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articles/ai-services/openai/quotas-limits.md

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---
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## gpt-4o audio
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The rate limits for each `gpt-4o-realtime-preview` model deployment are 100K TPM and 1K RPM. During the preview, Azure AI Foundry portal and APIs might inaccurately show different rate limits. Even if you try to set a different rate limit, the actual rate limit will be 100K TPM and 1K RPM.
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| Model|Tier| Quota Limit in tokens per minute (TPM) | Requests per minute |
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|---|---|:---:|:---:|
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|`gpt-4o-realtime-preview` | Default | 100 K | 1 K |

articles/ai-services/openai/whats-new.md

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recommendations: false
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---
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- Added support for [prompt caching](./how-to/prompt-caching.md) with the `gpt-4o-realtime-preview` model.
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- Added support for new voices. The `gpt-4o-realtime-preview` models now support the following voices: "alloy", "ash", "ballad", "coral", "echo", "sage", "shimmer", "verse".
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- Rate limits are no longer based on connections per minute. Rate limiting is now based on RPM (requests per minute) and TPM (tokens per minute) for the `gpt-4o-realtime-preview` model. The rate limits for the `gpt-4o-realtime-preview` model are 100K TPM and 1K RPM.
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- Rate limits are no longer based on connections per minute. Rate limiting is now based on RPM (requests per minute) and TPM (tokens per minute) for the `gpt-4o-realtime-preview` model. The rate limits for each `gpt-4o-realtime-preview` model deployment are 100K TPM and 1K RPM. During the preview, Azure AI Foundry portal and APIs might inaccurately show different rate limits. Even if you try to set a different rate limit, the actual rate limit will be 100K TPM and 1K RPM.
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For more information, see the [GPT-4o real-time audio quickstart](realtime-audio-quickstart.md) and the [how-to guide](./how-to/realtime-audio.md).
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articles/search/hybrid-search-how-to-query.md

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+ [vector.queries.weight](vector-search-how-to-query.md#vector-weighting) lets you set the relative weight of the vector query. This feature is particularly useful in complex queries where two or more distinct result sets need to be combined, as is the case for hybrid search. This feature is generally available.
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+ [hybridsearch.maxTextRecallSize and countAndFacetMode (preview)](#set-maxtextrecallsize-and-countandfacetmode-preview) give you more control over text inputs into a hybrid query. This feature requires a preview API version.
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+ [hybridsearch.maxTextRecallSize and countAndFacetMode (preview)](#set-maxtextrecallsize-and-countandfacetmode) give you more control over text inputs into a hybrid query. This feature requires a preview API version.
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## Prerequisites
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+ Search Explorer in the Azure portal (supports both stable and preview API search syntax) has a JSON view that lets you paste in a hybrid request.
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+ [**2024-07-01**](/rest/api/searchservice/documents/search-post) stable version or a recent preview API version if you're using preview features like [maxTextRecallSize and countAndFacetMode(preview)](#set-maxtextrecallsize-and-countandfacetmode-preview).
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+ [**2024-07-01**](/rest/api/searchservice/documents/search-post) stable version or a recent preview API version if you're using preview features like [maxTextRecallSize and countAndFacetMode(preview)](#set-maxtextrecallsize-and-countandfacetmode).
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For readability, we use REST examples to explain how the APIs work. You can use a REST client like Visual Studio Code with the REST extension to build hybrid queries. For more information, see [Quickstart: Vector search using REST APIs](search-get-started-vector.md).
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+ Postfilter is applied after query execution. If k=50 returns 50 matches on the vector query side, followed by a post-filter applied to the 50 matches, your results are reduced by the number of documents that meet filter criteria. This leaves you with fewer than 50 documents to pass to semantic ranker. Keep this in mind if you're using semantic ranking. The semantic ranker works best if it has 50 documents as input.
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## Set maxTextRecallSize and countAndFacetMode (preview)
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## Set maxTextRecallSize and countAndFacetMode
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[!INCLUDE [Feature preview](./includes/previews/preview-generic.md)]
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This section explains how to adjust the inputs to a hybrid query by controlling the amount BM25-ranked results that flow to the hybrid ranking model. Controlling over the BM25-ranked input gives you more options for relevance tuning in hybrid scenarios.
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Both "k" and "top" are optional. Unspecified, the default number of results in a response is 50. You can set "top" and "skip" to [page through more results](search-pagination-page-layout.md#paging-results) or change the default.
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> [!NOTE]
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> If you're using hybrid search in 2024-05-01-preview API, you can control the number of results from the keyword query using [maxTextRecallSize](#set-maxtextrecallsize-and-countandfacetmode-preview). Combine this with a setting for "k" to control the representation from each search subsystem (keyword and vector).
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> If you're using hybrid search in 2024-05-01-preview API, you can control the number of results from the keyword query using [maxTextRecallSize](#set-maxtextrecallsize-and-countandfacetmode). Combine this with a setting for "k" to control the representation from each search subsystem (keyword and vector).
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#### Semantic ranker results
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articles/search/hybrid-search-ranking.md

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By default, if you aren't using pagination, the search engine returns the top 50 highest ranking matches for full text search, and the most similar `k` matches for vector search. In a hybrid query, `top` determines the number of results in the response. Based on defaults, the top 50 highest ranked matches of the unified result set are returned.
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Often, the search engine finds more results than `top` and `k`. To return more results, use the paging parameters `top`, `skip`, and `next`. Paging is how you determine the number of results on each logical page and navigate through the full payload. You can set `maxTextRecallSize` to larger values (the default is 1,000) to return more results from the text side of hybrid query.
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Often, the search engine finds more results than `top` and `k`. To return more results, use the paging parameters `top`, `skip`, and `next`. Paging is how you determine the number of results on each logical page and navigate through the full payload. You can [set `maxTextRecallSize`](hybrid-search-how-to-query.md#set-maxtextrecallsize-and-countandfacetmode) to larger values (the default is 1,000) to return more results from the text side of hybrid query.
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By default, full text search is subject to a maximum limit of 1,000 matches (see [API response limits](search-limits-quotas-capacity.md#api-response-limits)). Once 1,000 matches are found, the search engine no longer looks for more.
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articles/search/index-similarity-and-scoring.md

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# Relevance in keyword search (BM25 scoring)
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As long as the same `sessionId` is used, a best-effort attempt is made to target the same replica, increasing the consistency of results your users will see.
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> [!NOTE]
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> Reusing the same `sessionId` values repeatedly can interfere with the load balancing of the requests across replicas and adversely affect the performance of the search service. The value used as sessionId cannot start with a '_' character.
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> Reusing the same `sessionId` values repeatedly can interfere with the load balancing of the requests across replicas and adversely affect the performance of the search service. The value used as sessionId can't start with a '_' character.
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By default, if you aren't using pagination, the search engine returns the top 50 highest ranking matches for full text search. You can use the `top` parameter to return a smaller or larger number of items (up to 1,000 in a single response). You can use `skip` and `next` to page results. Paging determines the number of results on each logical page and supports content navigation. For more information, see [Shape search results](search-pagination-page-layout.md).
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If your full text query is part of a [hybrid query](hybrid-search-how-to-query.md), you can [set `maxTextRecallSize`](hybrid-search-how-to-query.md#set-maxtextrecallsize-and-countandfacetmode) to increase or decrease the number of results from the text side of the query.
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Full text search is subject to a maximum limit of 1,000 matches (see [API response limits](search-limits-quotas-capacity.md#api-response-limits)). Once 1,000 matches are found, the search engine no longer looks for more.
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## See also

articles/search/search-api-preview.md

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| [**Normalizers**](search-normalizers.md) | Query | Normalizers provide simple text preprocessing: consistent casing, accent removal, and ASCII folding, without invoking the full text analysis chain.| [Search Documents (preview)](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2024-05-01-preview&preserve-view=true). |
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| [**featuresMode parameter**](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2024-05-01-preview&preserve-view=true) | Relevance (scoring) | BM25 relevance score expansion to include details: per field similarity score, per field term frequency, and per field number of unique tokens matched. You can consume these data points in [custom scoring solutions](https://github.com/Azure-Samples/search-ranking-tutorial). | [Search Documents (preview)](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2024-05-01-preview&preserve-view=true).|
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| [**vectorQueries.threshold parameter**](vector-search-how-to-query.md#vector-weighting) | Relevance (scoring) | Exclude low-scoring search result based on a minimum score. | [Search Documents (preview)](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2024-05-01-preview&preserve-view=true). |
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| [**hybridSearch.maxTextRecallSize and countAndFacetMode parameters**](hybrid-search-how-to-query.md#set-maxtextrecallsize-and-countandfacetmode-preview) | Relevance (scoring) | adjust the inputs to a hybrid query by controlling the amount BM25-ranked results that flow to the hybrid ranking model. | [Search Documents (preview)](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2024-05-01-preview&preserve-view=true). |
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| [**hybridSearch.maxTextRecallSize and countAndFacetMode parameters**](hybrid-search-how-to-query.md#set-maxtextrecallsize-and-countandfacetmode) | Relevance (scoring) | adjust the inputs to a hybrid query by controlling the amount BM25-ranked results that flow to the hybrid ranking model. | [Search Documents (preview)](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2024-05-01-preview&preserve-view=true). |
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| [**moreLikeThis**](search-more-like-this.md) | Query | Finds documents that are relevant to a specific document. This feature has been in earlier previews. | [Search Documents (preview)](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2024-05-01-preview&preserve-view=true). |
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## Control plane preview features

articles/search/search-pagination-page-layout.md

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The top matches are determined by search score, assuming the query is full text search or semantic. Otherwise, the top matches are an arbitrary order for exact match queries (where uniform `@search.score=1.0` indicates arbitrary ranking).
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Set `top` to override the default of 50. In newer preview APIs, if you're using a hybrid query, you can [specify maxTextRecallSize](hybrid-search-how-to-query.md#set-maxtextrecallsize-and-countandfacetmode-preview) to return up to 10,000 documents.
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Set `top` to override the default of 50. In newer preview APIs, if you're using a hybrid query, you can [specify maxTextRecallSize](hybrid-search-how-to-query.md#set-maxtextrecallsize-and-countandfacetmode) to return up to 10,000 documents.
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To control the paging of all documents returned in a result set, use `top` and `skip` together. This query returns the first set of 15 matching documents plus a count of total matches.
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articles/search/tutorial-csharp-create-load-index.md

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articles/search/tutorial-csharp-deploy-static-web-app.md

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articles/search/tutorial-csharp-overview.md

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- [.NET 9](https://dotnet.microsoft.com/download/dotnet) or latest version
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- [Git](https://git-scm.com/downloads)
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- [Visual Studio Code](https://code.visualstudio.com/)
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- [C# Dev Tools extension for Visual Studio Code](https://marketplace.visualstudio.com/items?itemName=ms-dotnettools.csdevkit)

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