gstatMerge branch 'main' of https://github.com/microsoftdocs/azure-docs-pr into payment-hsm

Author: msmbaldwin

articles/ai-services/containers/azure-kubernetes-recipe.md

@@ -7,7 +7,7 @@ author: aahill
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: conceptual
-ms.date: 01/10/2022
+ms.date: 02/26/2024
 ms.author: aahi
 ms.custom: devx-track-azurecli
 ms.devlang: azurecli

articles/ai-services/language-service/native-document-support/use-native-documents.md

@@ -26,7 +26,7 @@ ms.author: lajanuar
 > * Azure AI Language public preview releases provide early access to features that are in active development.
 > * Features, approaches, and processes may change, prior to General Availability (GA), based on user feedback.
 
-Azure AI Language is a cloud-based service that applies Natural Language Processing (NLP) features to text-based data. The native document support capability enables you to send API requests asynchronously, using an HTTP POST request body to send your data and HTTP GET request query string to retrieve the processed data.
+Azure AI Language is a cloud-based service that applies Natural Language Processing (NLP) features to text-based data. The native document support capability enables you to send API requests asynchronously, using an HTTP POST request body to send your data and HTTP GET request query string to retrieve the status results. Your processed documents are located in your Azure Blob Storage target container.
 
 A native document refers to the file format used to create the original document such as Microsoft Word (docx) or a portable document file (pdf). Native document support eliminates the need for text preprocessing before using Azure AI Language resource capabilities. Currently, native document support is available for the following capabilities:
 

articles/ai-services/language-service/whats-new.md

@@ -7,7 +7,7 @@ author: aahill
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: whats-new
-ms.date: 01/31/2024
+ms.date: 02/26/2024
 ms.author: aahi
 ---
 

articles/ai-services/media/cognitive-services-encryption/key-vault-access-policy.png

@@ -8,7 +8,7 @@ ms.service: azure-ai-openai
 ms.topic: quickstart
 author: aahill
 ms.author: aahi
-ms.date: 01/09/2023
+ms.date: 02/26/2024
 recommendations: false
 ms.custom: references_regions 
 ---
@@ -125,7 +125,12 @@ If you're using your own index, you will be prompted in the Azure OpenAI Studio
 
 In this example, the fields mapped to **Content data** and **Title** provide information to the model to answer questions. **Title** is also used to title citation text. The field mapped to **File name** generates the citation names in the response. 
 
-Mapping these fields correctly helps ensure the model has better response and citation quality. You can additionally configure this [in the API](../reference.md#completions-extensions) using the `fieldsMapping` parameter.   
+Mapping these fields correctly helps ensure the model has better response and citation quality. You can additionally configure this [in the API](../references/on-your-data.md) using the `fieldsMapping` parameter.   
+
+### Search filter (API)
+
+If you want to implement additional value-based criteria for query execution, you can set up a search filter using the `filter` parameter in the [REST API](../references/azure-search.md).
+
 
 # [Azure Cosmos DB for MongoDB vCore](#tab/mongo-db)
 
@@ -232,7 +237,7 @@ Once you have added the URL/web address for data ingestion, the web pages from y
 
 Data is ingested into Azure AI search using the following process:
 
-1. Ingestion assets are created in Azure AI Search resource and Azure storage account. Currently these assets are: indexers, indexes, data sources, a [custom skill](/azure/search/cognitive-search-custom-skill-interface) in the search resource, and a container (later called the chunks container) in the Azure storage account. You can specify the input Azure storage container using the [Azure OpenAI studio](https://oai.azure.com/), or the [ingestion API (preview)](../reference.md#start-an-ingestion-job-preview).  
+1. Ingestion assets are created in Azure AI Search resource and Azure storage account. Currently these assets are: indexers, indexes, data sources, a [custom skill](/azure/search/cognitive-search-custom-skill-interface) in the search resource, and a container (later called the chunks container) in the Azure storage account. You can specify the input Azure storage container using the [Azure OpenAI studio](https://oai.azure.com/), or the [ingestion API (preview)](/rest/api/azureopenai/ingestion-jobs).  
 
 2. Data is read from the input container, contents are opened and chunked into small chunks with a maximum of 1,024 tokens each. If vector search is enabled, the service calculates the vector representing the embeddings on each chunk. The output of this step (called the "preprocessed" or "chunked" data) is stored in the chunks container created in the previous step. 
 
@@ -261,7 +266,7 @@ Use the following sections to learn how to improve the quality of responses give
 
 ### Runtime parameters
 
-You can modify the following additional settings in the **Data parameters** section in Azure OpenAI Studio and [the API](../reference.md#completions-extensions). You don't need to reingest your data when you update these parameters. 
+You can modify the following additional settings in the **Data parameters** section in Azure OpenAI Studio and [the API](../references/on-your-data.md). You don't need to reingest your data when you update these parameters. 
 
 
 |Parameter name  | Description  |
@@ -274,7 +279,7 @@ You can modify the following additional settings in the **Data parameters** sect
 
 You can define a system message to steer the model's reply when using Azure OpenAI On Your Data. This message allows you to customize your replies on top of the retrieval augmented generation (RAG) pattern that Azure OpenAI On Your Data uses. The system message is used in addition to an internal base prompt to provide the experience. To support this, we truncate the system message after a specific [number of tokens](#token-usage-estimation-for-azure-openai-on-your-data) to ensure the model can answer questions using your data. If you are defining extra behavior on top of the default experience, ensure that your system prompt is detailed and explains the exact expected customization. 
 
-Once you select add your dataset, you can use the **System message** section in the Azure OpenAI Studio, or the `roleInformation` [parameter in the API](../reference.md#completions-extensions).
+Once you select add your dataset, you can use the **System message** section in the Azure OpenAI Studio, or the `roleInformation` [parameter in the API](../references/on-your-data.md).
 
 :::image type="content" source="../media/use-your-data/system-message.png" alt-text="A screenshot showing the system message option in Azure OpenAI Studio." lightbox="../media/use-your-data/system-message.png":::
 
@@ -361,9 +366,9 @@ You can send a streaming request using the `stream` parameter, allowing data to
         {
             "type": "AzureCognitiveSearch",
             "parameters": {
-                "endpoint": "'$SearchEndpoint'",
-                "key": "'$SearchKey'",
-                "indexName": "'$SearchIndex'"
+                "endpoint": "'$AZURE_AI_SEARCH_ENDPOINT'",
+                "key": "'$AZURE_AI_SEARCH_API_KEY'",
+                "indexName": "'$AZURE_AI_SEARCH_INDEX'"
             }
         }
     ],
@@ -386,9 +391,9 @@ When you chat with a model, providing a history of the chat will help the model
         {
             "type": "AzureCognitiveSearch",
             "parameters": {
-                "endpoint": "'$SearchEndpoint'",
-                "key": "'$SearchKey'",
-                "indexName": "'$SearchIndex'"
+                "endpoint": "'$AZURE_AI_SEARCH_ENDPOINT'",
+                "key": "'$AZURE_AI_SEARCH_API_KEY'",
+                "indexName": "'$AZURE_AI_SEARCH_INDEX'"
             }
         }
     ],

articles/ai-services/openai/concepts/use-your-data.md

@@ -6,7 +6,7 @@ author: mrbullwinkle
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 11/14/2022
+ms.date: 2/21/2024
 ms.author: mbullwin
 ---
 
@@ -22,37 +22,66 @@ Azure OpenAI is part of Azure AI services. Azure AI services data is encrypted a
 
 By default, your subscription uses Microsoft-managed encryption keys. There's also the option to manage your subscription with your own keys called customer-managed keys (CMK). CMK offers greater flexibility to create, rotate, disable, and revoke access controls. You can also audit the encryption keys used to protect your data.
 
-## Customer-managed keys with Azure Key Vault
+## Use customer-managed keys with Azure Key Vault
 
 Customer-managed keys (CMK), also known as Bring your own key (BYOK), offer greater flexibility to create, rotate, disable, and revoke access controls. You can also audit the encryption keys used to protect your data.
 
 You must use Azure Key Vault to store your customer-managed keys. You can either create your own keys and store them in a key vault, or you can use the Azure Key Vault APIs to generate keys. The Azure AI services resource and the key vault must be in the same region and in the same Microsoft Entra tenant, but they can be in different subscriptions. For more information about Azure Key Vault, see [What is Azure Key Vault?](../../key-vault/general/overview.md).
 
-To enable customer-managed keys, you must also enable both the **Soft Delete** and **Do Not Purge** properties on the key vault.
+To enable customer-managed keys, the key vault containing your keys must meet these requirements:
 
-Only RSA keys of size 2048 are supported with Azure AI services encryption. For more information about keys, see **Key Vault keys** in [About Azure Key Vault keys, secrets and certificates](../../key-vault/general/about-keys-secrets-certificates.md).
+- You must enable both the **Soft Delete** and **Do Not Purge** properties on the key vault.
+- If you use the [Key Vault firewall](/azure/key-vault/general/access-behind-firewall), you must allow trusted Microsoft services to access the key vault.
+- The key vault must use [legacy access policies](/azure/key-vault/general/assign-access-policy).
+- You must grant the Azure OpenAI resource's system-assigned managed identity the following permissions on your key vault: *get key*, *wrap key*, *unwrap key*.
 
-## Enable customer-managed keys for your resource
+Only RSA and RSA-HSM keys of size 2048 are supported with Azure AI services encryption. For more information about keys, see **Key Vault keys** in [About Azure Key Vault keys, secrets and certificates](../../key-vault/general/about-keys-secrets-certificates.md).
+
+### Enable your Azure OpenAI resource's managed identity
+
+1. Go to your Azure AI services resource.
+1. On the left, under **Resource Management**, select **Identity**.
+1. Switch the system-assigned managed identity status to **On**.
+1. Save your changes, and confirm that you want to enable the system-assigned managed identity.
+
+### Configure your key vault's access permissions
+
+1. In the Azure portal, go to your key vault.
+1. On the left, select **Access policies**.
+   
+   If you see a message advising you that access policies aren't available, [reconfigure your key vault to use legacy access policies](/azure/key-vault/general/assign-access-policy) before continuing.
+1. Select **Create**.
+1. Under **Key permissions**, select **Get**, **Wrap Key**, and **Unwrap Key**. Leave the remaining checkboxes unselected.
+
+   :::image type="content" source="../media/cognitive-services-encryption/key-vault-access-policy.png" alt-text="Screenshot of the Azure portal page for a key vault access policy. The permissions selected are Get Key, Wrap Key, and Unwrap Key.":::
+
+1. Select **Next**.
+1. Search for the name of your Azure OpenAI resource and select its managed identity.
+1. Select **Next**.
+1. Select **Next** to skip configuring any application settings.
+1. Select **Create**.
+
+### Enable customer-managed keys on your Azure OpenAI resource
 
 To enable customer-managed keys in the Azure portal, follow these steps:
 
 1. Go to your Azure AI services resource.
-1. On the left, select **Encryption**.
+1. On the left, under **Resource Management**, select **Encryption**.
 1. Under **Encryption type**, select **Customer Managed Keys**, as shown in the following screenshot.
 
-> [!div class="mx-imgBorder"]
-> ![Screenshot of create a resource user experience](./media/encryption/encryption.png)
+   > [!div class="mx-imgBorder"]
+   > ![Screenshot of create a resource user experience.](./media/encryption/encryption.png)
 
-## Specify a key
+### Specify a key
 
 After you enable customer-managed keys, you can specify a key to associate with the Azure AI services resource.
 
-### Specify a key as a URI
+#### Specify a key as a URI
 
 To specify a key as a URI, follow these steps:
 
 1. In the Azure portal, go to your key vault.
-1. Under **Settings**, select **Keys**.
+1. Under **Objects**, select **Keys**.
 1. Select the desired key, and then select the key to view its versions. Select a key version to view the settings for that version.
 1. Copy the **Key Identifier** value, which provides the URI.
 
@@ -67,9 +96,9 @@ To specify a key as a URI, follow these steps:
 1. Under **Subscription**, select the subscription that contains the key vault.
 1. Save your changes.
 
-### Specify a key from a key vault
+#### Select a key from a key vault
 
-To specify a key from a key vault, first make sure that you have a key vault that contains a key. Then follow these steps:
+To select a key from a key vault, first make sure that you have a key vault that contains a key. Then follow these steps:
 
 1. Go to your Azure AI services resource, and then select **Encryption**.
 1. Under **Encryption key**, select **Select from Key Vault**.

articles/ai-services/openai/encrypt-data-at-rest.md

@@ -1,13 +1,13 @@
 ---
 title: How to migrate to OpenAI Python v1.x
 titleSuffix: Azure OpenAI Service
-description: Learn about migrating to the latest release of the OpenAI Python library with Azure OpenAI
+description: Learn about migrating to the latest release of the OpenAI Python library with Azure OpenAI.
 author: mrbullwinkle 
 ms.author: mbullwin 
 ms.service: azure-ai-openai
 ms.custom: devx-track-python
 ms.topic: how-to
-ms.date: 11/15/2023
+ms.date: 02/26/2024
 manager: nitinme
 ---
 
@@ -17,7 +17,7 @@ OpenAI has just released a new version of the [OpenAI Python API library](https:
 
 ## Updates
 
-- This is a completely new version of the OpenAI Python API library.
+- This is a new version of the OpenAI Python API library.
 - Starting on November 6, 2023 `pip install openai` and `pip install openai --upgrade` will install `version 1.x` of the OpenAI Python library.
 - Upgrading from `version 0.28.1` to `version 1.x` is a breaking change, you'll need to test and update your code.  
 - Auto-retry with backoff if there's an error
@@ -259,7 +259,7 @@ print(completion.model_dump_json(indent=2))
 
 ## Use your data
 
-For the full configuration steps that are required to make these code examples work, please consult the [use your data quickstart](../use-your-data-quickstart.md).
+For the full configuration steps that are required to make these code examples work, consult the [use your data quickstart](../use-your-data-quickstart.md).
 # [OpenAI Python 0.28.1](#tab/python)
 
 ```python
@@ -270,10 +270,10 @@ import requests
 
 dotenv.load_dotenv()
 
-openai.api_base = os.environ.get("AOAIEndpoint")
+openai.api_base = os.environ.get("AZURE_OPENAI_ENDPOINT")
 openai.api_version = "2023-08-01-preview"
 openai.api_type = 'azure'
-openai.api_key = os.environ.get("AOAIKey")
+openai.api_key = os.environ.get("AZURE_OPENAI_API_KEY")
 
 def setup_byod(deployment_id: str) -> None:
     """Sets up the OpenAI Python SDK to use your own data for the chat endpoint.
@@ -299,19 +299,19 @@ def setup_byod(deployment_id: str) -> None:
 
     openai.requestssession = session
 
-aoai_deployment_id = os.environ.get("AOAIDeploymentId")
+aoai_deployment_id = os.environ.get("AZURE_OPEN_AI_DEPLOYMENT_ID")
 setup_byod(aoai_deployment_id)
 
 completion = openai.ChatCompletion.create(
     messages=[{"role": "user", "content": "What are the differences between Azure Machine Learning and Azure AI services?"}],
-    deployment_id=os.environ.get("AOAIDeploymentId"),
+    deployment_id=os.environ.get("AZURE_OPEN_AI_DEPLOYMENT_ID"),
     dataSources=[  # camelCase is intentional, as this is the format the API expects
         {
             "type": "AzureCognitiveSearch",
             "parameters": {
-                "endpoint": os.environ.get("SearchEndpoint"),
-                "key": os.environ.get("SearchKey"),
-                "indexName": os.environ.get("SearchIndex"),
+                "endpoint": os.environ.get("AZURE_AI_SEARCH_ENDPOINT"),
+                "key": os.environ.get("AZURE_AI_SEARCH_API_KEY"),
+                "indexName": os.environ.get("AZURE_AI_SEARCH_INDEX"),
             }
         }
     ]
@@ -328,9 +328,9 @@ import dotenv
 
 dotenv.load_dotenv()
 
-endpoint = os.environ.get("AOAIEndpoint")
-api_key = os.environ.get("AOAIKey")
-deployment = os.environ.get("AOAIDeploymentId")
+endpoint = os.environ.get("AZURE_OPENAI_ENDPOINT")
+api_key = os.environ.get("AZURE_OPENAI_API_KEY")
+deployment = os.environ.get("AZURE_OPEN_AI_DEPLOYMENT_ID")
 
 client = openai.AzureOpenAI(
     base_url=f"{endpoint}/openai/deployments/{deployment}/extensions",
@@ -351,9 +351,9 @@ completion = client.chat.completions.create(
             {
                 "type": "AzureCognitiveSearch",
                 "parameters": {
-                    "endpoint": os.environ["SearchEndpoint"],
-                    "key": os.environ["SearchKey"],
-                    "indexName": os.environ["SearchIndex"]
+                    "endpoint": os.environ["AZURE_AI_SEARCH_ENDPOINT"],
+                    "key": os.environ["AZURE_AI_SEARCH_API_KEY"],
+                    "indexName": os.environ["AZURE_AI_SEARCH_INDEX"]
                 }
             }
         ]

articles/ai-services/openai/how-to/migration.md

@@ -7,7 +7,7 @@ ms.service: azure-ai-openai
 ms.topic: how-to
 author: aahill
 ms.author: aahi
-ms.date: 02/09/2024
+ms.date: 02/23/2024
 recommendations: false
 ---
 
@@ -33,7 +33,7 @@ Along with Azure OpenAI Studio, APIs and SDKs, you can also use the available st
 
 ## Web app customization
 
-You can customize the app's frontend and backend logic. For example, you could change the icon that appears in the center of the app by updating `/frontend/src/assets/Contoso.svg` and then redeploying the app [using the Azure CLI](https://github.com/microsoft/sample-app-aoai-chatGPT#deploy-with-the-azure-cli).  See the source code for the web app, and more information on [GitHub](https://github.com/microsoft/sample-app-aoai-chatGPT).
+You can customize the app's frontend and backend logic. The app provides several [environment variables](https://github.com/microsoft/sample-app-aoai-chatGPT#common-customization-scenarios-eg-updating-the-default-chat-logo-and-headers) for common customization scenarios such as changing the icon in the app. See the source code for the web app, and more information on [GitHub](https://github.com/microsoft/sample-app-aoai-chatGPT).
 
 When customizing the app, we recommend:
 
@@ -43,6 +43,8 @@ When customizing the app, we recommend:
 
 - When you rotate API keys for your Azure OpenAI or Azure AI Search resource, be sure to update the app settings for each of your deployed apps to use the new keys.
 
+Sample source code for the web app is available on [GitHub](https://github.com/microsoft/sample-app-aoai-chatGPT). Source code is provided "as is" and as a sample only. Customers are responsible for all customization and implementation of their web apps. 
+
 ### Updating the web app
 
 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.

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

@@ -90,9 +90,9 @@ When using the API, pass the `filter` parameter in each API request. For example
         {
             "type": "AzureCognitiveSearch",
             "parameters": {
-                "endpoint": "'$SearchEndpoint'",
-                "key": "'$SearchKey'",
-                "indexName": "'$SearchIndex'",
+                "endpoint": "'$AZURE_AI_SEARCH_ENDPOINT'",
+                "key": "'$AZURE_AI_SEARCH_API_KEY'",
+                "indexName": "'$AZURE_AI_SEARCH_INDEX'",
                 "filter": "my_group_ids/any(g:search.in(g, 'group_id1, group_id2'))"
             }
         }