoft.com)](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xURE01NDY1OUhBRzQ3MkQxMUhZSE1ZUlJKTiQlQCN0PWcu)
 
-Customers are responsible for ensuring that applications integrating Azure OpenAI comply with the [Code of Conduct](/legal/cognitive-services/openai/code-of-conduct?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext). 
+This preview feature is available for the following Azure OpenAI models:
+* GPT model series (text) 
+* GPT-4 Turbo Vision 2024-04-09 (multi-modal text/image)
+* DALL-E 2 and 3 (image)
 
 Content filtering configurations are created within a Resource in Azure AI Studio, and can be associated with Deployments. [Learn more about configurability here](../how-to/content-filters.md).  
 
+Customers are responsible for ensuring that applications integrating Azure OpenAI comply with the [Code of Conduct](/legal/cognitive-services/openai/code-of-conduct?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext). 
+
 ## Scenario details
 
 When the content filtering system detects harmful content, you receive either an error on the API call if the prompt was deemed inappropriate, or the `finish_reason` on the response will be `content_filter` to signify that some of the completion was filtered. When building your application or system, you'll want to account for these scenarios where the content returned by the Completions API is filtered, which might result in content that is incomplete. How you act on this information will be application specific. The behavior can be summarized in the following points:
@@ -815,27 +820,29 @@ The escaped text in a chat completion context would read:
 
 ## Content streaming
 
-This section describes the Azure OpenAI content streaming experience and options. With approval, you have the option to receive content from the API as it's generated, instead of waiting for chunks of content that have been verified to pass your content filters.
+This section describes the Azure OpenAI content streaming experience and options. Customers have the option to receive content from the API as it's generated, instead of waiting for chunks of content that have been verified to pass your content filters.
 
 ### Default
 
 The content filtering system is integrated and enabled by default for all customers. In the default streaming scenario, completion content is buffered, the content filtering system runs on the buffered content, and – depending on the content filtering configuration – content is either returned to the user if it doesn't violate the content filtering policy (Microsoft's default or a custom user configuration), or it’s immediately blocked and returns a content filtering error, without returning the harmful completion content. This process is repeated until the end of the stream. Content is fully vetted according to the content filtering policy before it's returned to the user. Content isn't returned token-by-token in this case, but in “content chunks” of the respective buffer size.
 
-### Asynchronous modified filter
+### Asynchronous Filter
 
-Customers who have been approved for modified content filters can choose the asynchronous modified filter as an additional option, providing a new streaming experience. In this case, content filters are run asynchronously, and completion content is returned immediately with a smooth token-by-token streaming experience. No content is buffered, which allows for zero latency.
+Customers can choose the Asynchronous Filter as an additional option, providing a new streaming experience. In this case, content filters are run asynchronously, and completion content is returned immediately with a smooth token-by-token streaming experience. No content is buffered, which allows for a fast streaming experience with zero latency associated with content safety.
 
 Customers must be aware that while the feature improves latency, it's a trade-off against the safety and real-time vetting of smaller sections of model output. Because content filters are run asynchronously, content moderation messages and policy violation signals are delayed, which means some sections of harmful content that would otherwise have been filtered immediately could be displayed to the user.
  
 **Annotations**: Annotations and content moderation messages are continuously returned during the stream. We strongly recommend you consume annotations in your app and implement additional AI content safety mechanisms, such as redacting content or returning additional safety information to the user.
 
 **Content filtering signal**: The content filtering error signal is delayed. In case of a policy violation, it’s returned as soon as it’s available, and the stream is stopped. The content filtering signal is guaranteed within a ~1,000-character window of the policy-violating content. 
 
-Approval for modified content filtering is required for access to the asynchronous modified filter. The application can be found [here](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xURE01NDY1OUhBRzQ3MkQxMUhZSE1ZUlJKTiQlQCN0PWcu). To enable it in Azure OpenAI Studio, follow the [Content filter how-to guide](/azure/ai-services/openai/how-to/content-filters) to create a new content filtering configuration, and select **Asynchronous Modified Filter** in the Streaming section.
+**Customer Copyright Commitment**: Content that is retroactively flagged as protected material may not be eligible for Customer Copyright Commitment coverage. 
+
+To enable Asynchronous Filter in Azure OpenAI Studio, follow the [Content filter how-to guide](/azure/ai-services/openai/how-to/content-filters) to create a new content filtering configuration, and select **Asynchronous Filter** in the Streaming section.
 
 ### Comparison of content filtering modes
 
-| Compare | Streaming - Default | Streaming - Asynchronous Modified Filter |
+| Compare | Streaming - Default | Streaming - Asynchronous Filter |
 |---|---|---|
 |Status |GA |Public Preview |
 | Eligibility |All customers |Customers approved for modified content filtering |
@@ -925,7 +932,7 @@ data: {
 
 #### Sample response stream (passes filters)
 
-Below is a real chat completion response using asynchronous modified filter. Note how the prompt annotations aren't changed, completion tokens are sent without annotations, and new annotation messages are sent without tokens&mdash;they are instead associated with certain content filter offsets. 
+Below is a real chat completion response using Asynchronous Filter. Note how the prompt annotations aren't changed, completion tokens are sent without annotations, and new annotation messages are sent without tokens&mdash;they are instead associated with certain content filter offsets. 
 
 `{"temperature": 0, "frequency_penalty": 0, "presence_penalty": 1.0, "top_p": 1.0, "max_tokens": 800, "messages": [{"role": "user", "content": "What is color?"}], "stream": true}`
 

articles/ai-services/openai/index.yml

@@ -137,7 +137,7 @@ landingContent:
       - linkListType: concept
         links:
           - text: Asynchronous content filtering
-            url: ./concepts/content-filter.md#asynchronous-modified-filter
+            url: ./concepts/content-filter.md#asynchronous-filter
           - text: Red teaming large language models (LLMs)
             url: ./concepts/red-teaming.md
           - text: System message templates

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

@@ -82,9 +82,9 @@ While projects show up as their own tracking resources in the Azure portal, they
 
 ## Connections to Azure and third-party resources
 
-Azure AI offers a set of connectors that allows you to connect to different types of data sources and other Azure tools. You can take advantage of connectors to connect with data such as indices in Azure AI Search to augment your flows.
+Azure AI offers a set of connectors that allows you to connect to different types of data sources and other Azure tools. You can take advantage of connectors to connect with data such as indexes in Azure AI Search to augment your flows.
 
-Connections can be set up as shared with all projects in the same hub, or created exclusively for one project. To manage project connections via Azure AI Studio, navigate to a project page, then navigate to **Project settings** > **Connections**. To manage shared connections, navigate to the **Manage** page. As an administrator, you can audit both shared and project-scoped connections on a hub level to have a single pane of glass of connectivity across projects.
+Connections can be set up as shared with all projects in the same hub, or created exclusively for one project. To manage project connections via Azure AI Studio, go to your project and then select **Settings** > **Connections**. To manage shared connections for a hub, go to your hub settings. As an administrator, you can audit both shared and project-scoped connections on a hub level to have a single pane of glass of connectivity across projects.
 
 ## Azure AI dependencies
 
@@ -114,9 +114,9 @@ In the Azure portal, you can find resources that correspond to your project in A
 > This section assumes that the hub and project are in the same resource group. 
 1. In [Azure AI Studio](https://ai.azure.com), go to a project and select **Settings** to view your project resources such as connections and API keys. There's a link to your hub in Azure AI Studio and links to view the corresponding project resources in the [Azure portal](https://portal.azure.com).
 
-    :::image type="content" source="../media/concepts/azureai-project-view-ai-studio.png" alt-text="Screenshot of the project and related resources in the Azure AI Studio." lightbox="../media/concepts/azureai-project-view-ai-studio.png":::
+    :::image type="content" source="../media/concepts/azureai-project-view-ai-studio.png" alt-text="Screenshot of the AI Studio project overview page with links to the Azure portal." lightbox="../media/concepts/azureai-project-view-ai-studio.png":::
 
-1. Select **Manage in the Azure Portal** to see your hub in the Azure portal. 
+1. Select **Manage in Azure Portal** to see your hub in the [Azure portal](https://portal.azure.com). 
 
 ## Next steps
 

articles/ai-studio/concepts/architecture.md

@@ -77,15 +77,15 @@ For more information, see [Role-based access control in Azure AI Studio](rbac-ai
 
 ## Attribute-based access control
 
-Each AI hub you create has a default storage account. Each child AI project of the AI hub inherits the storage account of the AI hub. The storage account is used to store data and artifacts.
+Each hub you create has a default storage account. Each child project of the hub inherits the storage account of the hub. The storage account is used to store data and artifacts.
 
-To secure the shared storage account, Azure AI Studio uses both Azure RBAC and Azure attribute-based access control (Azure ABAC). Azure ABAC is a security model that defines access control based on attributes associated with the user, resource, and environment. Each AI project has:
+To secure the shared storage account, Azure AI Studio uses both Azure RBAC and Azure attribute-based access control (Azure ABAC). Azure ABAC is a security model that defines access control based on attributes associated with the user, resource, and environment. Each project has:
 
 - A service principal that is assigned the Storage Blob Data Contributor role on the storage account.
 - A unique ID (workspace ID).
-- A set of containers in the storage account. Each container has a prefix that corresponds to the workspace ID value for the AI project.
+- A set of containers in the storage account. Each container has a prefix that corresponds to the workspace ID value for the project.
 
-The role assignment for each AI project's service principal has a condition that only allows the service principal access to containers with the matching prefix value. This condition ensures that each AI project can only access its own containers.
+The role assignment for each project's service principal has a condition that only allows the service principal access to containers with the matching prefix value. This condition ensures that each project can only access its own containers.
 
 > [!NOTE]
 > For data encryption in the storage account, the scope is the entire storage and not per-container. So all containers are encrypted using the same key (provided either by Microsoft or by the customer).
@@ -94,10 +94,10 @@ For more information on Azure access-based control, see [What is Azure attribute
 
 ## Containers in the storage account
 
-The default storage account for an AI hub has the following containers. These containers are created for each AI project, and the `{workspace-id}` prefix matches the unique ID for the AI project. The container is accessed by the AI project using a [connection](connections.md).
+The default storage account for a hub has the following containers. These containers are created for each project, and the `{workspace-id}` prefix matches the unique ID for the project. The container is accessed by the project using a [connection](connections.md).
 
 > [!TIP]
-> To find the ID for your AI project, go to the AI project in the [Azure portal](https://portal.azure.com/). Expand **Settings** and then select **Properties**. The **Workspace ID** is displayed.
+> To find the ID for your project, go to the project in the [Azure portal](https://portal.azure.com/). Expand **Settings** and then select **Properties**. The **Workspace ID** is displayed.
 
 | Container name | Connection name | Description |
 | --- | --- | --- |