Merge branch 'main' into release-foundry-toc

v-alje · v-alje · commit 9504c1eb456d · 2025-01-28T18:22:51.000Z
diff --git a/articles/ai-foundry/model-inference/concepts/deployment-types.md b/articles/ai-foundry/model-inference/concepts/deployment-types.md
@@ -31,12 +31,13 @@ To learn more about deployment options for Azure OpenAI models see [Azure OpenAI
 
 Models from third-party model providers with pay-as-you-go billing (collectively called Models-as-a-Service), makes models available in Azure AI model inference under **standard** deployments with a Global processing option (`Global-Standard`). 
 
-Models-as-a-Service offers regional deployment options under [Serverless API endpoints](../../../ai-studio/how-to/deploy-models-serverless.md) in Azure AI Foundry. Prompts and outputs are processed within the geography specified during deployment. However, those deployments can't be accessed using the Azure AI model inference endpoint in Azure AI Services.
-
 ### Global-Standard
 
 Global deployments leverage Azure's global infrastructure to dynamically route traffic to the data center with best availability for each request. Global standard provides the highest default quota and eliminates the need to load balance across multiple resources. Data stored at rest remains in the designated Azure geography, while data may be processed for inferencing in any Azure location. Learn more about [data residency](https://azure.microsoft.com/explore/global-infrastructure/data-residency/).
 
+> [!NOTE]
+> Models-as-a-Service offers regional deployment options under [Serverless API endpoints](../../../ai-studio/how-to/deploy-models-serverless.md) in Azure AI Foundry. Prompts and outputs are processed within the geography specified during deployment. However, those deployments can't be accessed using the Azure AI model inference endpoint in Azure AI Services.
+
 ## Control deployment options
 
 Administrators can control which model deployment types are available to their users by using Azure Policies. Learn more about [How to control AI model deployment with custom policies](../../../ai-studio/how-to/custom-policy-model-deployment.md).
diff --git a/articles/ai-foundry/model-inference/faq.yml b/articles/ai-foundry/model-inference/faq.yml
@@ -5,7 +5,7 @@ metadata:
   description: Get answers to the most popular questions about Azure AI model inference
   #services: cognitive-services
   manager: nitinme
-  ms.service: azure-ai-models
+  ms.service: azure-ai-model-inference
   ms.topic: faq
   ms.date: 1/21/2025
   ms.author: fasantia
diff --git a/articles/ai-foundry/model-inference/index.yml b/articles/ai-foundry/model-inference/index.yml
@@ -6,7 +6,7 @@ summary: Azure AI model inference provides access to the most powerful models av
 metadata:
   title: Azure AI model inference documentation - Quickstarts, How-to's, API Reference - Azure AI Foundry | Microsoft Docs
   description: Learn how to use flagship models available in the Azure AI model catalog from the key model providers in the industry, including OpenAI, Microsoft, Meta, Mistral, Cohere, G42, and AI21 Labs.
-  ms.service: azure-ai-models
+  ms.service: azure-ai-model-inference
   ms.custom:
   ms.topic: landing-page
   author: mrbullwinkle
diff --git a/articles/ai-services/agents/includes/quickstart-csharp.md b/articles/ai-services/agents/includes/quickstart-csharp.md
@@ -38,6 +38,12 @@ dotnet add package Azure.AI.Projects
 dotnet add package Azure.Identity
 ```
 
+Next, to authenticate your API requests and run the program, use the [az login](/cli/azure/authenticate-azure-cli-interactively) command to sign into your Azure subscription.
+
+```azurecli
+az login
+```
+
 Use the following code to create and run an agent. To run this code, you will need to create a connection string using information from your project. This string is in the format:
 
 `<HostName>;<AzureSubscriptionId>;<ResourceGroup>;<ProjectName>`
@@ -56,6 +62,7 @@ For example, your connection string may look something like:
 
 Set this connection string as an environment variable named `PROJECT_CONNECTION_STRING`.
 
+
 ```csharp
 // Copyright (c) Microsoft Corporation. All rights reserved.
 // Licensed under the MIT License.
diff --git a/articles/ai-services/agents/includes/quickstart-python-openai.md b/articles/ai-services/agents/includes/quickstart-python-openai.md
@@ -41,6 +41,12 @@ pip install azure-identity
 pip install openai
 ```
 
+Next, to authenticate your API requests and run the program, use the [az login](/cli/azure/authenticate-azure-cli-interactively) command to sign into your Azure subscription.
+
+```azurecli
+az login
+```
+
 Use the following code to create and run an agent. To run this code, you will need to create a connection string using information from your project. This string is in the format:
 
 `<HostName>;<AzureSubscriptionId>;<ResourceGroup>;<ProjectName>`
diff --git a/articles/ai-services/agents/includes/quickstart-python.md b/articles/ai-services/agents/includes/quickstart-python.md
@@ -38,6 +38,11 @@ Run the following commands to install the python packages.
 pip install azure-ai-projects
 pip install azure-identity
 ```
+Next, to authenticate your API requests and run the program, use the [az login](/cli/azure/authenticate-azure-cli-interactively) command to sign into your Azure subscription.
+
+```azurecli
+az login
+```
 
 Use the following code to create and run an agent. To run this code, you will need to create a connection string using information from your project. This string is in the format:
 
@@ -115,7 +120,7 @@ with project_client:
     print(f"Messages: {messages}")
 
     # Get the last message from the sender
-    last_msg = messages.get_last_text_message_by_sender("assistant")
+    last_msg = messages.get_last_text_message_by_role("assistant")
     if last_msg:
         print(f"Last Message: {last_msg.text.value}")
 
diff --git a/articles/ai-services/immersive-reader/how-to-cache-token.md b/articles/ai-services/immersive-reader/how-to-cache-token.md
@@ -61,7 +61,7 @@ public async Task<string> GetTokenAsync()
 
 The `AuthenticationResult` object has an `AccessToken` property, which is the actual token you use when launching the Immersive Reader using the SDK. It also has an `ExpiresOn` property that denotes when the token expires. Before launching the Immersive Reader, you can check whether the token is expired, and acquire a new token only if it expired.
 
-## Using Node.JS
+## Using Node.js
 
 Add the [request](https://www.npmjs.com/package/request) npm package to your project. Use the following code to acquire a token, using the authentication values you got when you [created the Immersive Reader resource](./how-to-create-immersive-reader.md).
 
diff --git a/articles/ai-services/openai/how-to/assistant.md b/articles/ai-services/openai/how-to/assistant.md
@@ -7,7 +7,7 @@ manager: nitinme
 ms.service: azure-ai-openai
 ms.custom: references_regions
 ms.topic: how-to
-ms.date: 05/20/2024
+ms.date: 01/28/2025
 author: aahill
 ms.author: aahi
 recommendations: false
@@ -26,11 +26,6 @@ Azure OpenAI Assistants (Preview) allows you to create AI assistants tailored to
 
 Code interpreter is available in all regions supported by Azure OpenAI Assistants. The [models page](../concepts/models.md#assistants-preview) contains the most up-to-date information on regions/models where Assistants are currently supported.
 
-### API Versions
-
-- `2024-02-15-preview`
-- `2024-05-01-preview`
-
 ### Supported file types
 
 |File format|MIME Type|Code Interpreter |
diff --git a/articles/ai-services/openai/how-to/assistants-logic-apps.md b/articles/ai-services/openai/how-to/assistants-logic-apps.md
@@ -6,7 +6,7 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 05/21/2024
+ms.date: 01/28/2025
 author: aahill
 ms.author: aahi
 recommendations: false
diff --git a/articles/ai-services/openai/how-to/code-interpreter.md b/articles/ai-services/openai/how-to/code-interpreter.md
@@ -6,7 +6,7 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 10/15/2024
+ms.date: 01/28/2025
 author: aahill
 ms.author: aahi
 recommendations: false
@@ -32,8 +32,7 @@ We recommend using assistants with the latest models to take advantage of the ne
 
 ### API Versions
 
-- `2024-02-15-preview`
-- `2024-05-01-preview`
+- Starting in `2024-02-15-preview`
 
 ### Supported file types
 
@@ -94,7 +93,7 @@ assistant = client.beta.assistants.create(
 # [REST](#tab/rest)
 
 > [!NOTE]
-> With Azure OpenAI the `model` parameter requires model deployment name. If your model deployment name is different than the underlying model name then you would adjust your code to ` "model": "{your-custom-model-deployment-name}"`.
+> With Azure OpenAI the `model` parameter requires model deployment name. If your model deployment name is different than the underlying model name, then you would adjust your code to ` "model": "{your-custom-model-deployment-name}"`.
 
 ```console
 curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/assistants?api-version=2024-05-01-preview \
diff --git a/articles/ai-services/openai/how-to/file-search.md b/articles/ai-services/openai/how-to/file-search.md
@@ -6,7 +6,7 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 06/03/2024
+ms.date: 01/28/2025
 author: aahill
 ms.author: aahi
 recommendations: false
@@ -30,7 +30,7 @@ File search is available in [regions](../concepts/models.md#assistants-preview)
 
 ### API Version
 
-* 2024-05-01-preview
+* Starting in 2024-05-01-preview
 
 ### Supported file types
 
diff --git a/articles/ai-services/openai/how-to/on-your-data-best-practices.md b/articles/ai-services/openai/how-to/on-your-data-best-practices.md
@@ -4,7 +4,7 @@ titleSuffix: Azure OpenAI Service
 description: Learn about the best practices for using Azure OpenAI On Your Data, along with how to fix common problems.
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 04/08/2024
+ms.date: 01/28/2025
 ms.custom: references_regions, build-2023, build-2023-dataai, refefences_regions
 manager: nitinme
 author: aahill
diff --git a/articles/ai-services/openai/references/azure-machine-learning.md b/articles/ai-services/openai/references/azure-machine-learning.md
@@ -5,7 +5,7 @@ description: Learn how to use Azure OpenAI on your Azure Machine Learning index
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 03/14/2024
+ms.date: 01/28/2025
 author: aahill
 ms.author: aahi
 recommendations: false
diff --git a/articles/ai-services/openai/references/elasticsearch.md b/articles/ai-services/openai/references/elasticsearch.md
@@ -5,7 +5,7 @@ description: Learn how to use Azure OpenAI on your Elasticsearch data Python & R
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 03/14/2024
+ms.date: 01/28/2025
 author: aahill
 ms.author: aahi
 recommendations: false
@@ -14,7 +14,7 @@ ms.custom: devx-track-python
 
 # Data source - Elasticsearch (preview)
 
-The configurable options for Elasticsearch when using Azure OpenAI On Your Data. This data source is supported in API version `2024-02-15-preview`.
+The configurable options for Elasticsearch when using Azure OpenAI On Your Data. This data source is supported starting in API version `2024-02-15-preview`.
 
 |Name | Type | Required | Description |
 |--- | --- | --- | --- |
diff --git a/articles/ai-services/openai/references/pinecone.md b/articles/ai-services/openai/references/pinecone.md
@@ -5,7 +5,7 @@ description: Learn how to use Azure OpenAI on your Pinecone data Python & REST A
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 03/14/2024
+ms.date: 01/28/2025
 author: aahill
 ms.author: aahi
 recommendations: false
@@ -14,7 +14,7 @@ ms.custom: devx-track-python
 
 # Data source - Pinecone (preview)
 
-The configurable options of Pinecone when using Azure OpenAI On Your Data. This data source is supported in API version `2024-02-15-preview`.
+The configurable options of Pinecone when using Azure OpenAI On Your Data. This data source is supported starting in API version `2024-02-15-preview`.
 
 |Name | Type | Required | Description |
 |--- | --- | --- | --- |
diff --git a/articles/search/hybrid-search-how-to-query.md b/articles/search/hybrid-search-how-to-query.md
@@ -226,7 +226,7 @@ POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/d
 
 ## Semantic hybrid search
 
-Assuming that you [enabled semantic ranker](semantic-how-to-enable-disable.md) and your index definition includes a [semantic configuration](semantic-how-to-query-request.md), you can formulate a query that includes vector search and keyword search, with semantic ranking over the merged result set. Optionally, you can add captions and answers. 
+Assuming that you [have semantic ranker](semantic-how-to-enable-disable.md) and your index definition includes a [semantic configuration](semantic-how-to-query-request.md), you can formulate a query that includes vector search and keyword search, with semantic ranking over the merged result set. Optionally, you can add captions and answers. 
 
 Whenever you use semantic ranking with vectors, make sure `k` is set to 50. Semantic ranker uses up to 50 matches as input. Specifying less than 50 deprives the semantic ranking models of necessary inputs.
 
diff --git a/articles/search/index.yml b/articles/search/index.yml
@@ -5,7 +5,7 @@ summary: Information retrieval at scale for vector and text content in tradition
 metadata:
   title: Azure AI Search documentation
   description: Information retrieval at scale for vector and text content in traditional or generative search scenarios.
-  ms.service: service
+  ms.service: azure-ai-search
   ms.custom:
     - ignite-2023
     - ignite-2024
diff --git a/articles/search/search-indexer-how-to-access-private-sql.md b/articles/search/search-indexer-how-to-access-private-sql.md
@@ -7,7 +7,7 @@ author: mattgotteiner
 ms.author: magottei
 ms.service: azure-ai-search
 ms.topic: how-to
-ms.date: 12/10/2024
+ms.date: 01/27/2025
 ---
 
 # Create a shared private link for a SQL managed instance from Azure AI Search
@@ -38,11 +38,11 @@ Although you can call the Management REST API directly, it's easier to use the A
 
 ## 1 - Retrieve connection information
 
-Retrieve the FQDN of the managed instance, including the DNS zone. The DNS zone is part of the domain name of the SQL Managed Instance. For example, if the FQDN of the SQL Managed Instance is `my-sql-managed-instance.00000000000.database.windows.net`, the DNS zone is `00000000000`.
+In this section, get the DNS zone from the host name and a connection string.
 
 1. In Azure portal, find the SQL managed instance object.
 
-1. On the **Overview** tab, locate the Host property. Copy the DNS zone portion of the FQDN for the next step.
+1. On the **Overview** tab, locate the Host property. Copy the *DNS zone* portion of the FQDN for the next step. The DNS zone is part of the domain name of the SQL Managed Instance. For example, if the FQDN of the SQL Managed Instance is `my-sql-managed-instance.a1b22c333d44.database.windows.net`, the DNS zone is `a1b22c333d44`.
 
 1. On the **Connection strings** tab, copy the ADO.NET connection string for a later step. It's needed for the data source connection when testing the private connection.
 
@@ -64,11 +64,11 @@ For more information about connection properties, see [Create an Azure SQL Manag
    }
    ```
 
-1. Provide a meaningful name for the shared private link. The shared private link appears alongside other private endpoints. A name like "shared-private-link-for-search" can remind you how it's used.
+   Provide a meaningful name for the shared private link. The shared private link appears alongside other private endpoints. A name like "shared-private-link-for-search" can remind you how it's used.
 
-1. Paste in the DNS zone name in "dnsZonePrefix" that you retrieved in an earlier step.
+   Paste in the DNS zone name in "dnsZonePrefix" that you retrieved in an earlier step.
 
-1. Edit the "privateLinkResourceId" to reflect the private endpoint of your managed instance. Provide the subscription ID, resource group name, and object name of the managed instance.
+   Edit the "privateLinkResourceId", substitute valid for values for the placeholders. Provide a valid subscription ID, resource group name, and managed instance name.
 
 1. Save the file locally as *create-pe.json* (or use another name, remembering to update the Azure CLI syntax in the next step).
 
@@ -84,7 +84,7 @@ For more information about connection properties, see [Create an Azure SQL Manag
 
 1. Call the `az rest` command to use the [Management REST API](/rest/api/searchmanagement) of Azure AI Search. 
 
-   Because shared private link support for SQL managed instances is still in preview, you need a preview version of the REST API. Use `2021-04-01-preview` or a later preview API version for this step. We recommend using the latest preview API version.
+   Because shared private link support for SQL managed instances is still in preview, you need a preview version of the management REST API. Use `2021-04-01-preview` or a later preview API version for this step. We recommend using the latest preview API version.
 
    ```azurecli
    az rest --method put --uri https://management.azure.com/subscriptions/{{search-service-subscription-ID}}/resourceGroups/{{search service-resource-group}}/providers/Microsoft.Search/searchServices/{{search-service-name}}/sharedPrivateLinkResources/{{shared-private-link-name}}?api-version=2024-06-01-preview --body @create-pe.json
@@ -122,11 +122,9 @@ On the Azure AI Search side, you can confirm request approval by revisiting the
 
 You can now configure an indexer and its data source to use an outbound private connection to your managed instance.
 
-You could use the [**Import data**](search-get-started-portal.md) wizard for this step, but the indexer that's generated won't be valid for this scenario. You'll need to modify the indexer JSON property as described in this step to make it compliant for this scenario. You'll then need to [reset and rerun the indexer](search-howto-run-reset-indexers.md) to fully test the pipeline using the updated indexer.
+This article assumes a [REST client](search-get-started-rest.md) and uses the REST APIs.
 
-This article assumes a [REST client](search-get-started-rest.md) and uses the REST APIs to make it easier to see all of the properties. Recall that REST API calls for indexers and data sources use the [Search REST APIs](/rest/api/searchservice/), not the [Management REST APIs](/rest/api/searchmanagement/) used to create the shared private link. The syntax and API versions are different between the two REST APIs.
-
-1. [Create the data source definition](search-how-to-index-sql-database.md) as you would normally for Azure SQL. The format of the connection string is slightly different for a managed instance, but other properties are the same as if you were configuring a data source connection to Azure SQL database.
+1. [Create the data source definition](search-how-to-index-sql-database.md) as you would normally for Azure SQL. By default, a managed instance listens on port 3342, but on a virtual network it listens on 1433.
 
     Provide the connection string that you copied earlier with an Initial Catalog specified.
 
@@ -139,7 +137,7 @@ This article assumes a [REST client](search-get-started-rest.md) and uses the RE
          "description" : "A database for testing Azure AI Search indexes.",
          "type" : "azuresql",
          "credentials" : { 
-             "connectionString" : "Server=tcp:contoso.public.0000000000.database.windows.net,1433;Persist Security Info=false; User ID=<your user name>; Password=<your password>;MultipleActiveResultsSets=False; Encrypt=True;Connection Timeout=30;Initial Catalog=<your database name>"
+             "connectionString" : "Server=tcp:contoso.a1b22c333d44.database.windows.net,1433;Persist Security Info=false; User ID=<your user name>; Password=<your password>;MultipleActiveResultsSets=False; Encrypt=True;Connection Timeout=30;Initial Catalog=<your database name>"
             },
          "container" : { 
              "name" : "Name of table or view to index",
@@ -182,7 +180,7 @@ You can use [**Search explorer**](search-explorer.md) in Azure portal to check t
 
 If you ran the indexer in the previous step and successfully indexed content from your managed instance, then the test was successful. However, if the indexer fails or there's no content in the index, you can modify your objects and repeat testing by choosing any client that can invoke an outbound request from an indexer. 
 
-An easy choice is [running an indexer](search-howto-run-reset-indexers.md) in Azure portal, but you can also try a [REST client](search-get-started-rest.md) and REST APIs for more precision. Assuming that your search service isn't also configured for a private connection, the REST client connection to Search can be over the public internet.
+An easy choice is [running an indexer](search-howto-run-reset-indexers.md) in Azure portal, but you can also try a [REST client](search-get-started-rest.md) and REST APIs for more precision. Assuming that your search service isn't also configured for a private connection, the REST client connection to Azure AI Search can be over the public internet.
 
 Here are some reminders for testing:
 
diff --git a/articles/search/search-manage-rest.md b/articles/search/search-manage-rest.md
@@ -229,7 +229,7 @@ PATCH https://management.azure.com/subscriptions/{{subscriptionId}}/resourcegrou
 
 ## Disable semantic ranker
 
-Although [semantic ranker isn't enabled](semantic-how-to-enable-disable.md) by default, you could lock down the feature at the service level for greater certainty it can't be used.
+[Semantic ranker is enabled](semantic-how-to-enable-disable.md) by default at the free plan that allows up to 1,000 requests per month at no charge. You can lock down the feature at the service level to prevent usage.
 
 ```http
 ### disable semantic ranker
diff --git a/articles/search/search-manage.md b/articles/search/search-manage.md
@@ -109,7 +109,7 @@ Internally, Microsoft collects telemetry data about your service and the platfor
 
 ### Enable semantic ranker
 
-Semantic ranker is free for the first 1,000 requests per month, but you must opt in to get the free quota. 
+Semantic ranker is free for the first 1,000 requests per month. It's enabled by default on newer services.
 
 In Azure portal, under **Settings** on the leftmost pane, select **Semantic ranker** and then choose the Free plan. For more information, see [Enable semantic ranker](semantic-how-to-enable-disable.md).
 
diff --git a/articles/search/semantic-how-to-enable-disable.md b/articles/search/semantic-how-to-enable-disable.md
diff --git a/articles/search/semantic-search-overview.md b/articles/search/semantic-search-overview.md
