Merge pull request #4745 from mrbullwinkle/mrb_05_11_2025_rebrand

[Azure OpenAI] [Build] [Release branch] [BULK CHANGE] Rebranding

Author: JillGrant615

articles/ai-services/openai/api-version-deprecation.md

@@ -1,6 +1,6 @@
 ---
-title: Azure OpenAI Service API version lifecycle
-description: Learn more about API version retirement in Azure OpenAI Services.
+title: Azure OpenAI in Azure AI Foundry Models API version lifecycle
+description: Learn more about API version retirement in Azure OpenAI.
 services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
@@ -12,11 +12,10 @@ recommendations: false
 ms.custom:
 ---
 
-# Azure OpenAI API preview lifecycle
+# Azure OpenAI in Azure AI Foundry Models API preview lifecycle
 
 This article is to help you understand the support lifecycle for the Azure OpenAI API previews. New preview APIs target a monthly release cadence. Whenever possible we recommend using either the latest GA, or preview API releases.
 
-
 > [!NOTE]
 > New API response objects may be added to the API response without version changes. We recommend you only parse the response objects you require. 
 

articles/ai-services/openai/azure-government.md

@@ -10,16 +10,16 @@ ms.date: 5/1/2025
 recommendations: false
 ---
 
-# Azure OpenAI Service and features in Azure Government
+# Azure OpenAI and features in Azure Government
 
-This article highlights the differences when using Azure OpenAI in Azure Government as compared to the commercial cloud offering. Learn more about the Azure OpenAI Service itself in [Azure OpenAI Service documentation](/azure/ai-services/openai/).
+This article highlights the differences when using Azure OpenAI in Azure Government as compared to the commercial cloud offering. Learn more about the Azure OpenAI itself in [Azure OpenAI documentation](/azure/ai-services/openai/).
 <br><br>
 
 ## Azure OpenAI models
 
-Learn more about the different capabilities of each model in [Azure OpenAI Service models](./concepts/models.md). For customers with [Business Continuity and Disaster Recovery (BCDR) considerations](./how-to/business-continuity-disaster-recovery.md), take careful note of the deployment types, regions, and model availability as not all model/type combinations are available in both regions. 
+Learn more about the different capabilities of each model in [Azure OpenAI models](./concepts/models.md). For customers with [Business Continuity and Disaster Recovery (BCDR) considerations](./how-to/business-continuity-disaster-recovery.md), take careful note of the deployment types, regions, and model availability as not all model/type combinations are available in both regions. 
 
-The following sections show model availability by region and deployment type. Models and versions not listed are not currently available in Azure Government. For general limits, quotas, and other details refer to [Azure OpenAI Service quotas and limits](/azure/ai-services/openai/quotas-limits/). 
+The following sections show model availability by region and deployment type. Models and versions not listed are not currently available in Azure Government. For general limits, quotas, and other details refer to [Azure OpenAI quotas and limits](/azure/ai-services/openai/quotas-limits/). 
 
 <br>
 

articles/ai-services/openai/chatgpt-quickstart.md

@@ -1,7 +1,7 @@
 ---
-title: 'Quickstart - Get started using chat completions with Azure OpenAI Service'
-titleSuffix: Azure OpenAI Service
-description: Walkthrough on how to get started using chat completions with Azure OpenAI Service.
+title: 'Quickstart - Get started using chat completions with Azure OpenAI in Azure AI Foundry Models'
+titleSuffix: Azure OpenAI
+description: Walkthrough on how to get started using chat completions with Azure OpenAI.
 manager: nitinme
 ms.service: azure-ai-openai
 ms.custom: build-2023, build-2023-dataai, devx-track-python, devx-track-dotnet, devx-track-extended-java, devx-track-js, devx-track-go
@@ -13,7 +13,7 @@ zone_pivot_groups: openai-quickstart-new
 recommendations: false
 ---
 
-# Quickstart: Get started using chat completions with Azure OpenAI Service
+# Quickstart: Get started using chat completions with Azure OpenAI in Azure AI Foundry Models
 
 Use this article to get started using Azure OpenAI.
 

articles/ai-services/openai/concepts/abuse-monitoring.md

@@ -1,7 +1,7 @@
 ---
-title: Azure OpenAI Service abuse monitoring
+title: Azure OpenAI in Azure AI Foundry Models abuse monitoring
 titleSuffix: Azure OpenAI
-description: Learn about the abuse monitoring capabilities of Azure OpenAI Service
+description: Learn about the abuse monitoring capabilities of Azure OpenAI
 author: mrbullwinkle
 ms.author: mbullwin
 ms.service: azure-ai-openai
@@ -13,23 +13,23 @@ manager: nitinme
 
 # Abuse Monitoring
 
-Azure OpenAI Service detects and mitigates instances of recurring content and/or behaviors that suggest use of the service in a manner that might violate the [Code of Conduct](https://aka.ms/AI-CoC). Details on how data is handled can be found on the [Data, Privacy, and Security](/legal/cognitive-services/openai/data-privacy?context=/azure/ai-services/openai/context/context) page.
+Azure OpenAI in Azure AI Foundry Models detects and mitigates instances of recurring content and/or behaviors that suggest use of the service in a manner that might violate the [Code of Conduct](https://aka.ms/AI-CoC). Details on how data is handled can be found on the [Data, Privacy, and Security](/legal/cognitive-services/openai/data-privacy?context=/azure/ai-services/openai/context/context) page.
 
 ## Components of abuse monitoring
 
 There are several components to abuse monitoring:
 
 - **Content Classification**: Classifier models detect harmful text and/or images in user prompts (inputs) and completions (outputs). The system looks for categories of harms as defined in the [Content Requirements](/legal/ai-code-of-conduct?context=/azure/ai-services/openai/context/context), and assigns severity levels as described in more detail on the [Content Filtering](/azure/ai-services/openai/concepts/content-filter) page. The content classification signals contribute to pattern detection as described below.  
-- **Abuse Pattern Capture**: Azure OpenAI Service’s abuse monitoring system looks at customer usage patterns and employs algorithms and heuristics to detect and score indicators of potential abuse. Detected patterns consider, for example, the frequency and severity at which harmful content is detected (as indicated in content classifier signals) in a customer’s prompts and completions, as well as the intentionality of the behavior. The trends and urgency of the detected pattern will also affect scoring of potential abuse severity.
+- **Abuse Pattern Capture**: Azure OpenAI’s abuse monitoring system looks at customer usage patterns and employs algorithms and heuristics to detect and score indicators of potential abuse. Detected patterns consider, for example, the frequency and severity at which harmful content is detected (as indicated in content classifier signals) in a customer’s prompts and completions, as well as the intentionality of the behavior. The trends and urgency of the detected pattern will also affect scoring of potential abuse severity.
     For example, a higher volume of harmful content classified as higher severity, or recurring conduct indicating intentionality (such as recurring jailbreak attempts) are both more likely to receive a high score indicating potential abuse. 
 - **Review and Decision**: Prompts and completions that are flagged through content classification and/or identified as part of a potentially abusive pattern of use are subjected to another review process to help confirm the system’s analysis and inform actioning decisions for abuse monitoring. Such review is conducted through two methods: automated review and human review.
     - By default, if prompts and completions are flagged through content classification as harmful and/or identified to be part of a potentially abusive pattern of use, they may be sampled for review by using automated means including AI models such as LLMs instead of a human reviewer. The model used for this purpose processes prompts and completions only to confirm the system’s analysis and inform actioning decisions; prompts and completions that undergo such review are not stored by the abuse monitoring system or used to train the AI model or other systems.
-    - In some cases, when automated review does not meet applicable confidence thresholds in complex contexts or if automated review systems are not available, human eyes-on review may be introduced to make an extra judgment. Authorized Microsoft employees may assess content flagged through content classification and/or identified as part of a potentially abusive pattern of use, and either confirm or correct the classification or determination based on predefined guidelines and policies. Such prompts and completions can be accessed for human review only by authorized Microsoft employees via Secure Access Workstations (SAWs) with Just-In-Time (JIT) request approval granted by team managers. For Azure OpenAI Service resources deployed in the European Economic Area, the authorized Microsoft employees are located in the European Economic Area. This human review abuse monitoring process will not take place if the customer has been approved for modified abuse monitoring. 
+    - In some cases, when automated review does not meet applicable confidence thresholds in complex contexts or if automated review systems are not available, human eyes-on review may be introduced to make an extra judgment. Authorized Microsoft employees may assess content flagged through content classification and/or identified as part of a potentially abusive pattern of use, and either confirm or correct the classification or determination based on predefined guidelines and policies. Such prompts and completions can be accessed for human review only by authorized Microsoft employees via Secure Access Workstations (SAWs) with Just-In-Time (JIT) request approval granted by team managers. For Azure OpenAI resources deployed in the European Economic Area, the authorized Microsoft employees are located in the European Economic Area. This human review abuse monitoring process will not take place if the customer has been approved for modified abuse monitoring. 
 - **Notification and Action**: When a threshold of abusive behavior has been confirmed based on the preceding steps, the customer is informed of the determination by email. Except in cases of severe or recurring abuse, customers typically are given an opportunity to explain or remediate—and implement mechanisms to prevent recurrence of—the abusive behavior. Failure to address the behavior—or recurring or severe abuse—may result in suspension or termination of the customer’s access to Azure OpenAI resources and/or capabilities.
 
 ## Modified abuse monitoring 
 
-Some customers may want to use the Azure OpenAI Service for a use case that involves the processing of highly sensitive or highly confidential data, or otherwise may conclude that they don't want or don't have the right to permit Microsoft to store and conduct human review on their prompts and completions for abuse detection. To address these concerns, Microsoft allows customers who meet additional Limited Access eligibility criteria to apply to modify abuse monitoring by completing [this](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUOE9MUTFMUlpBNk5IQlZWWkcyUEpWWEhGOCQlQCN0PWcu)form. Learn more about applying for modified abuse monitoring at [Limited access to Azure OpenAI Service](/legal/cognitive-services/openai/limited-access?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext), and about the impact of modified abuse monitoring on data processing at [Data, privacy, and security for Azure OpenAI Service](/legal/cognitive-services/openai/data-privacy?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext&tabs=azure-portal).    
+Some customers may want to use the Azure OpenAI for a use case that involves the processing of highly sensitive or highly confidential data, or otherwise may conclude that they don't want or don't have the right to permit Microsoft to store and conduct human review on their prompts and completions for abuse detection. To address these concerns, Microsoft allows customers who meet additional Limited Access eligibility criteria to apply to modify abuse monitoring by completing [this](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUOE9MUTFMUlpBNk5IQlZWWkcyUEpWWEhGOCQlQCN0PWcu)form. Learn more about applying for modified abuse monitoring at [Limited access to Azure OpenAI](/legal/cognitive-services/openai/limited-access?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext), and about the impact of modified abuse monitoring on data processing at [Data, privacy, and security for Azure OpenAI](/legal/cognitive-services/openai/data-privacy?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext&tabs=azure-portal).    
 
 > [!NOTE]
 > When abuse monitoring is modified and human review is not performed, detection of potential abuse may be less accurate. Customers are notified of potential abuse detection as described above, and should be prepared to respond to such notification to avoid service interruption if possible.  
@@ -38,4 +38,4 @@ Some customers may want to use the Azure OpenAI Service for a use case that invo
 
 - Learn more about the [underlying models that power Azure OpenAI](../concepts/models.md).
 - Learn more about understanding and mitigating risks associated with your application: [Overview of Responsible AI practices for Azure OpenAI models](/legal/cognitive-services/openai/overview?context=/azure/ai-services/openai/context/context).
-- Learn more about how data is processed in content filtering and abuse monitoring: [Data, privacy, and security for Azure OpenAI Service](/legal/cognitive-services/openai/data-privacy?context=/azure/ai-services/openai/context/context#preventing-abuse-and-harmful-content-generation).
+- Learn more about how data is processed in content filtering and abuse monitoring: [Data, privacy, and security for Azure OpenAI](/legal/cognitive-services/openai/data-privacy?context=/azure/ai-services/openai/context/context#preventing-abuse-and-harmful-content-generation).

articles/ai-services/openai/concepts/advanced-prompt-engineering.md

@@ -1,6 +1,6 @@
 ---
 title: Design system messages with Azure OpenAI
-titleSuffix: Azure OpenAI Service
+titleSuffix: Azure OpenAI in Azure AI Foundry Models
 description: Learn about system message design
 author: mrbullwinkle
 ms.author: mbullwin 
@@ -42,7 +42,7 @@ The example below, shows a sample system message and the resulting model respons
 
 Some other examples of system messages are:
 -	“Assistant is a large language model trained by OpenAI.”
--	“Assistant is an intelligent chatbot designed to help users answer technical questions about Azure OpenAI Service. Only answer questions using the context below and if you're not sure of an answer, you can say "I don't know".
+-	“Assistant is an intelligent chatbot designed to help users answer technical questions about Azure OpenAI in Azure AI Foundry Models. Only answer questions using the context below and if you're not sure of an answer, you can say "I don't know".
 -	“Assistant is an intelligent chatbot designed to help users answer their tax related questions.”
 -	“You're an assistant designed to extract entities from text. Users will paste in a string of text and you'll respond with entities you've extracted from the text as a JSON object. Here's an example of your output format:
 

articles/ai-services/openai/concepts/assistants.md

@@ -1,6 +1,6 @@
 ---
-title: Azure OpenAI Service Assistants API concepts
-titleSuffix: Azure OpenAI Service
+title: Azure OpenAI in Azure AI Foundry Models Assistants API concepts
+titleSuffix: Azure OpenAI
 description: Learn about the concepts behind the Azure OpenAI Assistants API.
 ms.topic: conceptual
 ms.date: 02/04/2025
@@ -13,7 +13,7 @@ recommendations: false
 
 # Azure OpenAI Assistants API (Preview)
 
-Assistants, a feature of Azure OpenAI Service, is available in public preview starting in the `2024-02-15-preview` API version. Assistants API makes it easier for developers to create applications with sophisticated copilot-like experiences that can sift through data, suggest solutions, and automate tasks.
+Assistants, a feature of Azure OpenAI in Azure AI Foundry Models, is available in public preview starting in the `2024-02-15-preview` API version. Assistants API makes it easier for developers to create applications with sophisticated copilot-like experiences that can sift through data, suggest solutions, and automate tasks.
 
 * Assistants can call Azure OpenAI’s [models](../concepts/models.md) with specific instructions to tune their personality and capabilities.
 * Assistants can access **multiple tools in parallel**. These can be both Azure OpenAI-hosted tools like [code interpreter](../how-to/code-interpreter.md) and [file search](../how-to/file-search.md), or tools you build, host, and access through [function calling](../how-to/function-calling.md).

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

@@ -1,7 +1,7 @@
 ---
-title: Azure OpenAI Service audio
+title: Azure OpenAI in Azure AI Foundry Models audio
 titleSuffix: Azure OpenAI
-description: Learn about the audio capabilities of Azure OpenAI Service.
+description: Learn about the audio capabilities of Azure OpenAI.
 author: eric-urban
 ms.author: eur
 ms.service: azure-ai-openai
@@ -11,14 +11,14 @@ ms.custom: template-concept
 manager: nitinme
 ---
 
-# Audio capabilities in Azure OpenAI Service
+# Audio capabilities in Azure OpenAI in Azure AI Foundry Models
 
 > [!IMPORTANT]
-> The content filtering system isn't applied to prompts and completions processed by the audio models such as Whisper in Azure OpenAI Service. 
+> 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.
 
-For information about the available audio models per region in Azure OpenAI Service, 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.
+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.
 
 ## GPT-4o audio Realtime API
 
@@ -33,7 +33,7 @@ GPT-4o audio completion is designed to generate audio from audio or text prompts
 The audio models via the `/audio` API can be used for speech to text, translation, and text to speech. To get started with the audio API, see the [Whisper quickstart](../whisper-quickstart.md) for speech to text.
 
 > [!NOTE]
-> To help you decide whether to use Azure AI Speech or Azure OpenAI Service, see the [Azure AI Speech batch transcription](../../speech-service/batch-transcription-create.md), [What is the Whisper model?](../../speech-service/whisper-overview.md), and [OpenAI text to speech voices](../../speech-service/openai-voices.md#openai-text-to-speech-voices-via-azure-openai-service-or-via-azure-ai-speech) guides.
+> To help you decide whether to use Azure AI Speech or Azure OpenAI, see the [Azure AI Speech batch transcription](../../speech-service/batch-transcription-create.md), [What is the Whisper model?](../../speech-service/whisper-overview.md), and [OpenAI text to speech voices](../../speech-service/openai-voices.md#openai-text-to-speech-voices-via-azure-openai-service-or-via-azure-ai-speech) guides.
 
 ## Related content