Merge branch 'main' of https://github.com/MicrosoftDocs/azure-docs-pr into tamram24-0215

Author: tamram

articles/active-directory-b2c/custom-domain.md

@@ -1,12 +1,12 @@
 ---
-title: Enable Azure AD B2C custom domains
+title: Enable custom domains in Azure Active Directory B2C
 titleSuffix: Azure AD B2C
-description: Learn how to enable custom domains in your redirect URLs for Azure Active Directory B2C.
+description: Learn how to enable custom domains in your redirect URLs for Azure Active Directory B2C, so that my users have a seamless experience. 
 author: kengaderdus
 manager: CelesteDG
 ms.service: active-directory
 ms.topic: how-to
-ms.date: 01/26/2024
+ms.date: 02/14/2024
 ms.author: kengaderdus
 ms.subservice: B2C
 ms.custom: "b2c-support"
@@ -15,7 +15,7 @@ zone_pivot_groups: b2c-policy-type
 #Customer intent: As a developer, I want to use my own domain name for the sign-in and sign-up experience, so that my users have a seamless experience.
 ---
 
-# Enable custom domains for Azure Active Directory B2C
+# Enable custom domains in Azure Active Directory B2C
 
 [!INCLUDE [active-directory-b2c-choose-user-flow-or-custom-policy](../../includes/active-directory-b2c-choose-user-flow-or-custom-policy.md)]
 
@@ -52,8 +52,12 @@ When using custom domains, consider the following:
 
 - You can set up multiple custom domains. For the maximum number of supported custom domains, see [Microsoft Entra service limits and restrictions](/entra/identity/users/directory-service-limits-restrictions) for Azure AD B2C and [Azure subscription and service limits, quotas, and constraints](/azure/azure-resource-manager/management/azure-subscription-service-limits#azure-front-door-classic-limits) for Azure Front Door.
 - Azure Front Door is a separate Azure service, so extra charges will be incurred. For more information, see [Front Door pricing](https://azure.microsoft.com/pricing/details/frontdoor).
-- After you configure custom domains, users will still be able to access the Azure AD B2C default domain name *<tenant-name>.b2clogin.com* (unless you're using a custom policy and you [block access](#optional-block-access-to-the-default-domain-name).
-- If you have multiple applications, migrate them all to the custom domain because the browser stores the Azure AD B2C session under the domain name currently being used.
+- If you've multiple applications, migrate all oft them to the custom domain because the browser stores the Azure AD B2C session under the domain name currently being used.
+- After you configure custom domains, users will still be able to access the Azure AD B2C default domain name *<tenant-name>.b2clogin.com*. You need to block access to the default domain so that attackers can't use it to access your apps or run distributed denial-of-service (DDoS) attacks. [Submit a support ticket](find-help-open-support-ticket.md) to request for the  blocking of access to the default domain.
+
+> [!WARNING]
+> Don't request blocking of the default domain until your custom domain works properly.
+
 
 ## Prerequisites
 

articles/active-directory-b2c/media/b2c-global-identity-region-based-design/merge-link-account.png

@@ -2,7 +2,6 @@
 title: 'Quickstart: Create an Azure AI services resource using Terraform'
 description: 'In this article, you create an Azure AI services resource using Terraform'
 keywords: Azure AI services, cognitive solutions, cognitive intelligence, cognitive artificial intelligence
-#services: cognitive-services
 ms.service: azure-ai-services
 ms.topic: quickstart
 ms.date: 4/14/2023

articles/active-directory-b2c/media/b2c-global-identity-region-based-design/traveling-user-merge-link-account.png

@@ -426,7 +426,7 @@ sections:
       - question: |
             How can I move my trained models from one environment (like beta) to another (like production)?
         answer: |
-            The Copy API enables this scenario by allowing you to copy custom models from one Document Intelligence account or into others, which can exist in any supported geographical region. Follow [this document](disaster-recovery.md) for detailed instructions. The copy operation is limited to copying models within the specific cloud environment the model was trained in. For instance, copying models from the public cloud to the Azure Government clod isn't supported.
+            The Copy API enables this scenario by allowing you to copy custom models from one Document Intelligence account or into others, which can exist in any supported geographical region. Follow [this document](disaster-recovery.md) for detailed instructions. The copy operation is limited to copying models within the specific cloud environment the model was trained in. For instance, copying models from the public cloud to the Azure Government cloud isn't supported.
 
       - question: |
           Why was I charged for Layout when running custom training?

articles/active-directory-b2c/media/b2c-global-identity-region-based-design/traveling-user-sign-in.png

@@ -66,7 +66,7 @@ curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads?api-version=2024
 ## Retrieve thread
 
 ```http
-GET https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads{thread_id}?api-version=2024-02-15-preview
+GET https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads/{thread_id}?api-version=2024-02-15-preview
 ```
 
 Retrieves a thread.
@@ -224,4 +224,4 @@ curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads/{thread_id}?api-
 | `id` | string | The identifier, which can be referenced in API endpoints.|
 | `object` | string | The object type, which is always thread. |
 | `created_at` | integer | The Unix timestamp (in seconds) for when the thread was created. |
-| `metadata` | map | Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format. Keys can be a maximum of 64 characters long and values can be a maximum of 512 characters long. |
+| `metadata` | map | Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format. Keys can be a maximum of 64 characters long and values can be a maximum of 512 characters long. |

articles/active-directory-b2c/media/partner-grit-iam/grit-b2b2c-architecture.png

@@ -1,12 +1,12 @@
 ---
 title: Prompt engineering techniques with Azure OpenAI
 titleSuffix: Azure OpenAI Service
-description: Learn about the options for how to use prompt engineering with GPT-3, GPT-35-Turbo, and GPT-4 models
-author: suhridpalsule
+description: Learn about the options for how to use prompt engineering with GPT-3, GPT-35-Turbo, and GPT-4 models.
+author: mrbullwinkle
 ms.author: mbullwin 
 ms.service: azure-ai-openai
 ms.topic: conceptual 
-ms.date: 04/20/2023
+ms.date: 02/16/2024
 manager: nitinme
 keywords: ChatGPT, GPT-4, prompt engineering, meta prompts, chain of thought
 zone_pivot_groups: openai-prompt
@@ -23,7 +23,7 @@ While the principles of prompt engineering can be generalized across many differ
 
 Each API requires input data to be formatted differently, which in turn impacts overall prompt design. The **Chat Completion API** supports the GPT-35-Turbo and GPT-4 models. These models are designed to take input formatted in a [specific chat-like transcript](../how-to/chatgpt.md) stored inside an array of dictionaries.
 
-The **Completion API** supports the older GPT-3 models and has much more flexible input requirements in that it takes a string of text with no specific format rules. Technically the GPT-35-Turbo models can be used with either APIs, but we strongly recommend using the Chat Completion API for these models. To learn more, please consult our [in-depth guide on using these APIs](../how-to/chatgpt.md).
+The **Completion API** supports the older GPT-3 models and has much more flexible input requirements in that it takes a string of text with no specific format rules.
 
 The techniques in this guide will teach you strategies for increasing the accuracy and grounding of responses you generate with a Large Language Model (LLM). It is, however, important to remember that even when using prompt engineering effectively you still need to validate the responses the models generate. Just because a carefully crafted prompt worked well for a particular scenario doesn't necessarily mean it will generalize more broadly to certain use cases. Understanding the [limitations of LLMs](/legal/cognitive-services/openai/transparency-note?context=/azure/ai-services/openai/context/context#limitations), is just as important as understanding how to leverage their strengths.
 

articles/ai-services/create-account-terraform.md

@@ -160,14 +160,6 @@ See [model versions](../concepts/model-versions.md) to learn about how Azure Ope
 
 **<sup>1</sup>** This model will accept requests > 4,096 tokens. It is not recommended to exceed the 4,096 input token limit as the newer version of the model are capped at 4,096 tokens. If you encounter issues when exceeding 4,096 input tokens with this model this configuration is not officially supported.
 
-#### Azure Government regions
-
-The following GPT-3 models are available with [Azure Government](/azure/azure-government/documentation-government-welcome):
-
-|Model ID | Model Availability |
-|--|--|
-|`gpt-35-turbo` (1106) |US Gov Virginia<br>US Gov Arizona |
-
 ### Embeddings models
 
 These models can only be used with Embedding API requests.