Merge pull request #4125 from HeidiSteen/heidist-freshness

JamesJBarnett · web-flow · commit f33826307276 · 2025-04-14T16:54:10.000-07:00
April freshness pass
diff --git a/articles/search/cognitive-search-concept-image-scenarios.md b/articles/search/cognitive-search-concept-image-scenarios.md
@@ -6,23 +6,23 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: azure-ai-search
 ms.topic: how-to
-ms.date: 10/15/2024
+ms.date: 04/14/2025
 ms.custom:
   - devx-track-csharp
   - ignite-2023
 ---
 
 # Extract text and information from images by using AI enrichment
 
-Through [AI enrichment](cognitive-search-concept-intro.md), Azure AI Search gives you several options for creating and extracting searchable text from images, including:
+Images often contain useful information that's relevant in search scenarios. You can [vectorize images](search-get-started-portal-image-search.md) to represent visual content in your search index. Or, you can use [AI enrichment and skillsets](cognitive-search-concept-intro.md) to create and extract searchable *text* from images, including:
 
 + [OCR](cognitive-search-skill-ocr.md) for optical character recognition of text and digits
 + [Image Analysis](cognitive-search-skill-image-analysis.md) that describes images through visual features
 + [Custom skills](#passing-images-to-custom-skills) to invoke any external image processing that you want to provide
 
 By using OCR, you can extract text and from photos or pictures, such as the word *STOP* in a stop sign. Through image analysis, you can generate a text representation of an image, such as *dandelion* for a photo of a dandelion, or the color *yellow*. You can also extract metadata about the image, such as its size.
 
-This article covers the fundamentals of working with images, and also describes several common scenarios, such as working with embedded images, custom skills, and overlaying visualizations on original images.
+This article covers the fundamentals of working with images in skillsets, and also describes several common scenarios, such as working with embedded images, custom skills, and overlaying visualizations on original images.
 
 To work with image content in a skillset, you need:
 
diff --git a/articles/search/cognitive-search-custom-skill-web-api.md b/articles/search/cognitive-search-custom-skill-web-api.md
@@ -7,8 +7,8 @@ ms.author: gimondra
 ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
-ms.topic: conceptual
-ms.date: 10/21/2024
+ms.topic: reference
+ms.date: 04/14/2025
 ---
 
 # Custom Web API skill in an Azure AI Search enrichment pipeline
diff --git a/articles/search/cognitive-search-output-field-mapping.md b/articles/search/cognitive-search-output-field-mapping.md
@@ -8,7 +8,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 10/15/2024
+ms.date: 04/14/2025
 ---
 
 # Map enriched output to fields in a search index in Azure AI Search
diff --git a/articles/search/index-add-suggesters.md b/articles/search/index-add-suggesters.md
@@ -8,7 +8,7 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: azure-ai-search
 ms.topic: conceptual
-ms.date: 10/21/2024
+ms.date: 04/14/2025
 ms.custom:
   - devx-track-csharp
   - devx-track-dotnet
@@ -23,7 +23,7 @@ Matches on partial terms can be either an autocompleted query or a suggested mat
 
 ## Typeahead experiences in Azure AI Search
 
-Typeahead can use *autocomplete*, which completes a partial input for a whole term query, or *suggestions* that invite click through to a particular match. Autocomplete produces a query. Suggestions produce a matching document.
+Typeahead can be either *autocomplete*, which completes a partial input for a whole term query, or *suggestions* that invite click through to a particular match. Autocomplete produces a query. Suggestions produce a matching document.
 
 The following screenshot illustrates both. Autocomplete anticipates a potential term, finishing *tw* with *in*. Suggestions are mini search results, where a field like `hotel name` represents a matching hotel search document from the index. For suggestions, you can surface any field that provides descriptive information.
 
diff --git a/articles/search/search-add-autocomplete-suggestions.md b/articles/search/search-add-autocomplete-suggestions.md
@@ -10,7 +10,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 10/22/2024
+ms.date: 04/14/2025
 ---
 
 # Add autocomplete and search suggestions in client apps
diff --git a/articles/search/search-blob-metadata-properties.md b/articles/search/search-blob-metadata-properties.md
@@ -8,8 +8,8 @@ ms.author: heidist
 ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
-ms.topic: conceptual
-ms.date: 10/21/2024
+ms.topic: reference
+ms.date: 04/14/2025
 ---
 
 # Content metadata properties used in Azure AI Search
diff --git a/articles/search/search-how-to-create-search-index.md b/articles/search/search-how-to-create-search-index.md
@@ -7,7 +7,7 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: azure-ai-search
 ms.topic: how-to
-ms.date: 11/01/2024
+ms.date: 04/14/2025
 ---
 
 # Create an index in Azure AI Search
diff --git a/articles/search/search-how-to-define-index-projections.md b/articles/search/search-how-to-define-index-projections.md
@@ -8,12 +8,12 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 10/10/2024
+ms.date: 04/14/2025
 ---
 
 # Define an index projection for parent-child indexing
 
-For indexes containing chunked documents, an index projection specifies how parent-child content is mapped to fields in a search index for one-to-many indexing. Through an index projection, you can send content to:
+For indexes containing chunked documents, an *index projection* specifies how parent-child content is mapped to fields in a search index for one-to-many indexing. Through an index projection, you can send content to:
 
 - A single index, where the parent fields repeat for each chunk, but the grain of the index is at the chunk level. The [RAG tutorial](tutorial-rag-build-solution-index-schema.md) is an example of this approach.
 
diff --git a/articles/search/search-how-to-dotnet-sdk.md b/articles/search/search-how-to-dotnet-sdk.md
@@ -1,15 +1,15 @@
 ---
-title: Use Azure.Search.Documents (v11) in .NET
+title: Use Azure.Search.Documents in .NET
 titleSuffix: Azure AI Search
-description: Learn how to create and manage search objects in a .NET application using C# and the Azure.Search.Documents (v11) client library.
+description: Learn how to create and manage search objects in a .NET application using C# and the Azure.Search.Documents client library.
 
 manager: nitinme
 author: HeidiSteen
 ms.author: heidist
 ms.devlang: csharp
 ms.service: azure-ai-search
 ms.topic: how-to
-ms.date: 10/23/2024
+ms.date: 04/14/2025
 ms.custom:
   - devx-track-csharp
   - devx-track-dotnet
@@ -18,13 +18,9 @@ ms.custom:
 
 # How to use Azure.Search.Documents in a .NET application
 
-This article explains how to create and manage search objects using C# and the [**Azure.Search.Documents**](/dotnet/api/overview/azure/search) (version 11) client library in the Azure SDK for .NET.
+This article explains how to create and manage search objects using C# and the [**Azure.Search.Documents**](/dotnet/api/overview/azure/search) client library in the Azure SDK for .NET.
 
-## About version 11
-
-Azure SDK for .NET includes an [**Azure.Search.Documents**](/dotnet/api/overview/azure/search) client library from the Azure SDK team that is functionally equivalent to the previous client library, [Microsoft.Azure.Search](/dotnet/api/microsoft.azure.search). Version 11 is more consistent in terms of Azure programmability. Some examples include [`AzureKeyCredential`](/dotnet/api/azure.azurekeycredential) key authentication, and [System.Text.Json.Serialization](/dotnet/api/system.text.json.serialization) for JSON serialization.
-
-As with previous versions, you can use this library to:
+You can use this library for data plane operations, including:
 
 + Create and manage search indexes, data sources, indexers, skillsets, and synonym maps
 + Load and manage search documents in an index
@@ -40,19 +36,13 @@ The client library defines classes like `SearchIndex`, `SearchField`, and `Searc
 + [`Azure.Search.Documents.Indexes.Models`](/dotnet/api/azure.search.documents.indexes.models)
 + [`Azure.Search.Documents.Models`](/dotnet/api/azure.search.documents.models)
 
-Version 11 targets the [2020-06-30 search service specification](https://github.com/Azure/azure-rest-api-specs/tree/main/specification/search/data-plane/Azure.Search/stable/2020-06-30). 
-
-The client library doesn't provide [service management operations](/rest/api/searchmanagement/), such as creating and scaling search services and managing API keys. If you need to manage your search resources from a .NET application, use the [Microsoft.Azure.Management.Search](/dotnet/api/microsoft.azure.management.search) library in the Azure SDK for .NET.
-
-## Upgrade to v11
-
-If you've been using the previous version of the .NET SDK and you'd like to upgrade to the current generally available version, see [Upgrade to Azure AI Search .NET SDK version 11](search-dotnet-sdk-migration-version-11.md).
+The **Azure.Search.Documents** client library doesn't provide [service management operations](/rest/api/searchmanagement/), such as creating and scaling search services and managing API keys. If you need to manage your search resources from a .NET application, use the [Azure.ResourceManager.Search](/dotnet/api/overview/azure/resourcemanager.search-readme) library in the Azure SDK for .NET.
 
 ## SDK requirements
 
 + Visual Studio 2019 or later.
 
-+ Your own Azure AI Search service. In order to use the SDK, you need the name of your service and one or more API keys. [Create a service in the Azure portal](search-create-service-portal.md) if you don't have one.
++ [Azure AI Search](search-create-service-portal.md)
 
 + Download the [NuGet package](https://www.nuget.org/packages/Azure.Search.Documents) using **Tools** > **NuGet Package Manager** > **Manage NuGet Packages for Solution** in Visual Studio. Search for the package name `Azure.Search.Documents`.
 
diff --git a/articles/search/search-how-to-load-search-index.md b/articles/search/search-how-to-load-search-index.md
@@ -9,7 +9,7 @@ ms.author: heidist
 
 ms.service: azure-ai-search
 ms.topic: how-to
-ms.date: 03/21/2025
+ms.date: 04/14/2025
 ---
 
 # Load data into a search index in Azure AI Search
diff --git a/articles/search/search-howto-complex-data-types.md b/articles/search/search-howto-complex-data-types.md
@@ -11,7 +11,7 @@ ms.custom:
   - ignite-2023
 ms.service: azure-ai-search
 ms.topic: how-to
-ms.date: 10/21/2024
+ms.date: 04/14/2025
 ---
 
 # Model complex data types in Azure AI Search
diff --git a/articles/search/search-howto-powerapps.md b/articles/search/search-howto-powerapps.md
@@ -8,7 +8,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: tutorial
-ms.date: 10/31/2024
+ms.date: 04/14/2025
 ---
 
 # Tutorial: Query an Azure AI Search index from Power Apps
diff --git a/articles/search/search-query-create.md b/articles/search/search-query-create.md
@@ -10,7 +10,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 10/31/2024
+ms.date: 04/14/2025
 ---
 
 # Create a full text query in Azure AI Search
@@ -29,7 +29,7 @@ In Azure AI Search, a query is a read-only request against the docs collection o
 
 A full text query is specified in a `search` parameter and consists of terms, quote-enclosed phrases, and operators. Other parameters add more definition to the request.
 
-The following [Search POST REST API](/rest/api/searchservice/documents/search-post) call illustrates a query request using the mentioned parameters.
+The following [Search POST REST API](/rest/api/searchservice/documents/search-post) call illustrates a query request using `search` and other parameters.
 
 ```http
 POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2024-07-01
@@ -46,7 +46,7 @@ POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/
 
 ### Key points
 
-+ **`search`** provides the match criteria, usually whole terms or phrases, with or without operators. Any field that is attributed as *searchable* in the index schema is a candidate for this parameter.
++ **`search`** provides the match criteria, usually whole terms or phrases, with or without operators. Any field that is attributed as *searchable* in the index schema is within scope for a search operation.
 
 + **`queryType`** sets the parser: *simple*, *full*. The [default simple query parser](search-query-simple-examples.md) is optimal for full text search. The [full Lucene query parser](search-query-lucene-examples.md) is for advanced query constructs like regular expressions, proximity search, fuzzy and wildcard search. This parameter can also be set to *semantic* for [semantic ranking](semantic-search-overview.md) for advanced semantic modeling on the query response.
 
@@ -66,7 +66,7 @@ Parameters used to shape the response:
 
 ## Choose a client
 
-For early development and proof-of-concept testing, start with the Azure portal or a REST client. Both approaches are interactive, useful for targeted testing, and help you assess the effects of different properties without having to write any code.
+For early development and proof-of-concept testing, start with the Azure portal or a REST client or a Jupyter notebook. These approaches are interactive, useful for targeted testing, and help you assess the effects of different properties without having to write any code.
 
 To call search from within an app, use the `Azure.Document.Search` client libraries in the Azure SDKs for .NET, Java, JavaScript, and Python.
 
diff --git a/articles/search/search-query-fuzzy.md b/articles/search/search-query-fuzzy.md
@@ -10,7 +10,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 10/31/2024
+ms.date: 04/14/2025
 ---
 # Fuzzy search to correct misspellings and typos
 
diff --git a/articles/search/search-query-lucene-examples.md b/articles/search/search-query-lucene-examples.md
@@ -11,7 +11,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 10/31/2024
+ms.date: 04/14/2025
 ---
 
 # Examples of *full* Lucene search syntax (advanced queries)
diff --git a/articles/search/search-query-partial-matching.md b/articles/search/search-query-partial-matching.md
@@ -10,7 +10,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 10/21/2024
+ms.date: 04/14/2025
 ---
 
 # Partial term search and patterns with special characters (hyphens, wildcard, regex, patterns)
diff --git a/articles/search/search-query-simple-examples.md b/articles/search/search-query-simple-examples.md
@@ -10,7 +10,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 10/31/2024
+ms.date: 04/14/2025
 ---
 
 # Examples of *simple* search queries in Azure AI Search
diff --git a/articles/search/search-reliability.md b/articles/search/search-reliability.md
@@ -6,7 +6,7 @@ author: mattgotteiner
 ms.author: magottei
 ms.service: azure-ai-search
 ms.topic: conceptual
-ms.date: 03/21/2025
+ms.date: 04/14/2025
 ms.custom:
   - subject-reliability
   - references_regions
diff --git a/articles/search/search-security-get-encryption-keys.md b/articles/search/search-security-get-encryption-keys.md
@@ -10,7 +10,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 10/30/2024
+ms.date: 04/14/2025
 ---
 
 # Find encrypted objects and information
@@ -41,7 +41,7 @@ You must have [Search Service Contributor](search-security-rbac.md#built-in-role
 
 1. On the left side, select **Keys** and copy an admin API. 
 
-For the remaining steps, switch to PowerShell and the REST API. the Azure portal doesn't show encryption key information for any object.
+For the remaining steps, switch to PowerShell and the REST API. The Azure portal doesn't show encryption key information for any object.
 
 ## Retrieve object properties
 
diff --git a/articles/search/search-synonyms.md b/articles/search/search-synonyms.md
@@ -10,7 +10,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 10/28/2024
+ms.date: 04/14/2025
 ---
 
 # Add synonyms in Azure AI Search
diff --git a/articles/search/search-what-is-an-index.md b/articles/search/search-what-is-an-index.md
@@ -11,7 +11,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 10/21/2024
+ms.date: 04/14/2025
 ---
 
 # Search indexes in Azure AI Search
diff --git a/articles/search/service-configure-firewall.md b/articles/search/service-configure-firewall.md
@@ -10,7 +10,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 09/24/2024
+ms.date: 04/14/2025
 ---
 
 # Configure network access and firewall rules for Azure AI Search
diff --git a/articles/search/service-create-private-endpoint.md b/articles/search/service-create-private-endpoint.md
@@ -9,7 +9,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 10/08/2024
+ms.date: 04/14/2025
 ---
 
 # Create a private endpoint for a secure connection to Azure AI Search
@@ -18,7 +18,7 @@ This article explains how to configure a private connection to Azure AI Search s
 
 + [Create an Azure virtual network](#create-the-virtual-network), or use an existing one
 + [Configure a search service to use a private endpoint](#create-a-search-service-with-a-private-endpoint)
-+ [Create an Azure virtual machine in the same virtual network](#create-a-virtual-machine)
++ [Create an Azure virtual machine (client) in the same virtual network](#create-a-virtual-machine)
 + [Test using a browser session on the virtual machine](#connect-to-the-vm)
 
 Other Azure resources that might privately connect to Azure AI Search include Azure OpenAI for "use your own data" scenarios. Azure AI Foundry doesn't run in a virtual network, but it can be configured on the backend to send requests over the Microsoft backbone network. Configuration for this traffic pattern is enabled by Microsoft when your request is submitted and approved. For this scenario:
diff --git a/articles/search/tutorial-rag-build-solution.md b/articles/search/tutorial-rag-build-solution.md
@@ -8,13 +8,13 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: azure-ai-search
 ms.topic: overview
-ms.date: 03/11/2024
+ms.date: 04/14/2024
 
 ---
 
 # How to build a RAG solution using Azure AI Search
 
-This tutorial series demonstrates a pattern for building RAG solutions on Azure AI Search. It covers the components built in Azure AI Search, dependencies, and optimizations for maximizing relevance and minimizing costs.
+This tutorial series demonstrates a pattern for building RAG solutions on Azure AI Search. It explains the components that you need to build, enumerates the dependencies, and provides optimizations for maximizing relevance and minimizing costs.
 
 Sample data is a [collection of PDFs](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/nasa-e-book/earth_book_2019_text_pages) uploaded to Azure Storage. The content is from [NASA's Earth free e-book](https://www.nasa.gov/ebooks/earth/).
 
