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

Author: anaharris-ms

articles/ai-services/document-intelligence/containers/install-run.md

@@ -66,6 +66,10 @@ The host is a x64-based computer that runs the Docker container. It can be a com
 * [Azure Container Instances](../../../container-instances/index.yml).
 * A [Kubernetes](https://kubernetes.io/) cluster deployed to [Azure Stack](/azure-stack/operator). For more information, see [Deploy Kubernetes to Azure Stack](/azure-stack/user/azure-stack-solution-template-kubernetes-deploy).
 
+> [!NOTE]
+>
+> Note that Studio container cannot be deployed and run in Azure Kubernetes Service. Studio container is only supported to be run on local machine.
+
 ### Container requirements and recommendations
 
 #### Required supporting containers

articles/ai-services/language-service/question-answering/overview.md

@@ -14,7 +14,7 @@ ms.custom: language-service-question-answering
 # What is custom question answering?
 
 > [!NOTE]
-> [Azure Open AI On Your Data](../../openai/concepts/use-your-data.md) utilizes large language models (LLMs) to produce similar results to Custom Question Answering. If you wish to connect an existing Custom Question Answering project to Azure Open AI On Your Data, please check out our [guide]( how-to/azure-openai-integration.md).
+> [Azure OpenAI On Your Data](../../openai/concepts/use-your-data.md) utilizes large language models (LLMs) to produce similar results to Custom Question Answering. If you wish to connect an existing Custom Question Answering project to Azure OpenAI On Your Data, please check out our [guide]( how-to/azure-openai-integration.md).
 
 Custom question answering provides cloud-based Natural Language Processing (NLP) that allows you to create a natural conversational layer over your data. It is used to find appropriate answers from customer input or from a project.
 

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

@@ -5,7 +5,7 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: conceptual 
-ms.date: 05/20/2024
+ms.date: 07/01/2024
 author: mrbullwinkle
 ms.author: mbullwin
 recommendations: false
@@ -14,7 +14,7 @@ ms.custom:
 
 # Azure OpenAI 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. After July 1, 2024, the latest three preview APIs will remain supported while older APIs will no longer be supported unless support is explicitly indicated.
+This article is to help you understand the support lifecycle for the Azure OpenAI API previews. New preview APIs target a monthly release cadence. After February 3rd, 2025, the latest three preview APIs will remain supported while older APIs will no longer be supported unless support is explicitly indicated.
 
 > [!NOTE]
 > The `2023-06-01-preview` API will remain supported at this time, as `DALL-E 2` is only available in this API version. `DALL-E 3` is supported in the latest API releases. The `2023-10-01-preview` API will also remain supported at this time.
@@ -59,18 +59,6 @@ is currently the latest GA API release. This API version is the replacement for
 
 This version contains support for the latest GA features like Whisper, DALL-E 3, fine-tuning, on your data, etc. Any preview features that were released after the `2023-12-01-preview` release like Assistants, TTS, certain on your data datasources, are only supported in the latest preview API releases.
 
-## Retiring soon
-
-On July 1, 2024 the following API preview releases will be retired and will stop accepting API requests:
-
-- 2023-03-15-preview
-- 2023-07-01-preview
-- 2023-08-01-preview
-- 2023-09-01-preview
-- 2023-12-01-preview
-
-To avoid service disruptions, you must update to use the latest preview version before the retirement date.
-
 ## Updating API versions
 
 We recommend first testing the upgrade to new API versions to confirm there's no impact to your application from the API update before making the change globally across your environment.

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 | **Deprecation:** October 1, 2024 <br> **Retirement:** June 6, 2025 |
 | `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 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-4` | 1106-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on August 15, 2024, or later **<sup>1</sup>** |
+| `gpt-4` | 0125-preview |To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on August 15, 2024, or later  **<sup>1</sup>**  |
+| `gpt-4` | vision-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on August 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/concepts/models.md

@@ -4,7 +4,7 @@ titleSuffix: Azure OpenAI
 description: Learn about the different model capabilities that are available with Azure OpenAI.
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 06/25/2024
+ms.date: 07/01/2024
 ms.custom: references_regions, build-2023, build-2023-dataai, refefences_regions
 manager: nitinme
 author: mrbullwinkle #ChrisHMSFT
@@ -34,7 +34,7 @@ GPT-4o is the latest model from OpenAI. GPT-4o integrates text and images in a s
 
 GPT-4o is available for **standard** and **global-standard** model deployment.
 
-You need to [create](../how-to/create-resource.md) or use an existing resource in a [supported standard](#gpt-4-and-gpt-4-turbo-model-availability) or [global standard](#global-standard-model-availability-preview) region where the model is available.
+You need to [create](../how-to/create-resource.md) or use an existing resource in a [supported standard](#gpt-4-and-gpt-4-turbo-model-availability) or [global standard](#global-standard-model-availability) region where the model is available.
 
 When your resource is created, you can [deploy](../how-to/create-resource.md#deploy-a-model) the GPT-4o model. If you are performing a programmatic deployment, the **model** name is `gpt-4o`, and the **version** is `2024-05-13`.
 
@@ -164,7 +164,7 @@ You need to speak with your Microsoft sales/account team to acquire provisioned
 
 For more information on Provisioned deployments, see our [Provisioned guidance](./provisioned-throughput.md).
 
-### Global standard model availability (preview)
+### Global standard model availability
 
 **Supported models:**
 

articles/ai-services/openai/how-to/deployment-types.md

@@ -7,7 +7,7 @@ author: mrbullwinkle
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 05/19/2024
+ms.date: 07/01/2024
 ms.author: mbullwin
 ---
 
@@ -28,7 +28,7 @@ Our global deployments will be the first location for all new models and feature
 
 Azure OpenAI offers three types of deployments. These provide a varied level of capabilities that provide trade-offs on: throughput, SLAs, and price. Below is a summary of the options followed by a deeper description of each.
 
-| **Offering** | **Global-Standard** <sup>**1**</sup> | **Standard** | **Provisioned**  |
+| **Offering** | **Global-Standard** | **Standard** | **Provisioned**  |
 |---|:---|:---|:---|
 | **Best suited for**      | Applications that don’t require data residency. Recommended starting place for customers. | For customers with data residency requirements. Optimized for low to medium volume. | Real-time scoring for large consistent volume. Includes the highest commitments and limits.|
 | **How it works**         | Traffic may be routed anywhere in the world | | |
@@ -40,8 +40,6 @@ Azure OpenAI offers three types of deployments. These provide a varied level of
 | **Sku Name in code**     |    `GlobalStandard`               | `Standard`   |      `ProvisionedManaged`       |
 | **Billing model**        | Pay-per-token | Pay-per-token | Monthly Commitments |
 
-<sup>**1**</sup> Global-Standard deployment type is currently in preview.
-
 ## Provisioned
 
 Provisioned deployments allow you to specify the amount of throughput you require in a deployment. The service then allocates the necessary model processing capacity and ensures it's ready for you. Throughput is defined in terms of provisioned throughput units (PTU) which is a normalized way of representing the throughput for your deployment. Each model-version pair requires different amounts of PTU to deploy and provide different amounts of throughput per PTU. Learn more from our [Provisioned throughput concepts article](../concepts/provisioned-throughput.md).
@@ -52,7 +50,7 @@ Standard deployments provide a pay-per-call billing model on the chosen model. P
 
 Standard deployments are optimized for low to medium volume workloads with high burstiness. Customers with high consistent volume may experience greater latency variability.
 
-## Global standard (preview)
+## Global standard
 
 Global deployments are available in the same Azure OpenAI resources as non-global offers but allow you to leverage Azure's global infrastructure to dynamically route traffic to the data center with best availability for each request.  Global standard will provide the highest default quota for new models and eliminates the need to load balance across multiple resources.  
 

articles/ai-services/openai/how-to/use-web-app.md

@@ -50,7 +50,7 @@ Sample source code for the web app is available on [GitHub](https://github.com/m
 > [!NOTE]
 > After February 1, 2024, the web app requires the app startup command to be set to `python3 -m gunicorn app:app`. When updating an app that was published prior to February 1, 2024, you need to manually add the startup command from the **App Service Configuration** page.
 
-We recommend pulling changes from the `main` branch for the web app's source code frequently to ensure you have the latest bug fixes, API version, and improvements. Additionally, the web app must be synchronized every time the API version being used is [retired](../api-version-deprecation.md#retiring-soon). 
+We recommend pulling changes from the `main` branch for the web app's source code frequently to ensure you have the latest bug fixes, API version, and improvements. Additionally, the web app must be synchronized every time the API version being used is [retired](../api-version-deprecation.md)
 
 Consider either clicking the **watch** or **star** buttons on the web app's [GitHub](https://github.com/microsoft/sample-app-aoai-chatGPT) repo to be notified about changes and updates to the source code.
 

articles/ai-services/openai/quotas-limits.md

@@ -10,7 +10,7 @@ ms.custom:
   - ignite-2023
   - references_regions
 ms.topic: conceptual
-ms.date: 06/21/2024
+ms.date: 07/01/2024
 ms.author: mbullwin
 ---
 
@@ -60,9 +60,6 @@ The following sections provide you with a quick guide to the default quotas and
 
 ### gpt-4o global standard
 
-> [!NOTE]
-> The [global standard model deployment type](./how-to/deployment-types.md#deployment-types) is currently in public preview.
-
 |Tier| Quota Limit in tokens per minute (TPM) | Requests per minute |
 |---|:---:|:---:|
 |Enterprise agreement | 10 M | 60 K |