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Merge pull request #5270 from HeidiSteen/heidist-freshness
[azure search] Freshness pass, part 1
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articles/search/cognitive-search-concept-annotations-syntax.md

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articles/search/query-lucene-syntax.md

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articles/search/query-odata-filter-orderby-syntax.md

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articles/search/query-simple-syntax.md

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articles/search/speller-how-to-add.md

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# Add spell check to queries in Azure AI Search
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| Client library | Versions |
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|----------|----------|
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| REST API | Versions 2020-06-30-Preview and later. We recommend the latest preview API. [2024-05-01-preview](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2024-05-01-preview&preserve-view=true)|
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| Azure SDK for .NET | [version 11.5.0-beta.5](https://www.nuget.org/packages/Azure.Search.Documents/11.5.0-beta.5) |
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| Azure SDK for Java | [version 11.6.0-beta.5](https://central.sonatype.com/artifact/com.azure/azure-search-documents) |
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| REST API | Versions 2020-06-30-Preview and later. We recommend the latest preview API. [2025-05-01-preview](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2025-05-01-preview&preserve-view=true)|
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| Azure SDK for .NET | [version 11.7.0-beta.4](https://www.nuget.org/packages/Azure.Search.Documents/11.7.0-beta.4) |
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| Azure SDK for Java | [version 11.8.0-beta.7](https://central.sonatype.com/artifact/com.azure/azure-search-documents/11.8.0-beta.7) |
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| Azure SDK for JavaScript | [version 11.3.0-beta.8](https://www.npmjs.com/package/@azure/search-documents/v/11.3.0-beta.8) |
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| Azure SDK for Python | [version 11.4.0b3](https://pypi.org/project/azure-search-documents/11.4.0b3/) |
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| Azure SDK for Python | [version 11.6.0b12](https://pypi.org/project/azure-search-documents/11.6.0b12/) |
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## Spell correction with simple search
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The following example uses the built-in hotels-sample index to demonstrate spell correction on a simple text query. Without spell correction, the query returns zero results. With correction, the query returns one result for Johnson's family-oriented resort.
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```http
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POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2024-05-01-preview
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POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-05-01-preview
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{
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"search": "famly acitvites",
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"speller": "lexicon",
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This example uses fielded search over the Category field, with full Lucene syntax, and a misspelled query term. By including speller, the typo in "Suiite" is corrected and the query succeeds.
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```http
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POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2024-05-01-preview
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POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-05-01-preview
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"search": "Category:(Resort and Spa) OR Category:Suiite",
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This query, with typos in every term except one, undergoes spelling corrections to return relevant results. To learn more, see [Configure semantic ranker](semantic-how-to-query-request.md).
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```http
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POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2024-05-01-preview   
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POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-05-01-preview   
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"search": "hisotoric hotell wiht great restrant nad wiifi",
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## Supported languages
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Valid values for `queryLanguage` can be found in the following table, copied from the list of [supported languages (REST API reference)](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2024-05-01-preview&tabs=HTTP#querylanguage&preserve-view=true).
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Valid values for `queryLanguage` can be found in the following table, copied from the list of [supported languages (REST API reference)](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2025-05-01-preview&tabs=HTTP#querylanguage&preserve-view=true).
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| Language | queryLanguage |
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articles/search/troubleshoot-shared-private-link-resources.md

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# Troubleshoot issues with Shared Private Links in Azure AI Search

articles/search/tutorial-rag-build-solution-index-schema.md

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articles/search/tutorial-rag-build-solution-models.md

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# Tutorial: Choose embedding and chat models for RAG in Azure AI Search
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A RAG solution built on Azure AI Search takes a dependency on embedding models for vectorization, and on chat models for conversational search over your data.
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A RAG solution built on Azure AI Search takes a dependency on embedding models for vectorization, and on chat completion models for conversational search over your data.
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In this tutorial, you:
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> [!div class="checklist"]
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> - Learn which models in the Azure cloud work with built-in integration
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> - Learn about the Azure models used for chat
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> - Learn about the Azure models supported for built-in vectorization
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> - Learn about the Azure models supported for chat completion
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- [Azure AI Vision regions](/azure/ai-services/computer-vision/overview-image-analysis?tabs=4-0#region-availability)
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- [Azure AI Foundry](/azure/ai-foundry/reference/region-support) regions.
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- [Azure AI Foundry regions](/azure/ai-foundry/reference/region-support)
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- [Azure AI Search regions](search-region-support.md)
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## Review models supporting built-in vectorization
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articles/search/tutorial-rag-build-solution.md

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articles/search/vector-search-ranking.md

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# Relevance in vector search
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Vector search algorithms include exhaustive k-nearest neighbors (KNN) and Hierarchical Navigable Small World (HNSW).
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+ Exhaustive KNN performs a brute-force search that scans the entire vector space.
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+ Exhaustive KNN performs a brute-force scan of the entire vector space.
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+ HNSW performs an [approximate nearest neighbor (ANN)](vector-search-overview.md#approximate-nearest-neighbors) search.
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