Merge branch 'main' of https://github.com/MicrosoftDocs/azure-docs-pr into lbback

Author: dlepow

.openpublishing.redirection.active-directory.json

@@ -914,6 +914,11 @@
             "source_path_from_root": "/articles/defender-for-cloud/tutorial-security-incident.md",
             "redirect_url": "/azure/defender-for-cloud/managing-and-responding-alerts",
             "redirect_document_id": true
+        },
+        {
+            "source_path_from_root": "/articles/defender-for-cloud/how-to-migrate-to-built-in.md",
+            "redirect_url": "/azure/defender-for-cloud/how-to-transition-to-built-in",
+            "redirect_document_id": true
         }
     ]
 }

.openpublishing.redirection.defender-for-cloud.json

@@ -0,0 +1,53 @@
+---
+title: Azure OpenAI Service API version retirement
+description: Learn more about API version retirement in Azure OpenAI Services
+services: cognitive-services
+manager: nitinme
+ms.service: azure-ai-openai
+ms.topic: conceptual 
+ms.date: 01/08/2024
+author: mrbullwinkle
+ms.author: mbullwin
+recommendations: false
+ms.custom:
+---
+
+# Azure OpenAI API preview lifecycle
+
+This article is to help you understand the support lifecycle for the Azure OpenAI API previews.
+
+## Latest preview API release
+
+Azure OpenAI API version 2023-12-01-preview is currently the latest preview release.
+
+This version contains support for all the latest Azure OpenAI features including:
+
+- [Fine-tuning](./how-to/fine-tuning.md) `gpt-35-turbo`, `babbage-002`, and `davinci-002` models.[**Added in 2023-10-01-preview**]
+- [Whisper](./whisper-quickstart.md). [**Added in 2023-09-01-preview**]
+- [Function calling](./how-to/function-calling.md)  [**Added in 2023-07-01-preview**]
+- [DALL-E](./dall-e-quickstart.md)  [**Added in 2023-06-01-preview**]
+- [Retrieval augmented generation with the on your data feature](./use-your-data-quickstart.md).  [**Added in 2023-06-01-preview**]
+
+## Retiring soon
+
+On April 2, 2024 the following API preview releases will be retired and will stop accepting API requests:
+
+- 2023-03-15-preview
+- 2023-06-01-preview
+- 2023-07-01-preview
+- 2023-08-01-preview
+
+To avoid service disruptions, you must update to use the latest preview version prior to the retirement date.
+
+## Updating API versions
+
+We recommend first testing the upgrade to new API versions to confirm there is no impact to your application from the API update prior to making the change globally across your environment.
+
+If you are using the OpenAI Python client library or the REST API, you will need to update your code directly to the latest preview API version.
+
+If you are using one of the Azure OpenAI SDKs for C#, Go, Java, or JavaScript you will instead need to update to the latest version of the SDK. Each SDK release is hardcoded to work with specific versions of the Azure OpenAI API.
+
+## Next steps
+
+- [Learn more about Azure OpenAI](overview.md)
+- [Learn about working with Azure OpenAI models](./how-to/working-with-models.md)

.openpublishing.redirection.json

@@ -51,6 +51,7 @@ To force the model to call a specific function set the `tool_choice` parameter w
 > The default behavior (`tool_choice: "auto"`) is for the model to decide on its own whether to call a function and if so which function to call.
 
 ```python
+import os
 from openai import AzureOpenAI
 import json
 
@@ -60,8 +61,6 @@ client = AzureOpenAI(
   api_version="2023-12-01-preview"
 )
 
-from openai import OpenAI
-import json
 
 # Example function hard coded to return the same weather
 # In production, this could be your backend API or an external API

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

@@ -65,6 +65,8 @@ items:
       href: ./concepts/use-your-image-data.md
 - name: How-to 
   items:
+  - name: API version lifecycle
+    href: ./api-version-deprecation.md
   - name: Completions & chat completions
     items:
     - name: GPT-35-Turbo & GPT-4 

articles/ai-services/openai/how-to/function-calling.md

@@ -29,7 +29,7 @@ Here's example SSML in a request for text to speech with the voice name and the
 
 ```xml
 <speak version='1.0' xmlns='http://www.w3.org/2001/10/synthesis' xmlns:mstts='http://www.w3.org/2001/mstts' xml:lang='en-US'>
-    <voice xml:lang='en-US' xml:gender='Male' name='PhoenixV2Neural'> 
+    <voice name='PhoenixV2Neural'> 
     <mstts:ttsembedding speakerProfileId='your speaker profile ID here'> 
     I'm happy to hear that you find me amazing and that I have made your trip planning easier and more fun. 我很高兴听到你觉得我很了不起，我让你的旅行计划更轻松、更有趣。Je suis heureux d'apprendre que vous me trouvez incroyable et que j'ai rendu la planification de votre voyage plus facile et plus amusante.  
     </mstts:ttsembedding> 

articles/ai-services/openai/toc.yml

@@ -8,7 +8,7 @@ ms.custom:
   - ignite-2023
 ms.topic: conceptual
 ms.date: 12/14/2023
-ms.reviewer: eur
+ms.reviewer: Blackmist
 ms.author: eur
 author: eric-urban
 ---

articles/ai-services/speech-service/personal-voice-how-to-use.md

@@ -8,7 +8,7 @@ ms.custom:
   - ignite-2023
 ms.topic: how-to
 ms.date: 11/15/2023
-ms.reviewer: eur
+ms.reviewer: Blackmist
 ms.author: eur
 author: eric-urban
 ---

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

@@ -440,7 +440,7 @@ Each time a project subscribes to a given offer from the Azure Marketplace, a ne
 
 :::image type="content" source="../media/cost-management/marketplace/costs-model-as-service-cost-details.png" alt-text="A screenshot showing different resources corresponding to different model offers and their associated meters."  lightbox="../media/cost-management/marketplace/costs-model-as-service-cost-details.png":::
 
-Quota is managed per deployment. Each deployment has a rate limit of 20,000 tokens per minute. However, we currently limit one deployment per model per project. Contact Microsoft Azure Support if the current rate limits don’t suffice your scenarios.
+Quota is managed per deployment. Each deployment has a rate limit of 200,000 tokens per minute and 1,000 API requests per minute. However, we currently limit one deployment per model per project. Contact Microsoft Azure Support if the current rate limits don't suffice your scenarios.
 
 ### Considerations for Llama 2 models deployed as real-time endpoints