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articles/ai-foundry/foundry-models/how-to/use-blocklists.md

@@ -7,31 +7,28 @@ ms.service: azure-ai-foundry
 ms.custom:
   - ignite-2024
 ms.topic: how-to
-ms.date: 07/28/2025
+ms.date: 11/21/2025
 ms.author: pafarley
 author: PatrickFarley
 monikerRange: 'foundry-classic || foundry'
 ---
 
-# How to use blocklists with Foundry Models in Microsoft Foundry services
+# Use blocklists with Foundry Models in Microsoft Foundry
 
 The configurable content filters are sufficient for most content moderation needs. However, you might need to create custom blocklists in the [Microsoft Foundry portal](https://ai.azure.com/?cid=learnDocs) as part of your content filtering configurations to filter terms specific to your use case. This article shows how to create custom blocklists as part of your content filters in the [Foundry portal](https://ai.azure.com/?cid=learnDocs).
 
 ## Prerequisites
 
 * An Azure subscription. If you're using [GitHub Models](https://docs.github.com/en/github-models/), you can upgrade your experience and create an Azure subscription in the process. For more information, see [Upgrade from GitHub Models to Foundry Models](../../model-inference/how-to/quickstart-github-models.md).
-
 * A Foundry services resource. For more information, see [Create a Foundry Services resource](../../../ai-services/multi-service-resource.md?context=/azure/ai-services/model-inference/context/context).
-
 * A Foundry project [connected to your Foundry services resource](../../model-inference/how-to/configure-project-connection.md).
-
 * A model deployment. For more information, see [Add and configure models to Foundry services](../../model-inference/how-to/create-model-deployments.md).
 
     > [!NOTE]
     > Blocklist (preview) support is limited to Azure OpenAI models.
 
 [!INCLUDE [use-blocklists](../../includes/use-blocklists.md)]
 
-## Next steps
+## Next step
 
 * [Configure content filtering](../../model-inference/how-to/configure-content-filters.md)

articles/ai-foundry/openai/concepts/audio.md

@@ -7,7 +7,7 @@ ms.author: pafarley
 ms.service: azure-ai-foundry
 ms.subservice: azure-ai-foundry-openai
 ms.topic: conceptual 
-ms.date: 7/12/2025
+ms.date: 11/21/2025
 ms.custom: template-concept
 manager: nitinme
 ---
@@ -16,13 +16,14 @@ manager: nitinme
 
 [!INCLUDE [classic-banner](../../includes/classic-banner.md)]
 
-> [!IMPORTANT]
-> The content filtering system isn't applied to prompts and completions processed by the audio models such as Whisper in Azure OpenAI. 
 
-Audio models in Azure OpenAI are available via the `realtime`, `completions`, and `audio` APIs. The audio models are designed to handle a variety of tasks, including speech recognition, translation, and text to speech.
+Audio models in Azure OpenAI are available via the `realtime`, `completions`, and `audio` APIs. The audio models are designed to handle a variety of tasks including speech recognition, translation, and text to speech.
 
 For information about the available audio models per region in Azure OpenAI, see the [audio models](models.md?tabs=standard-audio#standard-deployment-regional-models-by-endpoint), [standard models by endpoint](models.md?tabs=standard-audio#standard-deployment-regional-models-by-endpoint), and [global standard model availability](models.md?tabs=standard-audio#global-standard-model-availability) documentation.
 
+> [!IMPORTANT]
+> The content filtering system isn't applied to prompts and completions processed by audio models in Azure OpenAI, such as Whisper.
+
 ## GPT-4o audio Realtime API
 
 GPT real-time audio is designed to handle real-time, low-latency conversational interactions, making it a great fit for support agents, assistants, translators, and other use cases that need highly responsive back-and-forth with a user. For more information on how to use GPT real-time audio, see the [GPT real-time audio quickstart](../realtime-audio-quickstart.md) and [how to use GPT-4o audio](../how-to/realtime-audio.md).

articles/ai-foundry/openai/concepts/content-filter-personal-information.md

@@ -3,7 +3,7 @@ title: Personally Identifiable Information (PII) Filter
 description: Learn about the Personally Identifiable Information (PII) filter for identifying and flagging known personal information in large language model outputs.
 author: ssalgadodev
 ms.author: ssalgado
-ms.date: 07/03/2025
+ms.date: 11/21/2025
 ms.topic: conceptual
 ms.service: azure-ai-openai
 monikerRange: 'foundry-classic || foundry'
@@ -24,4 +24,6 @@ There are many different types of PII, and you can specify which types you want
 
 ## Filtering modes
 
-The PII filter can be configured to operate in two modes. **Annotate** mode flags PII that's returned in the model output. **Annotate and Block** mode blocks the entire output if PII is detected. The filtering mode can be set for each PII category individually.
+The PII filter can be configured to operate in two modes. 
+- **Annotate** mode flags PII that's returned in the model output. 
+- **Annotate and Block** mode blocks the entire output if PII is detected. The filtering mode can be set for each PII category individually.

articles/ai-foundry/openai/how-to/dall-e.md

@@ -29,7 +29,7 @@ OpenAI's image generation models create images from user-provided text prompts a
 
 - An Azure subscription. You can [create one for free](https://azure.microsoft.com/pricing/purchase-options/azure-account?icid=ai-services).
 - An Azure OpenAI resource created in a supported region. See [Region availability](/azure/ai-foundry/openai/concepts/models#model-summary-table-and-region-availability).
-- Deploy a `dall-e-3` or `gpt-image-1` series model with your Azure OpenAI resource. For more information on deployments, see [Create a resource and deploy a model with Azure OpenAI](/azure/ai-foundry/openai/how-to/create-resource).
+- Deploy a `dall-e-3` or `gpt-image-1`-series model with your Azure OpenAI resource. For more information on deployments, see [Create a resource and deploy a model with Azure OpenAI](/azure/ai-foundry/openai/how-to/create-resource).
     - GPT-image-1 models are newer and feature a number of improvements over DALL-E 3. They are available in limited access: apply for access with [this form](https://aka.ms/oai/gptimage1access).
 
 ## Overview

articles/ai-foundry/openai/how-to/responses.md

@@ -1288,7 +1288,7 @@ Compared to the standalone Image API, the Responses API offers several advantage
 * **Flexible inputs**: Accept image File IDs as inputs, in addition to raw image bytes.
 
 > [!NOTE]
-> The image generation tool in the Responses API is only supported by the `gpt-image-1` series models. You can however call this model from this list of supported models - `gpt-4o`, `gpt-4o-mini`, `gpt-4.1`, `gpt-4.1-mini`, `gpt-4.1-nano`, `o3`, and `gpt-5` series models.<br><br>The Responses API image generation tool does not currently support streaming mode. To use streaming mode and generate partial images, call the [image generation API](./dall-e.md) directly outside of the Responses API.
+> The image generation tool in the Responses API is only supported by the `gpt-image-1`-series models. You can however call this model from this list of supported models - `gpt-4o`, `gpt-4o-mini`, `gpt-4.1`, `gpt-4.1-mini`, `gpt-4.1-nano`, `o3`, and `gpt-5` series models.<br><br>The Responses API image generation tool does not currently support streaming mode. To use streaming mode and generate partial images, call the [image generation API](./dall-e.md) directly outside of the Responses API.
 
 Use the Responses API if you want to build conversational image experiences with GPT Image.
 

articles/ai-foundry/responsible-ai/speech-service/text-to-speech/concepts-disclosure-guidelines.md

@@ -7,7 +7,7 @@ ms.author: pafarley
 manager: nitinme
 ms.service: azure-ai-speech
 ms.topic: article
-ms.date: 12/03/2019
+ms.date: 11/21/2025
 ---
 
 # Disclosure design guidelines for synthetic voices
@@ -24,7 +24,7 @@ Disclosure is a means of letting people know they're interacting with or listeni
 
 The need to disclose the synthetic origins of a computer-generated voice is relatively new. In the past, computer-generated voices were obviously that—no one would ever mistake them for a real person. Every day, however, the realism of synthetic voices improves, and they become increasingly indistinguishable from human voices.
 
-## Goals
+## Design principles
 
 These are the principles to keep in mind when designing synthetic voice experiences: 
 

articles/ai-foundry/responsible-ai/speech-service/text-to-speech/concepts-disclosure-patterns.md

@@ -7,7 +7,7 @@ ms.author: pafarley
 manager: nitinme
 ms.service: azure-ai-speech
 ms.topic: article
-ms.date: 12/03/2019
+ms.date: 11/21/2025
 ---
 
 # Disclosure design patterns for synthetic voices
@@ -16,7 +16,7 @@ ms.date: 12/03/2019
 
 Now that you've determined the right level of disclosure for your text to speech avatar experience, it's a good time to explore potential design patterns.
 
-## Overview
+## Design pattern overview
 
 There's a spectrum of disclosure design patterns you can apply to your synthetic voice experience. If the outcome of your disclosure assessment was 'High Disclosure', we recommend [explicit disclosure](#explicit-disclosure), which means communicating the origins of the synthetic voice outright. [Implicit disclosure](#implicit-disclosure) includes cues and interaction patterns that benefit voice experiences whether required disclosure levels are high or low.
 

articles/ai-services/computer-vision/quickstarts-sdk/client-library.md

@@ -6,7 +6,7 @@ author: PatrickFarley
 manager: nitinme
 ms.service: azure-ai-vision
 ms.topic: quickstart
-ms.date: 09/26/2025
+ms.date: 11/21/2025
 ms.author: pafarley
 ms.devlang: csharp
 # ms.devlang: csharp, golang, java, javascript, python